Water encyclopedia. Oceanography, meteorology, physics and chemistry 0471736848, 9786468600, 3175723993, 0471441643, 1181201241, 1441491511, 5986046056

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WATER ENCYCLOPEDIA

OCEANOGRAPHY; METEOROLOGY; PHYSICS AND CHEMISTRY; WATER LAW; AND WATER HISTORY, ART, AND CULTURE

WATER ENCYCLOPEDIA Editor-in-Chief Jay Lehr, Ph.D. Senior Editor Jack Keeley Associate Editor Janet Lehr Information Technology Director Thomas B. Kingery III

Editorial Staff Vice President, STM Books: Janet Bailey Editorial Director, STM Encyclopedias: Sean Pidgeon Executive Editor: Bob Esposito Director, Book Production and Manufacturing: Camille P. Carter Production Manager: Shirley Thomas Senior Production Editor: Kellsee Chu Illustration Manager: Dean Gonzalez Editorial Program Coordinator: Jonathan Rose

WATER ENCYCLOPEDIA

OCEANOGRAPHY; METEOROLOGY; PHYSICS AND CHEMISTRY; WATER LAW; AND WATER HISTORY, ART, AND CULTURE Jay Lehr, Ph.D. Editor-in-Chief Jack Keeley Senior Editor Janet Lehr Associate Editor Thomas B. Kingery III Information Technology Director

The Water Encyclopedia is available online at http://www.mrw.interscience.wiley.com/eow/

A John Wiley & Sons, Inc., Publication

Copyright  2005 by John Wiley & Sons, Inc. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400, fax 978-646-8600, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services please contact our Customer Care Department within the U.S. at 877-762-2974, outside the U.S. at 317-572-3993 or fax 317-572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print, however, may not be available in electronic format. Library of Congress Cataloging-in-Publication Data is available. Lehr, Jay Water Encyclopedia: Oceanography; Meteorology; Physics and Chemistry; Water Law; and Water History, Art, and Culture ISBN 0-471-73684-8 ISBN 0-471-44164-3 (Set) Printed in the United States of America 10 9 8 7 6 5 4 3 2 1

CONTENTS Preface Contributors

ix xi

The Permanent Service for Mean Sea Level Marine and Estuarine Microalgal Sediment Toxicity Tests Marine Stock Enhancement Techniques Physical and Chemical Variability of Tidal Streams Black Water Turns the Tide on Florida Coral Shallow Water Waves Water Waves Woods Hole: The Early Years An Analysis of the International Maritime Organization–London Convention Annual Ocean Dumping Reports Marine Sources of Halocarbons Food Chain/Foodweb/Food Cycle Plankton Major Ions in Seawater Tsunami

Oceanography Air–Sea Interaction NOAA’s Atlantic Oceanographic and Meteorological Laboratory Laboratory Experiments On Bivalve Excretion Rates of Nutrients Temporal Scaling of Benthic Nutrient Regeneration in Bivalve-Dominated Tidal Flat Breakwaters The Ocean in Climate Coastal Waters Marine Colloids Deep Water Corals Marine Debris Abatement Larvae and Small Species of Polychaetes in Marine Toxicological Testing ˜ The Interannual Prediction Problem El Nino: Renewable Energies from the Ocean Estuarian Waters NOS/NMFS Cooperative Research on Coastal Fisheries and Habitats at the Beaufort Laboratory Distribution and Dynamics of Gas Hydrates in the Marine Environment Oceanographic Environment of Glacier Bay NOS Sanctuaries Protect Nation’s Maritime History Quantification of Anoxia and Hypoxia in Water Bodies Floating Ice Technology Development: Hardware Development—Marine Instrumentation Laboratory (MIL) Seasonal Coupling Between Intertidal Macrofauna and Sediment Column Porewater Nutrient Concentrations Mapping the Sea Floor of the Historic Area Remediation Site (HARS) Offshore of New York City NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific Tidally Mediated Changes in Nutrient Concentrations The Role of Oceans in the Global Cycles of Climatically-Active Trace-Gases Pacific Marine Environmental Laboratory—30 Years of Observing The Ocean Seawater Temperature Estimates in Paleoceanography Physical Oceanography Coastal Water Pollutants Trace Element Pollution Coral Reefs and Your Coastal Watershed Sea Level and Climate

1 4 6 11 14 21 23 27 32 38 42 43 44 49

118 120 124 128 133 135 138 139

144 149 151 154 159 160

Meteorology Ballooning and Meteorology in the Twentieth Century Barometric Efficiency CERES: Understanding The Earth’s Clouds and Climate Chinook Global Climate Change Observations of Climate and Global Change from Real-Time Measurements Overview: The Climate System Climate and Society What is Climatology? Cloud Seeding Condensation Cosmic Water The Water Cycle Cyclones Water Cycle Degree Day Method Desertification Dew Dew Deserts Dew Point Droughts Drought Indices The Earth Observing System: Aqua Entropy Theory For Hydrologic Modeling Evaporation Evapotranspiration Fog Coastal Fog Along the Northern Gulf of Mexico Rain Forests Frost Frost Damage The Global Water Cycle Ground-Based GPS Meteorology at FSL

55 57 61 62 64 69

70

73

77 80 81 85 89 92 95 96 109 113 117 v

164 166 169 170 171 172 179 183 186 187 188 189 191 194 196 197 199 200 201 207 208 209 214 217 223 226 229 230 239 240 241 242 244

vi

CONTENTS

Climate and Water Balance on the Island of Hawaii Heat of Vaporization Hydrologic History, Problems, and Perspectives Humidity—Absolute Relative Humidity Hurricanes: Modeling Nature’s Fury Hydrologic Cycle Hydrosphere Hydrologic Cycle, Water Resources, and Society Isohyetal Method What About Meteorology? Basic Research for Military Applications Uncertainties in Rainfall–Runoff Modeling Monsoon African Monsoons Permanent Frost Radar Use in Rainfall Measurements Rainfall Rainfall and Runoff Remote Sensing of Applications in Hydrology Atmospheric Scientists Rain Simulators Snow Density Flattop Mountain Snotel Snowpack: Water Year 2004 Snow and Snowmelt Snow Surveys A Statistical Approach to Critical Storm Period Analysis Sublimation Transpiration Waterspout United States Weather Bureau Weather Forecasting Through The Ages Overview of Weather Systems Unit Hydrograph Theory Weather and the Atmosphere Vapor Pressure Adiabatic Cooling Rain and Rocks: The Recipe for River Water Chemistry

255 263 265 269 270 274 275 283 287 290 292 295 297 304 304 305 306 309 315 319 328 330 333 334 336 337 338 343 345 347 347 348 352 355 360 362 366 371

Physics and Chemistry of Water Acid Rain and Society Adsorption Capacity of Activated Carbon for Water Purification Adsorption of Organic Compounds Age Dating Old Groundwater Ammonia Beryllium in Water Dissolved Organic Carbon Mechanisms of Water Adsorption on Carbons The Effect of Carbon Surface Chemical Composition on the Mechanism of Phenol Adsorption from Aqueous Solutions Carbonate Geochemistry Carbonate in Natural Waters Chlorine-36 and Very Old Groundwaters Chlorofluorocarbons (CFCs)

377 381 384 388 390 394 399 400

404 408 413 416 420

Coagulation and Flocculation Conductivity-Electric Conservation and the Water Cycle Defluroidation Deuterium Distilled Water Electricity as a Fluid Analysis of Aqueous Solutions Using Electrospray Ionization Mass Spectrometry (esi ms) Fenton’s Reaction and Groundwater Remediation Where Water Floats Freshwater Dissolved Gases Hard Water An Analysis of The Impact of Water on Health and Aging: Is All Water The Same? Heavy Water Henry’s Law Hofmeister Effects Clathrate Hydrates Hydration The Mirage of The H2 Economy Hydrogen Ion The Hydronium Ion Infiltration and Soil Moisture Processes Ion Exchange and Inorganic Adsorption Iron Isotopes Isotope Fractionation Mariotte Bottle—Use in Hydrology Mars Exploration Rover Mission Removal of Organic Micropollutants and Metal Ions from Aqueous Solutions by Activated Carbons Molecular Network Dynamics In Situ Chemical Monitoring Nitrogen Osmosis-Diffusion of Solvent or Caused by Diffusion of Solutes? Partitioning and Bioavailability Physical Properties Environmental Photochemistry in Surface Waters Isotope Exchange in Gas-Water Reactions Radon in Water Silica in Natural Waters Sodium in Natural Waters Soft Water Solubility of Chemicals in Water Solubility of Hydrocarbons in Salt Water Solubility of Hydrocarbons and Sulfur Compounds in Water Sorption Kinetics Sound in Water Water on the Space Station Strontium Isotopes in Water and Rock Technetium in Water Water—Nature’s Magician

424 429 433 434 438 441 442

443 445 448 449 450 452 455 462 466 468 471 475 477 480 482 484 490 496 499 500 503 504

506 511 514 517 520 521 527 529 535 541 548 551 553 555 559 561 564 569 572 574 578 583

CONTENTS

Freezing and Supercooling of Water Chemical Precipitation Antimony in Aquatic Systems

585 586 589

Water Law and Economics The Clean Water Act Clean Water Act, Water Quality Criteria/Standards, TMDLs, and Weight-of-Evidence Approach for Regulating Water Quality The Constitution and Early Attempts at Rational Water Planning Economic Value of Water: Estimation Water Supply Planning—Federal Flood Control Act of 1944 Great Lakes Governors’ Agreement U.S./Canadian Boundary Waters Treaty and the Great Lakes Water Quality Agreement Great Lakes Water Quality Initiative Quantitative GroundWater Law Islamic Water Law Transboundary Waters in Latin America: Conflicts and Collaboration United States-Mexico Border Waters: Conventions, Treaties, and Institutions Negotiating between Authority and Polluters: An Approach to Managing Water Quality Water Resource Organizations A Brief History of the Water Pollution Control Act in the U.S. The National Pollution Discharge Elimination System Legal Protection for In-stream Flow Water Quality Interface between Federal Water Quality Regulation and State Allocation of Water Quantity Regulatory Issues and Remediation: Risk, Costs, and Benefits The Safe Drinking Water Act Representing Geopolitics of (Hydro) Borders in South Asia Water Transfers Reserved Water Rights for Indian and Federal Lands Wetlands Policy in the United States: From Drainage to Restoration

595

598 604 605 612 616 617 620 621 627 634 636 643 647 648 651 655 659 664

671 674 676 680 685 689 690

Water History, Art, and Culture Curious Uses of Agricultural Water in the World

695

Water Between Arabs and Israelis: Researching Twice-Promised Resources The Myth of Bad Cholesterol: Why Water Is A Better Cholesterol-Lowering Medication Early Clocks Water Clocks Our Evolving Water Consciousness Effective Water Education Strategies in a Nontraditional Setting Evolution History of Pond Fisheries in Poland Water: The Key to Natural Health And Healing Water in History Hoover Dam History Hydropsychology Jacob’s Well Jaubert de Passa: The First World History of Irrigation in 1846 Benjamin Franklin: From Kite to Lightning Rod Water and the History of Man Water, Bacteria, Life on Mars, and Microbial Diversity Canals in the Mekong Delta: A Historical Overview from 200 C.E. to the Present Conflict and Water Use in the Middle East Benjamin Franklin’s Armonica: A Water Music Instrument Water Transportation Occupations A Concise Glimpse of Water in the History of Photography Water as a Human Right Ancient Water and Soil Conservation Ecosystems of Sri Lanka Ben Franklin’s Gulf Stream Weather and Swim Fins Water Symbolism Gordon and Franklin Rivers and the Tasmanian Wilderness World Heritage Area The Mistake of Waiting to Get Thirsty Water and Well-Being Free Flowing Water: A Source of Wisdom The Medicinal Properties of the Waters of Saratoga Springs A History of Hawaiian Freshwater Resources

vii

699 701 702 704 707 713 715 718 722 726 732 733 735 736 741 745 746 748 753 758 762 766 769 772 780 785 788 789 791 793 797 801

Volume Index missing Cumulative Index (from Volume 5)

following p. 807

PREFACE No natural molecule on the planet is more fascinating than water. It has unique properties ranging from the unusual angles formed between its two hydrogen ions and its single oxygen molecule, to the fact that unlike most substances, it expands when it freezes rather than shrinks and reaches a maximum density as a liquid 4◦ F above its freezing point. These and many other aspects of the special physics and chemistry are described in this volume, including the impact of a wide variety of chemicals occurring in water, osmosis, diffusion, hydration, isotope exchange, along with the fun physics of the mariotte bottle. Equally fascinating are the many unusual physical and chemical encounters in both the ocean and the atmosphere. Although oceanography and meteorology are frequently considered separate sciences from hydrology, their limited inclusion in the Water Encyclopedia was deemed necessary to tell the complete story. Tidal changes, benthic nutrients, the sea floor, el nino, sea level, and ocean/climate relationships make up but a few of the oceans fascinating stories, whereas water spouts, hurricanes, monsoons, droughts, sublimation, and barometric efficiency just touch the tip of what this volume has in store in the area of meteorology.

But water has a wonderful human face as well. We have reached around the world to describe the history of water and its role in the development of civilizations and the many beliefs held about it. As society developed, the distribution of water needed supervision, which lead to a wide variety of water laws we have attempted to categorize and describe in an interesting and meaningful way. We are equally proud of our open-minded effort to describe the role that water has played in art and culture. We have attempted not be judgmental, with stories of water forms and water intelligence along with some medical theories and, of course, the wonderful descriptions of early water clocks. This volume is a true intellectual cornucopia of water in the life of humankind on a personal level. We are confident that in the coming years and editions of the Water Encyclopedia, this volume will expand with more participation from individuals working in unusual fields relating to water. Jay Lehr Jack Keeley

ix

CONTRIBUTORS Eli Dahi, Environmental Development Corporation, Søborg, Denmark, Defluroidation Carl W. David, University of Connecticut, Storrs, Connecticut, The Hydronium Ion Jana Davis, Smithsonian Environmental Research Center, Edgewater, Maryland, Marine Stock Enhancement Techniques Christine Dickenson, Florida Institute of Technology, Melbourne, Florida, An Analysis of the International Maritime Organization–London Convention Annual Ocean Dumping Reports Robert E. Dickinson, (from The Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, Wiley 2003), Overview: The Climate System Priyanka K. Dissanayake, Moratuwa, Sri Lanka, Estuarian Waters Iver W. Duedall, Florida Institute of Technology, Melbourne, Florida, An Analysis of the International Maritime Organization–London Convention Annual Ocean Dumping Reports Sandra Dunbar, Napier University, Edinburgh, Scotland, United Kingdom, Partitioning and Bioavailability ´ Anton´ın Dvoˇrak, University of Economics, Prague, Czech Republic, Negotiating between Authority and Polluters: An Approach to Managing Water Quality David R. Easterling, (from Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, Wiley 2003), Observations of Climate and Global Change from Real-Time Measurements Theodore A. Endreny, SUNY-ESF, Syracuse, New York, Remote Sensing of Applications in Hydrology, Evaporation, Radar Use in Rainfall Measurements, Rainfall and Runoff Environment Canada, Water—Nature’s Magician Timothy Erickson, National Weather Service New Orleans/Baton Rouge Forecast Office, Slidell, Louisiana, Coastal Fog Along the Northern Gulf of Mexico Kirsten Exall, National Water Research Institute, Burlington, Ontario, Canada, Coagulation and Flocculation David L. Feldman, University of Tennessee, Knoxville, Tennessee, Water Supply Planning—Federal, Water Transfers Montserrat Filella, University of Geneva, Geneva, Switzerland, Antimony in Aquatic Systems Sylwester Furmaniak, N. Copernicus University, Torun, ´ Poland, Mechanisms of Water Adsorption on Carbons Piotr A. Gauden, N. Copernicus University, Torun, ´ Poland, The Effect of Carbon Surface Chemical Composition on the Mechanism of Phenol Adsorption from Aqueous Solutions, Mechanisms of Water Adsorption on Carbons ˜ Geophysical Fluid Dynamics Laboratory—NOAA, El Nino: The Interannual Prediction Problem, Hurricanes: Modeling Nature’s Fury, Global Climate Change Andrea K. Gerlak, Columbia University, New York, New York, Wetlands Policy in the United States: From Drainage to Restoration Michael H. Glantz, (from The Handbook of Weather, Climate, and Water: Atmospheric Chemistry, Hydrology, and Societal Impacts, Wiley 2003), Climate and Society Global Change Research Program—U.S. Geological Survey, Flattop Mountain Snotel Snowpack: Water Year 2004 Jyotsna Goel, Centre for Fire, Explosives, and Environmental Safety, Timarpur, India, Ion Exchange and Inorganic Adsorption Kelly Goodwin, University of Miami, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific David M. Gray, Mettler-Toledo Thornton Inc., Bedford, Massachusetts, Conductivity-Electric Great Lakes Environmental Research Laboratory (NOAA), Technology Development: Hardware Development—Marine Instrumentation Laboratory (MIL) Seth I. Gutman, NOAA Forecast Systems Laboratory, Ground-Based GPS Meteorology at FSL Janusz Guziur, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland, History of Pond Fisheries in Poland David Haley, Picacadilly, Ulverston, Cumbria, United Kingdom, Water and Well-Being, Evolution

M. Abad, Universidad de Huelva. Avda. de las Fuerzas Armadas, Huelva, A Statistical Approach to Critical Storm Period Analysis Edinara Adelaide Boss, Artur-Nogueira-SP, Brazil, Sublimation Joseph H. Aldstadt, III, Genetic Technologies, Inc. Testing Institute, Waukesha, Wisconsin, In Situ Chemical Monitoring Alaska Biological Science Center—U.S. Geological Survey, Oceanographic Environment of Glacier Bay Sergio Alonso, University of the Balearic, Palma de Mallorca, Spain, Relative Humidity Marie de Angelis, Humboldt State University, Arcata, California, Major Ions in Seawater Carolyn Ann Koh, Colorado School of Mines, Golden, Colorado, Clathrate Hydrates, Hydration Yoseph Negusse Araya, Open University, Milton Keynes, United Kingdom, Hydrosphere Ann Azadpour-Keeley, National Risk Management Research Laboratory, ORD, U.S.EPA, Ada, Oklahoma, Water and the History of Man W.D. Bach, Jr., (from The Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, Wiley 2003), Basic Research for Military Applications Patrick L. Barry, NASA, Water on the Space Station F. Batmanghelidj, Global Health Solutions, Falls Church, Virginia, The Myth of Bad Cholesterol: Why Water Is A Better Cholesterol-Lowering Medication, Water: The Key to Natural Health And Healing, The Mistake of Waiting to Get Thirsty M. Eric Benbow, Michigan State University, East Lansing, Michigan, A History of Hawaiian Freshwater Resources Mike Bettwy, Goddard Space Flight Center, NASA, African Monsoons David Biggs, University of Washington, Seattle, Washington, Canals in the Mekong Delta: A Historical Overview from 200 C.E. to the Present Jessica Black, NOAA/CREST CCNY, New York, New York, Remote Sensing of Applications in Hydrology Peter E. Black, SUNY ESF, Syracuse, New York, Water Resource Organizations ´ Blasco, Institute of Marine Sciences of Analucia, Cadiz, Spain, Julian Marine and Estuarine Microalgal Sediment Toxicity Tests ¨ M. Bostrom, Link¨oping University, Link¨oping, Sweden, Hofmeister Effects, Dissolved Gases Kristofor R. Brye, University of Arkansas, Fayetteville, Arkansas, Nitrogen Bureau of Labor Statistics, U.S. Department of Labor, Water Transportation Occupations Bureau of Reclamation—U.S. Department of the Interior, Hoover Dam History Robert M. Burgess, U.S. Environmental Protection Agency, Narragansett, Rhode Island, Ammonia Albert J. Burky, University of Dayton, Dayton, Ohio, A History of Hawaiian Freshwater Resources James Butler, Climate Monitoring and Diagnostics Laboratory, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific Bradford Butman, U.S. Geological Survey, Mapping the Sea Floor of the Historic Area Remediation Site (HARS) Offshore of New York City Pietro Chiavaccini, Universita´ di Pisa, Pisa, Italy, Shallow Water Waves, Breakwaters G.G. Clarke, University of Hawaii, Hilo, Hawaii, Climate and Water Balance on the Island of Hawaii Jay Clausen, AMEC Earth and Environmental, Inc., Westford, Massachusetts, Technetium in Water, Beryllium in Water Aldo Conti, Frascati (RM), Italy, Floating Ice, Condensation, Desertification, Dew, Distilled Water, Isotopes, Rain Forests, Dew Point Giuseppe Cortese, Alfred Wegener Institute for Polar and Marine Research (AWI), Bremerhaven, Germany, Seawater Temperature Estimates in Paleoceanography Sara Cotton, University of Miami, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific ´ L.M. Caceres, Universidad de Huelva. Avda. de las Fuerzas Armadas, Huelva, A Statistical Approach to Critical Storm Period Analysis

xi

xii

CONTRIBUTORS

Jon Hare, NOAA Center for Coastal Fisheries and Habitat Research, NOS/NMFS Cooperative Research on Coastal Fisheries and Habitats at the Beaufort Laboratory Michael J. Hayes, Climate Impacts Specialist—National Drought Mitigation Center, Drought Indices William Henderson, University of Waikato, Hamilton, New Zealand, Analysis of Aqueous Solutions Using Electrospray Ionization Mass Spectrometry (esi ms) Warwick Hillier, The Australian National University, Canberra, Australia, Isotope Exchange in Gas-Water Reactions Joseph Holden, University of Leeds, Leeds, United Kingdom, Mariotte Bottle—Use in Hydrology, Rain Simulators S. Holgate, Proudman Oceanographic Laboratory, Birkenhead, United Kingdom, The Permanent Service for Mean Sea Level Arthur M. Holst, Philadelphia Water Department, Philadelphia, Pennsylvania, Frost Damage, Droughts, Water Cycle, Monsoon, Permanent Frost, United States Weather Bureau, Waterspout, Cloud Seeding, Cyclones, Fog, Frost, Chinook, Flood Control Act of 1944, Jacob’s Well, Gordon and Franklin Rivers and the Tasmanian Wilderness World Heritage Area Kirk L. Holub, NOAA Forecast Systems Laboratory, Ground-Based GPS Meteorology at FSL Paul R. Houser, (from The Handbook of Weather, Climate, and Water: Atmospheric Chemistry, Hydrology, and Societal Impacts, Wiley 2003), Infiltration and Soil Moisture Processes S.A. Hsu, Louisiana State University, Baton Rouge, Louisiana, Air–Sea Interaction Jason A. Hubbart, University of Idaho, Moscow, Idaho, Hydrologic Cycle, Water Resources, and Society, Hydrologic History, Problems, and Perspectives Basia Irland, University of New Mexico, Albuquerque, New Mexico, A Concise Glimpse of Water in the History of Photography Mohammed Riajul Islam, University of Idaho, Moscow, Idaho, Rain and Rocks: The Recipe for River Water Chemistry James A. Jacobs, Environmental Bio-Systems, Inc., Mill Valley, California, Fenton’s Reaction and Groundwater Remediation, Regulatory Issues and Remediation: Risk, Costs, and Benefits, Water, Bacteria, Life on Mars, and Microbial Diversity Sharad K. Jain, National Institute of Hydrology, Roorkee, India, Isohyetal Method, Hydrologic Cycle Purnima Jalihal, National Institute of Ocean Technology, Chennai, India, Renewable Energies from the Ocean S. Jevrejeva, Proudman Oceanographic Laboratory, Birkenhead, United Kingdom, The Permanent Service for Mean Sea Level Alicia Jimenez, Michigan State University, East Lansing, Michigan, Transboundary Waters in Latin America: Conflicts and Collaboration Anne Jones-Lee, G. Fred Lee & Associates, El Macero, California, Clean Water Act, Water Quality Criteria/Standards, TMDLs, and Weight-ofEvidence Approach for Regulating Water Quality Andrew Juhl, Lamont–Doherty Earth Observatory of Columbia University, Palisades, New York, Food Chain/Foodweb/Food Cycle James O. Juvik, University of Hawaii, Hilo, Hawaii, Climate and Water Balance on the Island of Hawaii K. Kadirvelu, Centre for Fire, Explosives, and Environmental Safety, Timarpur, India, Ion Exchange and Inorganic Adsorption Th.D. Karapantsios, Aristotle University, Thessaloniki, Greece, Sorption Kinetics Thomas R. Karl, (from Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, Wiley 2003), Observations of Climate and Global Change from Real-Time Measurements Melinda R. Kassen, Trout Unlimited, Colorado Water Project, Boulder, Colorado, Legal Protection for In-stream Flow, Interface between Federal Water Quality Regulation and State Allocation of Water Quantity Gholam A. Kazemi, Shahrood University of Technology, Shahrood, Iran, Age Dating Old Groundwater, Chlorine-36 and Very Old Groundwaters, Deuterium, Freshwater, Hard Water, Heavy Water, Hydrogen Ion, Isotope Fractionation, Soft Water, Strontium Isotopes in Water and Rock, Chlorofluorocarbons (CFCs) Jack W. Keeley, Environmental Engineer, Ada, Oklahoma, Water and the History of Man Giora J. Kidron, The Hebrew University of Jerusalem, Jerusalem, Israel, Dew Deserts

Daniel King, University of Colorado, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific Piotr Kowalczyk, Faculty of Science, Chiba University, Chiba, Japan, The Effect of Carbon Surface Chemical Composition on the Mechanism of Phenol Adsorption from Aqueous Solutions, Mechanisms of Water Adsorption on Carbons Upadhyayula V. K. Kumar, Choa Chu kang Ave-4, Singapore, Coastal Water Pollutants W. Kunz, University of Regensburg, Regensburg, Germany, Hofmeister Effects Frederic Lasserre, Laval University, Quebec City, Quebec, Canada, Great Lakes Governors’ Agreement Marshall Lawson, Land Conservation Legal Services, LLC, Columbia, South Carolina, Quantitative GroundWater Law Jamie R. Lead, University of Birmingham, Birmingham, United Kingdom, Dissolved Organic Carbon G. Fred Lee, G. Fred Lee & Associates, El Macero, California, Clean Water Act, Water Quality Criteria/Standards, TMDLs, and Weight-of-Evidence Approach for Regulating Water Quality Maggie Lee, Santa Fe, New Mexico, Free Flowing Water: A Source of Wisdom Nai Kuang Liang, National Taiwan University, Taipei, Taiwan, Water Waves Sharon L. Lien, The Groundwater Foundation, Lincoln, Nebraska, Effective Water Education Strategies in a Nontraditional Setting Clive D. Lipchin, Ann Arbor, Michigan, Water Between Arabs and Israelis: Researching Twice-Promised Resources, Conflict and Water Use in the Middle East Eileen Loiseau, Bigelow Laboratory for Ocean Sciences, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific M.X. Loukidou, Aristotle University, Thessaloniki, Greece, Sorption Kinetics Helen H. Lou, Lamar University, Beaumont, Texas, Solubility of Hydrocarbons and Sulfur Compounds in Water, Solubility of Chemicals in Water Nancy A. Lowery, San Diego, California, United States-Mexico Border Waters: Conventions, Treaties, and Institutions ´ Institute of Marine Sciences of Analucia, Cadiz, Spain, Lu´ıs M. Lubian, Marine and Estuarine Microalgal Sediment Toxicity Tests Paolo Magni, IMC—International Marine Centre, Torregrande-Oristano, Italy, Laboratory Experiments On Bivalve Excretion Rates of Nutrients, Temporal Scaling of Benthic Nutrient Regeneration in BivalveDominated Tidal Flat, Physical and Chemical Variability of Tidal Streams, Tidally Mediated Changes in Nutrient Concentrations Babs A. Makinde-Odusola, Riverside, California, Radon in Water William E. Marks, Water Consciousness, Inc., Martha’s Vineyard, Massachusetts, Benjamin Franklin: From Kite to Lightning Rod, Benjamin Franklin’s Armonica: A Water Music Instrument, Our Evolving Water Consciousness, Water Clocks, Ben Franklin’s Gulf Stream Weather and Swim Fins D.L. Marrin, Hanalei, Hawaii, Cosmic Water, Molecular Network Dynamics, Sound in Water, Water Symbolism K.A. Matis, Aristotle University, Thessaloniki, Greece, Sorption Kinetics Patricia Matrai, Bigelow Laboratory for Ocean Sciences, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific Mollie D. McIntosh, Michigan State University, East Lansing, Michigan, A History of Hawaiian Freshwater Resources Kevin S. McLeary, Physical Properties Lucius O. Mendis, Colombo, Sri Lanka, Ancient Water and Soil Conservation Ecosystems of Sri Lanka Carlos D. Messina, University of Florida, Gainesville, Florida, Degree Day Method Paulette Middleton, (from The Handbook of Weather, Climate, and Water: Atmospheric Chemistry, Hydrology, and Societal Impacts, Wiley 2003), Acid Rain and Society Elsie F. Millano, ERM, Inc., Vernon Hills, Illinois, Great Lakes Water Quality Initiative A. Trent Millet, Newark, Vermont, The Medicinal Properties of the Waters of Saratoga Springs Koichi Miyashita, Okayama University, Kurashiki, Japan, Transpiration

CONTRIBUTORS Eric P. Mollard, Institut de Recherche pour le D´eveloppement, France, Curious Uses of Agricultural Water in the World, Jaubert de Passa: The First World History of Irrigation in 1846 Shigeru Montani, Hokkaido University, Hakodate, Japan, Physical and Chemical Variability of Tidal Streams, Laboratory Experiments On Bivalve Excretion Rates of Nutrients, Tidally Mediated Changes in Nutrient Concentrations, Temporal Scaling of Benthic Nutrient Regeneration in Bivalve-Dominated Tidal Flat, Seasonal Coupling Between Intertidal Macrofauna and Sediment Column Porewater Nutrient Concentrations Robert M. Moore, Dalhousie University, Halifax, Nova Scotia, Canada, Marine Sources of Halocarbons Ignatio Moreno-Garrido, Institute of Marine Sciences of Analucia, Cadiz, Spain, Marine and Estuarine Microalgal Sediment Toxicity Tests Suparna Mukherji, IIT Bombay, Powai, Mumbai, India, Adsorption of Organic Compounds ˜ J.M. Munoz, Universidad de Sevilla. Avda. Reina Mercedes, Sevilla, A Statistical Approach to Critical Storm Period Analysis Prasad K. Narasimhan, Lamar University, Beaumont, Texas, Adsorption Capacity of Activated Carbon for Water Purification, Solubility of Hydrocarbons and Sulfur Compounds in Water, Solubility of Chemicals in Water, Solubility of Hydrocarbons in Salt Water NASA—Goddard Space Flight Center, Black Water Turns the Tide on Florida Coral, The Water Cycle, Weather Forecasting Through The Ages, The Earth Observing System: Aqua NASA—Langley Research Center, CERES: Understanding The Earth’s Clouds and Climate NASA Marshall Space Flight Center, Where Water Floats National Drought Mitigation Center, What is Climatology? National Oceanographic and Atmospheric Administration (NOAA), NOAA’s Atlantic Oceanographic and Meteorological Laboratory Natural Resources Conservation Service, Conservation and the Water Cycle John W. Nielsen-Gammon, (from Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, Wiley 2003), Overview of Weather Systems Robert Y. Ning, King Lee Technologies, San Diego, California, Silica in Natural Waters, Carbonate in Natural Waters B.W. Ninham, University of Regensburg, Regensburg, Germany and Australian National University, Canberra, Australia, Hofmeister Effects, Dissolved Gases NOAA Coral Reef Information System (CORIS), Deep Water Corals NOAA National Ocean Service, NOS Sanctuaries Protect Nation’s Maritime History NOAA—Pacific Marine Environmental Laboratory, Pacific Marine Environmental Laboratory—30 Years of Observing The Ocean Northeast Fisheries Science Center—NOAA, Woods Hole: The Early Years ¨ Gertrud K. Nurnberg, Freshwater Research, Baysville, Ontario, Canada, Quantification of Anoxia and Hypoxia in Water Bodies Pacific Fisheries Environmental Laboratory, NOAA, Physical Oceanography Pacific Northwest National Laboratory—Shrub-Steppe Ecology Series, What About Meteorology? Stefano Pagliara, Universita´ di Pisa, Pisa, Italy, Shallow Water Waves, Breakwaters Magni Paolo, IMC-International Marine Centre, Torregrande-Oristano, Italy, Seasonal Coupling Between Intertidal Macrofauna and Sediment Column Porewater Nutrient Concentrations Jose O. Payero, University of Nebraska-Lincoln, North Platte, Nebraska, Evapotranspiration Mauricio Peredo, NASA Goddard Space Flight Center, Electricity as a Fluid Naraine Persaud, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, Adiabatic Cooling, Humidity—Absolute, Heat of Vaporization, Vapor Pressure Geoff Petts, University of Birmingham, Birmingham, United Kingdom, Water in History Tony Phillips, NASA, Water on the Space Station Jim Philp, Napier University, Edinburgh, Scotland, United Kingdom, Partitioning and Bioavailability

xiii

Laurel Phoenix, Green Bay, Wisconsin, Water as a Human Right Physics Laboratory, National Institute of Standards and Technology, Early Clocks Ralph W. Pike, Louisiana State University, Baton Rouge, Louisiana, Solubility of Hydrocarbons and Sulfur Compounds in Water, Solubility of Chemicals in Water R. Pino, Universidad de Sevilla. Avda. Reina Mercedes, Sevilla, A Statistical Approach to Critical Storm Period Analysis Richard Z. Poore, U.S. Geological Survey, Reston, Virginia, Sea Level and Climate Bobby J. Presley, Texas A&M University, College Station, Texas, Trace Element Pollution Nitish Priyadarshi, Ranchi University, Ranchi, Jharkhand, India, Sodium in Natural Waters Jian-Wen Qiu, Hong Kong Baptist University, Kowloon Tong, Kowloon, Hong Kong, Larvae and Small Species of Polychaetes in Marine Toxicological Testing Climent Ramis, University of the Balearic, Palma de Mallorca, Spain, Relative Humidity Jorge Ram´ırez-Vallejo, Harvard University, Cambridge, Massachusetts, Economic Value of Water: Estimation Todd Rasmussen, The University of Georgia, Athens, Georgia, Barometric Efficiency Howard Reminick, Ohno Institute on Water and Health, Willoughby, Ohio, An Analysis of The Impact of Water on Health and Aging: Is All Water The Same? Martin Reuss, Ph.D, Office of History Headquarters, U.S. Army Corps of Engineers, The Constitution and Early Attempts at Rational Water Planning J. Rodr´ıguez Vidal, Universidad de Huelva. Avda. de las Fuerzas Armadas, Huelva, A Statistical Approach to Critical Storm Period Analysis A. Rodr´ıguez-Ram´ırez, Universidad de Huelva. Avda. de las Fuerzas Armadas, Huelva, A Statistical Approach to Critical Storm Period Analysis Romualdo Romero, University of the Balearic, Palma de Mallorca, Spain, Relative Humidity William R. Roy, Illinois State Geological Survey, Champaign, Illinois, Iron F. Ruiz, Universidad de Huelva. Avda. de las Fuerzas Armadas, Huelva, A Statistical Approach to Critical Storm Period Analysis David L. Russell, Global Environmental Operations, Inc., Lilburn, Georgia, A Brief History of the Water Pollution Control Act in the U.S. Timothy J. Ryan, Ohio University, Athens, Ohio, The Clean Water Act Gerhard Rychlicki, N. Copernicus University, Torun, ´ Poland, The Effect of Carbon Surface Chemical Composition on the Mechanism of Phenol Adsorption from Aqueous Solutions, Mechanisms of Water Adsorption on Carbons S. Sabri, University of Malaya, Petaling Jaya Selangor, Malaysia, Islamic Water Law Basu Saha, Loughborough University, Loughborough, United Kingdom, Removal of Organic Micropollutants and Metal Ions from Aqueous Solutions by Activated Carbons Eric Saltzman, University of Miami, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific Peter H. Santschi, Texas A&M University, Galveston, Texas, Marine Colloids Edward S. Sarachik, (from The Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, Wiley 2003), The Ocean in Climate Eva Saroch, Panjab University, Chandigarh, India, Representing Geopolitics of (Hydro) Borders in South Asia ˇ Petr Sauer, University of Economics, Prague, Czech Republic, Negotiating between Authority and Polluters: An Approach to Managing Water Quality Donald Savage, NASA Headquarters, Washington, Mars Exploration Rover Mission Reuel Shinnar, The City College of the CUNY, New York, The Mirage of The H2 Economy

xiv

CONTRIBUTORS

Melissa A. Singer Pressman, Genetic Technologies, Inc. Testing Institute, Waukesha, Wisconsin, In Situ Chemical Monitoring Pratap Singh, National Institute of Hydrology, Roorkee, India, Snow Density, Snow and Snowmelt, Snow Surveys Vijay P. Singh, Louisiana State University, Baton Rouge, Louisiana, Entropy Theory For Hydrologic Modeling, Unit Hydrograph Theory, Hydrologic Cycle, Isohyetal Method D.C. Singleton, University of Hawaii, Hilo, Hawaii, Climate and Water Balance on the Island of Hawaii Bellie Sivakumar, University of California, Davis, California, Hydropsychology E. Dendy Sloan, Colorado School of Mines, Golden, Colorado, Clathrate Hydrates James A. Smith, (from The Handbook of Weather, Climate, and Water: Atmospheric Chemistry, Hydrology, and Societal Impacts, Wiley 2003), Rainfall Fiona Stainsby, Napier University, Edinburgh, Scotland, United Kingdom, Partitioning and Bioavailability Susan-Marie Stedman, Silver Spring, Maryland, Coastal Waters Kenneth F. Steele, University of Arkansas, Fayetteville, Arkansas, Nitrogen, Carbonate Geochemistry David P. Stern, Goddard Space Flight Center, NASA, Electricity as a Fluid, Weather and the Atmosphere Bradley A. Striebig, Gonzaga University, Spokane, Washington, Chemical Precipitation Georgina Sturrock, Commonwealth Scientific and Industrial Research Organization—Australia, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific Artur P. Terzyk, N. Copernicus University, Torun, ´ Poland, The Effect of Carbon Surface Chemical Composition on the Mechanism of Phenol Adsorption from Aqueous Solutions, Mechanisms of Water Adsorption on Carbons Ryszard Tokarczyk, University of Miami, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific Marta E. Torres, Oregon State University, Corvallis, Oregon, Distribution and Dynamics of Gas Hydrates in the Marine Environment Christopher Tracey, U.S. Geological Survey, Reston, Virginia, Sea Level and Climate Anne M. Trehu, Oregon State University, Corvallis, Oregon, Distribution and Dynamics of Gas Hydrates in the Marine Environment Robert C. Upstill-Goddard, University of Newcastle upon Tyne, Newcastle upon Tyne, United Kingdom, The Role of Oceans in the Global Cycles of Climatically-Active Trace-Gases David B. Vance, ARCADIS, Midland, Texas, Regulatory Issues and Remediation: Risk, Costs, and Benefits, Water, Bacteria, Life on Mars, and Microbial Diversity Javier Velez-Arocho, U.S. Environmental Protection Agency, Washington, District of Columbia, Marine Debris Abatement Roger C. Viadero Jr., West Virginia University, Morgantown, West Virginia, Henry’s Law

Rolf R. von Oppenfeld, The TESTLaw Practice Group, Phoenix, Arizona, The National Pollution Discharge Elimination System, The Safe Drinking Water Act Linda Voss, U.S. Centennial of Flight Commission, Ballooning and Meteorology in the Twentieth Century U.S. Department of Labor, Bureau of Labor Statistics, Atmospheric Scientists U.S. Environmental Protection Agency—Oceans and Coastal Protection Division, Coral Reefs and Your Coastal Watershed U.S. Geological Survey, Water Quality U.S. Global Change Research Program, The Global Water Cycle Guy Webster, Jet Propulsion Laboratory, Pasadena, California, Mars Exploration Rover Mission Radosław P. Wesołowski, N. Copernicus University, Torun, ´ Poland, Mechanisms of Water Adsorption on Carbons Scott Whiteford, Michigan State University, East Lansing, Michigan, Transboundary Waters in Latin America: Conflicts and Collaboration Patrick Willems, Hydraulics Laboratory, Leuven, Belgium, Uncertainties in Rainfall–Runoff Modeling Richard S. Williams, Jr., U.S. Geological Survey, Woods Hole, Massachusetts, Sea Level and Climate Marek Wi´sniewski, N. Copernicus University, Torun, ´ Poland, Mechanisms of Water Adsorption on Carbons Ming Hung Wong, Hong Kong Baptist University, Kowloon Tong, Kowloon, Hong Kong, Larvae and Small Species of Polychaetes in Marine Toxicological Testing Eve Woods, Denver, Colorado, Reserved Water Rights for Indian and Federal Lands P.L. Woodworth, Proudman Oceanographic Laboratory, Birkenhead, United Kingdom, The Permanent Service for Mean Sea Level Tom Wydrzynski, The Australian National University, Canberra, Australia, Isotope Exchange in Gas-Water Reactions Carl L. Yaws, Lamar University, Beaumont, Texas, Adsorption Capacity of Activated Carbon for Water Purification, Solubility of Hydrocarbons and Sulfur Compounds in Water, Solubility of Chemicals in Water, Solubility of Hydrocarbons in Salt Water Brian Yocis, Bigelow Laboratory for Ocean Sciences, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific David W. Yoskowitz, Texas A&M University—Corpus Christi, Laredo, Texas, U.S./Canadian Boundary Waters Treaty and the Great Lakes Water Quality Agreement Mark A. Young, University of Iowa, Iowa City, Iowa, Environmental Photochemistry in Surface Waters Shari Yvon-Lewis, Atlantic Oceanographic and Meteorological Laboratory, NOAA and University Scientists Study Methyl Bromide Cycling in the North Pacific Karl Erik Zachariassen, Norwegian University of Science and Technology, Trondheim, Norway, Freezing and Supercooling of Water, OsmosisDiffusion of Solvent or Caused by Diffusion of Solutes? A. Zaharuddin, University of Malaya, Petaling Jaya Selangor, Malaysia, Islamic Water Law

OCEANOGRAPHY AIR–SEA INTERACTION

For stable conditions (Tair > Tsea ), z 620(Tair − Tsea ) = L (Tair + 273.2)Uz2

S.A. HSU Louisiana State University Baton Rouge, Louisiana

(2)

According to Hsu (13,14), B = 0.146(Tsea − Tair )0.49

INTRODUCTION Air–sea interaction is, according to Geer (1), the interchange of energy (e.g., heat and kinetic energy) and mass (e.g., moisture and particles) that takes place across the active surface interface between the top layer of the ocean and the layer of air in contact with it and vice versa. The fluxes of momentum, heat, moisture, gas, and particulate matter at the air–water interface play important roles, for example, in environmental hydraulics and water–environment–health interactions, during low wind speeds before the onset of wave breaking, the exchange of air bubbles is limited. If this situation persists for a long time, algal blooms may develop, ultimately affecting water quality. On the other hand, during typhoon/hurricane conditions, the storm surge may affect the sewerage outflow at a greater depth than normal because of shoaling. In the area on the right-hand side of the storm track (in the Northern Hemisphere), runoff may also be blocked due to the surge, thus increasing the flood potential and saltwater intrusion. Air–sea interaction encompasses vast scales in both spatial and temporal viewpoints, so only a few basic and applied topics are summarized here, including the parameterization of stability length, determination of friction velocity, wind–wave interaction, and the estimation of shoaling depth during storms. For more detailed laws and mechanisms in air–sea interaction, see Donelan (2) and recently Csanady (3); for air–sea exchange of gases and particles, see Liss (4) and most recently Donelan et al. (5); for the role of air–sea exchange in geochemical cycling, see Buat-Menard (6) and recently Liss (7); for larger scale air–sea interaction by La ˜ and its impacts, see Glantz (8); for more physics, Nina chemistry, and dynamics related to air–sea exchange, see Geernaert (9); and for wind–wave interaction, see Janssen (10).

where z is the height normally set to 10 m; Tair and Tsea stand for the air and sea temperatures, respectively; Uz is the wind speed at height z; and B is the Bowen ratio. For operational and engineering applications, z/L ≤ −0.4 is unstable, |z/L| < 0.4 is neutral, and z/L ≥ 0.4 is stable. PARAMETERIZATION OF THE ROUGHNESS LENGTH The roughness parameter Z0 can be computed based on the formula provided in Taylor and Yelland (15) that
4.5 Hs Z0 = 1200 Hs Lp

(4)

and, for deep water waves, Lp =

gT 2p 2π

(5)

where g is gravitational acceleration, Hs and Lp are the significant wave height and peak wavelength for the combined sea and swell spectrum, and Tp is its corresponding wave period. Note that Hs is defined as the average of the highest one-third of all wave heights during the 20-minute sampling period. ESTIMATION OF THE FRICTION VELOCITY The friction velocity (u∗ ) can be obtained as follows: 1/2

u∗ = U10 Cd

(6)

where U10 is the wind speed at 10 m and Cd is the drag coefficient. According to Amorocho and DeVries (16), the WAMDI Group (17), and Hsu (18), one may classify the air–sea interaction into three broad categories based on wave breaking conditions: In light winds, U10 < 7.5 m/s, prior to the onset of wave breakers,
 u∗ 2 = 1.2875 ∗ 10−3 (7) Cd = U10

PARAMETERIZATION OF THE STABILITY LENGTH In the atmospheric boundary layer, the buoyancy length scale, L, also known as the Obukhov (or Monin–Obukhov) length, is a fundamental parameter that characterizes the ‘‘stability’’ of the surface layer (11). L describes the relative importance between the buoyancy effect (or thermal turbulence) and wind shear (or mechanical turbulence). According to Hsu and Blanchard (12), L can be parameterized as follows. For unstable conditions (i.e., when Tsea > Tair ), 0.07 1000(Tsea − Tair )(1 + ) z B =− 2 L (Tair + 273.2)Uz

(3)

Both thermal and mechanical turbulence are important. In moderate winds, 7.5 ≤ U10 ≤ 20 m/s, the range after the onset but before the saturation of wave breakers,

(1)

Cd = (0.8 + 0.065U10 ) ∗ 10−3 1

(8)

2

AIR–SEA INTERACTION

Mechanical turbulence is more important than thermal effects. In strong winds, U10 > 20 m/s, after the saturation of wave breakers, (9) Cd = 2.5 ∗ 10−3 Mechanical turbulence dominates. ESTIMATING LATENT HEAT FLUX (OR EVAPORATION) Using the parameter of the Bowen ratio supplied by Hsu (13,14), as shown in Eq. 3, the latent heat flux (Hlatent ) can be estimated as 1 1 Hlatent (W m−2 ) = Hsensible = ρa Cp CT (Tsea − Tair )U10 B B (10) where Hsensible is the sensible heat flux, ρa (=1.2 kg m−3 ) is the air density, Cp (=1004 J kg−1 K−1 ) is the specific heat at constant pressure for dry air, CT (=1.1 ∗ 10−3 ) is the transfer coefficient for heat, (Tsea − Tair ) is in K, and U10 in m s−1 . A latent heat flux of 1 W m−2 is equivalent to an evaporation rate of 3.56 ∗ 10−3 cm day−1 , so Eq. 10 can be used to estimate the evaporation rate. ESTIMATING MAXIMUM SUSTAINED WIND SPEED DURING A HURRICANE Under hurricane/typhoon conditions, intense air–sea interaction occurs. Beach erosion, engineering structures, storm surge, and sewerage outflow can all be affected, so this topic should deserve more attention than the deepwater environment. The very first subject related to a tropical cyclone is to estimate its maximum sustained wind speed at the standard height of 10 m (i.e., U10 ). This is accomplished as follows. From the cyclostrophic equation (i.e., centrifugal force = pressure gradient) (11), 1 ∂P 1 P 1 Pn − P0 Ua2 = = = γ ρa ∂γ ρa γ ρa γ − 0

(11)

where Ua is the maximum sustained wind speed above the surface boundary layer, γ is the radius of the hurricane, ∂P/∂γ is the radial pressure gradient, Pn is the pressure outside the hurricane effect (1013 mb, the mean sea level pressure), and P0 is the hurricane’s minimum central pressure. Because ρa = 1.2 kg m−3 , P = (1013 − P0 ) mb, and 1 mb = 100 N m−2 = 100 kg m−1 s−2 , Eq. 11 becomes  Ua =

100 kg m−1 s−2 1.2 kg m

−3

1/2

√ √ P = 9 P

(12)

According to Powell (19), U10 = 0.7Ua ; therefore U10

√ = 6.3 P = 6.3(1013 − P0 )1/2

(13)

where U10 is in m s−1 and P in mb. Equation 13 has been verified by Hsu (18). In 1985, during Hurricane Kate over the Gulf of Mexico, the

U.S. National Data Buoy Center (NDBC) buoy #42003, located on the right-hand-side of the storm track near the radius of maximum wind, recorded a minimum sealevel pressure (P0 ) of 957.1 mb. Therefore, P = (1013 − 957.1) = 55.9 mb. Substituting this value in Eq. 13, U10 = 47.1 m s−1 which is in excellent agreement with the measured U10 = 47.3 m s−1 . Another verification is provided in Fig. 1. According to Anthes (20, p. 22 and Fig. 2.8),
U10γ = U10 max

R γ

0.5 (14)

where U10γ is the sustained wind speed at a distance 10 m away from the storm center and U10 max is the maximum sustained wind at 10 m at the radius of maximum wind, R. According to Hsu et al. (21), for operational applications, 
1013 − P0 R (15) = ln γ Pγ − P0 where Pγ is the pressure at a point located at a distance from the storm center and ln is the natural logarithm. Substituting Eq. 15 in Eq. 14, 
 1013 − P0 0.5 U10γ = U10 max ln Pγ − P0

(16)

During Hurricane Lili in 2002, the NDBC had two buoys, #42001 located near R, and #42003 located due east along 26 ◦ N, approximately 280 km from 42001. The wind speed measurement at both buoys was 10 m. From the NDBC website (www.ndbc.noaa.gov/), at 20Z 2 October 2002 at #42001, P0 = 956.1 mb. Substituting this P0 in Equation 13, U10 max = 47.5 m s−1 , in excellent agreement with the measured value of 47.2 m s−1 (=106 mph). Therefore, Eq. 13 is further verified. At the same time, Pγ = 1011.1 mb was measured at #42003. Substituting this Pγ in Eq. 16, we obtain U10γ = 8.8 m s−1 . The measured U10γ at 42003 was 9.2 m s−1 . The difference is only about 4%, so we conclude that Eqs. 13 and 16 can be used for nowcasting using the pressure measurements at Pγ and P0 which are normally available via the official ‘‘Advisory’’ during a hurricane. ESTIMATING MAXIMUM SIGNIFICANT WAVE HEIGHT DURING A HURRICANE According to the USACE (22, p. 3–85, Eq. 3–64),  Hs Tp = 12.1 g ∴

Hs gT 2p

= 0.0068

(17) (18)

More verification of Eq. 18 is provided in Hsu (23). According to Hsu et al. (21), based on the evaluation of nine fetch-limited wind–wave interaction formulas, that provided by Donelan et al. (24) ranked best as follows: 
gT p 1.65 gH s = 0.00958 2 U10 U10

(19)

AIR–SEA INTERACTION

3

Figure 1. Satellite data (visible channel from NOAA-16) received and processed at the Earth Scan Lab, Louisiana State University, during Hurricane Lili (2002) in the Gulf of Mexico. The solid line represents the storm track. Data from NDBC buoys 42001 and 42003 are employed in this study. Note that the anemometers for both bouys were located at the standard 10 m height.

ESTIMATING STORM SURGE AND SHOALING DEPTH

From Eqs. 18 and 19, 2 Hs = 0.00492 U10

(20)

Substituting Eq. 13 in Eq. 20, Hs

max

= 0.20 P

(21)

where Hs max is in meters and P is in mb. Equation 21 is verified in Fig. 1. Buoy 42001, located near the radius of maximum wind, measured P0 = 956.1 mb at 20Z 2 October 2002, so that P = (1013 − 956.1) = 56.9 mb. Substituting this value in Eq. 21, Hs max = 11.38 m, which is in excellent agreement with that of 11.22 m measured at 21Z 2 October 2002 (within 1 hour after the measured minimal P0 ).

To estimate a typhoon/hurricane—generated storm surge (S), and shoaling depth (Dshoaling ), the following formulas are useful operationally, provided that the storm’s minimum (or central) pressure near the sea surface (P0 ) is known. According to Hsu (23), for the storm surge in deep water before shoaling (i.e., when the waves feel the sea floor), SI = 0.070(1010 − P0 )

(22)

where SI is the initial peak storm surge before shoaling. For the peak surge at the coast, SP = 0.070 (1010 − P0 ) ∗ FS ∗ FM

(23)

4

NOAA’S ATLANTIC OCEANOGRAPHIC AND METEOROLOGICAL LABORATORY

where FS is a shoaling factor dependent on shelf topography and width and FM is a correction factor for storm motion. Both FS and FM for certain areas are included in Hsu (23). A verification of Eq. 23 during Hurricane Georges in 1998 is also available in Hsu (23). The shoaling depth is computed as follows: From Taylor and Yelland (15), Dshoaling = 0.2 Lp , and from Eq. 5,

12. Hsu, S.A. and Blanchard, B.W. (2004). On the estimation of overwater buoyancy length from routine measurements. Environ. Fluid Mech., in press.

gT 2p

15. Taylor, P.K. and Yelland, M.J. (2001). The dependence of sea surface roughness on the height and steepness of the waves. J. Phys. Oceanogr. 31: 572–590. 16. Amorocho, J. and DeVries, J.J. (1980). A new evaluation of the wind stress coefficient over water surfaces. J. Geophys. Res. 85(C1): 433–442.

Dshoaling = 0.2

2π

=

0.2 Hs  Hs 2π gT 2p

where Hs /gT p 2 is called wave steepness, a useful parameter in coastal engineering. From Hsu et al. (21) and under hurricane conditions from Eq. 18, Hs /gT p 2 = 0.0068. Thus, from Eq. 21, Dshoaling = 4.7 Hs = 4.7 ∗ 0.2(1013 − P0 ) ∴ shoaling depth (meters) ≈ (1013 − P0 )

(24)

CONCLUDING REMARKS Although all formulas presented in this article are based on the open literature, they may need some verification before being applied to site-specific conditions. For example, Eq. 22 for the storm surge is for an open coast before shoaling. It needs to be adjusted for flooding at the coast due to different storm speeds and local bathymetry, as needed in Eq. 23. BIBLIOGRAPHY 1. Geer, I.W. (Ed.). (1996). Glossary of Weather and Climate With Related Oceanic and Hydrologic Terms. American Meteorological Society, Boston, MA.

13. Hsu, S.A. (1998). A relationship between the Bowen ratio and sea-air temperature difference under unstable conditions at sea. J. Phys. Oceanogr. 28: 2222–2226. 14. Hsu, S.A. (1999). On the estimation of overwater Bowen ratio from sea-air temperature difference. J. Phys. Oceanogr. 29: 1372–1373.

17. The WAMDI Group. (1988). The WAM model—a third generation ocean wave prediction model. J. Phys. Oceanogr. 18: 1775–1810. 18. Hsu, S.A. (2003). Estimating overwater friction velocity and exponent of the power-law wind profile from gust factor during storms. J. Waterways Port Coastal Ocean Eng. 129(4): 174–177. 19. Powell, M.D. (1982). The transition of the Hurricane Frederic boundary-layer wind field from the open Gulf of Mexico to landfall. Mon. Weather Rev. 110: 1912–1932. 20. Anthes, R.A. (1982). Tropical Cyclones, Their Evolution, Structure, and Effects. Meteorological Monographs Number 41, American Meteorological Society, Boston, MA. 21. Hsu, S.A., Martin, M.F., Jr., and Blanchard, B.W. (2000). An evaluation of the USACE’s deepwater wave prediction techniques under hurricane conditions during Georges in 1998. J. Coastal Res. 16(3): 823–829. 22. U.S. Army Corps of Engineers. (1984). Shore Protection Manual. Vicksburg, MS. 23. Hsu, S.A. (2004). A wind-wave interaction explanation for Jelesnianski’s open-ocean storm surge estimation using Hurricane Georges (1998) measurements. Natl. Weather Dig., in press. 24. Donelan, M.A., Hamilton, J., and Hui, W.H. (1985). Directional spectra of wind-generated waves. Philoso. Transa. Roy. Soc. London, Ser. A 315: 509–562.

2. Donelan, M.A. (1990). Air-sea interaction. In: The Sea. Wiley, Vol. 9. Hoboken, NJ. 3. Csanady, G.T. (2001). Air-Sea Interaction: Laws and Mechanisms. Cambridge University Press, Cambridge, UK. 4. Liss, P.S. (1983). Air-Sea Exchange of Gases and Particles. Kluwer Academic, Springer, New York. 5. Donelan, M.A., Drennan, W.M., Saltman, E.S., and Wanninkhof, R. (Eds.). (2002). Gas Transfer at Water Surfaces. Geophysical Monograph #127, American Geophysical Society, Washington, DC. 6. Buat-Menard, P. (1986). Role of Air-Sea Exchange in Geochemical Cycling. Kluwer Academic, Springer, New York. 7. Liss, P.S. (1997). Sea Surface and Global Change. Cambridge University Press, Cambridge, UK. ˜ and Its Impacts: Facts and 8. Glantz, M.H. (2002). La Nina Speculation. Brookings Inst. Press, Washington, DC. 9. Geernaert, G.L. (1999). Air-Sea Exchange: Physics, Chemistry & Dynamics. Kluwer Academic, Springer, New York.

NOAA’S ATLANTIC OCEANOGRAPHIC AND METEOROLOGICAL LABORATORY National Oceanographic and Atmospheric Administration (NOAA)

June 18, 1999—The Atlantic Oceanographic and Meteorological Laboratory (AOML) in Miami, Florida, is one of 12 environmental research laboratories that work on environmental issues for NOAA’s Office of Oceanic and Atmospheric Research (OAR). OAR research advances NOAA’s ability to predict weather, helps monitor and provides understanding of climate and global change, as well as improve coastal ocean health.

10. Janssen, P. (2004). The Interaction of Ocean Waves and Wind. Cambridge University Press, Cambridge, UK. 11. Hsu, S.A. (1988). Coastal Meteorology. Academic Press, San Diego, CA.

This article is a US Government work and, as such, is in the public domain in the United States of America.

NOAA’S ATLANTIC OCEANOGRAPHIC AND METEOROLOGICAL LABORATORY

5

AOML’s mission is to conduct a basic and applied research program in oceanography, tropical meteorology, atmospheric and oceanic chemistry, and acoustics. The programs seek to understand the physical characteristics and processes of the ocean and the atmosphere, both individually and as a coupled system. The principal focus of these investigations is to provide knowledge that may ultimately lead to improved prediction and forecasting of severe storms, better use and management of marine resources, better understanding of the factors affecting both climate and environmental quality, and improved ocean and weather services for the nation.

Originally under the jurisdiction of the Environmental Science Services Administration (ESSA), the forerunner of NOAA, AOML was founded in Miami, Florida, in 1967. Several months after NOAA was established in 1970, groundbreaking began on a new 12-acre federally funded research facility on Virginia Key. AOML dedicated its new location on Feb. 9, 1973. It celebrated its 25th anniversary in 1998. AOML has four main research divisions: Hurricane Research, Ocean Acoustics, Ocean Chemistry, and Physical Oceanography. To learn more about AOML visit: http://www.aoml. noaa.gov/ HURRICANE RESEARCH DIVISION The Hurricane Research Division (HRD) is NOAA’s primary component for research on hurricanes. Its high-

est priority is improving the understanding and prediction of hurricane motion and intensity change. A key aspect of this work is the annual hurricane field program, supported by the NOAA Aircraft Operation’s Center research/reconnaissance aircraft. Research teams analyze data from field programs, develop numerical hurricane models, conduct theoretical studies of hurricanes, prepare storm surge atlases, and study the tropical climate. HRD works with the National Hurricane Center/Tropical Prediction Center in all phases of its research, the National Meteorological Center and the Geophysical Fluid Dynamics Laboratory—another of OAR’s research labs—in research related to numerical modeling of hurricanes, and the National Severe Storms Laboratory—yet another OAR lab—in the study of landfalling hurricanes,

6

LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS

as well as other NOAA groups, federal agencies, and universities in a variety of basic and applied research. OCEAN ACOUSTICS DIVISION The Ocean Acoustics Division (OAD) gathers, analyzes and reports coastal ocean data on human-related discharges and their potential environmental impacts. Additionally, OAD has an ongoing research program on the use of acoustics to measure coastal and deep ocean rainfall, an important element in calculating the global energy balance for climate monitoring and prediction. The Division works in cooperation with other federal, state, and local authorities to maximize research knowledge for use in economically and environmentally important projects in the coastal ocean.

OCEAN CHEMISTRY DIVISION With a diverse scientific staff of marine, atmospheric, and geological chemists, as well as chemical, biological, and geological oceanographers, the Ocean Chemistry Division (OCD) is able to use multidisciplinary approaches to solve scientific research questions. The Division’s work includes projects that are important in assessing the current and future effects of human activities on our coastal to deep ocean and atmospheric environments. PHYSICAL OCEANOGRAPHY DIVISION The Physical Oceanography Division (PhOD) provides and interprets oceanographic data and conducts research relevant to decadal climate change and coastal ecosystems. This research includes the dynamics of the ocean, its interaction with the atmosphere, and its role in climate and climate change. Data is collected from scientific expeditions, both in the deep ocean and in coastal regions. Satellite data is processed and incorporated into the analyses. PhOD manages the Global Ocean Observing (GOOS) Center, which manages the global collection, processing, and distribution of drifting buoy data and the information collected from ocean temperature profilers. This information is crucial to understanding and predicting shifts in weather patterns and the relationship of the ocean and the atmosphere as a coupled system.

LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS PAOLO MAGNI IMC—International Marine Centre Torregrande-Oristano, Italy

SHIGERU MONTANI Hokkaido University Hakodate, Japan

BACKGROUND Benthic nutrient regeneration may be referred to as a new availability to the water column of significant amounts of nitrogen, phosphorus, and other nutrients, as a consequence of the metabolism of organic matter by the benthos (1). The processes of benthic nutrient regeneration in coastal marine systems are strongly influenced by the presence of abundant macrofauna (2–5). Correct evaluation of the biogenic flux of nutrients due to the excretory activity of infaunal species is therefore an important background of information to investigate the cycling of biophilic elements (nitrogen, phosphorus, and silicon). In field studies, major drawbacks include the difficulty to discern between nutrient upward flux due to animal excretion and a number of local effects, such as microbial mineralization (4,6–8) and uptake (9–14), animal bioturbation and irrigation currents (15–19), tidal currents and

LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS

wind-generated waves (20–22). Laboratory experiments on the animal excretion rates of nutrients under more controlled conditions represent a useful tool for quantifying the actual biogenic contribution by macrofauna to the total upward flux of nutrients from sediments. Nevertheless, these experiments have often restricted their investigations to ammonium (23–28) or, in a few cases, to ammonium and phosphate (29). CASE STUDY This study was conducted within a multidisciplinary project on the cycling of nutrients and organic matter in a tidal estuary in the Seto Inland Sea (30–37). Laboratory experiments were carried out on the excretion rates of ammonium, phosphate, and silicate by different size classes of the bivalves, Ruditapes philippinarum and Musculista senhousia. These species were selected as they were dominant on a sandflat of the estuary under investigation. An extrapolation of these results to a field community is presented in TEMPORAL SCALING OF BENTHIC NUTRIENT REGENERATION IN BIVALVE-DOMINATED TIDAL FLAT. Both studies will be the basis of a third companion paper on the relationship between the temporal scaling of bivalve nutrient excretion and the seasonal change of nutrient concentrations in the porewater (SEASONAL COUPLING BETWEEN INTERTIDAL MACROFAUNA AND SEDIMENT COLUMN POREWATER NUTRIENT CONCENTRATIONS). In these experiments, 2.5 L aquaria with and without (control) animals were employed and run on two different occasions for 24 hours. Each experiment consisted of a 10 h day (light) and a 10 h night (dark) treatment in which the changes in nutrient concentrations were measured every 2 h. Between the two (light and dark) treatments, a low tide lasting 2 h (like that approximately on the flat where animals were collected) was created, during which the experimental animals were not removed from sediments to keep the experiment continuous. The experimental setup and procedure are detailed in our associated paper

7

where the bivalve excretion rates of ammonium and phosphate have been presented and discussed (35). We will extend this study to silicate, a nutrient species whose regeneration through animal excretory activity has been less investigated, either in situ (38,39) or in the laboratory (5,40). Table 1 includes some characteristics of the experimental animals, as well as the field-relevant (33) amount of algal food (Thalassiosira sp.) offered in four spikes during each experiment (35). In all treatments, there was a marked increase in all three nutrient concentrations, in the control (no animals), the increase was much more limited (i.e., silicate) or not observed (i.e., ammonium) (Fig. 1). Based on the differences in nutrient concentrations between treatments and controls, relevant linear regression lines of five to six measurements were used to calculate the nutrient excretion rates for each size class of R. philippinarum and M. senhousia (Table 2). This approach may be a more reliable way to quantify the daily bivalve excretion, whereas previous similar experiments have been based on shorter incubations and/or the sole difference between initial and final values of nutrient concentrations (4,7,22,28,29). The data sets were subjected to ANOVA in a two-factor randomized complete block design, using the day/night variable as factor A, the time (hour) variable as factor B, and the size classes of each bivalve species as replicates (35). As found for ammonium in R. philippinarum, but not in M. senhousia, silicate excretion was significantly higher (57%, p < 0.001, n = 36) during the day than during the night, suggesting a possible effect of light on the excretory activity of this bivalve species. A comparison of nutrient excretion rates (µmol g−1 DW h−1 ) of bivalve species obtained through in situ or laboratory experiments is given in Table 3. According to the excretion rates of silicate found in our laboratory experiments, this study points to the importance of the excretory activity of these bivalve species to the biogenic regeneration of silicate. This aspect

Table 1. Animals Employed in the Laboratory Experiments and Experimental Conditions. Ind.: Number of Individualsa,b Size, mm

Species

Ind., n

TOT, mg

DW, mg

Temp, ◦ C

Chla, (µg L− 1)

Expt, date

19.6 ±1.5 19.6 ±1.5 21.6 ±0.3

26.3 ±8.7 24.6 ±8.8 38.9 ±12.8

May 1996 – May 1996 – Sep 1996 –

19.6 ±1.5 21.6 ±0.3

24.5 ±9.1 47.4 ±22.8

May 1996 – Sep 1996 –

Ruditapes philippinarum Size class I Size class II Size class III

AVG SD AVG SD AVG SD

9.4 ±1.4 15.5 ±1.0 18.9 ±0.8

12 – 15 – 9 –

197 ±79 830 ±174 1520 ±149

9.9 ±4.0 37.0 ±9.2 63.6 ±10.4

Musculista senhousia Size class I Size class II a

AVG SD AVG SD

16.7 ±1.3 23.5 ±1.7

14 – 8 –

431 ±117 1264 ±172

27.6 ±7.7 52.4 ±8.0

Reproduced from Reference 35. TOT: mean (live) weight for each size class of the experimental animals; DW: mean dry soft-body weight for each size class of the experimental animals; Temp: experimental temperature; Chl a (Chlorophyll a) is the mean (AVG) ± standard deviation (SD) of four spikes of cultures of Thalassiosira sp. (Chl a = 0.01 × Thalassiosirasp. cell + 3.6, r2 = 0.908; p < 0.001, n = 40) for each day/night treatment b

8

LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS

May 9–10, 1996

September 6–7, 1996

Control

Control

R. philippinarum I R. philippinarum II M. senhousia I

R. philippinarum III M. senhousia II

30

50 Dark

40 NH4+, µM

NH4+, µM

Light 20 10

Light

Dark

Light

Dark

Light

Dark

30 20 10

0

0 Light

PO43−, µM

3 2 1

Si(OH)4, µM

30 20 10

Time, hour

Nutrient Excretion Rate, µmol g−1 DW h−1

Species

Light

Ruditapes philippinarum Size class I 10.6 Size class II 9.6 Size class III 5.0 Light/dark mean 8.4b Total mean 7.1

PO4 3− Dark Light 7.9 5.8 3.8 5.8

Musculista senhousia Size class I 9.3 11.4 Size class II 16.9 9.7 Light/dark mean 13.1 10.6 Total mean 11.8

Si(OH)4

Dark Light

3.4 1.0 0.9 1.8

3.9 1.1 0.7 1.9

10.9 3.3 1.1 5.1 6.6

1.5 1.3 1.4 1.4

Dark

15.8 4.1 4.0 8.0b

1.9 1.2 1.6 1.4

2

Dark

10 12 14 16 18 20 22 24 2 4 6 8

Si(OH)4, µM

Light

Table 2. Nutrient Excretion Rate for Each Size class of Ruditapes philippinarum and Musculista senhousia During day/night Treatments (Experimental Temperature as in Table 1)a

NH4 +

4

0

0

0

6

14.5 4.2 9.4

4.8 5.5 5.2 7.3

a

Based on Reference 35. Mean day (light) excretion significantly higher (ANOVA p < 0.001) than night (dark) excretion (based on Reference 35). b

has been more controversial than the contribution of bivalves to the regeneration of ammonium and phosphate. The extent of silicate excretion also varies considerably, depending on the bivalve species investigated and the environmental/experimental conditions employed.

40 30 20 10 0

10 12 14 16 18 20 22 24 2 4 6 8

PO43−, µM Figure 1. Laboratory experiments: changes of nutrient concentrations [ammonium, NH4 + –N); phosphate, PO4 3− –P; and silicate Si(OH)4 –Si] during the day (light) and night (dark) treatments. Vertical dashed lines: left line (time 20:00) indicates the end of the day (light) treatment; right line (time 22:00) indicates the start of the night (dark) treatment; between lines: low tide between treatments (based on Ref. 35).

Dark

Time, hour

In in situ experiments, Prins & Small (4) found no significant excretion of silicate by Mytilus edulis beds on an intertidal zone of the Westerschelde (The Netherlands). The occurrence of silicate fluxes was attributed to the possible increased rate of dissolution of silicate at higher temperature. Asmus et al. (38) in the eastern Wadden Sea (Germany) and Dame et al. (39) in the Easterschelde and the western Wadden Sea (The Netherlands) found high fluxes of silicate from mussel beds of M. edulis. Although, in both studies, the actual excretion rate of silicate by M. edulis was not estimated per biomass unit (e.g., µmol g−1 DW h−1 ), Dame et al. (39) suggested that silicate release from mussel beds results from phytoplankton cells breaking down as they are metabolized by the mussels. Dame et al. (39) argued that the longer turnover time for silicate, compared to phosphate and ammonium, implies a lesser role for the mussel beds in recycling this nutrient species in the two estuaries under investigation. In contrast, Asmus et al. (38) found rapid silicate release in the Sylt-flume study and suggested that the mussels are an accelerator in recycling biogenic silica. Similarly, a study on the nutrient excretion of R. philippinarum in core incubation experiments found that silicate regeneration was, on average, 9.2 times faster in the site farmed with clams (5). In mesocosm experiments using large tanks, Doering et al. (40) also found that the level of flux was elevated in the presence of another clam, Mercenaria mercenaria, by 86% and 57% for silicate and ammonium, respectively. Our results indicate

LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS

9

Table 3. Comparison of Nutrient Excretion Rates (µmol g−1 DW hour−1 ) for Different Species of Mussels (m), Clams (c) and Oysters (o)a Species and Study Area Mytilus edulis (m) Narragansett Bay, USA Linher River, U.K. Sound, DK Western Scheldt, NL Musculista senhousia (m) Seto Inland Sea, JPN Seto Inland Sea, JPN Modiolus demissus (m) Narragansett Bay, USA Great Sippewissett, USA Donax serra (m) Maitland River, S. Africa Sundays River, S. Africa Donax sordidus (m) Sundays River, S. Africa Aspatharia wahlbergi (m) Lake Kariba, Zimbabwe Corbicula africana (c) Lake Kariba, Zimbabwe Corbicula japonica (c) Lake Shinji, JPN Mercenaria mercenaria (c) Delaware Bay, USA Macoma balthica (c) Wadden Sea, DK Ruditapes philippinarum (c) Virgin Islands, USA Moss Landing, USA Moss Landing, USA Marennes-Ol´eron, F Hatchery, Ireland Seto Inland Sea, JPN Seto Inland Sea, JPN Crassostrea virginica (o) Delaware Bay, USA Crassostrea gigas (o) North Brittany, F

Methodb

NH4 +

PO4 3−

Si(OH)4

T, ◦ C

Reference

Lab Lab In situ In situ

3.1 4.9–34.6 0.14–3.1 1.1

ndc nd 0.10–0.53 nd

ndc nd nd nd

15 11–21 0.7–18 12

41 23 42 43

Lab Lab

9.3–16.9 9.3–16.9

1.2–1.6 1.2–1.6

– 4.2–14.5

18–22 18–22

35 This study

Lab Lab

3.58 ± 1.73 2.5

nd nd

nd nd

21 annual

41 2

In situ Lab/In situ

0.35–8.1 2.2

nd nd

nd nd

15–25

44 26

Lab/In situ

2.9

nd

nd

15–25

26

Lab

6.1

0.48

nd

25.2

29

Lab

12.9

nd

nd

25.2

29

Lab

14.3

nd

nd

27

28

Lab

0.9–1.5

nd

nd

20

45

Lab

0.1d

nd

nd

13–15

16

Lab Lab Lab Lab Lab Lab Lab

1.9–4.9 1–2.3 0.6–0.9 0.5–13 0.16–1 3.8–10.6 3.8–10.6

nd nd nd nd nd 0.7–3.9 0.7–3.9

nd nd nd nd nd — 1.1–15.8

20.1 27.1 12, 15, 18 5–25 18.8 18–22 18–22

24 46 47 25 27 35 This study

Lab

0.5–0.9

nd

nd

20.1

24

In situ

0.28–6.6

nd

nd

27.1

48

a

Based on Reference 35. Lab: laboratory experiments. c nd: not determined. d Excretion rate calculated as a wet soft-body weight. b

well-balanced stoichiometric ratios among the nutrient species excreted by the bivalves (35), which can also be related to the use of the diatom Thalassiosira sp. as a food (35). This was aimed to approximate the actual field situation on the tidal flat, where abundant microalgal biomass, including resuspended benthic diatoms, is available to filter-feeders such as in R. philippinarum and M. senhousia (31,33). The high excretion rates of silicate of these two dominant bivalve species found in our laboratory experiments, together with those of ammonium and phosphate, suggest a major contribution of bivalve nutrient excretion to the upward flux of nutrients from sediments in our relevant study area. This will be the subject of the subsequent paper where we will apply these rates to the actual bivalve standing stock found in the field (TEMPORAL SCALING OF BENTHIC NUTRIENT REGENERATION IN BIVALVE-DOMINATED TIDAL FLAT).

BIBLIOGRAPHY 1. Nixon, S.W., Oviatt, C.A., and Hale, S.S. (1976). Nitrogen Regeneration and the Metabolism of Coastal Marine Bottom Communities. The Role of Terrestrial and Aquatic Organisms in Decomposition Process. J. Anderson and A. MacFayden (Eds.). Blackwell, Oxford, pp. 269–283. 2. Jordan, T.E. and Valiela, I. (1982). A nitrogen budget of the ribbed mussel, Geukensia demissa and its significance in nitrogen flow in a New England salt marsh. Limnol. Oceanogr. 27: 75–90. 3. Murphy, R.C., and Kremer, J.N. (1985). Bivalve contribution to benthic metabolism in a California lagoon. Estuaries 8: 330–341. 4. Prins, T.C. and Smaal, A.C. (1994). The role of the blue mussel Mytilus edulis in the cycling of nutrients in Oosterschelde estuary (the Netherlands). Hydrobiol. 282/283: 413–429.

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LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS

5. Bartoli, M. et al. (2001). Impact of Tapes philippinarum on nutrient dynamics and benthic respiration in the Sacca di Goro. Hydrobiol. 455: 203–212.

23. Bayne, B.L. and Scullard, C. (1977). Rates of nitrogen excretion by species of Mytilus (Bivalvia: Mollusca). J. Mar. Biol. Ass. U.K. 57: 355–369.

6. Falcao, M. and Vale, C. (1990). Study of the Rio Formosa ecosystem: benthic nutrient remineralization and tidal variability of nutrients in the water. Hydrobiol. 207: 137–146.

24. Langton, R.W., Haines, K.C., and Lyon, R.E. (1977). Ammonia-nitrogen production by the bivalve mollusc Tapes japonica and its recovery by the red seaweed Hypnea musciformis in a tropical mariculture system. Helgol. Wiss Meeresunters 30: 217–229. 25. Goulletquer, P. et al. (1989). Ecophysiologie et bilan e´ nerg´etique de la palourde japonaise d’ e´ levage Ruditapes philippinarum. J. Exp. Mar. Biol. Ecol. 132: 85–108.

7. Gardner, W.S., Briones, E.E., Kaegi, E.C., and Rowe, G.T. (1993). Ammonium excretion by benthic invertebrates and sediment–water nitrogen flux in the Gulf of Mexico near the Mississipi river outflow. Estuaries 16: 799–808. 8. Smaal, A.C. and Zurburg, W. (1997). The uptake and release of suspended and dissolved material by oysters and mussels in Marennes-Ol´eron Bay. Aquat. Living Resour. 10: 23–30. 9. Rizzo, W.M. (1990). Nutrient exchanges between the water column and a subtidal benthic microalgal community. Estuaries 13: 219–226. ¨ 10. Sundback, K., Enoksson, V., Gran´eli, W., and Pettersson, K. (1991). Influence of sublittoral microphytobenthos on the oxygen and nutrient flux between sediment and water: a laboratory continuous-flow study. Mar. Ecol. Prog. Ser. 74: 263–279. 11. van Duyl, F.C., van Raaphorst, W., and Kop, A.J. (1993). Benthic bacterial production and nutrient sediment-water exchange in sandy North Sea sediments. Mar. Ecol. Prog. Ser. 100: 85–95. 12. Risgaard-Petersen, N., Rysgaard, S., Nielsen, L.P., and Revsbech, N.P. (1994). Diurnal variation of denitrification and nitrification in sediments colonized by benthic microphytes. Limnol. Oceanogr. 39: 573–579. 13. Feuillet-Girard, M., Gouleau, D., Blanchard, G., and Joassard, L. (1997). Nutrient fluxes on an intertidal mudflat in Marennes-Ol´eron Bay, and influence of the emersion period. Aquat. Living Resour. 10: 49–58. 14. Trimmer, M., Nedwell, D.B., Sivyer, D.B., and Malcolm, S.J. (1998). Nitrogen fluxes through the lower estuary of the river Great Ouse, England: the role of the bottom sediments. Mar. Ecol. Prog. Ser. 163: 109–124. 15. Callender, E. and Hammond, D.E. (1982). Nutrient exchange across the sediment–water interface in the Potomac river estuary. Estuar. Coast. Shelf Sci. 15: 395–413. 16. Henriksen, K., Rasmussen, M.B., and Jensen, A. (1983). Effect of bioturbation on microbial nitrogen transformations in the sediment and fluxes of ammonium and nitrate to the overlaying water. Environ. Biogeochem. 35: 193–205. 17. Yamada, H. and Kayama, M. (1987). Liberation of nitrogenous compounds from bottom sediments and effect of bioturbation by small bivalve, Theora lata (Hinds). Estuar. Coast. Shelf Sci. 24: 539–555. 18. Aller, R.C. (1988). Benthic fauna and biogeochemical processes: the role of borrow structures. In: Nitrogen Cycling in Coastal Marine Environments. T.H. Blackburn and J. Sørensen (Eds.). Wiley, pp. 301–338. 19. Luther, I.II. et al. (1998). Simultaneous measurements of O2 , Mn, Fe, I− , and S(-II) in marine pore waters with a solid-state voltammetric microelectrode. Limnol. Oceanogr. 43: 325–333. 20. Nakamura, Y. (1994). Effect of flow velocity on phosphate release from sediment. Water Sci. Technol. 30: 263–272. 21. Miller-Way, T. and Twilley, T.T. (1996). Theory and operation of continuous flow systems for the study of benthic–pelagic coupling. Mar. Ecol. Prog. Ser. 140: 257–269. 22. Asmus, R.M. et al. (1998). The role of water movement and spatial scaling for measurements of dissolved inorganic nitrogen fluxes in intertidal sediments. Estuar. Coast. Shelf Sci. 46: 221–232.

26. Cockcroft, A.C. (1990). Nitrogen excretion by the surf zone bivalves Donax serra and D. sordidus. Mar. Ecol. Prog. Ser. 60: 57–65. 27. Xie, Q. and Burnell, G.M. (1995). The effect of activity on the physiological rates of two clam species, Tapes philippinarum (Adams & Reeve) and Tapes decussatus (Linnaeus). Biol. Environ. Proc. Royal Irish Acad. 95B: 217–223. 28. Nakamura, M., Yamamuro, M., Ishikawa, M., and Nishimura, H. (1988). Role of the bivalve Corbicula japonica in the nitrogen cycle in a mesohaline lagoon. Mar. Biol. 99: 369–374. 29. Kiibus, M., and Kautsky, N. (1996). Respiration, nutrient excretion and filtratin rate of tropical freshwater mussels and their contribution to production and energy flow in Lake Kariba, Zimbabwe. Hydrobiol. 331: 25–32. 30. Magni, P. (2000). Distribution of organic matter in a tidal estuary of the Seto Inland Sea, Japan, and its relationship with the macrozoobenthic communities. In: Ad hoc Benthic Indicator Group—Results of Initial Planning Meeting. IOC Technical Series No. 57, UNESCO, pp. 20–25. 31. Magni, P. and Montani, S. (1997). Development of benthic microalgal assemblages on an intertidal flat in the Seto Inland Sea, Japan: effects of environmental variability. La mer 35: 137–148. 32. Magni, P. and Montani, S. (1998). Responses of intertidal and subtidal communities of the macrobenthos to organic load and oxygen depletion in the Seto Inland, Japan. J. Rech. Oc´eanogr. 23: 47–56. 33. Magni, P. and Montani, S. (2000). Physical and chemical variability in the lower intertidal zone of an estuary in the Seto Inland Sea, Japan: seasonal patterns of dissolved and particulate compounds. Hydrobiol. 432: 9–23. 34. Magni, P., Abe, N., and Montani, S. (2000). Quantification of microphytobenthos biomass in intertidal sediments: layerdependent variation of chlorophyll a content determined by spectrophotometric and HPLC methods. La mer 38: 57–63. 35. Magni, P., Montani, S., Takada, C., and Tsutsumi, H. (2000). Temporal scaling and relevance of bivalve nutrient excretion on a tidal flat of the Seto Inland Sea, Japan. Mar. Ecol. Progr. Ser. 198: 139–155. 36. Magni, P., Montani, S., and Tada, K. (2002). Semidiurnal dynamics of salinity, nutrients and suspended particulate matter in an estuary in the Seto Inland Sea, Japan, during a spring tide cycle. J. Oceanogr. 58: 389–402. 37. Montani, S. et al. (1998). The effect of a tidal cycle on the dynamics of nutrients in a tidal estuary in the Seto Inland Sea, Japan. J. Oceanogr. 54: 65–76. 38. Asmus, H., Asmus, R.M., and Reise, K. (1990). Exchange processes in an intertidal mussel bed: A Sylt-flume study in the Wadden Sea. Berichte Biolog. Anstalt Helgol. 6: 78. 39. Dame, R.F. et al. (1991). The influence of mussel beds on nutrients in the western Wadden Sea and Eastern Scheldt estuaries. Estuaries 14: 130–138.

TEMPORAL SCALING OF BENTHIC NUTRIENT REGENERATION IN BIVALVE-DOMINATED TIDAL FLAT 40. Doering, P.H., Kelly, J.R., Oviatt, C.A., and Sowers, T. (1987). Effect of the hard clam Mercenaria mercenaria on benthic fluxes of inorganic nutrients and gases. Mar. Biol. 94: 377–383. 41. Nixon, S.W., Oviatt, C.A., Garber, J., and Lee, V. (1976). Diel metabolism and nutrient dynamics in a salt marsh embayment. Ecology 57: 740–750. ¨ 42. Schluter, L. and Josefsen, S.B. (1994). Annual variation in condition, respiration and remineralisation of Mytilus edulis L. in the Sound, Denmark. Helgol. Meeres. 48: 419–430. 43. Smaal, A.C., Vonck, A.P.M.A., and Bakker, M. (1997). Seasonal variation in physiological energetics of Mytilus edulis and Cerastoderma edule of different size classes. J. Mar. Biol. Ass. U.K. 77: 817–838. 44. Prosh, R.M. and McLachlan, A. (1984). The regeneration of surf-zone nutrients by the sand mussel, Donax Serra R¨oding. J. Exp. Mar. Biol. Ecol. 80: 221–233. 45. Snra, R.F. and Baggaley, A. (1976). Rate of excretion of ammonia by the hard clam Mercenaria mercenaria and the American oyster Crassostrea virginica. Mar. Biol. 36: 251–258. 46. Mann, R. and Glomb, S.J. (1978). The effect of temperature on growth and ammonia excretion of the Manila clam Tapes japonica. Estuar. Coast. Shelf Sci. 6: 335–339. 47. Mann, R. (1979). The effect of temperature on growth, physiology, and gametogenesis in the Manila clam Tapes philippinarum (Adams & Reeve, 1850). J. Exp. Mar. Biol. Ecol. 38: 121–133. 48. Boucher, G. and Boucher-Rodoni, R. (1988). In situ measurements of respiratory metabolism and nitrogen fluxes at the interface of oyster beds. Mar. Ecol. Prog. Ser. 44: 229–238.

TEMPORAL SCALING OF BENTHIC NUTRIENT REGENERATION IN BIVALVE-DOMINATED TIDAL FLAT

11

dense assemblages of bivalves, it has been shown, play a major role in these processes (14–16). BACKGROUND The contribution of benthic macrofauna to the total upward flux of nutrients has been investigated (mostly for ammonium and, to a lesser extent, for phosphate) in many coastal and estuarine areas using several approaches. They include laboratory and mesocosm experiments (17–19). In situ benthic chambers and sediment core incubations (20–22), and open flow/tunnel systems (16,23–26). Measurements of macrofauna-influenced nutrient flux, however, often have temporal limitations as they are based on one or relatively few sampling occasions, and thus seasonal patterns are in most cases not known. In this article, we evaluate the magnitude and temporal scaling of biogenic flux of nutrients from intertidal sediments densely populated by bivalves, based on extrapolating nutrient excretion rates of dominant bivalves to a field community. In particular, we show that the seasonal pattern of nutrient fluxes can be strongly influenced by the animal standing stock and its temporal distribution. This is beside the effect and importance of variation in excretion rate due to animal physiological factors, such as seasonal cycles of gametogenesis, storage and use of body reserves, and water temperature (27,28). The nutrient species considered in this study include ammonium, phosphate, and silicate, for which we quantified in associated laboratory experiments LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS the excretion rates of different size classes of two dominant bivalve species. The relevance of macrofaunal excretion in regenerating the inorganic forms of three major bioelements such as N, P, and Si is discussed.

PAOLO MAGNI IMC—International Marine Centre Torregrande-Oristano, Italy

SHIGERU MONTANI Hokkaido University Hakodate, Japan

Beside light and temperature (1–5), nutrients such as ammonium (NH4 + -N), phosphate (PO4 3− -P), and silicate [Si(OH)4 -Si] are a key factor in controlling the growth, abundance, and structure of primary producers in the ocean (6,7). Hence, it is important to investigate the availability, sources, and distribution of these nutrient species, as well as their spatial and temporal scaling. Biological processes strongly influence nutrient regeneration in different marine systems. In the open ocean, an important portion of reduced N-forms (e.g., NH4 + -N), for instance, is made available in situ from waste products of plankton metabolism (8,9) and supports the socalled ‘‘regenerated’’ primary production (10). In coastal marine ecosystems, benthic nutrient regeneration is a major driving force in cycling biophilic elements (e.g., N, P, and Si) (11–13) and abundant macrofauna, for example,

MACROFAUNAL COMMUNITIES We present here the macrofaunal composition and distribution at an individual station (Stn B5) of a transect line selected in a sandflat of the Seto Inland Sea of Japan (29). At this station, the porewater nutrient concentrations (ammonium, phosphate, and silicate) in the uppermost 10 cm of sediments were also investigated in parallel from January 1995 to April 1996. They will be the subject of a subsequent associated paper focusing on the relationship between the seasonal pattern of bivalve nutrient excretion, described here, and the seasonal variation of porewater nutrient concentrations SEASONAL COUPLING BETWEEN INTERTIDAL MACROFAUNA AND SEDIMENT COLUMN POREWATER NUTRIENT CONCENTRATIONS. The total density and biomass of macrofauna varied from 7,400 (July 1995) to 22,050 ind.m−2 (October 1995), and from 70.9 (July 1995) to 244 g DW m−2 (September 7, 1995), respectively (Fig. 1). The bivalves Ruditapes philippinarum and Musculista senhousia and the polychaetes Ceratonereis erithraeensis and Cirriformia tentaculata were dominant; they accounted for 60.5% and 94.7% of the total density and biomass, respectively. Remarkably, R. philippinarum and M. senhousia alone accounted for up to 83.3 ± 6.7% of the total biomass when this exceeded

12

TEMPORAL SCALING OF BENTHIC NUTRIENT REGENERATION IN BIVALVE-DOMINATED TIDAL FLAT

estimate the magnitude and temporal scaling of biogenic nutrient excretion, we used an indirect approach. The mean excretion rates of ammonium, phosphate, and silicate for the two dominant bivalves R. philippinarum and M. senhousia, which were obtained in laboratory experiments LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS, were applied to the relevant monthly biomass values found in the field. The ammonium and phosphate excretion rates of each bivalve species and their scaling to a field community have been extensively reported in Magni et al. (29). In this article, we applied these excretion rates to the bivalve biomass found at Stn B5 and extended this scaling to silicate, whose size-class dependent excretion rates are presented in LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS. For silicate, we adopted the same temperature-dependent excretion rate factors as those used for ammonium and phosphate (Table 1).

20000 15000 10000

0

Biomass, g DW m−2

(b) 250 200 150

20 Jan 17 Feb 17 Mar 15 Apr 16 May 30 May 14 Jun 12 Jul 10 Aug 7 Sep 29 Sep 30 Oct 27 Nov 26 Dec 24 Jan 22 Feb 21 Mar 17 Apr

5000

Others Cirriformia tentaculata C.nereis erithraeensis Ruditapes philippinarum Musculista senhousia

100

BIVALVE NUTRIENT EXCRETION

50 0

The highest excretion rates of nutrients were estimated in September 7, 1995, up to a total of 50.2, 7.5, and 34.1 mmol m−2 d−1 for ammonium, phosphate, and silicate, respectively (Fig. 2). This corresponded to the period of highest biomass of both R. philippinarum and M. senhousia, which also accounted for the highest bivalve percentage (91.8%) of the total macrofaunal biomass. The lowest excretion rates occurred in April 1995 for R. philippinarum (lowest biomass on the same occasion), in March 1995 for M. senhousia (lowest biomass on May 16, 1995), and in February 1995 as the sum of the two bivalve species excretion rates. These latter rates were 4.1, 0.64, and 2.9 mmol m−2 d−1 for ammonium, phosphate, and silicate, respectively. The upward flux rates of nutrients obtained through this extrapolation of laboratory experiments on bivalve nutrient excretion to a field community are comparable to the highest biogenic releases reported for dense assemblages of bivalves such as oyster reefs (34) and mussel beds (16,35). This study also points to the importance of bivalve excretion to the biogenic regeneration of silicate, as previously suggested by field measurements indicating evidence of increased levels of silicate flux in the

20 Jan 17 Feb 17 Mar 15 Apr 16 May 30 May 14 Jun 12 Jul 10 Aug 7 Sep 29 Sep 30 Oct 27 Nov 26 Dec 24 Jan 22 Feb 21 Mar 17 Apr

Density, ind m−2

(a) 25000

1995

1996 Time, month

Figure 1. Seasonal variation of density (a) and biomass (b) of dominant macrozoobenthic species at Stn B5 (29). Note that in May 1995 and September 1995, sampling was carried out fortnightly.

120 g DW m−2 , from August 1995 till the end of the investigations. The high values of total macrofaunal and bivalve biomass may be regarded as a typical feature of many estuarine and intertidal areas, which are amongst the most productive systems in the ocean (30). In addition, biomass was markedly lower during the first half of the year (January 1995 to July 1995) than between late summer and winter; yet values progressively increased from early spring (March 1995) to early summer (June 1995). These marked temporal changes of macrofaunal communities reflect the high variability of these ecosystems. To

Table 1. Adopted Temperature-Dependent Excretion Rates of Ammonium (NH4 + -N), Phosphate (PO4 3− -P), and Silicate [Si(OH)4 -Si] for Ruditapes philippinarum and Musculista senhousia Period

Temperature, ◦ C

Month

Station

Dec, Jan, Feb Nov, Mar – Apr, May, Jun, Oct Jul, Aug, Sep a

AVG SD AVG SD AVG SD AVG SD

Excretion Rate, µmol g−1 DW h−1 R. philippinarum

B5-B1

H1

Y3

4.7 ±1.8 11.7 ±0.9 19.6 ±2.8 27.7 ±2.3

5.9 ±1.8 11.9 ±0.2 19.9 ±4.0 28.0 ±3.1

10.4 ±2.1 15.2 ±3.0 21.7 ±3.6 26.9 ±1.1

f

a

0.6 – 0.9 – 1 – 0.9 –

NH4 4.3 – 6.4 – 7.1 – 6.4 –

+

PO4

3−

1.1 – 1.7 – 1.9 – 1.7 –

M. senhousia Si(OH)4 4.0 – 5.9 – 6.6 – 5.9 –

a

NH4 +

PO4 3−

Si(OH)4

0.5 – 0.7 – 1 – 1.2 –

5.9 – 8.3 – 11.8 – 14.2 –

0.7 – 1.0 – 1.4 – 1.7 –

3.7 – 5.1 – 7.3 – 8.8 –

f

A factor (f ) of 1 is used for the mean of the excretion rates obtained in laboratory experiments (see LABORATORY EXPERIMENTS ON BIVALVE EXCRETION RATES OF NUTRIENTS and based on Ref. 29).

NH4+-N, mmol m−2 day−1

TEMPORAL SCALING OF BENTHIC NUTRIENT REGENERATION IN BIVALVE-DOMINATED TIDAL FLAT

60 50

Ruditapes philippinarum Musculista senhousia

40 30 20 10

20

Ruditapes philippinarum Musculista senhousia

15

BIBLIOGRAPHY 5 0

40

Ruditapes philippinarum Musculista senhousia

30

1. Admiraal, W. and Peletier, H. (1980). Influence of seasonal variations of temperature and light on the growth rate of culture and natural population of intertidal diatoms. Mar. Ecol. Progr. Ser. 2: 35–43. 2. Harrison, W.G. and Platt, T. (1980). Variations in assimilation number of coastal marine phytoplankton: effects of environmental co-variates. J. Plank. Res. 2: 249–260. 3. Verhagen, J.H.G. and Nienhuis, P.H. (1983). A simulation model of production, seasonal changes in biomass and distribution of eelgrass (Zoostera marina) in Lake Grevelingen. Mar. Ecol. Progr. Ser. 10: 187–195.

20 10 0 20 Jan 17 Feb 17 Mar 15 Apr 16 May 30 May 14 Jun 12 Jul 10 Aug 7 Sep 29 Sep 30 Oct 27 Nov 26 Dec 24 Jan 22 Feb 21 Mar 17 Apr

Si(OH)4-Si, mmol m−2 day−1

by a comparison with the extent of benthic nutrient regeneration through diffusive flux. In particular, nutrient flux measured from nutrient concentrations in the porewater in adjacent intertidal and coastal areas was more than one order of magnitude lower; it varied from 0.2 to 1.5 mmol NH4 + -N m−2 d−1 and from 0.01 to −2 d−1 . It can be inferred that a 0.05 mmol PO3− 4 -P m marked increase in biogenic nutrient regeneration is importantly controlled by the animal biomass increase (36) and has a major impact, acting as a positive feedback, on primary producers (41). These results indicate that abundant macrofauna and its excretory products play a primary role in benthic nutrient regeneration, are well balanced in their stoichiometric ratios, and thus act as a major factor to support primary production within the intertidal zone.

10

20 Jan 17 Feb 17 Mar 15 Apr 16 May 30 May 14 Jun 12 Jul 10 Aug 7 Sep 29 Sep 30 Oct 27 Nov 26 Dec 24 Jan 22 Feb 21 Mar 17 Apr

PO43−-P, mmol m−2 day−1

20 Jan 17 Feb 17 Mar 15 Apr 16 May 30 May 14 Jun 12 Jul 10 Aug 7 Sep 29 Sep 30 Oct 27 Nov 26 Dec 24 Jan 22 Feb 21 Mar 17 Apr

0

13

1996

1995 Time, month

Figure 2. Magnitude and temporal scaling of ammonium (NH4 + -N), phosphate (PO4 3− -P), and silicate [Si(OH)4 -Si] excretion by Ruditapes philippinarum and Musculista senhousia in a field community.

presence of bivalves (17,24,36). The temporal scaling of bivalve nutrient excretion showed a marked seasonal pattern of large variations of nutrient flux, up to ca. 10-fold (R. philppinarum) and 20-fold (M. senhousia) between March–April 1995 and September 7, 1995, and a progressive decrease from late summer through winter. This approach may involve some limitations, such as the effect of differences between the bivalve performance in controlled laboratory experiments and that in the field and a relative approximation in adopting different excretion rates at temperatures other than those actually employed in the laboratory experiments (29). However, it indicates the strong influence of animal distribution on the magnitude and temporal scaling of biogenic nutrient regeneration due to bivalve excretion. The great potential of this biogenic source of nutrients in cycling biophilic elements can also be highlighted

4. Giesen, W.B.J.T., van Katwijk, M.M., and den Hartog, C. (1990). Eelgrass condition and turbidity in the Dutch Wadden Sea. Aquat. Bot. 37: 71–85. 5. Agust´ı, S. et al. (1994). Light harvesting among photosynthetic organisms. Funct. Ecol. 8: 273–279. 6. Justic, D., Rabalais, N.N., and Turner, T. (1995). Stoichiometric nutrient balance and origin of coastal eutrophication. Mar. Poll. Bull. 30: 41–46. 7. Valiela, I. et al. (1997). Macroalgal blooms in shallow estuaries: controls and ecophysiological and ecosystem consequences. Limnol. Oceanogr. 5: 1105–1118. 8. Park, Y.C. and Carpenter, E.J. (1987). Ammonium regeneration and biomass of macrozooplankton and Ctenophores in Great South Bay, New York. Estuaries 4: 316–320. 9. Wen, Y.H. and Peters, R.H. (1994). Empirical models of phosphorus and nitrogen excretion rates by zooplankton. Limnol. Oceanogr. 39: 1669–1679. 10. Harrison, W.G. et al. (1992). Nitrogen dynamics at the VERTEX time-series site. Deep-Sea Res. 39: 1535–1552. 11. Rowe, G.T., Clifford, C.H., Smith, K.L., and Hamilton, P.L. (1975). Benthic nutrient regeneration and its coupling to primary productivity in coastal waters. Nature 225: 215–217. 12. Nixon, S.W. (1981). Remineralization and nutrient cycling in coastal marine ecosystems. In: Nutrient Enrichment in Estuaries. B. Nelson and L.E. Cronbin (Eds.). Humana Press, Clifton, NJ, pp. 111–138. 13. Klump, J.V. and Martens, C.S. (1983). Benthic nitrogen regeneration. In: Nitrogen in the Marine Environment. E.J. Carpenter and D.G. Capone (Eds.). Academic Press, New York, pp. 411–457. 14. Jordan, T.E. and Valiela, I. (1982). A nitrogen budget of the ribbed mussel, Geukensia demissa, and its significance in

14

BREAKWATERS nitrogen flow in a New England salt marsh. Limnol. Oceanogr. 27: 75–90.

15. Murphy, R.C. and Kremer, J.N. (1985). Bivalve contribution to benthic metabolism in a California lagoon. Estuaries 8: 330–341. 16. Prins, T.C. and Smaal, A.C. (1994). The role of the blue mussel Mytilus edulis in the cycling of nutrients in Oosterschelde estuary (the Netherlands). Hydrobiol. 282/283: 413–429. 17. Doering, P.H., Kelly, J.R., Oviatt, C.A., and Sowers, T. (1987). Effect of the hard clam Mercenaria mercenaria on benthic fluxes of inorganic nutrients and gases. Mar. Biol. 94: 377–383. 18. Nakamura, M., Yamamuro, M., Ishikawa, M., and Nishimura, H. (1988). Role of the bivalve Corbicula japonica in the nitrogen cycle in a mesohaline lagoon. Mar. Biol. 99: 369–374. 19. Kiibus, M. and Kautsky, N. (1996). Respiration, nutrient excretion and filtration rate of tropical freshwater mussels and their contribution to production and energy flow in Lake Kariba, Zimbabwe. Hydrobiol. 331: 25–32. 20. Yamada, H. and Kayama, M. (1987). Liberation of nitrogenous compounds from bottom sediments and effect of bioturbation by small bivalve, Theora lata (Hinds). Estuar. Coast. Shelf Sci. 24: 539–555. 21. G´omez-Parra, A. and Forja, J.M. (1993). Benthic fluxes in Cadiz Bay (SW Spain). Hydrobiol. 252: 23–34. 22. Yamamuro, M. and Koike, I. (1993). Nitrogen metabolism of the filter-feeding bivalve Corbicula japonica and its significance in primary production of a brackish lake in Japan. Limnol. Oceanogr. 35: 997–1007. 23. Dame, R.F., Zingmark, R.G., and Haskin, E. (1984). Oyster reefs as processors of estuarine materials. J. Exp. Mar. Biol. Ecol. 83: 239–247. 24. Asmus, H., Asmus, R.M., and Reise, K. (1990). Exchange processes in an intertidal mussel bed: a Sylt-flume study in the Wadden Sea. Berichte Biolog. Anstalt Helgol. 6: 78. 25. Prins, T.C. and Smaal, A.C. (1990). Benthic-pelagic coupling: the release of inorganic nutrients by an intertidal bed of Mytilus edulis. In: Trophic relationships in the marine environment. Proc. 24th Europ. Mar. Biol. Symp., Aberdeen Univ. Press, pp. 89–103. 26. Asmus, R.M., Asmus, H., Wille, A., Zubillaga, G.F., and Reise, K. (1994). Complementary oxygen and nutrient fluxes in seagrass beds and mussels banks? In: Changes in Fluxes in Estuaries: Implications from Science to Management. K.R. Dyer and R.J. Orth (Eds.). Olsen & Olsen, Fredensborg, pp. 227–238. 27. Bayne, B.L. and Scullard, C. (1977). Rates of nitrogen excretion by species of Mytilus (Bivalvia: Mollusca). J. Mar. Biol. Ass. U.K. 57: 355–369. ¨ 28. Schluter, L. and Josefsen, S.B. (1994). Annual variation in condition, respiration and remineralisation of Mytilus edulis L. in the Sound, Denmark. Helgol. Meeres. 48: 419–430. 29. Magni, P., Montani, S., Takada, C., and Tsutsumi, H. (2000). Temporal scaling and relevance of bivalve nutrient excretion on a tidal flat of the Seto Inland Sea, Japan. Mar. Ecol. Progr. Ser. 198: 139–155. 30. Heip, C.H.R. et al. (1995). Production and consumption of biological particles in temperate tidal estuaries. Oceanogr. Mar. Biol. Ann. Rev. 33: 1–149. 31. Magni, P. and Montani, S. (1997). Development of benthic microalgal assemblages on a tidal flat in the Seto Inland Sea, Japan: effects of environmental variability. La mer 35: 109–120.

32. Magni, P. and Montani, S. (1998). Responses of intertidal and subtidal communities of the macrobenthos to organic load and oxygen depletion in the Seto Inland Sea, Japan. J. Rech. Oc´eanogr. 23: 47–56. 33. Magni, P. and Montani, S. (2000). Physical and chemical variability in the lower intertidal zone of an estuary in the Seto Inland Sea, Japan: seasonal patterns of dissolved and particulate compounds. Hydrobiol. 432: 9–23. 34. Dame, R.F., Wolaver, T.G., and Libes, S.M. (1985). The summer uptake and release of nitrogen by an intertidal oyster reef. Neth. J. Sea Res. 19: 265–268. 35. Dame, R.F. et al. (1991). The influence of mussel beds on nutrients in the western Wadden Sea and Eastern Scheldt estuaries. Estuaries 14: 130–138. 36. Bartoli, M. et al. (2001). Impact of Tapes philippinarum on nutrient dynamics and benthic respiration in the Sacca di Goro. Hydrobiol. 455: 203–212. 37. Kuwae, T., Hosokawa, Y., and Eguchi, N. (1998). Dissolved inorganic nitrogen cycling in Banzu intertidal sand-flat, Japan. Mangroves Salt Marshes 2: 167–175. 38. Matsukawa, Y., Sato, Y., and Sasaki, K. (1987). Benthic flux of nutrient salts on an intertidal flat. Nippon Suisan Gakkaishi 53: 985–989. 39. Takayanagi, K. and Yamada, H. (1999). Effects of benthic flux on short term variations of nutrients in Aburatsubo Bay. J. Oceanogr. 55: 463–469. 40. Yamamoto, T., Matsuda, O., Hashimoto, T., Imose, H., and Kitamura, T. (1998). Estimation of benthic fluxes of dissolved inorganic nitrogen and phosphorus from sediments of the Seto Inland Sea. Umi to Kenkyu (Oceanogr. Soc. Japan) 7: 151–158 (in Japanese). 41. Peterson, B.J. and Heck, K.L. Jr. (2001). Positive interaction between suspension-feeding bivalves and seagrass—a facultative mutualism. Mar. Ecol. Progr. Ser. 213: 143–155.

BREAKWATERS STEFANO PAGLIARA PIETRO CHIAVACCINI Universita` di Pisa Pisa, Italy

Breakwaters are coastal structures used to protect harbor and shore areas by dissipating and reflecting wave energy. They are built to — reduce wave disturbance in coastal and harbor areas and preserve related activities; — protect ships and boats from wave forces; — when located near shore, in the same direction as the coastline, they can stabilize the coastline, modifying cross-shore and long-shore sediment transport. The choice of the type of structure depends on the availability of materials used, the characteristics of the incident wave, the bottom morphology, the geotechnical parameters of the soil, and the necessity of obtaining a flexible or rigid structure. Breakwaters can be classified as rubble-mound structures, vertical breakwaters, and floating breakwaters.

BREAKWATERS

RUBBLE-MOUND STRUCTURES The typical cross section of a rubble-mound breakwater is sketched in Fig. 1. It consists of different layers of stones. The center core is made up of quarry run. The external layer (armor) consists of large armor units, that can be either rock or specially designed concrete units (cubes, tetrapods, dolos). The breakwater crest is generally 1–2 m over the still water level (SWL). The crest width should be large enough to allow transport and installation of material during construction and when a repair is made (1). Because of the relative dimensions of the units of the armor and those of the core, in some cases, it is necessary to build the breakwater as a filter of three or four layers (underlayers), so that the finer material of the core cannot be removed by the waves through the voids of the armor layer. To prevent removal of finer material, the filter must satisfy the following relations: D15 (upper layer) < 4 ÷ 5D85 (lower layer)

(1)

D15 (upper layer) < 20 ÷ 25D15 (lower layer)

(2)

Armor Stability. The stability formulas are based on experiments carried out on hydraulic models. One of the most used stability formulas is Hudson’s (3) determined for a nonovertopping structure: H = (K cot α)1/3 D2n50 where

Stability The rubble-mound breakwater causes the dissipation of wave energy by generating eddies due to the breaking. The voids and the roughness of the structural material, as well as the permeability of the structure, are very important in the dissipation process. The wave energy entering through the structure creates shear stresses that can move the masses causing loss of stability.

Seaward

Crest width Breakwater crest

Crown wall

(3)

H = characteristic height of the wave (Hs to H1/10 ); Dn50 = equivalent cube length of median rock; α = slope angle;  = (ρs /ρw − 1) where ρs and ρw are rock density and water density, respectively; K = stability coefficient (Tables 1 and 2).

The damage D represents the measure of the modification of the structure’s profile under wave action. The damage can be defined by counting the number of rocks moved or by measuring the variation of the armor layer Table 1. Values of the Stability Coefficient K for H = Hs a Damage D 0–5%

where D15 = nominal size that is exceeded by the 85% of the sample D85 = nominal size that is exceeded by the 15% of the sample A toe filter is necessary if the breakwater is built on erodible material. The toe filter prevents breaking waves from removing material from the base of the structure. If the breakwater is located in shallow water, the filter toe is exposed to extreme wave action. To avoid, or just limit, wave overtopping, it is possible to use a concrete structure (crown wall) located over the crest (Fig. 1). When the breakwater is small and not high, it is possible to avoid using a center core. This kind of structure, of single sized stones, is called a ‘‘reef breakwater,’’ and it is normally used for small submerged breakwaters (2).

15

Stone Shape

Placement

Breaking Waves

Nonbreaking Waves

Smooth, rounded Rough, angular Rough, angular

Random Random Special

2.1 3.5 4.8

2.4 4.0 5.5

a

Slope 1.5 ≤ cot α ≤ 3.0.

Table 2. Values of the Stability Coefficient K for H = H1/10 Damage D 0–5% Breaking Waves Non Breaking Waves Stone shape Placement Trunk Smooth, rounded Rough, angular Rough, angular Tetrapods a b

Head

Trunk

Head

Random

1.2

1.1

2.4

1.9

Random

2.0

1.3a –1.9b

4.0

2.3a –3.2b

Special

5.8

5.3

7.0

6.4

Random

7.0

3.5a –5b

8.0

4.0a –6.0b

cot α = 3. cot α = 1.5.

Landward

SWL

r

Berm

mo

Ar

Underlayer

TOE filter core Figure 1. Typical section of a rubble-mound breakwater.

16

BREAKWATERS

area (eroded area A of the damaged section). For this second case, Broderick (4) introduced a parameter (relative eroded area) defined as S=

A D2n50

(4)

where Dn50 is the nominal diameter, corresponding to 50% of the weight of the sample. The damage can be considered the number of masses of dimension equal to Dn50 eroded in a strip of section of the same length. Zero damage means that there is nominally no removal of the armor units from the breakwater face. The K value of Hudson’s formula is different for the trunk and the head of the structure. The stones will be less stable on the head than on the trunk. In this case, K must be decreased by about 20%. Van der Meer (5) derives expressions that include some additional parameters for an incident wave: Hs −0.5 = 6.2S0.2 P0.18 Nz−0.1 ξm Dn50 plunging waves ξm < ξcm Hs P = 1.0S0.2 P−0.13 Nz−0.1 (cot α)0.5 ξm Dn50 surging waves ξm > ξcm ξm =

−0.5 sm

(5)

(6)

tan α

ξmc = [6.2P0.31 (tan α)0.5 ]1/(P+0.5) where

S = relative eroded area (normally equal to 2); P = notional permeability; Nz = number of waves; sm = wave steepness sm = Hs /Lom ; Lom = deepwater wavelength corresponding to the mean period.

For a homogeneous structure (no core, no filter, and stones of the same size), P = 0.6; a rock armor layer with a permeable core gives P = 0.5; an armor layer with filter on a permeable core gives P = 0.4. For a breakwater with an impermeable core, P = 0.1. For overtopped and low crested structures, Van der Meer suggests multiplying Dn50 by a reduction factor fi defined by


Rc sop (7) fi = 1.25 − 4.8 Hs 2π Rc is the freeboard, and sop = Hs /Lop (Lop is the deep water wavelength referred to the peak  Expression (7)
period). Rc sop < 0.052. can be used in the range 0 < Hs 2π For submerged breakwaters, the following expression can be used (6): hc = (2.1 + 0.1S) exp(0.14Ns∗ ) h where h = water depth; hc = height of the structure from the base; S = relative eroded area; Hs −1/3 Ns∗ = sp = spectral stability number. Dn50

(8)

Run Up and Overtopping Run up is a phenomenon in which the incident crest wave runs up along a sloping structure to a level higher then the original wave crest. Together with overtopping, it plays, a very important role in the design of a rubble-mound structure because it depends on the characteristics of the structure (slope roughness, berm length, permeability). Run up is expressed by Ru,x% that represents the level reached by the wave exceeded in x% of the cases by the incident wave. The run up level is referred to the SWL. For rubble-mound structures, Van der Meer’s (6) formula is used: Ru,x% = aξm , Hs Ru,x% c = bξm , Hs

ξm < 1.5

(9)

ξm > 1.5

(10)

These formulas are valid for breakwaters that have an impermeable or almost impermeable core (P < 0.1). If the breakwaters have a permeable core (0.1 < P < 0.4) Equations 9 and 10 become Ru,x% =d Hs

(11)

It is usual in breakwater design to consider that x% = 2; this means that Ru,2% is the run up exceeded by 2% of the waves. In this case, the values of the parameters of Equations (9,10), and 11 are a = 0.96, b = 1.17, c = 0.46, and d = 1.97. ξm is the breaker parameter for deep water, correspond−0.5 tan α where the symbols ing to the mean period (ξm = sm are explained in Equations 5 and 6). In a low crest elevation, overtopping is allowed. Overtopping is the quantity of water passing over the crest of a structure per unit time, and it has the same dimensions of a discharge Q(m3 /s), often expressed for unit length q[m3 /(sm)]. A knowledge of overtopping is important in defining the necessary protection of the splash area and in assessing the risk to people or installations behind the breakwater. The amount of overtopping varies considerably from wave to wave; the overtopping discharge changes in time and space, and the greatest quantity is due to a small number of the incident waves. Wave overtopping for an impermeable rock armored slope structure with a crown wall can be expressed by the equation of Bradbury and Allsop (7), using the parameters of Aminti and Franco (8): 


−b Rc 2 som q =a (12) gHs Tom Hs 2π where Som = deepwater wave steepness, based on mean period; Hs = significant wave height; Rc = crest freeboard relative to SWL in m; Tom = deepwater wave mean period; a, b = parameters as specified in Table 3. G is the width (seaward) of the armor crest till the crown wall, and α is the slope of the armor layer.

BREAKWATERS Table 3. Coefficients for Equation 15 from Experimental Results Armor Units

Cotα

Rock

2 2 2 1.33 1.33 1.33 2 2 2 1.33 1.33 1.33

Tetrapods

G/Hs

a

b −8

17 × 10 19 × 10−8 2.3 × 10−8 5.0 × 10−8 6.8 × 10−8 3.1 × 10−8 1.9 × 10−8 1.3 × 10−8 1.1 × 10−8 5.6 × 10−8 1.7 × 10−8 0.92 × 10−8

1.10 1.85 2.60 1.10 1.85 2.60 1.10 1.65 2.6 1.10 1.85 2.60

2.41 2.30 2.68 3.10 2.65 2.69 3.08 3.80 2.86 2.81 3.02 2.98

transmitted to incident characteristic wave height or the ratio of the square of transmitted mean energy to incident mean wave energy: Kt =

Hs Rc

3

Hs2 Ac B cot α

(13)

where Ac = level of the berm from SWL; B = the width of the berm; Rc = the level of the crest of the crown wall from SWL; α = slope of armor. Wave Reflection Each coastal structure causes a wave reflection. Reflection plays a very important role because of the interaction between reflected and incident waves that can create a very confused sea, increasing the wave steepness. It is a problem especially at the entrance of an harbor because the steepness makes ship and boat maneuver very difficult. Besides, strong reflection increases the erosive force in front of the structure. Rubble-mound breakwaters, which are permeable, rough, and sloping structures and structure of limited crest level, absorb a significant portion of the wave energy. For these structures, the reflection coefficient is small. For nonovertopped structures, that have a theoretical permeability P, we can use the following equation (10): Kr = 0.071P

−0.082

(cot α)

−0.62

−0.46 Sop

(14)

where Kr is the ratio of the reflected wave height and the incident wave height. Wave Transmission When energy passes over and through a breakwater, there is a wave transmission. The wave action in the landward side of the structure is smaller than in the seaward side. A wave is transmitted when a considerable amount of water overtops the structure and when the breakwater is very permeable and the wave period is relatively long. We define the coefficient of transmission as the ratio of




Est Es

0.5 (15)


 Hs Rc − 0.24 +b Kt = 0.031 Dn50 Dn50

For rock armored permeable slopes, that have a theoretical permeability P = 0.4 and a berm in front of a crown wall, we can use the Pedersen and Burcharth formula (9):


Hst = Hs

For rock armored, low crested, submerged and reef breakwaters, we can use the Van der Meer and d’Angremond formula (11):

where

qTom = 3.2 × 10−5 L2om

17

(16)


Hs B 1.84 − 0.0017 Dn50 Dn50 + 0.51 for a conventional structure, Hs b = −2.6sop − 0.05 + 0.85 for a reef type Dn50 structure, Hs = significant wave height; som = deepwater wave steepness, based on peak period; Rc = crest freeboard relative to SWL, negative for submerged breakwaters; B = width of crest; Dn50 = median of nominal diameter of rock for design conditions. b = −5.42sop + 0.0323

For conventional structures, Kt has a maximum of 0.75 and a minimum of 0.075, and for reef type structures, Kt varies between 0.15 and 0.6. This formula can be used in the following range: 1
30fold variability between layers and months (Fig. 2). Ammonium varied from 75.1 (0–0.5 cm, January 1995) to

Jan

PAOLO MAGNI

SEASONALITY OF POREWATER NUTRIENT CONCENTRATIONS

Feb

SEASONAL COUPLING BETWEEN INTERTIDAL MACROFAUNA AND SEDIMENT COLUMN POREWATER NUTRIENT CONCENTRATIONS

still a noticeable lack of knowledge about the relationship between macrofauna and the temporal distribution and spatial variability of nutrients in sediments. Some works have conducted a seasonal study of porewater chemistry focusing on nitrogen organic compounds, such as dissolved free amino acids (13), and ammonium profiles and production (13–15). These studies have indicated that temperature has a pronounced effect on the porewater ammonium production rate and seasonal variation. In addition to the effect of environmental parameters that exhibit seasonal patterns and mineralization processes in sediments by bacteria, macrofauna also contribute to the total benthic metabolism by feeding, assimilation, and respiration. Recently, we have shown that the excretory activity of macrofauna strongly influences the magnitude and seasonal variability of the biogenic upward flux of nutrients (16; TEMPORAL SCALING OF BENTHIC NUTRIENT REGENERATION IN BIVALVE-DOMINATED TIDAL FLAT). However, field studies on the relationship between porewater nutrient concentrations and macrofaunal communities come often from isolated surveys (17) or from transplantation/manipulation experiments (8,9). In particular, evidence of a coupling between the seasonal variability of nutrient concentrations in porewater and macrofauna-influenced upward flux of nutrients is still lacking.

Temperature, °C

the internet through real-time observations. The goal of this project is to put in place the infrastructure needed to simplify sensor deployment and data acquisition to allow information access by scientific researchers, educators and the public. This is an important contribution to GLERL’s leadership in supporting and promoting observation system development among Great Lakes universities and non-governmental organizations. The environmental observatory consists of an offshore buoy connected to a hub that receives data from various environmental sensors such as an acoustic doppler current profiler. The data are then sent through a wireless link to an onshore receiver connected to the internet.

73

’96

Figure 1. Seasonal variation of sediment temperature.

SEASONAL COUPLING NH4+-N

600 500 400 300 200

17 Apr

22 Feb

21 Mar

24 Jan

26 Dec

30 Oct

27 Nov

3 Oct

7 Sep

12 Jul

10 Aug

14 Jun

16 May

1 Mar

12 Apr

6 Feb

100

PO43−-P

µM

0–0.5 0.5–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10

30 25 20 15 10

17 Apr

22 Feb

21 Mar

24 Jan

26 Dec

30 Oct

27 Nov

3 Oct

7 Sep

12 Jul

10 Aug

14 Jun

16 May

1 Mar

12 Apr

Si(OH)4-Si

µM

0–0.5 0.5–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10

300 250 200 150 100

1995

908 µM (0–0.5 cm, 30 October 1995), phosphate from 0.9 (0–0.5 cm, January 1995) to 36.9 µM (4–5 cm, September 1995), and silicate from 17.1 (0–0.5 cm, February 1996) to 379 µM (5–6 cm, 30 September 1995). The spatial and temporal distribution of ammonium, phosphate, and silicate concentrations were consistent with each other. They were lowest in winter, progressively increased through spring and summer in the uppermost layers, and were highest between September and October 1995; a major increase occurred in intermediate layers (i.e., between 3 and 8 cm). Subsequently, minor but noticeable peaks of ammonium and phosphate concentrations were also found in March 1996, up to 518 and 32.7 µM at 6–7 cm, respectively. For each sampling occasion and nutrient species, we summed the concentrations measured in each layer of the sediment column to be representative of an alllayer monthly pool expressed on a square meter basis.

Time, month

17 Apr

22 Feb

21 Mar

24 Jan

26 Dec

30 Oct

27 Nov

3 Oct

7 Sep

12 Jul

10 Aug

14 Jun

16 May

1 Mar

12 Apr

50 13 Jan

Sediment depth, cm

(c)

6 Feb

5 13 Jan

Sediment depth, cm

(b)

Figure 2. Spatial and seasonal variation of porewater ammonium (NH4 + -N) (a), phosphate (PO4 3− -P) (b), and silicate [Si(OH)4 -Si] (c) concentrations.

µM

0–0.5 0.5–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10 13 Jan

Sediment depth, cm

(a)

6 Feb

74

1996

This was obtained by calculating the sediment porosity of each layer from the water content (weight loss on drying at 105◦ C for 20 h), assuming the bulk density of sediment particles as 2.5 g cm−3 . Each volume of porewater was subsequently multiplied by the relevant nutrient concentrations, which were finally expressed as areal depth-integrated values (mmol m−2 ). Ammonium, phosphate, and silicate concentrations showed a strong correlation with each other (Fig. 3). These results suggest that similar and/or coincident processes may govern the spatial and seasonal variability of major inorganic forms of N, P, and Si in sediment porewater. We were thus interested in assessing the existence of common environmental factors (i.e., temperature) and/or biological (i.e., macrofauna-influenced) processes that influence the variability of ammonium, phosphate, and silicate in porewater. Ammonium and silicate were highly correlated with temperature (Fig. 4). This could

SEASONAL COUPLING

35

r2 = 0.600 (p < 0.001)

25

Temperature, °C

Porew. NH4+-N, mmol m−2

30

20 15 10

30 25 20 15 10 5

5

0 0.0

0.3

0.6

0.9

1.2

Porewater PO43−-P, mmol m−2 r2

5 10 15 20 25 Porewater NH4+-N, mmol m−2

30

35

= 0.853 (p < 0.001)

Temperature, °C

30 Porew. NH4+-N, mmol m−2

r2 = 0.684 (p < 0.001)

0

0

25 20 15

30 25 20 15 10 r2 = 0.331 (p < 0.05)

5

10

0

5

0.0 3 6 9 12 Porewater Si(OH)4-Si, mmol m−2

15

0.6

0.9

1.2

35 Temperature, °C

0

0.3

Porewater PO43−-P, mmol m−2

0

Porew. Si(OH)4-Si, mmol m−2

75

15 r2 = 0.460 (p < 0.01) 12 9

30 25 20 15 10 r2 = 0.679 (p < 0.001)

5

6

0 0

3

3

6

9

12

15

Porewater Si(OH)4-Si, mmol m−2

0 0.0

0.3

0.6

0.9

1.2

Porewater PO43−-P, mmol m−2 Figure 3. Relationship between porewater ammonium (NH4 + -N), phosphate (PO4 3− -P), and silicate [Si(OH)4 -Si] concentrations in the uppermost 10 cm of sediments.

be consistent with previous studies that have focused on the distribution of ammonium and found that it was strongly dependent on seasonal variations in temperature (13,24,25), whereas little combined information is available on the distribution of ammonium, phosphate, and silicate in the sediment column and relevant influencing factors. In our study, for instance, the correlation between temperature and phosphate was significant, yet rather weak. We then tested the hypothesis that the seasonal variation of all three nutrient species could be related to the activity of in situ benthic macrofauna. COUPLING WITH THE EXCRETORY ACTIVITY OF DOMINANT BIVALVES We based our considerations on previous physiological measurements (LABORATORY EXPERIMENTS ON BIVALVE

Figure 4. Relationship between porewater ammonium (NH4 + -N), phosphate (PO4 3− -P), and silicate [Si(OH)4 -Si] concentrations in the uppermost 10 cm sediments and temperature.

EXCRETION RATES OF NUTRIENTS) and scaling up (TEMPORAL SCALING OF BENTHIC NUTRIENT REGENERATION IN BIVALVEDOMINATED TIDAL FLAT) of nutrient excretion rates by two bivalve species dominant on this flat, Ruditapes philippinarum and Musculista senhousia. The plots of bivalve excretion rates of ammonium, phosphate, and silicate versus their relevant pool in the porewater showed a highly significant positive correlation in all cases (Fig. 5). These results suggest the importance of the physiological activity of the benthos on the seasonal variability of porewater chemistry. We conclude that the seasonal patterns of nutrient concentrations in the porewater are strongly coupled with the extent of biogenic regeneration of nutrients due to bivalve excretory activity. This study thus provides evidence of the influence of biological processes on the seasonal patterns of porewater nutrient distribution, suggesting a major role of macrofauna not only at the sediment–water interface, but also in the year-round processes that occur within sediments.

SEASONAL COUPLING

Porew. NH4+-N, mmol m−2

76

Mytilus edulis. In: Trophic Relationships in the Marine Environment. Proc. 24th Europ. Mar. Biol. Symp. Aberdeen, Univ. Press, pp. 89–103.

30 25

7. Yamamuro, M. and Koike, I. (1993). Nitrogen metabolism of the filter-feeding bivalve Corbicula japonica and its significance in primary production of a brackish lake in Japan. Limnol. Oceanogr. 35: 997–1007.

20 15 10 5 0 0

Porew. PO43−-P, mmol m−2

8. Reusch, T.B.H. and Williams, S.L. (1998). Variable responses of native eelgrass Zostera marina to a non-indigenous bivalve Musculista senhousia. Oecologia 113: 428–441.

y = 0.34x + 10.3 r 2 = 0.584 (p < 0.001)

1.2

10 20 30 40 50 NH4+-N excretion, mmol m−2 day−1

60

9. Peterson, B.J. and Heck, K.L., Jr. (2001). Positive interaction between suspension-feeding bivalves and seagrass—a facultative mutualism. Mar. Ecol. Progr. Ser. 213: 143–155.

y = 0.10x + 0.15 r 2 = 0.719 (p < 0.001)

1.0

10. Uthike, S. (2001). Interaction between sediment-feeders and microalgae on coral reefs: grazing losses versus production enhancement. Mar. Ecol. Progr. Ser. 210: 125–138.

0.8 0.6

11. Uthike, S. (1999). Sediment bioturbation and impact of feeding activity of Holothuria (Halodeima) atra and Stichopus chloronotus, two sediment feeding holothurians, at Lizard Island, Great Barrier Reef. Bull. Mar. Sci. 64: 129–141.

0.4 0.2

12. Christensen, B., Vedel, A., and Kristensen, E. (2000). Carbon and nitrogen fluxes in sediments inhabited by suspension-feeding (Nereis diversicolor) and non-suspensionfeeding (N. virens) polychaetes. Mar. Ecol. Prog. Ser. 192: 203–217.

0.0 0

2

4

6

8

Porew. Si(OH)4-Si, mmol m−2

PO43−-P excretion, mmol m−2 day−1 15

13. Land´en, A. and Hall, P.O.J. (1998). Seasonal variation of dissolved and adsorbed amino acids and ammonium in a nearshore marine sediment. Mar. Ecol. Prog. Ser. 170: 67–84.

y = 0.24x + 3.2 r 2 = 0.495 (p < 0.01)

12 9

14. Blackburn, T.H. (1980). Seasonal variation in the rate of organic-N mineralization in oxic marine sediments. In: Biogechimie de la mati`ere organique a` l’interface eau-sediment ´ marine. Edition du CNRS, Paris, pp. 173–183.

6 3

15. Laima, M.J.C. (1992). Extraction and seasonal variation of NH4 + pools in different types of coastal marine sediments. Mar. Ecol. Prog. Ser. 82: 75–84.

0 0

10

20

Si(OH)4-Si excretion, mmol

30 m−2

40 day−1 +

Figure 5. Relationship between porewater ammonium (NH4 -N), phosphate (PO4 3− -P), and silicate [Si(OH)4 -Si] concentrations in the uppermost 10 cm of sediments and bivalve-influenced upward flux of those nutrients.

BIBLIOGRAPHY 1. Jordan, T.E. and Valiela, I. (1982). A nitrogen budget of the ribbed mussel, Geukensia demissa, and its significance in nitrogen flow in a New England salt marsh. Limnol. Oceanogr. 27: 75–90. 2. Dame, R.F., Zingmark, R.G., and Haskin, E. (1984). Oyster reefs as processors of estuarine materials. J. Exp. Mar. Biol. Ecol. 83: 239–247. 3. Murphy, R.C. and Kremer, J.N. (1985). Bivalve contribution to benthic metabolism in a California lagoon. Estuaries 8: 330–341. 4. Boucher, G. and Boucher-Rodoni, R. (1988). In situ measurements of respiratory metabolism and nitrogen fluxes at the interface of oyster beds. Mar. Ecol. Prog. Ser. 44: 229–238. 5. Nakamura, M., Yamamuro, M., Ishikawa, M., and Nishimura, H. (1988). Role of the bivalve Corbicula japonica in the nitrogen cycle in a mesohaline lagoon. Mar. Biol. 99: 369–374. 6. Prins, T.C. and Smaal, A.C. (1990). Benthic-pelagic coupling: the release of inorganic nutrients by an intertidal bed of

16. Magni, P., Montani, S., Takada, C., and Tsutsumi, H. (2000). Temporal scaling and relevance of bivalve nutrient excretion on a tidal flat of the Seto Inland Sea, Japan. Mar. Ecol. Progr. Ser. 198: 139–155. 17. Lomstein, B.A., Blackburn, T.H., and Henriksen, K. (1989). Aspects of nitrogen and carbon cycling in the northern Bering Shelf sediment: I. The significance of urea turnover in the mineralization of ammonium ion. Mar. Ecol. Prog. Ser. 57: 237–248. 18. Magni, P. (1998). A multidisciplinary study on the dynamics of biophilic elements (C, N, P, Si) in a tidal estuary of the Seto Inland Sea, Japan: physico-chemical variability and macrozoobenthic communities. Ph.D. Thesis, The United Graduate School of Ehime University, Japan, p. 258. 19. Montani, S. et al. (1998). The effect of a tidal cycle on the dynamics of nutrients in a tidal estuary in the Seto Inland Sea, Japan. J. Oceanogr. 54: 65–76. 20. Magni, P., Montani, S., and Tada, K. (2002). Semidiurnal dynamics of salinity, nutrients and suspended particulate matter in an estuary in the Seto Inland Sea, Japan, during a spring tide cycle. J. Oceanogr. 58: 389–402. 21. Magni, P. and Montani, S. (1997). Development of benthic microalgal assemblages on an intertidal flat in the Seto Inland Sea, Japan: effects of environmental variability. La mer. 35: 137–148. 22. Magni, P. and Montani, S. (1998). Responses of intertidal and subtidal communities of the macrobenthos to organic

MAPPING THE SEA FLOOR OF THE HISTORIC AREA REMEDIATION SITE (HARS) OFFSHORE OF NEW YORK CITY

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load and oxygen depletion in the Seto Inland Sea, Japan. J. Rech. Oc´eanogr. 23: 47–56. 23. Magni, P. and Montani, S. (2000). Physical and chemical variability in the lower intertidal zone of an estuary in the Seto Inland Sea, Japan: seasonal patterns of dissolved and particulate compounds. Hydrobiol. 432: 9–23. 24. Blackburn, T.H. and Henriksen, K. (1983). Nitrogen cycling in different types of sediments from Danish waters. Limnol. Oceanogr. 28: 477–493. 25. Klump, J.V. and Martens, C.S. (1989). Seasonality of nutrient regeneration in an organic-rich coastal sediment: kinetic modeling of changing pore-water nutrient and sulfate distribution. Limnol. Oceanogr. 34: 559–577.

MAPPING THE SEA FLOOR OF THE HISTORIC AREA REMEDIATION SITE (HARS) OFFSHORE OF NEW YORK CITY BRADFORD BUTMAN U.S. Geological Survey

Figure 1. Map showing the area offshore of New York and New Jersey that has been used for the disposal of dredged materials and other wastes since the late 1800’s. The Historic Area Remediation Site (HARS) is outlined in red.

Repeated surveys using a multibeam mapping system document changes in the topography and distribution of sediments on the sea floor caused by placement of dredged material, remedial capping, and natural processes. INTRODUCTION The area offshore of New York City has been used for the disposal of dredged material for over a century. The area has also been used for the disposal of other materials such as acid waste, industrial waste, municipal sewage sludge, cellar dirt, and wood. Between 1976 and 1995, the New York Bight Dredged Material Disposal Site, also known as the Mud Dump Site (MDS), received on average about 6 million cubic yards of dredged material annually. In September 1997 the MDS was closed as a disposal site, and it and the surrounding area were designated as the Historic Area Remediation Site (HARS) (Figs. 1 and 2). The sea floor of the HARS, approximately 9 square nautical miles in area, currently is being remediated by placing a minimum 1-m-thick cap of clean dredged material on top of the surficial sediments that are contaminated from previous disposal of dredged and other materials. The U.S. Geological Survey (USGS) is working cooperatively with the U.S. Army Corps of Engineers (USACE) to map the sea floor geology of the HARS and changes in the characteristics of the surficial sediments over time. HIGH-RESOLUTION SURVEYS OF THE SEA FLOOR OF THE HARS Surveys of the HARS were conducted in November 1996 (prior to the closing of the Mud Dump Site), November 1998 (during early remediation of the HARS),

This article is a US Government work and, as such, is in the public domain in the United States of America.

Figure 2. Shaded relief image of the Historic Area Remediation Site (HARS) in April 2000 showing the Primary Remediation Area (PRA, divided into nine cells), the no discharge zone (ND), the former Mud Dump Site (MDS), and the discontinued Cellar Dirt Disposal Site (CDDS). Companion images are shown in Figures 4 and 5. See text for a description of this image and major features. Bathymetric contour interval is 5 m (red lines).

and April 2000 (during continued remediation of the HARS) using a Simrad EM1000 multibeam mapping system (Fig. 3). Survey lines were run approximately 100 m apart to provide full coverage of the sea floor. The EM1000 measured the depth of water (to an accuracy of

78

MAPPING THE SEA FLOOR OF THE HISTORIC AREA REMEDIATION SITE (HARS) OFFSHORE OF NEW YORK CITY

Figure 3. High-resolution multibeam mapping systems use sound from an array of transducers to measure water depth and sediment characteristics of the sea floor. The horizontal resolution of the maps is a few meters, providing an image of the sea floor topography and sediment properties somewhat comparable to an aerial photograph.

about 30 cm) as well as the intensity of sound reflected from the sea floor, which is referred to as backscatter intensity. High backscatter intensity generally indicates the presence of rocks and coarse-grained sediments, while low backscatter intensity indicates the presence of finer grained sediments. Direct observations using bottom photographs, video, and grab samples are needed to verify interpretations of the sea floor geology based on backscatter intensity. IMAGES OF THE HARS SEA FLOOR In this fact sheet, the topography and backscatter intensity data measured by the multibeam mapping system are presented in three types of images. Each of these images highlights different features and characteristics of the sea floor. (1) A shaded relief image (Fig. 2) visually shows small topographic features (with relief of a few meters) that could not be effectively shown by contours alone at this scale. The image was created by vertically exaggerating the topography four times and then artificially illuminating the relief by a light source positioned 45◦ above the horizon from the north. In this image, topographic features are enhanced by strong illumination on the north-facing slopes and by shadows cast on the south-facing slopes. (2) A shaded relief image, colored by backscatter intensity, combines the high-resolution view of topography with a measure of sediment characteristics (Figs. 4, 5B, and 6). In these images, the backscatter intensity is represented by a suite of eight colors ranging from blue, which represents low intensity (fine-grained sediments), to red, which represents

Figure 4. Pseudo-colored backscatter intensity and shaded relief map of the entire HARS in April 2000. The faint north-trending stripes run parallel to the survey tracklines and are artifacts of data collection and environmental conditions. The pink, green, and yellow boxes outline areas shown in Figure 6 to illustrate changes in backscatter intensity between 1996, 1998, and 2000. See text for a description of this image and major features. Bathymetric contour interval is 5 m (red lines).

high intensity (rock outcrops and coarse-grained sediments). These data are draped over the shaded relief image. The resultant image displays light and dark intensities within each color band that result from a feature’s position with respect to the light source. For example, north-facing slopes, receiving strong illumination, show as a light intensity within a color band, whereas south-facing slopes, being in shadow, show as a dark intensity within a color band. (3) A shaded relief image, colored by bathymetry, combines the high-resolution view of topography with color to show water depth (Fig. 5A). THE SEA FLOOR OF THE HARS Within the HARS, one of the most striking aspects of the sea floor is the variability in backscatter intensity and bottom morphology over distances of a few kilometers or less, caused by both natural and anthropogenic processes. This fact sheet presents companion images showing the sea floor of the HARS as mapped in April 2000 in plan view (Figs. 2, 4, and 6) and in perspective view (Fig. 5). Images of selected areas in 1996, 1998, and 2000 illustrate changes over time (Fig. 6). Major features of the sea floor of the HARS shown in these images include two

MAPPING THE SEA FLOOR OF THE HISTORIC AREA REMEDIATION SITE (HARS) OFFSHORE OF NEW YORK CITY

Figure 5. Perspective view of the Historic Area Remediation Site, looking from south to north, based on the multibeam survey carried out in April 2000. A, Shaded relief map with color-coded bathymetry. B, Backscatter intensity draped over shaded relief (see text for a description of the color scheme). The north-trending stripes, running parallel to the survey tracklines, are artifacts of data collection and environmental conditions. The topography, surface features, and the surficial sediments of the HARS have been heavily influenced by the disposal of dredged and other material in this region over the last century, and by recent remedial capping. See text for a description of these images and major features.

relatively smooth topographic highs composed of material dumped in the late 1800’s and early 1900’s (‘‘Topographic highs’’ in Fig. 5A); mounds of material in the Mud Dump Site (‘‘Disposal mounds in MDS’’ in Fig. 5A); two circular features where contaminated sediments were placed and then capped with sand, one in the late 1980’s, and the other in 1997 (‘‘Sand capping’’ in Figs. 4 and 5B and ‘‘Previous capping’’ and ‘‘New sand capping’’ in Fig. 6); material deposited between the November 1996 and November 1998 survey (‘‘Recent placement’’ in Figs. 4 and 5A); many features about 50 m in size interpreted to be individual dumps of material (‘‘Historical dumps’’ in Figs. 4 and 5B); and material placed as part of remediation activities (‘‘Remedial capping’’ in Figs. 4, 5B, and 6). CHANGES IN SURFICIAL PROPERTIES BETWEEN 1996, 1998, AND 2000 Comparison of the topography and backscatter intensity from the three multibeam surveys show how the area changed as a result of dredged material placed before the Mud Dump Site was closed and ongoing remediation of the HARS (see Fig. 2 for locations of placed material from USACE records).

79

Figure 6. Pseudo-colored backscatter intensity and shaded relief map of parts of the HARS in 1996, 1998, and 2000 (see Fig. 4 for location). These images illustrate changes in the sea floor topography and backscatter intensity that occurred between 1996 and 1998 and between 1998 and 2000 caused by placement of dredged material and by remedial capping. See text for a description of these images and major features.

Between 1996 and 1998, changes include (1) mounds of medium backscatter intensity dredged material in the northeastern corner of the MDS, some as high as 6 m, placed between November 1996 and September 1997 (compare panels A and B, Fig. 6); (2) a circular area of low-backscatter intensity material about 1 km in diameter and 2 m thick in the southern part of the MDS associated with sand capping (compare panels C and D, Fig. 6); and (3) a circular area of low backscatter intensity material in PRA1 associated with remedial capping (compare panels E and F, Fig. 6). Between 1998 and 2000, changes include (compare panels F and G, Fig. 6) (1) increased backscatter intensity in PRA1 due to additional placement of material and consolidation, de-watering, and possible winnowing of the previous cover; (2) a series of crater-like features in the western part of PRA2, 30 to 70 m long and on the order of 20 m wide with elevated rims and central depressions, that were apparently formed as remedial material impacted the soft sediments on the sea floor; and (3) an area of reduced backscatter intensity in the northeastern corner of PRA2 caused by the placement of remedial material.

80

NOAA AND UNIVERSITY SCIENTISTS STUDY METHYL BROMIDE CYCLING IN THE NORTH PACIFIC

Resolution limits of the multibeam system, and the amount of material placed over a relatively large area, preclude using the repeated topographic surveys for determining the amount of material placed on the sea floor. However these multibeam data clearly show the overall regional geology and, through comparison of topography and backscatter intensity, document the location of placed material and changes in sediment properties over time.

NOAA AND UNIVERSITY SCIENTISTS STUDY METHYL BROMIDE CYCLING IN THE NORTH PACIFIC SHARI YVON-LEWIS Atlantic Oceanographic and Meteorological Laboratory

Figure 1. Cruise Track.

KELLY GOODWIN SARA COTTON University of Miami

JAMES BUTLER Climate Monitoring and Diagnostics Laboratory

DANIEL KING University of Colorado

ERIC SALTZMAN RYSZARD TOKARCZYK University of Miami

PATRICIA MATRAI BRIAN YOCIS EILEEN LOISEAU Bigelow Laboratory for Ocean Sciences

GEORGINA STURROCK Commonwealth Scientific and Industrial Research Organization—Australia

As part of a study supported by both NASA and NOAA, scientists from two NOAA laboratories, three universities and CSIRO participated in a research cruise aboard the R/V Ronald H. Brown. The cruise departed Kwajalein, Republic of the Marshall Islands on 14 September 1999 and arrived in Seattle, Washington on 23 October 1999 with stops in Honolulu, Hawaii, Dutch Harbor, Alaska, and Kodiak, Alaska. The objective of this research effort was to obtain reliable measurements of the uptake and emission of methyl bromide and other climatically important halocarbons in tropical to temperate regions of the North Pacific Ocean. Atmospheric methyl bromide (CH3 Br), which is of both natural and anthropogenic origin, has been identified as This article is a US Government work and, as such, is in the public domain in the United States of America.

Figure 2. Scientists collecting water samples for production and degradation incubations.

a Class I ozone-depleting substance in the amended and adjusted Montreal Protocol on Substances that Deplete Stratospheric Ozone. The role of the ocean in regulating the atmospheric burden of this gas is still somewhat uncertain. Methyl bromide is both produced and destroyed in the ocean through chemical and biological processes. The organisms or reactions that produce CH3 Br at rates sufficient to explain its observed concentrations are not known. Degradation has been shown to occur at rates that are faster than can be explained by known chemical degradation reactions, and evidence suggests that this additional degradation is bacterial consumption of CH3 Br. While recent measurements have shown that, on the whole, the ocean is a net sink for CH3 Br, measurement coverage to date has been limited and sporadic, which restricts our ability to map the spatial and temporal variations that are necessary for understanding how the system will respond to perturbations (e.g., Global Warming). The measurements made during this cruise are designed to help improve our understanding of the role that the oceans play in the cycling of CH3 Br. The program involved instrumentation from two NOAA

TIDALLY MEDIATED CHANGES IN NUTRIENT CONCENTRATIONS

laboratories and two universities. Measurements were made of the concentrations of CH3 Br and a suite of natural and anthropogenic halocarbons in the air and surface water, degradation rates of CH3 Br in the surface water, production rates of CH3 Br and other natural halocarbons in the surface water, and depth profiles of CH3 Br and other halocarbons. The combined results from these measurements will be used to constrain the budget of CH3 Br in these waters at this time of year. The relative importance of the biological and chemical processes will be examined for tropical and high latitudes. Attempts will also be made to extract relationships between the rates and concentrations measured and satellite measurements in order to develop proxies that can provide global coverage on shorter time scales. At this time, there is insufficient data to examine seasonal and long-term trends in net flux, production, or degradation. Until satellite measurable proxies can be found, additional research cruises are needed to reduce the uncertainty in the global net flux estimate and to map the spatial and temporal variations in the net fluxes, production rates, and degradation rates of CH3 Br and other climatically important halocarbons.

TIDALLY MEDIATED CHANGES IN NUTRIENT CONCENTRATIONS PAOLO MAGNI IMC—International Marine Centre Torregrande-Oristano, Italy

SHIGERU MONTANI Hokkaido University Hakodate, Japan

Freshwater runoff during ebb flow and salt water intrusion during the flood may have a major effect on short-term changes in nutrient (ammonium, nitrate+nitrite, phosphate, and silicate) concentrations along an estuary. Time series hourly measurements conducted in a mixedsemidiurnal type estuary (i.e., characterized by two major lower and higher tidal levels) show that these changes are a strong function of both tidal state (e.g., low vs. high tide) and amplitude (e.g., neap vs. spring tide). In particular, the changes in nutrient concentrations are higher during ebb than during flood tide and largest between the lower low tide and the higher high tide of a spring tide. Finally, the importance of investigating simultaneously different stations along the estuarine spine is highlighted, in addition to studying the nutrient distribution based on selected salinity intervals which may reflect only the conditions at a particular tidal state. BACKGROUND An important aspect of the high variability of tidal estuaries is related to the effect of the tidal cycle on the physical and chemical characteristics of the water. In particular, on a timescale of hours, freshwater runoff

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during ebb flow and salt water intrusion during the flood may determine strong changes in salinity and dissolved and particulate compounds. Several studies in riverine and estuarine waters have investigated the distribution of nutrient (e.g., ammonium, nitrate, phosphate, and silicate) concentrations, based on the salinity gradient in the system at a particular tidal state (1–3). Accordingly, plots of nutrients versus salinity are often used to assess the source of different nutrient species, whether from inland, outside the estuary, or within it (3–7). An evaluation of the distributional pattern of nutrients along an estuary has important ecological implications in relation to the cycling of biophilic elements, such as N (nitrogen), P (phosphorous), and Si (silicon). It is known that numerous processes influence the behavior of nutrients, whether they show conservative mixing or reflect removal or addition along an estuary. Ammonium consumption and ammonium oxidation, for instance, are predominant in the water column, whereas denitrification in sediments is responsible for nitrate removal from the water column (8–10). By contrast, bioturbation and excretion by abundant benthic animals may greatly contribute to the upward flux of regenerated nutrients, such as ammonium and phosphate, which in turn enhance primary production (11,12). Accordingly, it has been shown that regeneration processes within an estuary are consistent with often encountered nonconservative mixing of ammonium (4,8,13,14). This corresponds to the tendency of ammonium concentration to be high at midsalinity ranges, resulting in a poor correlation with salinity. In contrast, nitrate tends to show conservative behavior, as evidence of its riverine origin (2,14,15), although addition (15) or removal (7) is also found. Moreover, it must be considered that in some cases, nitrate versus salinity plots may fail to unravel active nitrate turnover, leading to an approximate balance of sources and sinks (16). As for silicate, a general pattern indicates that estuarine mixing of this nutrient species tends to be conservative (2,7,13). Yet, either silicate removal (7,17) or addition (4) occurs in relation to the development of an algal population in rivers or to a closer interaction with estuarine sediments, respectively, and varies with season (14). A major upward flux of silicate from sediments might also be related to the biological activity and excretory processes of abundant macrofaunal assemblages (18,19). In addition to these general considerations, the distribution and cycling of nutrients depend strongly on the specific characteristics of each estuary, including water residence time and water depth, nutrient levels, and the extent of salt-water intrusion. Uncles and Stephens (3) showed that saline intrusion was a strong function of the tidal state and a weaker function of freshwater inflow. Accordingly, Balls (2) indicated that conservative mixing of phosphate, is a function of estuarine flushing time, as related to particle–water interaction and chemical speciation (20). In particular, phosphate removal at low salinities may be due to adsorption to iron and aluminium colloidal oxyhydroxides that aggregate and undergo sedimentation (7).

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TIDALLY MEDIATED CHANGES IN NUTRIENT CONCENTRATIONS

Therefore, it is important that investigations of the distribution of nutrients as a function of salinity are conducted on proper spatial and temporal scales that take into account the extent and variability of salt-water intrusion. Time series surveys represent a valuable approach to quantifying such variability in estuarine waters (21,22). In particular, short-term monitoring surveys during a complete tidal cycle and simultaneous information at different stations can be a powerful tool for evaluating the extent of salt-water intrusion along the estuary and its direct impact on the water chemistry of an estuary. This approach may overcome the limitations of evaluating the distribution and behavior of nutrients based on a particular tidal state at arbitrarily selected salinity intervals. Major drawbacks when working across long distances to cover different salinity ranges include work time to travel between samplings, tidal-water displacements, variations in tidal velocities, and a possible wide range of river discharge. Simultaneous observations at different stations are expected to track changes in nutrient concentrations that occur along the estuarine spine in relation to the extent of salt-water intrusion over time. Case study This article reviews the results of 24-hour surveys in a tidal estuary of the Seto Inland Sea, Japan, during a spring tide of May 1995 (13,23). It is aimed to give an example of the effect of freshwater runoff and salt-water intrusion on the spatial and temporal variability of nutrient concentrations during a tidal cycle. The effect of a tide is also evaluated in relation to the mixed-semidiurnal behavior (i.e., with pronounced differences between two successive low and high tides) of the estuary. The fieldwork was conducted along a transect line of approximately 1.4 km linking the river to the rear to the subtidal zone. Multiprobe casts were used for hydrologic measurements. Nutrient concentrations were determined every hour in surface waters, simultaneously at a riverine, an intertidal, and a subtidal station, and every two hours at additional depths through the water column at the subtidal station. Details of the sampling scheme and analysis are given in Montani et al. (13) and Magni et al. (23). At the beginning of the survey, there was a marked salinity gradient along the estuary; surface water salinity was 2.0, 18.5, and 31.3 psu at the riverine, intertidal, and subtidal stations, respectively (Fig. 1). As the lower low tide approached, salinity remained low at the riverine station (Fig. 1a), sharply decreased also at the intertidal station (Fig. 1b) and, subsequently, at the subtidal station (Fig. 1c). By contrast, soon after the lower low tide, saltwater intrusion rapidly caused an abrupt increase in salinity at both the intertidal and the riverine stations, up to >30 psu (Figs. 1a,b). During the flood, there was a homogeneous distribution of high-salinity water along the transect line. At the subtidal station, a major change in salinity as a function of the tidal cycle was also apparent, but restricted to the surface layer, whereas salinity remained constantly >31 psu below the surface (Figs. 1c,d).

The nutrient concentrations were also markedly affected by the tidal cycle. At the beginning of the survey, silicate and nitrate+nitrite concentrations were markedly higher at the riverine station than at the intertidal and subtidal stations, whereas the ammonium concentration was relatively higher at the intertidal station (Figs. 1a, b, c). Approaching the lower low tide, the nutrient concentrations in surface water increased rapidly, especially at the intertidal and subtidal stations. Differently at the riverine station, the ammonium concentrations remained low, suggesting no significant import of this nutrient species through freshwater inflow (Fig. 1a). At the subtidal station, the nutrient concentrations also showed a relatively consistent increase below the surface, yet progressively less noticeable with depth (Fig. 1d). By contrast, during the flood, as high-salinity water flushed backward into the estuary, the nutrient concentrations dropped to the lowest values at all stations and depths (Figs. 1a, b, c, d); a 7.5-fold and 8.8-fold decrease of silicate and nitrate+nitrite concentrations, respectively, occurred at the riverine station. During the second part of the survey, after the higher high tide, both salinity and nutrient changes were less marked. Figure 2 summarizes the relationships between salinity and nutrient concentrations. Salinity versus nutrient plots demonstrate that the distributional pattern of nutrients largely varied with station, depth, and the different nutrient species. In particular at the riverine station, silicate and nitrate+nitrite were negatively correlated with salinity; r2 explained a large portion of total variance (i.e., r2 = 0.879 and 0.796, respectively). By contrast, at this station, ammonium showed a positive correlation with salinity, whereas phosphate did not significantly correlate with salinity. Differently at the intertidal and subtidal stations, the concentrations of all nutrient species in surface waters were negatively and significantly correlated with salinity; levels of confidence varied from p < .05 (ammonium) to p < .001 (phosphate and silicate). The variability of both salinity and nutrient concentrations was lowest at the subtidal station below the surface. This test data set (Fig. 2d) indicated that all nutrient species were correlated positively with salinity at a high level of significance (p < .001). Relevant plots also highlighted that, within such a restricted variability of salinity, silicate and nitrate+nitrite concentrations comprised narrower values than those of phosphate and ammonium (Fig. 2d). Accordingly, the model equation for the former two nutrient species explained a higher portion of the total variance (r2 = 0.423, and r2 = 0.457, respectively) than that explained by the latter (r2 = 0.221, and r2 = 0.245, respectively). These results showed that the riverine input was a major source of silicate and, partially, nitrate+nitrite and phosphate. It was also apparent that the increase in nutrient concentrations at the intertidal station and subsequently at the subtidal station, was largest during the first part of the survey (Figs. 1b, c). Companion papers demonstrated that the intertidal zone also plays a major role in nutrient cycling, as a major site of nutrient regeneration within the estuary (12,14,24).

TIDALLY MEDIATED CHANGES IN NUTRIENT CONCENTRATIONS

Subtidal station (surf. & water column)

(d) (a)

Riverine station (surface)

(b)

Intertidal station (surface)

(c)

Subtidal station (surface)

0

Depth, m

Salinity

25 20

Tidal range (2 m)

15

31

L 17.5

31 2

35 30

4 H

H

6 8

Salinity

5

0

0

Depth, m

Si(OH)4

H 76.7 50 40 10 L 30

2

Higher high tide

100 80 60 40

4 20 8

Lower low tide

10 L

L

Si(OH )4 50.3 H 25 25 20 15 20 15 10 5 10

0 5 2 Depth, m

60 40 20

15 10

4

47.4 20 25 5

5 6

50 40 40 30 20 30 20

10 L

6

20

NO3− + NO2−

27

31 29

31-23

10

0

83

L

L 5 L

8

5

NO3− + NO2−

0 0

H 4.9

2

4 Depth, m

PO43−

5

3 2 1

2

L

6 •

2 Depth, m

NH4+

0

30 20 10 0

4

May 30

May 31

May 30

May 31

May 30

May 31

Time, h

2 L

3 2 L

42.6 H 35.7 25 >30 >30 20 25 25 20 5 15 20 15 5 10 L 10 L 10 15

6 8

10 12 14 16 18 20 22 24 2 4 6 8 10 12 14 16 18 20 22 24 2 4 6 8 10 12 14 16 18 20 22 24 2 4 6 8 10

2 1

PO43−

0 40

3

3 1

4

8

2

NH4 +

10

10 10 12 14 16 18 20 22 24 2 4 6 8 10 May 30 May 31

Time, h

Figure 1. Time series of salinity (psu, practical salinity unit) and nutrient concentration (µM) in surface water at a riverine, intertidal, and subtidal station (Fig. 1a, b, c) and through the water column at the subtidal station (Fig. 1d) during a tidal cycle of a spring tide in a mixed-semidiurnal type estuary (Seto Inland Sea, Japan). Data sources: Fig. 1a, b, c from Montani et al. (13) (redrawn from Figs. 4 & 5); Fig. 1d: from Magni et al. (23) (adapted from Figs. 2 & 3).

CONCLUDING REMARKS This article showed that the effect of salt-water intrusion on the dynamics of nutrients varies strongly both spatially (on relatively short distances) and temporally (on an hour timescale), and that this is much dependent on the tidal state. In particular, it was shown that the effect of tidal amplitude is important in determining the extent of the variations in nutrient concentrations, which were stronger between the lower low tide and the higher high tide. It also indicated that nutrient concentrations were higher during the ebb than during the flood and highest at the surface layer, as strongly correlated inversely with salinity. Finally, this work highlighted the importance of considering simultaneous investigations at different stations along the estuarine spine during a tidal cycle, especially on short distances, besides studying the nutrient

dynamics based on selected salinity intervals that may reflect only the situation at a particular tidal state. BIBLIOGRAPHY ´ 1. Hernandez-Ay´ on, J.M., Galindo-Bect, M.S., Flores-Baez, B.P., and Alvarez-Borrego, S. (1993). Nutrient concentrations are high in the turbid waters of the Colorado River delta. Estuar. Coast. Shelf Sci. 37: 593–602. 2. Balls, P.W. (1994). Nutrient inputs to estuaries from nine Scottish east coast rivers; influence of estuarine processes on inputs to the North Sea. Estuar. Coast. Shelf Sci. 39: 329–352. 3. Uncles, R.J. and Stephens, J.A. (1996). Salt intrusion in the Tweed Estuary. Estuar. Coast. Shelf Sci. 43: 271–293. 4. Balls, P.W. (1992). Nutrient behaviour in two contrasting Scottish estuaries, the Forth and the Tay. Oceanol. Acta 15: 261–277.

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TIDALLY MEDIATED CHANGES IN NUTRIENT CONCENTRATIONS

Riverine station (surface )

PO43−

NO3− + NO2−

Si(OH)4

(a) 120 100 80 60 40 20 0 60

(c) Subtidal station (surface )

y = −2.9x + 110.7; r 2 = 0.879 (n = 25, p < .001)

y = −2.6x + 100.7; r 2 = 0.736 (n = 25, p < .001)

y = −1.25x + 48.8; r 2 = 0.796 (n = 25, p < .001)

y = −2.07x + 74.6; r 2 = 0.744 (n = 25, p < .001)

Subtidal station (d) (water column - no surface)

y = −3.6x + 133.7; r 2 = 0.624 (n = 25, p < .001)

y = −22.1x + 719; r 2 = 0.423 (n = 50, p < .001)

y = −2.10x + 80.7; r 2 = 0.381 (n = 25, p < .01)

y = −17.7x + 571; r 2 = 0.457 (n = 50, p < .001)

45 30 15 0 5 4 3 2 1 0

y = −1.79x + 58; r 2 = 0.221 (n = 50, p < .001)

y = −0.01x + 3.9; r 2 = 0.011 (n = 25, ns)

y = −0.19x + 8.0; r 2 = 0.428 (n = 25, p < .01)

y = −0.09x + 4.8; r 2 = 0.404 (n = 25, p < .001)

40 NH4 +

Intertidal station (surface )

(b)

y = 0.68x + 3.9; r 2 = 0.546 (n = 25, p < .001)

30

y = −14.5x + 472; r 2 = 0.245 (n = 50, p < .001)

20 y = −1.29x + 58.2; r 2 = 0.254 (n = 25, p < .05)

y = −0.63x + 35.2; r 2 = 0.337 (n = 25, p < .01)

10 0 0

5

10 15 20 25 30

0

5

10 15 20 25 30

0

5

10 15 20 25 30

0

5 10 15 20 25 30 35

Salinity, psu Figure 2. Plots of salinity (psu) versus nutrient concentration (µM) originated from the time series in Fig. 1. Data sources: Fig. 1a, b, c from Montani et al. (13) (redrawn from Figs. 8 to 11); Fig. 1d: after Magni et al. (23).

5. Clark, J.F., Simpson, H.J., Bopp, R.F., and Deck, B. (1992). Geochemistry and loading history of phosphate and silicate in the Hudson estuary. Estuar. Coast. Shelf Sci. 34: 213–233. 6. Page, H.M., Petty, R.L., and Meade, D.E. (1995). Influence of watershed runoff on nutrient dynamics in a southern California salt marsh. Estuar. Coast. Shelf Sci. 41: 163–180. 7. Eyre, B. and Twigg, C. (1997). Nutrient behaviour during post-flood recovery of the Richmond river estuary northern NSW, Australia. Estuar. Coast. Shelf Sci. 44: 311–326. 8. Soetart, K. and Herman, P.M.J. (1995). Nitrogen dynamics in the westerschelde (the Netherlands) using a box model with fixed dispersion coefficients. Hydrobiologia 311: 215–224. 9. Nixon, S.W. et al. (1996). The fate of nitrogen and phosphorus at the land–sea margin of the North Atlantic Ocean. Biogeochem. 35: 141–180. 10. Nedwell, D.B., Jickells, T.D., Trimmer, M., and Sanders, R. (1999). Nutrients in estuaries. Adv. Ecol. Res. 29: 43–92. 11. Herman, P.M.J., Middelburg, J.J., van de Koppel, J., and Heip, C.H.R. (1999). Ecology of estuarine macrobenthos. Adv. Ecol. Res. 29: 195–240. 12. Magni, P., Montani, S., Takada, C., and Tsutsumi, H. (2000). Temporal scaling and relevance of bivalve nutrient excretion on a tidal flat of the Seto Inland Sea, Japan. Mar. Ecol. Prog. Ser. 198: 139–155. 13. Montani, S. et al. (1998). The effect of a tidal cycle on the dynamics of nutrients in a tidal estuary in the Seto Inland Sea, Japan. J. Oceanogr. 54: 65–76. 14. Magni, P. and Montani, S. (2000). Water chemistry variability in the lower intertidal zone of an estuary in the Seto Inland

Sea, Japan: Seasonal patterns of nutrients and particulate compounds. Hydrobiologia 432: 9–23. 15. Middelburg, J.J. and Nieuwenhuize, J. (2000). Uptake of dissolved inorganic nitrogen in turbid, tidal estuaries. Mar. Ecol. Prog. Ser. 192: 79–88. 16. Middelburg, J.J. and Nieuwenhuize, J. (2001). Nitrogen isotope tracing of dissolved inorganic nitrogen behaviour in tidal estuaries. Estuar. Coast. Shelf Sci. 53: 385–391. 17. Liss, P.S. and Pointon, M.J. (1973). Removal of dissolved boron and silicon during estuarine mixing of sea and river waters. Geochim. Cosmochim. Acta 37: 1493–1498. 18. Bartoli, M. et al. (2001). Impact of Tapes philippinarum on nutrient dynamics and benthic respiration in the Sacca di Goro. Hydrobiologia 455: 203–212. 19. Magni, P. and Montani, S. (2004). Magnitude and temporal scaling of biogenic nutrient regeneration in a bivalvedominated tidal flat. In: Encyclopedia of Water. John Wiley & Sons, New York. 20. Froelich, P.N. (1988). Kinetic control of dissolved phosphate in natural rivers and estuaries: A primer on the phosphate buffer mechanism. Limnol. Oceanogr. 33: 649–668. 21. Yin, K., Harrison, P.J., Pond, S., and Beamish, R.J. (1995). Entrainment of nitrate in the Fraser river estuary and its biological implications. II. Effects of spring vs. neap tide and river discharge. Estuar. Coast. Shelf Sci. 40: 529–544. 22. Yin, K., Harrison, P.J., Pond, S., and Beamish, R.J. (1995). Entrainment of nitrate in the Fraser River estuary and its biological implications. III. Effects of winds. Estuar. Coast. Shelf Sci. 40: 545–558.

THE ROLE OF OCEANS IN THE GLOBAL CYCLES OF CLIMATICALLY-ACTIVE TRACE-GASES 23. Magni, P., Montani, S., and Tada, K. (2002). Semidiurnal dynamics of salinity, nutrients and suspended particulate matter in an estuary in the Seto Inland Sea, Japan, during a spring tide cycle. J. Oceanogr. 58: 389–402. 24. Montani, S., Magni, P., and Abe, N. (2003). Seasonal and interannual patterns of intertidal microphytobenthos in combination with laboratory and areal production estimates. Mar. Ecol. Prog. Ser. 249: 79–91.

THE ROLE OF OCEANS IN THE GLOBAL CYCLES OF CLIMATICALLY-ACTIVE TRACE-GASES ROBERT C. UPSTILL-GODDARD University of Newcastle upon Tyne Newcastle upon Tyne, United Kingdom

The oceans are important in the global cycles of a range of trace gases that influence atmospheric chemistry and climate. For some of these, the oceans are a net source to the atmosphere, whereas for others, they are a net sink. Major gases of interest are summarized in Table 1, along with their net flux directions and their principal roles in the troposphere and stratosphere. Carbon dioxide (CO2 ), methane (CH4 ), and nitrous oxide (N2 O) are major greenhouse gases: CO2 currently accounts for more than one-half of enhanced global warming, whereas CH4 and N2 O, respectively, account for about 15% and 6% (1). Volatile sulphurs are also implicated in climate forcing and they play important roles in atmospheric chemistry. As a result of length restrictions, our discussion focuses only on these gases. GLOBAL PARTITIONING OF ANTHROPOGENIC CO2 Several mechanisms contribute to natural CO2 cycling between the atmosphere and the Earth’s surface. The largest natural exchanges occur through respiration and photosynthesis on land and in the oceans, and by solubility-driven uptake in the oceans, and the net result of these exchanges is a natural carbon cycle in overall balance. By comparison with these natural fluxes, the flux

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of anthropogenic CO2 , which is derived primarily from the burning of fossil fuels, cement production, deforestation, and other land-use changes, is rather small, ∼7 ± 1 Gt C per year (1) (1 Gt = 1 gigatonne = 1015 g), which is nevertheless large enough to significantly disturb the natural CO2 cycle. As a result of its unreactive nature, the residence time of CO2 in the troposphere is of the order of 50–200 years, hence anthropogenic CO2 tends to accumulate there. In fact, tropospheric CO2 has risen from about 280 ppmv (parts per million by volume) preindustrially, as determined from ice core studies (2), to approaching 380 ppmv by mid-2004 (http://www.cmdl.noaa.gov/). However, this corresponds to somewhat less than one-half of the known anthropogenic release (1). During the 1980s (the latest decade for which estimates of all carbon sources and sinks are available), the mean rate of tropospheric CO2 growth was only about 3.3 ± 0.1 Gt C per year, the remainder, about 3.7 ± 1.0 Gt C per year, having been absorbed by ‘‘sinks’’ located in the oceans and within the terrestrial biosphere (1). The fraction of anthropogenic CO2 absorbed by these sinks is, however, not constant. Large fluctuations are evident in the continuous tropospheric records that date back to the late 1950s (1), and these fluctuations are believed to relate directly to short-term variations in global climate. For example, increased atmospheric growth rates correlate ˜ climate warming events, whereas cooling with El Nino periods, such as that which followed the eruption of Mount Pinatubo in the early 1990s, seem to be associated with reduced atmospheric growth. These variations are thought principally to reflect changes in the balance of terrestrial primary production (photosynthesis) versus respiration, decomposition, and the combustion of organic material (3). High background variability has precluded directly measuring the relative magnitudes of the oceanic and terrestrial CO2 sinks, hence they have hitherto been estimated using models, often with conflicting results (4). However, recent techniques based on measuring carbon and oxygen isotopes in air (5) now enable the partitioning of anthropogenic CO2 between these reservoirs to be determined with greater certainty, and it is now generally agreed that the ocean and land sinks are of about the same magnitude (although the uncertainties are large), i.e., about 1.9 ± 0.6 Gt C per year (6).

Table 1. Some Atmospherically Active Trace Gases with Important Marine Sources or Sinks Gas

Net Flux

Effect in the Atmosphere Infra-red activity Infra-red activity Atmospheric redox Ozone regulation Infra-red activity Ozone regulation Atmospheric redox Acidity, Cloud formation Sulphate aerosol (cooling) Source of COS Atmospheric redox Atmospheric redox

Carbon Dioxide Methane

(CO2 ) (CH4 )

Into Ocean Out of Ocean

Nitrous Oxide

(N2 O)

Out of Ocean

Carbon Monoxide Dimethyl sulphide Carbonyl Sulphide Carbon Disulphide Organohalogens (Natural) Nonmethane hydrocarbons

(CO) (DMS) (COS) (CS2 )

Out of Ocean Out of Ocean Out of Ocean Out of Ocean Out of Ocean Out of Ocean

Troposphere √ √

Stratosphere

√ √ √ √ √ √

√ √ √

86

THE ROLE OF OCEANS IN THE GLOBAL CYCLES OF CLIMATICALLY-ACTIVE TRACE-GASES

MECHANISMS OF OCEAN CO2 UPTAKE Compared with many other atmospheric trace gases, CO2 is rather soluble in seawater, where it occurs as three principal dissolved species that together comprise seawater dissolved inorganic carbon (DIC), which are bicarbonate (HCO3 − , 91% of DIC), carbonate (CO3 2− , 8% of DIC), and dissolved CO2 (1% of DIC). The capacity of the oceans to absorb atmospheric CO2 is ultimately buffered by the DIC system. CO2 uptake results in an increase both in the partial pressure of CO2 (pCO2 ) and in the concentration of HCO3 − , which is produced through the reaction of CO2 with CO3 2− . With further CO2 uptake, its conversion to HCO3 − becomes limited by the decreasing CO3 2− availability, the result being that more CO2 remains in solution, further decreasing the capacity for CO2 uptake at increasing tropospheric levels. As an illustration, for atmospheric CO2 to rise by about 100 ppmv relative to today, the increase in seawater DIC would only be about 60% of that which has accompanied the approximately 100 ppmv rise in tropospheric CO2 since the industrial revolution (1,6). Studies based on the downward penetration of chemical tracers, such as 14 C, coupled with simple box models of ocean mixing (7), or more sophisticated General Circulation Models (8), show that tropospheric CO2 equilibrates with the surface ocean mixed layer rather rapidly, on the order of a few years. In contrast, CO2 penetration into the deep ocean interior is constrained by relatively slow vertical transport; the whole ocean equilibrates with the atmosphere on a timescale of more than 1000 years. As a result of this slow rate of downward mixing, with few exceptions, anthropogenic CO2 has yet to penetrate below about 1000 m depth. Transport of CO2 into the ocean interior occurs via the thermohaline circulation, in which cool surface waters in the high latitude North Atlantic (Greenland Sea) and Southern Oceans sequester CO2 from the troposphere and sink because of their higher density. This downward transport is balanced in regions where deep water with a high capacity for CO2 uptake wells up to the surface, such as occurs in parts of the tropics and the Southern Ocean. The sinking waters eventually spread laterally toward the subtropics, giving rise to a relatively uniform distribution of anthropogenic CO2 . Eventually, on the 1000-plus year timescale of deep ocean mixing, the deep CO2 -rich waters formed in this way will again well up to the surface, the principal site for this being the Equatorial Pacific. As this water warms during upwelling, its pCO2 will increase, resulting in CO2 loss to the atmosphere by out gassing. One other potential removal process for tropospheric CO2 is through reaction with CaCO3 contained in deep sea sediments; however, their response time to changes in tropospheric CO2 is several thousand years (9). According to some coupled ocean-atmosphere models, one possible consequence of global warming is an increase in the intensity of vertical stratification in the oceans (1), which would reduce the rate of surface to deep water mixing and, consequently, the uptake rate of tropospheric CO2 . In addition to chemically and physically driven uptake, tropospheric CO2 is also processed through the so-called

‘‘biological pump,’’ in which organic matter produced via photosynthesis and cycled through the upper ocean food-web is ultimately transported downward via sinking organic particles or through vertical biomass migrations. This sinking flux of organic carbon is remineralized or respired back to inorganic carbon at depth with an accompanying release of dissolved inorganic nutrients (principally nitrate and phosphate). Model simulations suggest that without the biological pump, tropospheric CO2 could be about 150 ppmv higher than at present (1). However, the likely response of the biological pump to increasing tropospheric CO2 is uncertain. Most current evidence tends to discount increased productivity on the grounds of limitation by the supply of nutrients, which are seasonally depleted in most surface waters. However, extensive regions exist of the subarctic Pacific, equatorial Pacific, and Southern Ocean with abundant nitrate and phosphate throughout the year but with very low phytoplankton productivity, the so-called high-nutrientlow-chlorophyll (HNLC) regions. Their low productivity likely reflects a deficiency in the supply of a minor nutrient such as iron (10). Although predicting climate-induced changes in the supply rate of iron to the oceans is far from straightforward, these regions could conceivably play a significant role in the future ocean uptake of anthropogenic CO2 . It is also conceivable that global warming-induced changes in stratification described earlier could also modify the ocean’s biological carbon cycle; however, the consequences of this are difficult to predict given the intrinsic complexity of the system (11). THE GLOBAL ROLE OF CH4 AND N2 O As well as being important greenhouse gases, CH4 and N2 O play important roles in atmospheric chemistry; N2 O is involved in the stratospheric cycling of NOx (reactive nitrogen oxides) and ozone (12), and CH4 takes part in reactions that govern levels of tropospheric ozone and hydroxyl radical (· OH) and stratospheric H2 O (13). Like CO2 , N2 O and CH4 are currently increasing in the troposphere, both by about 0.3% per year (1). However, the role of the oceans in their global budgets differs from that for anthropogenic CO2 in two fundamental ways. First, the oceans are a net source of tropospheric N2 O and CH4 , and second, for both, the marine source is one of several global sources whose relative magnitudes remain rather uncertain. GLOBAL SOURCE UNCERTAINTIES The marine system is one of two major N2 O sources, the other being terrestrial soils. Combustion, biomass burning, and fertilizers make additional minor contributions. Although the uncertainties are large, the oceans are thought to contribute around 20% of the natural global source (1); however, the contribution is larger with anthropogenic sources included (see below). For CH4 , many more global sources exist, in descending order of magnitude, these are: agriculture, wetlands, fossil fuels, biomass burning, termites, oceans, CH4 hydrates, and

THE ROLE OF OCEANS IN THE GLOBAL CYCLES OF CLIMATICALLY-ACTIVE TRACE-GASES

landfills. However, the range of uncertainties is no better than it is for N2 O, ranging from ±100% (e.g., wetlands), to in excess of ±2000% (e.g., CH4 hydrates) (1). According to these data, marine waters contribute only about 3% of the total CH4 source to the troposphere, but this may be an underestimate (see below).

SOURCES OF SEAWATER N2 O In seawater, N2 O develops as a byproduct during microbial nitrification (the conversion of dissolved ammonium, NH4 + , to nitrate, NO3 − ) and as a reactive intermediate during microbial denitrification (the reduction of NO3 − to gaseous nitrogen). Nitrification principally occurs in oxygenated waters, although it is inhibited by light, whereas denitrification is restricted to anoxic sediments and O2 -deficient waters. For these reasons, N2 O production is insignificant in most open ocean surface waters. In extremely O2 -deficient waters, N2 O can be consumed during denitrification because of its use as an electron acceptor by denitrifying bacteria (14). Coupling of the two processes, in which the NO3 − developing from nitrification is consumed by denitrification, occurs both in marine sediments (15) and around the fringes of O2 depleted waters in the open ocean (16). The net rate of N2 O production by nitrification and denitrification is influenced by several factors in addition to dissolved O2 availability, including the supply rates of NO3 − and NH4 + , the composition of the microbial ecosystem, and in sediments, physicochemical aspects such as porosity and grain size. Consequently, both processes show pronounced seasonal variability. These aspects, coupled with a nonuniform distribution of N2 O source regions, makes the total marine source of N2 O difficult to quantify. Current data indicate around two-thirds of the marine source of tropospheric N2 O to derive from the open ocean, with the remainder coming from coastal waters. However, these estimates contain uncertainties resulting from incomplete spatial and seasonal sampling and difficulties related to estimating sea-to-air fluxes. Open ocean emissions are approximately equally distributed between the northern and southern hemispheres. Most of the N2 O is located below the surface-mixed layer and highest concentrations occur at around 500–1000 m depth, where a high O2 demand results from the bacterial decomposition of sinking organic particles. Exchange of this water with the atmosphere is usually slow, except during wintertime when the surface-mixed layer deepens because of cooling and wind-driven mixing, entraining waters from below. Regions experiencing strong seasonal upwelling are especially strong sources of tropospheric N2 O, which include the Tropical North Pacific, the Arabian Sea/northwestern Indian Ocean, the equatorial upwelling, and along the coasts of northwest Africa and western central and South America. In these areas, the upwellings bring N2 O-rich waters to the surface along with a plentiful supply of nutrients that fuels high primary productivity. The resultant large downward flux of organic particles gives rise to strongly O2 -deficient waters that replenish

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the deep water inventory of N2 O through nitrificationdenitrification coupling (17). Some areas of the subtropical gyres and the North Atlantic seem to be weak sinks for tropospheric N2 O in winter and weak sources in summer. The major coastal N2 O source regions are estuaries, open coastal shelf waters being generally at or close to equilibrium with tropospheric N2 O levels. Both water column nitrification associated with high suspended particle populations (18) and sediment denitrification (19) have been identified in estuaries. Whereas oceanic N2 O emissions are considered to be wholly natural, significant N2 O in coastal waters appears to derive indirectly from anthropogenic activity. In particular, the use of fertilizers is reflected in enhanced transport of nitrogen to coastal waters and a consequent increase in N2 O production and tropospheric flux. As much as 90% of current estuarine N2 O emissions and 25% of continental shelf emissions may be anthropogenic and consistent with the geographic distribution of fertilizer use, human population, and atmospheric nitrogen deposition, more than 80% of these anthropogenic sources are located in the Northern Hemisphere mid-latitudes between 20◦ N and 66◦ N (20). SOURCES OF SEAWATER CH4 Like N2 O, seawater CH4 has a microbial source (microbial methanogenesis). Methanogenesis is inhibited by dissolved O2 and therefore usually occurs in anoxic sediments or in waters that are strongly O2 -depleted. Even so, CH4 concentrations in the oxygenated surface ocean are on average about 30% above the tropospheric equilibrium value, most likely reflecting methanogenesis by O2 -tolerant methanogens inside bacterially maintained ‘‘anoxic microniches’’ in the guts of zooplankton and/or in particles (21). Consequently, the open ocean represents a small CH4 source. In addition, regions of much higher CH4 concentration occur in upwelling areas, associated with enhanced primary productivity as for N2 O (16,22). Based on the available open ocean data, the marine contribution to tropospheric CH4 is about 10 Tg CH4 per year, which is equivalent to about 3% of the total global source (1). Coastal waters have much higher CH4 concentrations than the open ocean but have, until recently, been excluded from global CH4 source estimates because of a lack of data. For estuaries, values of 100 to 200 times the background equilibrium value are common. Such CH4 levels reflect direct inputs from rivers, coastal seawater, underlying sediments, and in situ production/consumption from water column methanogenesis and microbial CH4 oxidation. Recent work suggests that correctly accounting for these regions could increase the estimated marine CH4 source by around 50% (23). A potentially even larger CH4 source may be geologically sourced CH4 from natural marine seeps, which are most common on shallow continental shelves (24). Seeps are episodic in nature, and the CH4 fluxes developing from them are predominantly by bubbles, which complicates making accurate measurements. As a result of CH4 losses because of bubble dissolution and subsequent CH4 oxidation in the water column, shallow water seeps are

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much more effective than deep water seeps at contributing CH4 to the troposphere. Revised source estimates that take account of seep occurrences suggest that the total marine source of tropospheric CH4 could be as much as 40 Tg yr−1 (25). If so, the oceans could be a much more important source of tropospheric CH4 than previously thought. VOLATILE SULPHUR COMPOUNDS The marine system is an important source of sulphur globally; in particular, it is the principal source of biogenic atmospheric sulphate aerosol, which plays important roles in atmospheric chemistry and climate. The predominant volatile sulphur in surface seawater is dimethyl sulphide (DMS) [(CH3 )2 S], which is a byproduct of algal metabolism and accounts for about 95% of marine sulphur emissions and 20% of total global sulphur emissions (1). DMS is rapidly oxidized by free radicals in the lower troposphere. Sulphur dioxide (SO2 ) is the major reaction product and is subsequently transformed to sulphate aerosol through gas-to-particle reactions. This process is hypothesized to impact directly the radiative forcing of global climate, primarily through changes to cloud albedo (26). Carbonyl sulphide (COS) has also been implicated in global climate forcing. Compared with other volatile sulphurs, COS has a long tropospheric residence time of around 2–6 years. Consequently, it is transported into the stratosphere, where its photo-oxidation is believed to be an important source of sulphate aerosol, which is thought to impact Earth’s radiation balance (27) and stratospheric ozone levels (28). DIMETHYL SULPHIDE A global database of more than 15,000 measurements of surface seawater (29) revealed distinct annual DMS cycles in the open ocean at mid to high latitudes. In the northern hemisphere, open ocean DMS increases during spring–summer, whereas in the southern hemisphere, concentrations peak six months later. These patterns relate to the timing of phytoplankton blooms and seasonal changes in mixed layer depth. In contrast, tropical regions show weak seasonality; DMS is elevated in the upwelling regions off western Africa and South America, but these concentrations are lower than those at high latitudes during summer. On coastal shelves, DMS is spatially and temporally variable, broadly correlating with seasonal primary productivity and the presence of algal blooms associated with upwelling at water mass boundaries (hydrographic fronts) (29). Similar concentrations are found in many estuaries, notable exceptions being those with high concentrations of suspended particles. Seasonal patterns are, however, rather different, with maximum concentrations occurring during late winter/early spring. The available data indicate that coastal regions may be larger emitters of DMS per unit area than the global mean, however, because of its much larger surface area, the open ocean is the most important source of tropospheric DMS (29).

CARBONYL SULPHIDE Direct marine emissions are thought to account for about 20% of the global COS source (30), although the tropospheric oxidation of marine-derived DMS and carbon disulphide (CS2 ) may increase this to as much as 55% (31). COS in seawater primarily develops from the photodecomposition of humic-like colored dissolved organic matter (CDOM) (32), although a small nonphotochemical source has also been inferred. The distribution of sea surface COS, therefore, corresponds closely to the concentration and reactivity of CDOM, which primarily derives from terrestrial sources. Consequently, COS concentrations are highest in estuaries, which are about an order of magnitude higher than those of adjacent coastal waters (32). COS undergoes hydrolysis removal in seawater at a similar rate to that for its photo-production, hence COS shows a pronounced diel cycle in surface seawater with concentrations peaking in the early afternoon and declining to a minimum just before sunrise (33). Strong seasonal variation also exists. In the mid to high latitude open ocean the balance of photo-chemical production versus hydrolysis removal can lead to these regions becoming a seasonal sink for tropospheric COS (34). Net ocean uptake of COS has also been found in the subtropical ocean gyres (35). Taking account of these findings, the marine COS source is most likely dominated by the contribution from coastal and shelf areas. BIBLIOGRAPHY 1. Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J., Dai, X., Maskell, K., and Johnson, C.A. (Eds.). (2001). Climate Change 2001: The Scientific Basis. Cambridge University Press. 2. Barnola, J.M. et al. (1995). CO2 evolution during the last millennium as recorded by Antarctic and Greenland ice. Tellus 47B: 264–272. 3. Le Qu´er´e, C., Orr, J., Monfray, P., and Aumont, O. (2000). Interannual variability in the oceanic sink of CO2 from 1979 through 1997. Glob Biogeochem Cyc. 14: 1247–1265. 4. Siengenthaler, U. and Sarmiento, J.L. (1993). Atmospheric carbon dioxide and the ocean. Nature 365: 119–125. 5. Keeling, R.F. and Shertz, S.R. (1992). Seasonal and interannual variations in atmospheric oxygen and implications for the global carbon cycle. Nature 358: 723. 6. Sarmiento, J.L. and Gruber, N. (2002). Sinks for anthropogenic carbon. Physics Today 55: 30–36. 7. Broecker, W.S., Takahashi, T., Simpson, H.J., and Peng, TH. (1979). Fate of fossil fuel carbon dioxide and the global carbon budget. Science 206: 409–418. 8. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A., and Totterdell, I.J. (2000). Acceleration of global warming due to carboncycle feedbacks in a coupled climate model. Nature 408: 184. 9. Archer, D.E., Kheshgi, H., and Maier-Reimer, E. (1997). Multiple timescales for neutralization of fossil fuel CO2 . Geophys Res. Lett. 24: 405–408. 10. Martin, J.H. (1992). Iron as a limiting factor. In: Primary Productivity and Biogeochemical Cycles in the Sea. P.G. Falkowski and A. Woodhead (Eds.). Plenum Press, New York, pp. 123–137.

PACIFIC MARINE ENVIRONMENTAL LABORATORY—30 YEARS OF OBSERVING THE OCEAN 11. Sarmiento, J.L., Hughes, T.M.C., Stouffer, R.J., and Manabe, S. (1998). Simulated response of the ocean carbon cycle to anthropogenic climate warming. Nature 393: 245–249. 12. Nevison, C. and Holland, E. (1997). A re-examination of the role of anthropogenically fixed nitrogen on atmospheric N2 O and the stratospheric O3 layer. J. Geophys Res. 10: 15809–15820. 13. Crutzen, P.J. (1990). Methane’s sinks and sources. Nature 350: 390–381. 14. Cohen, Y. and Gordon, L.I. (1979). Nitrous oxide in the oxygen minimum of the of the eastern tropical north Pacific: Evidence for its consumption during denitrification and possible mechanisms for its production. Deep Sea Res. 25: 509–524.

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predict sea surface DMS as a function of latitude, longitude, and month. Glob. Biogeochem. Cyc. 13: 399–444. 30. Watts, S.F. (2000). The mass budgets of carbonyl sulfide, dimethyl sulfide, carbon disulfide and hydrogen sulfide. Atmos. Environ. 34: 761–779. 31. Kettle, A.J. et al. (2001). Assessing the flux of different volatile sulfur gases from the ocean to the atmosphere. J. Geophys. Res. 106: 12193–12209. 32. Uher, G. and Andreae, M.O. (1997). Photochemical production of carbonyl sulfide in North Sea water: A process study. Limnol. Oceanogr. 42: 432–442. 33. Ulsh¨ofer, V.S., Fl¨ock, O.R., Uher, G., and Andreae, M.O. (1996). Photochemical production and air-sea exchange of carbonyl sulfide in the eastern Mediterranean Sea. Mar. Chem. 53: 25–39.

15. Vanraaphorst, W. et al. (1992). Nitrogen cycling in 2 types of sediments of the southern North-Sea (frisian front, broad fourteens)—field data and mesocosm results. Neth. J. Sea Res. 28: 293–316.

34. Ulshofer, V.S., Uher, G., and Andreae, M.O. (1995). Evidence for a winter sink of atmospheric carbonyl sulfide in the northeast Atlantic Ocean. Geophys. Res. Lett. 22: 2601–2604.

16. Naqvi, S.W.A. et al. (1998). Budgetary and biogeochemical implications of N2 O isotope signatures in the Arabian Sea. Nature 394: 462–464.

35. Weiss, P.S., Johnson, J.E., Gammon, R.H., and Bates, T.S. (1995). A reevaluation of the open ocean source of carbonyl sulfide to the atmosphere. J. Geophys. Res. 100: 23083–23092.

17. Suntharalingam, P. and Sarmiento, J.L. (2000). Factors governing the oceanic nitrous oxide distribution: Simulations with an ocean general circulation model. Glob. Biogeochem. Cyc. 14: 429–454. 18. Barnes, J. and Owens, N.J.P. (1998). Denitrification and nitrous oxide concentrations in the Humber estuary, UK, and adjacent coastal zones. Mar. Poll. Bul. 37: 247–260. 19. Dong, L.F., Nedwell, D.B., Underwood, G.J.C., Thornton, D.C.O., and Rusmana, I. (2002). Nitrous oxide formation in the Colne estuary, England: The central role of nitrite. Appl. Environ. Microbiol. 68: 1240–1249. 20. Seitzinger, S.P. and Kroeze, C. (2000). Global distribution of N2 O emissions from aquatic systems: natural emissions and anthropogenic effects. Chenmosphere 2: 267–279. 21. Lamontagne, R.A., Swinnerton, J.W., Linnenbom, V.J., and Smith, W.D. (1973). Methane concentrations in various marine environments. J. Geophys. Res. 78: 5317–5324. 22. Upstill-Goddard, R.C., Barnes, J., and Owens, N.J.P. (1994). Nitrous oxide and methane during the 1994 SW monsoon in the Arabian Sea/noerthwestern Indian Ocean. J. Geophys. Res. 104: 30,067–30,084. 23. Upstill-Goddard, R.C., Barnes, J., Frost, T., Punshon, S., and Owens, N.J.P. (2000). Methane in the southern North Sea: Low-salinity inputs, estuarine removal, and atmospheric flux. Glob. Biogeochem. Cyc. 14: 1205–1217. 24. Judd, A.G. (2003). The global importance and context of methane escape from the seabed. Geo-Marine Lett. 23: 147–154. 25. Kvenvolden, K.A., Lorenson, T.D., and Reeburgh, W.S. (2001). Attention turns to naturally occurring methane seepage. EOS 82: 457. 26. Charlson, R.J., Lovelock, J.E., Andreae, M.O., and Warren, S.G. (1987). Oceanic phytoplankton, atmospheric sulphur, cloud albedo and climate. Nature 326: 655–661. 27. Turco, R.P., Whitten, R.C., Toon, O.B., Pollack, J.B., and Hamill, P. (1980). OCS, stratospheric aerosols and climate. Nature 283: 283–286. 28. Chin, M. and Davies, D.D. (1995). A reanalysis of carbonyl sulphide as asource of stratospheric background sulphur aerosol. J. Geophys. Res. 100: 8993–9005. 29. Kettle, A.J. et al. (1999). A global database of sea surface dimethylsulfide (DMS) measurements and a procedure to

PACIFIC MARINE ENVIRONMENTAL LABORATORY—30 YEARS OF OBSERVING THE OCEAN NOAA—Pacific Marine Environmental Laboratory

Sept. 29, 2003—Although the NOAA Pacific Marine Environmental Laboratory in Seattle, Wash., celebrates its 30th anniversary this year, its staff has spent 43 years at sea. The figure of 15,654 days at sea was one of the many facts presented during the lab’s anniversary celebration in August. That, along with 1,290 published journal articles and 352,000,000 hits on the PMEL Web page indicate that there’s a lot going on out on Sand Point. For two-thirds of its life, the lab has been under the direction of Eddie Bernard. An oceanographer by training, Bernard became director in 1983, a decade after the former Pacific Oceanographic Laboratory became PMEL. ‘‘We have dedicated people at PMEL who devote a lot of energy and creativity to the work we do,’’ he said. NATIONAL TSUNAMI MITIGATION PROGRAM Some of that creativity and energy became evident when in 1994 the U.S. Senate asked NOAA to come up with a plan to reduce the risk of tsunamis to coastal residents. What resulted was the National Tsunami Hazard Mitigation Program, chaired by Bernard and composed of representatives from federal, state and local agencies from West Coast states, Alaska and Hawaii, working to save lives and property. ‘‘The National Tsunami Mitigation Program initiated by PMEL is a unique and effective partnership,’’ said Rich Eisner of the California Governor’s This article is a US Government work and, as such, is in the public domain in the United States of America.

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Office of Emergency Services, one of the program members. ‘‘The integration of science and mitigation policy, the warning centers, and local emergency management, and the application of new technologies fostered by PMEL have been successful beyond expectations.’’ Among the technological innovations is the system of buoys along the West Coast that serve as warning devices, or, as Bernard calls them, ‘‘tsunameters.’’ The tsunami program also includes a public education component that teaches coastal residents what to do in case of a possible tsunami. Signs now indicate evacuation routes and some coastal communities have been designated ‘‘TsunamiReady’’ for their efforts to educate and protect their residents. UNDERWATER VOLCANOES AND VENTS As one of NOAA’s ‘‘wet’’ labs, PMEL focuses on a variety of ocean issues. When underwater volcanoes or vents, were first discovered in the Galapagos Islands 26 years ago, PMEL was among the first to start investigating these unusual underwater communities, where unique marine life thrive on the chemical soup spewed from the sea floor. ‘‘We may be taking drugs in the future made of enzymes that are more compatible with our bodies than synthetic compounds, which may have side effects,’’ Bernard said.

‘‘What’s spewing from the ocean floor could someday give us resistance to some new strains of infection.’’ FISHERIES OCEANOGRAPHY COORDINATED INVESTIGATIONS PROGRAM PMEL began as a ‘‘small research laboratory with emphasis on water quality and environmental impact issues’’ in the waters off the West Coast extending to the equatorial Pacific Ocean. It now has an international reputation in many areas, especially its ability to collect ocean data and to work collaboratively in projects that cover many disciplines. One example is the Fisheries Oceanography Coordinated Investigations program that assists in forecasting fish stocks to help ensure a reliable supply and lower costs to consumers. ‘‘In 1985, Eddie Bernard took a big risk,’’ said Doug DeMaster of the NOAA Marine Fisheries Service. That risk was offering to establish with the Alaska Fisheries Science Center and his counterpart, William Aron, a cutting-edge, applied

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relaying surface wind, sea surface temperature, upper ocean temperatures and currents, air temperature and relative humidity in real-time via satellite. ‘‘We knew we were onto something when we linked data from the TAO buoys to the Internet and attracted millions of hits from all over the world,’’ Bernard said. ‘‘All it takes is time, money and commitment.’’ UNDERWATER ACOUSTICAL MONITORING

science program across NOAA line offices. Eighteen years after its inception, NOAA’s FOCI has published more than 450 scientific articles and was awarded the Department of Commerce Bronze Medal in 2002 for ‘‘scientific achievements that have advanced fisheries oceanography and marine ecology and have contributed to building sustainable fisheries in the North Pacific.’’ DeMaster noted, ‘‘Today, if you attend a FOCI meeting, you cannot tell which scientists are from NOAA Research and which are from NOAA Fisheries. In 1985, it took vision and courage to blur the lines between line offices. Today, it seems only natural.’’ PACIFIC TROPICAL ATMOSPHERE OCEAN ARRAY Understanding the natural systems is a key element of the lab. ‘‘The ocean is dynamic, it moves all of the time,’’ Bernard said. ‘‘We’re now in the third generation of observing systems. In the equatorial Pacific, we have the world’s longest continuous time series of open ocean data—25 years.’’ The equatorial Pacific also proved to be the place to be if humans wanted early warning ˜ events. El Nino ˜ is a disruption of the of El Nino ocean-atmosphere system in the tropical Pacific having important consequences for weather around the globe. ˜ considered the most intense After the 1982–83 El Nino, in the 20th century, the challenge was given to develop some sort of early warning device so people could prepare ˜ for the devastating and beneficial aspects of an El Nino ˜ Once again, in 1994, PMEL and its counterpart, La Nina. harnessed the creativity and talent of dedicated scientists and came up with the Pacific Tropical Atmosphere Ocean (TAO) array, the world’s largest ocean observing system. Bobbing in the Pacific are 70 buoys measuring and

Always eager to hear what the Earth has to say, PMEL scientists also listen to the planet via underwater acoustical monitoring. Using a variety of methods, including underwater hydrophones, PMEL listens for seismic activity, marine mammals and ship traffic. The systems also have picked up some so-far unidentified sounds. ‘‘People tend to think the ocean is quiet beneath the surface,’’ said Christopher Fox, director of the ocean acoustics project. ‘‘But it’s pretty noisy down there.’’ Some things are easy to identify, Fox said, such as whales and ship traffic. But visitors to the ocean acoustics Web site can listen to such unidentified sounds that the lab has dubbed ‘‘Train,’’ ‘‘Upsweep,’’ ‘‘Whistle’’ and ‘‘Bloop.’’ After 30 years, PMEL knows that the Earth still holds countless tantalizing secrets. And PMEL scientists and staff are eager to unlock those secrets. ‘‘As the planet aspirates, it provides new opportunities,’’ Bernard

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said. ‘‘It’s an ongoing science experiment with enormous challenges and rewards.’’ RELEVANT WEB SITES NOAA Pacific Marine Environmental Laboratory Dr. Eddie Bernard, Director, Pacific Marine Environmental Laboratory NOAA National Tsunami Hazard Mitigation Program NOAA Vents Program Fisheries Oceanography Coordinated Investigations program NOAA Marine Fisheries Service NOAA Alaska Fisheries Science Center ˜ Theme Page NOAA El Nino ˜ Theme Page NOAA La Nina NOAA Pacific Tropical Atmosphere Ocean (TAO) Project NOAA Vents Program: Underwater Acoustical Monitoring NOAA’s ALASKA FISHERIES SCIENCE CENTER Ocean Explorer: Sounds in the Sea

MEDIA CONTACT Jana Goldman, NOAA Research, (301) 713–2483

SEAWATER TEMPERATURE ESTIMATES IN PALEOCEANOGRAPHY GIUSEPPE CORTESE Alfred Wegener Institute for Polar and Marine Research (AWI) Bremerhaven, Germany

BACKGROUND Climatic issues, such as global warming, greenhouse gases release into the atmosphere, and the role mankind plays in affecting the climate of our planet have recently gained international interest. As a result, political panels and decision-makers are starting to look with growing interest at the results of committees established with the purpose of analyzing past, present, and future climate change. One of these panels [Intergovernmental Panel on Climate Change (IPCC)], established by the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP), regularly publishes reports (available also online at http://www.grida.no/climate/ipcc tar/) intended for scientists, politicians, and anybody interested in and/or concerned by climate change. The most powerful tools currently available to the scientific community for the analysis and prediction of climate are computer models, which simulate the functioning of Earth as a complex system. These models differ based on which components of the climate system (atmosphere, ocean, biosphere, cryosphere, etc.) they include and account for, their spatial scale and degree of detail, and on the different sets of physicochemical equations they

use to describe and parameterize phenomena taking place at a subgrid spatial scale. Regardless of setup and characteristics, though, models should be benchmarked against an observational base (e.g., to test how well the model reproduces a known distribution of a climatic variable). Models are moreover usually initialized by a set of observations (to let the incorporated physics modify the starting distribution). Some of these datasets are readily available in the form of measurements performed over historic timescales: One of the best known examples is the atmospheric CO2 concentration curve measured at Mauna Loa, Hawaii, since the late 1950s (1). Other important climatic variables cannot be observed or measured directly, and indirect methods, so-called ‘‘proxies,’’ have been developed to obtain information on them. Some of the methods that estimate seawater temperature on geological timescales are described in the following. INTRODUCTION The heat balance of Earth is strongly affected, to a first approximation, by the amount of solar radiation reaching the top of the atmosphere. The motion of currents in the atmosphere and in the ocean redistributes this heat between low and high latitudes, as the low latitudes receive a higher amount of heat compared with the higher latitudes. The ocean can be regarded as the ‘‘thermostat’’ of such a heat machine, because water has a much higher heat capacity compared with air, and because the turnover time for the ocean (thousands of years) is several orders of magnitude higher than for the atmosphere (days). One of the main features of the large-scale circulation in the ocean is the formation of deep waters at high latitudes, in the Weddell and Ross Seas (around Antarctica), and in the Labrador and Greenland/Iceland Seas (in the northern North Atlantic), because of the cooling of enormous amounts of warm surface waters advected to these locations by ocean currents (e.g., the Gulf Stream in the North Atlantic). When these waters move to higher latitudes, they cool, become denser, and sink to the ocean depths, where they start a reversed journey, from high to low latitudes. During this cooling, they also release latent heat and moisture, which help to mitigate the climate of the coastal areas they fringe, including the whole of western Europe. Indications exist, from geological records and model simulations (2), that during glacial times, this oceanic overturning did not operate with the same intensity as today, and/or that the places where deep waters formed were displaced compared with today. As seawater temperature, together with salinity, determines the density of seawater (and therefore it strongly influences its circulation and sinking characteristics), a variety of methods have been developed to determine this important climatic variable in the distant, geological past. METHODS Sediment cores collected from the bottom of the World Ocean represent an ideal archive to trace the history of

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the ocean. Some of these cores can be accurately dated, and often they contain the fossilized remains of organisms that lived in past oceans, and reacted to changes in their characteristics. The most useful of these organisms, because of their high fossilization potential, species diversity, and sensitivity to a range of climatic variables, are micro- and nannofossils. As their name implies, these organisms range from nanometer to millimeter size and leave fossilizable body parts, with the most commonly used groups belonging to algae (diatoms, nannoplankton) and protozoans (radiolarians, foraminifera). Most species in these groups live close to the sea surface, and each of them is adapted to a particular set of sea surface water variables, including temperature, salinity, and macro- and micro-nutrient content. Several techniques have been developed to exploit this close link between species occurrences/abundances and past environmental variables. Our first global view of surface water temperatures in the ocean during the Last Glacial Maximum (ca. 18,000 years Before Present) came from one such technique, namely, Q-Mode Principal Component Analysis applied to foraminifer and radiolarian abundance data in sediment cores (3). Semiquantitative Floral/Faunal Estimates Some of the first attempts to obtain seawater temperature information from microfossil assemblages tried to derive this value directly from a formula. The latter was based on the presence/absence, in the fossil samples, of species having a well-known distribution in the modern ocean, and being representative of different climatic zones (e.g., equatorial, subtropical, temperate, etc.). This approach, initially developed for diatoms (4), has also been applied to radiolarians (5). Information on species diversities of modern planktonic foraminifera in the Indian Ocean have also been used, in the late 1970s, to estimate ocean paleotemperatures (6). Transfer Functions With the expansion of the knowledge about the biogeography of most plankton groups (and the ecological and environmental significance of many species), and the development of computers (allowing the implementation of more sophisticated algorithms and techniques), transfer functions made their breakthrough in paleoceanography. They were first described and applied to planktonic foraminifera by Imbrie and Kipp (7), who illustrated their utilization in paleoclimatology. The species assemblage present in a collection of modern sediment samples (calibration dataset), containing up to several hundreds of samples, is ‘‘simplified’’ into a limited number of faunal factors/assemblages. A multivariate regression is then used to calibrate these simplified assemblages to the desired environmental variable (e.g., surface seawater temperature) measured, in the water column, at the same locations where the surface sediment samples were recovered. The value of the environmental variable at a certain time in the past is estimated by calculating ‘‘pseudo-factors’’ for each of the past samples (i.e., the value the calibrated assemblages have in these samples) and replacing them in the calibration equation. One main

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assumption of this method is that the considered environmental variable (in our case, surface temperature) plays a major role in influencing the biogeographic distribution of the considered microfossil species, and that it is therefore responsible for most of the variance observed in the calibration dataset. Transfer functions have been successfully applied to past ocean surface temperature reconstructions by using planktonic foraminifera (8–14), radiolarians (15–22), and diatoms (23,24). Geochemical Methods Several methods have been recently developed to estimate past ocean temperatures by measuring chemical elements or organic compounds, which are either incorporated in the organism shell or produced during its life cycle. The general approach is to develop a calibration equation by growing the desired species in culture under a variety of environmental conditions, and measuring how its geochemical composition changes. Additionally, a calibration equation can also be obtained by analyzing extensive collections of recent sediments, covering areas where the environmental variables display a wide range. The resulting equation is then applied to fossil samples to derive the past value of the desired variable. Mg/Ca The relative amount of magnesium compared with calcium a certain planktonic foraminifera species incorporates in its test depends on temperature, and the Mg/Ca ratio can therefore also be used as a paleo-thermometer. The calibration equation is derived from laboratory culture studies, based on different species, including Globigerinoides sacculifer (25), Globigerina bulloides, and Orbulina universa (26). Revised calibrations and applications to geological records are being continuously developed (27–31). Another paleo-thermometer derived from elemental ratios in foraminifera tests is the Sr/Ca ratio (32). Alkenones Several species of nannoplankton, living in the shallower layer of the ocean (less than ca. 50 m depth), produce organic compounds named long-chain (C37 -C39 ) unsaturated ketones, also known as alkenones. The two species being responsible for most of the alkenone production are Emiliania huxleyi and Gephyrocapsa oceanica. Although it is still not clear what the function of such compounds is, they have become a very useful tool for the estimation of past seawater temperature. It has been demonstrated (33,34) that the three different varieties of the C37 unsaturated compounds (C37:2 , C37:3 , C37:4 ), characterized by 2, 3, or 4 double bonds, display abundance variations related to seawater temperature. The alkenone unsatu ration ratio (35), Uk 37 = [C37:2 ]/([C37:2 ] + [C37:3 ]), was calibrated to temperature (36) by growing E. huxleyi in culture under a range of temperatures. Since then, alkenones have been widely applied in paleoclimatology (37–45). Other Methods Other methods commonly used to estimate past ocean temperatures are as follows the modern analogue technique and its variations (46–51); artificial neural

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SEAWATER TEMPERATURE ESTIMATES IN PALEOCEANOGRAPHY

networks (52,53); and the δ 18 O isotopic composition of planktonic foraminifera (54–58). The study of the isotopic signal stored in corals, although covering shorter time intervals than marine sediment cores, provides excellent temporal resolution archives (down to a few weeks), which allow to analyze seasonal climate variability (59,60). BIBLIOGRAPHY 1. Keeling, C.D., Whorf, T.P., Wahlen, M., and van der Plicht, J. (1995). Interannual extremes in the rate of rise of atmospheric carbon dioxide since 1980. Nature 375: 666–670. 2. Ganopolski, A. and Rahmstorf, S. (2001). Rapid changes of glacial climate simulated in a coupled climate model. Nature 409: 153–158. 3. CLIMAP. (1976). The surface of the ice-age Earth. Science 191: 1131–1137. 4. Kanaya, T. and Koizumi, I. (1966). Interpretation of diatom thanatocoenoses from the North Pacific applied to a study of core V20-130 (studies of a deep-sea core V20-120, part IV). Sci. Rep. Tohoku Univ. Ser. 2. 37: 89–130. 5. Nigrini, C. (1970). Radiolarian assemblages in the North Pacific and their application to a study of Quaternary sediments in core V20-130. Memoir of the Geological Society of America 126: 139–183. 6. Williams, D.F. and Johnson, W. (1975). Diversity of recent planktonic foraminifera in the southern Indian Ocean and late Pleistocene paleotemperatures. Quaternary Res. 5: 237–250. 7. Imbrie, J. and Kipp, N.G. (1971). A new micropaleontological method for quantitative paleoclimatology: Application to a late Pleistocene Caribbean core. In: Late Cenozoic Glacial Ages. K. Turekian (Ed.). Yale University Press, New Haven, CT, pp. 71–181. 8. CLIMAP. (1981). Seasonal Reconstructions of the Earth’s Surface at the Last Glacial Maximum. Geological Society of America, Map and Chart Series MC-36. 9. CLIMAP. (1984). The Last Interglacial ocean. Quaternary Research 21: 123–224. 10. Mix, A.C. and Morey, A.E. (1996). Climate feedback and pleistocene variations in the atlantic south equatorial current. In: The South Atlantic: Present and Past Circulation. G. Wefer, W.H. Berger, G. Siedler, and D.J. Webb (Eds.). Springer-Verlag, Berlin, pp. 503–525. 11. Ortiz, J.D. and Mix, A.C. (1997). Comparison of Imbrie-Kipp transfer function and modern analog temperature estimates using sediment trap and core top foraminiferal faunas. Paleoceanography 12(2): 175–190. 12. Mix, A.C., Morey, A.E., Pisias, N.G., and Hostetler, S.W. (1999). Foraminiferal faunal estimates of paleotemperature: Circumventing the no-analog problem yields cool ice age tropics. Paleoceanography 14: 350–359. 13. Feldberg, M.J. and Mix, A.C. (2002). Sea-surface temperature estimates in the Southeast Pacific based on planktonic foraminiferal species; modern calibration and Last Glacial Maximum. Marine Micropaleontol. 44: 1–29. 14. Niebler, H.S. et al. (2003). Sea-surface temperatures in the Equatorial and South Atlantic Ocean during the Last Glacial Maximum (23-19 ka). Paleoceanography 18: 1069. 15. Moore, T.C., Jr. (1973). Late Pleistocene-Holocene oceanographic changes in the northeastern Pacific. Quaternary Res. 3(1): 99–109. 16. Morley, J.J. (1979). A transfer function for estimating paleoceanographic conditions, based on deep-sea surface

distribution of radiolarian assemblages in the South Atlantic. Quaternary Res. 12: 381–395. 17. Pisias, N.G., Roelofs, A., and Weber, M. (1997). Radiolarianbased transfer functions for estimating mean surface ocean temperatures and seasonal range. Paleoceanography 12(3): 365–379. 18. Bjørklund, K.R., Cortese, G., Swanberg, N., and Schrader, H.J. (1998). Radiolarian faunal provinces in surface sediments of the Greenland, Iceland and Norwegian (GIN) Seas. Marine Micropaleontology 35: 105–140. 19. Abelmann, A., Brathauer, U., Gersonde, R., Sieger, R., and Zielinski, U. (1999). Radiolarian-based transfer function for the estimation of sea surface temperatures in the Southern Ocean (Atlantic sector). Paleoceanography 14(3): 410–421. 20. Brathauer, U. and Abelmann, A. (1999). Late quaternary variations in sea surface temperatures and their relationship to orbital forcing recorded in the Southern Ocean (Atlantic sector). Paleoceanography 14(2): 135–148. 21. Cortese, G. and Abelmann, A. (2002). Radiolarian-based paleotemperatures during the last 160 kyrs at ODP Site 1089 (Southern Ocean, Atlantic Sector). Palaeogeography, Palaeoclimatology, Palaeoecology 182(3–4): 259–286. 22. Dolven, J.K., Cortese, G., and Bjørklund, K.R. (2002). A high-resolution radiolarian-derived paleotemperature record for the Late Pleistocene-Holocene in the Norwegian Sea. Paleoceanography 17(4): 1072. 23. Koc-Karpuz, N. and Schrader, H.J. (1990). Surface sediment diatom distribution and Holocene paleotemperature variations in the Greenland, Iceland and Norwegian Sea. Paleoceanography 5(4): 557–580. ¨ 24. Zielinski, U., Gersonde, R., Sieger, R., and Futterer, D. (1998). Quaternary surface water temperature estimations: Calibration of a diatom transfer function for the Southern Ocean. Paleoceanography 13: 365–383. ¨ 25. Nurnberg, D., Bijma, J., and Hembelen, C. (1996). Assessing the reliability of magnesium in foraminiferal calcite as a proxy for water mass temperatures. Geochim. Cosmochim. Acta 60: 803–814. 26. Lea, D.W., Mashiotta, T.A., and Spero, H.J. (1999). Controls on magnesium and strontium uptake in planktonic foraminifera determined by live culturing. Geochim. Cosmochim. Acta 63: 2369–2379. 27. Hastings, D.W., Russell, A.D., and Emerson, S.R. (1998). Foraminiferal magnesium in G. sacculifer as a paleotemperature proxy in the equatorial Atlantic and Caribbean surface oceans. Paleoceanography 13(2): 161–169. 28. Mashiotta, T.A., Lea, D.W., and Spero, H.J. (1999). Glacial– interglacial changes in Subantarctic sea surface temperature and d18O-water using foraminiferal Mg. Earth Planetary Sci. Lett. 170: 417–432. ¨ ¨ 29. Nurnberg, D., Muller, A., and Schneider, R.R. (2000). Paleosea surface temperature calculations in the equatorial east Atlantic from Mg/Ca ratios in planktic foraminifera: A comparison to sea surface temperature estimates from  Uk 37 , oxygen isotopes, and foraminiferal transfer function. Paleoceanography 15(1): 124–134. 30. Dekens, P.S., Lea, D.W., Pak, D.K., and Spero, H.J. (2002). Core top calibration of Mg/Ca in tropical foraminifera: Refining paleotemperature estimation. Geochem. Geophys. Geosyst. 3(4): 10.1029/2001GC000200. 31. Lea, D.W., Pak, D.K., Peterson, L.C., and Hughen, K.A. (2003). Synchroneity of tropical and high-latitude Atlantic temperatures over the last glacial termination. Science 301: 1361–1364.

PHYSICAL OCEANOGRAPHY 32. Cronblad, H.G. and Malmgren, B.A. (1981). Climatically controlled variation of Sr and Mg in Quaternary planktonic foraminifera. Nature 291: 61–64. 33. Brassell, S.C., Eglinton, G., Marlowe, I.T., Pflaumann, U., and Sarnthein, M. (1986). Molecular stratigraphy: A new tool for climatic assessment. Nature 320: 129–133. 34. Prahl, F.G., Collier, R.B., Dymond, J., Lyle, M., and Sparrow, M.A. (1993). A biomarker perspective on prymnesiophyte productivity in the northeast Pacific Ocean. Deep-Sea Res. I 40: 2061–2076. ¨ 35. Prahl, F.G., Muhlhausen, L.A., and Zahnle, D.L. (1988). Further evaluation of long-chain alkenones as indicators of paleoceanographic conditions. Geochim. Cosmochim. Acta 52: 2303–2310. 36. Prahl, F.G. and Wakeham, S.G. (1987). Calibration of unsaturation patterns in long-chain ketone compositions for palaeotemperature assessment. Nature 330: 367–369. 37. Lyle, M.W., Prahl, F.G., and Sparrow, M.A. (1992). Upwelling and productivity changes inferred from a temperature record in the central equatorial Pacific. Nature 355: 812–815. 38. Rostek, F.G. et al. (1993). Reconstructing sea surface temperature and salinity using δ 18 O and alkenone records. Nature 364: 319–321. 39. Zhao, M., Rosell, A., and Eglinton, G. (1993). Comparison of two Uk 37 -sea surface temperature records for the last climatic cycle at ODP Site 658 from the sub-tropical Northeast Atlantic. Palaeogeography, Palaeoclimatology, Palaeoecology 103: 57–65. 40. Ohkouchi, N., Kawamura, K., Nakamura, T., and Taira, A. (1994). Small changes in the sea surface temperature during the last 20,000 years: molecular evidence from the western tropical Pacific. Geophys. Res. Lett. 21: 2207–2210. 41. Sikes, E.L. and Keigwin, L.D. (1994). Equatorial Atlantic sea  surface temperature for the last 30 kyr: A comparison of Uk 37 , 18 δ O, and foraminiferal assemblage temperature estimates. Paleoceanography 9(1): 31–45. ¨ 42. Schneider, R.R., Muller, P.J., and Ruhland, G. (1995). Late quaternary surface circulation in the east equatorial South Atlantic: evidence from alkenone sea surface temperatures. Paleoceanography 10(2): 197–219. ¨ 43. Schneider, R.R., Muller, P.J., Ruhland, G., Meinecke, G., Schmidt, H., and Wefer, G. (1996). Late quaternary surface temperatures and productivity in the East-Equatorial South Atlantic: Response to changes in Trade/Monsoon wind forcing and surface water advection. In: The South Atlantic: Present and Past Circulation. G. Wefer, W.H. Berger, G. Siedler, and D.J. Webb (Eds.). Springer-Verlag, Berlin, pp. 527–551. ¨ 44. Muller, P.J., Cepek, K., Ruhland, G., and Schneider, R.R. (1997). Alkenone and coccolithophorid species changes in Late Quaternary sediments from Walvis Ridge: Implications for the alkenone paleotemperature method. Palaeogeography, Palaeoclimatology, Palaeoecology 135: 71–96.

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48. Pflaumann, U., Duprat, J., Pujol, C., and Labeyrie, L. (1996). SIMMAX: A modern analog technique to deduce Atlantic sea surface temperatures from planktonic foraminifera in deep-sea sediments. Paleoceanography 11: 15–35. 49. Waelbroeck, C. et al. (1998). Improving past sea surface temperature estimates based on planktonic fossil faunas. Paleoceanography 13(3): 272–283. 50. Hale, W. and Pflaumann, U. (1999). Sea-surface temperature estimations using a Modern Analog Technique with foraminiferal assemblages from Western Atlantic Quaternary sediments. In: Use of Proxies in Paleoceanography—Examples from the South Atlantic. G. Fischer and G. Wefer (Eds.). Springer, Berlin, pp. 69–90. 51. Hendy, I.L. and Kennett, J.P. (2000). Dansgaard-Oeschger cycles and the California Current System: Planktonic foraminiferal response to rapid climate change in Santa Barbara Basin, Ocean Drilling Program Hole 893A. Paleoceanography 15: 30–42. 52. Malmgren, B.A. and Nordlund, U. (1997). Application of artificial neural networks to paleoceanographic data. Palaeogeography, Palaeoclimatology, Palaeoecology 136: 359–373. 53. Malmgren, B.A., Kucera, M., Waelbroeck, C., and Nyberg, J. (2001). Comparison of statistical and artificial neural network techniques for estimating past sea-surface temperatures from planktonic foraminifer census data. Paleoceanography 16(5): 520–530. 54. Emiliani, C. (1955). Pleistocene temperatures. J. Geol. 63: 538–578. 55. Shackleton, N.J. and Opdyke, N.D. (1973). Oxygen isotope and palaeomagnetic stratigraphy of equatorial Pacific Core V28-238: Oxygen isotope temperatures and ice volumes on a 105 year and 106 year scale. Quaternary Res. 3: 39–55. 56. Broecker, W.S. (1986). Oxygen isotope constraints on surface ocean temperatures. Quaternary Research 26: 121–134. ¨ 57. Mulitza, S., Durkoop, A., Hale, W., Wefer, G., and Niebler, H.S. (1997). Planktonic foraminifera as recorders of past surface-water stratification. Geology 25: 335–338. 58. Bemis, B.E., Spero, H.J., Bijma, J., and Lea, D.W. (1998). Reevaluation of the oxygen isotopic composition of planktonic foraminifera: Experimental results and revised paleotemperature equations. Paleoceanography 13(2): 150–160. 59. Felis, T. et al. (2000). A coral oxygen isotope record from the northern Red Sea documenting NAO, ENSO, and North Pacific teleconnections on Middle East climate variability since the year 1750. Paleoceanography 15: 679–694. 60. Nyberg, J., Winter, A., Malmgren, B., and Christy, J. (2001). Surface temperatures in the eastern Caribbean during the 7th century AD average up to 4 ◦ C cooler than present. Eos Trans. AGU 82(47).

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¨ ¨ 45. Ruhlemann, C., Mulitza, S., Muller, P.J., Wefer, G., and Zahn, R. (1999). Warming of the tropical Atlantic Ocean and slowdown of thermohaline circulation during the last deglaciation. Nature 402: 511–514.

Pacific Fisheries Environmental Laboratory, NOAA

46. Hutson, W.H. (1980). The Agulhas Current during the late Pleistocene: analysis of modern faunal analogs. Science 207: 64–66.

A great deal of the patterns and fluctuations observed in our living marine resources are attributable to the impact of physical processes in the environment on marine

47. Prell, W.L. (1985). The Stability of Low Latitude Sea Surface Temperatures: An Evaluation of the CLIMAP Reconstruction with Emphasis on the Positive SST Anomalies. Rep. TR 025 U.S. Dept. of Energy, Washington, DC, pp. 1–60.

This article is a US Government work and, as such, is in the public domain in the United States of America.

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ecosystems and their components. For this reason, PFEL places a strong emphasis on research that examines the role of the physical environmental variability on marine ecosystems in general and commercially important fish stocks specifically. The objectives of the physical oceanography task are: • perform research on the temporal and spatial scales of environmental variability in eastern boundary current systems in relation to other marine ecosystems • provide environmental input to SWFSC research programs, particularly the coastal groundfish program • provide high quality marine information to the research community. Research is performed at PFEL which integrates environmental and biological data sets, investigating the linkages between environmental variability and fluctuations in the abundance and distribution of marine populations on a continuum of scales (from global, basin-wide spatial scales to the scale of local upwelling centersand on time scales from decades down to days). Physical oceanography research is directed to: • large-scale climatic variability • environment/recruitment relationships in eastern boundary current ecosystems • mesoscale (smaller scale) processes affecting coastal circulation and fisheries recruitment Examples of research on the large-scale variability include studies of recurring temperature changes off the west coast of the U. S. and their effects on groundfish recruitment, and the investigation of environmental changes in the California Current region associated with recent ENSO events. Much of the mesoscale research focuses on relating environmental variability on day-to-year and 5–100 nm scales to patterns and events in the life history of groundfish (e.g., recruitment success). The physical oceanography research program is linked closely to those of the other tasks at PFEG and to research programs at the other SWFSC labs. PFEG scientists also are involved in numerous cooperative studies with oceanographers and

fisheries scientists at many federal and state government, academic and privately supported research institutions. Expertise in physical oceanography at PFEG and the linkages to the Navy’s Fleet Numerical Meteorology and Oceanography Center (FNMOC) and Naval Postgraduate School, as well as numerous other government, academic, and private research facilities, has historically meant that this task serves regionally, nationally and internationally as a resource to other ocean scientists. Within the SWFSC, many cooperative research programs have been developed and planned. As an example, the task provides physical oceanographic expertise to the Tiburon Laboratory Rockfish Recruitment surveys each spring, to relate ocean variability off central California to rockfish recruitment. PFEG physical oceanographers are asked frequently to attend workshop and present seminars as experts on environmental-fishery linkages, and represent SWFSC, NMFS and NOAA on numerous committees and working groups.

COASTAL WATER POLLUTANTS UPADHYAYULA V. K. KUMAR Choa Chu kang Ave-4 Singapore

POLLUTANT INPUT INTO THE MARINE ENVIRONMENT Among all the diversity of human activities and sources of pollution, we can distinguish three main ways that pollutants enter the marine environment: • direct discharge of effluents and solid wastes into the seas and oceans (industrial discharge, municipal waste discharge, coastal sewage, and others); • land runoff into the coastal zone, mainly from rivers; • atmospheric fallout of pollutants transferred by the air mass onto the sea surface. Certainly, the relative contribution of each of these channels to the combined pollution input into the sea

COASTAL WATER POLLUTANTS

will be different for different substances and in different situations. At present, the signs and consequences of human activity can be found everywhere on Earth. One of the typical features of marine pollution is global spreading of a number of contaminants. Numerous data undoubtedly indicate the existence of a large-scale (global) field of background contamination of the hydrosphere. Another important feature of marine pollution is the existence of increased pollution levels in the enclosed seas and coastal waters, compared with the open ocean. Contamination levels also increase during the transition from the southern parts of all oceans to the north, where the main industrial centers and main pollution sources are concentrated. Besides the general distribution pattern of pollution sources, there are two other factors explaining the relative stability of global pollutant distribution in the world ocean: the relative confinement of large-scale water circulation within the limits of each hemisphere and the predominance of the zonal transport of the traces in the atmosphere. Another distinctive and repeatedly registered feature of the general picture of contaminant distribution in the marine environment is their localization at the water–atmosphere and water–bottom sediment boundaries. Practically everywhere and for all trace components (primarily for oil hydrocarbons), their concentrations are considerably (usually hundreds and thousands of times) higher in the surface microlayer of water and in the upper layer of bottom sediments. These boundaries provide the biotopes for the communities of hyponeuston and benthos, respectively. The existence of elevated levels of contaminants in zones of high bioproductivity is extremely alarming ecologically. These zones include the water layer up to 100 m from the water surface (photic layer) and boundaries of natural environments (water–atmosphere and water–bottom sediment, as previously mentioned), as well as enclosed seas, estuaries, and coastal and shelf waters. In particular, in shelf and coastal zones, which occupy 10% of the world ocean surface and less than 3% of its volume, the most intense processes of bioproduction, including the self-reproduction of the main living resources of the sea, take place. The main press of anthropogenic impact is also concentrated here. The number and diversity of pollution components is growing as well. Contaminants that are globally distributed are combined here with hundreds and thousands of ingredients of local and regional distribution. Most of these substances are wastes and discharges from different local industries and activities. Based on the extreme diversity of marine pollution components, the variety of their sources, the scales of distribution, and the degree of hazards, these pollutants can be classified in different ways, depending on their composition, toxicity, persistence, sources, volumes, and so on. TYPES AND FORMS OF WATER POLLUTION Water pollution is attributed to various sources and can be broadly divided into three categories: domestic, industrial, and radioactive wastes, which can be categorized in

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the following forms: (1) thermal pollution; (2) the addition of pathogenic organisms, leading to public health hazard; (3) oil pollution; (4) the addition of inert, insoluble mineral material; (5) the addition of biodegradable organic material that will result in the depletion or complete removal of dissolved oxygen; (6) toxicity due to the presence of synthetic organic compounds and salts of heavy metals; (7) enhanced eutrophication; (8) acid deposition or discharges; and (9) radioactivity. Domestic Sewage The objectionable features of domestic sewage are its population of pathogenic bacteria; its high content of organic matter, which gives it a high oxygen demand; its nutrient content, which gives it the potential of supporting large populations of algae and other plants, which in turn may be as objectionable as the sewage itself; and the obvious aesthetics. The first and last of these can be overcome by proper treatment in biological sewage treatment plants, but the effluent from these plants is generally rich in nutrients. So, the effluent discharged into nearby inshore waters may result in large objectionable weed crops and other plants. An additional difficulty of disposing of domestic sewage and even the effluents from sewage treatment plants in the sea is that the density of the sewage is invariably less than that of seawater. Thus, the sewage tends to float on the surface unless introduced in a region of strong currents, will mix with seawater, and is diluted only slowly. Industrial Wastes These can be highly varied in composition and present a variety of special problems. The wastes may be toxic to plants or animals. They may be highly acidic or basic. If they contain large quantities of organic matter, their BOD may be objectionably high. Surface-active ingredients such as detergents may cause objectionable foaming or disrupt normal bacterial populations. The settable chemicals tend to settle to the seabed, react with mineral content there, and change the entire infrastructure of the seabed itself, which is causing accumulation of heavy metals in the sediments of several seas. Pathogens A variety of pathogenic organisms, including viruses, bacteria, protozoa, and parasitic worms, exist in seawater and can cause diseases in plants, animals, and people. Impacts include human illness, seafood contamination, and recreational beach closures. Pathogens are discharged to coastal waters through both point and nonpoint sources, especially from insufficiently treated sewage that is released from septic systems on land and on ships and from agriculture and storm water runoff. Higher concentrations tend to occur after storms and related overflow of sewer systems, making it difficult to interpret trends and temporal fluctuations. Nutrients Important parameters for monitoring nutrient pollution in coastal waters include the following: nitrogen and

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phosphorus concentrations, maximum bottom dissolved oxygen levels, extent and duration of anoxic and hypoxic conditions, extent of SAV, chlorophyll-a concentrations, turbidity, and duration and extent of algal blooms (by type). Some parameters are important in assessing the vulnerability of an area to pollutants, such as nitrogen and phosphorus, or in determining baseline conditions of the area. Oil Petroleum residues can contaminate marine and coastal waters through various routes: accidental oil spills from tankers, pipelines, and exploration sites; regular shipping and exploration operations, such as exchange of ballast water; runoff from land; and municipal and industrial wastes. Although the main global impact is due to tar balls that interfere with recreational activities at beaches, the impact of petroleum hydrocarbon concentrations on marine organisms in the neuston zone in the ocean—particularly fish eggs and larvae—requires more attention. Large-scale oil spills from tankers often make the headlines; yet, nonpoint sources, such

as regular maritime transportation operations and runoff from land, are actually considered the main contributors to the total oil discharge into the ocean, although conclusive statistics are lacking. Runoff and routine maintenance of the oil infrastructure, it is estimated, account for more than 70% of the total annual oil discharge into the ocean. Both the number and amount of accidental oil spills have been monitored and seem to have declined in the past decade. A single catastrophic event can, however, influence the statistics significantly and have a localized, yet tremendous impact on the ecosystem. Tables 1 and 2 show the variety of oil pollution sources and give expert estimates of the scales of distribution and impact of each of these sources on the marine environment. Even though these estimates can vary up to one to two orders of magnitude (especially for natural oil sources, atmospheric input, and river runoff), the main anthropogenic flows of oil pollution into the marine environment come from land-based sources (refineries, municipal wastes, and river runoff) and transportation activity (tanker oil transportation and shipping). Polycyclic aromatic hydrocarbons (PAHs),

Table 1. Sources and Scale of Oil Pollution Input Into the Marine Environment Environment Types and Source of Input

Scale of Distribution and Impact

Hydrosphere

Atmosphere

Local

Regional

Global

+ +

− −

+ +

? +

− +

+

−

+

+

?

+

−

+

?

−

+ + + + −

+ − − − +

+ + + + +

? + − + +

− ? − ? ?

Natural: Natural seeps and erosion of bottom sediments Biosynthesis by marine organisms Anthropogenic: Marine oil transportation (accidents, operational discharges from tankers, etc.) Marine nontanker shipping (operational, accidental, and illegal discharges) Offshore oil production (drilling discharges, accidents, etc.) Onland sources: sewage waters Onland sources: oil terminals Onland sources: rivers, land runoff Incomplete fuel combustion

Note: +, −, and ? mean, respectively, presence, absence, and uncertainty of corresponding parameters.

Table 2. Estimates of Global Inputs of Oil Pollution Into the Marine Environment (Thousands Tons/Year of Oil Hydrocarbon) 1981∗

1985∗ ∗ ∗

1990∗ ∗ ∗

Source

1973∗

1979∗∗

Land-based sources: Urban runoff and discharges Coastal refineries Other coastal effluents

2,500 200 –

2,100 60 150

1,080 (500–1,250) 100 (60–600) 50 (50–200)

34% – –

1,175 (50%) – –

Oil transportation and shipping: Operational discharges from tankers Tanker accidents Losses from nontanker shipping

1,080 300 750

600 300 200

700 (400-1,500) 400 (300–400) 320 (200–600)

45% – –

564 (24%) – –

Offshore production discharges

80

60

50 (40–60)

2%

47 (2%) 306 (13%)

Atmospheric fallout

600

600

300 (50–500)

10%

Natural seeps

600

600

200 (20–2,000)

8%

259 (11%)

Total discharges

6,110

4,670

3,200

100%

2,351

COASTAL WATER POLLUTANTS

especially benzo(a)pyrene, enter the marine environment mostly from atmospheric deposition. Table 2 illustrates the general trend of declining total input of oil pollution into the world ocean over the years. The global situation reflected in this table certainly may differ at the regional level, which depends on natural conditions, the degree of coastal urbanization, the population density, industrial development, navigation, oil and gas production, and other activities. For example, in the North Sea, offshore production input reached 28% of the total input of oil pollution in last decade, instead of the ‘‘modest’’ 2% on the world scale shown in Table 2, which equaled the annual input of more than 23,000 tons of oil products at the background of their general changeable flow of 120,000–200,000 tons a year in the North Sea. One can expect similar situations in other regions of intensive offshore oil and gas development, for example, in the Gulf of Mexico, Red Sea, Persian Gulf, and Caspian Sea. The persistent pollution in oil production areas in the Caspian Sea or the amounts of annual discharges (about 40 million tons of produced waters polluted by oil products) during offshore drilling in the Gulf of Mexico. At the same time, no reliable balance estimates exist for these regions. The continental shelf of the Gulf of Mexico is also distinctive for intense seepage of natural liquid and gaseous hydrocarbons, which can lead to formation of oil slicks and tar balls on the sea surface, which makes assessing and identifying anthropogenic oil pollution more difficult. In any case, the input of oil hydrocarbons from natural sources into the Gulf of Mexico is larger than in many other areas. In the Baltic Sea, the Sea of Azov, and the Black Sea, the leading role in oil input most likely belongs to landbased sources, which are dominated by river inflow. The Danube River alone annually brings about 50,000 tons of oil to the Black Sea, half of the total oil input of about 100,000 tons. Observations in the Caribbean basin, where annually up to 1 million tons of oil enter the marine environment, showed that about 50% of this amount came from tankers and other ships. In the Bay of Bengal and the Arabian Sea, oil pollution inputs from tanker and other ship discharges equal, respectively, 400,000 tons and 5 million tons of oil a year. The most intense tanker traffic exists in the Atlantic Ocean and its seas, which accounts for 38% of international maritime oil transportation. In the Indian and Pacific Oceans, this portion is, respectively, 34% and 28%. Enforcing stricter requirements on activities accompanied by oil discharges led to a global decline of oil pollution inputs in the marine environment mentioned before. A number of dramatic events show the vulnerability of making an optimistic prognosis about decreasing oil pollution at the regional and global levels. For instance, catastrophic large-scale events took place in the Persian Gulf during and after the 1991 Gulf War. Between 0.5 and 1 million tons of oil were released into coastal waters. Besides, products of combustion of more than 70 million tons of oil and oil products were emitted into the atmosphere. Another large-scale accident occurred in Russia in September–November 1994. About 100,000 tons of oil

99

were spilled on the territory of the Komi Republic, which threatened to cause severe oil pollution for the Pechora River basin and, possibly, Pechora Bay. It must be remembered that catastrophes, in spite of the obvious consequences and all the attention they attract, are inferior to other sources of oil pollution in their scales and degree of environmental hazard. Land-based, oil-containing discharges and atmospheric deposition of products of incomplete combustion can accordingly give 50% and 13% of the total volume of oil pollution input into the world ocean (see Table 2). These diffuse sources continuously create relatively low but persistent chronic contamination across huge areas. Many aspects of the chemical composition and biological impacts of these contaminants remain unknown. Persistent Organic Pollutants Persistent organic pollutants (POPs) consist of a number of synthetic compounds, including industrial polychlorinated biphenyl’s (PCBs); polychlorinated dioxins and furans; and pesticides, such as DDT, chlordane, and heptachlor, that do not exist naturally in the environment. A number of POPs often persist in the environment and accumulate through the food chain or in the sediment to a toxic level that is directly harmful to aquatic organisms and humans. The marine environment collects contaminants from the air, but also from ocean currents, rivers discharging into the ocean, and sea ice that transports POPladen particles. Figure 1 presents some examples of contaminant levels in seawater. Hexachlorocyclohexane dominates the picture, except for Russian waters where PCB levels are high, up to 15 nanograms per liter in the Kara Sea. These high levels seem to mirror the high input of PCBs from Russian rivers. Levels in seawater can also be used to shed light on the mechanisms that transport contaminants to the Arctic. Detailed measurements in the Bering and Chukchi Seas show that hexachlorocyclohexane levels in the water increase along a south–north gradient, which has been suggested as evidence for a cold-condensation theory; those semivolatile contaminants condense out of the atmosphere as temperatures drop. Less volatile contaminants, such as PCBs, DDT, and chlordane, were present at lower levels in the Bering and Chukchi Seas than in more temperate latitudes. Concentrations of organic contaminants in Arctic marine sediments are, in general, extremely low compared with freshwater sediments, and are ten to a hundred times lower than in the Baltic Sea. The most apparent geographic trends are that concentrations of PCBs, hexachlorocyclohexane, and hexachlorobenzene are higher closer to the shore along the Norwegian coast than in the open sea. They are also higher in gulfs and river mouths along the Russian coast and around Svalbard. Heavy Metals Heavy metals exist naturally in the environment, and it is sometimes difficult to distinguish variations developing from anthropogenic inputs and those from the

100

COASTAL WATER POLLUTANTS Annual nitrogen load to the Baltic Sea 11%

Annual phosphorus load to the Baltic Sea 11%

12%

10%

Sweden

2% 6%

6%

Baltic States* 12%

Sweden

8%

Finland

Finland

Baltic States*

18%

Poland

13%

Denmark

5%

Denmark Atmosphere

Atmosphere

33% 18%

N2 Fixation *Belarus, Estonia Latvia, Lithuania

Source : Helcom 1993

Poland Germany

Germany

35%

*Belarus, Estonia Latvia, Lithuania

Helcom. 1993. First assessment of the state of the coastal waters of the Baltic sea. Baltic sea Environ. Proc. No. 54, 160 pp.

Source : Helcom 1993

Figure 1. Nutrient release to coastal waters taking the Baltic Sea as an example.

natural hydrologic cycle and the atmosphere. Among the trace metals commonly monitored are cadmium, copper, mercury, lead, nickel, and zinc. When they accumulate through the food chain at moderate to high concentrations, some of these metals can affect the human nervous system. The marine environment receives heavy metals from atmospheric deposition, river runoff, and local pollution. The relative importance of these sources will differ between regions. For example, rivers carrying metal-laden sediments deposit almost their entire load in the shelf seas, and only a minor portion reaches the deep ocean. Natural sources of metals are important and, in many cases, it is found that they are the main source to the marine environment. Mining has contaminated ocean waters with several heavy metals. One documented example is in the fjord outside the Black Angel zinc mine in Greenland, where the levels of lead in the bottom water are up to 200 micrograms of lead per kilogram of water. These high lead levels are also reflected in seaweed, blue mussels, prawns, and in some fish; in capelin, lead levels are up to 5 micrograms per gram in the bone. However, no one has been able to document any biological effects in the fish. Cadmium levels in the water are also high, up to 2.5 micrograms per kilogram of water; but in contrast to lead, the animals in the fjord have cadmium levels close to background. The cryolite mine in Ivittuut in southern Greenland has also contaminated the nearby water. Lead levels of 18 micrograms per kilogram of water have been measured. At Strathcona Sound in northern Baffin Bay, a lead-zinc mine has released lead, making concentrations in the fjord water one to two orders of magnitude higher than background concentrations in the open ocean. Some of the lead has also been taken up by seaweed and crustaceans. Outside a lead-zinc mine in east Greenland, shorthorn sculpins also have elevated levels of lead, whereas the fish outside the cryolite mine on southern Greenland have not been affected.

The mines at Ivittuut and Strathcona Sound have also contaminated their respective fjords with cadmium, but the levels are much lower than those outside the Black Angel mine. At these sites, the cadmium is not affecting the local sediment, nor are elevated levels found in nearby plants and animals. Metal levels in Arctic Ocean water away from local sources are generally similar to global background levels. Today’s global lead concentrations in oceans are generally more than ten times higher than those in prehistoric times. The levels are consistently higher in surface waters than in deeper layers. One might expect the lead levels in the upper Arctic sediments to mirror this increased long-distance transport, but this does not seem to be the case. Recent seawater analyses from Pechora Bay and Kara and Laptev Seas show very high lead levels, ranging from 0.16 to 0.5 micrograms per kilogram of water. However, these data require confirmation before any conclusions are drawn. Filter-feeders such as mussels take up lead from sediment particles. The concentration increases slightly with increasing shell length, indicating a moderate accumulation as the mussel ages. However, lead levels are low in crustaceans as well as in fish. The highest levels, 0.05 micrograms per gram of liver, have been recorded in Orkdalsfjorden in Norway. Lead does not seem to accumulate in fish-eating birds or in marine mammals. In general, levels in marine mammals are low. Cadmium Levels are High in Marine Biota. Cadmium levels in seawater fall within what could be considered natural background levels. Moreover, there is no indication from sediments that the levels have increased from preindustrial times, nor have temporal trends been detected. An interesting phenomenon relating to cadmium is that its concentration increases farther away from the coast,

COASTAL WATER POLLUTANTS

101

Alpha-HCH in seawater, ng/liter 5 4 3 2 1 0 Chukchi sea Beaufort sea

Bering sea Okoisk sea

North pacific ocean

East china sea

Java sea

Figure 2. Alpha-hexachlorocyclohexane concentration in seawater increases from south to north, illustrating the cold-condensation effect (1).

which is probably connected with the change in salinity of the water. The result is that cadmium levels in both plants and animals are higher in the open ocean than in the inner region of large fjords, even when there are local sources contaminating the water. Cadmium accumulates with age in mussels and crustaceans. In general, the levels in crustaceans are higher than global background levels but show large variations. Mercury levels are high and may be increasing. Several sets of data indicate that mercury levels are higher in the upper layers of Arctic marine sediments than in the layers representing preindustrial inputs see the upper right diagram of Fig. 3. Mercury is enriched even in the marine sediments taken at the North Pole. Natural processes may have caused these profiles, but they could indicate that human activities have increased the environmental mobility of existing stores of mercury.

Radioactive Wastes These can somewhat be divided into high and low level wastes, depending on their activity. Radioactive wastes are characterized by losing their radioactivity with time. Some nuclides lose it quickly; others very slowly. A second consideration is that radioactive elements will enter the biological cycle and therefore the food web. High level radioactive wastes pose a complex problem in their disposal; the low level has been and is being disposed of directly in the sea. Reprocessing plants have added radionuclides to the sea. Spent nuclear fuel is often processed to recover plutonium. Water used in reprocessing contains a mix of different radionuclides, and some of this contaminated water has been released routinely into the sea. In Europe, three reprocessing plants are relevant to the Arctic because of transport of radionuclides by ocean

102

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0.000 0.0 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22.5 24 25 27.5 29 31 33.5 34 37.5

Figure 3. Mercury concentration at different depths in marine sediment cores (1).

0.020

0.040

0.060

Hg mg/kg 0.080

0.100

0.120

0.140

0.160

North pole Alesund Eastern hudson bay Central west greenland

Eastern hudson bay Central west greenland

North pole

Alesund

Depth cm

Figure 4 indicates the rates of liquid discharges from 1952 to 1992. Cesium-137 dominates. The peak of the release for most radionuclides was in the mid-tolate 1970s.

TBq/y 6000 5000 4000 3000 2000 1000 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 106

Ru

241

Pu

90

Sr

137

Cs AMAP

Figure 4. Discharges of beta-emitters from the Sellafield nuclear reprocessing plant, 1012 bequerels per year.

currents: Sellafield (formerly Windscale) in Cumbria on the northwest coast of England; La Hague near Cherbourg, France; and Dounreay in northeast Scotland. Sellafield has been the most important source of radionuclides to the Arctic marine environment because of the scale of its discharge. The effluent has been released into the sea and carried north by ocean currents. The releases, which started in 1952, are well documented.

Underwater Weapon Tests Have Contaminated Chernaya Bay. Chernaya Bay is a fjord inlet, connected to the Barents Sea, on the southwestern coast of Novaya Zemlya. The former Soviet Union used the bay to conduct underwater tests of nuclear bombs in 1955 and 1957 and in the vicinity of the bay in 1961. As a result of these detonations, the bottom sediments of the bay are contaminated by elevated levels of radioactive plutonium and cesium, as well as other radioactive isotopes. However, the mobility of radionuclides in sediment is low and may at present cause only insignificant exposure of people. Exposure of biota is unknown. Today, the inventory of plutonium in Chernaya Bay is similar to other sites of major plutonium contamination, such as the most contaminated areas of Bylot Sound (where a B-52 bomber crashed) and the Irish Sea in the vicinity of the Sellafield reprocessing plant. Three underground nuclear detonations were carried out by the United States on Amchitka Island in the Aleutian Islands in 1965, 1969, and 1971. These detonations caused radioactive contamination of deep groundwater and rock around the shot cavities. Long-term monitoring activity is planned for this site to 2025. In 1996, aboveground radioactive contamination was detected at the site.

COASTAL WATER POLLUTANTS MSr

Bq/m3 40

Greenland water Barents sea Kara sea

30

20

10

0 1960

1965

1970

1975

1980

1985

1990

1995

A major direct input of radionuclides into the marine environment has been from European nuclear reprocessing plants, particularly Sellafield on the shore of the Irish Sea. Currents transport the material along the Norwegian coast and into the Arctic Ocean. After 6 to 8 years, some of the contamination leaves the Arctic by way of the East Greenland Current, but much of it stays in the Arctic Basin much longer. Environmental radiocesium levels have been measured since the early 1970s. As can be seen in Fig. 6, the releases of cesium-137 from Sellafield are virtually mirrored in the levels found in the Barents Sea after a transport time of 4 to 5 years. The peak in concentration in the early 1980s is probably the highest level that has ever occurred in that area of the ocean. The Chernobyl accident in 1986 added cesium to the Arctic Ocean and continues to

Levels in seawater (Bq/m3) Releases from sellafield (TBq) 50 6000 East greenland current Barents sea Sellafield

40

4000 30 3000 20 2000 1000

do so via outflow from the Baltic Sea. Figure 6 shows the recent levels of cesium-137 in seawater around the Arctic. Strontium-90 has been measured in surface seawater collected around Greenland and the Barents Sea; see Fig. 5. During the past 35 years, levels in the waters around Greenland have decreased, approximately half was removed or decayed every 13.5 years. This value is probably representative of the Arctic Ocean as a whole. The highest levels of cesium-137 in people were recorded in the mid-1960s; see the Fig. 6. For the following 20 years, the human body burden decreased by a factor of 3 to 7. However, in 1986, the Chernobyl fallout changed the trend in areas directly affected by the accident. Assessment of Receiving Waters

Figure 5. Time trends of activity concentrations of strontium-90 in seawater.

5000

103

10

0 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 Figure 6. Releases of cesium-137 from Sellafield nuclear reprocessing plant (1012 bequerels per cubic meter).

The effects of the ocean waste disposal are the result of a complex relation between two variables, concentration and time. The effect of the oceanic environment on the effluent is of critical significance. After discharge to the ocean, the effluent experiences changes in its physical and microbiological properties, which vary, each point as a function of time. An accurate prediction of pollution conditions or environmental impact depends on knowledge of the oceanographic conditions in the area. These conditions vary in time and space. A significant and representative quantitative judgement requires refined statistical analysis. A statistical description of receiving coastal waters should be based on adequate observation of an entire area for a sufficiently long period of time (at least 1 year). The factors operating should be recorded simultaneously to provide a comprehensive picture of the physical and microbiological properties of the area. The data collected should enable probability distributions of the variables to be derived to select a coherent and suitable set of design parameters. Continuous and periodic records should be taken to cover all typical oceanographic conditions at stations strategically located at different sites and should record the following: (1) Currents (direction and speed) distributed in time/space to permit a comprehensive study of coastal water circulation patterns. (2) A continuous record of tides and winds in the area. (3) The density field obtained from time and space distribution of salinity and temperature enabling the stratification conditions of the coastal waters to be determined. (4) The waves recorded periodically, covering the most critical conditions and enabling a probability distribution of the wave characteristics (height, period, and direction) to be derived for structural design. (5) Periodic dispersion and diffusion experiments using dye tracers. (6) Simultaneously with the oceanographic survey a program on bacterial concentration decrease should be carried out, covering typical oceanographic conditions. The experiments should be made in situ,

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COASTAL WATER POLLUTANTS

preferably in the existing continuous sewage field. Simultaneously sampling for bacteria and dye tracer direction will enable bacterial die-off rates and dilution to be investigated and the derivation of bacterial concentration decrease from both these effects. During concentration decrease experiments, the water temperature, solar radiation, and other climatic data should be collected. Mainly tides and winds, to a lesser controlled extent by the density field, govern coastal currents near the shore. A comprehensive study of coastal circulation requires a continuous record of winds and tides and simultaneous measurements of vertical profiles of temperature, salinity, and currents. A detailed vector statistical analysis of the current field is an important requirement. The seasonal or climatological associations between oceanographic and meteorological data and in situ bacterial assays are of paramount importance; their interactions determine major design parameters. Statistical analysis of the sewage field is required to predict the seasonal variations in initial dilution and final height of the rise. This analysis should be based on simulations of alternative diffuser discharges at various density stratification conditions. Oceanic Processes To assess the oceanic equivalent dilution factors, the following formulations may be used. Initial Dilution. The initial dilution, RI, and terminal rise height, Ym , were estimated, assuming that the diffuser is a finite line source of buoyancy flux only, by the equation RI = FI · Ym where FI = f (F, θ )U/q; in which f (f , θ ) is an experimental factor, which depends on θ and a type of Froude number F = u3/B. The current and density stratification are the oceanographic variables that directly interface in the initial dilution. We may consider a critical stratification condition in which this interface extends to a constant depth and the dilution layer increases linearly with the bottom slope according to a relation of the type Ym = a + b(x − x0 ), where x is the distance from a horizontal plume perpendicular to the shore. The subsequent dilutions RM, represent a minor part of the overall receiving water reductions. Thus the total physical dilution can be evaluated as RF = RI · RM, RF = FI(1 + FMx)[a + b(x − x0 )] All soluble pollutants experience this composite dilution factor. Small particulate matter will also disperse proportionately. Floatable matter may disperse to a lesser extent, remaining visually detectable and liable to be carried to shore by currents and surface winds. The removal of this material is required, and an initial dilution of 100 is required to provide sufficient emulsification for these materials.

Dilution Equivalent to Bacterial Concentration Decreases. Most experiments on bacterial concentration decrease have been shown to fit Chick’s law very satisfactorily. C(t) = C0 · 10 − t/T90, where C0 = coliform concentration at the origin, and T90 = time required for 90% reduction. Thus the dilution equivalent to the concentration decrease may be computed directly from RB = C0 /C(x) = 10 x/X90 where X90 = u · T90 = distance required for the coliform concentration reduction of 90%.

Dilution Equivalent to Sedimentation. The disappearance rate of coliforms due to sedimentation of solids depends on the degree of removal in the treatment plant. Data collected by experts revealed the fact that T90 values decrease as the effluent TSS increases. Therefore, sedimentation effects are already incorporated in the field experimental results for the concentration decrease. Dilution Equivalent to Treatment. The relation between removal rates and corresponding factor RT is RT = 100/[100 − T (%)]. Dilution Equivalent to Disinfection. The dilution equivalent to disinfection is evaluated by the equation RD = 1/rd, where rd is the bacteria reduction factor. Chlorination of less treated sewage produces organic chlorine compounds, which are toxic and deleterious to the environment. Therefore, chlorination may compromise the already recognized ecologically beneficial effects of enrichment of coastal waters by the supply of nutrients and organic matter from those effluents. Overall Equivalent Dilution. Assuming that RS = 1, the overall equivalent dilution can be evaluated by the equation Rtotal = RT · RD · RI · RM(x) · RB(x) Rtotal = RR · f (F, θ )(bu/q)[a + b(x − x0 )] · [1 + (KL/bo )x] · 10 x/u · T90 For a given set of parameters, Rtotal = CE/CP, Q and the oceanic parameters are u(u, θ ), T90 and KL are the total equivalent approximation, a linear function of the diffuser length and an exponential quadratic function of the outfall length.

The Effect of Current. Separating the current factors including the current speed u from the above equation, a dilution function may be defined as Fu = u · 10 x/uT90 , which represents the effect of current on overall oceanic dilution. The figure given shows curves of Fu as a function of u for the various values of the parameter u90 = x/T90 , that is, the velocity for a 90% concentration decrease. It may be seen that the curves show ‘‘inflections’’ that have been connected by the line. The inflection increases as u90 decreases or as T90 increases. This inflection divides the graph into two domains:

COASTAL WATER POLLUTANTS

105

The initial dilution domain (linear) The concentration decrease dilution factor dilution factor domain (exponential).

Depending on the type of impact on water organisms, communities, and ecosystems, the pollutants can be grouped in the following order of increasing hazard:

For strong currents, the initial dilution is the dominant factor, and for a given T90 , the only way to increase Fu is by initial dilution mixing depth, which can be attained by increasing the outfall length. For light currents, the dilution factor equivalent to die-off dominates. Thus, the current data is collected, as it is useful in the design in

• substances that cause mechanical impacts (suspensions, films, solid wastes) that damage the respiratory organs, digestive system, and receptive ability; • substances that provoke eutrophic effects (e.g., mineral compounds of nitrogen and phosphorus, and organic substances) that cause mass rapid growth of phytoplankton and disturb the balance, structure, and functions of water ecosystems; • substances that have saprogenic properties (sewage with a high content of easily decomposing organic matter) that cause oxygen deficiency followed by mass mortality of water organisms and appearance of specific microflora; • substances causing toxic effects (e.g., heavy metals, chlorinated hydrocarbons, dioxins, and furans) that damage the physiological processes and functions of reproduction, feeding, and respiration; • substances with mutagenic properties (e.g., benzo(a)pyrene and other polycyclic aromatic compounds, biphenyls, radionuclides) that cause carcinogenic, mutagenic, and teratogenic effects.

1. 2. 3. 4.

analysis of coastal circulation hydrodynamics; prediction of initial dilution; prediction of far field dilution and transport; Prediction of waste field impaction probability.

Thus, a comprehensive oceanographic study is necessary to describe the characteristics of the receiving waters. Therefore, an adequate program of oceanographic investigation in situ, including bacterial concentration decrease, is obligatory. The existence of elevated levels of contaminants in zones of high bioproductivity is extremely alarming ecologically. These zones include the water layer up to 100 m from the water surface (photic layer) and boundaries of natural environments (water–atmosphere and water–bottom sediment, as previously mentioned) as well as enclosed seas, estuaries, and coastal and shelf waters. In particular, in shelf and coastal zones, which occurs in 10% of the world ocean surface and less than 3% of its volume, the most intense processes of bioproduction, including self-reproduction of the main living resources of the sea, take place. The main press of anthropogenic impact is also concentrated here.

EFFECTS OF POLLUTANTS ON MARINE HABITAT To estimate the hazard of different pollutants, we should take into account not only their hazardous properties, but other factors, too. These include the volumes of their input into the environment, the ways and scale of their distribution, the patterns of their behavior in water ecosystems, their ability to accumulate in living organisms, the stability of their composition, and other properties, such as the extreme diversity of marine pollution components, the variety of their sources, the scales of distribution, and the degree of hazards. Pollutants can be classified in different ways, depending on their composition, toxicity, persistence, sources, volumes, and so on. To analyze large-scale pollution and its global effects, it is common to distinguish groups of the most widespread pollutants, which include chlorinated hydrocarbons, heavy metals, nutrients, oil hydrocarbons, surface-active substances, and artificial radionuclides. These substances form the so-called background contamination that exists now any place in the hydrosphere.

Some of these pollutants (especially chlorinated hydrocarbons) cause toxic and mutagenic effects. Others (decomposing organic substances) lead to eutrophic and saprogenic effects. Oil and oil products are a group of pollutants that have complex and diverse composition and various impacts on living organisms—from physical and physicochemical damage to carcinogenic effects. Discharge of heated waters can change the structure and function of coastal marine communities. Impacts of fly ash from coal-fired power plants, hot salty water, and residual chlorine are also important. Dumping of fly ash in coastal waters and into the atmosphere has caused severe impacts on spinner dolphins and mangroves in an area of the south coast of India, and has reportedly changed the number of species of plankton. Effects of Marine Oil Spills Oil spills can have a serious economic impact on coastal activities and on those who exploit the resources of the sea. In most cases, such damage is temporary and is caused primarily by the physical properties of oil creating nuisance and hazardous conditions. The impact on marine life is compounded by toxicity and tainting effects resulting from the chemical composition of oil, as well as by the diversity and variability of biological systems and their sensitivity to oil pollution. Biological Effects of Oil. Simply, the effects of oil on marine life are caused by either the physical nature of the oil (physical contamination and smothering) or by its chemical components (toxic effects and accumulation leading to tainting). Marine life may also be affected by cleanup operations or indirectly through physical damage to the habitats in which plants and animals live.

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COASTAL WATER POLLUTANTS

The main threat posed to living resources by the persistent residues of spilled oils and water-in-oil emulsions (‘‘mousse’’) is physical smothering. The animals and plants most at risk are those that could come into contact with a contaminated sea surface: marine mammals and reptiles; birds that feed by diving or form flocks on the sea; marine life on shorelines; and animals and plants in mariculture facilities. The most toxic components in oil tend to be those lost rapidly through evaporation when oil is spilled. Because of this, lethal concentrations of toxic components leading to large-scale mortality of marine life are relatively rare, localized, and short-lived. Sublethal effects that impair the ability of individual marine organisms to reproduce, grow, feed, or perform other functions can be caused by prolonged exposure to a concentration of oil or oil components far lower than will cause death. Sedentary animals in shallow waters such as oysters, mussels, and clams that routinely filter large volumes of seawater to extract food are especially likely to accumulate oil components. Although these components may not cause any immediate harm, their presence may render such animals unpalatable if they are consumed by humans, due to the presence of an oily taste or smell, which is a temporary problem as the components that cause the taint are lost when normal conditions are restored. The ability of plants and animals to survive contamination by oil varies. The effects of an oil spill on a population or habitat must be viewed in relation to the stresses caused by other pollutants or by any exploitation of the resource. In view of the natural variability of animal and plant populations, it is usually extremely difficult to assess the effects of an oil spill and to determine when a habitat has recovered to its prespill state. In recognition of this problem, detailed prespill studies are sometimes undertaken to define the physical, chemical, and biological characteristics of a habitat and the pattern of natural variability. A more fruitful approach is to identify which specific resources of value might be affected by an oil spill and to restrict the study to meeting defined and realistic aims related to such resources. Impact of Oil on Specific Marine Habitats. Within each habitat, a wide range of environmental conditions prevails, and often there is no clear division between one habitat and another. Plankton is a term applied to floating plants and animals carried passively by water currents in the upper layers of the sea. Their sensitivity to oil pollution has been demonstrated experimentally. In the open sea, the rapid dilution of naturally dispersed oil and its soluble components, as well as the high natural mortality and patchy, irregular distribution of plankton, make significant effects unlikely. In coastal areas, some marine mammals and reptiles, such as turtles, may be particularly vulnerable to adverse effects from oil contamination because of their need to surface to breathe and to leave the water to breed. Adult fish that live in nearshore waters and juveniles in shallow

water nursery grounds may be at greater risk to exposure from dispersed or dissolved oil. The risk of surface oil slicks affecting the sea bed in offshore waters is minimal. However, restrictions on the use of dispersants may be necessary near spawning grounds or in some sheltered, nearshore waters where the dilution capacity is poor. The impact of oil on shorelines may be particularly great where large areas of rocks, sand, and mud are uncovered at low tide. The amenity value of beaches and rocky shores may require the use of rapid and effective cleanup techniques, which may not be compatible with the survival of plants and animals. Marsh vegetation shows greater sensitivity to fresh light crude or light refined products, although weathered oils cause relatively little damage. Oiling of the lower portion of plants and their root systems can be lethal, whereas even a severe coating on leaves may be of little consequence especially if it occurs outside the growing season. In tropical regions, mangrove forests are widely distributed and replace salt marshes on sheltered coasts and in estuaries. Mangrove trees have complex breathing roots above the surface of the organically rich and oxygen-depleted muds in which they live. Oil may block the openings of the air breathing roots of mangroves or interfere with the trees’ salt balance, causing leaves to drop and the trees to die. The root systems can be damaged by fresh oil that enters nearby animal burrows; the effect may persist for some time and inhibit recolonization by mangrove seedlings. Protection of wetlands, by responding to an oil spill at sea, should be a high priority because physical removal of oil from a marsh or from within a mangrove forest is extremely difficult. Living coral grows on the calcified remains of dead coral colonies, which form overhangs, crevices, and other irregularities, inhabited by a rich variety of fish and other animals. If the living coral is destroyed, the reef itself may be subject to wave erosion. The proportion of toxic components, the duration of oil exposure, as well as the degree of other stresses, largely determine the effects of oil on corals and their associated fauna. The waters over most reefs are shallow and turbulent, and few cleanup techniques can be recommended. Birds that congregate in large numbers on the sea or shorelines to breed, feed, or moult are particularly vulnerable to oil pollution. Although oil ingested by birds during preening may be lethal, the most common cause of death is from drowning, starvation, and loss of body heat following damage to plumage by oil. Impact of Oil on Fisheries and Mariculture. An oil spill can directly damage the boats and gear used for catching or cultivating marine species. Floating equipment and fixed traps extending above the sea surface are more likely to become contaminated by floating oil, whereas submerged nets, pots, lines, and bottom trawls are usually well protected, provided they are not lifted through an oily sea surface. Experience from major spills has shown that

COASTAL WATER POLLUTANTS

the possibility of long-term effects on wild fish stocks is remote because the normal overproduction of eggs provides a reservoir to compensate for any localized losses. Cultivated stocks are more at risk from an oil spill: Natural avoidance mechanisms may be prevented in the case of captive species, and oiling of cultivation equipment may provide a source for prolonged input of oil components and contamination of the organisms. The use of dispersants very close to mariculture facilities is ill advised because tainting by the chemical or by the dispersed oil droplets may result. An oil spill can cause loss of market confidence because the public may be unwilling to purchase marine products from the region, irrespective of whether the seafood is actually tainted. Bans on fishing and harvesting marine products may be imposed following a spill to maintain market confidence and to protect fishing gear and catches from contamination. Mercury levels in marine animals, including bivalves and crustaceans, are generally low, whereas mercury seems to accumulate in fish. The highest values in fish are from northern Canada. For seals and whales, concentrations often exceed 0.5 micrograms per gram of muscle, especially in older individuals. Livers from ringed seals in the western Canadian Arctic have very high levels of mercury; up to 205 micrograms per gram of liver have been measured. Levels in livers of bearded seals from the Amundsen Gulf are higher than those of both global background and other Arctic areas, as are mercury levels in toothed whales and polar bears. Some of the highest levels, 280 microgram per gram liver (wet weight), have been recorded in pilot whales from the Faroe Islands. The effects of these mercury levels on the animals are difficult to assess, because some of the mercury may be inactivated by high selenium levels. Moreover, the scientific focus so far has been on tissues relevant for human consumption, and very little information is available on the target organs for mercury, such as the brain. There are no effect studies from the Arctic. However, even for the most exposed animal populations in the western Canadian Arctic and in Greenland, selenium should be abundant enough to protect against mercury poisoning. Mercury is a major concern because the levels in some animals high in the food chain indicate that the environmental load may have increased in recent years. For example, mercury levels in ringed seals from western Canada show that they accumulated mercury about three times faster during the late 1980s and early 1990s than in the early 1970s. Similar increases have been seen in ringed seals from northwest Greenland taken in 1984 and 1994 and in beluga livers from the western Canadian Arctic. Interpreting these findings is difficult because natural variations that may affect the trends are unknown. Moreover, other data, such as those from Atlantic walrus and ringed seal from central-east Greenland, have not indicated any temporal trends. Very little information is available on temporal trends in Arctic marine fish, but measurements from the Baltic Sea from 1980 to

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1993 seem to confirm observations that mercury levels are increasing. The seas are being polluted by organic and inorganic wastes from sewage, from agricultural and industrial wastes, and from runoff containing oil, hydrocarbons, and heavy metals. All of these contribute to sediment runoff and increased turbidity. Siltation of coral regions is also caused by excessive deforestation and land clearing for commercial crops. Construction and land reclamation has caused changes in water circulation and has increased sedimentation. On the coral reefs, there has been extensive overexploitation of resources by heavy fishing pressure, including very destructive methods such as blasting, coral mining, and cyanide poisoning for live fish collection. Industrial Pollution Industrial pollutants that affect coral reefs include nutrients from sewage and organic matter, fertilizer runoff, detergents containing phosphorus, and thermal discharge—the heated water from the cooling systems of power plants and other industries. These all cause nutrient overload, the growth of aquatic plant life, and depletion of dissolved oxygen, or eutrophication, which retards coral growth by decreasing light penetration and changing the dynamics of fish assemblages. Other industrial pollutants include heavy metals and other toxic substances. The coral reefs bordering major cities throughout Southeast Asia have been largely destroyed. Pollution from oil refineries and drilling platforms, it has been shown, kill reef fish and have negative effects on growth rates, recruitment, and feeding of corals. Thermal pollution from hot water discharge from industrial areas is an additional threat to reef species, many of them cannot withstand sudden and drastic increases in temperature. Sedimentation. Land-based human activities often cause sedimentation, a major source of reef degradation. As more people move to coastal cities on the South China Sea, there has been a big increase in construction and land reclamation. Land reclamation and sedimentation have been particularly intensive in Singapore. Land was reclaimed by dumping sand and dirt directly onto coral reef flats and shallow water. These add to the erosion of beaches and sediment runoff that smothers corals and leads to the degradation of a reef. Increased sedimentation also leads to a change in the composition of marine fauna, favoring more resilient species. Sedimentation also comes from soil erosion from unsound agricultural practices, mismanagement of watersheds, exploitation of mangroves, land reclamation and construction, oil drilling, and dumping of terrestrial and marine mine tailings. Overfishing. Overfishing is a force extremely destructive to corals in the South China Sea. Densities of fish are greatly decreased by overfishing. Coral is damaged by destructive fishing techniques and by removal for trade. It is estimated that 10–15% of the total fish yield in the Philippines comes from coral reef fisheries.

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Fishing degrades a reef in several ways. Destructive and illegal fishing methods are common, especially in the Philippines, Indonesia, and Malaysia. These methods include dynamite blasting and cyanide fishing. Overfishing not only depletes fish stocks of target species but also changes the dynamics of the entire reef. Decreases in herbivores can lead to algal blooms that overtop coral growth and can cause mass mortality. Blooms of noxious algae have increased in the past 20 years worldwide and are being blamed on inputs of excess nutrients due to human activities. Some of these noxious algae produce powerful nerve toxins that can cause massive fish kills or even kill a person who unsuspectingly eats shellfish that was harvested from waters tainted with toxic algae. The case of the ‘‘Cell from Hell’’ now blooming in East Coast waters (North Carolina, Virginia, Maryland) is especially noteworthy. Until recently, Pfiesteria was only a curiosity of academic specialists. In the past few years, this organism has been blamed for fish kills unprecedented in their size and has been linked to neurological damage in people who worked or swam in these waters (memory loss, learning difficulties, and decreases in white blood cell content upward of 20% have been recorded in people who were exposed to Pfiesteria). Blooms of Pfiesteria have been linked to nutrient enrichment of coastal waters due to nonpoint pollution from agriculture. Nutrients in waters allow huge population increases of toxic organisms in water that were unknown or rare. The U.S. EPA has pledged to adopt new standards for nutrient inputs to waters. It is hard to imagine an organism more bizarre than Pfiesteria. When no fish prey are present, it goes into a cyst form and settles to the bottom, lying dormant in the sediments. It can also emerge to form an amoeba that feeds on algae in the water column, and even can become a photosynthetic plankton-like organism, except that it ‘‘steals’’ the chloroplasts of algae from its algal prey and uses photosynthesis only to supplement its nutrient supply in the water column. In the presence of certain species of fish, however, it becomes a ‘‘monster’’ predator capable of mass fish kills. As a ‘‘predatory’’ dinoflagellate, it produces different types of toxins that do an incredible array of damage to fish. Some toxins attack internal organs. Another works on the fish immune system. And one toxin actually strips the skin off of the fish. Those who have witnessed the power of Pfiesteria report thousands of fish flopping and thrashing on the water surface, and fish actually beaching themselves, fleeing the water as if on fire.

SUMMARY The introduction by man, directly or indirectly, of substances or energy into the marine environment (including estuaries) results in such deleterious effects as harm to living resources, hazards to human health, and hindrance to marine activities, including fishing, impairment of quality for use of seawater, and reduction of amenities. As the uses of coastal waters and the ocean have increased, pollution of the ocean waters has increased in turn. River pollution has also had an impact on the ocean as the rivers transport material to the

ocean and, as a result, make it the ultimate sink for the world’s waste. The following chart summarizes the sources of wastes and their effects.

Sources and Effects of Marine Pollution. Type Nutrients

Primary Source/Cause

Effect

Runoff approxiFeed algal blooms in mately 50% coastal waters. sewage, 50% from Decomposing algae forestry, farming, depletes water of and other land use. oxygen, killing Also airborne other marine life. nitrogen oxides Can spur algal from power plants, blooms (red tides), cars, etc. releasing toxins that can kill fish and poison people. Sediments Erosion from mining, Cloud water; impede forestry, farming, photosynthesis and other land-use; below surface coastal dredging waters. Clog gills of and mining. fish. Smother and bury coastal ecosystems. Carry toxins and excess nutrients. Pathogens Sewage, livestock. Contaminate coastal swimming areas and seafood, spreading cholera, typhoid, and other diseases. Alien Several thousand per Outcompete native species day transported in species and reduce ballast water; also biological diversity. spread through Introduce new canals linking marine diseases. bodies of water and Associated with fishery increased incidence enhancement of red tides and projects. other algal blooms. Problem in major ports. Persistent Industrial discharge; Poison or cause toxins wastewater disease in coastal (PCBs, discharge from marine life, heavy cities; pesticides especially near metals, from farms, major cities or DDT, etc.) forests, home use industry. etc.; seepage from Contaminate landfills. seafood. Fat-soluble toxins that bioaccumulate in predators can cause disease and reproductive failure.

TRACE ELEMENT POLLUTION

Oil

46% from cars, heavy Low level machinery, contamination can industry, other kill larvae and land-based sources; cause disease in 32% from oil marine life. Oil tanker operations slicks kill marine and other shipping; life, especially in 13% from accidents coastal habitats. at sea; also offshore Tar balls from oil drilling and coagulated oil litter natural seepage. beaches and coastal habitat. Oil pollution is down 60% from 1981. Plastics Fishing nets; cargo Discarded fishing and cruise ships; gear continues to beach litter; wastes catch fish. Other from plastics plastic debris industry and entangles marine landfills. life or is mistaken for food. Plastics litter beaches and coasts and may persist for 200 to 400 years. Radioactive Discarded nuclear Hot spots of substances submarine and radioactivity. Can military waste; enter food chain atmospheric and cause disease fallout; also in marine life. industrial wastes. Concentrate in top predators and shellfish, which are eaten by people. Thermal Cooling water from Kills off corals and power plants and other temperatureindustrial sites. sensitive sedentary species. Displaces other marine life.

READING LIST Brown, L. (1997). Can we raise grain yields fast enough? Worldwatch 10(4): 9–17. Engleman and LeRoy. (1996). Sustaining Water: Population and the Future of Renewable Water Supplies. Population Action International. EPA. (1994). National Water Quality Inventory, 1992: Report to Congress. Office of Wetlands, Oceans and Watersheds, US EPA, Washington, DC. Kane, H. (1997). Eco-farming in Fiji. Worldwatch 10(4): 29–34. Nixon, S. et al. The fate of nitrogen and phosphorus at the landsea margin of the North Atlantic Ocean. Biogeochemistry 35: 141–180. NRC (National Research Council). (1993). Managing Wastewater in Coastal Urban Areas. NRC, Washington, DC. NRC (National Research Council). (1994). Priorities for Coastal Science. NRC, Washington, DC. Hotta, K. and Dutton, I.M. (Eds.). (1995). Coastal Management in the Asia-Pacific Region: Issues and Approaches. Japan

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International Marine Science and Technology Federation, Tokyo. Web Sites http://www.nos.noaa.gov/icri/state.html http://www.cutter.com/osir/ http://www.igc.apc.org/wri/indictrs/reefrisk.htm http://www.enn.com http://www.env.gov.sg Journals and Newspapers Environet The Straits Times Science and Technology-The Hindu

TRACE ELEMENT POLLUTION BOBBY J. PRESLEY Texas A&M University College Station, Texas

INTRODUCTION All three words in the term ‘‘trace element pollution’’ need to be defined. Defining an element, that is a chemical element, is relatively straightforward. It is a substance consisting entirely of atoms having the same number of protons. All such substances are listed by name and symbol on the periodic charts of the elements found in many science textbooks. Definitions for ‘‘trace’’ and ‘‘pollution’’ are not so straightforward. It is sometimes convenient to classify the chemical elements making up a complex substance or matrix into major, minor, and trace, based on their relative amounts (concentrations). Most authors designate those elements present in a matrix at one part per million or less by weight as trace elements. Although trace elements are in low concentration in the environment, they can be either essential or harmful to organisms, depending on the element and the circumstances. A definition of pollution can be inferred from the widely accepted definition of marine pollution given by the United Nations Group of Experts on the Scientific Aspects of Marine Pollution (GESAMP). They say pollution is ‘‘the introduction by man, directly or indirectly, of substances or energy to the marine environment resulting in such deleterious effects as harm to living resources; hazards to human health; hindrance of marine activities including fishing; impairment of the quality for use of seawater; and reduction of amenities.’’ This definition can be applied to all environments, not just to the marine environment. By the GESAMP definition, pollution must be harmful and must be caused by human activity. In some cases, it is easy to show both a human cause and harm to the environment. In other cases, one or both parts of the definition can be hard to prove. For example, it might be possible to show that the concentration of a trace element, such as mercury, is elevated above normal values in, for example, fish. It might be harder to show harm to the fish or to the consumer of the fish and it might be hard to show

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that the enrichment is because of human activity. In such a case, it might be better to say contamination has been documented, but not pollution.

As a first step in determining the significance of a given amount of a trace element in a particular environment, it is essential to know the ranges in concentration expected to occur naturally in various media (soil, water, organisms, etc.). Most trace elements were tied up in igneous rocks on the primitive earth. Table 1 gives average concentrations of selected elements in the uppermost part of the earth’s crust along with data for organisms, soil, sediment, and water. These values can be considered to be ‘‘background’’ concentrations or at least concentrations not greatly influenced by human activity. As igneous rocks ‘‘weather’’ to give soil and sediment some fraction of each element in the rock, it becomes dissolved in rivers, lakes, and the ocean. For most trace elements, however, a large fraction is retained in the solids during weathering. For this reason, the natural (background) trace element concentration in soils and sediments varies, depending on the igneous rocks they came from. Many trace elements behave similarly during weathering, soil formation, erosion, and deposition. For example, fine-grained clay minerals become enriched in most trace elements and quartz sand and carbonate minerals become depleted. It is, therefore, important to have information on the grain size and mineralogy of soils and sediments when evaluating their trace element content. Thus, a given concentration, say 20 ppm Cu, might be background for a clay sediment but be contamination in a sand. Reliable data on trace elements dissolved in rivers, lakes, and seawater is more difficult to produce than is data on rocks, soil, and sediment. Concentrations are generally a thousand or more times lower (Table 1), and this causes sensitivity and matrix interference problems for even the newest analytical instruments. It is also difficult to avoid contaminating samples with trace elements during

ABUNDANCE, DISTRIBUTION, AND BEHAVIOR OF TRACE ELEMENTS Trace elements occur naturally in the environment. Unlike pesticides, plastics, organic solvents, and other manufactured products, the mere presence of trace elements does not imply pollution, contamination, or even human activity. Sufficiently sensitive analytical techniques can detect some amount of all elements in almost any substance. To determine the amount accurately and precisely is, however, a challenge, and to decide what portion of the element is natural and what portion is because of human activity is an even bigger challenge. In order to evaluate the significance of trace element occurrences in the environment, information is needed on: 1. Amounts (concentrations) in various compartments (air, soil, water, organisms, etc.). 2. Sources to the environment (both natural and human). 3. Transport mechanism and pathways between compartments (continents to oceans, water to organisms, etc.). 4. Transfer mechanism within compartments (shallow to deep water, fish gill surface to other organs, etc.). 5. Ultimate fate of the element (burial in sediments, mixing throughout the ocean, etc.). 6. Effect of the element on organisms (both short and long term).

Table 1. Average Concentration of Selected Elements in Various Materials. Values for Sediment, Soil, Crust, Oysters and Fish are µg/g Dry Weight (ppm) Except Ca and Fe in Percent Dry Weight. Values for Water are µg/l (ppb) Material Continental Crust Gulf Coast Seds Gulf Slope Seds San Joaquin Soil Sediment Criteria Average Seawater Miss. River Water Seawater Criteria Fresh Water Criteria Gulf Oysters Tuna Fish

Ref.

As

Ba

Ca

1 2 3 4 5 6 7 8 9 10 11

1.5 6 8.6 17.7 55 1.7

550 – 660

3.00 – 11.3 1.9 –

–

Cr

Cu

35 44 54 130 145 0.2

25 10 27 34.6 390 0.25 1.5 4.8 13 146 2.8

65 69 340 10.3 3.8

100

1100 16 0.57 0.75

Fe 3.5 1.8 2.76 – 0.05 2.2

294 72

Mn

Ni

Pb

V

Hg

Zn

600 330 300 538 – 0.2 1.4

20. 16 38 88 50 0.5 1.5 74 470 1.77 0.5

20. 15 17 18.9 110 0.002 0.008 210 65 0.64 0.5

60 – 100 112 – 1.5 1.0

– 0.050 0.028 1.4 1.3 0.001

71 60 81 106 270 0.4 0.27 90 120 2150 17.4

14.4 0.6

1.8 1.4 0.13 4.1

1. Average metal levels in upper continental crust (95% igneous rock). Taylor and McClennon (1). 2. Median estuarine (inshore) surface sediment metal levels from the U.S. Environmental Protection Agency’s northern Gulf of Mexico (GOM) Environmental Mapping and Assessment Program 1991–1993. 3. Average surface sediment metal levels observed among 43 stations ion the Gulf of Mexico Slope. BJ Presley, unpublished 4. Agricultural soil from the San Joaquin Valley, CA. US NIST Standard Reference Material #2709. 5. ER-M values from Long and Morgan (2), indicating sediment metal levels at which biological effects are often seen. 6. Average seawater values from Bruland, (3). 7. Average Mississippi River dissolved values from Shiller, (4). 8. Maximum Contaminant Concentration for seawater, US EPA, (5). 9. Maximum Contaminant Concentration for fresh water, US EPA, (5). 10. Average concentration in 485 pooled samples of 20 oysters each from the Gulf of Mexico. Presley (6). 11. Fillets from 16 Large Mediterranean Sea Tuna. International Atomic Energy Agency reference material # 350.

TRACE ELEMENT POLLUTION

collection, storage, and analysis. For these reasons, nearly all of the dissolved trace element data published before 1970, and much of the recent data, is unreliable. Much of the published data for both fresh and seawater is too high by factors of up to 100. Only data that has been produced by a lab using a well-documented quality assurance program should be accepted. Trace element concentrations in organisms are generally intermediate between those in sediments and those in water. However, concentrations vary widely with the specie of organism and with the specific organ within organisms. Livers, for example are enriched in some elements and kidneys in others and some species of organisms are highly enriched in one or another trace element. Trace element concentrations in organisms can also change with season, life stage, health, food supply, etc. Thus, identification of abnormal trace element concentrations is difficult unless reliable data is available for the same organism over a wide area and/or over some time period. Good general compilations of reliable trace element data for organisms are not as available as are those for soil and sediment. General guidance can be acquired from Furness and Rainbow (7) or similar publications. Many recent journal articles give trace element data for specific organisms from specific locations, but it is not always clear which are background levels. In addition to natural sources, many different human activities can add trace elements to the environment. Mining and metal processing are classic sources of contamination, but other manufacturing, transportation, and waste disposal practices can also be important. In the United States, the EPA’s ‘‘Superfund’’ program has spent many millions of dollars to clean up trace element contamination at dozens of sites around the country. The kinds of practices that led to this gross contamination are very rare today. Environmental regulations and public pressure have caused industry to greatly reduce trace metal releases to the environment. However, as the world population grows, the Earth’s surface is increasingly disturbed by agriculture, petroleum production, forestry, urban development, civil conflicts, and war, all of which make trace elements more available for uptake by humans and other organisms. As discussed above, numerous possible sources exist of trace elements to the environment. It is almost always difficult to determine which possible source is most important for any given element at any given location. Although it is important to identify the source of trace elements, their environmental impact depends not on source but on concentration and behavior. Behavior, including mobility, transport, transfer, and biological uptake, depends strongly on the chemical and physical form of the trace element. In this respect, the size of the trace element specie or the particle with which it is associated is critical, as this will control its transport and settling behavior in air and water. A given trace element will behave differently physically, chemically, and biologically in each of its different forms, and it will partition itself among the various possible forms in response to environmental conditions. It is important to note that many trace elements are ‘‘particle-reactive’’

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and will quickly associate with particles if added to the environment in a dissolved form. Trace element concentrations are almost always much higher in particles than in dissolved forms. Although the behavior of a trace element, including its biological behavior, depends on its form, there is some form of most trace elements that will affect the health of organisms, including humans. At least 20 trace elements have long been known to be essential to health [e.g., (8)]. Diseases because of trace element deficiencies are well known among both humans and other organisms. A number of trace elements such as Cu, Ni, Zn, and Se are essential to life at very low concentrations but toxic at slightly higher concentrations. Good data on trace element concentrations in the environment are needed in order to know whether too little or too much of a giver element is present. The toxic effects of both essential and nonessential trace elements are well known, in the case of As and Pb, human toxicity has been known for more than 2000 years. For other trace elements, toxic effects are less well recognized. In general, however, for all trace elements, an optimal concentration in the environment and in the organism gives optimal function (growth, reproduction, etc.) and higher or lower concentrations result in less than optimal function and possibly death. In order for a trace element in the environment to have an effect on an organism, the element must, of course, be taken up by the organism. For plankton and other aquatic plants, this uptake is directly from solution, but for animals, some, or most, of the uptake might be from food or from ingestion of nonfood particles. In any case, at some point the trace element must be in a soluble form and be transferred across cell membranes and possibly transferred to some vital organ within the organism. The form of the trace element is very important in controlling these transfers and the resulting effects, but both environmental conditions (pH, temperature, etc.) and the type of organism and its condition (age, health, etc.) also play a role. Factors that influence the toxicity of trace elements have been discussed by Bryan (9), Luoma (10), and many others, and the large differences in sensitivity to trace elements exhibited by different organisms are well known [e.g., (11)]. ASSESSING BIOLOGICAL IMPACTS The effect of a trace element on organisms depends on the abundance, distribution, and behavior of the trace element. As discussed above, these are difficult to determine and are subject to complex and incompletely understood processes. The environmental impact of waste disposal or other human activity is, therefore, often controversial. Environmental groups and industry often engage in public fingerpointing and lawsuits over specific activities. Often, more money is spent on lawyers than on attempts to scientifically document impacts. One reason for this is the difficulty in clearly documenting harmful effects in the field, especially at the population or ecosystem level. Laboratory toxicity testing is not easy, but it can usually show dose-response relationships that allow establishment of trace element concentrations above which harmful effects to a given organism are likely to

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result. Such results are, however, usually difficult to apply to the complex conditions in the field, as is discussed below. The simplest laboratory toxicity tests are those that use death of the organism as the only indicator of effect. This crude measurement has been much criticized, but it does establish the rough relative toxicity for various trace elements to various organisms. This test will show, for example, that Cu is much more toxic to most plankton than is As. More subtle effects can also be sought in laboratory cultures of various organisms, for example, changes in metabolism, ability to reproduce, find food, grow, etc. A vast amount of literature exists on methods for detecting sublethal effects of toxins on organisms [e.g., (2,12)]. Different sublethal tests often give different results in rating the relative toxicities of different trace elements, but they have the potential for indicating possible long-term effects on organisms that might not show up in short-term acute tests. Most laboratory toxicity tests use water as free from trace elements, complexing ligands, organic matter, etc. as is possible, so the response of the test organisms can be more clearly related to the trace element added in the test procedure. Consequently, a trace element is almost always less toxic in the environment than it is in the laboratory, because of complexing, adsorption, and other interactions in the environment. Laboratory toxicity tests, even when they try to imitate the environment by using ambient water, multiple trace elements, varying salinities, temperatures, different life stages of organisms, etc., can never truly duplicate natural conditions. It is useful, then, to look for effects of pollutants in the environment, especially at the population level. This is, however, a difficult task, because of the natural temporal and spatial variability in abundance and health of organisms. As a result of the relative expense and time involved in toxicity tests, and their sometimes ambiguous results, many environmental assessment programs seek only to determine concentrations of trace elements in the environment and to look for enrichments caused by human activity. If a trace element enrichment is detected, its significance can then be resolved by toxicity testing or detailed ecological field analysis. In any case, trace element enrichments could be sought in air, water, sediment, or organisms. Water analysis might seem a logical way to detect trace element enrichments in the environment. Furthermore, the significance of trace element concentrations in water can be judged because the US EPA has published values for each element above which harm to organisms is likely (Table 1). However, ambient water, be it river water, groundwater, rainwater, or seawater, is notoriously hard to collect, store, and analyze for trace element content, as was discussed above. Water concentrations can also change over short time scales in some circumstances, which further complicates their use. Soil or sediment can usually be more easily analyzed accurately for trace element content than can water. Soil and sediment also integrate trace element input over some time scale, so they don’t need to be sampled as often as does water. Another advantage of sediment analysis is

that it gives a historical view of pollutant input at sites where sediment is laid down layer by layer, year after year. Dates can be assigned to the different layers by use of radio-isotopes, pollen identification, or other means. Furthermore, sediment layers from prehistoric times give a background value for each trace element that can be compared with values in near-surface layers in order to quantify human-induced enrichments. Recognizing gross sediment contamination is easy. Any sediment that is several-fold higher in a given trace element than the average crustal abundance of that element is contaminated unless some unusual mineralogy exists. However, it is harder to recognize subtle contamination because of difficulties in establishing an exact background concentration for a given location. Values from prehistoric depths in the sediment column are a possible background, as noted above. Another background is sediment well away from any point source of pollutant input. In using either of these methods, care should be taken to compare similar sediment types or to compare element to element concentration ratios rather than absolute concentrations (13). Another problem with using sediment data is that only some unknown fraction of the trace element in the sediment is likely to be available to organisms, which has been much discussed in the literature [e.g., (14)], especially in conjunction with disposal of dredge spoil [e.g., (15)]. Many authors have suggested leaching sediments with dilute acids or other solutions [e.g., (14)] in order to remove only the trace element that could potentially be removed by an organism. Another suggestion that has been much debated is the ability of sulfide in the sediment to limit availability of trace elements to organisms [e.g., (16)]. Thus, although it generally agreed that only a fraction of the total trace element in sediments is available to organisms, no consensus exists on how to measure that fraction. Long and Morgan [(2) and elsewhere] suggest another way to identify sediment that is potentially harmful to organisms because of chemical contamination. They compiled published matching biological health and chemical data from numerous field, laboratory, and modeling studies. The data was then ranked from the lowest to the highest contaminant concentration where any adverse biological effect was reported. From the ranking they derived two guideline concentrations for each contaminant. These two values separate the data into values that (1) rarely, (2) occasionally, or (3) frequently cause adverse biological effects. These derived values have been widely used in monitoring programs. See Table 1 for some of the actual values. If both water and sediment offer analytical and data interpretation challenges, would it not be better to analyze organisms in order to assess trace element contamination? Certainly, advantages to this approach exist. For one thing, there is no question as to whether the element is available to organisms. For another, concentrations are often high enough to make analyses relatively easy, at least for common trace elements such as Cu and Zn. There are, however, problems, for example, deciding what organisms to analyze. It is not practical to analyze every organism at a given location, or even to analyze a

CORAL REEFS AND YOUR COASTAL WATERSHED

representative specie from each major taxonomic group. What, then, should be analyzed? Farrington (17) summarized the rationale for using common mussels (Mytilus sp.), various oyster species (Crassostrea and Ostrea), and other bivalves as ‘‘sentinel’’ organisms in monitoring studies in the marine environment. This approach has resulted in a very large worldwide data set for trace elements in bivalves. In the United States, the National Oceanic and Atmospheric Administration’s ‘‘National Status and Trends Program’’ (NS&T) has been analyzing bivalves from the entire U.S. coastline since 1986 and has produced an especially useful and highquality data set. As a result of the NS&T and similar data, bivalves should be the first choice for organisms to analyze in marine environmental monitoring programs. Many different kinds of plants and animals have been used in nonmarine environmental monitoring studies, everything from plankton and moss to polar bears. It all depends on what is available and the purpose of the monitoring. In general, organisms that have low natural variability in trace element concentration and are geographically widespread and easy to collect should be selected. Data from good, long-term environmental monitoring programs can help answer the question ‘‘are things getting better or worse.’’ Since strict environmental laws took effect in the United States in the 1970s, billions of dollars have been spent on pollution-control devices and cleanup of polluted sites. Have the efforts worked? (O’Connor (18,19) looked for temporal trends in the NS&T data discussed earlier. He found that for 2744 combinations of 14 chemicals and 196 collection sites over a 10-year time period, only 88 increases and 348 decreases in concentration are significant at the 95% confidence level. Chance alone predicts 69 increases and 69 decreases, so by this analysis, it is quite possible that no real increases occurred over that 10-year period and environmental quality along the U.S. coastline may have improved. This finding is consistent with observations of other environmental scientists. At least for chemical contaminants, environmental laws have worked and the U.S. environment is cleaner now than it was in the 1970s. BIBLIOGRAPHY 1. Taylor, S.R. and McClennon, S.M. (1985). The Continental Crust: Its Composition and Evolution. Blackwell Scientific Publications, Oxford, p. 312. 2. Long, E.R. and Morgan, L.G. (1990). The Potential for Biological Effects of Sediment-sorbed Contaminants Tested in the National Status and Trends Program. NOAA Tech. Memo. NOS OMA 52, Rockville, MD, p. 167. 3. Bruland, K.W. (1983). Trace elements in sea-water. In: Chemical Oceanography. Vol. 8, J.P. Riley and R. Chester (Eds.). Academic Press, London, pp. 158–220. 4. Shiller, A.M. (1997). Dissolved trace elements in the Mississippi River: Seasonal Interannual and decadal variability. Geochemica et Cosmochemica Acta 61: 4321–4330. 5. U.S. Environmental Protection Agency. (2002). National Recommended Water Quality Criteria: 2002. EPA-822-R-02047, US EPA Office of Water, Washington, DC. 6. Presley, B.J. (1990). Trace metals in Gulf of Mexico oysters. The Science of the total Environment 97/98: 551–593.

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7. Furness, R.W. and Rainbow, P.S. (1990). Heavy Metals in the Marine Environment. Lewis Publishers, p. 264. 8. Mertz, W. (1981). The essential trace elements. Science, V. 213: 1332–1338. 9. Bryan, G.W. (1976). Factors influenceing toxicity of heavy metals. In: Marine Pollution. R. Johnson (Ed.). Academic Press, London, pp. 185–302. 10. Luoma, S.N. (1983). Bioavailability of trace metals to aquatic organisms-A review. Science of the Total Environment 28: 1–29 11. U.S. Environmental Protection Agency. (1987). Biomonitoring to Achieve Control of Toxic Effluents. EPA/625/8-87/013, US EPA Office of Water, Washington, DC. 12. U.S. Environmental Protection Agency. (1988). Short-Term Methods For Estimating Chronic Toxicity of Effluents and Receiving Waters to Marine and Estuarine Organisms. Environmental Protection Agency, EPA 60014-87/028 Cincinnati, OH. 13. Trefry, J.H. and Presley, B.J. (1976). Heavy Metals in Sediments from San Antonio Bay and the Northwest Gulf of Mexico. Environmental Geology 1: 283–294. 14. Campbell, P.G.C. (1988). Biologically Available Metals in Sediments. National Research Council of Canada, ISSN 03160114, Ottawa, Canada, p. 298. 15. Lake, J., Hoffman, G.L., and Schimmel, S.C. (1985). Bioaccumulation of Contaminants from Black Rock Harbor Dredged Material by Mussels and Polychaetes. U.S. Army, Corp of Engineers, Tech. Report D-85-2, Vicksburg, MS. 16. Allen, H.E., Fu, G., and Deng, B. (1993). Analysis of acidvolatile sulfide (AVS) and simultaneously extracted metals (SEM) for estimation of potential toxicity in aquatic sediments. Environ. Toxicol. and Chem. 12: 1441–1453. 17. Farrington, J.W. (1983). Bivalves as sentinels of coastal chemical pollution; The mussel (oyster) watch. Oceanus 26: 18–29. 18. O’Connor, T.P. (1998). Mussel Watch results from 1986 to 1996. Mar. Poll. Bull. 37: 14–19 19. O’Connor, T.P. (1990). Recent Trends in Environmental Quality: Results of the First Five Years of the NOAA Mussel Watch Project. NOAA/ORCA, Silver Spring, MD.

CORAL REEFS AND YOUR COASTAL WATERSHED U.S. Environmental Protection Agency—Oceans and Coastal Protection Division

Coral reefs are among the world’s richest ecosystems, second only to tropical rain forests in plant and animal diversity. However, they are extremely sensitive environments that have special temperature, salinity, light, oxygen, and nutrient requirements. If environmental conditions fall outside the acceptable range of these requirements, the health and dynamics of a coral reef community can be severely disrupted. That’s why coral communities are sensitive indicators of water quality

This article is a US Government work and, as such, is in the public domain in the United States of America.

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and the ecological health of the coastal watershed. They respond to alterations within the entire coastal watershed, such as changes in freshwater flows and nutrient inputs. Consequently, pollution from the destruction and alteration of surrounding coastal watersheds can directly affect the health and productivity of a coral reef. WHAT ARE CORAL REEFS AND WHAT DO THEY DO? Coral reef ecosystems are unique, biologically diverse systems recognized as valuable economic and environmental resources. Many people think coral reefs are made of plants or rocks, but they are actually made of animals! A coral polyp is a delicate, limestone-secreting animal. The limestone serves as a skeleton that either is embedded within the living tissue of the coral or encloses the animal. A coral reef is made up of colonies of these coral polyps. There are several benefits of coral reefs. • Coral reefs are an important recreational and aesthetic resource for people visiting or living in coastal areas. People use coral reefs for fishing, underwater photography, scuba diving, and snorkeling. • Coral reefs provide protection for harbors and beaches, which are often found behind reefs because the reefs provide natural protection from heavy wave action caused by coastal storms. • Coral reefs are home to a number of species of fish and other marine species, including many that we rely on for food and economic purposes. • Coral reefs also serve as a laboratory for students and scientists to study and learn about complex ecological and biological processes. In addition, the reefs yield many biological treasures that are increasingly being recognized as natural sources of biomedical chemicals. SOME IMPACTS ON CORAL REEFS Coral reef habitats are extremely sensitive to disturbances, such as various forms of pollution and physical contact. Pollution of coastal watersheds poses a threat to

the existence of coral reefs. Impacts can result from activities occurring near the reef itself or from areas within the coastal watershed that drain to the reef. Disturbances and pollution can lead to diseases in coral such as bleaching (when the algae that give corals their color die). Natural occurrences, such as hurricanes, can adversely impact coral reefs through high-energy storm surges and the resulting resuspension of sediment. However, reefs are usually able to recover from natural disturbances. People using the reef can have an adverse impact on reef resources. Portions of a coral reef can be broken by the impact of boat anchors and boat groundings. Divers and snorkelers can harm the reef by simply touching it or by removing the corals. Suntan oil from swimmers and snorkelers can harm or even kill sensitive corals. Dragging hooks, fishing line, and nets across the coral reef, as well as placing and recovering lobster traps on reefs, can be damaging. Overfishing also harms coral reefs by removing important species that eat the algae growing on corals. When these fish species are removed, the algae overgrow the corals, smothering them. Marine debris, trash floating on the ocean or resting on the ocean floor, comes from many sources, including boaters, divers, improper disposal of trash on land, storm water runoff to rivers and streams, ships and other vessels, and offshore oil platforms. Marine debris can harm fish species and other aquatic organisms that use the reef. Trash that lands on the reef can kill corals by continually rubbing against it or smothering it. An excessive amount of nutrients from improperly treated sewage, atmospheric deposition, agricultural and urban runoff, and cleaning products high in phosphates can harm coral reef habitats. In excess levels, nutrients overstimulate the growth of aquatic plants and algae. When nutrient levels increase, the delicate balance that exists between corals and algae is destroyed and the algae can overgrow the corals. When this situation is prolonged, the corals are smothered and die beneath the algal carpet. This, in turn, affects the fish and other aquatic organisms using the area, leading to a decrease in animal and plant diversity and affecting use of the water for fishing and swimming. Some of the leading causes of nearshore coral decline can be related to land development and nearshore

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like industrial discharges, urban and agricultural runoff, mining activities, and runoff from landfills. Some toxic substances bind to sediment and are transported to coastal waters through sedimentation. These toxic substances can cause scarring, death, or reproductive failure in fish, shellfish, and other marine organisms. In addition, they can accumulate in fish tissue, leading to fish consumption advisories. The sensitivity of corals makes them especially vulnerable to the introduction of toxic substances. WHAT IS EPA DOING TO PROTECT CORAL REEFS?

International Coral Reef Initiative

construction that are not environmentally sensitive. Sediment, silt, and other suspended solids wash off plowed fields, construction and logging sites, urban areas, strip-mined land, and eroded stream banks when it rains. Increases in coastal sediment are also caused by construction of seawalls, docks, and marinas; land-clearing; boats running through shallow waters, disturbing and suspending silts with their propellers; and snorkelers and divers kicking up sediment. Sediment can block sunlight that is essential for the survival of some corals, which live in a very close relationship with microscopic plants (algae) that require sunlight to survive. In addition, heavy sedimentation can bury corals, inhibiting their growth or killing them. Pathogens are disease-causing microorganisms such as viruses, bacteria, and parasites. Pathogens are harmful to corals, causing disease and scarring in many species. These microorganisms enter water bodies from sources such as: inadequately treated sewage, storm water drains, septic systems, runoff from livestock pens, and boats that discharge sewage. Coral reefs are vulnerable to the introduction of a wide variety of toxic substances, including metals (such as mercury and lead), toxic organic chemicals (such as PCBs and dioxin), pesticides, and herbicides found in sources

In 1994, EPA, along with the State Department, the National Oceanic and Atmospheric Administration, and the Department of the Interior, formed an international coalition to coordinate information and bring higher visibility to the need for coral reef ecosystem preservation. The coalition became the International Coral Reef Initiative (ICRI), which now includes a membership of more than 90 countries. EPA’s Watershed Approach. EPA has joined with others to promote the Watershed Approach nationally as a means to further restore and maintain the physical, chemical, and biological quality of our nation’s waters, including coral reefs. By addressing issues on a watershed scale, those areas that pose the greatest risk to human and ecological health can be targeted, several pollutants can be addressed at one time, the public can be involved in cleaning up the environment and protecting coral habitats, and integrated solutions for environmental protection can be considered. This is particularly important given the contribution of activities and sources of pollution within the larger watershed to the decline of coral reefs. Through the Watershed Approach, integrated coastal zone management tools and watershed concepts can be applied in the development of comprehensive management and conservation plans. The Watershed Approach aims

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to determine protective approaches for controlling identified stressors to coral reef ecosystems. EPA’s Coastal Watershed Protection Strategy specifically provides technical assistance and support to priority coastal watersheds, such as National Estuary Programs (NEPs) and other coastal waters identified by states. Other EPA Programs. In assisting coastal states with the development of their Coastal Nonpoint Pollution Control Programs, EPA and other federal agencies developed guidance specifying management measures for sources of nonpoint pollution (diffuse runoff of pollutants) in coastal waters. In its program, a state or territory describes how it will implement nonpoint source pollution controls. EPA also works with other federal agencies to protect human health and coral reefs by reducing marine debris. The efforts include the establishment of the National Marine Debris Monitoring Program, which looks at the origins and amounts of marine debris deposited along U.S. coasts. EPA and the Coast Guard work together to regulate the transportation of municipal and commercial waste on vessels and to issue regulations for the manufacture, maintenance, and efficiency of marine sanitation devices (boat toilets), as well as the establishment of ‘‘no discharge zones’’ for vessel sewage. EPA also regulates the discharge of pollutants from facilities into sensitive marine waters. EPA assists states in the development of water quality standards designed to protect human health and aquatic life. This assistance includes the development of criteria for water quality that accurately reflects the most up-to-date scientific knowledge about the effects of pollutants on aquatic life, such as corals, and human health. What Can You Do to Help Protect Coral Reefs? You can do several things to help protect coral reefs and your coastal watershed:

• Be Informed and Involved. Learn about coral reefs and their importance to your coastal watershed. Participate in training or educational programs that focus on reef ecology. Be an informed consumer; ask the store owner or manager from what country the coral was taken and whether that country has a management plan to ensure that the harvest was legal and sustainable over time. Support the creation and maintenance of marine parks and reserves. Become a citizen volunteer. As a volunteer you might be involved in taking water quality measurements, tracking the progress of protection and restoration projects, or reporting special events like fish kills and storm damage. Volunteer for a reef cleanup or a beach cleanup. If you don’t live near a coast, get involved in your local watershed program. Report dumping or other illegal activities. • Take Responsibility for Your Own Backyard. Determine whether additional nutrients or pesticides are needed before you apply them, and look for alternatives to fertilizers and pesticides where the chance of runoff into surface waters might occur. Even if you live far from a coral reef ecosystem, these products might ultimately affect the waters that support coral. Consider selecting plants and grasses with low maintenance requirements. Water your lawn conservatively; the less water you use, the less runoff will eventually find its way into the oceans. • Practice Good Housekeeping. Learn about procedures for disposing of harmful household wastes so they do not end up in sewage treatment plants that can’t treat them or in landfills not designed to receive hazardous materials. Around the house, keep litter, pet waste, leaves, and grass clippings out of street gutters and storm drains to prevent their entrance into streams that might flow to reefs. Use the minimum amount of water needed when you wash your car to prevent waste and runoff. Never dump any household, automotive, or gardening wastes into a storm drain. They might end up on the reef. Take used motor oil, paints, and other hazardous household

SEA LEVEL AND CLIMATE

materials to proper collection sites such as approved service stations or designated landfills. Always follow label directions for the use and disposal of household chemicals. Keep your septic tank in good working order. The improper disposal of wastes and hazardous materials can lead to water quality problems and harm to the sensitive coral reef habitats. • Respect the Reef. Help keep the reef healthy by following local guidelines, recommendations, regulations, and customs. If you dive, don’t touch the coral. Keep your fins, gear, and hands away from the coral since this contact can hurt you and will damage the delicate coral animals. Stay off the bottom because stirred-up sediment can settle on corals and smother them. Avoid entering sensitive habitat areas with your boat or other motorized watercraft. Maintain your boat engine to prevent oil and gas leaks. Keep all waste produced during your excursions in a safe place to be disposed of properly when you’re back on land. If you go boating near a coral reef, don’t anchor your boat on the reef. Use mooring buoy systems if they are available. Maintain and use your marine sanitation devices properly. Conserve energy and keep your auto in good running condition. By conserving energy, harmful air emissions leading to air deposition are minimized.

SEA LEVEL AND CLIMATE RICHARD Z. POORE CHRISTOPHER TRACEY U.S. Geological Survey Reston, Virginia

RICHARD S. WILLIAMS, JR. U.S. Geological Survey Woods Hole, Massachusetts

INTRODUCTION Global sea level and the Earth’s climate are closely linked. The Earth’s climate has warmed about 1 ◦ C (1.8 ◦ F) during the last 100 years. As the climate has warmed following the end of a recent cold period known as the ‘‘Little Ice Age’’ in the 19th century, sea level has been rising about 1 to 2 millimeters per year due to the reduction in volume of ice caps, ice fields, and mountain glaciers in addition to the thermal expansion of ocean water. If present trends continue, including an increase in global temperatures caused by increased greenhouse-gas emissions, many of the world’s mountain glaciers will disappear. For example, at the current rate of melting, all glaciers will be gone from Glacier National Park, Montana, by the middle of the next century (Fig. 1). In Iceland, about 11 percent of the island is covered by glaciers (mostly ice caps). If warming continues, Iceland’s glaciers will decrease by 40 percent by 2100 and virtually disappear by 2200. This article is a US Government work and, as such, is in the public domain in the United States of America.

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Figure 1. Grinnell Glacier in Glacier National Park, Montana; photograph by Carl H. Key, USGS, in 1981. The glacier has been retreating rapidly since the early 1900’s. The arrows point to the former extent of the glacier in 1850, 1937, and 1968. Mountain glaciers are excellent monitors of climate change; the worldwide shrinkage of mountain glaciers is thought to be caused by a combination of a temperature increase from the Little Ice Age, which ended in the latter half of the 19th century, and increased greenhouse-gas emissions.

Most of the current global land ice mass is located in the Antarctic and Greenland ice sheets (Table 1). Complete melting of these ice sheets could lead to a sea-level rise of about 80 meters, whereas melting of all other glaciers could lead to a sea-level rise of only one-half meter. GLACIAL-INTERGLACIAL CYCLES Climate-related sea-level changes of the last century are very minor compared with the large changes in sea level that occur as climate oscillates between the cold and warm intervals that are part of the Earth’s natural cycle of long-term climate change. Table 1. Estimated Potential Maximum Sea-Level Rise from the Total Melting of Present-Day Glaciers. [Modified from Williams and Hall (1993). See also http://pubs.usgs.gov/factsheet/fs50-98/]

Location East Antarctic ice sheet West Antarctic ice sheet Antarctic Peninsula Greeland All other ice caps, ice fields, and valley glaciers Total

Volume (km3 )

Potential Sea-Level Rise (m)

26,039,200 3,262,000 227,100 2,620,000 180,000

64.80 8.06 .46 6.55 .45

32,328,300

80.32

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During cold-climate intervals, known as glacial epochs or ice ages, sea level falls because of a shift in the global hydrologic cycle: water is evaporated from the oceans and stored on the continents as large ice sheets and expanded ice caps, ice fields, and mountain glaciers. Global sea level was about 125 meters below today’s sea level at the last glacial maximum about 20,000 years ago (Fairbanks, 1989). As the climate warmed, sea level rose because the melting North American, Eurasian, South American, Greenland, and Antarctic ice sheets returned their stored water to the world’s oceans. During the warmest intervals, called interglacial epochs, sea level is at its highest. Today we are living in the most recent interglacial, an interval that started about 10,000 years ago and is called the Holocene Epoch by geologists. Sea levels during several previous interglacials were about 3 to as much as 20 meters higher than current sea level. The evidence comes from two different but complementary types of studies. One line of evidence is provided by old shoreline features (Fig. 2). Wave-cut terraces and beach deposits from regions as separate as the Caribbean and the North Slope of Alaska suggest higher sea levels during past interglacial times. A second line of evidence comes from sediments cored from below the existing Greenland and West Antarctic ice sheets. The fossils and chemical signals in the sediment cores indicate that both major ice sheets were greatly reduced from their current size or even completely melted one or more times in the recent geologic past. The precise timing and details of past sea-level history are still being debated, but there is clear evidence for past sea levels significantly higher than current sea level. POTENTIAL SEA-LEVEL CHANGES If Earth’s climate continues to warm, then the volume of present-day ice sheets will decrease. Melting of the current

Figure 3. Red shows areas along the Gulf Coast and East Coast of the United States that would be flooded by a 10-meter rise in sea level. Population figures for 1996 (U.S. Bureau of the Census, unpublished data, 1998) indicate that a 10-meter rise in sea level would flood approximately 25 percent of the Nation’s population.

Greenland ice sheet would result in a sea-level rise of about 6.5 meters; melting of the West Antarctic ice sheet would result in a sea-level rise of about 8 meters (Table 1). The West Antarctic ice sheet is especially vulnerable, because much of it is grounded below sea level. Small changes in global sea level or a rise in ocean temperatures could cause a breakup of the two buttressing ice shelves (Ronne/Filchner and Ross). The resulting surge of the West Antarctic ice sheet would lead to a rapid rise in global sea level. Reduction of the West Antarctic and Greenland ice sheets similar to past reductions would cause sea level to rise 10 or more meters. A sea-level rise of 10 meters would flood about 25 percent of the U.S. population, with the major impact being mostly on the people and infrastructures in the Gulf and East Coast States (Fig. 3). Researchers at the U.S. Geological Survey and elsewhere are investigating the magnitude and timing of sea-level changes during previous interglacial intervals. Better documentation and understanding of these past changes will improve our ability to estimate the potential for future large-scale changes in sea level. READING LIST Fairbanks, R.G. (1989). A 17,000-year glacio-eustatic sea level record; influence of glacial melting rates on the Younger Dryas event and deep-ocean circulation. Nature 342(6250): 637–642. Williams, R.S., and Hall, D.K. (1993). Glaciers, in Chapter on the cryo-sphere, in Gurney, R.J., Foster, J.L., and Parkinson, C.L., eds., Atlas of Earth Observations Related to Global Change. Cambridge University Press, Cambridge, UK, pp. 401–422.

THE PERMANENT SERVICE FOR MEAN SEA LEVEL Figure 2. Wave-cut terraces on San Clemente Island, California. Nearly horizontal surfaces, separated by step-like cliffs, were created during former intervals of high sea level; the highest terrace represents the oldest sea-level high stand. Because San Clemente Island is slowly rising, terraces cut during an interglacial continue to rise with the island during the following glacial interval. When sea level rises during the next interglacial, a new wave-cut terrace is eroded below the previous interglacial terrace. Geologists can calculate the height of the former high sea levels by knowing the tectonic uplift rate of the island. Photograph by Dan Muhs, USGS.

S. JEVREJEVA S. HOLGATE P.L. WOODWORTH Proudman Oceanographic Laboratory Birkenhead, United Kingdom

Mean sea level (MSL) is the average level of the sea, relative to the level of the land on which the measurements

THE PERMANENT SERVICE FOR MEAN SEA LEVEL

are being made, recorded over an extended period such as a month, year, or the lunar nodal period of 18.6 years by an instrument called a tide gauge (or coastal sea level recorder). MSL data are used in a wide range of scientific applications including studies into climate change, ocean circulation variability and geology, as well as in practical applications such as surveying and the establishment of national leveling datums. The Permanent Service for Mean Sea Level (PSMSL) is the global data bank for such MSL information, and it has since 1933 been responsible for the collection, publication, analysis, and interpretation of sea level data from the global network of tide gauges. It is based at the Proudman Oceanographic Laboratory (POL) in Liverpool, U.K. and is a member of the Federation of Astronomical and Geophysical Data Analysis Services (FAGS) established by the International Council for Science (ICSU). The PSMSL is supported by FAGS, the Intergovernmental Oceanographic Commission of the United Nations Educational, Scientific and Cultural Organisation (IOC/UNESCO), and NERC. The database of the PSMSL contains almost 53,000 station-years of monthly and annual mean values of sea level from nearly 2000 tide gauge stations around the world received from almost 200 national authorities (see Fig. 1). On average, approximately 2000 stationyears of data are entered into the database each year. All data are readily available from the PSMSL website: www.pol.ac.uk/psmsl. Data for all stations are included in the PSMSL METRIC (or total) dataset. The METRIC monthly and annual means for any one station-year are necessarily required to be measured to a common datum, although, at this stage, datum continuity between years is not essential. The year-to-year datum checks become essential, however, if the data are subsequently to be

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included in the PSMSL ‘Revised Local Reference (RLR)’ component of the dataset. The RLR dataset contains records for which time series analysis of sea level changes can be performed. Long records from this dataset have been the basis of all analyses of secular changes in global sea level during the last century. The geographical distribution of longer RLR records contains significant geographical bias toward the Northern Hemisphere, a situation that is being rectified by means of international collaboration. Aside from its central role of operation of the global sea level data bank, the PSMSL has a responsibility as a member of FAGS to provide the sea level community with as full a Service as possible with regard to the acquisition, analysis, and interpretation of sea level data. Consequently, the PSMSL provides a range of advice to tide gauge operators and data analysts. It has occupied a central planning and management role in the development of the Global Sea Level Observing System (GLOSS) of the IOC. Through GLOSS and via other routes, the PSMSL provides advice and training to national sea level authorities and individual sea level scientists and technologists. In addition to the provision of training materials (e.g., tide gauge operation manuals), the PSMSL supplies software packages suitable for tidal data analysis and quality control purposes. In addition to the training courses associated with GLOSS, the PSMSL has every few years hosted important study groups and international conferences on sea level science. The study groups have concerned themselves with topics such as the use of global positioning system (GPS) receivers at tide gauge sites to determine the local rates of vertical land movement and have been held under the auspices of the International Association for the Physical Sciences of the Ocean (IAPSO) Commission on Mean Sea Level and Tides (CMSLT), the scientific body to which

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Figure 1. Distribution of PSMSL stations.

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the PSMSL reports formally. The PSMSL hosted a major Symposium in Vienna in 1991 as part of the International Union of Geodesy and Geophysics (IUGG) Congress, an international conference at the Linnean Society in London in 1993 as part of its 60th anniversary celebrations, co-organized ‘‘Tidal Science 96’’ at the Royal Society in London in 1996, and took a major part in ‘‘A Celebration of UK Sea Level Science’’ at the Royal Society in 2004. The proceedings of each of these conferences have since been published. A further major conference is planned in 2008 for the PSMSL 75th anniversary. Probably the most important recent scientific publications with which the PSMSL is associated are those of the First (1990), Second (1995), and Third (2000) Scientific Assessments of Intergovernmental Panel on Climate Change (IPCC). The PSMSL Director has been a lead author for the sea level chapters in each of the IPCC studies. Major conclusions have been that global sea level has indeed risen by approximately 10–20 cm during the past century and may rise by amounts several times larger during the next 100 years. The PSMSL is conscious that developments in technology have expanded the field of sea and land level studies. During the 1990s, satellite radar altimetry and GPS recording become established techniques, whereas space gravity offers the potential for being an effective source of sea-level-related information in the future. Therefore, the PSMSL maintains full participation with altimeter and space gravity working groups in view of the importance of those techniques to sea level research. PSMSL personnel have Principal Investigator status for the TOPEX/Poseidon, Jason, ERS, and Envisat altimeter missions, in addition to the GRACE and GOCE space gravity projects. The major challenge for the future, to which the PSMSL is committed, is to see the established tide gauge and new space-based techniques closely linked within one coherent global sea level monitoring system. READING LIST Woodworth, P.L. and Player, R. (2003). The Permanent Service for Mean Sea Level: an update to the 21st century. J. Coastal Res. 19: 287–295. Woodworth, P.L., Aarup, T., Merrifield, M., Mitchum, G.T., and Le Provost, C. (2003). Measuring progress of the Global Sea Level Observing System. EOS, Trans. Am. Geophys. Union. 84(50): 565.

MARINE AND ESTUARINE MICROALGAL SEDIMENT TOXICITY TESTS IGNATIO MORENO-GARRIDO ´ M. LUBIAN ´ LUIS ´ BLASCO JULIAN Institute of Marine Sciences of Analucia Cadiz, Spain

The term microphytobentos refers to the microscopic algae that live on the submerged (temporary or not)

floor in fresh water, estuarine, or marine environments. Microphytobenthos are mainly composed of mobile, pennate diatoms and cyanophytes. In marine and estuarine environments, those organisms can be found in habitats such as salt marshes, submerged vegetation beds, intertidal (sand or mud) flats, or subtidal sediments where light permits microalgal growth. As the presence of these photosynthetic organisms is not always evident, MacIntyre et al. (1) borrowed the term ‘‘secret garden’’ from the homonymous book published in 1888 and written by Frances Hodgson Burnett (1849–1874), in order to make a literary allusion to microphytobenthos. In fact, habitats where microphytobentos are the only primary producers are recognized as ‘‘unvegetated’’ areas, but the concentration of chlorophyll a in the upper 0.5 cm of the sediments where those organisms live generally exceed the depth-integrated chlorophyll in the entire overlying water column (2). In some cases, chlorophyll from microphytobenthos can be up to six orders of magnitude higher than that for the overlying water (3). Nevertheless, some authors estimate that primary production in the bottom would be lower than in the free plankton in spite of that exceptional data (4). But in some habitats, biomass from benthic microalgae can match or even exceed biomass of bacteria present in the same space (5). Thus, microphytobenthos necessarily play a key role in the benthic trophic webs (6–8). In certain biocenosis, the organisms of the microphytobenthos are the main—sometimes the only—source of carbon for grazers or bacteria (7,9,10). The microphytobenthos are also very important in relation to the stability of coastal and estuarine sediments. Although some cyanobacteria can show hydrophobicity as a mechanism to attach sediment particles or other cells (11), the main strategy of microphytobenthos to keep attached to the sediment is the production of agglutinant molecules [carbohydrates (CH) or exopolysaccharides (EPS)] (12–15). The presence of these molecules has important trophic implications, but their role in the maintenance of the structure of the upper part of the sediment is also important (16–19), because the film of adherent substances produced by microphytobenthos increases the sediment stability. Toxicants such as herbicides can alter microphytobenthic growth and the production of CH and EPS can be diminished. A loss of sediment stability can induce an increase in the turbidity of the water and a higher rate of deposition of fine particles on submerged higher plants or macroalgae, thus reducing even more the primary production of the whole and adjacent systems (20). The importance of sediments in accumulation of xenobiotics in coastal and estuarine environments has been pointed out. Most chemical contaminants entering marine or estuarine environments eventually accumulate in sediments due to different reasons, including higher salinity values that diminish solubility of such substances in water. Sediment can act as a sink for these substances but also as a subsequent source for the same (25). On the other hand, and except in cases of extreme contamination, chemical data by themselves do not predict hazard (21,22). Thus, bioassays are needed to assess the potential toxicity of sediments.

MARINE AND ESTUARINE MICROALGAL SEDIMENT TOXICITY TESTS

In spite of the importance of microphytobenthos, few efforts have been made to develop standard toxicity test on these organisms. Guidelines from the SETAC (23) and recent revisions (24–27) about toxicity testing on benthic organisms offer good information on macro and meiofauna but completely ignore microphytobenthos. The reason for this ‘‘exclusion’’ cannot be found in the lack of importance of benthic microalgae, because of all the reasons expressed above. Probably the most important reasons for the scarcity of work on microphytobenthos ecotoxicology are the difficulties that this biological material cause. First, it is not easy to efficiently remove microphytobenthos from sediments. Size and weight of microalgae on the sediment match part of the sediment particles mixed with them. There are descriptions of techniques that use the migration capacity of the microphytobenthic organisms in order to remove them from sediment. It is well known that microphytobenthos vertically migrate through the sediment as a function of the light and tide conditions. During low tide and light conditions, cells unbury and remain at the surface of the sediment, but during high tide or night conditions, microphytobenthic cells bury themselves again, in order to avoid being removed by the current or waves or grazed during nonphotosynthetic conditions (1,28,29). This vertical movement can be exploited to make cells migrate through a plankton net separated from the sediment by one or more lens tissue papers (8). Other authors improved on this method by covering the plankton net with a few millimeters of silica powder, where

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living mobile cells accumulate (30). Less effective seems to be the technique that uses the adherent capacity of microphytobenthos for removing cells by the disposition of a cover glass on the sediment (19). It is supposed that cells will attach to the cover glass, but it is not easy to ensure the efficiency and repeatability of the technique. Another approach is to take cores (made of Plexiglas, PVC, or other materials) (31) from the upper sediment and resuspend subsamples of the previously sliced sediment in order to directly count (and taxonomically identify) cells by light microscopy (4). This latter method ensures the integration of all species (motile or not). The use of fluorescence microscopy can help in distinguishing photosynthetic cells from debris: with a blue filter and a barrier filter of 530 nm, chlorophyll emits a bright red fluorescence that clearly reveals cells and facilitates their localization and count, something that is difficult if this technique is not used (32,33) (Fig. 1). Other techniques use density differences to separate diatoms from debris by centrifugation in a Percoll gradient (34). Although this technique seems to be good for isolating cells, the percentage of cell recovery is low (near 5% of total population in natural locations). Due to the difficulties of handling cells among the sediment, several works were limited to analyzing photosynthetic pigments or photosynthesis in the upper sediments (35–37) as biomarkers for the microphytobenthic biomass. The analysis of degraded pigment molecules in sediments can be useful as a biomarker for grazing pressure (38).

Figure 1. Cells of the diatom Cylindrotheca closterium among sediment particles, observed under fluorescence microscopy. Using a barrier filter of 530 nm, the two chloroplasts of each cell are bright red, facilitating the counting and location of the algal cells.

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But difficulties in handling microphytobenthos do not end there. The disposition in ‘‘patches’’ of microphytobenthos in field locations is evident, providing a spatial heterogeneous distribution of the cells (39,40). This spatial distribution is sometimes conditioned by the presence of ridges and runnels (41) in the sediment surface, provoked by the natural dynamics of the ecosystem. This must be taken into account when estimations of microphytobenthic organism density are intended to be developed in actual locations (15). Delgado (4) described spatial heterogeneity in the delta of the Ebro River as being insignificant over distances between 10 cm and 10 m. Another consideration is that in emerged (low tide) conditions, there is a process of gradual compaction of sediment due to dewatering, which implies a higher density but a lower content of total pigments, exopolysaccharides, or individuals (42). In spite of all this, in situ or in vitro bioassays involving microphytobenthos should be considered as powerful tools to determine potential toxicity of sediments (24). Some efforts have been made in this direction. Wong et al. (43) described a microalgal toxicity test on sediments from the coast of Hong Kong, but they used a planktonic (and not benthic) species (the chlorophyte Dunaliella salina) that, additionally, belongs to a genus that demonstrates strong resistance to toxicants. Abalde et al. (44) did not find growth inhibition of populations of D. tertiolecta at levels of 8 mg · L−1 Cu, and Moreno-Garrido et al. (45) found that D. salina was the most resistant species to Cu and Cd among the assayed microalgal strains. Each microalgal species shows different sensitivity for toxicants, but there are references showing similar (on the same order of magnitude) sensitivities for very different taxons (46). In this respect, Isochrysis galbana, Cylindrotheca (Nitzschia) closterium, and Nannochloropsis species showed similar responses to water soluble fraction of petroleum. Phytoplankton (free swimming or floating microalgae), periphyton (microalgae growing on solid substrate), and epipsammon (microalgae growing more or less attached to sand) showed comparable toxicity sensitivity responses to paraquat and simazine (47). Other works describe sediment toxicity tests on elutriates or extracts (48). Tolun et al. (49) described experiments where natural sediment toxicity tests on Phaeodactylum tricornutum, based on elutriates and bulk exposure, are compared: in the case of elutriates, the authors found different degrees of growth inhibition, although for direct exposure to sediments all organisms died, supporting the idea that direct exposure to sediment will give more realistic (or more sensitive) responses because part of the toxicants could not be extracted in elutriates or extracts (50). A very interesting approach to sediment toxicity tests on benthic algae was that made by Dahl and Blank (31), in which epipsammic communities were transported to a laboratory where they were kept and used in subsequent measurements of metabolic activities and short-term toxicity tests. Cairns et al. (51) defended the use of microorganisms in toxicity tests, because they can show very high sensitivities to toxicants and thus should be included in regulatory-proposed guidelines. But incorporation in those guidelines of multispecies tests that could be more ‘‘environmentally realistic’’ are very slow, fundamentally

because of methodological questions (regarding replication and reproducibility). On the other hand, predictions based on multispecies tests are no more accurate than those based on monospecific bioassays, which are cheaper and more reproducible than a multispecies bioassay (51). As far as we know, the first attempts to develop a standardized, repeatable protocol for sediment toxicity testing involving a microphytobenthic strain and direct exposure of microalgal cells to sediment have only recently taken place (32,33). In those works, populations of the benthic diatom Cylindrotheca closterium were exposed to sediment spiked with heavy metals or tensides. The test also considers the effect of particle size distribution on growth of the tested microalgal strain, which could mask actual responses of algae to present toxicants in other experiments such as those described by Tolun et al. (49). The test is simple, repeatable, and cheap, and it does not require special facilities other than those found in any laboratory. It is based on the 72-h algal growth inhibition test from OECD (52), adapted to sediments and marine or estuarine habitats. Cylindrotheca closterium, formerly known as Nitzschia closterium, demonstrated to be a good subject in other toxicity bioassays and there is a good pool of previous information about this species (53–58). This species is cosmopolitan for temperate coastal waters, ubiquitous, easy to handle in the laboratory, fast growing, sensitive to toxicants, and presents very low nutrient requirements. Nevertheless, other species have been assayed and compared with C. closterium in order to detect toxicity in natural sediments. EC50 values were calculated for three benthic diatoms exposed to sediment obtained from six different locations from Aveiro Lagoon (Portugal). Those values are shown in Table 1. Locations I, II, and VI were less toxic to microalgae than locations III, IV, and V, since C. closterium is slightly more sensitive than the other two species assayed for the majority of the samples. When a chemical analysis of the samples was performed and a similarity analysis carried out crossing toxicity values with possible substances involved (heavy metals, C, N, PCBs), it was found that some heavy metals (Sn, Zn, Hg, Cu, and Cr) had a great effect (Sn the greatest), as shown by the more than 50% of similarity between samples that showed significant growth inhibition for the benthic diatoms assayed (unpublished data). Other recent work from Adams and Stauber (59) also describes a whole-sediment toxicity test on a benthic microalgal diatom (Entomoneis cf. punctulata). In this case, a flow cytometer is used to detect viability of living algae by the use of a fluorochrome (fluorescein diacetate,

Table 1. EC50 Values for Sediments from Six Locations at the Aveiro Lagoon (Portugal) and Three Benthic Diatoms Sample Sites Algal Species P. tricornutum C. closterium Navicula sp.

I N.I. 92 N.I.

a

II

III

IV

V

VI

N.I. 90 N.I.

27 62 64

51 31 71

62 61 65

N.I N.I. N.I.

a If 100% of the sediment does not exhibit a growth inhibition value of 50%, EC50 is denoted as N.I. (no inhibition).

MARINE AND ESTUARINE MICROALGAL SEDIMENT TOXICITY TESTS

FDA). In this technique, used previously (60) to determine the toxic response in planktonic microalgal cells, FDA absorbed by living or dead cells is only hydrolyzed by nonspecific esterases inside the living cells. Hydrolyzed FDA is converted into fluorescein and can be detected by flow cytometry techniques. Although the FDA technique is less sensitive than growth inhibition measurements (60), flow cytometry opens a wide field of possibilities for microalgal toxicity testing on sediments, because several different fluorochromes can be used to measure quite different cellular parameters used as biomarkers.

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MARINE STOCK ENHANCEMENT TECHNIQUES JANA DAVIS Smithsonian Environmental Research Center Edgewater, Maryland

The United Nations estimates that 28% of all ocean fishery stocks are overexploited or severely depleted, and another 47% is fully exploited (1). Included in this statistic are species that are long-lived and short-lived, open-ocean and coastal, migratory and sedentary. About 75% of fishery

MARINE STOCK ENHANCEMENT TECHNIQUES

stocks are unable to withstand further exploitation, so only 25% of stocks remain to satisfy the increasing human demand, as human population grows, for fishery products. As a result of the pressure on fishery populations and the degradation of many of these resources, a suite of fishery management techniques have been developed. One such technique, stock enhancement, is broadly defined as the (human) activity by which the population of a species is increased. In contrast, more traditional management techniques generally focus on limiting human activities that reduce the population of a species. Traditional measures may focus on reducing fishing effort, for example, by limiting the number of days fishermen can fish, restricting the amount of gear a fishermen can use, regulating the type of gear a fisherman can deploy, or setting restrictions on the types of individuals caught by size or gender. Not only does this latter method serve to reduce catch, it strives to shift the pressure away from more reproductively important individuals toward those with less likely contributions to the next generation over the course of their lifetimes. GOALS OF STOCK ENHANCEMENT: A NONTRADITIONAL MANAGEMENT TECHNIQUE The technique of stock enhancement, while often used in concert with more traditional catch-reducing techniques, does not describe limitations to human activities but rather the active improvement of a fishery stock. Enhancement efforts can encompass many approaches. The population can be bolstered both by increasing carrying capacity (the number of individuals that can be supported by their habitat) or by increasing the number of individuals themselves (2,3). The former method is effective only when the factor limiting population is related to habitat, food, or some other resource. The latter method, a special case of aquaculture, is effective only when the habitat can hold more individuals than it does at present. The key to success in stock enhancement is to identify the factor(s) that limit the population in question and then increase the level of that factor. Incorrect identification of this factor could lead to wasted time, money, and energy. Consider the hypothetical case of a coral reef fish. If the fish population is not habitat-limited, but is recruitment-limited, adding more coral reef habitat would likely serve only to spread out the population spatially. No additional recruits would be available to settle on the new habitat substrate. On the other hand, if the fish is habitatlimited, adding additional individuals will not increase the ultimate population, as there would be no space for them to occupy. Enhancement directed toward habitat-limited populations has included efforts to enhance stocks of both fish, especially salmonids, and invertebrates (4–7). Often these cases are referred to as ‘‘habitat restoration,’’ stressing the action rather than the consequence. Most often when people refer to ‘‘stock enhancement,’’ they are referring to hatchery-raised individuals, usually juveniles, that are released into the wild to bolster recruitment-limited populations directly. These added juveniles are raised outside

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of the system, for example, in, an aquaculture facility or a field pen. The juveniles may be offspring of wild parents collected from the field (8) or offspring from generations of parents held in captivity (9). The goal of stock enhancement is to raise the individuals beyond the initial phase of high early lifehistory mortality and then release them into the wild. The stage at which they are released is determined through economic optimization, survivorship maximization, or a combination of both. Maintaining individuals, especially heterotrophs, in a hatchery or a pen is expensive. The expense tends to increase as organisms grow. One might calculate the optimum release size or age as a trade-off between the cost of maintaining an individual in the hatchery and the survivorship advantage that the hatchery offers. Often, as individuals grow, the survivorship advantage of the hatchery environment over the natural environment begins to reverse. Many organisms are cannibalistic when held in extremely high densities (10), a trend that increases as organisms grow. Disease transmission also becomes a problem at high densities. Lowering densities requires an expensive solution of creating more tank or pen space. Therefore, at a certain point, mortality rates are actually lower if the organisms are released into the wild than if held in the hatchery. The optimum release point is different for each species. For example, Kemp’s ridley sea turtles are released at the age of 1 year (11). Blue crabs are released at the age of 2 to 3 months (12). Individuals that are never released but harvested in the hatchery are part of a complete aquaculture program such as, for example, farm-raised salmon, catfish, or shrimp (13,14). In populations truly at risk, the goal of stock enhancement is not simply to provide more fish to catch. Ideally, after release, these hatchery-reared individuals contribute to the spawning stock and have a potential exponential impact on overall population generation after generation, depending on the degree of recruitment limitation. In these cases, a purely economic model to predict optimum size at release is not appropriate. Stock enhancement therefore has a potential role beyond fishery application and into the realm of threatened or endangered species protection. STOCK ENHANCEMENT EXAMPLES Stock enhancement techniques have been applied to many types of organisms worldwide. Finfish populations have been the most common recipients of hatchery-raised juveniles, including many salmon from both the Atlantic and Pacific (15,16), Japanese flounder (17), Hawaiian mullet (18), Nassau grouper (19), and Chesapeake Bay striped bass (20), just to name a few. Holothurians have been hatchery-raised for stock enhancement (21). Bivalves, such as quahogs (22) and soft-shell clams (23), and gastropods, such as abalones (24) and queen conch (25), have been the subject of stock enhancement efforts. Finally, crustaceans are beginning to receive more attention as possible stock enhancement targets; programs have been initiated for decades with American and

126

MARINE STOCK ENHANCEMENT TECHNIQUES

European lobsters (26,27), more recent programs for prawn (28) and the Japanese swimming crab (3), and a new exploratory program established for the Chesapeake Bay blue crab (8). Stock enhancement efforts extend worldwide. In Japan, stock enhancement programs are in place for at least 34 finfish and 12 crustaceans (3). Programs relying on various specific techniques exist in South America, North America, Africa, Europe, Asia, Australia/New Zealand, and in the developed world as well as the developing world (29–31). Specific techniques to optimize stock enhancement depend on the life-history traits of the species. Sessile organisms may be enhanced by seeding areas with young individuals (32). Depending on how closely the success of the enhancement effort is to be monitored, more mobile species may be released into isolated areas where they can be followed, similar to the idea of stocking freshwater lakes (8,28). For extremely mobile open-ocean species, juveniles are released into the open ocean (3), and even if tagged, large numbers cannot be followed over time. PROBLEMS OF STOCK ENHANCEMENT Enhancement has been a controversial management method for several reasons (15,29,33). First, hatcheryraised animals may not survive well in the wild. The hatchery environment can offer conditions very different from the natural environment: food is likely to be different, the method of foraging is different, and therefore the hatchery-raised organisms may have mortality-threatening inexperience with natural prey after their introduction into the wild. They may similarly be inexperienced in avoiding predators. Holding tanks may restrict movement, may have unnatural substrates, may have unnatural light regimes, or may have different flow regimes. As a result of all of these differences, stock enhancement efforts, often funded by the taxpayer, may not be successful (34). Many studies have noted differences in hatchery-raised and wild individuals in factors such as behavior, morphology, growth rates, and therefore survivorship (17,35,36). A second concern is that hatchery-raised individuals may be too successful. Hatchery animals may compete with and displace wild animals (2,37). If at any point the population becomes habitat-limited, rather than recruitment-limited (or if the stock enhancement effort pushes the population over the carrying capacity), the survivorship of wild individuals may actually decrease. The ultimate result would then be a decline in the population of wild individuals, even if the overall population has increased. A third concern is that hatchery-raised organisms may carry diseases into the wild, affecting the survivorship of wild individuals. Fourth, increases in stock size due to hatchery successes may provoke a rise in fishing effort and therefore greater pressure on the remaining wild individuals (34,38). Stock enhancement efforts are generally performed in concert with traditional management techniques, such as lowering catch and/or restricting catch to certain segments of the population. However, if the human population increases, pressure

may be put on managers to reduce fishing regulations. Again, the ultimate result would be a decline in the survivorship rates of wild individuals, even if overall population has increased. Finally, and perhaps the reason for the controversy generating the most attention in recent years is genetics, or ‘‘gene dilution.’’ Even if efforts in the hatchery are expended to obtain brood stock from many different parents, genetic variability in the brood stock is unlikely to approach that of the wild parental stock. The offspring produced will be more similar to each other than the offspring of wild stock. Opponents of stock enhancement fear that releasing genetically relatively homogenous hatchery individuals will reduce genetic variability in wild populations as hatchery and wild individuals interbreed. The ultimate result after several to many generations might be a decline in population because lack of genetic diversity can limit a population’s response to environmental change. The controversy over stock enhancement has been fueled by the fact that most enhancement efforts have not been studied quantitatively (37,41,42). Quantitative, hypothesis-driven study did not begin until the late 1980s (43). However, now that the necessity to understand better the outcomes of enhancement programs has been recognized, in many cases the enhancement process has been refined. Methods to select better candidate species have been developed (44). Advances in tagging techniques have allowed better assessment and comparison of hatchery and wild animal survivorship (44). Most importantly, calls have been made for quantitative study of small-scale enhancement efforts before investment in large-scale programs begins (42,43). OPTIMIZING STOCK ENHANCEMENT SUCCESS Stock enhancement is becoming a more often commonly used method for addressing declines in fished species. Many of the problems identified above can be addressed to a comfortable degree before the program is initiated. For example, several programs are considering conditioning individuals to limit the differences between hatcheryraised and wild organisms before release into the wild (12,45,46). In this way, survivorship rates of hatchery organisms are increased, along with the output per enhancement program dollar spent. In addition, carrying capacities of targeted release areas can be determined before programs are initiated to (1) determine whether the case is appropriate for stock enhancement and (2) determine optimum release densities of hatchery-raised organisms. Certain microhabitats within a targeted release region may have higher carrying capacity and greater food or refuge resources than others, and therefore distribution of hatchery-raised organisms can be optimized. Methods of determining whether stock enhancement is successful are more difficult. Determining success requires knowledge about how well hatchery-raised organisms survive, how well wild organisms survive to allow comparison, and the contribution of hatchery organisms to the total population. As programs are developed, a wide

MARINE STOCK ENHANCEMENT TECHNIQUES

range of survivorship and contribution values have been reported. For example, survivorship to fishery size was 3–4% for stocked panaeid shrimp (28), 21% for red drum in Texas (47), and up to 30% for Japanese flounder (3). Even among programs for the same species, values range widely. For example, in some European lobster programs, no hatchery-raised lobsters were recaptured in the fishery, and in others, 10–35% of landed lobsters were of hatchery origin (37). Often the steps to quantify the success of a stock enhancement program take years of scientific study and require laborious study efforts, such as tagging and resampling individuals over time. Such efforts have been deemed mandatory by critics of stock enhancement programs before public monies are used to support these efforts to bolster fishery stocks, one of the world’s most important natural resources. BIBLIOGRAPHY 1. Food and Agriculture Organization of the United Nations. (2002). The State of World Fisheries and Aquaculture. United Nations, Rome, Italy. 2. Castro, K.M., Cobb, J.S., Wahle, R.A., and Catena, J. (2001). Habitat addition and stock enhancement for American lobsters, Homarus americanus. Mar. Freshwater Res. 52: 1253–1261. 3. Masuda, R. and Tsukamoto, K. (1998). Stock enhancement in Japan: Review and perspective. Bull. Mar. Sci. 62: 337–358. 4. Beamesderfer, R.C.P. and Farr, R.A. (1997). Alternatives for the protection and restoration of sturgeons and their habitat. Environ. Biol. Fish. 48: 407–417. 5. Hendry, K., Cragge-Hine, D., O’Grady, M., Sambrook, H., and Stephen, A. (2003). Management of habitat for rehabilitation and enhancement of salmonid stocks. Fish. Res. 62: 171–192. 6. Peterson, C.H., Grabowsi, J.H., and Powers, S.P. (2003). Estimated enhancement of fish production resulting from restoring oyster reef habitat: Quantitative valuation. Mar. Ecol. Prog. Ser. 264: 149–264. 7. Rodwell, L.D., Barbier, E.B., Roberts, C.M., and McClanahan, T.R. (2003). The importance of habitat quality for marine reserve—fishery linkages. Can. J. Fish. Aquat. Sci. 60: 171–181. 8. Davis, J.L.D., Young-Williams, A.C., Hines, A.H., and Zohar, Y. (in press). Assessing the feasibility of stock enhancement in the case of the Chesapeake Bay blue crab. Can. J. Fish. Aquat. Sci. 9. Iguchi, K., Watanabe, K., and Nishida, M. (1999). Reduced mitochondrial DNA variation in hatchery populations of ayu (Plecoglossus altivelis) cultured for multiple generations. Aquaculture 178: 235–243. 10. Kestemont, P. et al. (2003). Size heterogeneity, cannibalism and competition in cultured predatory fish larvae: Biotic and abiotic influences. Aquaculture 227: 333–356. 11. Caillouet, C.W., Fontaine, C.T., Manzella-Tirpak, S.A., and Shaver, D.J. (1995). Survival of head-started Kemp’s ridley sea turtles (Lepidochelys kempii) released into the Gulf of Mexico or adjacent bays. Chelate Conserv. Biol. 1: 285–292. 12. Davis, J.L.D., Eckert-Mills, M.G., Young-Williams, A.C., Hines, A.H., and Zohar, Y. (in press). Morphological conditioning of a hatchery-raised invertebrate, Callinectes sapidus, to improve field survivorship after release. Aquaculture 133: 1–14.

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13. Fleming, I.A. et al. (2000). Lifetime success and interactions of farm salmon invading a native population. Proc. R. Soc. London Ser. B 267: 1517–1523. 14. Wirth, F.F. and Davis, K.J. (2003). Seafood dealers’ shrimppurchasing behavior and preferences with implications for United States shrimp farmers. J. Shellfish Res. 22: 581–588. 15. Washington, P.M. and Koziol, A.M. (1993). Overview of the interactions and environmental impacts of hatchery practices on natural and artificial stocks of salmonids. Fish. Res. 18: 105–122. 16. Thorpe, J.E. (1998). Salmonid life-history evolution as a constraint on marine stock enhancement. Bull. Mar. Sci. 62: 465–475. 17. Kellison, G.T., Eggleston, D.B., and Burke, J.S. (2000). Comparative behaviour and survival of hatchery-reared versus wild summer flounder (Paralichthys dentatus). Can. J. Fish. Aquat. Sci. 57: 1870–1877. 18. Leber, K.M., Blankenship, H.L., Arce, S.M., and Brennan, N.P. (1996). Influence of release season on sizedependent survival of cultured striped mullet, Mugil cephalus, in a Hawaiian estuary. Fish. Bull. 95: 267–279. 19. Roberts, C.M., Quinn, N., Tucker, J.W., and Woodward, P.N. (1995). Introduction of hatchery-reared Nassau grouper to a coral reef environment. N. Am. J. Fish. Manage. 15: 159–164. 20. Secor, D.H. and Houde, E.D. (1998). Use of larval stocking in restoration of Chesapeake Bay striped bass. ICES J. Mar. Sci. 55: 228–239. 21. Battaglene, S.C., Seymour, J.E., and Ramofafia, C. (1999). Survival and growth of cultured juvenile sea cucumbers, Holothuria scabra. Aquaculture 178: 293–322. 22. Walton, W.C. and Walton, W.C. (2001). Problems, predators, and perception: Management of quahog (hardclam), Mercenaria mercenaria, stock enhancement programs in southern New England. J. Shellfish Res. 20: 127–134. 23. Beal, B.F., Kraus, F., and Gayle, M. (2002). Interactive effects of initial size, stocking density, and type of predator deterrent netting on survival and growth of cultured juveniles of the soft-shell clam, Mya arenaria L., in eastern Maine. Aquaculture 208: 81–111. 24. Tegner, M.J. and Butler, R.A. (1985). The survival and mortality of seeded and native red abalones, Haliotis rufescens, on the Palos Verdes Penninsula. Calif. Fish Game 71: 150–163. 25. Stoner, A.W. and Glazer, R.A. (1998). Variation in natural mortality: Implications for queen conch stock enhancement. Bull. Mar. Sci. 62: 427–442. 26. Bannister, R.C.A. and Addison, J.T. (1998). Enhancing lobster stocks: A review of recent European methods, results, and future prospects. Bull. Mar. Sci. 62: 369–387. 27. Beal, B.F., Chapman, S.R., Irvine, C., and Bayer, R.C. (1998). Lobster (Homarus americanus) culture in Maine: A community-based, fishermen-sponsored, public stock enhancement program. Can. Ind. Rep. Fish. Aquat. Sci. 244: 47–54. 28. Davenport, J., Ekaratne, S.U.K., Walgama, S.A., Lee, D., and Hills, J.M. (1999). Successful stock enhancement of a lagoon prawn fishery at Rekawa, Sri Lanka, using cultured postlarvae of penaeid shrimp. Aquaculture 180: 65–78. 29. Bell, J.D. and Gervis, M. (1999). New species for coastal aquaculture in the tropical Pacific: Constraints, prospects and considerations. Aqua Int. 7: 207–223. 30. Cowx, I.G. (1999). An appraisal of stocking strategies in the light of developing country constraints. Fish. Manage. Ecol. 6: 21–34.

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31. Phillips, B.F. and Liddy, G.C. (2003). Recent developments in spiny lobster aquaculture. In: Phillips, B., Megrey, B.A., and Zhou, Y. (Eds). Proc. 3rd World Fish. Congr.: Feeding the world with fish in the next millenium—the balance between production and environment. American Fisheries Society Symposium Vol. 38, pp. 43–57. 32. Barbeau, M.A. et al. (1996). Dynamics of juvenile sea scallop (Placopecten magellameus) and their predators in bottom seeding trials in Lanenburg Bay, Nova Scotia. Can J. Fish. Aquat. Sci. 53: 2494–2512. 33. Li, J. (1999). An appraisal of factors constraining the success of fish stock enhancement programmes. Fish. Manage. Ecol. 6: 161–169. 34. Hilborn, R. (1998). The economic performance of marine stock enhancement projects. Bull. Mar. Sci. 62: 661–674. 35. Mana, R.R. and Kawamura, G. (2002). A comparative study on morphological differences in the olfactory system of red sea bream (Pagrus major) and black sea bream (Acanthopagrus schlegeli) from wild and cultured stocks. Aquaculture 209: 285–306. 36. Davis, J.L.D. et al. (2004). Differences between hatcheryraised and wild blue crabs (Callinectes sapidus): Implications for stock enhancement potential. Trans. Am. Fish. Soc. 37. Bannister, R.C.A., Addison, J.T., and Lovewell, S.R.J. (1994). Growth, movement, recapture rate and survival of hatcheryreared lobsters (Homarus gammarus (Linnaeus, 1758)) released into the wild on the English East Coast. Crustaceana 67: 156–172. 38. Bannister, R.C.A. (2000). Lobster Homarus gammarus stock enhancement in the U.K.: Hatchery-reared juveniles do survive in the wild, but can they contribute significantly to ranching, enhancement, and management of lobster stocks? Can. Spec. Publ. Fish. Aquat. Sci. 130: 23–32. 39. Tringali, M.D. and Bert, T.M. (1998). Risk to genetic effective population size should be an important consideration in fish stock-enhancement programs. Bull. Mar. Sci. 62: 641–659. 40. Utter, F. (1998). Genetic problems of hatchery-reared progeny released into the wild, and how to deal with them. Bull. Mar. Sci. 62: 623–640. 41. Heppell, S.S. and Crowder, L.B. (1998). Prognostic evaluation of enhancement programs using population models and life history analysis. Bull. Mar. Sci. 62: 495–507. 42. Crowe, T.P. et al. (2002). Experimental evaluation of the use of hatchery-reared juveniles to enhance stocks of the topshell Trochus niloticus in Australia, Indonesia and Vanuatu. Aquaculture 206: 175–197. 43. Leber, K.M. (1999). Rational for an experimental approach to stock enhancement. In: Stock Enhancement and Sea ¨ Ranching. B.R. Howell, E. Moksness, and T. Svasand (Eds.). Blackwell Science, Oxford, pp. 63–75. 44. Blackenship, H.L. and Leber, K.M. (1995). A responsible approach to marine stock enhancement. Am. Fish. Soc. Symp. 15: 167–175. 45. Olla, B.L. and Davis, M.W. (1989). The role of learning and stress in predator avoidance of hatchery-reared coho salmon (Oncorhynchus kisutch) juveniles. Aquaculture 76: 209–214. 46. Berejikian, B.A. (1995). The effects of hatchery and wild ancestry and experience on the relative ability of steelhead trout fry (Oncorhynchus mykiss) to avoid a benthic predator. Can. J. Fish. Aquat. Sci. 52: 2476–2482. 47. McEachron, L.W., Colura, R.L., Bumgaurdner, B.W., and Ward, R. (1998). Survival of stocked red drum in Texas. Bull. Mar. Sci. 62: 359–368.

PHYSICAL AND CHEMICAL VARIABILITY OF TIDAL STREAMS PAOLO MAGNI IMC—International Marine Centre Torregrande-Oristano, Italy

SHIGERU MONTANI Hokkaido University Hakodate, Japan

This article focuses on the variability of major hydrologic parameters of tidal streams that occur on different temporal and spatial scales within an individual estuary. Rapid changes in water temperature and salinity take place on a timescale of 31 to 2.0 psu, coincident with the lower low tide, and rapidly increased up to >31 psu again before the following higher high tide (Fig. 1a). At the subsequent higher low tide, the decrease in salinity was less marked, and minimum values were about 25 psu. An overall more restricted fluctuation of salinity occurred in the 1996

PHYSICAL AND CHEMICAL VARIABILITY OF TIDAL STREAMS

(a)

2 Depth, m

(b)

May 30−31, 1995 Spring tide

1 A.M.

Higher high tide

1

2

129

May 28−29, 1996 Neap tide

1 A.M.

1

Temperature, °C

Lower low tide 0

0

22

24 23

21

22

20

21

19

20 19

18

18

Salinity, psu

17

17

16

16

30

30

20

20

10

Dissolved oxygen, mg/L

0

10

(100%)

0 7.0 mg/L (88%)

17.4 mg/L (224%) 15

6 12 9

4

(100%) 6 2

(20%)

3 1.4 mg/L

0 10:00

20:00 6:00 Time, h

1.3 mg/L

0 16:00

10:00

survey, consistent with the reduced amplitude of the tide (Fig. 1b) and a rainfall regime more limited in spring 1996 than in spring 1995 (1). These results show that saline intrusion is a strong function of tidal state (e.g., low vs. high tide) and amplitude (e.g., spring vs. neap tide). They also demonstrate that tidal streams may experience, within a few hours, strong changes in salinity that cause very different habitat conditions at the same location in an estuary. These may vary from oligohaline (0.51–5 psu)

20:00 6:00 Time, h

(20%) 16:00

Figure 1. Daily fluctuations of water depth, temperature, salinity and dissolved oxygen (DO) concentration of a tidal stream in an estuarine intertidal zone (Seto Inland Sea, Japan). Measurements were made using a CTD cast placed ca. 10 cm from the bottom sediment at the end of May of 2 consecutive years (a: 1995; b: 1996). Relevant sensors were logged every 15 min. Notes: horizontal dashed lines in temperature and DO boxes individuate major differences within the same range of values (17–22 ◦ C and 20–100% of air saturation, respectively) recorded in the 2 years. In DO boxes, absolute minimum and maximum values are also indicated. The vertical dashed line is arbitrarily depicted at 1 A.M. to highlight the temporal differences in tidal state and amplitude between the two surveys.

to euhaline (30.1–40 psu) conditions, in agreement with salinity ranges given by the Venice Conference (5). The daily fluctuation in water temperature varied according to the tidal cycle and showed a temporal pattern opposite to that of salinity during both surveys (Fig. 1a, b). The range of temperature was relatively larger in May 1996 (17.7–24.5 ◦ C) than in 1995 (16.9 ◦ C–22.3 ◦ C). In both cases, it was apparent that warmer waters were brought into the estuary by the freshwater runoff during

PHYSICAL AND CHEMICAL VARIABILITY OF TIDAL STREAMS

were conducted (see above section and Fig. 1). Between January 1995 and April 1996, the water temperature varied from 3.6 ◦ C ± 0.3 (December) to 29.0 ◦ C ± 1.8 (July) (Fig. 2). Statistically significant differences were demonstrated for the specific geographical area (latitude 34◦ 21 N, longitude 43◦ 21 E) between a warm period (May–October, water temperature 23.5 ± 4.2 ◦ C) and a cold period (November–April, water temperature 10.0 ± 4.4 ◦ C) (1). The seasonal variability in low-tide salinity (Fig. 2) was consistent with the results obtained from the shortterm measurements of May 1995 and May 1996 during a complete tidal cycle (Fig. 1). In particular, the salinity recorded during the seasonal survey was lowest on May 16, 1995 at 4.6 ± 1.5 psu (Fig. 2). Accordingly, the short-term measurements of May 1995 showed a salinity decrease during low tide to 25 psu between the end of September 1995 and April 1996 and reached the highest values in November 1995 at 31.4 ± 1.1 psu (Fig. 2). Consistently, also during the short-term measurements of May 1996, the decrease in salinity during low tide was more limited than that found in May 1995 (Fig. 1a, b). The DO concentration also varied greatly from 5.4 ± 1.7 mg/L (September 1995) to 15.1 ± 1.1 mg/L (April 1996)

Salinity, psu

40 Temperature, °C

30

20

10

0 15 12 9 6 3 0 20 Jan 17 Feb 17 Mar 15 Apr 16 May 30 May 14 Jun 12 Jul 10 Aug 7 Sep 29 Sep 30 Oct 27 Nov 26 Dec 24 Jan 22 Feb 21 Mar 17 Apr

ebb flow. These results are consistent with the period and site of measurements; physical processes of heat transfer in spring–summer (and water cooling in winter) are most effective in the upper and shallower riverine zone of the estuary (1). Dissolved oxygen (DO) concentration was subjected to strong daily fluctuations, partly as a function of the tidal state (and water depth). The two surveys also showed major differences (Figs. 1a and b). In the 1995 survey, DO concentration was mostly within normoxic values, ranging from 1.4 mg/L to 7.0 mg/L. Differently in the 1996 survey, DO concentration showed a larger variation, in much higher values up to 17.4 mg/L. Elevated DO concentrations are related to ecosystem processes of primary production (6). It is known that shallow lagoons and coastal areas dominated by seagrass or macroalgae are subjected to oversaturation of DO (i.e., >100% of air saturation), especially during the warm period (7,8). Viaroli et al. (7) reported DO oversaturation up to 150% in the near-bottom water of a coastal lagoon dominated by the macroalga Ulva. This was followed by the outbreak of a dystrophic crisis, complete anoxia through the water column at some stations of the lagoon. The development of large amounts of macroalgae (Ulva sp.) also tends to occur in the estuarine sand flat of this study coincident with increasing temperature and solar radiation during the spring. Extended beds of macroalgal biomass were present during the field measurements of the 1996 survey (personal observations). Accordingly, during the daytime measurements of May 28, DO concentration rapidly rose to oversaturation; a major increase of >200% of air saturation occurred between 16:00 and 16:30 (Fig. 1b), indicating a period of major oxygen production by macroalgae. Similar to the extremely high DO values found in this study, Piriou & M´enesguen (9) reported that the in vitro growth of Ulva under light saturation and nutrient enrichment raised the DO concentration to 22 mg/L, 4 hours after the experiment started. By contrast, during nighttime, a progressive decrease in DO concentration occurred, down to hypoxic values of 20. If the water height is small, the cnoidal wave profile becomes the sinusoidal one. The cnoidal wave is periodic with the profile given by   
x t ,κ (5) − η(x, t) = hCn2 2K(κ) L T




2π d tan h L




 =

gL 2π




tan h

2π d L

 (2)

The solitary wave is a progressive wave consisting of a single crest and is not oscillatory as the other examined. The wave form is (4) 

3H 2 (x − Ct) (6) η(x, t) = H sec h 4d3 where C (wave celerity) is defined by  
H C = gd 1 + 2d

(7)

According to the dispersion relation of the linear wave theory, the celerity of water waves in shallow water (Eq. 3) is smaller than solitary wave phase velocity because of the inclusion of terms that depend on H/d. The solitary wave describes enough well waves approaching shallow water, even if wave period or wave

SHALLOW WATER WAVES

length are not associated with the theory. When the wave pass from deep to shallow water their crests peak up and are separated by flat troughs appearing like a series of solitary waves. Solitary theory appears reasonable even if the periodicity is neglected, because in shallow water the period is not particularly significant, but rather the water depth becomes important. As the solitary wave advances into shallow water, its height increases, the crests becomes greater and sharper, the trough becomes longer and flatter: in this condition, a wave is well represented by solitary waves. The solitary wave is not an oscillatory wave, as those obtained with other theories, but a translation one. Water particles, as a wave passes, are subjected to a translation in wave direction, whereas in the oscillatory waves it moves forward and backward, remaining after a period in its original position. Wave profiles, according to the theories illustrated above, are presented in Fig. 1. WAVE REFRACTION AND SHOALING Waves passing from deep to shallow water are subjected to refraction in which the direction of their travel changes in such a way that approaching the coast the crests tends to become more parallel to the depth contours (Fig. 2). To

determine the variation of the wave direction, Snell’s law can be applied sin θ2 sin θ1 = = cons C1 C2

Linear theory wave S.W.L.

Cnoidal wave

S.W.L.

Solitary wave

S.W.L. Figure 1. Wave profiles.

a1

Celerity CA

a2

b1

Greater depth

Contour line

B

A Shallower depth

B

Wave ray

Contour line

Cel e CB rity

a1

Greater depth A

(8)

where q1 and q2 are the angles between adjacent wave crests and the respective bottom contours, whereas C1 and C2 are the wave celerity at the two depths. With a regular bottom (straight and parallel contours), the relation can be applied directly between the angle at any depth and the deep water angle approach. With an irregular bottom, wave refraction may cause a spreading or a convergence of the wave energy. This effect can be easily illustrated taking in account the wave rays (Fig. 2), defined as the lines drawn normal to the wave crests and directed in the wave advance. If the wave rays spread, the wave crests become longer and the energy flux, assumed constant between two rays, must be extended over a greater length. The opposite (energy concentration) happens if the waves rays converge. Actually, the calculations of the rays are made by software based on models such as a mild slope, parabolic, or Boussinesq wave model. Another effect of the change in the wave length in shallow water is that the wave height increases. This effect is the consequence of the energy conservation in

Shallower depth

a2

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Shoreline Figure 2. Wave refraction and wave rays.

b2

Shoreline

SHALLOW WATER WAVES

concert with the decrease of the celerity approaching the shallow water. This phenomenon is referred to as shoaling. The effects of shoaling and refraction in water can be expressed by the following formula: H = H0 Ks Kr

(9)

where H0 is wave height in deep water, Ks is the shoaling coefficient    CG0 1  Ks = = (10)  2π d CG 2n tan h L   with n =

1 1 + 2π d 2 L

tion coefficient

 1 
and Kr is the refrac2π d  senh L

b0 Kr = (11) b

where b0 and b are the distance between two adjacent rays, respectively, in deep water and at a generic depth. For straight and parallel contours lines, the refraction coefficient becomes

cos θ0 (12) Kr = cos θ WAVE BREAKING Waves shoaling causes the increasing of wave height until its physical limit because of steepness of wave H/L. When this limit is reached, the wave breaks and dissipates energy. Battjes (5) has shown that the breaking wave characteristics can be correlated to a parameter, called surf similarity x, which is defined as tan β ξ=

H0 L0

— spilling (x < 0.5), in which each wave gradually peaks until the wave becomes unstable and cascades down as white water, bubbles, and foam; — plunging (0.5 < x < 3.3), in which the shoreward face of the wave becomes vertical, curls over, and

Spilling

Plunging

plunges forward and downward as an intact mass of water; — surging (3.3 < x < 5), in which the base of the wave, while it is peaking up, finds the shore, and then the crest collapses and disappears. When the surf similarity x is >5, reflection happens and no breaking occurs. According to Galvin (6), a fourth breaker, called collapsing, intermediate between plunging and surging types, exists. It is difficult to identify which type of breaker can verify, because it depends on the individual heights and interactions of the waves. Plunging and surging breakers can be seen on a beach during the same storm. However, spilling breakers are typical of very low sloping beaches with waves of high steepness values; plunging waves occur in steeper beaches and waves of intermediate steepness; surging, instead, is associated with high gradient beaches with waves of low steepness. The breaking happens when the water particle velocity is greater than wave celerity. According to solitary wave theory, this condition is described by (7)


Hb db

 = 0.78

(14)

max

where the subscript b denotes the breaking. Laboratory tests pointed out that Equation (14) is verified more for oscillatory waves than solitary wave. However, it is considered fundamental to express the relation between the relative depth and the breaking condition. Other parameters playing a role in wave breaking exist, such as beach slope and bottom roughness. An empirical relation considers the beach slope m (8):


(13)

where tan b is the beach slope and H0 and L0 are the wave height and length in deep water, respectively. Three common type of breakers are recognized (Fig. 3):

137

Hb db

 = 0.75 + 25m − 112m2 + 3870m3

(15)

max

in which as the slope increases, the breaking happens more and more nearshore. Another expression was developed by Goda (9)  
L0 15π db (1 + 15m4/3 ) 1 − exp − db L0 max (16) where L0 is the deep water wave lenght. For irregular waves (waves with different height and period), Kamphuis (10) proposed two criteria based on


Hb db



= 0.17

Collapsing

Surging

Figure 3. Breaking types.

138

WATER WAVES

extensive model tests




Hsb = 0.095e4m Lbp tan h

2π db Lbp

(17)

hurricane may generate huge waves. This storm usually causes disasters. Tidal and wind waves contain a lot of energy. Electric power can be generated by them.

(18)

BASIC CHARACTERISTICS OF A WATER WAVE



Hsb = 0.56e3.5m db

where Hsb is the significant wave breaking, Lbp the breaking wave length, and db is the breaking depth. BIBLIOGRAPHY 1. Airy, G.B. (1845). Tides and waves. Encyclopedia Metropolitana. 192: 241–396. 2. Korteweg, D.J. and de Vries, G. (1895). On the change of form of long waves advancing in a rectangular canal and on a type of long stationary wave. Phil. Mag. 5: 442–443. 3. Wiegel. (1960). 4. Russell, J.S. (1884). Report on waves. 14th Meeting of the British Association for the Advancement of Science. pp. 311–390. 5. Battjes, J.A. (1974). Surf similarity. Proceedings of the 14th Coastal Engineering Conference, ASCE. pp. 466–497. 6. Galvin, C.J. (1968). Breaker type classification on three laboratory beaches. J. Geophys. Res. 73: 3651–3659. 7. Munk, W.H. (1949). The solitary wave theory and its application to surfs problems. Ann. New York Acad. Sci. 51: 376–424. 8. SPM. (1984). 9. Goda, Y. (1970). A synthesis of breaker indices. Trans. Japan Soc. Civil Engrs. 2: 227–230. 10. Kamphuis, J.W. (1991). Wave transformation. Co. Eng. 15: 173–184.

FURTHER READING CERC U.S. Corps of Eng. (1984). Shore Protection Manual. Vicksburg, VA.

WATER WAVES

The water wave was studied mathematically in the nineteenth century as a form of oscillatory wave. In 1847, Stokes (1) published his famous paper entitled ‘‘On the theory of oscillatory waves.’’ Stokes’ wave theory has been widely used till now. The elements of an oscillatory wave are wave height, wave period, and wavelength. The wave height H is the distance between the wave crest and trough. The wavelength L is the distance between successive crests, and the wave period T the time difference between successive crests. In deep water, the water depth H is larger than the half of the wavelength L. After Stokes, L is a function of the wave period T in the following equation: gT 2 (1) L= 2π The wave celerity C is then C=

National Taiwan University Taipei, Taiwan

INTRODUCTION As one stands at the coast, an endlessly moving succession of irregular humps and hollows can be seen reaching to the shore. This is the water wave generated by wind. There are different kinds of water waves, which are driven by different forces. Beside wind waves, the tide and the tsunami are other well-known water waves. Different Water waves are distinguished by their wavelength, which is defined as the length between successive humps. The wavelength of a wind wave is shorter and is easily recognized. A water wave is an important physical phenomenon in an ocean, sea, or lake. It influences beach morphology, maritime structures, and human activities very much. Because the wind varies tremendously, a typhoon or

(2)

in which g is the earth’s gravitational acceleration. Obviously, the celerity C is proportional to the wave period T. The water depth is less than L/2, so then the wave particle movement touches the bottom. Tides and tsunamis usually are shallow water waves or long waves. Equations 1 and 2 become the following: 
2π h gT 2 (3) tanh L= 2π L
 2π h gT C= tanh (4) 2π L A wave contains kinetic and potential energy. The average energy E per unit sea surface area is the following: E=

NAI KUANG LIANG

gT L = T 2π

1 ρgH 2 8

(5)

The wave energy propagates in a group velocity, Cg, which is given by the following equation (2):
 4π h/L C 1+ (6) Cg = 2 sinh 4π h/L The wave energy flux P is as follows: P = E · Cg

(7)

A real ocean wave is not oscillatory, as Stokes’ theory described, but irregular in a stochastic process. Pierson (3,4) introduced the technique of communication engineering to the ocean wave and proposed the random wave theory. The ocean wave would be a superposition of sinusoidal wave components of different directions, amplitudes, frequencies, and angular phases, in which the phase is a random variable of equal probability density between—π and π . Then the ocean wave can be represented by a power spectrum. However, for

WOODS HOLE: THE EARLY YEARS

convenience, engineers usually use the significant wave to represent the ocean wind wave. For a group of N wave heights measured at a point, waves are ordered from the largest to the smallest and assigned a number from 1 to N to them. The significant wave height H1/3 is defined as the average of the first (highest) N/3 wave heights (5). The order of the wave period is accompanied by its wave height as a pair. The significant wave period T1/3 is defined as the average of the first N/3 wave periods. WIND WAVE FORECASTING During the Second World War, two famous American oceanographers, Dr. H.U. Sverdrup and Dr. W.H. Munk, were assigned by the U.S. Navy to develop a wind wave forecasting scheme for the Normandy landing operations. The work was originally completed in 1943 and classified and published in 1947(6). Later, the scheme was extensively patched and amended by Bretschneider(7). Therefore, the scheme has been named the SMB method. In the SMB method, the wind speed, wind duration, and fetch are the main parameters, where fetch is defined as the wind blowing distance in the water area. Modern ocean wave modeling was initiated in 1956 and extensively developed and revised (8). So far it is still developing. The basic concept is the evolution of energy spectrum F governed by the energy balance equation: df = Sin + Snl + Sds dt

(8)

in which Sin is the energy input flux from wind to wave spectrum components, Snl the energy flux exchange due to nonlinear wave–wave interaction, and Sds the energy flux output due to dissipation. The present operating ocean models are WOM, NWW3, etc. TYPHOON WAVE The typhoon or hurricane is an atmospheric eddy that originates in tropical or subtropical ocean regions. The typhoon wind speed is usually very high so that the typhoon wave plays a significant role in the design of coastal and offshore structures. Because the wind velocity changes rapidly, the generation process within typhoons is complicated. Parametric typhoon or hurricane wave prediction models were developed (9,10), which pointed out that the maximum wave exists at the right side of the typhoon center as one faces the forward direction. The radius of a typhoon is about 200–400 km. When a typhoon is still far away from a location, the swell may arrive because the swell energy propagates usually faster than the typhoon moves. The typhoon can be regarded as a point source of wave generation. If Person A, who does not move, throws balls to Person B at a fixed time interval and the speed of the ball relative to the ground is constant, then Person B receives balls at the same time interval. If Person A moves toward Person B, Person B receives balls at a shorter time interval. If the ball is like energy, Person A throws more energy flux to Person B, as Person A moves toward Person B. This is the same as the well-known Doppler effect. As a whistling

139

train moves toward an observer, the sound heard by the observer is higher in frequency than the actual whistle at the source. The observer receives more sound energy flux. As shown in Equation 7, wave energy flux P is wave energy E × group velocity Cg, which is proportional to the wave period. The wave energy is proportional to H 2 (Equation 5). Because the typhoon wave moving speed has little effect on the swell period, then the swell height is enhanced, as the typhoon approaches a station (11). There were cases where swell heights were larger than those inside the typhoon because the moving velocity was close to the group velocity of the swell. BIBLIOGRAPHY 1. Stokes, G.G. (1847). On the theory of oscillatory waves. Trans. Cambridge Philos. Soc. 8: 441. 2. Kinsman, B. (1965). Wind Waves: The Generation and Propagation on the Ocean Surface. Prentice-Hall, Englewood Cliffs, NJ. 3. Pierson, W.J., Jr. (1952). A Unified Mathematical Theory for the Analysis, Propagation and Refraction of Storm Generated Ocean Surface Waves, Parts I and II. New York University, College of Engineering, Research Division, Department of Meteorology and Oceanography prepared for the Beach Erosion Board, Department of the Army, and Office of Naval Research, Department of the Navy. 4. Pierson, W.J., Jr. (1955). Wind-generated gravity waves. In: Advances in Geophysics. Vol. 2. Academic Press, New York, pp. 93–178. 5. Dean, R.G. and Dalrymple, R.A. (1984). Water Wave Mechanics for Engineers and Scientists. Prentice-Hall, Englewood Cliffs, NJ. 6. Sverdrup, H.U. and Munk, W.H. (1947). Wind, Sea and Swell: Theory of Relations for Forecasting. U. S. Navy Hydrographic Office Pub. No. 601. 7. Bretschneider, C.L. (1952). The generation and decay of wind waves in deep water. Trans. Am. Geophys. University 33(3): 381–389. 8. Komen, G.J., Cavaleri, L., Donelan, M., Hasselmann, K., Hasselmann, S., and Janssen, P.A.E.M. (1994). Dynamics and Modeling of Ocean Waves. Cambridge University Press. 9. Bretschneider, C.L. and Tamaye, E.E. (1976). Hurricane wind and wave forecasting techniques. Proc. 15th Int. Coastal Eng. Conf., Honolulu, HI, pp. 202–237. 10. Young, I.R. (1988). Parametric hurricane wave prediction model. J. Waterway Port Coastal Ocean Eng. 114(5): 637–652. 11. Liang, N.K. (2003). The typhoon swell Doppler effect. Ocean Eng. 30: 1107–1115.

WOODS HOLE: THE EARLY YEARS Northeast Fisheries Science Center—NOAA

The beginning of Woods Hole dates back to the early 17th century. Five years before the settlement of Jamestown, This article is a US Government work and, as such, is in the public domain in the United States of America.

140

WOODS HOLE: THE EARLY YEARS

Virginia, and 18 years before the Pilgrims landed at Provincetown and Plymouth, Bartholomew Gosnold coasted along Cape Cod and Marthas Vineyard, and about May 31, 1602, he is believed to have landed at what is now known as Woods Hole. The Town of Falmouth, of which Woods Hole is presently a part, was first settled in 1659–61 when several persons were granted permission to purchase land. The date of the settlement of Woods Hole took place 17 years later. The town (Falmouth) was incorporated on June 4, 1686, and called Succonessett, the name which later, probably in 1694, was changed to Falmouth. On July 23, 1677, the land around Little Harbor of Woods Hole was divided among the 13 settlers in ‘‘lots of 60 acres upland to a share’’ and an ‘‘Indian deed’’ confirming the land title was signed by Job Notantico on July 15, 1679. Fishing, hunting, and sheep breeding were the principal occupations of the early settlers and their descendents. Later on a grist mill was built and salt was made by solar evaporation of sea water in pans built along the banks of Little Harbor. These quiet, rural conditions, devoid of adventure, persisted until about 1815, when Woods Hole became an important whaling station from which ships operated on the high seas. The whaling industry in the United States became a very profitable business, and Woods Hole was a part of it. In 1854, the total receipts for the American whaling fleet amounted to $10.8 million, the largest part of this amount resulted from whaling carried out by Massachus tts captains. Woods Hole participated in these activities and prospered. It is known that between 1815 and 1860, not less than nine whaling ships were making port at the Bar Neck wharf, which was located where the U.S. Navy building of the Woods Hole Oceanographic Institution now stands. The place was busy processing oil and whalebone and outfitting ships. A bake house for making sea biscuits for long voyages stood next to the present ‘‘Old Stone Building’’ built in 1829 as a candle factory. This conspicuous old landmark on Water Street of Woods Hole, identified by an appropriate bronze plaque, now serves as a warehouse for the Marine Biological Laboratory for storing preserved zoological specimens. About 1860, whaling became less profitable and Woods Hole entered into the second phase of its economic life which was dominated by the establishment and operation of a new commercial venture known as the Pacific Guano Works. During the years from 1863 to 1889, when the Pacific Guano Works was in operation the life of Woods Hole centered around the plant which was built at Long Neck near the entrance to what is known now as Penzance Point. Many large sailing vessels carrying sulphur from Italy, nitrate of soda from Chile, potash from Germany, and many schooners under the American flag loaded with guano and phosphorus from the Pacific Coast of South America were anchored in Great Harbor waiting for their turn to unload their cargoes. The number of laborers regularly employed by the Guano Company varied from 150 to 200 men, mostly Irishmen brought in under contract. Several local fishermen found additional employment as pilots for guano ships. The company maintained a store where various goods such as leather,

lead pipe, tin, coal, wood, and other items were bought and sold. The store acted also as a labor housing agency. Through efforts of the business manager of the Guano Company, the Old Colony Railroad was persuaded to extend its branch from Monument Beach to Woods Hoie. The establishment of well-organized and reliable transportation to Boston was an important factor in the future life of the community. The Pacific Guano Works was established by the shipping merchants of Boston who were seeking cargo for the return voyage of their ships. The guano deposits of one of the Pacific islands seemed to furnish this opportunity. As soon as the joint stock company was organized in 1859 with the capital of $1 million, arrangements were made almost immediately by which the newly formed concern came into possession and control of Howland Island. This island is located in the middle of the Pacific Ocean at longitude 177 deg. W., a short distance north of the Equator, about 1, 500 miles true south from Midway Island of the Hawaiian archipelago. At the same time appropriate plant and docking facilities were built at Woods Hole and 33 large sailing ships became available for hauling guano. Unlike the well-known guano islands off the coast of Peru, Howland Island is located in the zone of abundant rainfall. Consequently, the guano deposits of the island were leached of organic components and consisted of highly concentrated phosphate of lime. Fertilizer produced by the company was made by restoring the lost organic matter of the phosphate rock

1887 Map of Woods Holl (Fisheries is bottom left)

WOODS HOLE: THE EARLY YEARS

by adding the right proportion of organic constituents which were obtained from menhaden, pogy, and other industrial fish which abound in Cape Cod waters. The rock was pulverized and purified by washing; fish brought in by local fishermen were first pressed to extract oil, and the residue digested with sulphuric acid, washed, and dried. Acid was produced locally from sulphur imported from Sicily, and the digestion of fish flesh was carried out in large lead-lined vats. The plant was well equipped with machinery needed for the process and even had a chemical laboratory where chemists made the necessary analyses. Various sheds for storage and drying, barracks for laborers, and a business office completed the facilities. When the deposits of phosphate rock on Howland Island were exhausted, the company acquired title to the Greater and Lesser Swan Islands from the U.S. Government. These islands are located in the Caribbean Sea at latitude 17 deg. N. and longitude 83 deg. W. off the coast of Honduras. The islands are only 400 miles from Key West, Florida, and 500 miles from New Orleans. They contained good-quality phosphate rock and being much closer to Woods Hole greatly reduced the voyage time and cost of delivery. Further expansion of the company consisted in the acquisition of Chisolm’s Island near the coast of South Carolina, construction of a plant for cracking and washing phosphate rock on the Ball River side of the island, and establishment of a processing plant in Charleston, S.C. From the initial production (in 1865) of 7, 540 sacks of fertilizer weighing 200 pounds each, the output reached 11, 420 tons in 1871 and continued to grow until the combined annual production in 1879 of the works at Woods Hole and Charleston reached from 40, 000 to 45, 000 tons of guano fertilizer. Spencer Baird, Secretary of the Smithsonian Instution and first commissioner of the U.S. Commission of Fish and Fisheries arrived in Woods Hole in 1871. Baird was greatly impressed by the idea of utilizing menhaden and other fishes for the production of guano fertilizer and considered it a worthwhile project. In a letter dated October 18, 1875, to John M. Glidden, treasurer of the Pacific Guano Works Company, Baird urged him ‘‘to make a display of your wares at the centennial (in Philadelphia),

141

as this is one of the most important interests in the United States.’’ He writes further that ‘‘there is no species (of fish) worked up elsewhere comparable to the movement with the menhaden, or pogy, as to numbers and the percentage of oil. The combination, too, of the pogy scrap with the South Carolina phosphates and the guanos of the West Indies and of the PacificA are also quite novel, and as being especially an American industry, are eminently worthy of full appreciation.’’ While the scientists, agriculturalists, and stockholders of the company thought very highly of the guano works, the existence of a malodorous plant was not appreciated by the residents of Woods Hole who suffered from a strongly offensive odor whenever the wind was from the west. Woods Hole might have continued to grow as one of the factory towns of Massachusetts but, fortunately for the progress of science and good fortune of its residents (except those who invested their savings in the shares of Pacific Guano Works), the company began to decline and became bankrupt in 1889. Cessation of business and heavy monetary losses brought financial disaster to many residents of Woods Hole. The gloom prevailing in the village after the closing of the guano works began to dissipate, however, with the development of Woods Hole as a place of scientific research and with the increasing tourist trade. The factory buildings were torn down, the chimney which dominated the Woods Hole landscape was dynamited, and over 100,000 pounds of lead lining the acid chambers were salvaged. Large cement vats and the remnants of the old wharf remained; in the following years the latter became a favored place for summer biologists to collect interesting marine animals and plants. The years from 1871 to the death of Baird in 1887 were the formative period of the new era of Woods Hole as a scientific center. In historical documents and in old books the present name Woods Hole is spelled in a different way. The old name ‘‘Woods Holl’’ is considered by some historians of Cape Cod to be a relic of the times prior to the 17th century when the Norsemen visited the coast. The ‘‘Holl’’, supposed to be the Norse word for ‘‘hill’’, is found in the old records. The early settlers gave the name ‘‘Hole’’ to inlets or to passages between the islands, such as ‘‘Robinson’s Hole’’ between Naushon and Pasque Islands, or ‘‘Quick’s Hole’’ between Pasque and Nashawena Islands, and Woods’ Hole between the mainland and Nonamesset Island. In 1877 the Postmaster General ordered the restoration of the original spelling ‘‘Wood’s Holl’’, which remained in force until 1896 when the United States Post Office changed it back to Woods

142

WOODS HOLE: THE EARLY YEARS

Hole and eliminated the apostrophe in Wood’s. The change was regretted by the old timers and by C. O. Whitman who had given the specific name ‘‘hollensis’’ to some local animals he described. At the time of his arrival at Woods Hole in 1871, Baird was well known to the scientific circles of this country and abroad as a naturalist, student of classification and distribution of mammals and birds, and as a tireless collector of zoological specimens. He maintained voluminous correspondence with the scientists in the United States and Europe, and was Permanent Secretary of the recently organized American Association for the Advancement of Science. To the general public he was known as a contributor to a science column in the New York Herald and author of many popular magazine articles. His newly acquired responsibilities as Commissioner of Fisheries greatly added to his primary duties as Assistant Secretary of the Smithsonian Institution which was primarily responsible for the establishment of the National Museum in Washington. As a scientist, Baird belonged to the time of Louis Agassiz, Th. H. Huxley, and Charles Darwin. Like Agassiz he attended medical college but never completed his studies, although the degree of M. D. honoris causa was later conferred upon him by the Philadelphia Medical College. In the words of Charles F. Holder, ‘‘he was a typical American of the heroic type. A man of many parts, virtues, and intellectual graces, and of all the zoologists science has given the world.. . . he was most prolific in works of practical value to man and humanity.’’ Commissioner Baird attended many Congressional hearings and conferences with state officials and fishermen at which the probable causes of the decline of fisheries were discussed and various corrective measures suggested. From the lengthy and frequently heated discussions and evidence presented by the fishermen and other persons familiar with the fisheries problems, he became convinced that an alarmingly rapid decrease in the catches of fish had continued for the last 15 or 20 years. Such a decline was particularly noticeable in the case of scup, tautog, and sea bass in the waters of Vineyard Sound. It was logical, therefore, that the new Commissioner of Fisheries would select for his initial activities the New England

coastal area where the fishing industry was of greatest importance as a politico-economical factor. Woods Hole, however, was not a significant fishing center. In the ‘‘Fisheries and Fishlng Industry of the United States’’ prepared and edited by Goode (1884–87) for the 1880 Census, the fishing activity at Woods Hole is described in the following words: ‘‘Of the male inhabitants only seven are regularly engaged in fishing, the remainder being employed in the guano factory, in farming and other minor pursuits.. . . There is one ship carpenter in Wood’s Holl, but he finds employment in his legitimate business only at long intervals. Of sailmakers, riggers, caulkers, and other artisans there are none. Four men are employed by Mr. Spindel, during the height of the fishing season, in icing and boxing fish. The boat fishery is carried on by seven men from April until September, inclusive. Only three species of fish are usually taken, namely, scup, tautog, and sea bass. The total catch of each fisherman is about 15 barrels, or about 2400 pounds. In addition about 6,720 lobsters are annually taken.’’ Before selecting a location for permanent headquarters for the work on fishery management and conservation, Baird undertook extensive explorations of the fishing grounds off the entire New England Coast. Section 2 of the Joint Resolution Number 8 of Congress gave the Commissioner full authority to carry out the necessary research. In part it reads as follows ‘‘and further resolved, That it shall be the duty of the said Commissioner to prosecute investigations and inquiries on the subject, with the view of ascertaining whether any and what diminution in the number of the food-fishes of the coast and the lakes of the United States has taken place; and, if so, to what causes the same is due; and also, whether any and what protective, prohibitory, or precautionary measures should be adopted in the premises; and to report upon the same

WOODS HOLE: THE EARLY YEARS

to Congress.’’ Section 4 of the same Resolution contains an important clause which authorizes the Commissioner of Fisheries ‘‘to take or cause to be taken, at all times, in the waters of the seacoast of the United States, where the tide ebbs and flows, and also in the waters of the lakes, such fish or specimens thereof as many in his judgement, from time to time, be needful or proper for the conduct of his duties as aforesaid, any law, custom, or useage of any State to the contrary notwithstanding.’’ The significant words ‘‘where the tide ebbs and flows’’ were interpreted by Baird in a very broad scientific sense which extended the authority for his investigations to the offshore areas of the open ocean. Pounds and weirs were most frequently accused by the public as destructive methods of fishing responsible for the decline in the abundance of food fishes along the coast. Although Baird gave very serious consideration to the possible destructiveness of fixed nets, traps, pounds, pots, fish weirs, and other stationary apparatus, he was fully aware of the complexity of the factors which may cause the decline in fish populations. He discusses this difficult problem in a paper entitled ‘‘Report on the condition of the sea fisheries of the south coast of New England’’ and published as the first section of the voluminous First Report of the Commissioner of Fish and Fisheries for 1871. Of the causes which may have contributed to the decrease of summer shore fisheries of the south side of Massachusetts and Rhode Island, a fact which he considered as well established by the testimonies of competent persons, he lists the following: (1) decrease or disappearance of the food of commercial fishes; (2) migration of fishes to other localities; (3) epidemic diseases and ‘‘peculiar atmospheric agencies, such as heat, cold, etc.’’; (4) destruction by other fishes; (5) man’s activities resulting in the pollution of water, in overfishing, and the use of improper apparatus. The biologist of today will recognize in this statement Baird’s broad philosophical approach to the major problem of fishery biology. The outlined program combined oceanographical and meteorological investigations with the studies of biology, ecology, parasitology, and population dynamics of various fish species. Baird’s program of research is as comprehensive and valid today as it was 90 years ago. No time was lost in initiating this program. Woods Hole was selected as the base of the sea coast operations during the first summer and Vinal N. Edwards became the first permanent federal employee of the fisheries service. In spite of the insignificance of local fisheries, this locality offered a number of advantages which were recognized by Baird. Communication with Boston, New York, and Washington was good and promised to be better with the expected opening of the railroad branch in 1872. Being centrally located in relation to principal fishing grounds of New England and having good dock facilities and water of sufficient depth for sea going vessels, Woods Hole was a suitable base for visiting the offshore grounds. Furthermore, it was believed that the alleged decrease in food fishes was most clearly manifested in the region around Vineyard Sound. The small yacht Mazeppa of the New Bedford Custom House and the revenue-cutter

143

Moccasin attached to the custom-house at Newport, R.I., were placed at the disposal of Baird; and the LightHouse Board granted permission to occupy some vacant buildings and the wharf at the buoy-station on the west bank of Little Harbor. The Secretary of the Navy came to Baird’s assistance by placing at his command a small steam launch which belonged to the Boston Navy Yard and by giving many condemned powder tanks which could be used for the preservation of specimens. Nets, dredges, tanks, and other gear were provided by the Smithsonian Institution. Cooperation of the various governmental agencies was authorized by Congress which in Section 3 of the Resolution specified that ‘‘the heads of the Executive Departments be, and they are hereby directed to cause to be rendered all necessary and practicable aid to the said Commissioner in the prosecution of the investigations and inquiries aforesaid.’’ This provision of the law was of great value. It is apparent, however, that the success in obtaining cooperation authorized by law depended a great deal on the personal characteristics of Baird, his great ability of getting along with people, and his remarkable power of persuasion, These qualifications played the major role in his success in organizing the Commission’s work and also in obtaining the cooperation of scientists as well as that of fishermen and businessmen. The investigation during the first summer consisted primarily in collecting large numbers of fishes and studying their spawning, rate of growth, distribution, and food. In the course of this work nearly all the fish pounds and traps, some 30 in number, in the vicinity of Woods Hole, were visited and their location recorded. There was no difficulty in obtaining the owners’ permission to examine these installations and to collect the needed

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THE INTERNATIONAL MARITIME ORGANIZATION–LONDON CONVENTION ANNUAL OCEAN DUMPING REPORTS

specimens. Altogether 106 species of fish were secured, photographed, and preserved for the National Museum. Of this number 20 or more species had not previously been known from Massachusetts waters. Information gained in this manner was supplemented by the testimonies of various fishermen who presented their ideas either for or against the use of traps and pounds. Among them was Isaiah Spindel, who at the request of Baird, prepared a description of a pound net used at Woods Hole and explained its operation. In the following years Spindel became an influential member of the group of local citizens who supported Baird’s plan of establishing a permanent marine station at Woods Hole. The ship Moccasin under the command of J. G. Baker was engaged in taking samples of plankton animals, in determining the extent of beds of mussels, starfish, and other bottom invertebrates, and in making temperature observations. One of the principal collaborators in the studies conducted at Woods Hole in 1871 was A. E. Verrill of Yale University, a professor whom Baird appointed as his assistant and placed in charge of the investigations of marine invertebrates. Dredging for bottom animals during the first summer was carried out on a relatively small scale from a chartered sailing yacht Mollie and a smaller vessel used in the immediate vicinity of Woods Hole. Extensive collections were made by wading on tidal flats exposed at low water. Zoological work attracted considerable interest among the biologists of this country. Many of them stopped at Woods Hole for greater or lesser periods and were encouraged by Baird to use the facilities of the Fish Commission. The group included such well known men as L. Agassiz, A. Hyatt, W. G. Farlow, Theodore Gill, Gruyure Jeffries of England, and many others. The first year’s work extended until the early part of October. Before returning to Washington, Baird commissioned Vinal N. Edwards of Woods Hole to continue the investigation as far as possible. By the end of the first year a general plan of study of the natural histories of the fishes and the effect of fishing on fish populations was prepared with the assistance of the well-known ichthyologist, Theodore N. Gill. His old ‘‘Catalogue of the fishes of the Eastern Coast of North America from Greenland to Georgia’’, was revised and the next text including the recently collected data concerning the Massachusetts fishes, appeared in the First Report of the U.S. Commissioner of Fish and Fisheries. The plan of investigation suggested by Gill was adopted by Baird as a guide for the work of his associates for the purpose of ‘‘securing greater precision in the inquiries.’’ The plan is composed of 15 sections, such as Geographical distribution, Abundiance, Reproduction, etc., with detailed subdivisions under each one. A questionnaire containing 88 different items was included in order to facilitate the inquiries conducted among the fishermen. The scope of the highly comprehensive program is complete enough to be useful today; marine biologists of today would probably only rephrase it, using modern terminology. During the first year of operations conducted at Woods Hole, Baird and his associates laid down the foundation of the new branch of science which we now call fishery biology or fishery science.

AN ANALYSIS OF THE INTERNATIONAL MARITIME ORGANIZATION–LONDON CONVENTION ANNUAL OCEAN DUMPING REPORTS CHRISTINE DICKENSON IVER W. DUEDALL Florida Institute of Technology Melbourne, Florida

Trends are analyzed for types and quantities of permitted wastes, primarily dredged material, sewage sludge, and industrial waste, to be dumped at sea by member countries to the London Convention (LC) from 1992 and 1995 through 1998. In 1972, the Inter-Governmental Conference on the Dumping of Wastes at Sea led to the creation of the London Dumping Convention (now called the London Convention) to help regulate the dumping of wastes at sea. The act of dumping, as defined by the LC, is international disposal at sea of any material and in any form, from vessels, aircraft, platforms, or other artificial structures. The first consultative meeting of the LC contracting parties was held in 1976 by the InterGovernmental Maritime Consultative Organization [now called the International Maritime Organization (IMO)]. During this meeting, the procedure for the reporting of permits issued, on an annual basis, for dumping at sea by contracting parties, was determined. The IMOLC annual reports on permitted wastes list the number of permits issued by member countries, the types and quantities of wastes permitted for dumping at sea, and the location and designation of dump sites. Now with nearly 25 years of dumping records available, we are able to see trends in permitted dumping activity. In 1976, the first year of permitted dumping records, the combined amount of permitted wastes was nearly 150 million tons. In the last four years (1995 through 1998), where data are available, the total amount of wastes permitted to be dumped by the LC contracting parties as between 300 and 350 million tons. Currently, a majority of these wastes are being disposed of in the East Asian Seas and the North Sea and the largest quantity of waste being dumped is dredged material. Although the disposal of wastes at sea is considered to be a major issue, it is only responsible for about 10% of the total anthropogenic contaminants entering the ocean. Unfortunately, the longterm impacts of this dumping in the ocean are still largely unknown. INTRODUCTION ‘‘Historically, most coastal countries used the sea for waste disposal. It was generally the most economic way to manage waste, since land usually had, and still has, a high price tag while the sea has no private owner in the normal sense. In addition, dilution processes served the illusion that dumping at sea does not cause any permanent damage. So why risk contaminating land or drinking water with wastes if the sea was close by?’’ (1). ‘‘Accurate

THE INTERNATIONAL MARITIME ORGANIZATION–LONDON CONVENTION ANNUAL OCEAN DUMPING REPORTS

worldwide records on the amounts of wastes disposed at sea prior to 1976 are virtually impossible to obtain’’ (1). However, as a result of the international activities leading to the creation of the London Dumping Convention (LC) in 1972, information is now available on the number of permits issued by many countries for disposal at sea, their dumpsite locations, and the kinds and quantities of wastes that have been dumped (1). According to the LC, the most common form of ocean dumping today is disposal from ships or barges (1,2). Wastes are loaded on these vessels and then taken to the dumpsites. Dumpsites are chosen based on the kind of waste and the ocean’s properties at each site (2). Liquid wastes are generally disposed of in more dispersive environments, where mixing will rapidly dilute the dumped material. Solid wastes, on the other hand, are usually disposed of in less dispersive near-shore sites to keep the solids confined. Here we specifically analyze trends in types and quantities of permitted wastes to be dumped at sea by member countries to the LC from 1992 and 1995 through 1998. The types of wastes that have been dumped in the ocean include industrial waste, sewage sludge, dredged material, incineration at sea, and radioactive wastes. Industrial waste may include both liquid and solid wastes and it may contain such items as acid-iron waste, fishprocessing liquids, metal refinery wastes, and gas pipeline flushing wastes (2). An overall reduction in the dumping of these types of wastes has been achieved over the years by switching to alternative disposal methods, reusing wastes, and creating cleaner production technologies. The dumping of industrial wastes at sea has been prohibited since 1996 (3). ‘‘Sewage sludge is an anaerobic waste product from treatment of municipal wastewater. The sludge is in aqueous form containing about 3% suspended particles by weight’’ (2). Alternatives for the disposal of sewage sludge at sea include incineration, deposit on land, and agriculture use (3). ‘‘Dredged materials range from clean sands to heavily contaminated fine grained materials’’ (2). ‘‘Physical properties of dredged materials, including grain size, bulk density, water content, and geotechnical characteristics, are especially variable due to the kind or type of sediment being dredged, which is itself dependent on geological and watershed characteristics, as well as to the operational procedures used in dredging and disposal’’ (2). Incineration at sea is defined as the burning of liquid chlorinated hydrocarbons as well as other halogenated compounds in which all ash is dumped into the sea (3). This type of dumping was phased out early in 1991. The dumping of radioactive wastes, however, might be the most harmful practice of all. Although the dumping of high level radioactive wastes has never been allowed under the London Convention, it has still occurred in some cases, and even though a moratorium was placed on the dumping of low level radioactive wastes in 1983, this type of dumping still occurred (3,4). It was not until 1994 that this act became legally binding. Finally, the other waste category includes such wastes as inert geological materials, decommissioned vessels, scrap metals, and fish wastes (3).

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METHODS Annual reports on permitted dumping at sea by contracting parties were obtained from the IMO-LC (5). There is approximately a three-year delay before the most recent year’s records are put into report format and published. Older records that only existed in hard copy form had to be entered into Excel spreadsheets to create a new database. Early on, it was decided that all wastes would be reported in tons to make comparisons from year to year easier. Many of the older reports had wastes recorded in cubic meters. These records were converted into tons by multiplying the cubic meters by the density of the waste (1.3 g/cm3 for dredged material and other varying factors as indicated by each permit). Newer records, however, were received in Excel format and, for the most part, they were already converted into tons, making them very easy to add to the database. The primary categories of wastes of importance to this study include dredged material, sewage sludge, industrial waste, and other matter. From the 1992 and 1995 through 1998 reports (5), it was desired to find out which waste was being dumped in the largest quantity, as well as which countries were dumping the most wastes and which water bodies were receiving the most wastes. The more recent data is compared to earlier reports from 1976 to 1985. Comparisons of the different sources of pollutants in the oceans and comparisons between land dumping and sea dumping are also made. Then the past, as well as the future, of ocean dumping can be assessed. RESULTS Tables in the IMO-LC annual reports (5) on permitted wastes (IMO, 1992, 1995–1998) list the number of permits issued to member countries, the types and quantities of wastes permitted for disposal at sea, and the location and designation of dumping sites. It is important to know that these reports are reflective of what has been permitted to be dumped and not of what has actually been dumped. The accuracy of these records, therefore, is somewhat questionable (1). It is also important to remember that not all of the contracting parties report their activities every year and some reports from contracting parties may be incomplete (2). For example, in 1995, thirty-eight of the seventy-five contracting parties registered did not report their activities. There is also no way of knowing how much noncontracting parties are dumping (2). In 1992, 473 million tons were reported as permitted for disposal at sea. In the last four years (1995 through 1998) where data are available, the total amount of wastes permitted to be dumped by the LC contracting parties was 351 million tons in 1995, 312 million tons in 1996, 309 million tons in 1997, and 348 million tons in 1998. Figure 1 illustrates these data. As seen in Fig. 2, a majority of these wastes are being disposed of in the East Asian Seas (Fig. 3) and the North Sea (Fig. 4). The ‘‘other areas’’ category is represented mostly by the United States and its disposal in the Gulf of Mexico (Fig. 5).

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THE INTERNATIONAL MARITIME ORGANIZATION–LONDON CONVENTION ANNUAL OCEAN DUMPING REPORTS Total tons permitted for disposal at sea per year

500,000,000 400,000,000 300,000,000 200,000,000 100,000,000 0

Year 1992

1995

1996

1997

1998

Figure 1. London Convention permitted dumping from 1992 and 1995 through 1998.

The countries responsible for dumping the most wastes, in descending order, are China, the United States, Hong Kong, the United Kingdom, Germany, and Belgium (Table 1). As shown in Fig. 6, the largest quantity of waste being dumped is dredged material. At 327 million tons in 1998, it is the largest quantity by far, with sewage sludge coming in as the next highest quantity with only 15 million tons. DISCUSSION In 1976, the first year of permitted dumping records, the combined amount of permitted wastes was nearly 150 million tons (1). By 1985, this amount had grown to approximately 300 million tons (1). This apparent doubling, however, partly corresponds to an increase in the number of contracting parties to the LC. It is also important to remember that not all of the contracting parties report their activities every year and some reports from contracting parties may be incomplete. Therefore, it is not possible to provide a highly accurate interpretation of these data and the reader should be cautioned that any analysis must be considered approximate.

Figure 3. China and Hong Kong dumping in the East Asian Seas. (From Ref. 6).

Looking back to the data in Fig. 1, waste disposal in the ocean seems to continue to increase into the early 1990s with 473 million tons in 1992. However, by 1995 through 1998 this amount had leveled off to between 300 and 350 million tons. This decrease could be representative of the many changes in policy occurring within the LC in the 1990s to intentionally decrease the amount of waste disposed of in the ocean (3). It is also known that a major dredging project took place in Hong Kong in the early 1990s in order to expand the airport there (3). This may explain why the amount of waste dumped in 1992 was so high. The East Asian Seas section of Fig. 2 supports this theory, with data from 1992 being much higher than in the following years. Yearly fluctuations like this occur due to the variation in maintenance dredging and new works associated with shipping activities (3). According to the IMO-LC web page, ‘‘in early 1991, incineration at sea operations came to a halt, ahead of

Permitted quantities (in tons) per location 250,000,000 200,000,000 North, central, & south america

East asia & australasia

North east atlantic & adjacent waters 150,000,000 100,000,000 50,000,000 0 Atlantic ocean

North English sea channel

Irish sea

Other areas

1992

South west pacific 1995

East asian seas 1996

Indian ocean

1997

Other NW NE areas Atlantic Pacific ocean ocean 1998

Figure 2. Locations of dumping sites with their respective amounts of wastes dumped.

Arctic seas

Other areas

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Table 1. Highest Combined Tons for 1992 and 1995–1998

Figure 4. The United Kingdom, Germany, and Belgium dumping in the North Sea. (From Ref. 6).

the agreed global deadline of December 31, 1992. . .. In 1990, contracting parties to the LC agreed to phase-out sea disposal of industrial waste effective by January 1, 1996. . .. In 1993, contracting parties started a detailed

Rank

Country

Tons

1 2 3 4 5 6

China United States Hong Kong United Kingdom Germany Belgium

295,482,060 293,272,190 285,437,056 246,759,318 132,149,000 127,507,436

review of the LC, leading to the adoption of a few crucial amendments. . .. These amendments consolidated in a legally binding manner the prohibition to dump all radioactive wastes or other radioactive matter and of industrial wastes, the latter as per January 1, 1996, as well as the prohibition of incineration at sea of industrial wastes and of sewage sludge’’ (3). According to reports by contracting parties, no permits for the dumping of industrial waste have been issued since 1996. Before this phase-out, Japan and the Republic of Korea were responsible for most of the industrial waste being dumped (3). The amount of sewage sludge being dumped at sea decreased in the early 1990s, reflecting the phase-out of this practice by several countries, Ireland and the United Kingdom being the most recent. Currently, only Japan, the Philippines, and the Republic of Korea dispose of sewage sludge at sea (3).

Figure 5. The United States dumping in the Gulf of Mexico and the northwest Atlantic. (From Ref. 6).

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Waste category comparisons

500,000,000 450,000,000 400,000,000 350,000,000 300,000,000 250,000,000 200,000,000 150,000,000 100,000,000 50,000,000 0 1992

1995

1996

Figure 6. Dredged material, by far, makes up the largest quantity of waste being dumped at sea.

Dredged material makes up the majority of what is being dumped at sea (see Fig. 6). Unlike other wastes, the amount of dredged material dumped each year tends to fluctuate greatly due to variable maintenance dredging and new works associated with shipping activities (3). For example, there were huge dredging efforts going on in Hong Kong with the extension of the airport there in 1992. One hundred forty-four million tons of dredged material were permitted to be disposed of at sea that year by Hong Kong. Arguably, this could be responsible for the 1994 anomaly of the combined total of 473 million tons, meaning that the average amount of wastes dumped annually actually leveled out to between 300 and 350 million tons much earlier than the later 1990s. The interactions of the wastes dumped at sea with seawater and the toxicity of these wastes to organisms, including humans, are of great importance to the scientific community. Although the long-term effects of disposal at sea are unknown, many studies have looked at some of the short-term effects, particularly in relation to radioactive wastes that have been dumped. Studies conducted in the Arctic by the IAEA and the U.S. Congress Office of Technology Assessment found that (1) releases from dumped objects were small and confined to the immediate vicinity of the dumped objects, (2) projected future doses to the general public were small, (3) doses to marine organisms were insignificant in the context of populations, and (4) remediation on radiological grounds was not warranted (7). A study by Hill et al. (8) assesses the possible effects of 40 years of dredging, and how it might have affected benthos in the Irish Sea. Zooplankton and micronekton communities, off eastern Tasmania, as studied by Bradford et al. (9), were found to be affected by the presence of a warm-core eddy instead of jarosite wastes dumped within the vicinity. As de La Fayette (7) said, it is difficult to draw conclusions from data that has been collected because more research, monitoring, and prevention projects are still needed for us to understand all of the factors that are involved in knowing how, when, and where ocean stored wastes might affect us and the environment.

Dredged material Sewage sludge Other matter Industrial waste 1997

1998

Year

Although such concern is felt about disposal at sea, it is not the largest contributor of pollutants to the oceans. As seen in Fig. 7, the IMO-LC puts it in fourth place, making up only 10% of the total pollutants in the oceans. Runoff and land-based discharges are the largest source, making up 44%. Even maritime transportation, at an estimated 12%, pollutes the oceans more than dumping does. In an attempt to compare ocean dumping to disposal in landfills, we look at the United States. According to Zero Waste America (10), in 2001, 409 million tons of municipal waste were generated in the United States. Of that, 278 million tons were disposed of in landfills. Table 2 illustrates dumping on land and in the ocean by the United States during 1992 and 1995 through 1998. Those five years of ocean dumping, totaling 293 million tons, is only 15 million tons more than what was disposed of in landfills in 2001 alone. In conclusion, we note that much more waste is being disposed of in landfills than in the ocean. Therefore, shouldn’t we be more concerned about the land? CONCLUSION Although the environmental impacts of dumping at sea are still largely unknown, it is comforting that the LC is moving in a positive direction toward more regulations for the better protection of our oceans. With industrial

Dumping in relation to other sources of pollutants in the oceans 10% 1% Run-off and land-based discharges

12% 44%

Land-based discharges through the atmosphere Maritime transportation Dumping Offshore productions

33%

Figure 7. At 10%, dumping ranks fourth compared to the other sources of pollutants in the ocean.

MARINE SOURCES OF HALOCARBONS Table 2. Ocean Dumping versus Land Dumping in the United States Tons in Millions Year

Land

Ocean

1992 1995 1996 1997 1998

241 249 238 236 238

67 58 46 53 69

Data taken from Reference 10.

waste already phased out and sewage sludge on its way to becoming completely phased out, that leaves dredged material and ‘‘other matter’’ as the future of ocean dumping. Other matter mostly makes up inert geological material from mining and excavations; bulky wastes such as steel equipment, scrap metal, and concrete; fish wastes; obsolete ammunition and explosives; discontinued oil platforms; spoiled food; and other random wastes. This category may also eventually be phased out, but dredged material will most likely continue to be dumped since this form of waste, in the normal sense, either came ‘‘from the ocean floor’’ or somewhere close to it being that twothirds of dredged material is connected with maintenance operations to keep harbors, rivers, and other waterways from being blocked up. Unfortunately, according to the IMO-LC, about 10% of dredged material is moderately to heavily contaminated from a variety of sources including shipping, industrial and municipal discharges, and land runoff. Whether we find somewhere to dispose of dredged material on land, or we continue to dispose of it in the sea, it will continue to affect our environment. Acknowledgments We are grateful to Rene Coenen, Office of the London Convention, International Maritime Organization, for kindly providing the LC dumping records. We are also thankful to Ruth Caulk and Melissa Sheffer for assisting in the preparation of the ocean dumping spreadsheets.

BIBLIOGRAPHY 1. Duedall, I.W. (1990). A brief history of ocean disposal. Oceanus 33(2): 29. 2. Connell, D.W. and Hawker, D.W. (1992). Pollution in Tropical Aquatic Systems. CRC Press, Boca Raton, FL. 3. London Convention. (2003). Available: http://www.londonconvention.org. 4. Ahnert, A. and Borowski, C. (2000). Environmental risk assessment of anthropogenic activity in the deep sea. J. Aquat. Ecosys. Stress Recov. 7: 299–315. 5. IMO. (1972). Convention on the Prevention of Marine Pollution by Dumping of Wastes and Other Matter, London Convention 1972. Final Reports on Permits Issued in 1992, 1995, 1996, 1997, and 1998. 6. Karls, F. (1999). World History: The Human Experience—The Modern Era. Glencoe/McGraw-Hill, New York. 7. de La Fayette, L. (1998). The London Convention 1972: preparing for the future. Int. J. Mar. Coastal Law 13(4): 515–536.

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8. Hill, A.S. et al. (1999). Changes in Irish Sea benthos: possible effects of 40 years of dredging. Estuarine Coastal Shelf Sci. 48: 739–750. 9. Bradford, X. et al. (1999). 10. Zero Waste America. (2001). Available: http://www.zerowasteamerica.org/Statistics.htm.

MARINE SOURCES OF HALOCARBONS ROBERT M. MOORE Dalhousie University Halifax, Nova Scotia, Canada

Halogenated gases are important in the atmosphere by virtue of their ability to carry chlorine, bromine, and iodine to high altitude, where they can act as efficient catalysts of ozone destruction. The effect on ozone of chlorine release in the stratosphere by certain manufactured chlorofluorocarbons is well known, but naturally occurring halogen carriers account for a part of the background cycle of ozone breakdown. The oceans constitute an enormous reservoir of dissolved halogens in the form of halide ions, but the transport of this material to the upper atmosphere is inefficient because sea salt particles, introduced to the atmosphere as sea spray from breaking waves and bubblebursting, have short lifetimes, being readily washed out by rain. For this reason the relatively minute concentrations of dissolved halogenated gases, such as methyl chloride occurring in surface seawater at concentrations around 10−10 M, have the potential to drive significant transport of chlorine into the upper atmosphere. Since the role of anthropogenic chlorine and bromine gases in stratospheric ozone depletion was recognized, there has been renewed interest in the ocean as a source of halogenated trace gases. The emission of iodine compounds from the ocean has more recently been shown to be potentially important in aerosol production as well as in affecting ozone concentrations over the ocean (1). The fluxes of trace gases such as those between the ocean and atmosphere is most commonly calculated from concentration measurements in the surface ocean and the overlying atmosphere together with empirical relationships between gas exchange coefficients and wind velocity (2). Supersaturation of a gas at the sea surface with respect to the atmosphere will support an outward flux, the magnitude of which is strongly dependent on wind speed, and to a lesser extent on temperature. Gas fluxes can be highly variable spatially and seasonally, and, in general, estimated global fluxes will have a substantial degree of uncertainty due to the sparseness of the concentration measurements combined with a large uncertainty in the exchange velocity. Ideally, gas fluxes would be calculable based on a firm understanding of the processes governing both the production and loss of the gas in the upper ocean and the processes controlling gas exchange. This remains a distant goal, and current studies are directed at developing an understanding of these processes. Some of the first measurements made of halogenated methanes in seawater suggested that the ocean could be

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MARINE SOURCES OF HALOCARBONS

the predominant source of methyl chloride accounting for most of the 4 million tonnes that must be added annually to the atmosphere to support the observed concentrations (3). More recently, it has been demonstrated that, in the case of methyl chloride, the ocean is just one of many sources (including biomass burning, woodrot fungi, and vegetation) and can probably account for only about 15% of the total flux to the atmosphere (4). In contrast, the ocean is still recognized to be the most important source of atmospheric methyl iodide. Impetus for the study of sources of methyl bromide came with the discovery of the efficiency with which bromine could catalyze stratospheric ozone loss, working either directly or in concert with chlorine. This led to concern about the possible role of methyl bromide, manufactured for use as a fumigant, in observed ozone loss. The existence of natural sources and sinks for methyl bromide made it more difficult to quantify the deleterious effect of the anthropogenic component. Extensive studies of the distribution of methyl bromide in the oceans and of its flux across the air–sea interface in different regions demonstrated the existence of both production and loss processes within the ocean (5). The balance between these determines whether a particular region will emit CH3 Br to the atmosphere or take it up. A major oceanic sink results from the reaction between CH3 Br and chloride ion, the rate being strongly dependent on temperature. Other losses include chemical hydrolysis and also biological uptake. Bromine is carried to the atmosphere by many other gases produced in the ocean, notably bromoform and dibromomethane (6). Early studies pointed to an association between certain halogenated compounds in seawater, such as methyl iodide, and coastal beds of macrophytes. The more general phenomenon of organohalogen production by seaweeds has long been known, and a wide range of halogenated organic compounds of varying molecular weight and complexity have been identified (7). The focus here is on halogenated compounds that play a role in atmospheric chemistry, so these are typically volatile compounds. Two such compounds that have been shown to have major sources in macrophytes are di- and tribromomethane (CH2 Br2 and CHBr3 ). The latter has been found to occur within certain seaweeds at concentrations up to the percent level. It is apparent that haloperoxidase enzymes are involved in the biosynthesis of organohalogens by macrophytes. In spite of the variety and abundance of halogenated methanes in seaweeds and the flux of halogen to the atmosphere that can thus be supported in the coastal zone, the overall importance of these algae on an oceanwide scale is small on account of their limited distribution (8), although, in the case of bromoform and dibromomethane, Carpenter and Liss, (9) estimated that macrophytes are a major source. For this reason there has been interest in the possible production of the same compounds by marine microalgae, which are ubiquitous in the sunlit waters of the world’s oceans. An approach that has been adopted with some success to study this question has been the use of laboratory cultures of specific algae. This has demonstrated the capacity of a range of phytoplankton of

different algal classes to produce compounds such as CH3 I, CH2 Br2 , CHBr3 , and CH2 I2 (10,11), although species vary in the spectrum of compounds that they produce as well as in the production rates. There has been some progress in elucidating the production mechanism of these compounds with the identification of haloperoxidase enzymes in a few phytoplankton species (11). However, much uncertainty remains regarding the oceanic source of methyl chloride, bromide, and iodide. For although there are published studies that point to the capacity of some phytoplankton to produce methyl halides (12), the measured rates when normalized to biomass concentrations have typically been found to be quite inadequate to account for the observed fluxes from the ocean into the atmosphere (10). This may be due in part to the limitations of laboratory studies of phytoplankton cultures: relatively few species can be grown successfully in the laboratory and the conditions are very dissimilar to those in the ocean itself. Alternative possible explanations include the involvement of microbial processes (13), zooplankton, and photochemistry, or a combination of sources. One laboratory study has provided some evidence for the production of methyl iodide in seawater irradiated with simulated sunlight (14), but it has yet to be demonstrated that this process is significant in the ocean. Open ocean studies of halocarbon distributions show that there is no simple correlation with phytoplankton biomass, quantified as chlorophyll a concentration. This means that the production of a particular compound cannot be attributed uniformly to all species of phytoplankton. More success has been obtained in studies that measured a series of photosynthetic pigments and evidence is forthcoming from one such study that CH3 Br has a source in Prymnesiophytes (15). Measurements of dissolved methyl halides in the ocean typically show relatively high concentrations in the surface mixed layer, frequently with a maximum directly beneath, declining to levels at or near detection limits in deep waters (16). Such profiles are broadly consistent with a source at or near the surface and net consumption at greater depths. The maximum may be explained as occurring in a zone of production beneath the surface mixed layer that is poorly ventilated, so with reduced emission to the atmosphere. However, certain halocarbons have quite different distributions with depth. The chlorofluorocarbons such as CFC11 and CFC12 may have higher concentrations below the surface and at intermediate depths, with levels diminishing to low values in some of the deepest waters of the ocean. These distributions are well understood to be the result of transport of these anthropogenic gases from the atmosphere either by direct exchange at the surface or via downward mixing and advection of cold, dense, ventilated waters to intermediate and abyssal depths. There is now evidence that some halocarbons that have relatively short atmospheric lifetimes (e.g., dichloromethane and tri- and tetrachloroethylene) are also introduced to the ocean by the same processes, and that these gases have much longer lifetimes in the ocean than in the atmosphere. This apparently explains the presence of dichloromethane in the near bottom waters of the Labrador Sea (17).

FOOD CHAIN/FOODWEB/FOOD CYCLE

Chloroform is likely to undergo the same processes but may have an additional in situ source. Loss processes occurring in the ocean can be inferred for most organohalogens by their lower concentrations at depth than at the surface. They have been studied most thoroughly for methyl bromide and, for this compound, are known to include bacterial removal and chemical loss through hydrolysis and reaction with chloride ion (18). Other loss processes affecting a range of halogenated compounds apparently exist in waters that are depleted in dissolved oxygen (19). It should be noted a loss process for one halocarbon might represent a source for another: thus, reaction of both CH3 Br and CH3 I with chloride ion yields CH3 Cl. The photocatalyzed loss of CH2 I2 is a source of CH2 ICl. Continued measurement of halocarbons both in the ocean and atmosphere will improve our knowledge of the magnitude, geographic distribution, and seasonality of their fluxes, but a greater challenge is likely to be identifying more accurately their sources. That knowledge is essential if we hope to be able to predict how the fluxes of these atmospherically reactive gases may change in the future. BIBLIOGRAPHY 1. O’Dowd, C.D. et al. (2002). Marine aerosol formation from biogenic iodine emissions. Nature 417: 632–636. 2. Wanninkhof, R. (1992). Relationship between wind speed and gas exchange over the ocean. J. Geophys. Res. 97: 7373–7382. 3. Harper, D.B. (2000). The global chloromethane cycle: biosynthesis, biodegradation and metabolic role. Nat. Prod. Rep. 17: 337–348. 4. Moore, R.M. (2000). The solubility of a suite of low molecular weight organochlorine compounds in seawater and implications for estimating the marine source of methyl chloride to the atmosphere. Chemosphere: Global Change Sci. 2: 95–99. 5. Lobert, J.M. et al. (1995). Science 267: 1002–1005. 6. Quack, B. and Wallace, D.W. (2003). Air–sea flux of bromoform: controls, rates, and implications. Global Biogeochem. Cycles 17(1): 1023–1029. 7. Gribble, G.W. (2003). The diversity of naturally produced organohalogens. In: The Handbook of Environmental Chemistry. Vol. 3, Part P, G.W. Gribble (Ed.). Springer, New York, pp. 1–15. 8. Baker, J.M. et al. (2001). Emissions of CH3 Br, organochlorines and organoiodines from temperate macroalgae. Chemosphere Global Change Sci. 3: 93–106. 9. Carpenter, L.J. and Liss, P.S. (2000). On temperate sources of bromoform and other reactive organic bromine gases. J. Geophys. Res. 105: 20,539–20,547. 10. Manley, S.L. and de la Cuesta, J. (1997). Methyl iodide production from marine phytoplankton cultures. Limnol. Oceanogr. 42: 142–147. 11. Moore, R.M., Webb, M., Tokarczyk, R., and Wever, R. (1996). Bromoperoxidase and iodoperoxidase enzymes and production of halogenated methanes in marine diatom cultures. J. Geophys. Res. 101: 20,899–20,908. 12. Scarratt, M.G. and Moore, R.M. (1996). Production of methyl chloride and methyl bromide in laboratory cultures of marine phytoplankton. Mar. Chem. 54: 263–272.

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13. Amachi, S., Kamagata, Y., Kanagawa, T., and Muramatsu, Y. (2001). Bacteria mediate methylation of iodine in marine and terrestrial environments. Appl. Environ. Microbiol. 67: 2718–1722. 14. Moore, R.M. and Zafiriou, O.C. (1994). Photochemical production of methyl iodide in seawater. J. Geophys. Res. 99: 16,415–16,420. 15. Baker, J.M. et al. (1999). Biological production of methyl bromide in the coastal waters of the North Sea and open ocean of the northeast Atlantic. Mar. Chem. 64: 267–285. 16. Moore, R.M. and Groszko, W. (1999). Methyl iodide distribution in the ocean and fluxes to the atmosphere. J. Geophys. Res. 104: 11,163–11,171. 17. Moore, R.M. (2004). Dichloromethane in N. Atlantic Ocean waters. J. Geophys. Res. 109: 9004. 18. King, D.B. and Saltzman, E.S. (1997). Removal of methyl bromide in coastal seawater: chemical and biological rates. J. Geophys. Res. 102: 18,715–18,721. ¨ (1996). Reduction ¨ 19. Tanhua, T., Fogelqvist, E., and Basturk, O. of volatile halocarbons in anoxic seawater, results from a study in the Black Sea. Mar. Chem. 54: 159–170.

FOOD CHAIN/FOODWEB/FOOD CYCLE ANDREW JUHL Lamont–Doherty Earth Observatory of Columbia University Palisades, New York

A representation of the feeding relationships of the organisms, or groups of organisms, within an ecological community will be shown here. By showing which organisms feed on which other organisms, the pathways of energy flow through the ecosystem can be followed. ‘‘Food chain’’ is an older term and is currently less used than ‘‘foodweb’’ or ‘‘food cycle.’’ The newer terms were coined to acknowledge the complexity of feeding relationships within most ecosystems. Examples of marine planktonic and intertidal foodwebs will be used below to illustrate specific points, but the concepts are applicable to any ecosystem. The simplest food chain is organized in a strict hierarchy with primary producers (organisms that generate organic matter by fixing inorganic carbon, usually through photosynthesis) eaten by herbivores (primary consumers), the herbivores eaten by carnivores (secondary consumers), on to tertiary consumers, quaternary consumers, and soon. Each level within the food chain is termed a trophic level. Figure 1 shows an example of a very simple food chain for a planktonic ecosystem where phytoplankton are the primary producers, eaten by zooplankton herbivores. Zooplankton, in turn, are eaten by fish. Each group of organisms is represented by a shape, and the feeding connection and direction of energy flow are shown with an arrow. Simple food chains have heuristic value and are the basis of many quantitative ecosystem models. However, they can be criticized for oversimplification and for missing major groups of organisms. One step toward a more realistic picture of an ecosystem is to disaggregate the trophic levels. Ideally, each level

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Fish

Herring adults Herring larvae

Zooplankton Ciliates

Calanus copepods

Small phytoplankton

Large phytoplankton

Phytoplankton Figure 1. A simple food chain for a planktonic ecosystem.

could be broken down into its constituent species. One problem to consider is whether rare species should be depicted. A food chain diagram could include any feeding relationship that occurs within a system, whether common or unusual. This could lead to so many boxes and connecting arrows that any heuristic value would be jeopardized. In addition, the required information to fully disaggregate species groups may not be available. For example, microorganisms can be difficult to distinguish to the species level. Practical considerations often lead researchers to lump microorganisms into size classes and functional groups (e.g., primary producers >2 µm, 2–20 µm, 99.8% of the mass of the total dissolved salts in the ocean, are known as the major ions and are defined as dissolved species having a concentration in seawater of >1 mg kg−1 (1 ppm) (Table 1). Na+ and Cl− alone account for 86% of all dissolved chemical species in seawater. The source of Cl− , and most anions in seawater, is outgassing of the Earth’s interior, or volcanic emissions. The majority of the major cations are derived from the effects of continental weathering and are delivered to the ocean via rivers. The gross composition of seawater is the result of the partitioning of elements between continental rock and seawater over geologic time. The major ions represent the more soluble elements, which have preferentially partitioned into seawater. The major ions are found to occur in nearly constant ratios to each other throughout most of the world’s oceans. That is, although the salinity or the total amount of salt dissolved in seawater varies from location to location in the ocean, the ratios of the major ions to each other remains nearly constant, which is true from ocean to ocean as well as from surface to deep waters (Table 2). Table 1. Major Ions in Seawater

Chloride, Cl− Sodium, Na+ Sulfate, SO4 2− Magnesium, Mg2+ Calcium, Ca2+ Potassium, K+ Bicarbonate, HCO3 2− Bromide, Br− Boron, B (as B(OH)3 Strontium, Sr2+ Fluoride, F−

Table 2. Ion to Chloride Ratios in Various Oceans and Selected Seas for Na+ and K+ Ocean or Depth Interval Atlantic Pacific Indian Red Sea Mediterranean 0–100 m 700–1500 m >1500 m MEAN

Na+ /Cl−

K+ /Cl−

0.5552 0.5555 0.5554 0.5563 0.5557 0.5554 0.5557 0.5555 0.5555+ /−0.0007

0.0206 0.0206 0.0207 0.0206 0.0206 0.0206 0.0206 0.0206 0.0206+ /−0.0002

Also shown are ion to chloride ratios for selected depth intervals in the world ocean. Mean values are for the world ocean over all depth intervals.

MARIE DE ANGELIS

Major Ion

159

g kg−1 Seawater at Salinity of 35.000 ppt

% by wt

g ion/g Cl−

19.353 10.781 2.712 1.284 0.4119 0.399 0.126 0.0673 0.0257 0.00794 0.00130

55.30 30.77 7.75 3.69 1.18 1.14 0.41 0.19 0.013 0.023 0.0037

1 0.5561 0.1400 0.0668 0.0213 0.0206 0.0075 0.0035 0.00024 0.00041 0.00006

Concentrations are presented in terms of g of ion per kg of seawater, % by weight in seawater, and the weight ratio g ion per g Cl− .

This observation is known as ‘‘The Rule of Constant Proportions’’ or conservative behavior. As Cl− is the single most abundant ionic species in seawater, the Rule of Constant Proportion is usually expressed as the ratio of major ions to chloride ion (e.g., Na+ /Cl− ). Exceptions to this rule exist for calcium (Ca2+ ), strontium (Sr2+ ), and bicarbonate (HCO3 2− ) as a small fraction of the total concentration of these species participate in biological reactions resulting in slight variations of ion/Cl− ratios between surface and deep water. The residence time (τ ) of a chemical species in the ocean can be defined as the average time an individual atom for a given element remains in seawater before being permanently removed. Assuming that the major source of dissolved salts to the ocean is from riverine input, residence time of a given ion can be calculated as the total mass (in g) of ion in the ocean (Mocean ) divided by the mass of ion delivered by rivers annually (Fluxin ) (in g yr−1 ). τ (years) =

Mocean Fluxin

Flux in can be estimated from the average concentration of the ion in the world’s rivers (in g L−1 ) multiplied by the total volume of river water entering the ocean annually (in L yr−1 ). Mocean can be estimated from mean seawater concentrations (in g L−1 ) multiplied by the volume of the ocean (in L). The residence times for the major ions calculated by this method are extremely large, on the order of millions to hundreds of millions of years (Table 3). The long residence times of major ions reflects the relatively low reactivity of these chemical species. Except Table 3. Mean Seawater and River Water Concentrations and Residence Times for Several Major Ions Species Cl− Na+ Mg2+ SO4 2− K+ Ca2+ Br−

Mean SW (mg L−1 )

Mean RW (mg L−1 )

19, 350 10, 760 1, 294 2, 712 399 412 67

5.75 5.25 3.35 8.25 1.3 13.4 0.02

SW RW 3, 365 2, 090 386 338 307 31 3, 350

τ (106 years) 123 75 14 12 11 1.1 123

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for Ca2+ , Sr2+ , and HCO3 2− , no biological processes exist that accelerate the removal of these species to the oceanic sediment. The main removal mechanisms for major ions are kinetically slow reactions such as precipitation or incorporation into clay minerals in the sediment or oceanic crust. Thus, major ions are conservative or remain in constant proportion to each other because the major ions have very long residence times relative to either the residence time of water in the ocean (40,000 years) or the oceanic circulation time (1000 years). Even if the salt content (salinity) of seawater changes from location to location in the ocean, the ratios of the major ions do not change because they react on much longer time scales than the removal or addition of water by precipitation or evaporation. As the residence time of major ions greatly exceeds the average oceanic circulation time of approximately 1000 years, no change is seen in major ion concentrations from ocean to ocean or between surface water and deep water The major ion composition of river water and seawater are different (Table 3). The composition of present-day river water reflects the weathering of continental rock, whose composition reflects the long-term partitioning of chemical species between the continents and seawater. The composition of seawater with respect to its major ion composition is not believed to have changed over the past several million years despite the constant input of river water of different composition. The oceans are believed to be at steady-state equilibrium with respect to the major ions. That is, the composition of seawater remains constant because the flux of major ions into the ocean equals the flux of major ions out of the ocean. Although the major source of major ions is river input, hydrothermal circulation of seawater through oceanic basalt, particularly at relatively low temperatures, may be a significant source of some major cations (Na+ , K+ ). To achieve steady-state equilibrium, the sum of the sinks or fluxes out of major ions must balance the input from rivers. Several processes, most occurring at extremely slow rates over large areas of the oceanic seafloor, have been identified as sinks for major ions. These processes include: (a) Cation exchange in which clay minerals within the oceanic sediment as well as clays delivered to the oceans by rivers exchange cations in seawater to form new clay minerals relatively enriched in Na, K, and Mg at the expense of Ca. (b) Trapping and eventual burial of seawater within interstitial water of marine sediments. This process removes the more concentrated ions in seawater (Na, Cl). (c) Evaporite formation during some periods of Earth’s history, in which large deposits of minerals derived from seawater have formed when seawater was trapped and evaporated from shallow, closed basins. Although the areal extent of such basins is limited at the present time, formation of evaporites is an important removal mechanism for some major ions, including Na, Cl, and SO4 2− , over geologic time. (d) Sea spray transported to land can result in net removal of Na and Cl. (e) Reverse weathering involving reactions between ions in seawater and cation-poor aluminosilicates derived from continental weathering. This process results in the formation of new cation-rich clay minerals and CO2 , resulting in the net

removal of Na, K, and Mg from seawater. (f) Hydrothermal circulation involving the reaction of major ions between seawater and oceanic basalt is a net sink for Mg2+ and SO4 2− . READING LIST Mackenzie, F.T. and Garrels, R.M. (1966). Chemical balance between rivers and oceans. Amer. J. Sci. 264: 507–525. Holland, H.D. (1984). The Chemical Evolution of the Atmosphere and Oceans. Princeton University Press, Princeton, NJ, p. 584. Pilson, M.E.Q. (1998). An Introduction to the Chemistry of the Sea. Prentice-Hall, Englewood Cliffs, NJ, p. 431.

TSUNAMI Tsunami (also called Seismic Sea Wave, and popularly, Tidal Wave), an ocean wave produced by a submarine earthquake, landslide, or volcanic eruption. These waves may reach enormous dimensions and have sufficient energy to travel across entire oceans. From the area of the disturbance, the waves will travel outward in all directions, much like the ripples caused by throwing a rock into a pond. The time between wave crests may be from 5 to 90 minutes, and the wave speed in the open ocean will average 450 miles per hour. Tsunamis reaching heights of more than 100 feet have been recorded. As the waves approach the shallow coastal waters, they appear normal and the speed decreases. Then, as the tsunami nears the coastline, it may grow to great height and smash into the shore, causing much destruction. 1. Tsunamis are caused by an underwater disturbance—usually an undersea earthquake. Landslides, volcanic eruptions, and even meteorites can also generate a tsunami. 2. Tsunamis can originate hundreds or even thousands of miles away from coastal areas. Local geography may intensify the effect of a tsunami. Areas at greatest risk are less than 50 feet above sea level and within one mile of the shoreline. 3. People who are near the seashore during a strong earthquake should listen to a radio for a tsunami warning and be ready to evacuate at once to higher ground. 4. Rapid changes in the water level are an indication of an approaching tsunami. 5. Tsunamis arrive as a series of successive ‘‘crests’’ (high water levels) and ‘‘troughs’’ (low water levels). These successive crests and troughs can occur anywhere from 5 to 90 minutes apart. They usually occur 10 to 45 minutes apart. The Tsunami Warning System, a cooperative international organization and operated by the United States Weather Service, has been in operation since the 1940s. The headquarters of the center is located in Hawaii. An associated Alaska Regional Tsunami Warning System is located in Alaska. Tsunami prediction essentially

TSUNAMI

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PACIFIC

NORTH

SOUTH

PACIFIC

commences with earthquake monitoring and prediction information. Inputs from these systems are linked with information from a series of tide monitoring installations. Locations of tide stations and of seismograph stations in the Tsunami Warning System are shown in Fig. 1. When inputs indicate conditions are favorable for a tsunami, a watch is issued for the probable affected area. Warnings are issued when readings from various tidal stations appear to match the seismographic information. Because of the complexity of the factors involved and a large degree of uncertainty nearly always present, there is a tendency to issue watches and warnings as a safety precaution even though a tidal wave of significance may not develop. Unfortunately, after awhile, persons in likely areas to be affected grow callous to watches and tend to ignore them. A tsunami that hit Hilo, Hawaii in 1960 killed 60 residents even though they had been warned of the coming event an ample 6 hours in advance of the strike. This, however, was not the reason for the most devastating Tsunami in history which occurred on December 26, 2004 in the Indian Ocean as a result of a 9.0 earthquake off the shore of Banda Aceh, Indonesia. The resulting Tsunami quickly hit the Indonesian coastline, but hours later struck Sri Lanka, India, The Maldives, and later yet, Keyna and Somalia on the East coast of Africa. More than 150,000 lives were lost because no network existed to communicate the likely result of the 9.0 quake in the Indian Ocean. No such event had occurred in this area of the

Figure 1. Network of tide and seismograph stations that are part of the Tsunami Warning System, headquartered in Hawaii. (National Oceanic and Atmospheric Administration.).

world in over 120 years since Kakatoa erupted in 1883. Twenty three earthquake monitoring stations picked up the seismic shocks in Indonesia itself, and the U.S. Geological Survey’s worldwide monitoring system, with 120 stations, pinpointed the quake immediately. However, on that fateful Sunday, the few warning telephone calls that were made went unanswered. Thus, lack of communication, more than lack of technology, caused the extreme loss of life. The material destruction, however, touching so many countries, was a result of the movement of the Earth’s crust beneath the Indian Ocean extending along a fracture believed to have been 600 miles in length, ultimately creating a tidal wave nearly 1000 miles long. Such horror can never again touch the Indian Ocean nations as they continue to build a Tsunami Watch System containing all the elements of the early warning capability that has existed in the Pacific Ocean since the middle of the 20th century. In the late 1970s, scientists suggested an improved method for making tsunami predictions. For a number of years, specialists have suggested that better analysis and interpretation of seismic waves produced by earthquakes may improve the prediction of tsunamis. Seismic waves range from very short-period waves that result from the sharp snap of rocks under high stress to very long-period waves, due mainly to the slower movements of large sections of the ocean floor. Many researchers believe that tsunamis result mainly from the vertical movement of these large blocks, leading to a tentative conclusion that the strength of seismic waves of very long period may be

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TSUNAMI

the best criterion for an earthquake’s ability to generate a tsunami. Part of the problem is that most seismographs installed in the system are not very sensitive to very long-period waves, and thus a given earthquake cannot be analyzed effectively in terms of its potential for producing a tsunami. Equipment has been refined so that, today, shorter period waves are used to locate an earthquake and 20-second waves are used to calculate the magnitude. However, some scientists feel that the true magnitude of some earthquakes can only be determined by measuring the characteristics of longer waves, such as 100-second waves. Brune and Kanamori (University of California at San Diego) have observed that the Chilean earthquake of 1960 had a magnitude of 8.3 when calculated on the basis of 20-second waves, but its magnitude was 9.5, or more than 10 times larger in wave amplitude and more than 60 times larger in energy released, when calculated by Kanamori’s method, which attempts to include the energy release represented by very long-period seismic waves. Other scientists are coming to the viewpoint that many warnings could be omitted if predictions were based on longer waves. Two of the first long-period seismographs incorporated in the Tsunami Warning System were installed in Hawaii and on the Russian island of Yuzhno-Sakhalinsk, which is northeast of Vladivostok. Later, an installation was made at the Alaska Warning Center in Palmer. Whether the latest reasoning proves successful must await a number of years of experience with the earthquakes of the future and the resulting tsunamis. CONTINUING TSUNAMI RESEARCH During the 2000s, research pertaining to the fundamentals of tsunamis and the development of mathematical models of the phenomenon continues. Considerable attention is being directed to specific regions, including the west coasts of Mexico and Chile, the southwestern shelf of Kamchatka (Russia) and, in the United States, the generation of tsunamis in the Alaskan bight and in the Cascadia Subduction Zone off the west coasts of Washington (Puget Sound) and Oregon. Research also is being directed toward the development of simple and more economic warning systems, particularly in the interest of the developing countries, the coasts of which border on the Pacific Ocean. The Tsunami Warning System previously described requires millions of dollars for equipment, maintenance, and operation, well beyond the means of some countries. Also, some scientists believe that more localized equipment installations could possibly serve local shore communities better while costing less. These observations, however, do not challenge the need and validity for the larger tsunami network. The National Oceanic and Atmospheric Administration (NOAA) has developed a system costing in the range of $20,000 that can be installed and operated by non experts. The system has been undergoing trials at Valparaiso, Chile, a city that has been struck by nearly 20 tsunamis within the past two centuries. A sensor (accelerometer) is installed in bedrock under the city and can measure tectonic activity in excess of 7.0 on the

Richter scale. These measurements are interlocked with level sensors. Researchers B.F. Atwater and A.L. Moore (University of Washington), in their attempts to model earthquake and tsunami activity in the area over the last thousand years, have reported what they believe to have been a large earthquake on the Seattle fault some time between 1000 and 1100 years ago. The researchers report, ‘‘Water surged from Puget Sound, overrunning tidal marshes and mantling them with centimeters of sand. One overrun site is 10 km northwest of downtown Seattle; another is on Whidbey Island, some 30 km farther north. Neither site has been widely mantled with sand at any other time in the past 2000 years. Deposition of the sand coincided—to the year or less—with abrupt, probably tectonic subsidence at the Seattle site and with landsliding into nearby Lake Washington. These findings show that a tsunami was generated in Puget Sound, and they tend to confirm that a large shallow earthquake occurred in the Seattle area about 1000 years ago.’’ Simulations of tsunamis from great earthquakes on the Cascadia subduction zone have been carried out by M. Ng, P.H. Leblond, and T.S. Murty (University of British Columbia). A numerical model has been used to simulate and assess the hazards of a tsunami generated by a hypothetical earthquake of magnitude 8.5 associated with rupture of the northern sections of the subduction zone. The model indicates that wave amplitudes on the outer coast are closely related to the magnitude of seabottom displacement (5 meters). The researchers observe, ‘‘Some amplification, up to a factor of 3, may occur in some coastal embayments. Wave amplitudes in the protected waters of Puget Sound and the Straits of Georgia are predicted to be only about one-fifth of those estimated on the outer coast.’’ READING LIST Atwater, B.F. and Moore, A.L (December 4, 1991). A tsunami about 1000 years ago in Puget Sound, Washington. Science: 1614. Bernard, E.N. (Ed.). (July 1989). Tsunami Hazard: A Practical Guide for Tsunami Hazard Reduction, (Papers from Symposium at Novosibirsk, Russia). International Union of Geodesy and Geophysics, New York. Bryant, E. (2001). Tsunami: The Underrated Hazard. Cambridge University Press, New York. Collins, E. (February 1988). Wave Watch. Sci. Amer: 28. Kubota, I. (Spring 1987). Japan’s Weather Service and the Sea. Oceanus: 71. Lander, J.F., Lockridge, P.A., and Kozuch, M.J. (1997). Tsunamis Affecting the West Coast of the United States, 1806–1992. DIANE Publishing Company, Collingdale, PA. Lander, J.F. (1997). Tsunamis Affecting Alaska, 1737–1996. DIANE Publishing Company, Collingdale, PA. Ng, M.K-F., Leblond, P.H., and Murty, T.S. (November 30, 1990). Simulation of Tsunamis from Great Earthquakes on the Cascade Subduction Zone. Science: 1248. Prager, E.J. (1999). Furious Earth: The Science and Nature of Earthquakes, Volcanoes, and Tsunamis. McGraw-Hill Professional Book Group, New York.

TSUNAMI Soloviev, S.L., Kim, K.S., Solovieva, O.N. et al. (2000). Tsunamis in the Mediterranean Sea, 2000 B.C. –2000 A.D. Kluwer Academic Publishers, Norwell, MA. Staff. (1997). Long-Wave Runup Models. World Scientific Publishing Company, Inc., River Edge, NJ. Tsuchiya, Y. and Shuto, N. (1995). Tsunami: Progress in Prediction, Disaster Prevention and Warning. Kluwer Academic Publishers, Norwell, MA.

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WEB REFERENCES International Tsunami Information Center (ITIC): http://www. shoa.cl/oceano/itic/frontpage.html. National Tsunami Hazard Mitigation Program: http://www.pmel. noaa.gov/tsunami/. Tsunami Links: http://www.pmel.noaa.gov/tsunami-hazard/links. html.

METEOROLOGY BALLOONING AND METEOROLOGY IN THE TWENTIETH CENTURY LINDA VOSS U.S. Centennial of Flight Commission

Balloons are ideal for gathering meteorological information and have been used for that purpose throughout their history. Meteorological measurements of wind and air pressure have gone hand in hand with the earliest balloon launches and continue today. Balloons can climb through the denser air close to the Earth to the thinner air in the upper atmosphere and collect data about wind, the different layers of the atmosphere, and weather conditions as they travel. The first meteorological balloon sondes, or ‘‘registering balloons,’’ were flown in France in 1892. These balloons were relatively large, several thousand cubic feet, and carried instruments to record barometric pressure (barometers), temperature (thermometers), and humidity (hygrometers) data from the upper atmosphere. They were open at the base of the balloon and were inflated with a lifting gas, which could be hydrogen, helium, ammonia, or methane. The lifting gas in the balloon exited through the

A balloon equipped for meteorological observations. A German balloon ascent in the late 1800s. 17 Balloon Equipped for Meteorological Observations.

A zero-pressure balloon being inflated at Alice Springs, Australia.

opening as the balloon expanded during its ascent and the air became thinner and the pressure dropped. At the end of the day, as the lifting gas cooled and took up less space, the balloon descended very slowly. The meteorologists had to wait until the balloon descended all the way to Earth to

Two men performing balloon tests for the U.S. Weather Bureau.

This article is a US Government work and, as such, is in the public domain in the United States of America. 164

BALLOONING AND METEOROLOGY IN THE TWENTIETH CENTURY

Weather balloons are used daily to carry meteorological instruments to 20 miles (30 kilometers) and above into the atmosphere to measure temperature, pressure, humidity, and winds. The balloons are made of rubber and weigh up to 2.2 pounds (one kilogram). More than 200,000 weather soundings are made with such balloons worldwide each year.

Preparing to launch America’’s first ‘‘ballon-sonde.’’ Since this first launch on September 15, 1904, in St. Louis, Missouri, literally millions of weather balloons have been launched by the National Weather Service and its predecessor organization. From: The Principles of Aerography, by Alexander McAdle, 1917.

retrieve their instruments, which often had drifted up to 700 miles (1,126 kilometers) from their launch point. The German meteorologist Assmann solved the problem of drifting balloons and retrieval of instruments in 1892 by introducing closed rubber balloons that burst when they reached a high altitude, dropping the instruments to Earth by parachute much closer to the launch

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site. These balloons also had fairly constant rates of ascent and descent for more accurate temperature readings. Assmann also invented a psychrometer, a type of hygrometer used to measure humidity in the air that laboratories generally use. In the 1930s, meteorologists were able to get continuous atmospheric data from balloons when the radiosonde was developed. A radiosonde is a small, radio transmitter that broadcasts or radios measurements from a group of instruments. Balloons, usually unmanned, carry the transmitter and instruments into the upper atmosphere. The radiosonde transmits data to Earth while measuring humidity, temperature, and pressure conditions. Today, three types of balloons are commonly used for meteorologic research. Assmann’s rubber, or neoprene, balloon is used for measuring vertical columns in the atmosphere, called vertical soundings. The balloon, inflated with a gas that causes the balloon to rise, stretches as it climbs into thin air, usually to around 90,000 feet (27,400 meters). Data is taken as the balloon rises. When the balloon has expanded from three to six times its original length (its volume will have increased 30 to 200 times its original amount), it bursts. The instruments float to Earth under a small parachute. The neoprene balloon can either carry radiosondes that transmit meteorological information or be tracked as a pilot balloon, a small balloon sent aloft to show wind speed and direction. Around the world, balloons equipped with radiosondes make thousands of soundings of the winds, temperature, pressure, and humidity in the upper atmosphere each day. But these balloons are launched and tracked from land, which limits what the radiosondes can measure to less than one-third of the Earth’s surface. Zero-pressure plastic (usually polyethylene) balloons were first launched in 1958. They carry scientific instruments to a predetermined atmospheric density level. Zero-pressure balloons are the best for extremely high altitudes because the balloons can be lighter and stress on them can be distributed over the surface of the balloon. About the same time, the Air Force Cambridge Research Laboratories (AFCRL) started working on super-pressure balloons, which were made from mylar. The development of mylar plastic films and advances in electronic miniaturization made constant-altitude balloons possible. Mylar is a plastic that can withstand great internal pressure. The mylar super-pressure balloon does not expand as it rises, and it is sealed to prevent the release of gas as the balloon rises. By the time the balloon reaches the altitude where its density equals that of the atmosphere, the gas has become pressurized because the heat of the sun increases the internal gas pressure. However, because mylar can withstand great internal pressure, the volume of the balloon remains the same. By carefully calculating the weight of the balloon and whatever it is carrying, the altitude at which the balloon will achieve equilibrium and float can be calculated. As long as the pressure inside the balloon remains the same, it will remain at that altitude. These balloons could be launched to remain aloft at specified altitudes for weeks or months at a time.

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Moreover, satellites could be used to track and request data from many balloons in the atmosphere to obtain a simultaneous picture of atmospheric conditions all over the globe. Another advantage of super-pressure balloons is that, since they transmit their data to satellites, they can gather data from over oceans as well as land, which is a limitation of balloons equipped with radiosondes. The AFCRL program resulted in the Global Horizontal Sounding Technique (GHOST) balloon system. With GHOST, meteorologists at last achieved their goal of semipermanent platforms floating high in the atmosphere. Eighty-eight GHOST balloons were launched starting in March of 1966. The GHOST balloons and their French counterpart, EOLE, (the name Clement Ader used for one of his aircraft—named after the Greek god of the wind) used strong, plastic super-pressure balloons to trace air circulation patterns by drifting with the wind at constant density altitudes. Many super-pressure balloons were aloft at a time, grouped at constant density levels. Each balloon had a sensing device and transmitting system for gathering information on its position and weather data and transmitted atmospheric and weather data to weather satellites. They first transmitted their data to the NASA Nimbus-4 meteorological satellite in 1970. In 1966, a GHOST balloon circled the Earth in 10 days at 42,000 feet (12,801 meters). By 1973, NASA had orbited scientific instrument packages aboard sealed balloons at altitudes up to 78,000 feet (23,774 meters). Other GHOST balloons remained aloft for up to a year. The program lasted for 10 years. The ultimate of the super-pressure balloons was the balloon satellite Echo I. Launched into space in 1960, the balloon inflated to a sealed volume by residual air, benzoic acid, and a chemical called anthraquinone. Constant-altitude, super-pressure balloons continue to fly over the oceans and land surfaces. These balloons have been relied on for decades to provide extensive knowledge of global meteorology and improve worldwide weather forecasting.

concise.asp?ti=761576250&sid=3#s3. http://www.encarta.msn .com. ‘‘Measuring the Weather,’’ USAToday.com. http://www.usatoday .com/weather/wmeasur0.htm. ‘‘Meteorology,’’ Microsoft Encarta Online Encyclopedia 2000. 1997–2000 Microsoft Corporation. http://encarta.msn.com. Warner, Lucy, ed. ‘‘Forecasts: Observing and Modeling the Global Atmosphere,’’ UCAR at 25. University Center for Atmospheric Research. Boulder, Colorado. Oct. 17, 2000. http://www.ucar.edu/communications/ucar25/forecasts.html. ‘‘Weather Instruments to Make.’’ http://asd-www.larc.nasa.gov/ SCOOL/psychrometer.html To find out how you can make your own psychrometer, link to The CERES S’COOL Project at http://asdwww.larc.nasa.gov/SCOOL. The link has lots of information about making weather observations. Making a Psychrometer is in the Table of Contents or go to http://explorer.scrtec.org/explorer/explorer-db/html/783750680447DED81.html. To learn more about weather instruments and even set up your own weather station to report to the U.S. National Weather Service, go to http://www.usatoday.com/weather/wmeasur0.htm.

Educational Organization

Standard Designation (where Content of applicable) Standard

National Science Education Standards

Content Standard D

International Technology Education Association International Technology Education Association

Standard 9

Crouch, Tom D. The Eagle Aloft: Two Centuries of the Balloon in America. Washington, DC.: Smithsonian Institution Press, 1983. Tannenbaum, Beulah and Harold E. Making and Using Your Own Weather Station. New York. Venture Books, 1989. Vaeth, J. Gordon. ‘‘When the Race for Space Began.’’ U.S. Naval Institute Proceedings. August 1961.

International Technology Education Association

Standard 7

ONLINE REFERENCES

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Standard 10

READING LIST

Cowens, John. ‘‘Building a Psychrometer,’’ Greenwood Elementary, La Grande, OR 97850. September 28, 1993. http://explorer.scrtec.org/explorer/explorer-db/html/783750680447DED81.html ‘‘Hygrometer,’’ Microsoft Encarta Online Encyclopedia 2000. 1997–2000 Microsoft Corporation. http://encarta.msn.com. Lally, Vincent E. ‘‘Balloon: Modern Scientific Ballooning,’’ Microsoft Encarta Online Encyclopedia 2000. 1997–2000 Microsoft Corporation. http://www.encarta.msn.com//find/

Students should develop an understanding of energy in the earth system. Students will develop an understanding of engineering design. Students will develop an understanding of the role of trouble shooting, research and development, innovation, and experimentation in problem solving. Students will develop an understanding of the influence of technology on history.

TODD RASMUSSEN The University of Georgia Athens, Georgia

Water levels in wells are often observed to fluctuate as the air pressure changes. Blaise Pascal described this effect in 1663 (1) and was the first to attribute the water level changes in wells to changes in atmospheric pressure. He

BAROMETRIC EFFICIENCY

CONFINED AQUIFERS For confined aquifers, Jacob (4) showed that increasing the load on the ground surface increases the load on the aquifer. This additional weight is either carried by the mineral grains or by the water within the aquifer pores. If the entire weight is borne by the mineral grains, and these grains do not deform with the increase in load, then the total head within the aquifer remains unchanged, and the barometric efficiency is 100%. The barometric efficiency is smaller if some of the weight is carried by the fluid. A very low barometric efficiency in confined aquifers occurs when the fluid within

Barometric effciency, BE = 1

Total head Water level Barometric pressure Barometric effciency, BE = 0

5

5

4

4

3

3 Head

where consistent units (e.g., feet of water, mm of Hg, hPa) are used for both water levels and barometric pressure (2,3). To understand why this relationship exists, we can conceive of an aquifer that is entirely isolated from the atmosphere. Such an aquifer maintains a constant total head, H = Ho , within the aquifer and is entirely unaffected by atmospheric pressure changes. Water level elevations, W, in the aquifer are measured in an open borehole. The total head within the well is the sum of the water level elevation plus the barometric pressure exerted on the water surface, H = W + B. If the total head within the well is equal to the total head within the aquifer, Ho = W + B, and the total head within the aquifer is constant, then the water level varies inversely with barometric pressure, W = Ho − B. The change in water level is just the negative of the change in barometric pressure,
W =
(Ho − B) = −
B, so that the barometric efficiency is 100 percent, BE = −
W/
B = −(−
B)/
B = 1. A second example assumes that the total head in the hypothetical aquifer increases with barometric pressure, H = Ho + B, so that the head in the aquifer goes up and down over time. In this case, the water levels in the well remain unchanged, and the barometric efficiency of the aquifer is zero. These two extremes are shown in Fig. 1. Note that the barometric pressure is identical in both cases. In the left figure, the barometric efficiency is 100%, so that the water level varies inversely with barometric pressure. The total head is the sum of the barometric pressure and water levels, so it remains unchanged. In the right figure, the barometric efficiency is zero, so that the water level is unaffected by barometric pressure changes and the total head varies directly with barometric pressure. Most aquifers lie between these two extremes, however, and the actual response depends, in large part, on whether the aquifer is confined or unconfined. Both of these cases are described below.

Total head Water level Barometric pressure

Head

noted that water levels declined as the barometric pressure increased, and vice versa. The barometric efficiency, BE, is used to relate changes in water levels,
W, to changes in barometric (air) pressure,
B:
W (1) BE = −
B

2 1

2 1

0

0

−1

−1

0

10

20 Time

30

167

0

10

20

30

Time

Figure 1. Effect of barometric pressure on water levels in wells. Both figures show barometric pressure (lower, dashed line), total head (solid line), and water levels (dotted line). Left figure shows effects when the barometric efficiency is 100%, BE = 1, and right figure shows effects when the barometric efficiency is zero, BE = 0.

the aquifer bears most of the weight. Examples of such aquifers include poorly consolidated sedimentary aquifers or horizontal fractures that extend great distances. Figure 2 shows the extreme conditions. In the left figure, the entire increase in load caused by an increase in barometric pressure is carried by the mineral grains. In this case, the pore fluids are not affected by the increase in load, the total head remains unchanged, and water levels drop in an amount equal to the increase in barometric pressure. In the right figure, the mineral grains do not carry the load and the fluid carries the increased load, causing an increase in total head. In confined aquifers, the barometric response is virtually instantaneous. A change in barometric pressure should cause an immediate change in water levels in wells. Water levels in large-diameter wells may not respond immediately, however, because of the time required for water levels to adjust to the new level. Instead of a rapid

B

Aquitard

Mineral grains ∆W = − ∆ B α=1

B

Aquitard

Pore fluids ∆H = ∆B α=0

Figure 2. Effect of barometric pressure on total head in confined aquifers. The mineral grains carry the load in the left figure, whereas the pore fluids carry the load in the right figure. Most confined aquifers, however, are intermediate between these two extremes.

BAROMETRIC EFFICIENCY

response to pressure changes, a slow response may be found in these wells. This phenomena is called borehole storage and is a function of the diameter of the borehole, the length of the screened interval relative to the aquifer thickness, the aquifer hydraulic properties (e.g., transmissivity and storativity), and the rate at which the barometric pressure is changing. The effects of borehole storage can be eliminated by placing a packer in the well below the water surface, but above the screened interval, which eliminates the need for the water level to change in response to changes in barometric pressure. Some change in volume may result from the slight compressibility of water, but this effect is very small. A gauge-type pressure sensor (i.e., internally vented to the atmosphere) is then placed below the packer to measure the water pressure. Several techniques are available for estimating the confined aquifer barometric efficiency, including linear regression and Clark’s Method (5). Clark’s method is an unbiased technique for estimating the barometric efficiency that performs well when a water level trend is present in the data (6). Regression provides a better estimate, but only when the trend function can be accurately specified (7).

UNCONFINED AQUIFERS Barometric pressure changes commonly do not affect water levels in wells located in shallow, unconfined aquifers, which is because the air pressure moves rapidly through the unsaturated zone and causes an immediate increase in total head within the aquifer. In deeper unconfined aquifers, however, the typical response to barometric pressure changes is to see an immediate inverse response (i.e., an increase in barometric pressure causes an equivalent and opposite water level response), followed by a slow decay back to the original water level (5,8,9). To understand this complex response, we focus on how total head responds to barometric pressure changes. Initially, no increase in total head within the unconfined aquifer occurs because the water held within pores is not confined by an overlying confining unit. The total head within the aquifer can rise over time, however, as air diffuses downward through the unsaturated zone. The total head in the unconfined aquifer increases once the air pressure change reaches the water table. The time required for the total head to respond to barometric pressure changes is a function of the depth of the water table and the air diffusivity within the unsaturated zone. The air diffusivity is higher in coarse, dry soils and is lower in wet soils or in soils with a low air permeability. As the water level response in observation wells is the total head minus the barometric pressure, the fact that the total head does not change initially means that a rapid water-level response occurs to barometric pressure changes. In fact, the barometric efficiency is one in wells with a deep unsaturated zone—or where the air permeability of the unsaturated zone is low—followed

Unsaturated zone barometric response 1.5 1 0.5 Head

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0 −0.5 −1 −1.5

Barometric pressure Total head Water level

0

5

10

15 Time

20

25

30

Figure 3. Effect of barometric pressure on total head and water levels in confined aquifers. The barometric pressure in this example takes a step from zero to one at t = 10. The total head slowly rises as the barometric pressure makes its way through the unsaturated zone. The water levels initially fall to maintain the constant total head, but then return to normal once the barometric pressure signal reaches the water table.

by a gradual decrease as air diffuses downward to the water table. This concept is illustrated graphically in Fig. 3. Note that the barometric pressure is simplified to a simple step change from zero to one. The total head does not initially respond, but slowly rises over time as the barometric pressure moves through the unsaturated zone and eventually reaches the water table. The observed water level in a well placed in this aquifer responds immediately (as long as borehole storage can be neglected), but eventually decays back to its original level The barometric efficiency of unconfined aquifers is not single valued like the confined aquifer barometric efficiency. Instead, the response includes a delay that can be estimated using regression deconvolution (5,9). The resulting response can be used to estimate the unsaturated air diffusivity of the unsaturated zone. BIBLIOGRAPHY 1. Pascal, B. (1973). The Physical Treatises of Pascal. Octagon Books, New York. 2. Bear, J. (1972). Dynamics of Fluids in Porous Media. Dover Publications, New York. 3. Walton, W.C. (1970). Groundwater Resource Evaluation. McGraw-Hill, New York. 4. Jacob, C.E. (1940). On the flow of water in an elastic artesian aquifer. Amer. Geophys. Union Trans. 21: 574–586. 5. Rasmussen, T.C. and Crawford, L.A. (1997). Identifying and removing barometric pressure effects in confined and unconfined aquifers. Ground Water. 35(3): 502–511. 6. Clark, W.E. (1967). Computing the barometric efficiency of a well. J. Hydraul. Divi. Amer. Soc. Civil Engin. 93(HY4): 93–98. 7. Davis, D.R. and Rasmussen, T.C. (1993). A comparison of linear regression with Clark’s method for estimating barometric

CERES: UNDERSTANDING THE EARTH’S CLOUDS AND CLIMATE efficiency of confined aquifers. Water Resources Res. 29(6): 1849–1854. 8. Weeks, E.P. (1979). Barometric fluctuations in wells tapping deep unconfined aquifers. Water Resources Res. 15(5): 1167–1176. 9. Spane, F.A., Jr. (2002). Considering barometric pressure in groundwater flow investigations. Water Resources Res. 38(6): 1078.

READING LIST Spane, F.A., Jr. and Mercer, R.B. (1985). HEADCO: A Program for Converting Observed Water Levels and Pressure Measurements to Formation Pressure and Standard Hydraulic Head. Pacific Northwest National Laboratory, Rockwell Hanford Operations, Richland, WA. Report PNL-10835.

CERES: UNDERSTANDING THE EARTH’S CLOUDS AND CLIMATE NASA—Langley Research Center

The Clouds and the Earth’s Radiant Energy System (CERES) instrument is one of several launched aboard the Earth Observing System’s (EOS) Aqua spacecraft in 2002. Scientists use observations from the CERES instrument to study the energy exchanged between the Sun; the Earth’s atmosphere, surface and clouds; and outer space. The CERES Aqua instruments are the fourth and fifth CERES instruments in orbit. NASA launched the first CERES instrument aboard the Tropical Rainfall Measuring Mission satellite or TRMM in November 1997. Results of the TRMM mission show that the first CERES provided better measurement capabilities than any previous satellite instrument of its kind. Two other CERES instruments are currently orbiting the Earth on the EOS Terra spacecraft, launched in late 1999. Early CERES Terra results give new insights into the effects of clouds on climate and how the climate system changes from decade to decade. Two CERES instruments on each of the Terra and Aqua spacecraft will provide global coverage of energy radiated and reflected from the Earth. Scientists use measurements from both satellites’ orbits to improve observations of the daily cycle of radiated energy. NASA Langley Research Center manages the CERES mission. Langley’s highly successful Earth Radiation Budget Experiment (ERBE) provided the foundation for the design of the CERES instrument. ERBE used three satellites to provide global energy measurements from 1984 through the 1990s. The TRW Space & Electronics Group in Redondo Beach, Calif., built all six CERES instruments.

This article is a US Government work and, as such, is in the public domain in the United States of America.

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WHAT CERES WILL MEASURE CERES measures the energy at the top of the atmosphere, as well as estimate energy levels in the atmosphere and at the Earth’s surface. Using information from very high resolution cloud imaging instruments on the same spacecraft, CERES will determines cloud properties, including altitude, thickness, and the size of the cloud particles. All of these measurements are critical for advancing the understanding of the Earth’s total climate system and the accuracy of climate prediction models. BALANCING THE EARTH’S ENERGY BUDGET The balance between Earth’s incoming and outgoing energy controls daily weather and climate (long-term weather patterns). Sunlight or solar energy is the planet’s only incoming energy source. Heat emitted from the sunlight reflected by the Earth’s surface, atmosphere and clouds make up the planet’s outgoing energy. Scientists have been working for decades to understand this critical energy balance, called the Earth’s ‘‘energy budget.’’ The energy received from the Sun is at short wavelengths, while the energy emitted by the surface of the Earth, the atmosphere and clouds is at long wavelengths. Greenhouse gases in the atmosphere absorb the long wavelength energy or heat emitted by the Earth. Increases in the amounts of greenhouse gases produced by both natural processes or human activities can lead to a warming of the Earth’s surface. Such changes may, in turn, alter the planet’s daily weather and climate. Clouds and small particles in the atmosphere called aerosols also reflect some sunlight back into space. Major sources of aerosols include windblown dust, emissions from the burning of fossil fuels, such as gasoline, and the burning of forests and agricultural fields. CLOUD EFFECTS One of the most intriguing questions facing climate modelers today is how clouds affect the Earth’s climate

CERES detects low (blue and white) to high (yellow) amounts of emitted heat

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CHINOOK

Earth’s radiation budget is the balance between incoming and outgoing energy

and vice versa. The U.S. Global Change Research Program classifies understanding the role of clouds and the Earth’s energy budget as one of its highest scientific priorities. Understanding cloud effects requires a detailed knowledge of how clouds absorb and reflect sunlight, as well as how they absorb and re-emit outgoing heat emitted by the planet. For example, low, thick clouds primarily reflect incoming solar energy back to space causing cooling. Thin, high clouds, however, primarily trap outgoing heat and produce warming. To date, satellite studies have found that clouds have an overall cooling effect on the Earth. Analyses of satellite data also indicate that clouds which form over water are very different from clouds which form over land. These differences affect the way clouds reflect sunlight back into space and how much heat emitted from the Earth the clouds absorb and re-emit. For example, over the equator in the eastern Pacific Ocean ˜ events, there is a significant decrease during El Nino in the amount of energy emitted by the Earth due to ˜ events occur when portions increased cloudiness. El Nino of the eastern Pacific Ocean become considerably warmer than normal, causing an increase in cloudiness over the region. These changes can affect weather patterns around the world. WATER VAPOR EFFECTS Water vapor in the atmosphere also impacts our daily weather and climate, though scientists are only beginning to understand how this complex mechanism works. Water vapor acts like a greenhouse gas and absorbs outgoing heat to warm the Earth. Because water vapor also condenses to make clouds, additional water vapor in the atmosphere also may increase the amount of clouds. FUTURE MISSIONS One additional CERES instrument is available to fill the gap between Aqua and the next generation of highly accurate Earth radiation budget measurements. These

observations are expected to be made on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) starting around 2010. To continue the 22-year record of global energy measurements, the next CERES mission should launch in 2007. EDUCATIONAL OUTREACH As a CERES instrument passes overhead, students worldwide are observing clouds and then sending their observations to NASA Langley’s Atmospheric Sciences Data Center (ASDC). At the ASDC, scientists store data for further analysis by the CERES science team. The student observations are part of a global educational outreach program called the Students’ Cloud Observations On-Line (S’COOL) project. Since the project began five years ago, S’COOL has reached over 1,000 schools in all 50 states and 57 other countries on five continents. COMMERCIAL APPLICATIONS CERES supports commercial applications by providing data about weather and sunlight at the Earth’s surface for the renewable energy industry via an innovative Web site (http://eosweb.larc.nasa.gov/sse/). The Surface Meteorology and Solar Energy Project maintains the site. In the first three years of operation, the number of registered users of the Web site, including major energy companies, financial institutions and federal agencies, has grown to over 2,000 from nearly 100 countries. With 35,000 hits per month since January 2001, SSE is the most accessed Web site at the ASDC.

CHINOOK ARTHUR M. HOLST Philadelphia Water Department Philadelphia, Pennsylvania

Wind is defined as the movement of air. Although we commonly define wind as a gentle breeze or a harsh gust of

GLOBAL CLIMATE CHANGE

cold air, there is a wind phenomenon that can increase the temperature instead of lowering it. It is called a Chinook wind. Chinooks are most commonly associated with the Rocky Mountain range in North American but can also be found in the Swiss Alps and the Andes. They can increase temperatures high enough to melt the snow in their path as they travel down the mountainside. The Chinook wind falls under the classification of katabatic wind, which means that it moves downhill. The name ‘‘Chinook’’ was taken from the Chinook Indians that lived along the Rocky Mountains until the early 1800s when the tribe became extinct due to disease. Although the tribe died off, their legends and tales live on. One such legend is that of the Chinook wind, which in its literal translation means ‘‘snow-eater.’’ It is possible for a Chinook to take place anytime during the year, but its effects are much more dramatic during the winter months. Chinook winds cause dramatic increases in the temperature on the eastern side of the Rockies and can send temperatures into the fifties and sixties. A temperature change of this magnitude can take anywhere from an hour to a day. The heat produced is a reaction formed from the change of gas to liquid in the atmosphere. These warm gusts of air then cause the evaporation of any snow on the ground, hence the name snow-eater. There is no definite length of time that a Chinook will last. On average, it can last hours or days. Chinooks are the end result of the warm moist air of the Pacific Ocean moving up and down the Rocky Mountains. A westerly wind collects the warm moist air in the Pacific Ocean and carries it to the coast where it meets the western side of the Rockies. As the air makes its way up the mountain, the air becomes cooler, and the precipitation is squeezed out of it. Through this process warm, dry air is produced as it makes its way down the eastern side of the mountain. This process is repeated over and over again on each mountain that is in the way of the wind and each time produces warmer, dryer air. The air that makes its way down the last mountain is extremely dry and warm. This wind is called the Chinook wind. These warm gusts of air can reach speeds up to 100 mph. The results from Chinook winds are both positive and negative. Chinook winds cause evaporation of the snow covering the ground, so the length of the grazing season is extended. A longer grazing season decreases the need to stock up on feed for animals. A negative result is the decreased amount of precipitation due to the quick evaporation of snow. Less precipitation causes hardships in planting. READING LIST Alberta Agriculture, Food, and Rural Development. (2002). Weather in Alberta. Available: http://www.agric.gov.ab.ca/ agdex/000/7100001b.html. (March 11). The Alberta Traveller. (2002). Chinook Winds. Available: http://www.traveller.babelfish.com/weather guides/Chinook. html. (March 11). Black Hills Weather. (2002). The Snow Eating Wind. Available: http://www.blackhillsweather.com/chinook.html. (March 11). Ho, I. (2002). Snow-Eater. The Catalyst. Available: http://www. brown.edu/Students/Catalyst/archive/spring99/ch.html. (March 11).

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Under the Chinook Arch. http://www.nucleus.com/∼cowboy/ Misc/Chinooks.html. (11 March 2002).

GLOBAL CLIMATE CHANGE Geophysical Fluid Dynamics Laboratory—NOAA

In 1967, two GFDL scientists, Syukuro Manabe and Richard Wetherald, published what is now regarded as the first credible calculation of the effect of increased carbon dioxide on the climate. They calculated that a doubling of atmospheric carbon dioxide would warm the earth’s surface by about 2 ◦ C. This result laid the foundation for what has become an international, multi-disciplinary research effort on global warming. Manabe, in collaboration with oceanographer Kirk Bryan and other scientists at GFDL, has continued to lead the international effort to develop the coupled oceanatmosphere climate models that are crucial to understanding and predicting the impact of greenhouse gases.

Three-dimensional view of projected surface air temperature and ocean warming ( ◦ C) due to greenhouse gases as calculated by a low-resolution GFDL coupled ocean-atmosphere climate model. The top panel shows the surface air temperature change over North and South America and surrounding regions. The three-dimensional box illustrates the depth to which a 1 ◦ C and 0.2 ◦ C warming has penetrated in the model’s Pacific Ocean. The gray surface depicts the model’s ocean floor. Note the deep mixing of the ocean warming signal in the southern hemisphere ocean near Antarctica. The temperature changes are projections of the warming due to greenhouse gases by the latter half of the twenty-first century in the absence of further increases in sulfate aerosol forcing. Results shown are based on years 61–80 of a transient CO2 increase experiment (+1% per year compounded). [Source: adapted from Syukuro Manabe and Ronald Stouffer, Nature, 15 July 1993.]

This article is a US Government work and, as such, is in the public domain in the United States of America.

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OBSERVATIONS OF CLIMATE AND GLOBAL CHANGE FROM REAL-TIME MEASUREMENTS

is enough to cause the ocean’s global thermohaline circulation to almost disappear in the model. The global thermohaline circulation is important because it is responsible for a large portion of the heat transport from the tropics to higher latitudes in the present climate. In addition, sea level continues rising steadily for centuries after the CO2 increase is halted. From this perspective, global warming can no longer be viewed as just as a problem of our own lifetimes, but as a legacy—with uncertain consequences—now being passed forward to many future generations. EVALUATING CLIMATE MODELS GFDL scientists, including Tony Broccoli and Tom Delworth, are searching for innovative ways to evaluate climate models and to distinguish between human-induced climate change and natural climate variability. Measurements of the current climate, historical observations, and glimpses of earth’s climate during the ice ages and other past climates all provide opportunities to test climate models. Through research on climate models and observations, scientists at GFDL will continue to evaluate and refine the climate models that will be needed to help answer critical policy-relevant questions about global warming and its consequences.

OBSERVATIONS OF CLIMATE AND GLOBAL CHANGE FROM REAL-TIME MEASUREMENTS DAVID R. EASTERLING THOMAS R. KARL

Impact of increasing CO2 on the earth’s climate as simulated in a GFDL coupled ocean-atmosphere climate model. Shown are timeseries of: a) prescribed CO2 concentration on a logarithmic scale in comparison to present levels; b) global mean surface air temperature ( ◦ C); c) global mean increase of sea level (cm) due to thermal expansion; and d) intensity of the North Atlantic Ocean’s meridional overturning circulation (10**6 m**3/sec). The labels ‘‘Control’’, ‘‘2xCO2 ’’, and ‘‘4xCO2 ’’ refer to separate experiments where CO2 either remains constant (Control), or increases at 1% per year (compounded) to double (2xCO2 ) or quadruple (4xCO2 ) the current concentration. Note that the sea level rise estimates do not include the effect of melted continental ice sheets. With this effect included, the total rise could be larger by a substantial factor. [Source: Syukuro Manabe and Ronald Stouffer, Nature, 15 July 1993.]

A PROBLEM FOR CENTURIES TO COME? In a recent paper, published 26 years after Manabe’s pioneering one-dimensional CO2 sensitivity study, he and Ron Stouffer of GFDL used a three-dimensional coupled ocean-atmosphere model to examine possible CO2 -induced climate changes over several centuries. Earlier studies had focused on shorter time horizons. In their scenario, CO2 quadruples over a period of 140 years, then no longer increases. This perturbation

(from Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, Wiley 2003)

INTRODUCTION Is the planet getting warmer? Is the hydrologic cycle changing? Is the atmospheric/oceanic circulation changing? Is the weather and climate becoming more extreme or variable? Is the radiative forcing of the climate changing? These are the fundamental questions that must be answered to determine if climate change is occurring. However, providing answers is difficult due to an inadequate or nonexistent worldwide climate observing system. Each of these apparently simple questions are quite complex because of the multivariate aspects of each question and because the spatial and temporally sampling required to address adequately each question must be considered on a global scale. A brief review of our ability to answer these questions reveals many successes, but points to some glaring inadequacies that must be addressed in any attempt to understand, predict, or assess issues related to climate and global change.

OBSERVATIONS OF CLIMATE AND GLOBAL CHANGE FROM REAL-TIME MEASUREMENTS

IS THE PLANET GETTING WARMER? There is no doubt that measurements show that nearsurface air temperatures are increasing. Best estimates suggest that the warming is around 0.6 ◦ C (+−0.2 ◦ C) since the late nineteenth century (1). Furthermore, it appears that the decade of the 1990s was the warmest decade since the 1860s, and possibly for the last 1000 years. Although there remain questions regarding the adequacy of this estimate, confidence in the robustness of this warming trend is increasing (1). Some of the problems that must be accounted for include changes in the method of measuring land and marine surface air temperatures from ships, buoys, land surface stations as well as changes in instrumentation, instrument exposures and sampling times, and urbanization effects. However, recent work evaluating the effectiveness of corrections of sea surface temperatures for time-dependent biases, and further evaluation of urban warming effects on the global temperature record have increased confidence in these results. Furthermore, by consideration of other temperature-sensitive variables, e.g., snow cover, glaciers, sea level and even some proxy non-realtime measurements such as ground temperatures from boreholes, increases our confidence in the conclusion that the planet has indeed warmed. However, one problem that must be addressed is that the measurements we rely upon to calculate global changes of temperature have never been collected for that purpose, but rather to aid in navigation, agriculture, commerce, and in recent decades for weather forecasting. For this reason there remain uncertainties about important details of the past temperature increase and our capabilities for future monitoring of the climate. The IPCC (1) has summarized latest known changes in the temperature record, which are summarized in Fig. 1. Global-scale measurements of layer averaged atmospheric temperatures and sea surface temperatures from instruments aboard satellites have greatly aided our ability to monitor global temperature change (2–4), but the situation is far from satisfactory (Hurrell and Trenberth, 1996). Changes in satellite temporal sampling (e.g., orbital drift), changes in atmospheric composition (e.g., volcanic emissions), and technical difficulties related to overcoming surface emissivity variability are some of the problems that must be accounted for, and reduce the confidence that can be placed on these measurements (5). Nonetheless, the space-based measurements have shown, with high confidence, that stratospheric temperatures have decreased over the past two decades. Although perhaps not as much as suggested by the measurements from weather balloons, since it is now known that the data from these balloons high in the atmosphere have an inadvertent temporal bias due to improvements in shielding from direct and reflected solar radiation (6).

IS THE HYDROLOGIC CYCLE CHANGING? The source term for the hydrologic water balance, precipitation, has been measured for over two centuries in

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some locations, but even today it is acknowledged that in many parts of the world we still cannot reliably measure true precipitation (7). For example, annual biases of more than 50% due to rain gauge undercatch are not uncommon in cold climates (8), and, even for more moderate climates, precipitation is believed to be underestimated by 10 to 15% (9). Progressive improvements in instrumentation, such as the introduction of wind shields on rain gauges, have also introduced time-varying biases (8). Satellitederived measurements of precipitation have provided the only large-scale ocean coverage of precipitation. Although they are comprehensive estimates of largescale spatial precipitation variability over the oceans where few measurements exist, problems inherent in developing precipitation estimates hinder our ability to have much confidence in global-scale decadal changes. For example, even the landmark work of Spencer (10) in estimating worldwide ocean precipitation using the microwave sounding unit aboard the National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites has several limitations. The observations are limited to ocean coverage and hindered by the requirement of an unfrozen ocean. They do not adequately measure solid precipitation, have low spatial resolution, and are affected by the diurnal sampling inadequacies associated with polar orbiters, e.g., limited overflight capability. Blended satellite/in situ estimates also show promise (11); however, there are still limitations, including a lack of long-term measurements necessary for climate change studies. Information about past changes in land surface precipitation, similar to temperature, has been compared with other hydrologic data, such as changes in stream flow, to ascertain the robustness of the documented changes of precipitation. Figure 1 summarizes some of the more important changes of precipitation, such as the increase in the mid to high latitude precipitation and the decrease in subtropical precipitation. Evidence also suggests that much of the increase of precipitation in mid to high latitudes arises from increased autumn and early winter precipitation in much of North America and Europe. Figure 2 depicts the spatial aspects of this change, reflecting rather large-scale coherent patterns of change during the twentieth century. Other changes related to the hydrologic cycle are summarized in Fig. 1. The confidence is low for many of the changes, and it is particularly disconcerting relative to the role of clouds and water vapor in climate feedback effects.∗ Observations of cloud amount long have been made by surface-based human observations and more recently by satellite. In the United States, however, human observers have been replaced by automated measurements, and neither surface-based or spaced-based data sets have proven to be entirely satisfactory for detecting changes in clouds. Polar orbiting satellites have an enormous difficulty to overcome related to sampling aliasing and satellite drift (12). For human observers changes in observer schedules, observing biases, and incomplete sampling have created major problems in data ∗ An enhancement or diminution of global temperature increases or decreases due to other causes.

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OBSERVATIONS OF CLIMATE AND GLOBAL CHANGE FROM REAL-TIME MEASUREMENTS Surface temperature indicators Ocean

Land

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* 1990s warmest decade and 1998 warmest year since instrument records began (1861) * 1990s warmest decade of the millennium and 1998 warmest year for at least the N. Hemisphere * N.Hemisphere warming for 20th Century greatest of past 10 centuries Since the retreat of the last glacial maximum (18,000 years ago): * Local changes > 3°C/10yr * Global increases ~ 2°C/1000yr ** N. Hemisphere snow cover extent: since 1987, ** Marine air temperature: 10% below 1973-86 mean 0.4 to 0.7°C increase since late 19th Century

*** Widespread retreat of mountain glaciers during 20th century

* Lake and river ice retreat since the late 19th century (nearly 2-weeks decrease in ice ** Sea surface temperature: duration) 0.4 to 0.8˚C increase *** Land air temperatures: 0.4 to 0.8˚C increase since the late 19th since late 19th century century. *** Reduction in freeze-free season over much of the mid-to-high-latitude region ** Land nighttime air temperature increases at twice the rate as daytime temperatures since 1950

Figure 1. Schematic of observed variations of selected indictors regarding (a) temperature and (b) the hydrologic cycle (based on Ref. 1).

interpretations, now compounded by a change to new automated measurements at many stations. Nonetheless, there is still some confidence (but low) that global cloud amounts have tended to increase. On a regional basis this is supported by reductions in evaporation as measured by pan evaporimeters over the past several decades in Russia and the United States, and a worldwide reduction in the land surface diurnal temperature range. Moreover, an increase in water vapor has been documented over much of North America and in the tropics (1). Changes in water vapor are very important for understanding climate change since water vapor is the most important greenhouse gas in the atmosphere. The measurement of changes in atmospheric water vapor is hampered by both data processing and instrumental difficulties for both weather balloon and satellite retrievals. The latter also suffers from discontinuities among successive satellites and errors introduced by changes in orbits and calibrations. Upper tropospheric water vapor is particularly important for climate feedbacks, but, as yet, little can be said about how it has varied over the course of the past few decades. IS THE ATMOSPHERIC/OCEANIC CIRCULATION CHANGING? Surprisingly, there is a considerable lack of reliable information about changes in atmospheric circulation,

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*** Virtually certain (probability > 99%) ** Very likely (probability > 90% but < 9%) * Likely (probability > 66% but < 90%) ? Uncertain (probability > 33% but < 66%)

even though it is of daily concern to much of the world since it relates to day-to-day weather changes. Analyses of circulation are performed every day on a routine basis, but the analysis schemes have changed over time, making them of limited use for monitoring climate change. Moreover, even the recent reanalysis efforts by the world’s major numerical weather prediction centers, whereby the analysis scheme is fixed over the historical record, contains time-varying biases because of the introduction of data with time-dependent biases and a changing mix of data (e.g., introducing satellite data) over the course of the reanalysis (13). Even less information is available on measured changes and variations in ocean circulation. A few major atmospheric circulation features have been reasonably well measured because they can be represented by rather simple indices. This includes the ˜ El Nino–Southern Oscillation (ENSO) index, the North Atlantic Oscillation (NAO) index, and the Pacific–North American (PNA) circulation pattern index. There are interesting decadal and multidecadal variation, but it is too early to detect any long-term trends. Evidence exists that ENSO has varied in period, recurrence interval, and strength of impact. A rather abrupt change in ENSO and other aspects of atmospheric circulation seems to have occurred around 1976–1977. More frequent ENSOs with rare excursions into its other extreme ˜ (La Nina) became much more prevalent. Anomalous circulation regimes associated with ENSO and largeamplitude PNA patterns persisted in the North Pacific

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Surface hydrological and storm-related indicators Land

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* N. Hemisphere oceans: 20th-Century increase in storm frequency/intensity and significant wave height

** No widespread changes in tropical storm frequency/intensity during the 20th century

** 5 to 10% increase in N. Hemisphere mid-to-high latitude precipitation since 1900, with much of it due to heavy and extreme precipitation events * Widespread significant increases in surface water vapor in the N.H., 1975–1995 ***

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Figure 2. Precipitation trends over land 1900–1999. Trend is expressed in percent per century (relative to the mean precipitation from 1961–1990) and magnitude of trend is represented by area of circle with green reflecting increases and brown decreases of precipitation.

from the late 1970s into the late 1980s, affecting temperature anomalies. Moreover, the NAO has been persistent in its association with strong westerlies into the European continent from the late 1980s until very recently when it abruptly shifted. As a result, temperature anomalies and storminess in Europe have abruptly changed over the past 2 years compared to the past 7 or 8 years. Increases in the strength of the Southern Hemisphere circumpolar vortex during the 1980s have been documented (14,15) using station sea level pressure data. This increase was associated with a delayed breakdown in the stratospheric polar vortex and ozone deficit in the Antarctic spring. A near-global sea level pressure data set has been used to identify changes in circulation patterns in the Indian Ocean. Allan et al. (16) and Salinger et al. (17) find that circulation patterns in the periods 1870–1900 and 1950–1990 were more meridional than those in the 1900–1950 period, indicating intensified circulation around anticyclones. These changes may be related to changes in the amplitude of longwave troughs to the south and west of Australia and the Tasman Sea/New Zealand area and a subsequent decrease in precipitation in Southwest Australia (18,19).

IS THE WEATHER AND CLIMATE BECOMING MORE EXTREME OR VARIABLE? Climate and weather extremes are of great interest. Due to inadequate monitoring as well as prohibitively expensive access to weather and climate data held by the world’s national weather and environmental agencies, only limited reliable information is available about large-scale changes in extreme weather or climate variability. The time-dependent biases that affect climate means are even more difficult to effectively eliminate from the extremes of the distributions of various weather and climate elements. There are a few areas, however, where regional and global changes in weather and climate extremes have been reasonably well documented (20). Interannual temperature variability has not changed significantly over the past century. On shorter time scales and higher frequencies, e.g., days to a week, temperature variability may have decreased across much of the Northern Hemisphere (8). Related to the decrease in high-frequency temperature variability there has been a tendency for fewer low-temperature extremes, but widespread changes in extreme high temperatures have not been noted. Trends in intense rainfall have been examined for a variety of countries. Some evidence suggests an increase in

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intense rainfalls (United States, tropical Australia, Japan, and Mexico), but analyses are far from complete and subject to many discontinuities in the record. The strongest increases in extreme precipitation are documented in the United States and Australia (21). Intense tropical cyclone activity may have decreased in the North Atlantic, the one basin with reasonably consistent tropical cyclone data over the twentieth century, but even here data prior to World War II is difficult to assess regarding tropical cyclone strength. Elsewhere, tropical cyclone data do not reveal any longterm trends, or if they do they are most likely a result of inconsistent analyses. Changes in meteorological assimilation schemes have complicated the interpretations of changes in extratropical cyclone frequency. In some regions, such as the North Atlantic, a clear trend in activity has been noted, as also in significant wave heights in the northern half of the North Atlantic. In contrast, decreases in storm frequency and wave heights have been noted in the south half of the North Atlantic over the past few decades. These changes are also reflected in the prolonged positive excursions of the NAO since the 1970s.

IS THE RADIATIVE FORCING OF THE PLANET CHANGING? Understanding requires a time history of forcing global change. The atmospheric concentration of CO2 , an important greenhouse gas because of its long atmospheric residence time and relatively high atmospheric concentration, has increased substantively over the past few decades. This is quite certain as revealed by precise measurements made at the South Pole and at Mauna Loa Observatory since the late 1950s, and from a number of stations distributed globally that began operating in subsequent decades. Since atmospheric carbon dioxide is a long-lived atmospheric constituent and it is well mixed in the atmosphere, a moderate number of well-placed stations operating for the primary purpose of monitoring seasonal to decadal changes provides a very robust estimate of global changes in carbon dioxide. To understand the causes of the increase of atmospheric carbon dioxide, the carbon cycle and the anthropogenic carbon budget must be balanced. Balancing the carbon budget requires estimates of the sources of carbon from anthropogenic emissions from fossil fuel and cement production, as well as the net emission from changes in land use (e.g., deforestation). These estimates are derived from a combination of modeling, sample measurements, and high-resolution satellite imagery. It also requires measurements for the storage in the atmosphere, the ocean uptake, and uptake by forest regrowth, the CO2 and nitrogen fertilization effect on vegetation, as well as any operating climate feedback effects (e.g., the increase in vegetation due to increased temperatures). Many of these factors are still uncertain because of a paucity of ecosystem measurements over a sustained period of time. Anthropogenic emissions from the burning of fossil fuel and cement production are the primary cause of the atmospheric increase.

Several other radiatively important anthropogenic atmospheric trace constituents have been measured for the past few decades. These measurements have confirmed significant increases in atmospheric concentrations of CH4 , N2 O, and the halocarbons including the stratospheric ozone destructive agent of the chloroflourocarbons and the bromocarbons. Because of their long lifetimes, a few wellplaced high-quality in situ stations have provided a good estimate of global change. Stratospheric ozone depletion has been monitored both by satellite and ozonesondes. Both observing systems have been crucial in ascertaining changes of stratospheric ozone that was originally of interest, not because of its role as a radiative forcing agent, but its ability to absorb ultraviolet (UV) radiation prior to reaching Earth’s surface. The combination of the surfaceand space-based observing systems has enabled much more precise measurements than either system could provide by itself. Over the past few years much of the ozonesonde data and satellite data has been improved using information about past calibration methods, in part because of differences in trends between the two observing systems. Figure 3 depicts the IPCC (9) best estimate of the radiative forcing associated with various atmospheric constituents. Unfortunately, measurements of most of the forcings other than those already discussed have low or very low confidence, not only because of our uncertainty about their role in the physical climate system, but because we have not adequately monitored their change. For example, estimates of changes in sulfate aerosol concentrations are derived from model estimates of source emissions, not actual atmospheric concentrations. The problem is complicated because of the spatially varying concentrations of sulfate due to its short atmospheric lifetime. Another example is measurements of solar irradiance, which have been taken by balloons and rockets for several decades, but continuous measurements of top-of-the-atmosphere solar irradiance did not begin until the late 1970s with the Nimbus

Trend (%/century) in annual precipitation 1900–1999 85N 55N 30N 10N 10S 30S 55S 85S −50% −40% −30% −20% −10% 0%

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Figure 3. Estimates of globally and annually averaged radiative forcing (in W/m−2 ) for a number of agents due to changes in concentrations of greenhouse gases and aerosols and natural changes in solar output from 1750 to the present day. Error bars are depicted for all forcings (from Ref. 1).

OBSERVATIONS OF CLIMATE AND GLOBAL CHANGE FROM REAL-TIME MEASUREMENTS

7 and the Solar Maximum Mission satellites. There are significant absolute differences in total irradiance between satellites, emphasizing the critical need for overlaps between satellites and absolute calibration of the irradiance measurements to determine decadal changes. Spectrally resolved measurements will be a key element in our ability to model the effects of solar variability, but at the present time no long-term commitment has been made to take these measurements. Another important forcing that is estimated through measured, modeled, and estimated changes in optical depth relates to the aerosols injected high into the atmosphere by major volcanic eruptions. The aerosols from these volcanoes are sporadic and usually persist in the atmosphere for at most a few years. Improved measurements of aerosol size distribution and composition will help better understand this agent of climate change. WHAT CAN WE DO TO IMPROVE OUR ABILITY TO DETECT CLIMATE AND GLOBAL CHANGE? Even after extensive reworking of past data, in many instances we are incapable of resolving important aspects concerning climate and global change. Virtually every monitoring system and data set requires better data quality, continuity, and fewer time-varying biases if we expect to conclusively answer questions about how the planet has changed, because of the need to rely on observations that were never intended to be used to monitor the physical characteristics of the planet of the course of decades. Long-term monitoring, capable of resolving decade-to-century-scale changes, requires different strategies of operation. In situ measurements are currently in a state of decay, decline, or rapid poorly documented change due to the introduction of automated measurements without adequate precaution to understand the difference between old and new observing systems. Satellite-based systems alone will not and cannot provide all the

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necessary measurements. Much wiser implementation and monitoring practices must be adopted for both spacebased and surface-based observing systems in order to adequately understand global change. The establishment of the Global Climate Observing System (GCOS) is a high priority (22), and continued encouragement by the World Meteorological Organization (WMO) of a full implementation of this system in all countries is critical. Furthermore, in the context of the GCOS, a number of steps can be taken to improve our ability to monitor climate and global change. These include: 1. Prior to implementing changes to existing environmental monitoring systems or introducing new observing systems, standard practice should include an assessment of the impact of these changes on our ability to monitor environmental variations and changes. 2. Overlapping measurements in time and space of both the old and new observing systems should be standard practice for critical environmental variables. 3. Calibration, validation, and knowledge of instrument, station, and/or platform history are essential for data interpretation and use. Changes in instrument sampling time, local environmental conditions, and any other factors pertinent to the interpretation of the observations and measurements should be recorded as a mandatory part of the observing routine and be archived with the original data. The algorithms used to process observations must be well documented and available to the scientific community. Documentation of changes and improvements in the algorithms should be carried along with the data throughout the data archiving process. 4. The capability must be established to routinely assess the quality and homogeneity of the historical

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Figure 4. Global, annual-mean radiative forcings (Wm−2 ) due to a number of agents for the period from pre-industrial (1750) to the present. The height of the vertical bar denotes the central or ‘‘best’’ estimate, no bar indicates that it is not possible to provide a ‘‘best’’ estimate. The vertical line indicates an estimate of the uncertainty range and the level of scientific understanding is a subjective judgement about the reliability of the forcing estimate based on such factors as assumptions, degree of knowledge of the physical/chemical mechanisms, etc. (From Ref. 1).

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5.

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database for monitoring environmental variations and change, including long-term high-resolution data capable of resolving important extreme environmental events. Environmental assessments that require knowledge of environmental variations and change should be well integrated into a global observing system strategy. Observations with a long uninterrupted record should be maintained. Every effort should be made to protect the data sets that document long-term homogeneous observations. Long term may be a century or more. A list of prioritized sites or observations based on their contribution to long-term environmental monitoring should be developed for each element. Data-poor regions, variables, regions sensitive to change, and key measurements with inadequate temporal resolution should be given the highest priority in the design and implementation of new environmental observing systems. Network designers, operators, and instrument engineers must be provided environmental monitoring requirements at the outset of network design. This is particularly important because most observing systems have been designed for purposes other than long-term monitoring. Instruments must have adequate accuracy with biases small enough to resolve environmental variations and changes of primary interest. Much of the development of new observation capabilities and much of the evidence supporting the value of these observations stem from researchoriented needs or programs. Stable, long-term commitments to these observations, and a clear transition plan from research to operations, are two requirements in the development of adequate environmental monitoring capabilities. Data management systems that facilitate access, use, and interpretation are essential. Freedom of access, low cost, mechanisms that facilitate use (directories, catalogs, browse capabilities, availability of metadata on station histories, algorithm accessibility and documentation, on-line accessibility to data, etc.), and quality control should guide data management. International cooperation is critical for successful management of data used to monitor long-term environmental change and variability.

BIBLIOGRAPHY 1. IPCC (2001). Climate Change, 2001: The Scientific Basis. Contribution of Working Group 1 to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, and C.A. Johnson (Eds.). Cambridge University Press, New York. 2. Spencer, R.W. and Christy, J.R. (1992). Precision and radiosonde validation of satellite gridpoint temperature anomalies, Part I: MSU channel 2. J. Climate 5: 847–857.

3. Spencer, R.W. and Christy, J.R. (1992). Precision and radiosonde validation of satellite gridpoint temperature anomalies, Part II: A tropospheric retrieval and trends during 1979–90. J. Climate 5: 858–866. 4. Reynolds, R.W. (1988). A real-time global sea surface temperature analysis. J. Climate 1: 75–86. 5. National Research Council (NRC) (2000). Reconciling Observations of Global Temperature Change, Report of the Panel on Reconciling Temperature Observations. National Academy Press, Washington, DC. 6. Luers, J.K. and Eskridge, R.E. (1995). Temperature corrections for the VIZ and Vaisala radiosondes. Appl. Meteor. 34: 1241–1253. 7. Sevruk, B. (1982). Methods of correcting for systematic error in point precipitation measurements for operational use. Hydrology Rep. 21. World Meteorological Organization, Geneva, 589. 8. Karl, T.R., Knight, R.W., and Plummer, N. (1995). Trends in high-frequency climate variability in the twentieth century. Nature 377: 217–220. 9. IPCC (1992). Climate Change, 1992, Supplementary Report, WMO/UNEP. J.T. Houghton, B.A. Callander, and S.K. Varney (Eds.). Cambridge University Press, New York, pp. 62–64. 10. Spencer, R.W. (1993). Global oceanic precipitation from the MSU during 1979–1992 and comparison to other climatologies. J. Climate 6: 1301–1326. 11. Huffman, G.J., Adler, R.F., Arkin, P., Chang, A., Ferraro, R., Gruber, A., Janowiak, J., McNab, A., Rudolf, B., and Schneider, U. (1997). The global precipitation climatology project (GPCP) combined precipitation dataset. Bull. Am. Meteor. Soc. 78: 5–20. 12. Rossow, W.B. and Cairns, B. (1995). Monitoring changes in clouds. Climatic Change 31: 175–217. 13. Trenberth, K.E. and Guillemot, C.J. (1997). Evaluation of the atmospheric moisture and hydrologic cycle in the NCEP reanalysis. Clim. Dyn. 14: 213–231. 14. van Loon, H., Kidson, J.W., and Mullan, A.B. (1993). Decadal variation of the annual cycle in the Australian dataset. J. Climate 6: 1227–1231. 15. Hurrell, J.W. and van Loon, H. (1994). A modulation of the atmospheric annual cycle in the Southern Hemisphere. Tellus 46A: 325–338. 16. Allan, R.J., Lindesay, J.A., and Reason, C.J.C. (1995). Multidecadal variability in the climate system over the Indian Ocean region during the austral summer. J. Climate 8: 1853–1873. 17. Salinger, M.J., Allan, R., Bindoff, N., Hannah, J., Lavery, B., Leleu, L., Lin, Z., Lindesay, J., MacVeigh, J.P., Nicholls, N., Plummer, N., and Torok, S. (1995). Observed variability and change in climate and sea level in Oceania. In: Greenhouse: Coping with Climate Change. W.J. Bouma, G.I. Pearman, and M.R. Manning (Eds.). CSIRO, Melbourne, Australia, 100–126. 18. Nicholls, N. and Lavery, B. (1992). Australian rainfall trends during the twentieth century. Int. J. Climatology 12: 153–163. 19. Allan, R.J. and Haylock, M.R. (1993). Circulation features associated with the winter rainfall decrease in southwestern Australia. J. Climate 6: 1356–1367. 20. Easterling, D.R., Meehl, G., Parmesan, C., Changnon, S., Karl, T., and Mearns, L. (2000). Climate extremes: observations, modeling, and impacts. Science 289: 2068–2074.

OVERVIEW: THE CLIMATE SYSTEM 21. Easterling, D.R., Evans, J.L., Groisman, P.Ya., Karl, T.R., Kunkel, K.E., and Ambenje, P. (2000). Observed variability and trends in extreme climate events: A brief review. Bull. Am. Meteor. Soc. 81: 417–426. 22. Spence, T. and Townsend, J. (1995). The Global Climate Observing System (GCOS). Climatic Change 31: 131–134.

READING LIST Elliott, W.P. (1995). On detecting long-term changes in atmospheric moisture. Climatic Change 31: 219–237. Groisman, P.Y., and Legates, D.R. (1995). Documenting and detecting long-term precipitation trends: Where we are and what should be done. Climatic Change 31: 471–492. Hurrell, J.W. and Trenberth, K.E. (1996). Satellite versus surface estimates of air temperature since 1979. J. Climate 9: 2222–2232.

OVERVIEW: THE CLIMATE SYSTEM ROBERT E. DICKINSON (from The Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical Meteorology, Weather Systems, and Measurements, Wiley 2003)

The climate system consists of the atmosphere, cryosphere, oceans, and land interacting through physical, chemical, and biological processes. Key ingredients are the hydrological and energy exchanges between subsystems through radiative, convective, and fluid dynamical mechanisms. Climate involves changes on seasonal, year-to-year, and decadal or longer periods in contrast to day-to-day weather changes. However, extreme events and other statistical measures are as, or more, important than simple averages. Climate is seen to impact human activities most directly through the occurrence of extremes. The frequency of particular threshold extremes, as, for example, the number of days with maximum temperatures above 100 ◦ F, can change substantially with shifts in climate averages.

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increases with altitude in the stratosphere in response to increasing heating per the unit mass by ozone absorption of ultraviolet radiation. The variation of temperature structure with latitude is indicated in Fig. 2. The troposphere is deepest in the tropics because most thunderstorms occur there. Because of this depth and stirring by thunderstorms, the coldest part of the atmosphere is the tropical tropopause. In the lower troposphere temperatures generally decrease from the equator to pole, but warmest temperatures shift toward the summer hemisphere, especially in July. Longitudinally averaged winds are shown in Fig. 3. Because of the geostrophic balance between wind and pressures, winds increase with altitude where temperature decreases with latitude. Conversely, above about 8 km, where temperatures decrease toward the tropical tropopause, the zonal winds decrease with altitude. The core of maximum winds is referred to as the jet stream. The jet stream undergoes large wavelike oscillations in longitude and so is usually stronger at a given latitude than in its longitudinal average. These waves are especially noticeable in the winter hemisphere as illustrated in Fig. 4. GLOBAL AVERAGE ENERGY BALANCE Solar radiation of about 342 W/m−2 entering Earth’s atmosphere is absorbed and scattered by molecules. The major gaseous absorbers of solar radiation are water vapor in the troposphere and ozone in the stratosphere. Clouds and aerosols likewise scatter and absorb. Clouds are the dominant scatterer and so substantially enhance the overall planetary reflected radiation, whose ratio to incident solar radiation, about 0.31, is referred to as albedo. Thermal infrared radiation, referred to as longwave, is controlled by clouds, water vapor, and other greenhouse gases. Figure 5 (4) illustrates a recent estimate of the various terms contributing to the global 120 Thermosphere

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THE ATMOSPHERE The atmosphere is described by winds, pressures, temperatures, and the distribution of various substances in gaseous, liquid, and solid forms. Water is the most important of these substances. Also important are the various other radiatively active (‘‘greenhouse’’) gases, including carbon dioxide and liquid or solid aerosol particulates. Most of the mass of the atmosphere is in the troposphere, which is comprised of the layers from the surface to about 12 km (8 km in high latitudes to 16 km at the equator) where the temperature decreases with altitude. The top of the troposphere is called the tropopause. Overlying this is the stratosphere, where temperatures increase with altitude to about 50 km or so (Fig. 1). The tropospheric temperature decreases with altitude are maintained by vertical mixing driven by moist and dry convection. The temperature

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energy balance. The latent heat from global average precipitation of about 1.0 m per year is the dominant nonradiative heating term in the atmosphere. Because of the seasonally varying geometry of Earth relative to the sun, and the differences in cloudiness and surface albedos, there are substantial variations in the distribution of absorbed solar radiation at the surface and in the atmosphere, as likewise in the transfer of latent heat from the surface to the atmosphere. This heterogeneous distribution of atmospheric heating drives atmospheric wind systems, either directly or through the creation of available potential energy, which is utilized to maintain random occurrences of various kinds of instabilities, such as thunder-storms and wintertime

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cyclonic storm systems. These dynamical systems hence act to redistribute energy within the atmosphere and so determine the distributions of temperature and water vapor. Likewise, the balances at the surface between fluxes of radiative, latent, and thermal energies determine surface temperatures and soil moistures. The properties of the near-surface air we live in are determined by a combination of surface and atmospheric properties, according to processes of the atmospheric boundary layer. Thus climatic anomalies in surface air may occur either because of some shift in atmospheric circulation patterns or through some modification of surface properties such as those accompanying deforestation or the development of an urban area.

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THE ATMOSPHERIC BOUNDARY LAYER The term boundary layer is applied in fluid dynamics to layers of fluid or gas, usually relatively thin, determining the transition between some boundary and the rest of the fluid. The atmospheric boundary layer is the extent of atmosphere that is mixed by convective and mechanical stirring originating at Earth’s surface. Such stirring is commonly experienced by airplane travelers as the bumps that occur during takeoff or landing, especially in the afternoon, or as waves at higher levels in flying over mountainous regions. The daytime continental boundary layer, extending up to several kilometers in height, is most developed and vigorously mixed, being the extent to which the daytime heating of the surface drives convective overturning of the atmosphere. The land cools radiatively at night, strongly stabilizing the atmosphere against convection, but a residual boundary layer extends up to about 100 m stirred by the flow of air over the underlying rough surface. This diurnal variation of fluxes over the ocean is much weaker and the boundary layer is of intermediate height. The temperature of the atmosphere, when stirred by dry mixing, decreases at a rate of 9.8 K/km. Above the boundary layer, temperatures decrease less rapidly with height, so that the atmosphere is stable to dry convection. A layer of clouds commonly forms at the top of the daytime and oceanic boundary layers and contributes to the convection creating the boundary layer through its radiative cooling (convection results from either heating at the bottom of a fluid or cooling at its top). Also, at times the clouds forming near the top of the boundary layer can be unstable to moist convection, and

Figure 4. Mean 500-mb contours in January, Northern Hemisphere. Heights shown in tens of meters (3).

so convect upward through a deep column such as in a thunderstorm. ATMOSPHERIC HYDROLOGICAL CYCLE The storage, transport, and phase changes of water at the surface and in the atmosphere are referred to as the hydrological cycle. As already alluded to, the hydrological cycle is closely linked to and driven by various energy exchange processes at the surface and in the atmosphere. On the scale of continents, water is moved from oceans to land by atmospheric winds, to be carried back to the oceans by streams and rivers as elements of the land hydrological cycle. Most of the water in the atmosphere is in its vapor phase, but water that is near saturation vapor pressure (relative humidity of 100%) converts to droplets or ice crystals depending on temperature and details of cloud physics. These droplets and crystals fall out of the atmosphere as precipitation. The water lost is replenished by evaporation of water at the surface and by vertical and horizontal transport within the atmosphere. Consequently, much of the troposphere has humidities not much below saturation. Saturation vapor pressure increases rapidly with temperature (about 10% per kelvin of change). Hence, as illustrated in Fig. 6, the climatological concentrations of water vapor vary from several percent or more when going from near-surface air to a few parts per million near the tropical tropopause. Water vapor concentrations in the stratosphere are close to that of the tropical tropopause, probably because much of the air in the lower stratosphere has been pumped through the tropical tropopause by moist convection.

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OVERVIEW: THE CLIMATE SYSTEM Reflected solar radiation 107 W m-2

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CLIMATE OF THE STRATOSPHERE The dominant radiative processes in the stratosphere are the heating by absorption of solar ultra violet (UV) radiation and cooling by thermal infrared emission from carbon dioxide and, to a lesser extent, ozone molecules. The stratospheric absorption of UV largely determines how much harmful UV reaches the surface. Ozone in the upper troposphere and lower stratosphere additionally adds heat by absorption of thermal emission from the warmer surface and lower layers. The stratosphere, furthermore, enhances the greenhouse warming of CO2 in the troposphere through substantial downward thermal emissions to the troposphere.

How changes of ozone change stratospheric and tropospheric radiative heating depends on the amounts of overlying ozone and, for thermal effect, on pressure and radiative upwelling depending on underlying temperatures. Besides radiative processes, stratospheric climate is characterized by its temperature and wind patterns and by the chemical composition of its trace gases. At midstratosphere, temperature increases from winter pole to summer pole with an accompanying eastward jet stream in the winter hemisphere extending upward from the tropospheric jet steam. This wind configuration allows planetary wave disturbances to propagate into the stratosphere, contributing significant temporal and longitudinal

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variabilities. Conversely, the westward jet, found in the summer stratosphere attenuates wave disturbances from below, and so is largely zonally symmetric, changing only with the seasonal heating patterns.

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4. Kiehl, J.T. and Trenberth, K.E. (1997). Earth’s annual global mean energy budget. J. Clim. 78: 197–208. 5. Peixoto, J.P. and Oort, A.H. (1992). Observed atmospheric branch of the hydrological cycle, Chapter 12.3. Physics of Climate. American Institute of Physics, New York.

THE CRYOSPHERE The term cryosphere refers to the components of the climate system dominated by water in its frozen phase, that is, in high latitudes and extratropical winter conditions. Elements include snow, its distribution and depths, sea ice, its distribution and properties, highlatitude ice caps, and temperate glaciers. The largest volume of frozen water is stored in ice caps, and glaciers. This storage acts to remove water from the oceans. How it changes with climate change is, hence, of interest for determining changing sea levels. Ice is highly reflective of sunlight, especially in crystal form. The loss of solar heating because of this high albedo acts to substantially reduce high-latitude temperatures especially in spring and early summer where near-maximum solar radiation sees white snow-covered surfaces. This high albedo can be substantially masked by cloud cover and, over land, tall vegetation such as conifer forests. THE OCEAN Oceans are a major factor in determining surface temperatures and fluxes of water into the atmosphere. They store, release, and transport thermal energy, in particular, warming the atmosphere under wintertime and high-latitude conditions, and cooling it under summer and tropical conditions. How the oceans carry out these services depends on processes coupling them to the atmosphere. Atmospheric winds push the oceans into wind-driven circulation systems. Net surface heating or cooling, evaporation, and precipitation determine oceanic densities through controlling temperature and salinity, hence oceanic buoyancy. This net distribution of buoyancy forcing drives ‘‘thermohaline’’ overturning of the ocean, which acts to transport heat. Climate of the surface layers of the ocean includes the depth to which waters are stirred by waves and net heating or cooling. Heating acts to generate shallow warm stable layers, while cooling deepens the surface mixed layers. Under some conditions, convective overturning of cold and/or high-salinity water can penetrate to near the ocean bottom. BIBLIOGRAPHY 1. Hartmann, D.L. (1994). Atmospheric temperature, Chapter 1.2. In: Global Physical Climatology. Academic Press, San Diego. 2. Grotjahn, R. (1993). Zonal average observations, Chapter 3. In: Global Atmospheric Circulations: Observations and Theories. Oxford University Press, New York. 3. Holton, J.R. (1992). The observed structure of extratropical circulations, Chapter 6.1. In: An Introduction to Dynamic Meteorology. Academic, San Diego.

CLIMATE AND SOCIETY MICHAEL H. GLANTZ (from The Handbook of Weather, Climate, and Water: Atmospheric Chemistry, Hydrology, and Societal Impacts, Wiley 2003)

At the turn of the twentieth century, scholars who wrote about the interplay between climate and society did so based on their perceptions of climate as a boundary constraint for the development prospects of a society. Perceptions of climate were used as an excuse to dominate societies in Africa, Asia, and Latin America. As a result, climate–society studies soon became viewed as a colonial ploy to control populations in developing areas in the tropics. Perhaps the most cited book in this regard was written by Ellsworth Huntington, Climate and Civilization, published in 1915 (1). In his view, inhabitants of the tropics were destined to accept lower levels of economic and social development because their climate setting was not conducive to lively (i.e., productive) human activity or an aggressive work ethic. According to Huntington, tropical climate was the main culprit causing people in the tropics to be less productive than people in temperate regions. Huntington argued that the temperate climate has an energizing effect on humans. With the growing belief that such an argument was racist in intent, Huntington’s work was challenged, and discussion of the various ways in which climate might influence human behavior was stifled for decades, notwithstanding a few notable exceptions. One such exception is entitled Climate and the Energy of Nations (2) in which Markham referred to the ‘‘air-conditioning revolution,’’ a revolution based on the development and spread of a new technology into the tropical areas. Markham asserted that technology brings islands of temperate-zone climate into the tropics, thereby generating a more aggressive work ethic. Following the end of World War II and the onset of the Cold War between Soviet-style communism and Western capitalism and democracy, attention of governments turned to Cold War conflicts, avoidance of nuclear war, searches for allies, and decolonization. The major Cold War nations were in a competition to show that their approach to economic development was the only way for the newly independent countries to follow. A main stated objective was their intent to assist these countries to become food secure based on the nation’s resources. Consideration of climate was making its way back into the discussions of economic development in developing countries. Once again interest was raised with regard to climatic constraints to economic development in tropical countries. In the 1950s and 1960s, attention focused on decolonization and political development of the newly

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independent states (e.g., 3). In the mid-1970s, a World Bank report about the economic prospects for developing countries—The Tropics and Economic Development: A Provocative Inquiry into the Poverty of Nations—hinted at the economic, social, and political problems caused by climate variability from one year to the next. Its author (4) noted that recurrent droughts in northeast Brazil are a chronic constraint on the region’s economic development prospects. His reference to interannual climate variability was brief and unelaborated. However, climate as a boundary constraint was starting to give way to climate as something that societies might be able to forecast and cope with, at least in its extremes. In the 1970s, attention focused on how the vagaries of weather exposed hundreds of millions of people to hunger and, depending on the socioeconomic situation in a particular country, to famine as well (e.g., 5,6). Thus, there was a growing number of examples of the notion that climate was not really a boundary constraint to the level of development that a people or culture could expect to attain. This notion began to give way to the belief that variability in climate, from one year to the next or one decade to the next, could be coped with so as to soften the impacts of climate variability and weather extremes on agriculture and livestock and, more generally, on the productivity of the land’s surface (e.g., 7,8). Recall that the 1970s was a disruptive decade with respect to climate: 5 years of drought in the West African Sahel (5); failure of the Soviet harvest and subsequent large-scale, low-cost grain purchases by the Soviet Union in the early 1970s (9); the global food crisis (10); talk of a possible return to an ice age (e.g., 11,12); the Ethiopian famine (13); drought-related coups in subSaharan Africa; drought in the wheat-producing Canadian prairie provinces (7); the first drop in global fish catches since the end of World War II (10), and so forth. A devastating 5-year drought from 1968 to 1973 in the West African Sahel and its associated death and environmental destruction in the region drew attention to the impacts on household and village responses to prolonged, multiyear droughts. Widespread droughts around the globe in 1972–1973, famines in West Africa and Ethiopia, ˜ event, along blamed for the most part on an El Nino with the drop in fish landings, prompted the U.N. Secretary General to convene a series of UN-sponsored world conferences on food (1974), population (1974), human settlements (1976), water (1977), desertification (1977), climate (1979) and technology (1979). Thus, toward the middle of the 1970s, at least five new major climate-related scientific issues emerged: the effect of chlorofluorocarbons (CFCs) on the ozone layer in the stratosphere, talk of an impending Ice Age suddenly shifted to talk of a human-induced global warming, acid ˜ Each of these issues rain, desertification, and El Nino. raised interest in climate–society interactions to higher levels among researchers in different disciplines, government agencies, economic sectors, the media, and the public. Societies around the globe responded (and continue to respond) in different ways to each of these climate-related issues. For example, desertification is an environmental issue that is of great concern to African countries.

North Americans, however, refused to accept the view that desertification could occur in the U.S. West as a result of mismanagement of the land’s surface, while noting that desertification was the plight of poor developing countries in Africa. The term desertification first appeared in a report on the destruction of dry forests in central Africa by a French forester (14). Since then, the concept of desertification has been expanded to include such land degradation processes as soil erosion, wind deflation, soil salinization, water logging, livestock overgrazing, and soil trampling. While many of these processes were exposed during the prolonged drought in the West African Sahel and then labeled as desertification, it is not difficult to show that similar processes also take place in the U.S. West. The acid rain issue was addressed in the United States with the implementation by the U.S. Congress of a decade-long national assessment called NAPAP (National Acid Precipitation Assessment Program). Stratospheric ozone depletion was addressed globally in the 1980s with the development of international legal instruments culminating in the Montreal Protocol of 1987 and, later, amendments to it (15). It was in the early 1970s, 1972–1973 to be exact, ˜ event (defined briefly as an invasion of that an El Nino warm water from the Western Pacific into the central and eastern equatorial Pacific Ocean) attracted global attention. An event in 1982–1983, the biggest in a century until that time, captured the full attention of the scientific community and various governments as a natural phenomenon that spawned hazards around the globe. Such hazards included, but were not limited to, droughts, floods, frosts, fires and food shortages, famine, and disease. Ever since the mid-1970s, research funding ˜ of El Nino–related research has been growing along with international interest in the phenomenon and its societal ˜ and environmental impacts. The extraordinary El Nino ˜ and its cold event of 1997–1998 helped to make El Nino ˜ household words throughout much counterpart, La Nina, of the world. Only at the end of the twentieth century ˜ events become of serious interest to the did La Nina ˜ research and forecasting communities (16). This El Nino belated interest is even more surprising given the scientific observation that tropical storms and hurricanes in the Atlantic Basin and in the Gulf of Mexico tend to increase ˜ events and drop in number in number during La Nina ˜ events. during El Nino Global warming is an environmental issue that arose out of discussions and governmental and scientific concerns about the possibility of a global cooling. It was first suggested in 1896 by Swedish chemist Arrhenius (17,18) that the burning of coal by human societies would add enough extra carbon dioxide into the air to eventually heat up Earth’s atmosphere by a few degrees Celsius. This issue was revisited in the 1930s by Callendar (19), who thought that a human-induced global warming of the atmosphere could stave off the imminent recurrence of an ice age. The issue was again revisited in the 1950s when global warming was looked at in neutral terms, as an experiment that societies were performing on the chemistry of the atmosphere, for which the outcome is unknown (20).

CLIMATE AND SOCIETY

It was not until the mid-1970s that human-induced global warming began to be viewed as an adverse event for future generations of human societies and ecosystems that might not be able to adapt to the rate of warming expected to occur. The cause of the warming was attributed to the increasing amounts of greenhouse gases (CO2 , CFCs, CH4 , NOx , collectively referred to as GHGs) being emitted into the atmosphere as a result of human activities. Carbon dioxide is a product of the burning of fossil fuels, and its amount in the atmosphere has been rising since the onset of the Industrial Revolution in the late 1700s. Tropical deforestation also contributes carbon dioxide to the atmosphere. Tropical forests have served as sinks for carbon dioxide, pulling it out of the air and storing it. When trees are felled, decompose or burned, the stored carbon is emitted into the air. Chlorofluorocarbons (CFCs), a greenhouse gas as well as a stratospheric ‘‘ozone eater,’’ are man-made chemicals first discovered in the 1920s for use as a refrigerant. Methane resulting from livestock rearing (e.g., cattle, pigs) and from the increasing number of landfills is another greenhouse gas. Nitrous oxides are used by farmers in fertilizers and have been widely applied to agricultural lands around the globe in increasing amounts since the end of World War II. Of these major greenhouse gases, carbon dioxide is seen at the main culprit in the global warming debate. Current scientific research suggests that the level of climate change that might be expected (at current rates of greenhouse gas emissions) is on the order of 1.5 to 4.5 ◦ C by the end of the twenty-first century (21–23). Concerned with the prospects of a changing global climate, many nations have come together to call for a technical assessment of the state of the science through the Intergovernmental Panel on Climate Change (IPCC). The degree of warming, however, is dependent on numerous factors: the rate at which GHGs continue to be emitted into the atmosphere, the shift by societies to alternative energy sources, the rate of tropical deforestation, the residence time of GHGs in the atmosphere (several of these gases will remain in the atmosphere for decades to centuries), the development of methods to sequester carbon (i.e., taking it from the atmosphere and binding it in some way in Earth’s land surface, vegetation, or oceans), and so forth. Some degree of global warming is inevitable, given the residence time of the GHGs already emitted into the atmosphere. This means that societies around the globe, from local to national, must attempt to ascertain how a warmer global climate regime might affect regional and local climates. Will there be more extreme climate events (such as droughts, floods, frosts, fires) or fewer? These societies must also seriously consider nationally, as well as collectively in cooperation with other countries, the most effective way(s) to cope with the potentially adverse impacts of some degree of human-induced global warming. Coping mechanisms for climate change likely to occur decades in the future can be divided into three categories: preventive, mitigative and adaptive measures. Preventive measures are designed to prevent the increased buildup of GHGs in human-induced global warming, acid rain,

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˜ Each of these issues raised desertification, and El Nino. interest in climate–society interactions to higher levels among researchers in different disciplines, government agencies, economic sectors, the media, and the public. Societies around the globe responded (and continue to respond) in different ways to each of these climate-related issues. For example, desertification is an environmental issue that is of great concern to African countries. Climate-related surprise is not a black-and-white condition. People are hardly ever either totally surprised or never surprised. There are shades of surprise with regard to human responses to the same climate-related event. They can be hardly surprised, mildly surprised, somewhat surprised, very surprised, extremely surprised or totally surprised (NB: each of these examples was taken from the scientific literature). Myers (24, p. 358) introduced the interesting notion of ‘‘semisurprised.’’ Thus, surprise may best be described in ‘‘fuzzy’’ terms with the degree of surprise dependent on several intervening variables such as personal experience, core beliefs, expectations, or knowledge about a phenomenon or about a geographic location. One could argue that there are knowable as well as unknowable surprises (25). Knowable refers to the fact that some climate surprises can be anticipated (24). For example, certain parts of the globe are drought prone. It is known that drought will likely recur. What is not known is exactly when it will take place, how long it will last, how intense it will be, or where its most devastating impacts ˜ is in this category. While we are likely to occur. El Nino have now come to expect these events to recur, we do not know when that will happen or what it will be like. The uncertainty then cascades down the ‘‘impacts chain,’’ and ˜ the as we speculate about likely impacts of an El Nino, degree of uncertainty will increase. ˜ Even with Take, for example, the 1997–1998 El Nino. the best monitoring and observing system in the world focused on minute changes in various aspects of the tropical Pacific Ocean, forecasters and modelers were unable to predict the onset of one of the biggest El ˜ events in the past 100 years. Nor were they able Nino to predict the course of development of that event. They were better than in earlier times, however, at predicting some of its impacts on societies in certain parts of the globe, especially those where the influences of changes in the sea surface temperatures in the tropical Pacific are known to be strong. Societies (and their scientists) are on a learning curve with regard to the various ways that climate variability and climate change might affect climate-related human activities. They must avoid becoming complacent as a result of a belief that they fully understand atmospheric processes or their impacts. They must accept that there will be climate surprises in the future, even if the global climate does not change. They must learn from past experiences on how best to cope with the vagaries of climate (26). Many countries now realize that climate-related problems do not stop at international boundaries. There are many transboundary issues that demand regional (if not international) cooperation, given that countries share river basins, inland seas, airsheds, the global

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atmosphere as well as the onslaught and impacts of extreme meteorological events such as droughts, floods, and tropical storms. While climate-related anomalies cannot be prevented, societal preparation for, and response to, their adverse impacts can be improved through better knowledge of the direct and indirect ways in which atmospheric processes interact with human activities and ecological processes. The enhancement of such knowledge will lead to better forecasts as well as better computer modeling of the interactions among land, sea, and air. A society forewarned of climate-related hazards is forearmed to cope with those hazards more effectively. BIBLIOGRAPHY 1. Huntington, E. Civilization and Climate. Yale University Press, New Haven, Connecticut, 1915, rev, ed. 1924, reprinted by University Press of the Pacific, 2001. 2. Markham, S.F. (1944). Climate and the Energy of Nations. Oxford University Press, London. 3. Pye, L. (1966). Aspects of Political Development. Little, Brown and Co., Boston, Massachusetts. 4. Kamarck, A.M. (1976). The Tropics and Economic Development: A Provocative Inquiry into the Poverty of Nations. The Johns Hopkins University Press, Baltimore, Maryland. 5. Glantz, M.H. (Ed.). (1976). The Politics of Natural Disaster: The Case of the Sahel Drought. Praeger Press, New York. 6. Sen, A. (1981). Poverty and Famines: An Essay on Entitlement and Deprivation. Oxford University Press, Oxford, UK. 7. Glantz, M.H. (Ed.). (1977). Desertification: Environmental Degradation in and around Arid Lands. Westview Press, Boulder, Colorado. 8. Hare, K. (1977). Connections between climate and desertification. Environ. Conserv. 4(2): 82. 9. Trager. (1975). 10. Brown, L., and Eckholm, E.P. (1974). By Bread Alone. Praeger Press, New York. 11. Ponte, L. (1976). The Cooling. Prentice-Hall, Inc., Englewood Cliffs, New Jersey. 12. Weather Conspiracy: The Coming of the New Ice Age, Ballentine Books, New York, compiled by The Impact Team, 1977. 13. Wolde Mariam, M. (1984). Rural Vulnerability to Famine in Ethiopia, 195777, Vikas Publishing House, New Delhi. 14. Aubreville, A. (1949). Climate, Forests and Desertification in Tropical Africa, Soci´ete d’Editions G´eographiques, Maritimes et Coloniales. 15. Benedick, R.E. (1998). Ozone Diplomacy: New Directions in Safeguarding the Planet. Harvard University Press, Cambridge, Massachusetts, Enlarged Edition. 16. Glantz, M.H. (Ed.). (2002). La Nina ˜ and Its Impacts: Facts and Speculation. United Nations University Press, Tokyo, Japan. 17. Arrhenius, S. (1896). On the influence of carbonic acid in the air upon the temperature of the ground. Philos. Mag. 41: 237–276. 18. Arrhenius, S. (1908). Worlds in the Making. Harper & Brothers, New York. 19. Callendar, G.S. (1938). The artificial production of carbon dioxide and its influence on temperatures. Q. J. Roy. Meteor. Soc. 64: 223–237.

20. Revelle, R.R., and Suess, H.E. (1957). Carbon dioxide exchange between atmosphere and ocean and the question of an increase of atmospheric CO2 during the past decades. Tellus 9: 18–27. 21. IPCC (1990). Climate Change: The IPCC Scientific Assessment. Cambridge University Press, Cambridge, UK. 22. IPCC (1996). Climate Change 1995: The Science of Climate Change, Contribution of Working Group I to Second Assessment Report, Cambridge University Press, Cambridge, UK. 23. IPCC (Intergovernmental Panel on Climate Change). (2001). Climate Change 2001: Impacts, Adaptation, and Vulnerability, Contribution of Working Group II to Third Assessment Report, Cambridge University Press, Cambridge, UK. 24. Myers, N. (1995). Environmental unknowns. Science 269: 358–360. 25. Streets, D.G., and Glantz, M.H. (2000). Exploring the concept of climate surprise. Global Environ. Chang. 10: 97–107. 26. Glantz, M.H. (Ed.). (1988). Societal Responses to Regional Climatic Change: Forecasting by Analogy. Westview Special Study, Boulder, Colorado.

READING LIST Smith, J.B., Bhatti, N., Menzhulin, G., Benioff, R., Bodyko, M.I., Campos, M., Jallow, B., and Rijsberman, F. (Eds.). (1996). Adapting to Climate Change: An International Perspective. Springer-Verlag, New York.

WHAT IS CLIMATOLOGY? National Drought Mitigation Center

‘‘CLIMATE IS WHAT YOU EXPECT. WEATHER IS WHAT YOU GET.’’ Weather is the condition of the atmosphere over a brief period of time. For example, we speak of today’s weather or the weather this week. Climate represents the composite of day-to-day weather over a longer period of time. People in Minneapolis–St. Paul expect a white Christmas, and people in New Orleans expect very warm, humid summers. And a traveler going to Orlando, Florida, in March will not pack the same kind of clothing as a traveler going to Vail, Colorado, in March. These examples show how climate influences our daily lives. Additionally: • Our houses are designed based on the climate where we live. • Farmers make plans based on the length of the growing season from the last killing freeze in the spring to the first freeze in the fall. • Utility companies base power supplies on what they expect to be the maximum need for heating in the winter and the maximum need for cooling in the summer. This article is a US Government work and, as such, is in the public domain in the United States of America.

CLOUD SEEDING

A climatologist attempts to discover and explain the impacts of climate so that society can plan its activities, design its buildings and infrastructure, and anticipate the effects of adverse conditions. Although climate is not weather, it is defined by the same terms, such as temperature, precipitation, wind, and solar radiation. Climate is usually defined by what is expected or ‘‘normal’’, which climatologists traditionally interpret as the 30-year mean. By itself, ‘‘normal’’ can be misleading unless we also understand the concept of variability. For example, many people consider sunny, idyllic days normal in southern California. History and climatology tell us that this is not the full story. Although sunny weather is frequently associated with southern California, severe floods have had a significant impact there, including major floods in 1862 and 1868, shortly after California became a state. When you also factor in severe droughts, most recently those of 1987–94, a more correct statement would be that precipitation in southern California is highly variable, and that rain is most likely between October and April. The misconception that weather is usually normal becomes a serious problem when you consider that weather, in one form or another, is the source of water for irrigation, drinking, power supply, industry, wildlife habitat, and other uses. To ensure that our water supply, livelihoods, and lives are secure, it is essential that planners anticipate variation in weather, and that they recognize that drought and flood are both inevitable parts of the normal range of weather. HOW DOES CLIMATOLOGY HELP US PREPARE FOR DROUGHT? Climatology provides benchmarks, such as the drought of record. The drought of record is the drought remembered as having the greatest impact on a region. Most of us are not consciously aware of how much the climate fluctuates from one decade or century to the next. One way for reservoir managers, municipal water suppliers, and other planners to check reality is to compare expectations of water supply against a region’s drought of record. But caution is necessary here: although the weather conditions could recur, the impacts would likely be very different. For most of the country, the drought of record was 30 to 60 years ago, and population concentrations and water use patterns have shifted substantially since then. Planners need to consider and watch out for a variety of problems and misconceptions. Specifically, climatology answers crucial questions such as: • • • •

How often does drought occur in this region? How severe have the droughts been? How widespread have the droughts been? How long have the droughts lasted?

Examining water supplies and understanding the impact of past droughts help planners anticipate the effects of drought:

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• What would happen if the drought of record occurred here now? • Who are the major water users in the community, state, or region? • Where does our water supply come from and how would the supplies be affected by a drought of record? • What hydrological, agricultural, and socioeconomic impacts have been associated with the various droughts? • How can we prepare for the next drought of record?

CLOUD SEEDING ARTHUR M. HOLST Philadelphia Water Department Philadelphia, Pennsylvania

Cloud seeding is the deliberate treatment of certain clouds or cloud systems to affect the precipitation process within those clouds. The treating of clouds can alter weather conditions, thus cloud seeding is also called weather modification. The technology that led to cloud seeding has been developed only during the past 60 years. Yet as this technology becomes more efficient, increased worldwide application of cloud seeding for practical use is likely to continue into the future. THE CLOUD SEEDING PROCESS To understand how cloud seeding works, one must understand some facts about the weather. All air in the atmosphere contains moisture. Warm air rises from the earth’s surface and begins to cool. As the air cools, the moisture condenses into tiny droplets that make up clouds. A cloud is almost 100% air. The tiny droplets composing clouds are not heavy enough to fall to the ground until they merge with millions of other droplets at temperatures below 32 ◦ F and interact with dust, salt, or sand particles. One type of cloud seeding, known as cold cloud seeding, introduces silver iodide and other agents to enhance ice crystallization in clouds colder than 32 ◦ F. This is often called as the static seeding effect. Once the droplets within the clouds freeze, the resulting ice crystals grow at the expense of the water droplets surrounding them, a process called sublimation. Other crystals grow through contact with neighboring droplets; this is known as riming. Through these two processes, the tiny crystals form snowflakes. If these snowflakes are heavy enough, they fall from the clouds and, depending on the temperatures below, will come to the earth as snow, raindrops, or a mixture. The other type of cloud seeding, warm cloud seeding, produces rainfall from clouds that are above 32 ◦ F. This process involves introducing additional condensation nuclei (salt particles), which cause additional water droplets to condense within the clouds. If the collision of these particles makes the droplets heavy enough, precipitation can fall from the clouds. In each case, it will usually take the clouds 20 to 30 minutes to produce rain, making it crucial to monitor cloud movement.

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CONDENSATION

USES OF WEATHER MODIFICATION The primary goal of most weather modification projects is to increase levels of precipitation or to suppress fog or hail. Water agencies, local municipalities, farmers, ranchers, hydroelectric power facility operators, ski resort owners, and others sponsor cloud seeding activities. To date, cloud seeding has successfully stimulated precipitation in more than 50 countries. More than half of the United States now has some type of regulation concerning cloud seeding programs. More recently, cloud seeding has been used to suppress certain damaging effects of weather. Airports have employed programs to disperse fog levels and increase flight visibility. And in areas damaged by hail, programs have been undertaken to decrease hailstorms. As technology continues to enhance the weather modification process, it can be assumed that more entities will sponsor cloud seeding programs. Cloud seeding technology is highly portable and very flexible to changing weather conditions. For those who use it, cost/benefit ratios are typically very favorable.

still contain only about 3% of the moisture, leaving 97% available. Furthermore, some analyses of precipitation data downwind from seeding projects have indicated small increases in precipitation. To date, no scientific studies have shown that some areas receive precipitation at the expense of their neighbors. FUTURE OF CLOUD SEEDING Despite all of the advances made during the past 60 years, weather modification continues to receive relatively little support. Many states and the federal government acknowledge and regulate cloud seeding, but few provide significant funding for weather modification studies or projects. Most scientists insist that more research must be done and more data must be gathered before weatherchanging programs garner public trust on a larger scale. However, most researchers are optimistic that new studies and technological advances will continue to advance the science of weather modification. READING LIST

EFFECTIVENESS OF CLOUD SEEDING From the earliest experiment, which produced just a few droplets of rain, cloud seeding has progressed to make some significant and valuable impacts on weather. Various studies have documented the effects of different programs. For the most part, these programs are overwhelmingly successful. To augment precipitation, well-designed and well-conducted projects yield an average winter precipitation of 5 to 20% more in continental regions and 5 to 30% more in coastal areas; they have yielded as much as 100% more in warm weather. Increases depend on a variety of factors, including spatial coverage of suitable cloud systems and the frequency of different systems. ENVIRONMENTAL HEALTH CONCERNS OF WEATHER MODIFICATION To date, no significant environmental problems have been attributed to cloud seeding programs, though government agencies, private firms, and research institutions have conducted many studies. Researchers believe that any negative effects are minimal because relatively little seeding material is used compared to the large surface area that is targeted. For example, the most common seeding material, silver iodide, will yield a concentration of less than 0.1 microgram per liter in rainwater or snow. The U.S. Public Health Service states that the acceptable amount of silver iodide in water is 50 micrograms per liter. One other common question about cloud seeding is whether the stimulation of rainfall in one area results in decreased rainfall in other areas. It does not. Clouds are inefficient in the way they gather and distribute moisture. They never gather or release all the moisture that is available; rather, clouds gather only about 1% of the moisture in the atmosphere. Even if a seeding program tripled the efficiency of cloud formation, the cloud would

American Society of Civil Engineers. (1995). Guidelines for Cloud Seeding to Augment Precipitation. ASCE Manuals and Reports on Engineering Practice No. 81. Stauffer, N.E. and Williams, K. (2000). Utah Cloud Seeding Program, Increased Runoff/Cost Analysis. Technical Report, Utah Department of Natural Resources, Division of Water Resources. Weather Modification Advisory Board. (1978). The Management of Weather Resources. Report to the Secretary of Commerce, 2 volumes. Klien, D.A. (1978). Environmental Impacts of Artificial Ice Nucleating Agents. Dowden, Hutchinson & Ross, Inc., Stroudsburg, PA. Brown, K.J., Elliot, R.D., and Edelstein, M.W. (1978). Transactions of Total-Area Effects of Weather Modification. Report to the National Science Foundation on a workshop held August 8–12, 1977, Fort Collins, CO. Cloud Seeding (Weather Modification) Frequently Asked Questions—http://www.xmission.com/∼nawc/wmfaq.html. The Science of Cloud Seeding—http://twri.tamu.edu/twripubs/ WtrResrc/v20n2/text-1.htm. Cloud Seeding Circus.com—www.cloudseedingcircus.com. Al Weather Modification Page—www.atmos-inc.com/weamod. html.

CONDENSATION ALDO CONTI Frascati (RM), Italy

Condensation is the physical process by which a vapor changes to its liquid state. Condensation happens when the temperature of the vapor decreases below the so-called dew point. In physics, this sort of process is called a phase change because the matter involved changes its state (i.e., from gaseous to liquid, in this case). Water condensation

COSMIC WATER

is evident in our atmosphere; it produces fog, mist, dew, clouds, and rain, depending on the conditions. It can be seen on a cold sheet of glass, where condensed water forms a maze of droplets. Condensation depends mainly on temperature, and it is a process that happens at the molecular level. When the temperature is high, the molecules in a vapor have plenty of energy and collide at high speed, which means that the molecules bounce immediately and do not stay together long enough to establish a bond. In this situation, the vapor remains. But when the temperature, and therefore the speed, decreases, then the molecules can stick to each other. The result is a droplet of liquid. Condensation is ruled not only by temperature, but by pressure as well, which is the reason why one speaks about dew point and not dew temperature. As a general rule, the dew point temperature increases with pressure. Condensation, with evaporation, is very important in the water cycle of the earth. By condensation, water falls back as rain, hail, or snow and becomes available again for human use.

COSMIC WATER D.L. MARRIN Hanalei, Hawaii

Once believed by science to be the substance that distinguished the earth from the rest of the universe, it is now understood that water is ubiquitous in the cosmos—not only as ice and vapor, but also as liquid. Sophisticated scientific instruments can detect cosmic water on the basis of the light, or other electromagnetic, waves that it absorbs and emits (1). Unlike the legendary ‘‘waters of chaos’’ that gave rise to the material world, water’s component hydrogen and oxygen atoms owe their existence to the Big Bang and to the stars, respectively. HYDROGEN AND OXYGEN Hydrogen is both the simplest and the most abundant atom in the universe. It represents about 75% of the atomic mass in the cosmos. The word hydrogen literally means ‘‘water-forming’’ according to the Greek language from which it is derived. Hydrogen atoms are generally traced back to the so-called Big Bang, when a tremendous amount of energy was released and subsequently expanded into what we call our universe. As the newborn universe began to cool, subatomic and atomic particles (e.g., quarks, protons, electrons) were initially created and later drawn together by a number of fundamental forces to form atoms. Possessing one proton and one electron, hydrogen is believed to have been the first atom created. As more hydrogen atoms were created in the early universe, they coalesced into dense gas clouds that contained much of the conventional matter. Oxygen is the third most abundant atom in the cosmos—behind hydrogen and helium. Because helium is a very inert (nonreactive) atom, water is sometimes

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described as an interaction between the two most abundant ‘‘reactive’’ atoms in the cosmos. Unlike hydrogen, the origins of the oxygen atom are rooted in dying stars rather than in the Big Bang. As stars near the end of their stellar life, they begin to cool and to switch from hydrogen to helium as a source for nuclear fusion. The cooling stars then enter a phase where they become increasingly dense as intense gravitational energy compresses them into an extremely unstable state that may explode during the final stages of compression (2). This explosion or supernova releases the outer layer of the star, which contains many common heavier atoms (e.g., oxygen, carbon), into space as interstellar clouds. Dust grains comprising these clouds are composed of both silicate (oxygen-rich) and carbonaceous (carbon-rich) minerals that are available to react with hydrogen (1).

INTERSTELLAR SPACE In the interstellar realms of galaxies, water exists predominantly as ice—adhering to the tiny particles that comprise the ubiquitous dust and gas clouds. Water is the primary molecular ice attached to these particles, although methane, carbon monoxide, and water–ammonia mixtures may also be present depending on physical conditions in the gas clouds (3). Water ice in the 10 K temperatures and vacuum conditions of interstellar space is what physical chemists refer to as amorphous ice or glassy water; it is relatively unstructured compared to the highly crystalline ices that are formed at higher temperatures (e.g., those characteristic of the earth’s surface and atmosphere). Amorphous ice is so unstructured that it can flow, not unlike a viscous version of liquid water (4). Some astrophysicists posit that the simple organic molecules responsible for biological life may have been created in this strange ice (4). As interstellar temperatures rise above 150 K (as often occurs near stars), amorphous ice irreversibly transits to more familiar crystalline ice. The various phases and molecular structures of water as a function of temperature are shown in Table 1. Although water’s component atoms are plentiful in interstellar dust and gas clouds, creation of molecular water requires either converting O and OH species directly to water ice on the surfaces of dust grains or producing water vapor via heat energy—usually in the form of stellar radiation (5). The latter process requires that water vapor adhere to dust grains, where the newly formed water molecule is protected from the same ionizing radiation that created it. Scientists currently believe that stars facilitate the creation of water vapor and also that water vapor assists in the birthing of stars. Stars are being born and are dying on an ongoing basis, such that star birthing regions (e.g., the Orion Cloud Complex of the Milky Way Galaxy) generate up to 20% of a galaxy’s luminosity as gas and dust clouds are gravitationally compressed into newborn stars. Recent data indicate that these cloud complexes contain an extremely high concentration of water vapor, which has been estimated of the order of 1 part in 2000 (6). The superabundance of water in stellar nurseries (about 20 times greater than that in similar interstellar clouds)

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COSMIC WATER Table 1. Representative Temperature Ranges and Cosmic Locations for the Three Phases of Water

Location

Temperature, Ka

Phase

Stellar surfaces

4000 to 50,000

None

Stellar/planetoid surfaces

100

Solid (crystalline)

Interstellar space

10 to 150

Solid (amorphous)

Comments Water molecules do not exist. Only hydrogen and oxygen atoms or plasma. Water exists at the surface of cool stars and in cooler regions of some hot stars. Few places in the cosmos possess the requisite temperatures and pressures. Crystalline ices possess both a cubic and a more common hexagonal structure. The depths of interstellar space are cold enough to produce glassy water.

a These temperatures, which are measured on the Kelvin scale, are only approximate and vary depending on environmental conditions (e.g., pressure, rate of cooling or heating).

may permit the gas and dust to cool sufficiently so that condensation can proceed and stars are eventually formed. As hot winds (in the form of shock waves) are sent out during stellar birthing, the cloud must be cooled—initially by molecular hydrogen and subsequently by water and other simple gases (7). Water vapor is created during the interstellar cloud shocks as oxygen reacts explosively with hydrogen, causing the water vapor concentration to increase substantially during star birthing. Scientists have theorized one of two eventual fates for water created in star birthing. One is that the intense heat of the fledgling star rapidly dissociates water into its component atoms. The other is that the water is deposited on dust grains that later form the star’s planetoids. The origin of earthly water is usually attributed to either this second process or the impact of large comets, which are believed to have been more prevalent during the earth’s early history. STARS Two of the brightest supergiants in our galaxy, Betelgeuse and Antares, have water in their photospheres, which constitutes the visible portion of a star (8). A star’s photosphere is where its gases transit from opaque to transparent, permitting us to see the stars that are located closest to the earth. This stellar water is actually present within the star itself, not simply as a component of the surrounding dust and gas cloud from which the star was birthed. Aging supergiant stars release massive amounts of water as they die; however, the exact source and role of this water are not yet known. In addition to cool stars, water has been discovered in the photosphere of at least one hot or main sequence star—the Sun. Water cannot exist on the surface of the Sun, where temperatures of 6000 K dissociate the water molecule into its component hydrogen and oxygen atoms. Water can exist in the dark centers of sunspots, where temperatures are less than 3500 K (9). Sunspots are relatively calm solar regions where strong magnetic fields filter out the energy emanating from the intense interior, rendering them both the coolest and darkest regions of the Sun. Water is a major player in determining a star’s radiative opacity, which describes the extent to which light escapes from stars into interstellar space (10).

In this role, water impedes the outward flow of radiation from stars by absorbing energy within certain wavelengths and, thus, renders the star more opaque than it would otherwise appear.

COMETS AND METEORS Comets are one of the few interstellar objects that are commonly associated with water, predominantly as ice. Comets are composed primarily of water ice that incorporates many of the other simple molecules in interstellar dust and gas clouds (e.g., carbon monoxide, methane, ammonia). Comets are most easily recognized by their unmistakable tails, which can extend millions to hundreds of millions of kilometers behind the icy body of the comet. The tail consists of dust and ionized particles (mostly water ice) that are always transported away from the Sun by the solar wind, which is an ionized stream of particles consisting predominantly of protons and electrons. The ionization of water ices is the primary mechanism influencing the properties of a comet’s tail, including the steam jets that release tons of water vapor per second from the comet. It is now believed that these steam jets result from solar-induced changes in ice’s molecular geometry (e.g., a transition from the amorphous to crystalline structure). Large comets are generally accepted as a source of planetary water, but controversy surrounds the hypothesis that many small comets hitting the planet’s upper atmosphere also contribute significantly to the volume of water on the earth. The first liquid water in the solar system, it was projected, made its appearance on meteors just 20 million years after our Sun and its debris emerged from the interstellar dust and gas cloud (11). Although liquid water is rarely present on the surface of meteors today, the chemical interaction of water with primitive rocks produced carbonate minerals, suggesting that the chemical processes of water evaporation and condensation were among the earliest in the solar system. Recently, a small meteorite found in southwestern North America contained actual liquid water within its salt crystals, which were believed to have been created from the original interstellar cloud that gave rise to the solar system.

THE WATER CYCLE

PLANETOIDS Most planet-sized bodies in our solar system (and probably in others) are now known or suspected to contain water in some form. A number of recent missions have revealed a Martian landscape that almost certainly indicates the large-scale flow of liquid water. The surface features of Mars (e.g., flood plains, river beds, mud deposits) suggest the recent presence of liquid water and also the mineralogy of Martian rocks could have resulted only from aqueous processes. Moreover, it has been hypothesized that Mars may have also once possessed surface oceans. The Jovian moon, Europa, is another of the solar system planetoids that probably contains liquid water located tens of kilometers beneath its icy surface. The liquid water underlying Europa’s surface ice is believed to be an ocean containing saltwater that may be similar in composition to the seawater of the earth’s oceans. Unlike the earth, the heat required to maintain water in a liquid phase on Europa is believed to originate from an internal source such as volcanic activity rather than from the heat of the Sun. Data collected from the Infrared Space Observatory indicate the presence of water in the upper atmospheres of our solar system’s gas giant planets and on one of Saturn’s moons (1). The source of water in these planet’s atmospheres is attributed to comets or to water-containing interplanetary dust. Based on recently developed techniques for measuring a suite of stellar characteristics (e.g., orbital velocity, position, brightness), the search for planets has been extended beyond our solar system to other star systems in the galaxy (12). Various planets have been identified orbiting stars in the constellations of Leo, Pegasus, Virgo, and Ursa Major that probably possess surface temperatures ranging from slightly less than 100 ◦ C down to −100 ◦ C. Planets or moons characterized by this temperature range could possess water in solid, gaseous, and liquid phases. BIBLIOGRAPHY 1. Salama, A. and Kessler, M. (2000). ISO and Cosmic Water. European Space Agency Bulletin 104, pp. 31–38. 2. Lewis, J. (1995). Physics and Chemistry of the Solar System. Academic, San Diego, pp. 30–31. 3. Tielens, A.G.G.M., Hagen, W., and Greenberg, J.M. (1983). Interstellar ice. J. Phys. Chem. 87: 4220–4229. 4. Blake, D. and Jenniskens, P. (2001). The ice of life. Sci. Am. August: 44–51. 5. O’Neill, P.T. and Williams, D.A. (1999). Interstellar water and interstellar ice. Astrophys. Space Sci. 266: 539–548. 6. Cowen, R. (1998). Unveiling the hidden universe. Sci. News 153: 328–330. 7. Harwit, M., Neufield, D.A., Melnick, G.J., and Kaufman, M.J. (1998). Thermal water vapor emission from shocked regions in Orion. Astrophys. J. Lett. 497: 105–108. 8. Jennings, D.E. and Sada, P.V. (1998). Water in Betelgeuse and Antares. Science 279: 844–847. 9. Oka, T. (1997). Water on the sun: Molecules everywhere. Science 277: 328–329. 10. Tsuji, T. (1986). Molecules in stars. Annu. Rev. Astron. Astrophys. 24: 89–125.

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11. Endress, M., Zinner, E., and Bischoff, A. (1996). Early aqueous activity on primitive meteorite parent bodies. Nature 379: 701–703. 12. Boss, A. (1996). Extrasolar planets. Phys. Today September: 32–38.

THE WATER CYCLE NASA—Goddard Space Flight Center

INTRODUCTION As seen from space, one of the most unique features of our home planet is the water, in both liquid and frozen forms, that covers approximately 75% of the Earth’s surface. Believed to have initially arrived on the surface through the emissions of ancient volcanoes, geologic evidence suggests that large amounts of water have likely flowed on Earth for the past 3.8 billion years, most of its existence. As a vital substance that sets the Earth apart from the rest of the planets in our solar system, water is a necessary ingredient for the development and nourishment of life. HYDROLOGIC HISTORY The notion that water is continually circulating from the ocean to the atmosphere to the land and back again to the ocean has interested scholars through most of recorded history. In Book 21 of the lliad, Homer (ca. 810 B.C.) wrote of ‘‘the deep-flowing Oceanus, from which flow all rivers and every sea and all springs and deep wells.’’ Thales (ca. 640 B.C.–ca. 546 B.C.) and Plato (ca. 427 B.C.–347 B.C.) also alluded to the water cycle when they wrote that all waters returned by various routes to the sea. But it wasn’t until many centuries later that scientific measurements confirmed the existence of a water (or hydrologic) cycle. Seventeenth century French physicists Pierre Perrault (1608–1680) and Edmond Mariotte (1620–1684) separately made crude precipitation measurements in the Seine River basin in France and correlated these measurements with the discharge of the river to demonstrate that quantities of rainfall and snow were adequate to support the river’s flow. WATER, WATER, EVERYWHERE Water is everywhere on Earth and is the only known substance that can naturally exist as a gas, liquid, and solid within the relatively small range of air temperatures and pressures found at the Earth’s surface. In all, the Earth’s water content is about 1.39 billion cubic kilometers (331 million cubic miles) and the vast bulk of it, about 96.5%, is in the global oceans. Approximately 1.7% is

This article is a US Government work and, as such, is in the public domain in the United States of America.

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THE WATER CYCLE

Table 1. One Estimate of Global Water Distribution. Estimates of Groundwater are Particularly Difficult and Vary Widely Amongst Sources, with the Value in this Table Being Near the High End of the Range. Using the Values in This Table, Groundwater Constitutes Approximately 30% of Fresh Water, Whereas Ice (Including Ice Caps, Glaciers, Permanent Snow, Ground Ice, and Permafrost) Constitute Approximately 70% of Fresh Water. With Other Estimates, Groundwater is Sometimes Listed as 22% and Ice as 78% of Fresh Water Volume (1000 km3 ) Oceans, Seas, & Bays Ice caps, Glaciers, & Permanent Snow Groundwater Fresh Saline Soil Moisture Ground Ice & Permafrost Lakes Fresh Saline Atmosphere Swamp Water Rivers Biological Water Total

Percent of Percent of Total Water Fresh Water

1,338,000 24,064

96.5 1.74

— 68.7

23,400 (10,530) (12,870) 16.5 300

1.7 (0.76) (0.94) 0.001 0.022

— 30.1 — 0.05 0.86

176.4 (91.0) (85.4) 12.9 11.47 2.12 1.12 1,385,984

0.013 (0.007) (0.006) 0.001 0.0008 0.0002 0.0001 100.0

— 0.26 — 0.04 0.03 0.006 0.003 100.0

Source: Gleick, P.H., 1996: Water resources. In Encyclopedia of Climate and Weather, ed. by S. H. Schneider, Oxford University Press, New York, vol. 2, pp. 817–823.

Figure 1. In the hydrologic cycle, individual water molecules travel between the oceans, water vapor in the atmosphere, water and ice on the land, and underground water.

of their leaves. Together, evaporation, sublimation, and transpiration, plus volcanic emissions, account for all the water vapor in the atmosphere. While evaporation from the oceans is the primary vehicle for driving the surface-toatmosphere portion of the hydrologic cycle, transpiration is also significant. For example, a cornfield 1 acre in size can transpire as much as 4000 gallons of water every day. After the water enters the lower atmosphere, rising air currents carry it upward, often high into the atmosphere,

stored in the polar icecaps, glaciers, and permanent snow, and another 1.7% is stored in groundwater, lakes, rivers, streams, and soil. Finally, a thousandth of 1% exists as water vapor in the Earth’s atmosphere (Table 1). A MULTI-PHASED JOURNEY The hydrologic cycle describes the pilgrimage of water as water molecules make their way from the Earth’s surface to the atmosphere, and back again. This gigantic system, powered by energy from the sun, is a continuous exchange of moisture between the oceans, the atmosphere, and the land (Fig. 1). Studies have revealed that the oceans, seas, and other bodies of water (lakes, rivers, streams) provide nearly 90% of the moisture in our atmosphere. Liquid water leaves these sources as a result of evaporation, the process by which water changes from a liquid to a gas. In addition, a very small portion of water vapor enters the atmosphere through sublimation, the process by which water changes from a solid (ice or snow) to a gas. (The gradual shrinking of snow banks, even though the temperature remains below the freezing point, results from sublimation.) The remaining 10% of the moisture found in the atmosphere is released by plants through transpiration (Fig. 2). Plants take in water through their root systems to deliver nutrients to their leaves, then release it through small pores, called stomates, found on the undersides

Figure 2. Plants return water to the atmosphere through transpiration. In this process, water evaporates from pores in the plant’s leaves, after being drawn, along with nutrients, from the root system through the plant.

THE WATER CYCLE

where the air cools and loses its capacity to support water vapor. As a result, the excess water vapor condenses (i.e., changes from a gas to a liquid) to form cloud droplets, which can eventually grow and produce precipitation (including rain, snow, sleet, freezing rain, and hail), the primary mechanism for transporting water from the atmosphere back to the Earth’s surface. When precipitation falls over the land surface, it follows various routes. Some of it evaporates, returning to the atmosphere, and some seeps into the ground (as soil moisture or groundwater). Groundwater is found in two layers of the soil, the ‘‘zone of aeration,’’ where gaps in the soil are filled with both air and water, and, further down, the ‘‘zone of saturation,’’ where the gaps are completely filled with water. The boundary between the two zones is known as the water table, which rises or falls as the amount of groundwater increases or decreases (Fig. 3). The rest of the water runs off into rivers and streams, and almost all of this water eventually flows into the oceans or other bodies of water, where the cycle begins anew (or, more accurately, continues). At different stages of the cycle, some of the water is intercepted by humans or other life forms. Even though the amount of water in the atmosphere is only 12,900 cubic kilometers (a minute fraction of Earth’s total water supply that, if completely rained out, would cover the Earth’s surface to a depth of only 2.5 centimeters), some 495,000 cubic kilometers of water are cycled through the atmosphere every year, enough to uniformly cover the Earth’s surface to a depth of 97 centimeters. Because water continually evaporates, condenses, and precipitates, with evaporation on a global basis approximately equaling global precipitation, the total amount of water vapor in the atmosphere remains approximately the same over time. However, over the continents, precipitation routinely exceeds evaporation, and conversely, over the oceans, evaporation exceeds precipitation. In the case of the oceans, the routine excess of evaporation over precipitation would eventually leave

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the oceans empty if they were not being replenished by additional means. Not only are they being replenished, largely through runoff from the land areas, but, over the past 100 years, they have been over-replenished, with sea level around the globe rising by a small amount. Sea level rises both because of warming of the oceans, causing water expansion and thereby a volume increase, and because of a greater mass of water entering the ocean than the amount leaving it through evaporation or other means. A primary cause for increased mass of water entering the ocean is the calving or melting of land ice (ice sheets and glaciers). Throughout the hydrologic cycle, there are an endless number of paths that a water molecule might follow. Water at the bottom of Lake Superior may eventually fall as rain in Massachusetts. Runoff from the Massachusetts rain may drain into the Atlantic Ocean and circulate northeastward toward Iceland, destined to become part of a floe of sea ice, or, after evaporation to the atmosphere and precipitation as snow, part of a glacier. Water molecules can take an immense variety of routes and branching trails that lead them again and again through the three phases of ice, liquid water, and water vapor. For instance, the water molecules that once fell 100 years ago as rain on your great grandparents’ farmhouse in lowa might now be falling as snow on your driveway in California. THE WATER CYCLE AND CLIMATE CHANGE Amongst the highest priorities in Earth science and environmental policy issues confronting society are the potential changes in the Earth’s water cycle due to climate change. The science community now generally agrees that the Earth’s climate will undergo changes in response to natural variability, including solar variability, and to increasing concentrations of greenhouse gases and aerosols. Furthermore, agreement is widespread that these changes may profoundly affect atmospheric water vapor concentrations, clouds, and precipitation patterns. For example, a warmer climate, directly leading to increased evaporation, may well accelerate the hydrologic cycle, resulting in an increase in the amount of moisture circulating through the atmosphere. Many uncertainties remain, however, as illustrated by the inconsistent results given by current climate models regarding the future distribution of precipitation. THE AQUA MISSION AND THE WATER CYCLE

Figure 3. The water table is the top of the zone of saturation and intersects the land surface at lakes and streams. Above the water table lies the zone of aeration and soil moisture belt, which supplies much of the water needed by plants.

As mentioned earlier, the hydrologic cycle involves evaporation, transpiration, condensation, precipitation, and runoff. NASA’s Aqua satellite monitors many aspects of the role of water in the Earth’s systems, and will do so at spatial and temporal scales appropriate to foster a more detailed understanding of each of the processes that contribute to the hydrologic cycle. These data and the analyses of them nurture the development and refinement of hydrologic process models and a corresponding improvement in regional and global climate models, with a direct anticipated benefit of more-accurate weather and climate forecasts.

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CYCLONES

Aqua’s contributions to monitoring water in the Earth’s environment involves all six of Aqua’s instruments: the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), the Humidity Sounder for Brazil (HSB), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), the Moderate Resolution Imaging Spectroradiometer (MODIS), and Clouds and the Earth’s Radiant Energy System (CERES). The AIRS/AMSU/HSB combination provides more-accurate space-based measurements of atmospheric temperature and water vapor than have ever been obtained before, with the highest vertical resolution to date as well. Since water vapor is the Earth’s primary greenhouse gas and contributes significantly to uncertainties in projections of future global warming, it is critical to understand how it varies in the Earth system. The water in clouds is examined with MODIS, CERES, and AIRS data; and global precipitation is monitored with AMSR-E. The cloud data includes the height and areal coverages of clouds, the liquid water content, and the sizes of cloud droplets and ice particles, the latter sizes being important to the understanding of the optical properties of clouds and their contribution to the Earth’s albedo (reflectivity). HSB and AMSR-E, both making measurements at microwave wavelengths, have the ability to see through clouds and detect the rainfall under them, furthering the understanding of how water is cycled through the atmosphere. Frozen water in the oceans, in the form of sea ice, is examined with both AMSR-E and MODIS data, the former allowing routine monitoring of sea ice at a coarse resolution and the latter providing greater spatial resolution but only under cloud-free conditions. Sea ice can insulate the underlying liquid water against heat loss to the often frigid overlying polar atmosphere and also reflects sunlight that would otherwise be available to warm the ocean. AMSR-E measurements allow the routine derivation of sea ice concentrations in both polar regions, through taking advantage of the marked contrast in microwave emissions of sea ice and liquid water. This continues with improved resolution and accuracy, a 22year satellite record of changes in the extent of polar ice. MODIS, with its finer resolution, permits the identification of individual ice floes, when unobscured by clouds. AMSR-E and MODIS also provide monitoring of snow coverage over land, another key indicator of climate change. Here too, the AMSR-E allows routine monitoring of the snow, irrespective of cloud cover, but at a coarse spatial resolution, while MODIS obtains data with much greater spatial detail under cloud-free conditions. As for liquid water on land, AMSR-E provides an indication of soil moisture, which is crucial for the maintenance of land vegetation, including agricultural crops. AMSR-E’s monitoring of soil moisture globally should permit, for example, the early identification of signs of drought episodes. THE AQUA SPACECRAFT Aqua is a major mission of the Earth Observing System (EOS), an international program centered in NASA’s

Earth Science Enterprise to study the Earth in detail from the unique vantage point of space. Focused on key measurements identified by a consensus of U.S. and international scientists, EOS is further enabling studies of the complex interactions amongst the Earth’s land, ocean, air, ice and biological systems. The Aqua spacecraft circles the Earth in an orbit that ascends across the equator each day at 1:30 p.m. local time and passes very close to the poles, complementing the 10:30 a.m. measurements being made by Terra, the first of the EOS spacecraft, launched in December 1999. The instrument complement on Aqua is designed to provide information on a great many processes and components of the Earth system, including cloud formation, precipitation, water vapor, air temperature, cloud radiative properties, sea surface temperature, surface wind speeds, sea ice concentration and temperature, snow cover, soil moisture, and land and ocean vegetation. The individual swaths of measurements will be compiled into global images, with global coverage of many variables being obtained as frequently as every two days or, with the help of numerical models, combined every 6 or 12 hours into comprehensive representations of the Earth’s atmospheric circulation and surface properties. In combination with measurements from other polar orbiting satellites, Aqua measurements also provide accurate monthly-mean climate assessments that can be compared with and assimilated into computer model simulations of the Earth’s climate. The Earth Observing System has three major components: the EOS spacecraft, an advanced ground-based computer network for processing, storing, and distributing the collected data (the EOS Data and Information System); and teams of scientists and applications specialists who study the data and help users in universities, industry, and the public apply it to issues ranging from weather forecasting and climate prediction to agriculture and urban planning.

CYCLONES ARTHUR M. HOLST Philadelphia Water Department Philadelphia, Pennsylvania

Cyclones are hazardous weather conditions characterized by extreme gusts of wind moving in a circular pattern, low pressure, and intense rain. They form over tropical or subtropical waters; however, some can reach land, where they have in the past inflicted great amounts of damage on buildings and communities. Based on wind strength, cyclones are given various names. Tropical depressions have maximum surface winds of less than 39 mph. Those cyclones whose maximum winds are between 39 and 74 mph are known as tropical storms. Upon attaining 74-mph surface winds, a cyclone is known as one of a number of names that are all regional equivalents of the same type of storm. The names of cyclones are typhoon (in the NW Pacific Ocean), hurricane (in the North Atlantic, NE Pacific, and South Pacific Ocean), tropical cyclone (in the SW Indian

CYCLONES

Ocean), severe cyclonic storm (in the North Indian Ocean), and severe tropical cyclone (in the SW Pacific and SE Indian Oceans). Cyclones always build over tropical seas. There are seven basins in which the majority of tropical cyclones form: the Atlantic Basin, the North Indian Basin, the Southwest Indian Basin, the Southeast IndianAustralian Basin, the Australian-Southwest Pacific Basin, the Northwest Pacific Basin, and the Northeast Pacific Basin. Heat gives cyclones their energy, and thus the water over which a cyclone forms must be at least as warm as 80◦ F (i.e., tropical). Other conditions necessary for a cyclone include a fast cooling atmosphere, moisture in the middle troposphere area, a distance of more than 300 miles from the equator to be influenced by the Coriolis force, and minimal vertical wind shear. This vertical wind shear is the result of differences between winds in the lower and upper portions of the atmosphere. However, the main contributor to the formation of a cyclone is a disturbance in the form of a thunderstorm or group of showers. When all of these factors come together, conditions are right for a tropical cyclone, although the presence of each of these factors does not guarantee the formation of a cyclone. Cyclones are spontaneous; a minute variation in one variable can be the difference between a hurricane and a thunderstorm. The circular area in the center of a cyclone, known as the ‘‘eye,’’ has conditions quite different from those in the region surrounding it. Calmness and a light breeze characterize the eye. Temperatures are generally higher than those in the surrounding area, and the sky is usually very clear. Since the 1970s, cyclones have been regularly named by various people and agencies, depending on where the cyclones originated. They are named to ensure ease of description among newscasters, weatherpeople, and the general public. Names are often taken from rotating lists, one name for each letter of the alphabet. When an exceptional cyclone occurs, its name is taken out of use (‘‘retired’’) to avoid confusion. Strong cyclones often cause extensive damage to whatever they encounter. Damage can range from crop destruction to total devastation of building structures, depending on the severity of the cyclone. They become most dangerous as they hit land and spawn tornadoes. These are formed when tropical cyclones begin to lose their power. The diameter of a tropical cyclone is measured in kilometers; the diameter of a tornado is measured in meters. In 1980, one of the most destructive cyclonespawned tornadoes in the United States caused nearly $100,000,000 worth of damage to the Austin, Texas, area. Along with destruction, cyclones (and the subsequent tornadoes) cause death. Large objects lifted from the path of the extreme wind are tossed about like lethal weapons. In 1964, twenty-two people were killed by a tornado that hit the Los Angeles area in the United States. The most damaging cyclone in history was Hurricane Andrew, which caused over $26 billion in damage to the Southeastern United States. The most deadly cyclone ever may have been the Bangladesh Cyclone, which killed at least 300,000 people in 1970. One of the ways in which a hurricane will cause damage is through the storm surge. This is the name

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given to the phenomenon whereby sea level in the area of a cyclone rises due to cyclonic winds. Once a cyclone reaches 74 mph maximum winds and is considered a hurricane, it’s intensity is rated by the Saffir–Simpson Scale, used since the 1970s by the National Oceanic and Atmospheric Administration (NOAA). Hurricanes are referred to as category one, category two, category three, category four, or category five. Category one hurricanes have winds between 74 and 95 mph. They cause negligible damage to buildings and other structures, although they can damage mobile homes and road signs. They carry a storm surge of about 5 feet. Category two hurricanes have maximum winds of 96–110 mph. They can cause minor damage to buildings and sizable damage to mobile homes and trees. Their storm surge is usually around 7 feet. Category three hurricanes have winds from 111–130 mph. They cause noticeable damage to buildings and trees; buildings near the shoreline are often destroyed by flooding. Evacuation of certain low-lying areas can be necessary for category three hurricanes, and their storm surge ranges from 9–12 feet. Category four hurricanes have winds between 131 and 155 mph. These hurricanes can cause massive damage to smaller structures. They destroy trees and mobile homes utterly. Evacuation of large areas can be necessary, as the storm surge can reach up to 18 feet. Category five hurricanes are the most powerful; they have maximum sustained winds of more than 155 mph. Residential as well as industrial structures are often destroyed. Damage is catastrophic, and major evacuations usually take place. The storm surge exceeds 18 feet above normal. Cyclones can range from relatively simple tropical storms to devastating hurricanes whose winds swirl at furious speeds. Their effects can be disastrous and longlasting. READING LIST Bureau of Meteorology. (2002). Surviving Cyclones. Available: http://www.bom.gov.au/info/cyclone/. (March 13). Department of Public Safety. (2002). ‘‘General Hurricane Information.’’ Available: http://www.escambia-emergency.com/geninfo. asp. (March 13). Landsea, Christopher W. FAQ: Hurricanes, Typhoons, and Tropical Cyclones. Available: http://www.aoml.noaa.gov/hrd/tcfaq/ tcfaqA.html. (March 13). National Weather Service Houston/Galveston. (2002). Tropical Cyclone FAQ. Available: http://www.srh.noaa.gov/hgx/index3/ tropical3/geninfo3.htm. (March 13). Hurricane Research Division: FAQ Available: http://www.aoml. noaa.gov/hrd/tcfaq/F1.html. Hurricane Research Division: FAQ Available: http://www.aoml. noaa.gov/hrd/tcfaq/E7.html. Hurricane Research Division: FAQ Available: http://www.aoml. noaa.gov/hrd/tcfaq/B1.html. Hurricane Research Division: FAQ Available: http://www.aoml. noaa.gov/hrd/tcfaq/A10.html. Hurricane Research Division: FAQ Available: http://www.aoml. noaa.gov/hrd/tcfaq/A1.html. Wonders of Weather. Available: http://school.discovery.com/lessonplans/programs/wondersofweather/vocab.html.

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WATER CYCLE

The Saffir–Simpson Hurricane Scale. Available: http://www.nhc. noaa.gov/aboutsshs.shtml.

WATER CYCLE ARTHUR M. HOLST Philadelphia Water Department Philadelphia, Pennsylvania

The water cycle—a series of steps through which virtually all water on earth is constantly cycling. The names of these steps vary, but they generally follow this order: storage, evaporation, transpiration, condensation, precipitation, infiltration, and runoff. Due to the nature of the water cycle, there is really no ‘‘beginning’’ or ‘‘end’’, but for simplicity, the cycle can be said to begin at the storage stage. Storage is the storing of water on, in, and above the earth. There are about 340 million cubic miles of water on the earth. This water is stored in many places: glaciers, seas, rivers, lakes, polar ice caps, and all living things on the planet. The largest percentage of water, approximately 97.25%, exists as salt water in the ocean. Water is also stored in the earth’s atmosphere and as groundwater. Groundwater in the top few miles of the earth’s crust is easily obtainable, whereas groundwater further down is chemically attached to rocks and usually cannot be accessed. Evaporation is an essential way in which water is transferred from the earth to the atmosphere. During evaporation, water molecules change from a liquid state directly into a gaseous state, known as water vapor. Changes in temperature and air pressure on the earth cause millions of gallons of water to evaporate into the atmosphere each day. The majority of the water that is transferred into the atmosphere is primarily in a liquid state before the change; however, a small percentage of new water vapor comes from ice. The process of water changing state from a solid directly to a gas is called sublimation. Sublimation occurs on glaciers and polar ice sheets. When the sun strikes these massive ice structures, the temperature and pressure allow no room for a liquid, only a solid and a gas. Transpiration is another way that water is transferred into the atmosphere. Although similar in process to evaporation, transpiration differs because the medium from which the water comes is not earth, it is plants. Transpiration is the process through which water absorbed from the ground by plant roots evaporates into the atmosphere. After the plants absorb the water from the soil, the water moves up through the veins of the plant, eventually reaching the leaves (or the plant’s equivalent). These leaves have pores, or stomata, which allow water to evaporate. Large forests can release massive amounts of water into the atmosphere through transpiration. Once the water has been transferred into the atmosphere by either evaporation or transpiration, the molecules will eventually condense. This process is called condensation. Condensation is the reciprocal process of evaporation. During condensation, water changes state from a gas to a liquid. Once again, a change in

either temperature or pressure initiates the change. Condensation is most visible in the formation of dew, fog, and clouds. Dew usually appears in the morning and is water that has condensed on any solid object during the rapid temperature change that occurs from day to night. If the water vapor is dense enough around objects when the temperature change happens, dew is formed. Fog is really a low level cloud formation. When the conditions are right, fog is formed on or near the ground. The only difference between fog and cloud formations is their locations with reference to the earth. Clouds form when water vapor in the atmosphere encounters a critical temperature or air pressure, causing the water vapor to change state into a liquid. Water molecules then ‘‘stick together’’ causing physical cloud structures to emerge. When the molecules in the cloud that are stuck together reach a certain critical mass, they release the moisture causing precipitation to begin. Precipitation is the process by which water is transferred from the medium of the atmosphere to the medium of the earth. Precipitation literally comes in all shapes and sizes, including rain, snow, and ice. The differentiating factor that determines the form water takes when precipitating is air temperature. The lower the temperature, the more likely it is that the precipitation will be either snow or ice (the closer the temperature is to the freezing point of water, 32 ◦ F or 0 ◦ C the more likely). Droplets of rain form around small particles of dust or dirt to form a cohesive raindrop as a vehicle for the trip to the earth. Regardless of the form it takes on its descent, water will take one of two paths once it arrives on the earth’s crust. It will either seep into the ground or flow into larger bodies of water such as streams, seas, oceans, and rivers. The former process is infiltration, and the latter is runoff. Infiltration restores groundwater to the water table that has been lost from wells. During the infiltration process, the water is purified by cascading amongst rocks and minerals that draw impurities out of the water. Water that does not infiltrate the earth’s crust runs off into streams, rivers, seas, and oceans. Runoff replenishes bodies of water that have lost water due to evaporation. Runoff can occur either above the land or below it. Large amounts of water can run across the land immediately after precipitation. Smaller amounts of water run through the ground and along the water table until they reach a larger body of water. So thusly does the water complete its cycle throughout the different media of the earth. This process is essential for the survival of life on the earth because it allows water to permeate every accessible region of the crust and atmosphere, thereby allowing life to flourish wherever water exists. READING LIST Hydrologic Cycle. (2002). Available: http://www.und.nodak.edu/ instruct/eng/fkarner/pages/cycle.htm. (April 1). The Water Cycle: Scientific Concepts. (1995–1998). Available: http://mbgnet.mobot.org/fresh/cycle/concepts.htm. (March 28, 2002).

DEGREE DAY METHOD

approaches based on the time of the year or the number of days (3). Because of the close coupling between the timescale of plants and temperature, Ritchie and NeSmith (6) proposed that the most appropriate term to describe plant development would be ‘‘thermal time’’ or degree days (DD), whose units are ◦ C-day. The degree day method is based on the effects of temperature on developmental rates, rather than on the duration of a phase. Figure 1b shows the linear relationship between temperature and rate of development, the reciprocal of the duration of the phase in days. The base temperature (Tb ), temperature at which the rate of development is zero, is obtained by extrapolating this linear relationship to the intersection with the x-axis:

Gedzelman, S.D. (2001). The Water Cycle. In: Microsoft Encarta Encyclopedia Deluxe 2001.

DEGREE DAY METHOD CARLOS D. MESSINA University of Florida Gainesville, Florida

An adequate description and prediction of plant development is critical for understanding plant growth and its responses to the environment. Only then we can assess the impact of a changing environment on plant productivity and survival, understand plant adaptation, design adequate agricultural production systems, and optimize natural resources management. Of particular importance for water resource management are the effects of plant ontogeny on plant water use and productivity throughout the regulation of leaf area. This determines the patterns of plant water demand and the partitioning between transpiration and evaporation components. Therefore, plant development dictates the selection of cultivars that best fit the water availability patterns under dryland conditions, and the amount, frequency and timing for irrigation otherwise. Plant development is responsive to environmental cues such as photoperiod, water availability, and temperature. Figure 1a shows an example of the close association between ambient temperature and plant development for boll growth duration in cotton. Rameur first suggested in 1735 that the duration of any developmental stage was related to temperature and that this duration can be characterized by a thermometric constant, which can be predicted by the sum of daily air temperatures (2). Since then, several methods based on the concept of normalizing time by temperature to predict developmental rates were developed (2,3) and applied in life sciences. Although we can formulate some hypothesis to explain the relationship between plant development and temperature based on the effects of temperature on circadian oscillations (4), lipid composition and membranes fluidity, and cell division (5), the scientific basis of these empirical methods remains elusive. It was shown, however, that degree day based methods significantly improved the description and prediction of phenological events relative to other

100 90

y = 0.1503x 2 − 10.7x + 226.15 R 2 = 0.9952

80 70 60 50

20

25

30

Tb = −

y0 α

where y0 is the intercept and α is the slope of the linear regression equation (Fig. 1b). Then, the rate of development (RD) can be calculated as RD(t) = α (Ta − Tb ) where Ta is the mean temperature. Integrating the rate of development in time,

RD dt = α (Ta − Tb ) dt and considering a daily time step (
t = 1) for integration, we can estimate the cumulative development (CD) at time n (tn ), provided that t0 = 0, as CD = α



(Ta − Tb )

n

For constant temperatures, given that development is complete when CD equals one, the degree days above a certain base temperature for a given phase are DD = (Ta − Tb ) n or DD =

1 α

For the example of cotton shown in Fig. 1, boll growth requires 1000 ◦ C-days above a base temperature

0.03 0.025 0.02 0.015 a 0.01 0.005

40 30 15

(b) Rate boll growth duration, 1/days

Boll growth duration, days

(a)

197

0 0 35 Mean temperature, ° C

y = 0.001x − 0.0065 R 2 = 0.9922

Tb 10

20

30

Figure 1. Responses of boll growth duration in cotton (Gossypium hirsutum, L.) development to air temperature. (a) Boll growth duration, (b) rate of boll growth duration (1/d). Tb denotes base temperature (see below), and α is the slope of the regression line. Data is from (1).

198

DEGREE DAY METHOD

of 6.5 ◦ C to reach maturity. Although this formulation for calculating DD is useful for estimating the requirements of the plant to complete a given developmental phase, in natural environments, temperature fluctuates and makes this procedure inadequate. The following canonical form to calculate DD is frequently used: DD =

  Tmax + Tmin  n

2

 − Tb

where Tmax and Tmin are maximum and minimum daily temperatures, n is the number of days of temperature observations, and [(Tmax + Tmin )/2] = Tb when [(Tmax + Tmin )/2] < Tb . An alternative method, frequently used in calculating DD for corn, compares Tmax and Tmin with Tb individually before calculating their average. Significant discrepancies in calculated DD between these procedures may arise under some circumstances (3). These procedures for calculating DD are adequate, provided that (1) the daily temperature does not fall below Tb and does not exceed an upper threshold for a significant part of the day, (2) the temperature of the growing plant tissue is the same as the air temperature, and (3) the response of the rate of development to temperature is linear over the range of temperature that the crop experiences (5). When these assumptions are not satisfied, alternative approaches are required. For example, McMaster et al. (5) and Vinocur and Ritichie (7) used soil or apex temperatures to calculate DD because the growing points were close to the soil rather than at the height where the temperature is normally measured. In simulation models such as CERES (8), hourly temperatures are approximated from Tmax and Tmin , and if the temperature is below Tb , DD is set to zero for that part of the day. For a thorough discussion of the limitations of the degree day method, see Ritchie and NeSmith (5). The degree day method can be found in the literature in a different mathematical form under the concept of physiological day. This model is generally used to simulate development in legumes and is particularly adequate for incorporating the effects of photoperiod on development (9). The rate of development is calculated as the product of two functions: RD(t) = f (P) × f (T) One function accounts for the effects of photoperiod (P) and the other for the effects of temperature (T) on development. The model predicts relative development; the maximum rate of development is standardized to 1.0. At optimum temperature (Topt ) and photoperiod (P < Pmin in short day species and P > Pmax in long day species), the rate of progress in calendar days equals the rate of progress in physiological days. When conditions deviate from the optimum, the rate of progress per day decreases and becomes a fraction of a physiological day. Then, cumulative development is measured in photothermal time units. The effects of the photoperiod on the rate of development are

nonlinear: f (P) = 0,

P − Pmin f (P) = 1 − , Pmax − Pmin f (P) = 1,

if P > Pmax if Pmin < P ≤ Pmax if P ≤ Pmin

In short day species, the relative rate of development is maximum below a threshold Pmin , above which the development decreases to zero at Pmax . Both Pmin and Pmax are characteristic of the species and cultivar (Table 1). A similar function is used to describe the effects of temperature: f (T) = 0, T − Tb f (T) = , Topt1 − Tb f (T) = 1, T − Topt2 f (T) = 1 − , Tupper − Topt2 f (T) = 0,

if T ≤ Tb if Tb < T < Topt1 if Topt2 ≥ T ≥ Topt1 if Tupper > T > Topt2 if T ≥ Tupper

where Topt1 and Topt2 define a plateau whose rate of development is maximum. For temperatures above Topt2 and below Topt1 , the rate of development decreases linearly to zero at Tupper and Tb , respectively. Table 1 shows characteristic values for selected cereals and legumes. In this chapter, a derivation of the degree day method is shown along with a mathematical variant that incorporates the effects of the photoperiod. The literature about models that uses degree days is vast, it is not

Table 1. Cardinal Temperatures and Photoperiods for Selected Models of Cereals and Legumesa Temperature, ◦ C Tb Topt1 Topt2 Tupper

Photoperiod, h Pmin

Pmax

Legumes Soybean Vegetative 7 Early reproductive 6 Late reproductive −48 Bean Vegetative 4 Early reproductive 5 Late reproductive 0 Peanutb Vegetative 11 Early reproductive 11 Late reproductive 5

28 26 26

35 30 34

45 45 45

11.7–14.6 15.5–21.0

27 22 18

35 35 35

45 45 45

12.2–13.2

— —

28 28 26

30 28 26

55 55 55

—

—

Cereals Wheat & Barley Millet Rice Maize Sorghum a

0 10 9 8 8

15 36 — 34 34

— — — — —

— — — — —

20 — 12 125–150c 11.7–12.8 35–189c 12.5 0.3–0.8d 12.5–13.6 30–90c

Adapted from Reference 10. insensitive to photoperiod. c DD ( ◦ C-day) per hour increase in photoperiod. d Units are in days per hour increase in photoperiod (11). b

DESERTIFICATION

the intent to review it here. However, the rationale and concept presented here covers most of the models currently used. Summerfield et al. (12) discuss additive photothermal models and Jones et al. (13) provide further details on multiplicative ones. Ritchie and NeSmith (6) and McMaster and Wilhelm (3) discuss some limitations of the degree day method. As emphasized in these previous papers, to obtain reliable and accurate predictions or descriptions of plant development, the parameters and the method used for their estimation must be consistent. BIBLIOGRAPHY 1. Reddy, K.R., Davidonis, G.H., Johnson, A.S., and Vinyard, B.T. (1999). Temperature regime and carbon dioxide enrichment alter cotton roll development and fiber properties. Agron. J. 91: 851–858. 2. Wang, J.Y. (1960). A critique of the heat unit approach to plant-response studies. Ecology 41: 785–790. 3. McMaster, G.S. and Wilhelm, W.W. (1997). Growing degreedays: one equation, two interpretations. Agric. Forest Meteorol. 87: 291–300. 4. Michael, T.P., Salome’, P.A., and McClung, C. (2003). Two arabidopsis circadian oscillators can be distinguished by differential temperature sensitivity. Proc. Nat. Acad. Sci. USA 100: 6878–6883. 5. McMaster, G.S. et al. (2003). Spring wheat leaf appearance and temperature: extending the paradigm? Ann. Bot. 91: 697–705. 6. Ritchie, J.T. and NeSmith, D.S. (1991). Temperature and crop development. In: Modeling Plant and Soil Systems. R.J. Hanks and J.T. Ritchie (Eds.). Agronomy 31. American Society of Agronomy, Madison, WI, pp. 5–29. 7. Vinocur, M.G. and Ritchie, J.T. (2001). Maize leaf development biases caused by air-apex temperature differences. Agron. J. 93: 767–772. 8. Ritchie, J.T., Singh, U., Godwin, D.C., and Bowen, W.T. (1998). Cereal growth, development and yield. In: Understanding Options for Agricultural Production. G.Y. Tsuji, G. Hoogenboom, and P.K. Thornton (Eds.). Kluwer Academic, Dordrecht, the Netherlands, pp. 79–98. 9. Boote, K.J., Jones, J.W., and Hoogenboom, G. (1998). Simulation of crop growth: CROPGRO model. In: Agricultural Systems Modeling and Simulation. R.M. Peart and R.B. Curry (Eds.). Marcel Dekker, New York, pp. 651–693. 10. Jones, J.W., Tsuji, G.Y., Hoogenboom, G., Hunt, L.A., Thornton, P.K., Wilkens, P.W., Imamura, D.T., Bowen, W.T., and Singh, U. (1998). Decision support system for agrotechnology transfer. In: Understanding Options for Agricultural Production. G.Y. Tsuji, G. Hoogenboom, and P.K. Thornton (Eds.). Kluwer Academic, Dordrecht, the Netherlands, pp. 157–177. 11. Kiniry, J.R. (1991). Maize phasic development. In: Modeling Plant and Soil Systems. R.J. Hanks and J.T. Ritchie (Eds.). Agronomy 31. American Society of Agronomy, Madison, WI, pp. 55–69. 12. Summerfield, R.J. et al. (1993). Towards the reliable prediction of time to flowering in 6 annual crops .2. soybean (Glycine max). Exp. Agric. 29: 253–289. 13. Jones, J.W., Boote, K.J., Jagtap, S.S., and Mishoe, J.W. (1991). Soybean development. In: Modeling Plant and Soil Systems. R.J. Hanks and J.T. Ritchie (Eds.). Agronomy 31. American Society of Agronomy, Madison, WI, pp. 71–90.

199

DESERTIFICATION ALDO CONTI Frascati (RM), Italy

Desertification is a degradation of the top layer of the soil that reduces its ability to support plant life and to produce food. As a result, the soil becomes dusty and dry, and it is easily carried away by erosion, which affects wild and domestic animals, wild plants and crops and, finally, humans. Desertification can be the result of human activities or of natural climate changes. In the latter case, the process is very slow and can take several thousand years to produce its effects. A common misconception about desertification is that it spreads from a desert core. The truth is that land degradation can occur where land abuse has become excessive. If it is not stopped in time, desertification spreads from that spot. Eventually, many of these spots merge and form a large homogeneous area. Another misconception is that desertification is the result of droughts. In fact, well-managed land can recover from even a long period of drought with very little adverse effect as soon as rains return. But it is true that droughts can increase the pace of desertification already taking place. Desertification is a term that has been in use since at least 1949, when Aubreville, a perceptive and wellinformed botanist and ecologist, published a book on Climate, Forets, et Desertification de l’Afrique Tropicale. Aubreville observed desertification in tropical Africa and understood immediately that the culprit was not the Sahara desert gaining land. He noticed instead that the main reasons behind desertification were tree cutting, indiscriminate use of fire to clear the land, and cultivation. Many processes can lead to desertification. Logging, for instance, makes the soil unstable on mountain slopes. Eventually, all the soil runs down as a dangerous landslide or mud river and leaves behind exposed rocks, unable to support any life. What is left behind are barren mountains, particularly evident in China. In Europe, one of the leading causes of desertification is overgrazing. In the past, wild animals used to move following the rainfall, always grazing the richest areas. In modern times, the use of fences prevented these movements, and the result was heavy overgrazing that left the soil exposed to erosion. In many areas, desertification is the result of agriculture. A typical example of this is salinization of soil that happens normally when the soil is overirrigated. The water that is not used by plants evaporates, leaving behind salts that concentrate in the soil. Eventually, the concentration of salts in the soil becomes so high that plants cannot survive, again exposing the land to erosion. In same cases, desertification is the more direct result of urbanization, mining, and recreational activities. In any case, the adverse effects are still the same. Nowadays, desertification is a serious problem that affects, according to some estimates, up to 30% of dry lands. Worldwide, desertification is making approximately 12 million hectares useless for cultivation every year. But land degradation and desertification are by no means new problems, despite the attention focused on them in

200

DEW

recent years. During the first conquest of Africa, it was normal to clear patches of land with fire and then use them to grow crops. After three or four seasons, the land was depleted of nutrients and unable to support any plant life. Moreover, there is some historical evidence that serious and extensive land deterioration was already occurring several centuries before. It started in arid regions, and it had three epicenters: the Mediterranean Sea and other places where destructive changes in soil and plant cover had occurred, but were small in extent or not well known. Luckily, desertification in many areas has been stopped, but very little effort has been made to restore the land to its original productivity. Today, desertification can be defeated using techniques already known, if financial resources are available and the political will to act is present. For instance, only in the last few decades, satellite images have allowed a better understanding and monitoring of the problem on a large scale. There are several possible remedies available, even at the local level. The first is to avoid cutting trees or, at least, to replace them with new ones. Plants, a major soil stabilizer, can alone stop erosion. Moreover, the use of available local water and ways to control the salinity of the soil can be very effective. On this topic, genetic engineering is trying to help. Scientists are working on the development of crops that can survive higher salinity, both as a way to use the land and produce food and as a way to save lost soils. Curiously, one of the remedies until now used against desertification is to pollute the soil. In Iran, oil is sprayed over semiarid land with crops. The oil covers the seedlings, retains the moisture, and prevents them from being blown away by the wind until they grow large enough. As stated at the beginning, desertification is sometimes a slow natural process. As an example, it should be enough to say that 20,000 years ago, the Sahara Desert was a lush forest. This is proved by the fossils of the animals that used to live in this forest. Moreover, pictures taken using radar from the Space Shuttle allow us to identify numerous dry riverbeds under a few meters of sand. This is already happening again due to the global warming on the earth. Many deserts are expanding, even though it is not possible to find a human reason for that. Desertification seems to threaten, in particular, all countries in the Mediterranean region. The coasts of North Africa are already disappearing into the sand, but the same might start happening in Europe. The heat wave of 2003 caused lots of problems. In Italy, many crops were heavily affected, and in the whole Mediterranean region, but in particular in Spain and Portugal, large areas of forest were destroyed by fires.

DEW ALDO CONTI Frascati (RM), Italy

Dew forms when water condenses on objects on the surface near the ground and forms a thin layer or many

droplets. Dew forms normally during the night when the air temperature decreases and approaches the dew point. Objects on the surface cool down, too, by radiative cooling, facilitating the condensation of small droplets of water. Dew formation is helped by the high humidity of the bottom layer of air, close to the surface. This layer can supply the needed water and prevent the evaporation of the dew already deposited. Strong winds can inhibit the formation of dew. Turbulence mixes a larger layer of air and creates a more homogeneous distribution of humidity and heat, thus preventing the formation of the right conditions near the ground. Dew forms more easily on surfaces that cool efficiently, like metals, which is the reason that cars are often covered with dew in the morning. But dew is often seen on grass or plants because their transpiration creates a thin layer of very humid air. Dew is very important in the ecology of many deserts, especially those along the western coasts of Africa and South America. In some of them, water from condensation of dew caused by night cooling often exceeds that of rainfall. But dew can be an interesting source of water for human consumption, too. For instance, data recorded in the Negev desert of Israel, a country where water is really scarce, have shown that dew falls for 200 days each year. Moreover, dew is plentiful on many little islands that, surrounded by water, have high humidity but where no water dwells. Some islands of the Mediterranean Sea suffer from a chronic water shortage, which is the reason that one of the first dew-collecting plants has been built in Ajaccio (Corsica Island in France). It is also interesting to describe an old project studied in India and unfortunately never actually realized. The idea was to pump water at 4.5 ◦ C from the sea at a depth of 500 meters. The pumping scheme called for the use of four 1.2-meter pipes and wind-powered pumps. A heat exchanger of 130,000 square meters could then condense, every day, more than 600 cubic meters of dew. But many animals and plants have already learned how to survive on dew. A place particularly interesting for this kind of adaptation is the Namib desert in Namibia (Africa). Here, many insects in the early morning sit on top of sand dunes trying to catch some dew (or fog) on their wings and legs. In particular, the beetle Stenocara has even modified the surface of its hard shell surface to trap mist more efficiently. This beetle shell is covered with bumps whose peaks are smooth like glass and attract water. The troughs around the bumps are covered with a wax that repels water. The water is therefore collected by the peaks, and when a droplet is big enough to touch the water repelling valley it rolls down to the animal’s mouth. Some researchers think that the easy trick of the animal can be used in dew collecting devices. A similar surface can be prepared in many ways, even with an ink-jet printer that sprays hydrophilic ink onto an acetate sheet. Dewcollecting devices have the problem of making the water run off the collecting surface. Another Namibian creature well adapted to survive on dew is the plant Welwitschia mirabilis. Despite its look, it is a close relative of pine trees. It has a short trunk split in two and from each side grows a single leaf that can be several meters long. Welwitschias are among the oldest

DEW DESERTS

plants on the earth, and some of them are 1500 years old. The trick that allows this plant to survive in one of the driest deserts of the planet is a two-part root system. Welwitschias have a long root that goes deep in the soil trying to reach the water table and extends for several meters away from the plant. These roots collect all the dew that forms on the top layer of soil. Moreover, all the water that condenses on the leaves forms big drops that eventually run down, so that the plant can water its own roots.

DEW DESERTS GIORA J. KIDRON The Hebrew University of Jerusalem Jerusalem, Israel

The term dew deserts denotes deserts that receive dew precipitation throughout the year. Dew is defined as condensation of atmospheric vapor and does not include vapor condensation that stems from the wet ground, i.e., distillation. We term dew desert as a desert that receives at least 10 mm of dew in >0.1 mm of daily precipitation. As a result of dew precipitation, primary production in dew deserts is much higher, affecting the entire food chain. Like the Atacama Desert in South America, the Namib Desert in South Africa, and the Sonora Desert in Baja California (North America), dew only affects those portions of the desert close to a sea or ocean, i.e., to a large body of water that can serve as an adequate vapor source. As most deserts occupy mainly the interior of the continents, the term applies only to a small part of near sea deserts. At present, information regarding the extent of dew precipitation within deserts is scarce. Most of the available information pertains to the heart of the Negev Desert where annual precipitation is 90–100 mm (1). There, a total of 33 mm was annually measured (2). Nevertheless, based on rain isohyets and the proximity to a sea or ocean (3), one may hypothesize that parts of the Sahara and the Arabian Peninsula are in fact dew deserts. Certain areas within the fog deserts may also be dew deserts (4–6). Although daily dew amounts may usually range between 0.1 and 0.3 mm and the total annual sum may be much smaller than that of rain precipitation, the occurrence of a steady and constant source may be of great importance in arid and semiarid zones (7–9). As the threshold for organism activity was found to be 0.03 mm of dew (10), amounts of 0.1–0.3 mm are still sufficient to allow growth activity. Although small, the dew amounts received may allow the establishment and distribution of many species, otherwise not capable of inhabiting the site. Consequently, higher biomass and higher species diversity may characterize the dew deserts. Biomass increase per millimeter of dew may be much higher than that calculated for rain (7) and that extrapolated, by adding the addition of water from dew to that of rain. The dew may thus be an important source of moisture for the primary food chain in arid and semiarid zones (11).

201

Many groups of micro-organisms were hypothesized to use dew. Among them, cyanobacteria, hypolithic algae and cyanobacteria that occupy the underside of stones (12,13), and lichens (14,15). Among the lichens are the endolithic lichens, embedded within calcite or dolomite crystals at the upper 1–5 mm of the rock and stone surface (16); epilithic and epedaphic lichens that dwell on the rock and soil surface, respectively (17); foliose (18); and fruticose lichens (18,19). In addition, bugs, ants, and beetles were reported to use dew directly by drinking it (20), whereas isopods and beetles were reported to use it indirectly by consuming wet food (20). When wet, snails in the Negev Desert were reported to successfully graze on endolithic lichens. By doing so, the snails disintegrate the limestone, a weathering phenomenon that can take place only upon rock moistening (21). Although cyanobacteria, hypolithic algae, and cyanobacteria, epedaphic, endolithic, epilithic, foliose, and fruticose lichens were all hypothesized to use dew, positive evidence for dew use under field conditions was obtained only from endolithic, epilithic, foliose, and fruticose lichens. These lichens were shown to photosynthesize for 2–4 h in the morning following dew in the Negev Desert (Fig. 1) (10,18,22). One should note that whereas lithobiontic lichens (inhabiting rocks and stones) were shown to use dew (22), dew use by micro-organisms inhabiting the soil is still controversial. Whereas Lange et al. (22) and Veste et al. (23) showed the use of dew by epedaphic lichens inhabiting soil and sand, respectively, and indirect evidence, expressed by the development of sexual and vegetative reproduction organs, were also monitored in mosses in the Negev Desert (24), the use of dew by endedaphic cyanobacteria inhabiting sand is not certain. According to Jacobs et al. (25), dew may moisten the surface. However, other reports indicate that dew moistening of the soil is rare (24,26). According ¨ to Bunnenberg and Kuhn (26), an amount of 0.13 mm of dew at 9 cm above ground amounted to 0.03 mm only at the surface. Similarly, Kidron et al. (24) showed that average dew precipitation of 0.1 mm measured on glass plates at 0.7 cm above ground amounted to only 0.034 mm at the surface. As cyanobacteria need liquid water for growth (27), and the necessary threshold for net photosynthesis was 0.1 mm (28), only rarely sufficient dew will moisten the surface to reach >0.1 mm, and thus the contribution of dew to the growth and development of endedaphic cyanobacteria may be negligible. The uncertainty regarding the use of dew by certain micro-organisms and at certain habitats is mainly linked to two factors: (a) Does dew condense at all habitats? (b) Is the amount supplied sufficient for use and for net carbon gain? As for the second question, rapid dew evaporation during the morning may result in a net loss of carbon, as was shown for the lichen Ramalina maciformis following mornings of low dew precipitation (10). Whereas the efficiency to which different microorganisms may use dew may be species-dependent, no controversy exists as to the perquisite conditions necessary, i.e., the capability of the dew to condense at their habitat. This ability depends, of course, on the existence of sufficient moisture in the air. It also depends

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mg CO2 g−1 h1

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1.00

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0.75

Balance Assim.-yield − resp.-loss = net yield

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0 −0.25

60 Water content

% H2O

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0000

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Figure 1. Apparent CO2 exchange rate (above) and the thalli water content (below) of Ramalina maciformis during 24 h in September 1967. Net carbon yield resulted in 0.146 mg C per gram of dry weight a day (18).

on substrate temperatures that will dictate whether the dew point temperature, necessary for vapor condensation, will be reached. Once reached, dew condensation will take place. As dew was found to condense at a more or less constant rate (29), the time during which the dew point is reached may dictate, to a large extent, the overall amount of dew that will be condensed. Furthermore, as phototrophic microorganisms necessitate light hours for photosynthesis, the length of time during which dew is available may dictate, to a large extent, the overall net gain of organic carbon owing to dew use. Thus, variables that may affect dew condensation and dew duration should be considered once dew availability in different habitats is examined. Factors such as topographical elevation, height above ground, aspect, location along the slope, and angle may all affect dew condensation. Recent dew measurements carried in the Negev Desert aimed to examine the role of the above-mentioned factors. Thus, in order to obtain continuous dew amounts and duration, a simple and inexpensive method was adapted. The Cloth-Plate Method (CPM) consists of 10 × 10 × 0.2 glass plates glued at their bottom to 10 × 10 × 0.5 cm plywood plates, thus creating an identical substratum (30). Velvet-like cloth (6 × 6 × 0.15 cm) are attached each afternoon to the center of the glass plate and collected throughout the following morning into glass jars that are immediately sealed and then weighed in a nearby lab, oven dried (in 70 ◦ C) and then weighed again, and their moisture content is calculated. By placing plates next to each other within a certain habitat, the CPM facilitates inexpensive large-scale continuous measurements (Fig. 2). The readings are also not affected by wind, as might be the case with some other devices (31).

Figure 2. Dew measurements by the CPM in the Negev Highlands.

The CPM was used to assess the possible role of altitude and distance from the sea. When simultaneous measurements at three locations at 250, 550, and 1000 m above sea level being 37, 55, and 98 km from the Mediterranean Sea were carried out in the Negev Desert, positive correlations between dew and fog amounts and altitude were found (Fig. 3). Dew precipitation, as well as fog precipitation, increased with altitude, with the most elevated location receiving more than twice the amount obtained at the topographically lowest location, which was the case, although the most elevated location was also the farthest away from the Mediterranean Sea, i.e., from a vapor source. The data thus indicate that, within 100 km from the sea, topographical height may compensate for

DEW DESERTS 0.45 0.4

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r = 0.93

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6

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9.5 10 10.5 11

Figure 4. A typical condensation and evaporation pattern during the morning hours (30).

0.4 0.35 0.3 Dew amounts (mm)

the increase in distance from the vapor source. In this regard, one should note that elevation plays a major role in controlling dew and fog precipitation also in the Atacama Desert (4). The CPM facilitates careful analysis of dew precipitation. When continuous dew measurements were carried out, a typical condensation and evaporation pattern was obtained during the morning hours (Fig. 4). Dew condensation was found to continue also after dawn and sunrise, explained by radiation-induced air turbulence (30). As for the relationship between dew amounts and height above ground, dew values showed high variability (33,34). When dew was measured on a hilltop in the Negev Highlands at 0.7, 10, 20, 30, 40, and 50 cm above ground, maximal values were recorded at 10 cm above ground (Fig. 5). The findings reflected two effects: the warming effect of the soil as a result of a nocturnal heat flux that rises from the deeper horizons of the soil, responsible for the decrease in dew values near the ground (31,34,35), and the air turbulence at height, resulting from higher wind velocities, responsible for lower dew values farther away from the ground (35,36). High variability in dew amounts and duration was also found in the Negev Desert when dew was measured at 0.7 and 40 cm above ground along limestone slopes (approximately 50 m long) of four aspects (north, south, east, and west) within a second-order drainage basin (Fig. 6). Whereas at 0.7 cm above ground, the hilltops and the bottom parts of the northern and western aspects received the highest amounts, the wadi beds received approximately half these values (Fig. 6a). The lowest values were received at the south-facing midslope (located at the lee side of the prevailing north north-west winds), being approximately a quarter of the maximal values recorded. At 40 cm above ground, a reverse trend was obtained with the south-facing midslope and the wadi beds receiving the highest values (Fig. 7). And thus, whereas the 0.7 cm above-ground results were not in accordance with the classical model that predicts high dew values

203

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Figure 3. The relationships between dew and fog precipitation with altitude in the Negev Desert (32).

at the wadi beds (because of nocturnal katabatic wind) and higher amounts at the lee side of the wind, i.e., at the south-facing slope (because of undisturbed inversion), the 40 cm above ground measurements corresponded to the classical model. The discrepancy was explained by the overwhelming impact of the rock surface temperatures on the dew values at 0.7 cm above ground, with southfacing rock surfaces being 3–8 degrees higher than the north-facing rock surfaces throughout the night. As for the higher amounts of dew received at 0.7 cm above ground at the hilltops in comparison with the wadi

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Figure 6. Dew amounts (a) and duration (b) within 18 stations located at 4 aspects of a second-order drainage basin in the Negev Desert. Top = hilltop, Up = Upper slope, Mid = Midslope, Bot = Bottom slope (37).

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beds, it was hypothesized that the afternoon winds act as a cooling agent, facilitating a much earlier drop in surface temperatures (and thus reaching much faster the necessary dew point temperature) at the wind-exposed hilltops (37). Aspect and slope location also dictate dew duration, seen as being of even greater ecological importance to organisms than the maximal amount (38–40). Generally, a positive correlation between dew amounts and duration was found (34,37), and thus, by affecting dew amounts, aspect and slope position also affect dew duration (Fig. 6b). Nevertheless, dew duration was also affected by slope

0.3

2

N/S E/W Wadi

Figure 7. Dew measurements at 0.7 and 40 cm above ground at three habitats within a second-order drainage basin in the Negev Desert. N = northern exposure, S = southern exposure, Wadi N/S = wadi between the northern and southern exposure, Wadi E/W = wadi between the eastern and western exposures (37).

location and aspect beyond these relations. Although condensation was found to take place in all habitats also after sunrise (for usually 0.5–1.0 h after sunrise), condensation at the sun-sheltered habitats of the bottom north- and west-facing slopes continued for up to 1.5 h following sunrise (41). As a result of the higher maximal values and the limited desiccation effect of the sun in these habitats, these habitats were characterized by longer dew duration. The substrate angle is another factor found to affect dew amounts and duration. When cloths were attached to 50 × 50 × 10 cm wooden boxes, having sides of different angles (30, 45, 60, 75, and 90◦ ) placed at different aspects (facing north, south, west, and east) on a hilltop, a decrease in dew amounts with an increase in angle, from 30◦ to 90◦ , was found and dew amounts were positively correlated with cos(θ ) (Fig. 8). Thus, dew amounts obtained at an angle of 90◦ was approximately a quarter of the values obtained at a horizontal surface and at an angle of 30◦ , both of which received similar values. This difference was explained by the slower rate of nocturnal cooling that takes place with an increase in angle in accordance with the lower proportion of sky seen by the substrate (43). No preferential condensation in accordance with aspect was found. Nevertheless, dew duration was aspect-dependent with a decrease in duration following the order west>north>south>east (Fig. 9). Thus, daylight dew duration was approximately double at the westfacing sun-sheltered angle than at the sun-exposed eastfacing aspect. The variability in dew amounts and duration may have important consequences for micro-organisms. For

DEW DESERTS (a)

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1

Figure 9. The relationships between dew duration with (a) angle (in degrees) and (b) cos(θ) in the Negev Desert (42).

Cos (∅)

most micro-organisms, the ability to use dew is primarily a function of the amount condensed and the duration during which dew is available, both of which are habitatdependent. Thus, when cloths were attached to different substrates, high variability in dew amounts was received on loose cobbles, partially embedded cobbles, and rock surfaces (Fig. 10). Loose cobbles that rapidly cool at night were found to receive approximately twice the amounts of embedded cobbles and more than 4 times the amounts condensed on a nearby rock (44). Whereas the cobbles were primarily inhabited by endolithic lichens, the rock surfaces were mainly inhabited by epilithic lichens. Similarly, lichen growth on loose cobbles was controlled by angle-induced dew. Thus, the top of loose cobbles, inhabited by lichens, received approximately twice the amount condensed on the uninhabited side of the cobble (45). Consequently, dew contribution to the ecosystem biomass may be highly important. For instance, in research conducted by Kappen et al. (22,46) in the Negev Desert, the biomass of lichens (with Ramalina maciformis predominating) in the northern aspect was over 200 g m−2 , three to five times as much than at the other aspects. Although some of the differences can certainly be attributed also to use of rain-induced moisture, the fact that the main water source for Ramalina maciformis and other endolithic and epilithic lichens in the Negev Desert was dew pointed to the importance of dew on lichen biomass. The difference in lichen cover of

the sun-sheltered and the sun-exposed slopes points also to the role of dew in lichen distribution (47). As lichens may serve as food for snails, the whole food chain may be affected by dew precipitation. Dew precipitation may also affect vascular plants. The effect may not always be positive, as dew may hasten plant fungal infection (7,48). Dew may preferentially accumulate on leaves because of their lower temperature (0.5–2 ◦ C lower in comparison to the ambient air) (35,36) and thus, wet the leaves for several hours during the morning (34).

B

0.3

B

0.25 Dew amounts (mm)

Figure 8. The relationships between dew amounts with (a) angle (in degrees) and (b) cos(θ) as measured in the Negev Desert (42).

J H

B

Loose Cobbles Embedded Cobbles Rock

B

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Days of measurements

Figure 10. Simultaneous dew amounts as obtained on loose and embedded cobbles inhabited by endolithic lichens, and rock surface inhabited by epilithic lichens (44).

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However, no conclusive evidence of direct dew use by vascular plants is yet available, and the research conducted on this topic is controversial (7,8,31,49,50). Dew, however, may have an indirect effect, facilitating stomata opening (51), longer hours of photosynthesis (39), reducing transpiration (7), and affecting flowering (7). Dew may facilitate seedling survival (52), recovery from wilting (34), plant growth (34), and yield (34,53). By affecting micro-organisms and plant growth, and by facilitating insect survival (20), dew also indirectly affects the nutrient cycling (54) and soil-forming processes (55), which in turn has an important impact on the ecosystem and may thus call for a specific awareness of the dew deserts. BIBLIOGRAPHY 1. Rosenan, N. and Gilad, M. (1985). Meteorological data. In: Atlas of Israel. Carta, Jerusalem. 2. Evenari, M. (1981). Ecology of the Negev Desert, a critical review of our knowledge. In: Developments in Arid Zone Ecology and Environmental Quality. H. Shuval (Ed.). Balaban ISS, Philadelphia, PA, pp. 1–33. 3. Reitan, C.H. and Green, C.R. (1968). Appraisal of research on weather and climate of desert environments. In: Deserts of the World, An Appraisal of Research Into Their Physical and Biological Environments. W.G. McGinnies, B.J. Goldman, and P. Paylore (Eds.). The University of Arizona Press, Tucson, AZ, pp. 19–92. 4. Redon, J. and Lange, O.L. (1983). Epiphytic lichens in the region of a Chilean ‘‘fog oasis’’ (Fray Jorge). 1. Distributional patterns and habitat conditions. Flora. 174: 213–243. 5. Lange, O.L., Meyer, A., Ullmann, I., and Zellner, H. (1991). Microclimate conditions, water content and photosynthesis of lichens in the coastal fog zone of the Namib Desert: measurements in the fall. Flora. 185: 233–266. 6. Lange, O.L., Meyer, A., Zellner, H., and Heber, U. (1994). Photosynthesis and water relations of lichen soil crusts: field measurements in the coastal fog zone of the Namib Desert. Functional Ecol. 8: 253–264. 7. Wallin, G.R. (1967). Agrometeorological aspects of dew. Agric. Meteorol. 4: 85–102. 8. Evenari, M., Shanan, L., and Tadmor, N. (1971). The Negev, the Challenge of a Desert. Harvard Univ. Press, Cambridge, MA, p. 345. 9. Noy-Meir, I. (1973). Desert ecosystems: environment and producers. Ann. Rev. Ecol. Syst. 4: 25–51. 10. Kappen, L. etal. (1979). Ecophysiological investigations on lichens of the Negev Desert, IV: Annual course of the photosynthetic production of Ramalina maciformis (Del.) Bory. Flora. 168: 85–108. 11. Shachak, M. and Steinberger, Y. (1980). An algae-desert snail food chain: energy flow and soil turnover. Oecologia. 46: 402–411. 12. Berner, T. (1974). The Ecophysiology of the Hypolithic Algae in the Negev Highlands of Israel. Ph.D. Thesis, The Hebrew University of Jerusalem. 13. Berner, T. and Evenari, E. (1978). The influence of temperature and light penetration on the abundance of the hypolithic algae in the Negev Desert of Israel. Oecologia. 33: 255–260. 14. Friedmann, E.I., Lipkin, Y., and Ocampo-Paus, R. (1967). Desert algae of the Negev. Phycologia. 6: 185–195. 15. Friedmann, E.I. and Galun, M. (1974). Desert algae, lichens and fungi. In: Desert Biology II. G.W. Brown (Ed.). Academic Press, New York, pp. 165–212.

16. Fry, E.I. (1922). Some types of endolithic lichens. Ann. Bot. 35: 541–562. 17. Golubic, S., Freiedmann, I., and Schneider, J. (1981). The lithobiontic ecological niche, with special reference to microorganisms. J. Sedimentary Petrol. 51: 475–478. 18. Lange, O.L., Schulze, E-D., and Koch, W. (1970). Ecophysiological investigations on lichens of the Negev Desert, II: CO2 gas exchange and water conservation of Ramalina maciformis (Del.) Bory in its natural habitat during the summer dry period (Technical translation 1655. National Research Council of Canada). Flora. 159: 38–62. 19. Lange, O.L. (1969). Ecophysiological investigations on lichens of the Negev Desert. I. CO2 gas exchange of Ramalina maciformis (Del.) Bory under controlled conditions in the laboratory (Technical translation 1654. National Research Council of Canada). Flora. 158: 324–359. 20. Broza, M. (1979). Dew, fog and hygroscopic food as a source of water for desert arthropods. J. Arid. Environ. 2: 43–49. 21. Shachak, M., Jones, C.G., and Granot, Y. (1987). Herbivory in rocks and the weathering of a desert. Science 236: 1098–1099. 22. Lange, O.L., Schulze, E-D., and Koch, W. (1970). Ecophysiological investigations on lichens of the Negev Desert, III: CO2 gas exchange and water metabolism of crustose and foliose lichens in their natural habitat during the summer dry period. Flora. 159: 525–538. 23. Veste, M., Littmann, T., and Friedrich, H. (2001). Microclimate boundary conditions for activity of soil lichen crusts in sand dunes of the north-western Negev Desert, Israel. Flora. 196: 465–474. 24. Kidron, G.J., Hernstadt, I., and Barzilay, E. (2002). The role of dew as a moisture source for sand microbiotic crusts in the Negev Desert, Israel. J. Arid. Environ. 52: 517–533. 25. Jacobs, A.F.G., Heusinkveld, B.G., and Berkowicz, S.M. (2000). Dew measurements along a longitudinal sand dune transect, Negev Desert, Israel. Int. J. Biometeorol. 43: 184–190. ¨ 26. Bunnenberg, C. and Kuhn, W. (1977). Application of the βabsorption method to measure dew on soil and plant surfaces. Int. J. Appl. Radiation Isotopes 28: 751–754. 27. Lange, O.L., Kilian, E., and Ziegler, H. (1986). Water vapor uptake and photosynthesis of lichens: performance differences in species with green and blue-green algae as phycobionts. Oecologia 71: 104–110. 28. Lange, O.L. et al. (1992). Taxonomic composition and photosynthetic characteristics of the ‘‘biological soil crusts’’ covering sand dunes in the Western Negev Desert. Func. Ecol. 6: 519–527. 29. Zangvil, A. (1996). Six years of dew observation in the Negev Desert, Israel. J. Arid. Environ. 32: 361–372. 30. Kidron, G.J. (1998). A simple weighing method for dew and fog measurements. Weather 53: 428–433. 31. Noffsinger, T.L. (Ed.). (1965). Survey of techniques for measuring dew. In: Humidity and Moisture, Measurement and Control in Science and Industry. A. Wexler (Ed.). Reinhold Publishing Corporation, New York, pp. 523–531. 32. Kidron, G.J. (1999). Altitude dependent dew and fog in the Negev desert, Israel. Agric. Forest Meteorol. 96: 1–8. 33. Lloyd, M.G. (1961). The contribution of dew to the summer water budget of Northern Idaho. Bull. Am. Meteorol. Soc. 42: 572–580. 34. Duvdevani, S. (1964). Dew in Israel and its effect on plants. Soil Sci. 98: 14–21. 35. Long, I.F. (1958). Some observations on dew. Meteorol. Mag. 87: 161–168.

DEW POINT 36. Monteith, J.L. (1957). Dew. Quart. J. Royal Meteorol. Soc. 83: 322–341.

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37. Kidron, G.J., Yair, A., and Danin, A. (2000). Dew variability within a small arid drainage basin in the Negev highlands, Israel. Quart. J. Royal Meteorol. Soc. 126: 63–80. 38. Lange, O.L., Geiger, I.L., and Schulze, E-D. (1977). Ecophysiological investigations on lichens in the Negev Desert. V. A model to simulate net photosynthesis and respiration of Ramalina macifomis. Oecologia. 28: 247–259. 39. Kappen, L. et al. (1980). Ecophysiological investigations on lichens of the Negev Desert, VII: The influence of the habitat exposure on dew imbibition and photosynthetic productivity. Flora. 169: 216–229. 40. Lange, O.L. and Tenhunen, J.D. (1982). Water relations and photosynthesis of desert lichens. J. Hattori. Bot. Lab. 53: 309–313. 41. Kidron, G.J. (2000). Analysis of dew precipitation in three habitats within a small arid drainage basin, Negev Highlands, Israel. Atmos. Res. 55: 257–270. 42. Kidron, G.J. (in press). Angle and aspect dependent dew precipitation in the Negev Desert, Israel. J. Hydrol. 43. Oke, T.R. (1978). Boundary Layer Climates. John Wiley & Sons, New York, p. 372. 44. Kidron, G.J. (2000). Dew moisture regime of endolithic and epilithic lichens inhabiting calcareous cobbles and rock outcrops, Negev Desert, Israel. Flora. 195: 145–153. 45. Kidron, G.J. (2002). Causes of two patterns of lichen colonization on cobbles in the Negev Desert, Israel. Lichenologist. 34: 71–80. 46. Kappen, L., Lange, O.L., Schulze, E-D., Evenari, M., and Buschbom, U. (1975). Primary production of lower plants (lichens) in the desert and its physiological basis. In: Photosynthesis and Productivity in Different Environments. J.P. Cooper (Ed.). Cambridge University Press, Cambridge, UK, pp. 133–143. 47. Danin, A. and Garty, J. (1983). Distribution of cyanobacteria and lichens on hillsides of the Negev Highlands and their impact on biogenic weathering. Z. Geomorph. 27: 423–444. 48. Duvdevani, S., Reichert, I., and Palti, J. (1946). The development of downy and powdery mildew of Cucumbers as related to dew and other environmental factors. Palestine J. Bot. (Rehovot Series). 2: 127–151. 49. Stone, E.C. (1957). Dew as an ecological factor. I. A review of the literature. Ecology 38: 407–413. 50. Waisel, Y. (1958). Dew absorption by plants of arid zones. Bull. Res. Counc. Israel 6D: 180–186. 51. Schulze, E-D. et al. (1972). Stomatal responses to changes in humidity in plants growing in the desert. Planta 108: 259–270. 52. Stone, E.C. (1957). Dew as an ecological factor. II. The effect of artificial dew on the survival of Pinus ponderosa and associated species. Ecology 38: 414–422. 53. Rotem, J. and Reichert, J. (1964). Dew - a principal moisture factor enabling early blight epidemics in a semi-arid region of Israel. Plant Disease Reptr. 48: 211–215. 54. Jones, C.G. and Shachak, M. (1990). Fertilization of the desert soil by rock-eating snails. Nature 345: 839–841. 55. Shachak, M., Jones, C.G., and Brand, S. (1995). The role of animals in an arid ecosystem: Snails and isopods as controllers of soil formation, erosion and desalinization. Adv. GeoEcol. 28: 37–50.

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Frascati (RM), Italy

The dew point is the temperature to which air must be cooled at constant pressure until it reaches saturation and the water, or any other vapor, begins condensing. The result is the formation of fog. When the dew point falls below freezing, it is called the frost point. In this case, water forms ice crystals directly. The dew point is also a good indicator of the amount of water contained in the air. The more humid the air, the higher the dew temperature. The dew point is often reached in the evening, when the air cools down, which is why fog is more common in the evening, or why one normally finds that dew or frost are common in the morning but disappear as soon as the temperature increases. Dew point and relative humidity can be measured with an instrument called a wet- and dry-bulb psychrometer. The dry bulb is a normal thermometer that measures the actual air temperature. The wet bulb is another thermometer, but has a bulb wrapped in a piece of cloth dampened by a string that dips into a bottle of distilled water. Unless the air is so humid that it is very close to saturation, the wet bulb thermometer measures a lower temperature, because it is cooled by the evaporation of water. The difference between the dry-bulb and wet-bulb temperatures is called the wet-bulb depression. It is then possible to calculate the dew point as a function of the wet-bulb depression and of the dry-bulb temperature. To calculate the dew point starting from the psychrometer readings, the first step is to calculate the saturation vapor pressure in millibars, corresponding to the dry- and wet-bulb temperature: Es = 6.11 × 10.0[7.5T/(237.7 + T)] Eswb = 6.11 × 10.0[7.5Twb /(237.7 + Twb )] where T and Twb are the readings of the dry- and wet-bulb temperatures. Now we are ready to calculate the actual mixing ratio of the air: W = [(T − Twb )(Cp ) − Lv (Eswb /P)]/[−(T − Twb )(Cpv ) − Lv ] where

Cp = specific heat of dry air at constant pressure (J/g)∼1.005 J/g Cpv = specific heat of water vapor at constant pressure (J/g)∼4.186 J/g Lv = Latent heat of vaporization (J/g)∼2500 J/g T = air temperature in ◦ C Twb = wet bulb temperature in ◦ C Eswb = saturation vapor pressure at the wet-bulb temperature (mb) P = atmospheric pressure at the surface ∼1013 mb at sea level

We can now use the following formula to obtain the saturation mixing ratio for the air: Ws = Es /P

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RH = W/Ws Now we can use the relative humidity to calculate the actual vapor pressure (E) of the air as follows: E = RH × Es The dew point temperature is then Td = [−430.22 + 237.7 × ln(E)]/[− ln(E) + 19.08] Let us now assume a psychrometer that gives the following readings at a pressure of 1013 mbar: ◦

T = 30 C ◦

Twb = 20 C Then, Eswb = 23.34 mbar Es = 42.31 mbar The mixing ratio becomes W = 0.019 Ws = 0.042 The relative humidity is then, RH = 0.45 (or 45%) The actual vapor pressure is then, E = 18.95 mbar and the dew point is ◦

Td = 16.7 C Instead of going through all these formulas, it is possible to use tables that give the dew point temperature as a function of the readings for different pressures.

DROUGHTS ARTHUR M. HOLST Philadelphia Water Department Philadelphia, Pennsylvania

A drought is a period of time during which weather is in one way or another excessively dry. A drought’s severity is determined by the degree of moisture deficiency in the affected area, as measured by various methods. Droughts are a standard, recurring, and normal feature of longterm climate. There are four generally accepted categories of drought: meteorological, socioeconomic, hydrologic, and agricultural.

Meteorological droughts involve a lack of precipitation during a given time period. Their specific definition depends mostly on the region in question; a lack of precipitation for some areas would be excessive precipitation in others. Some regions receive rain yearround, and some receive virtually none. Likewise, some regions receive precipitation consistently throughout the year, and others have seasonal precipitation patterns. A departure from any of these climatological characteristics as abnormally low precipitation can cause a meteorological drought. Meteorological droughts are usually measured in terms of their duration and in contrast to established precipitation averages for specified time periods for a specified area. This type of drought generally precedes the other three types. Agricultural droughts need not involve a severe lack of precipitation. They are marked by damage to crops and plants due to insufficient water supplies. Because water from rain and snow is more likely to run into creeks and rivers instead of filtering into the soil due to human intervention, agricultural droughts can sometimes occur in spite of noticeable rainfall. Depending on a plant’s species and stage of growth, it needs varying amounts of water from the soil; when the majority of crops cannot obtain the amount of water they need, an area is said to be undergoing an agricultural drought. This type of drought is most damaging to farmers and those in poor countries, and it generally comes after the onset of a meteorological drought. A hydrologic drought involves water shortages in reservoirs, lakes, and streams due to lack of precipitation. These droughts are measured by stream flow and water levels in local reservoirs. Local climate is not the only factor that causes a hydrologic drought; altered land usage, dams, and degraded soil quality can all have effects as well. Reduced precipitation in one area can cause a hydrologic drought in another because various areas are hydrologically connected by their rivers, lakes, and other bodies of water. The primary cause of this type of drought is generally a meteorological drought; hydrologic droughts usually come some time after agricultural droughts. The final category of drought is socioeconomic. This type of drought, like the other three, involves a lack of precipitation. It occurs when reduced precipitation causes a shortage of water as related to the demands of the local populace. The socioeconomic drought is the only type of drought that has a major effect on the general population, and it is generally the last of the four types to occur. Aside from lack of rain, the three most important variables to look at during a drought are air temperature, humidity, and circulation patterns in the atmosphere. Atmospheric circulation patterns that produce little or no precipitation are often associated with droughts. Climate abnormalities are another component of a drought. Precipitation levels that would be considered a drought in one area are normal in another that has a different climate. To understand the cause of a drought, scientists study the circulation patterns of the atmosphere across global distances, using computer-generated atmospheric simulator models.

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Droughts also have direct effects on communities that experience this phenomenon. Both water quality and cost are negatively affected by droughts. Changes in the taste and odor of drinking water can also occur. Those who draw their water from wells may have to drill more deeply to reach the lowered level of the water table. During a drought, water conservation is important. Restrictions on watering gardens, washing cars, and using sprinkler systems are applied when a drought emergency or warning is in effect. There are generally three stages of drought preparedness: drought watches, drought warnings, and drought emergencies. During a drought watch, no restrictions are enforced, but citizens are encouraged to curb water usage because the possibility of drought has been established for an area. During a drought warning, restrictions are still not enforced, but citizens are instructed to reduce water usage further in response to impending drought conditions. The final stage is a drought emergency. This is the most serious stage, often involving mandatory water usage guidelines to ensure that sufficient water is available for critical needs. At this stage, officials try to avoid local shortages by evenly distributing the water available. Droughts can have a great impact in many ways. There are three main types of impact they can have: economic, social, and environmental. A lack of water in the soil for crops can cause farmers great financial difficulty. The resulting decrease in crop production has a ripple effect on the economy, causing short-term and long-term problems. One of the biggest short-term problems is unemployment. Certain industries can also be affected by long-term problems. For instance, loss of tax revenue can hinder tourism. Brush and trees can become very dry, and an outbreak of destructive fires can result. Drought can harm the logging industry, fisheries, and hydroelectric power generation, all economic effects. It can also cause insect problems in agriculture, as well as erosion and disease. Environmental effects include reduced biodiversity, degraded air quality, and perhaps most importantly, devastating forest fires. Social impacts include induced emigration, rampant famine, and, indirectly, greater poverty. These are merely a few of the multitude of impacts, direct and indirect, that drought can have.

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Understanding and Defining Drought. Available: http://www.drought.unl.edu/whatis/concept.htm. Drought Information Center. Available: http://www.dep.state.pa. us/dep/subject/hotopics/drought/drtterm.htm.

DROUGHT INDICES MICHAEL J. HAYES Climate Impacts Specialist—National Drought Mitigation Center

INTRODUCTION Drought indices assimilate thousands of bits of data on rainfall, snowpack, streamflow, and other water supply indicators into a comprehensible big picture. A drought index value is typically a single number, far more useful than raw data for decision making. There are several indices that measure how much precipitation for a given period of time has deviated from historically established norms. Although none of the major indices is inherently superior to the rest in all circumstances, some indices are better suited than others for certain uses. For example, the Palmer Drought Severity Index has been widely used by the U.S. Department of Agriculture to determine when to grant emergency drought assistance, but the Palmer is better when working with large areas of uniform topography. Western states, with mountainous terrain and the resulting complex regional microclimates, find it useful to supplement Palmer values with other indices such as the Surface Water Supply Index, which takes snowpack and other unique conditions into account. The National Drought Mitigation Center is using a newer index, the Standardized Precipitation Index, to monitor moisture supply conditions. Distinguishing traits of this index are that it identifies emerging droughts months sooner than the Palmer Index and that it is computed on various time scales. Most water supply planners find it useful to consult one or more indices before making a decision. What follows is an introduction to each of the major drought indices in use in the United States and in Australia.

READING LIST PERCENT OF NORMAL All About Droughts. (2002). Available: http://205.156.54.206/om/ drought.htm. (March 13). Hanson, Ronald L. Evaporation and Droughts, U.S. Geological Survey. (2002). Available: http://geochange.er.usgs.gov/sw/ changes/natural/er/. (March 13). Impacts of Drought. (2002). Available: http://enso.unl.edu/ndmc/ enigma/impacts.htm. (March 13). McNab, A. and Karl, T. Climate and Droughts, National Oceanic and Atmospheric Administration. (2002). Available: http://geochange.er.usgs.gov/sw/changes/natural/drought/. (March 13). Stormfax Guide to Droughts, Stormfax. Available: http://www.stormfax.com/drought.htm. Understanding Your Risk: Impacts of Drought. Available: http://www.drought.unl.edu/risk/impacts.htm. All About Droughts. Available: http://www.nws.noaa.gov/om/drought.htm.

Overview: The percent of normal is a simple calculation well suited to the needs of TV weathercasters and general audiences. Pros: Quite effective for comparing a single region or season. Cons: Easily misunderstood, as normal is a mathematical construct that does not necessarily correspond with what we expect the weather to be. The percent of normal precipitation is one of the simplest measurements of rainfall for a location. Analyses using This article is a US Government work and, as such, is in the public domain in the United States of America.

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the percent of normal are very effective when used for a single region or a single season. Percent of normal is also easily misunderstood and gives different indications of conditions, depending on the location and season. It is calculated by dividing actual precipitation by normal precipitation—typically considered to be a 30-year mean—and multiplying by 100%. This can be calculated for a variety of time scales. Usually these time scales range from a single month to a group of months representing a particular season, to an annual or water year. Normal precipitation for a specific location is considered to be 100%. One of the disadvantages of using the percent of normal precipitation is that the mean, or average, precipitation is often not the same as the median precipitation, which is the value exceeded by 50% of the precipitation occurrences in a long-term climate record. The reason for this is that precipitation on monthly or seasonal scales does not have a normal distribution. Use of the percent of normal comparison implies a normal distribution where the mean and median are considered to be the same. An example of the confusion this could create can be illustrated by the long-term precipitation record in Melbourne, Australia, for the month of January. The median January precipitation is 36.0 mm (1.4 in.), meaning that in half the years less than 36.0 mm is recorded, and in half the years more than 36.0 mm is recorded. However, a monthly January total of 36.0 mm would be only 75% of normal when compared to the mean, which is often considered to be quite dry. Because of the variety in the precipitation records over time and location, there is no way to determine the frequency of the departures from normal or compare different locations. This makes it difficult to link a value of a departure with a specific impact occurring as a result of the departure, inhibiting attempts to mitigate the risks of drought based on the departures from normal and form a plan of response (1). STANDARDIZED PRECIPITATION INDEX (SPI) Overview: The SPI is an index based on the probability of precipitation for any time scale. Who uses it: Many drought planners appreciate the SPI’s versatility. Pros: The SPI can be computed for different time scales, can provide early warning of drought and help assess drought severity, and is less complex than the Palmer. Cons: Values based on preliminary data may change. Developed by: T.B. McKee, N.J. Doesken, and J. Kleist, Colorado State University, 1993. SPI Values 2.0+ 1.5 to 1.99 1.0 to 1.49 −.99 to .99 −1.0 to −1.49 −1.5 to −1.99 −2 and less

extremely wet very wet moderately wet near normal moderately dry severely dry extremely dry

Monthly maps: http://www.drought.unl.edu/monitor/ spi.htm; http://www.wrcc.dri.edu/spi/spi.html. The understanding that a deficit of precipitation has different impacts on groundwater, reservoir storage, soil moisture, snowpack, and streamflow led McKee, Doesken, and Kleist to develop the Standardized Precipitation Index (SPI) in 1993. The SPI was designed to quantify the precipitation deficit for multiple time scales. These time scales reflect the impact of drought on the availability of the different water resources. Soil moisture conditions respond to precipitation anomalies on a relatively short scale. Groundwater, streamflow, and reservoir storage reflect the longer-term precipitation anomalies. For these reasons, McKee et al. (2) originally calculated the SPI for 3-, 6-, 12-, 24-, and 48-month time scales. The SPI calculation for any location is based on the long-term precipitation record for a desired period. This long-term record is fitted to a probability distribution, which is then transformed into a normal distribution so that the mean SPI for the location and desired period is zero (3). Positive SPI values indicate greater than median precipitation, and negative values indicate less than median precipitation. Because the SPI is normalized, wetter and drier climates can be represented in the same way, and wet periods can also be monitored using the SPI. McKee et al. (2) used the classification system shown in the SPI values table to define drought intensities resulting from the SPI. McKee et al. (2) also defined the criteria for a drought event for any of the time scales. A drought event occurs any time the SPI is continuously negative and reaches an intensity of −1.0 or less. The event ends when the SPI becomes positive. Each drought event, therefore, has a duration defined by its beginning and end, and an intensity for each month that the event continues. The positive sum of the SPI for all the months within a drought event can be termed the drought’s ‘‘magnitude’’. Based on an analysis of stations across Colorado, McKee determined that the SPI is in mild drought 24% of the time, in moderate drought 9.2% of the time, in severe drought 4.4% of the time, and in extreme drought 2.3% of the time (2). Because the SPI is standardized, these percentages are expected from a normal distribution of the SPI. The 2.3% of SPI values within the ‘‘Extreme Drought’’ category is a percentage that is typically expected for an ‘‘extreme’’ event (Wilhite 1995). In contrast, the Palmer Index reaches its ‘‘extreme’’ category more than 10% of the time across portions of the central Great Plains. This standardization allows the SPI to determine the rarity of a current drought, as well as the probability of the precipitation necessary to end the current drought (2). The SPI has been used operationally to monitor conditions across Colorado since 1994 (4). Monthly maps of the SPI for Colorado can be found on the Colorado State University website (http://ulysses.atmos.colostate.edu/SPI.html). It is also being monitored at the climate division level for the contiguous United States by the National Drought

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Mitigation Center and the Western Regional Climate Center (WRCC). You can download the SPI program and sample files here. PALMER DROUGHT SEVERITY INDEX (THE PALMER; PDSI) Overview: The Palmer is a soil moisture algorithm calibrated for relatively homogeneous regions. Who uses it: Many U.S. government agencies and states rely on the Palmer to trigger drought relief programs. Pros: The first comprehensive drought index developed in the United States. Cons: Palmer values may lag emerging droughts by several months; less well suited for mountainous land or areas of frequent climatic extremes; complex—has an unspecified, built-in time scale that can be misleading. Developed by: W.C. Palmer, 1965. Weekly maps: http://www.cpc.ncep.noaa.gov/products/ analysis monitoring/regional monitoring/palmer .gif. Palmer Classifications 4.0 or more 3.0 to 3.99 2.0 to 2.99 1.0 to 1.99 0.5 to 0.99 0.49 to −0.49 −0.5 to −0.99 −1.0 to −1.99 −2.0 to −2.99 −3.0 to −3.99 −4.0 or less

extremely wet very wet moderately wet slightly wet incipient wet spell near normal incipient dry spell mild drought moderate drought severe drought extreme drought

In 1965, W.C. Palmer developed an index to measure the departure of the moisture supply (5). Palmer based his index on the supply-and-demand concept of the water balance equation, taking into account more than just the precipitation deficit at specific locations. The objective of the Palmer Drought Severity Index (PDSI), as this index is now called, was to provide measurements of moisture conditions that were standardized so that comparisons using the index could be made between locations and between months (5). The PDSI is a meteorological drought index, and it responds to weather conditions that have been abnormally dry or abnormally wet. When conditions change from dry to normal or wet, for example, the drought measured by the PDSI ends without taking into account streamflow, lake and reservoir levels, and other longer-term hydrologic impacts (6). The PDSI is calculated based on precipitation and temperature data, as well as the local Available Water Content (AWC) of the soil. From the inputs, all the basic terms of the water balance equation can be determined, including evapotranspiration, soil recharge, runoff, and moisture loss from the surface layer. Human impacts on the water balance, such as irrigation, are not considered.

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Complete descriptions of the equations can be found in the original study by Palmer (5) and in the more recent analysis by Alley (7). Palmer developed the PDSI to include the duration of a drought (or wet spell). His motivation was as follows: an abnormally wet month in the middle of a long-term drought should not have a major impact on the index, or a series of months with near-normal precipitation following a serious drought does not mean that the drought is over. Therefore, Palmer developed criteria for determining when a drought or a wet spell begins and ends, which adjust the PDSI accordingly. Palmer (5) described this effort and gave examples, and it is also described in detail by Alley (7). In near-real time, Palmer’s index is no longer a meteorological index but becomes a hydrological index referred to as the Palmer Hydrological Drought Index (PHDI) because it is based on moisture inflow (precipitation), outflow, and storage, and does not take into account the long-term trend (6). In 1989, a modified method to compute the PDSI was begun operationally (8). This modified PDSI differs from the PDSI during transition periods between dry and wet spells. Because of the similarities between these Palmer indices, the terms Palmer Index and Palmer Drought Index have been used to describe general characteristics of the indices. The Palmer Index varies roughly between −6.0 and +6.0. Palmer arbitrarily selected the classification scale of moisture conditions based on his original study areas in central Iowa and western Kansas (5). Ideally, the Palmer Index is designed so that a −4.0 in South Carolina has the same meaning in terms of the moisture departure from a climatological normal as a −4.0 in Idaho (7). The Palmer Index has typically been calculated on a monthly basis, and a long-term archive of the monthly PDSI values for every climate division in the United States exists with the National Climatic Data Center from 1895 through the present. In addition, weekly Palmer Index values (actually modified PDSI values) are calculated for the climate divisions during every growing season and are available in the Weekly Weather and Crop Bulletin. These weekly Palmer Index maps are also available on the World Wide Web from the Climate Prediction Center at http://www.cpc.ncep.noaa.gov/products/analysis monitoring/regional monitoring/palmer.gif. The Palmer Index is popular and has been widely used for a variety of applications across the United States. It is most effective measuring impacts sensitive to soil moisture conditions, such as agriculture (1). It has also been useful as a drought monitoring tool and has been used to trigger actions associated with drought contingency plans (1). Alley (7) identified three positive characteristics of the Palmer Index that contribute to its popularity: (1) it provides decision makers with a measurement of the abnormality of recent weather for a region; (2) it provides an opportunity to place current conditions in historical perspective; and (3) it provides spatial and temporal representations of historical droughts. Several states, including New York, Colorado, Idaho, and Utah, use the Palmer Index as one part of their drought monitoring systems.

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There are considerable limitations when using the Palmer Index, and these are described in detail by Alley (7) and Karl and Knight (6). Drawbacks of the Palmer Index include: • The values quantifying the intensity of drought and signaling the beginning and end of a drought or wet spell were arbitrarily selected based on Palmer’s study of central Iowa and western Kansas and have little scientific meaning. • The Palmer Index is sensitive to the AWC of a soil type. Thus, applying the index for a climate division may be too general. • The two soil layers within the water balance computations are simplified and may not be accurately representative of a location. • Snowfall, snow cover, and frozen ground are not included in the index. All precipitation is treated as rain, so that the timing of PDSI or PHDI values may be inaccurate in the winter and spring months in regions where snow occurs. • The natural lag between when precipitation falls and the resulting runoff is not considered. In addition, no runoff is allowed to take place in the model until the water capacity of the surface and subsurface soil layers is full, leading to an underestimation of runoff. • Potential evapotranspiration is estimated using the Thornthwaite method. This technique has wide acceptance, but it is still only an approximation. Several other researchers have presented additional limitations of the Palmer Index. McKee et al. (4) suggested that the PDSI is designed for agriculture but does not accurately represent the hydrological impacts resulting from longer droughts. Also, the Palmer Index is applied within the United States but has little acceptance elsewhere (9). One explanation for this is provided by Smith et al. (10), who suggested that it does not do well in regions where there are extremes in the variability of rainfall or runoff. Examples in Australia and South Africa were given. Another weakness in the Palmer Index is that the ‘‘extreme’’ and ‘‘severe’’ classifications of drought occur with a greater frequency in some parts of the country than in others (1). ‘‘Extreme’’ droughts in the Great Plains occur with a frequency greater than 10%. This limits the accuracy of comparing the intensity of droughts between two regions and makes planning response actions based on a certain intensity more difficult. CROP MOISTURE INDEX (CMI) Description: A Palmer derivative, the CMI reflects moisture supply in the short term across major crop-producing regions and is not intended to assess long-term droughts. Pros: Identifies potential agricultural droughts. Developed by: W.C. Palmer, 1968. Weekly maps: http://www.cpc.ncep.noaa.gov/products/ analysis monitoring/regional monitoring/cmi.gif.

The Crop Moisture Index (CMI) uses a meteorological approach to monitor week-to-week crop conditions. It was developed by Palmer (11) from procedures within the calculation of the PDSI. Whereas the PDSI monitors long-term meteorological wet and dry spells, the CMI was designed to evaluate short-term moisture conditions across major crop-producing regions. It is based on the mean temperature and total precipitation for each week within a climate division, as well as the CMI value from the previous week. The CMI responds rapidly to changing conditions, and it is weighted by location and time so that maps, which commonly display the weekly CMI across the United States, can be used to compare moisture conditions at different locations. Weekly maps of the CMI are available as part of the USDA/JAWF Weekly Weather and Crop Bulletin (http://www.usda.gov/oce/waob/jawf/wwcb.html). Because it is designed to monitor short-term moisture conditions affecting a developing crop, the CMI is not a good long-term drought monitoring tool. The CMI’s rapid response to changing short-term conditions may provide misleading information about long-term conditions. For example, a beneficial rainfall during a drought may allow the CMI value to indicate adequate moisture conditions, while the long-term drought at that location persists. Another characteristic of the CMI that limits its use as a long-term drought monitoring tool is that the CMI typically begins and ends each growing season near zero. This limitation prevents the CMI from being used to monitor moisture conditions outside the general growing season, especially in droughts that extend over several years. The CMI also may not be applicable during seed germination at the beginning of a specific crop’s growing season. SURFACE WATER SUPPLY INDEX (SWSI; PRONOUNCED ‘‘SWAZEE’’) Description: The SWSI is designed to complement the Palmer in the state of Colorado, where mountain snowpack is a key element of water supply; calculated by river basin, based on snowpack, streamflow, precipitation, and reservoir storage. Pros: Represents water supply conditions unique to each basin. Cons: Changing a data collection station or water management requires that new algorithms be calculated, and the index is unique to each basin, which limits interbasin comparisons. Developed by: Shafer and Dezman, 1982. The Surface Water Supply Index (SWSI) was developed by Shafer and Dezman (12) to complement the Palmer Index for moisture conditions across the state of Colorado. The Palmer Index is basically a soil moisture algorithm calibrated for relatively homogeneous regions, but it is not designed for large topographic variations across a region and it does not account for snow accumulation and subsequent runoff. Shafer and Dezman designed the SWSI to be an indicator of surface water conditions and described the index as ‘‘mountain

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water dependent’’, in which mountain snowpack is a major component. The objective of the SWSI was to incorporate both hydrological and climatological features into a single index value resembling the Palmer Index for each major river basin in the state of Colorado (Shafer and Dezman 1982). These values would be standardized to allow comparisons between basins. Four inputs are required within the SWSI: snowpack, streamflow, precipitation, and reservoir storage. Because it is dependent on the season, the SWSI is computed with only snowpack, precipitation, and reservoir storage in the winter. During the summer months, streamflow replaces snowpack as a component within the SWSI equation. The procedure to determine the SWSI for a particular basin is as follows: monthly data are collected and summed for all the precipitation stations, reservoirs, and snowpack/streamflow measuring stations over the basin. Each summed component is normalized using a frequency analysis gathered from a long-term data set. The probability of non-exceedence—the probability that subsequent sums of that component will not be greater than the current sum—is determined for each component based on the frequency analysis. This allows comparisons of the probabilities to be made between the components. Each component has a weight assigned to it depending on its typical contribution to the surface water within that basin, and these weighted components are summed to determine a SWSI value representing the entire basin. Like the Palmer Index, the SWSI is centered on zero and has a range between −4.2 and +4.2. The SWSI has been used, along with the Palmer Index, to trigger the activation and deactivation of the Colorado Drought Plan. One of its advantages is that it is simple to calculate and gives a representative measurement of surface water supplies across the state. It has been modified and applied in other western states as well. These states include Oregon, Montana, Idaho, and Utah. Monthly SWSI maps for Montana are available from the Montana Natural Resource Information System (http://nris.state.mt.us/wis/SWSInteractive/). Several characteristics of the SWSI limit its application. Because the SWSI calculation is unique to each basin or region, it is difficult to compare SWSI values between basins or regions (13). Within a particular basin or region, discontinuing any station means that new stations need to be added to the system and new frequency distributions need to be determined for that component. Additional changes in the water management within a basin, such as flow diversions or new reservoirs, mean that the entire SWSI algorithm for that basin needs to be redeveloped to account for changes in the weight of each component. Thus, it is difficult to maintain a homogeneous time series of the index (8). Extreme events also cause a problem if the events are beyond the historical time series, and the index will need to be reevaluated to include these events within the frequency distribution of a basin component.

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RECLAMATION DROUGHT INDEX Description: Like the SWSI, the RDI is calculated at the river basin level, incorporating temperature as well as precipitation, snowpack, streamflow, and reservoir levels as input. Who uses it: The Bureau of Reclamation; the State of Oklahoma as part of their drought plan. Pros: By including a temperature component, it also accounts for evaporation. Cons: Because the index is unique to each river basin, interbasin comparisons are limited. Developed by: The Bureau of Reclamation, as a trigger to release drought emergency relief funds. RDI Classifications 4.0 or more 1.5 to 4.0 1 to 1.5 0 to −1.5 −1.5 to −4.0 −4.0 or less

extremely wet moderately wet normal to mild wetness normal to mild drought moderate drought extreme drought

The Reclamation Drought Index (RDI) was recently developed as a tool for defining drought severity and duration, and for predicting the onset and end of periods of drought. The impetus to devise the RDI came from the Reclamation States Drought Assistance Act of 1988, which allows states to seek assistance from the Bureau of Reclamation to mitigate the effects of drought. Like the SWSI, the RDI is calculated at a river basin level, and it incorporates the supply components of precipitation, snowpack, streamflow, and reservoir levels. The RDI differs from the SWSI in that it builds a temperature-based demand component and a duration into the index. The RDI is adaptable to each particular region and its main strength is its ability to account for both climate and water supply factors. Oklahoma has developed its own version of the RDI and plans to use the index as one tool within the monitoring system designated in the state’s drought plan. The RDI values and severity designations are similar to the SPI, PDSI, and SWSI. DECILES Description: Groups monthly precipitation occurrences into deciles so that, by definition, ‘‘much lower than normal’’ weather cannot occur more often than 20% of the time. Who Uses It: Australia. Decile Classifications Deciles 1–2: lowest 20% Deciles 3–4: next lowest 20% deciles 5–6: middle 20% deciles 7–8: next highest 20% deciles 9–10: highest 20%

much below normal below normal near normal above normal much above normal

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THE EARTH OBSERVING SYSTEM: AQUA

Pros: Provides an accurate statistical measurement of precipitation. Cons: Accurate calculations require a long climatic data record. Developed by: Gibbs and Maher, 1967. Arranging monthly precipitation data into deciles is another drought-monitoring technique. It was developed by Gibbs and Maher (14) to avoid some of the weaknesses within the ‘‘percent of normal’’ approach. The technique they developed divided the distribution of occurrences over a long-term precipitation record into tenths of the distribution. They called each of these categories a decile. The first decile is the rainfall amount not exceeded by the lowest 10% of the precipitation occurrences. The second decile is the precipitation amount not exceeded by the lowest 20% of occurrences. These deciles continue until the rainfall amount identified by the tenth decile is the largest precipitation amount within the long-term record. By definition, the fifth decile is the median, and it is the precipitation amount not exceeded by 50% of the occurrences over the period of record. The deciles are grouped into five classifications. The decile method was selected as the meteorological measurement of drought within the Australian Drought Watch System because it is relatively simple to calculate and requires less data and fewer assumptions than the Palmer Drought Severity Index (10). In this system, farmers and ranchers can only request government assistance if the drought is shown to be an event that occurs only once in 20–25 years (deciles 1 and 2 over a 100-year record) and has lasted longer than 12 months (15). This uniformity in drought classifications, unlike a system based on the percent of normal precipitation, has assisted Australian authorities in determining appropriate drought responses. One disadvantage of the decile system is that a long climatological record is needed to calculate the deciles accurately. BIBLIOGRAPHY 1. Willeke, G., Hosking, J.R.M., Wallis, J.R., and Guttman, N.B. (1994). The National Drought Atlas. Institute for Water Resources Report 94–NDS–4, U.S. Army Corps of Engineers. 2. McKee, T.B., Doesken, N.J., and Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Preprints, 8th Conference on Applied Climatology, pp. 179–184. January 17–22, Anaheim, CA. 3. Edwards, D.C. and McKee, T.B. (1997). Characteristics of 20th century drought in the United States at multiple time scales. Climatology Report Number 97–2, Colorado State University, Fort Collins, CO. 4. McKee, T.B., Doesken, N.J., and Kleist, J. (1995). Drought monitoring with multiple time scales. Preprints, 9th Conference on Applied Climatology, pp. 233–236. January 15–20, Dallas, TX. 5. Palmer, W.C. (1965). Meteorological drought. Research Paper No. 45, U.S. Department of Commerce Weather Bureau, Washington, DC. 6. Karl, T.R. and Knight, R.W. (1985). Atlas of Monthly Palmer Hydrological Drought Indices (1931–1983) for the Contiguous United States. Historical Climatology Series 3–7, National Climatic Data Center, Asheville, North Carolina.

7. Alley, W.M. (1984). The palmer drought severity index: limitations and assumptions. Journal of Climate and Applied Meteorology 23: 1100–1109. 8. Heddinghaus, T.R. and Sabol, P. (1991). A review of the palmer drought severity index and where do we go from here? In: Proc. 7th Conf. on Applied Climatology, pp. 242–246. American Meteorological Society, Boston. 9. Kogan, F.N. (1995). Droughts of the late 1980s in the United States as derived from NOAA polar-orbiting satellite data. Bulletin of the American Meteorological Society 76(5): 655–668. 10. Smith, D.I., Hutchinson, M.F., and McArthur, R.J. (1993). Australian climatic and agricultural drought: Payments and policy. Drought Network News 5(3): 11–12. 11. Palmer, W.C. (1968). Keeping track of crop moisture conditions, nationwide: The new Crop Moisture Index. Weatherwise 21: 156–161. 12. Shafer, B.A. and Dezman, L.E. (1982). Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. In: Proceedings of the Western Snow Conference. Colorado State University, Fort Collins, CO, pp. 164–175. 13. Doesken, N.J., McKee, T.B., and Kleist, J. (1991). Development of a surface water supply index for the western United States. Climatology Report Number 91–3, Colorado State University, Fort Collins, CO. 14. Gibbs, W.J. and Maher, J.V. (1967). Rainfall deciles as drought indicators. Bureau of Meteorology Bulletin No. 48, Commonwealth of Australia, Melbourne. 15. White, D.H. and O’Meagher, B. (1995). Coping with exceptional droughts in Australia. Drought Network News 7(2): 13–17.

READING LIST Gommes, R. and Petrassi, F. (1994). Rainfall variability and drought in Sub-Saharan Africa since 1960. Agrometeorology Series Working Paper No. 9, Food and Agriculture Organization, Rome, Italy. Le Hou´erou, H.N., Popov, G.F., and See, L. (1993). Agrobioclimatic classification of Africa. Agrometeorology Series Working Paper No. 6, Food and Agriculture Organization, Rome, Italy. Wilhite, D.A. (1995). Developing a precipitation-based index to assess climatic conditions across Nebraska. Final report submitted to the Natural Resources Commission, Lincoln, NE. Wilhite, D.A. and Glantz, M.H. (1985). Understanding the drought phenomenon: The role of definitions. Water International 10(3): 111–120.

THE EARTH OBSERVING SYSTEM: AQUA NASA—Goddard Space Flight Center

EARTH SYSTEM SCIENCE Beginning in the 1960s, NASA pioneered the study of the atmosphere from the unique perspective of space This article is a US Government work and, as such, is in the public domain in the United States of America.

THE EARTH OBSERVING SYSTEM: AQUA

with the launch of its Television Infrared Observation Satellite (TIROS-1). Thanks to new satellite and computer technologies, it is now possible to study the Earth as a global system. Through their research, scientists are better understanding and improving their forecasting of short-term weather phenomena. Long-term weather and climate prediction is a greater challenge that requires the collection of better data over longer periods. Since climate changes occur over vast ranges of space and time, their causes and effects are often difficult to measure and understand. Scientists must obtain long-term data if they are to reach a full understanding of the interactions among the Earth’s physical and biological systems. NASA’s Earth Observing System (EOS) will help us to understand the complex links among air, land, water and life within the Earth system. WHAT IS AQUA? NASA’s commitment to studying the Earth as a global system continues with the Aqua spacecraft (originally called EOS PM-1), representing a key contribution by NASA to the U.S. Global Change Research Program. Aqua carries six state-of-the-art instruments to observe the Earth’s oceans, atmosphere, land, ice and snow covers, and vegetation, providing high measurement accuracy, spatial detail, and temporal frequency. This comprehensive approach to data collection enables scientists to study the interactions among the four spheres of the Earth system—the oceans, land, atmosphere, and biosphere. Aqua, Latin for ‘‘water,’’ is named for the large amount of information that the Aqua spacecraft will collect about the Earth’s water cycle. In particular, the Aqua data will include information on water vapor and clouds in the atmosphere, precipitation from the atmosphere, soil wetness on the land, glacial ice on the land, sea ice in the oceans, snow cover on both land and sea ice, and surface waters throughout the world’s oceans, bays, and lakes. Such information will help scientists improve the quantification of the global water cycle and examine such issues as whether or not the cycling of water might be accelerating. In addition to information about the water cycle, Aqua also provides information on many additional elements of the Earth system. For instance, Aqua enables studies of the fluxes of radiation from the Sun and from the Earth that combine to constitute the Earth’s radiation

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balance. It also enables studies of small particles in the atmosphere termed ‘‘aerosols’’ and such trace gases in the atmosphere as ozone, carbon monoxide, and methane. The trace gases each have a potential contribution to global warming, whereas the aerosols are more likely to have a cooling effect. Aqua also provides observations on vegetation cover on the land, phytoplankton and dissolved organic matter in the oceans, and the temperatures of the air, land, and water. All of these measurements have the potential to contribute to improved understanding of the changes occurring in the global climate and the role of the interactions among the various elements of the climate system. One of the most exciting of the potential practical benefits likely to derive from the Aqua data is improved weather forecasting. Aqua carries a sophisticated sounding system that allows determination of atmospheric temperatures around the world to an accuracy of 1◦ Celsius in 1-km-thick layers throughout the troposphere, the lowest portion of the atmosphere. The troposphere extends to an altitude of about 10–15 km, depending on location, and contains most of the global cloud cover. The anticipated 1◦ Celsius accuracy far exceeds current accuracies from satellite observations and, in conjunction with the moisture profiles also obtainable from the Aqua sounding system, offers the potential of improved weather fore-casting. NASA is working with the U.S. National Oceanic and Atmospheric Administration and the European Centre for MediumRange Weather Forecasts to facilitate the incorporation of the Aqua data in their weather forecasting efforts. INTERNATIONAL COLLABORATION Aqua is a joint project of the United States, Japan, and Brazil. THE SPACECRAFT The spacecraft was designed and built by TRW in Redondo Beach, California. Aqua is based on TRW’s modular, standardized AB1200 common spacecraft bus. This design features common subsystems scalable to the mission-specific needs of Aqua as well as future missions. Instrument payloads can be attached on a ‘‘mix and match’’ basis without changing the overall design or subsystem support requirements. THE INSTRUMENTS The Atmospheric Infrared Sounder (AIRS), built by BAE Systems, was provided by NASA’s Jet Propulsion Laboratory in Pasadena, California. AIRS is the highlighted instrument in the AIRS/AMSU-A/HSB triplet centered on measuring humidity, temperature, cloud properties, and the amounts of greenhouse gases throughout the atmosphere. AIRS/AMSU-A/HSB will improve weather forecasting, establish the connection between severe weather and climate change, examine whether the global water cycle is accelerating, and detect the effects of greenhouse gases.

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THE EARTH OBSERVING SYSTEM: AQUA

The Advanced Microwave Scanning Radiometer for EOS (AMSR-E), built by Mitsubishi Electronics Corporation, was provided by Japan’s National Space Development Agency. AMSR-E measures precipitation rate, cloud water, water vapor, sea surface winds, sea surface temperature, ice, snow, and soil moisture. The Advanced Microwave Sounding Unit (AMSU-A), built by Aerojet and provided by NASA’s Goddard Space Flight Center (GSFC) in Greenbelt, Maryland, obtains temperature profiles in the upper atmosphere (especially the stratosphere) and will provide a cloud-filtering capability for tropospheric temperature observations. The EOS AMSU-A is part of the closely coupled AIRS/AMSUA/HSB triplet. The Clouds and the Earth’s Radiant Energy System (CERES), built by TRW, was provided by NASA’s Langley Research Center in Hampton, Virginia. This instrument measures the Earth’s total thermal radiation budget, and, in combination with Moderate Resolution Imaging Spectro-radiometer (MODIS) data, provides detailed information about clouds. The first CERES instrument was launched on the Tropical Rainfall Measuring Mission (TRMM) satellite in November 1997; the second and third CERES instruments were launched on the Terra satellite in December 1999; and the fourth and fifth CERES instruments was on board the Aqua satellite launched in May 2002. The pairs of CERES on both Terra and Aqua satellites allow coincident measurements by one CERES scanning in lines perpendicular to the path of the satellite and by the other CERES scanning in lines at various angles with respect to the satellite’s path. The Humidity Sounder for Brazil (HSB), built by MatraMarconi, was provided by Brazil’s Instituto Nacional de Pesquisas Espaciais, the Brazilian Institute for Space Research. The HSB obtains humidity profiles throughout the atmosphere. The HSB is the instrument in the AIRS/AMSU-A/HSB suite that allows humidity measurements even under conditions of heavy cloudiness and haze. MODIS, built by Raytheon Santa Barbara Remote Sensing, was provided by GSFC. MODIS is a 36band spectroradiometer measuring visible and infrared radiation and obtaining data that is used to derive products ranging from vegetation, land surface cover, and ocean chlorophyll fluorescence, to cloud and aerosol properties, fire occurrence, snow cover on the land, and sea ice cover on the oceans. The first MODIS instrument was launched on board the Terra satellite. Aqua was launched in May 2002 aboard a Delta 792010L launch vehicle from Vandenberg Air Force Base, California. The stowed spacecraft is 8.8 ft (2.68 m) × 8.2 ft (2.49 m) × 21.3 ft (6.49 m). Deployed, Aqua is 15.8 ft (4.81 m) × 54.8 ft (16.70 m) × 26.4 ft (8.04 m). The spacecraft, at launch, weighed 6784 lbs with a full propellant load of 508 lbs and is powered by 4.6 kilowatts of electric power from its solar array. Aqua was launched into a circular 680-km orbit. Over a period of days after separation from the launch vehicle, it was commanded by the ground to raise its orbit to the prescribed 705-km (438-mile) orbit. This was necessary in order to allow for proper phasing of Aqua with other

spacecraft in orbit and the polar ground stations used for communications. The spacecraft was ultimately be positioned in a near-polar (98◦ ) orbit around the Earth in synchronization with the Sun, with its path over the ground ascending across the equator at the same local time every day, approximately 1:30 p.m. The early afternoon observation time contrasts with the 10:30–10:45 a.m. equatorial crossing time (descending in this case) of the Terra satellite. The two daytime crossing times account for why the Terra and Aqua satellites were originally named ‘‘EOS AM’’ and ‘‘EOS PM,’’ respectively. The combination of morning and afternoon observations allows studies concerning the diurnal variability of many of the parameters discussed above. MANAGEMENT Overall management of the Aqua mission is located at GSFC, which is managing the integration and testing of the spacecraft. The Aqua data is processed, archived, and distributed using distributed components of the Earth Observing System Data and Information System (EOSDIS). EOSDIS also provides the mission operations systems that perform the functions of command and control of the spacecraft and the instruments. NASA’s Kennedy Space Center is responsible for the launch operations, including Boeing’s Delta launch vehicle and the prelaunch integrated processing facility. The U.S. Air Force is responsible for all range-related matters. GSFC manages EOS for NASA’s Earth Science Enterprise (ESE), headquartered in Washington, DC. DATA PROCESSING AND DISTRIBUTION Aqua provides a major part of a 15-year environmental dataset focusing on global change. The Aqua instruments produce more than 750 gigabytes of data per day, which is equivalent to 75 personal computer hard disks at 10 gigabytes each per day. This massive amount of information is handled using EOSDIS, in addition to its present accumulation of nearly 3000 gigabytes per day. EOSDIS provides the high-performance computing resources needed to process, store, and rapidly transmit terabytes (thousands of gigabytes) of the incoming data every day. EOSDIS has several distributed sites that perform these functions: Distributed Active Archive Centers (DAACs) that process, store and distribute the data, and Science Investigator-led Processing Systems that process the data and send them to the DAACs for storage and distribution. EOSDIS uses an ‘‘open’’ architecture to allow insertion of new technology while enabling the system to support the changing mission and science needs throughout the EOS Program. GOALS AND OBJECTIVES NASA’s ESE identified several high-priority measurements that EOS should make to facilitate a better understanding of the components of the Earth system—the atmosphere, the land, the oceans, the polar ice caps,

ENTROPY THEORY FOR HYDROLOGIC MODELING

and the global energy budget. The specific objectives of Aqua include: • producing high-spectral resolution obtaining 1 K/ 1 km global root-mean-square temperature profile accuracy in the troposphere by 1 year after launch; • extending the improved TRMM rainfall characterization to the extra tropics; • producing global sea surface temperature daily maps under nearly all sky conditions for a minimum of 1 year; • producing large-scale global soil moisture distribution for regions with low vegetation; • producing calibrated global observations of the Earth’s continents and ocean surfaces 150 days after the mission is declared operational; • capturing and documenting three seasonal cycles of terrestrial and marine ecosystems and atmospheric and cloud properties; • producing three sets of seasonal/annual Earth radiation budget records; • producing improved measurements of the diurnal cycle of radiation by combining Aqua measurements with Terra measurements for months of overlap; • producing combined cloud property and radiation balance data to allow improved studies of the role of clouds in the climate system; and, • capturing, processing, archiving, and distributing Aqua data products, by 150 days after the mission is declared operational. A NEW PERSPECTIVE Complemented by Terra, aircraft and ground-based measurements, Aqua data enable scientists to distinguish between natural and human-induced changes. The EOS series of spacecraft are the cornerstone of NASA’s ESE, a

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long-term research effort to study the Earth as a global environment. More information on EOS and the science related to it can be found at the EOS Project Science Office website at http://eospso.gsfc.nasa.gov and at the Earth Observatory website at http://earthobservatory.nasa.gov. Further information on Aqua can be found at http://aqua.nasa.gov

ENTROPY THEORY FOR HYDROLOGIC MODELING VIJAY P. SINGH Louisiana State University Baton Rouge, Louisiana

INTRODUCTION Entropy theory has recently been employed in a broad range of applications in hydrology, and new applications continue to unfold. This paper revisits entropy theory and its application to hydrologic modeling. Hydrologic systems are inherently spatial and complex, and our understanding of these systems is less than complete. Many of the systems are either fully stochastic or part stochastic and part deterministic. Their stochastic nature can be attributed to randomness in one or more of the following components that constitute them: (1) system structure (geometry), (2) system dynamics, (3) forcing functions (sources and sinks), and (4) initial and boundary conditions. As a result, a stochastic description of these systems is needed, and entropy theory enables the development of such a description. Engineering decisions concerning hydrologic systems are frequently made with less than adequate information. Such decisions may often be based on experience, professional judgment, rules of thumb, crude analyses, safety factors, or probabilistic methods. Usually, decision-making under uncertainty tends to be relatively conservative. Quite often, sufficient data are not available to describe the random behavior of such systems. Although probabilistic methods allow for a more explicit and quantitative accounting of uncertainty, their major difficulty occurs due to the lack of sufficient or complete data. Small sample sizes and limited information render estimation of probability distributions of system variables by conventional methods difficult. This problem can be alleviated by using entropy theory that enables determining the least biased probability distributions based on limited knowledge and data. Where the shortage of data is widely rampant, as is normally the case in many countries, entropy theory is particularly appealing. Since the development of entropy theory by Shannon in the late 1940s and of the principle of maximum entropy (POME) by Jaynes in the late 1950s, there has been a proliferation in applications of entropy. The real impetus to entropy-based modeling in hydrology was, however, provided in the early 1970s, a great variety of entropybased applications have since been reported, and new applications continue to unfold. This article aims to revisit

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ENTROPY THEORY FOR HYDROLOGIC MODELING

entropy theory and to underscore its usefulness for both modeling and decision-making in hydrology. ENTROPY THEORY Entropy theory is comprised of three (1) Shannon entropy, (2) the principle entropy, and (3) the principle of minimum Before discussing these parts, it will be discuss briefly the meaning of entropy.

main parts: of maximum cross entropy. instructive to

Meaning of Entropy Entropy originated in physics. It is an extensive property like mass, energy, volume, momentum, charge, or number of atoms of chemical species, but unlike these quantities, it does not obey a conservation law. The entropy of a system is an extensive property, so the total entropy of the system equals the sum of the entropies of individual parts. The most probable distribution of energy in a system is the one that corresponds to the maximum entropy of the system. This occurs under the condition of dynamic equilibrium. During evolution toward a stationary state, the rate of entropy production per unit mass should be minimum, compatible with external constraints. This is the Prigogin principle. In thermodynamics, entropy is decomposed into two parts: (1) entropy exchanged between the system and its surroundings and (2) entropy produced in the system. According to the second law of thermodynamics, the entropy of a closed and isolated system always tends to increase. In hydraulics, entropy is a measure of the amount of irrecoverable flow energy that the hydraulic system expands to overcome friction. The system converts a portion of its mechanical energy to heat energy which then is dissipated to the external environment. Thus, the process equation in hydraulics expressing the energy (or head) loss, it can be argued, originates in the entropy concept. Entropy has been employed in thermodynamics as a measure of the degree of ignorance about the true state of a system. If there were no energy loss in a hydraulic system, the system would be orderly and organized. The energy loss and its causes make the system disorderly and chaotic. Thus, entropy can be interpreted as a measure of the amount of chaos within a system. Algebraically, it is proportional to the logarithm of the probability of the state of the system. The constant of proportionality is the Boltzmann constant, and this defines Boltzmann entropy. Shannon Entropy Shannon (1) developed the entropy theory for expressing information or uncertainty. To understand the informational aspect of entropy, we perform an experiment on a random variable X. There may be n possible outcomes x1 , x2 , . . . , xn , whose probabilities are p1 , p2 , . . . , pn ; P(X = x1 ) = p1 , P(X = x2 ) = p2 , . . . , P(X = xn ) = pn . These outcomes can be described by P(X) = ( p1 , p2 , . . . , pn );

n 

pi = 1; pi ≥ 0, i = 1, 2, . . . , n

i

(1)

If this experiment is repeated, the same outcome is not likely, implying that there is uncertainty as to the outcome of the experiment. Based on one’s knowledge about the outcomes, the uncertainty can be more or less. For example, the total number of outcomes is a piece of information, and the number of those outcomes of nonzero probability is another piece of information. The probability distribution of the outcomes, if known, provides a certain amount of information. Shannon (1) defined a quantitative measure of uncertainty associated with a probability distribution or the information content of the distribution in terms of entropy, H(P) or H(X), called Shannon entropy or informational entropy as H(X) = H(P) = −

n 

pi ln pi = E[− ln p]

(2)

i=1

If the random variable X is continuous, then Shannon entropy is expressed as


∞

H(X) = −

f (x) ln[ f (x)] dx


=−

0

ln[ f (x)] dF(x) = E[− ln f (x)]

(3)

where f (x) is the probability density function (PDF) of X, F(x) is the cumulative probability distribution function of X, and E [.] is the expectation of [.]. Thus, entropy is a measure of the amount of uncertainty represented by the probability distribution and is a measure of the amount of chaos or of the lack of information about a system. If complete information is available, entropy = 0; otherwise, it is greater than zero. The uncertainty can be quantified using entropy by taking into account all different kinds of available information. Shannon entropy is the weighted Boltzmann entropy. Principle of Maximum Entropy In search of an appropriate probability distribution for a given random variable, entropy should be maximized. In practice, however, it is common that some information about the random variable is available. The chosen probability distribution should then be consistent with the given information. There can be more than one distribution consistent with the given information. From all such distributions, we should choose the distribution that has the highest entropy. To that end, Jaynes (2) formulated the principle of maximum entropy (POME), a full account of it is presented in a treatise by Levine and Tribus (3). According to POME, the minimally prejudiced assignment of probabilities is that which maximizes entropy subject to the given information, that is, POME takes into account all of the given information and at the same time avoids considering of any information that is not given. If no information about the random variable is available, then all outcomes are equally likely, that is, pi = 1/n, i = 1, 2, 3, . . . , n. It can be shown that Shannon entropy is maximum in this case and may serve as an upper bound of entropy for all cases involving some

ENTROPY THEORY FOR HYDROLOGIC MODELING

information. In a more general case, let the information available about P or X be pi ≥ 0,

n 

pi = 1

(4)

where the cross entropy D is minimized. If no a priori distribution is available and if, according to Laplace’s principle of insufficient reason, Q is chosen as a uniform distribution U, then Eq. 7 takes the form

i=1

and

n 

D(P, U) = gr (xi )pi = ar

r = 1, 2, . . . , m

(5)

i=1

where m is the number of constraints, m + 1 ≤ n and gr is the rth constraint. Equations 4 and 5 are not sufficient to determine P uniquely. Therefore, there can be many distributions that satisfy Eqs. 4 and 5. According to POME, there will be only one distribution that will correspond to the maximum value of entropy, and this distribution can be determined using the method of Lagrange multipliers which will have the following form: pi = exp[−λ0 − λ1 g1 (xi ) − λ2 g2 (xi ) . . . − λm gm (xi )] i = 1, 2, . . . , n

(6)

where λi , i = 0, 1, 2, . . . , m, are Lagrange multipliers that are determined by using the information specified by Eqs. 4 and 5. Because the POME-based distribution is favored over those with less entropy among those that satisfy the given constraints, according to Shannon entropy as an information measure, entropy defines a kind of measure on the space of probability distributions. Intuitively, distributions of higher entropy represent more disorder, are smoother, are more probable, are less predictable, or assume less. The POME-based distribution is maximally noncommittal with regard to missing information and does not require invoking ergodic hypotheses. Principle of Minimum Cross Entropy According to Laplace’s principle of insufficient reason, all outcomes of an experiment should be considered equally likely, unless there is information to the contrary. On the basis of intuition, experience, or theory, a random variable may have an a priori probability distribution. Then, Shannon entropy is maximum when the probability distribution of the random variable is one which is as close to the a priori distribution as possible. This is called the principle of minimum cross entropy (POMCE) which minimizes Bayesian entropy (4). This is equivalent to maximizing Shannon entropy. To explain POMCE, let us suppose that we guess a probability distribution for a random variable x as Q = {q1 , q2 , . . . , qn } based on intuition, experience, or theory. This constitutes the prior information in the form of a prior distribution. To verify our guess, we take some observations X = (x1 , x2 , . . . , xn ) and compute some moments of the distribution. To derive the distribution P = {p1 , p2 , . . . , pn } of X, we take all the given information and make the distribution as near to our intuition and experience as possible. Thus, POMCE is expressed as D(P, Q) =

n  i=1

pi ln

pi qi

(7)

219

n 

 pi ln

i=1

 n    pi pi ln pi = ln n 1/n

(8)

i=1

Hence, minimizing D(P, U) is equivalent to maximizing Shannon entropy. Because D is a convex function, its local minimum is its global minimum. Thus, a posterior distribution P is obtained by combining a prior Q with the specified constraints. The distribution P minimizes the cross (or relative) entropy with respect to Q, defined by Eq. 7, where the entropy of Q is defined as in Eq. 2. Cross-entropy minimization results asymptotically from Bayes’ theorem. JOINT ENTROPY, CONDITIONAL ENTROPY, AND TRANSINFORMATION If there are two random variables X and Y whose probability distributions are P(x) = {p1 , p2 , . . . , pn } and Q(y) = {q1 , q2 , . . . , qn }, which are independent, then Shannon entropy of the joint distribution of X and Y is the sum of the entropies of the marginal distributions expressed as H(P, Q) = H(X, Y) = H(P) + H(Q) = H(X) + H(Y)

(9)

If the two random variables are dependent, then Shannon entropy of the joint distribution is the sum of the marginal entropy of one variable and the conditional entropy of the other variable conditioned on the realization of the first. Expressed algebraically, H(X, Y) = H(X) + H(Y | X)

(10)

where H(Y|X) is the conditional entropy of Y conditioned on X. The conditional entropy can be defined as H(X|Y) = −

m n  

p(xi , yj ) ln( p(xi | yj )

(11)

i=1 j=1

It is seen that if X and Y are independent, then Eq. 10 reduces to Eq. 9. Furthermore, the joint entropy of dependent X and Y will be less than or equal to the joint entropy of independent X and Y, that is, H(X, Y) ≤ H(X) + H(Y). The difference between these two entropies defines transinformation T(X, Y) or T(P, Q) expressed as T(X, Y) = H(X) + H(Y) − H(X, Y)

(12)

Transinformation represents the amount of information common to both X and Y. If X and Y are independent, T(X, Y) = 0. Substitution of Eq. 10 in Eq. 12 yields T(X, Y) = H(Y) − H(Y|X)

(13)

220

ENTROPY THEORY FOR HYDROLOGIC MODELING

Equation 13 states that stochastic dependence reduces the entropy of Y. ENTROPY AS A MODELING TOOL Although entropy theory has been applied in recent years to a variety of problems in hydrology, its potential as a decision-making tool has not been fully exploited. A brief discussion follows highlighting this potential. Fundamental to the concepts presented below is the need for probability distributions that can be derived by using entropy theory. Information Content of Data One frequently encounters a situation in which one exercises freedom of choice, evaluates uncertainty, or measures information gain or loss. The freedom of choice, uncertainty, disorder, information content, or information gain or loss has been variously measured by relative entropy, redundancy, and conditional and joint entropies employing conditional and joint probabilities. As an example, in the analysis of empirical data, the variance has often been interpreted as a measure of uncertainty and as revealing gain or loss in information. However, entropy is another measure of dispersion—an alternative to variance. This suggests that it is possible to determine the variance whenever it is possible to determine entropy measures, but the reverse is not necessarily true. However, variance is not the appropriate measure if the sample size is small. To measure correlation or dependence between any two variables, an informational coefficient of correlation r0 is defined as a function of transinformation, T0 , as r0 = [1 − exp(−2T0 )]0.5

(14)

The transinformation, given by Eq. 14, expresses the upper limit of common information between two variables and represents the level of dependence (or association) between the variables. It represents the upper limit of transferable information between the variables, and its measure is given by r0 . The ordinary correlation coefficient r measures the amount of information transferred between variables under specified assumptions, such as linearity and normality. An inference similar to that of the ordinary correlation coefficient, r, can be drawn by defining the amount (in percent) of transferred information by the ratio T/T0 , where T can be computed in terms of ordinary r. Criteria for Model Selection Usually, there are more models than one needs, and so a model has to be chosen. Akaike (5) formulated a criterion, called the Akaike information criterion (AIC), for selecting the best model from amongst several models as AIC = 2 log(maximized likelihood) + 2k

(15)

AIC provides a method of model identification and can be expressed as minus twice the logarithm of the maximum

likelihood plus twice the number of parameters used to find the best model. The maximum likelihood and entropy are uniquely related. When there are several models, the model that gives the minimum value of AIC should be selected. When the maximum likelihood is identical for two models, the model that has the smaller number of parameters should be selected, for that will lead to a smaller AIC and comply with the principle of parsimony. Hypothesis Testing Another important application of entropy theory is testing of hypotheses (6). By using Bayes’ theorem in logarithmic form, an evidence function is defined for comparing two hypotheses. The evidence in favor of a hypothesis over its competitor is the difference between the respective entropies of the competition and the hypothesis under test. Defining surprisal as the negative of the logarithm of the probability, the mean surprisal for a set of observations is expressed. Therefore, the evidence function for two hypotheses is obtained as the difference between the two values of the mean surprisal multiplied by the number of observations. Risk Assessment In common language, risk is the possibility of loss or injury and the degree of probability of such loss. Rational decision-making requires a clear and quantitative way of expressing risk. In general, risk cannot be avoided, and a choice has to be made between risks. There are different types of risk, such as business risk, social risk, economic risk, safety risk, investment risk, and occupational risk. To put risk in proper perspective, it is useful to clarify the distinction between risk, uncertainty, and hazard. The notion of risk involves both uncertainty and some kind of loss or damage. Uncertainty reflects the variability of our state of knowledge or state of confidence in a prior evaluation. Thus, risk is the sum of uncertainty plus damage. Hazard is commonly defined as a source of danger that involves a scenario identification (e.g., failure of a dam) and a measure of the consequence of that scenario or a measure of the ensuing damage. Risk encompasses the likelihood of converting that source into the actual delivery of loss, injury, or some form of damage. Thus, risk is the ratio of hazard to safeguards. By increasing safeguards, risk can be reduced, but it is never zero. Awareness of risk reduces risk, so awareness is part of safeguards. Qualitatively, risk is subjective and is relative to the observer. Risk involves the probability of a scenario and its consequence resulting from the occurrence of the scenario. Thus, one can say that risk is probability and consequence. Kaplan and Garrick (7) analyzed risk using entropy. HYDROLOGIC MODELING USING ENTROPY THEORY A historical perspective on entropy applications in environmental and water resources is given in Singh and Fiorentino (8) and Singh (9). Harmancioglu and Singh (10) discussed the use of entropy in water resources. A brief synopsis of entropy-based applications follows.

ENTROPY THEORY FOR HYDROLOGIC MODELING

Derivation of Probability Distributions Frequency distributions that satisfy the given information are often needed. Entropy theory is ideally suited to that end. POME has been employed to derive a variety of distributions; some have found wide applications in environmental and water resources. Many of these distributions have been summarized in Singh and Fiorentino (8) and by Singh (9). Let p(x) be the probability distribution of X that is to be determined. The information on X is available in terms of constraints given by Eq. 2. Then, the entropy-based distribution is given by Eq. 6. Substitution of Eq. 5 in Eq. 2 yields exp(λ0 ) = Z =

n 

 exp −

i=1

m 

spectra that have high-degree resolutions (13). The statistical characteristics that are used in stochastic model identification can also be estimated using MESA, thus permitting integration of spectral analysis and computations related to stochastic model development. Ulrych and Clayton (14) reviewed the principles of MESA and the closely related problem of autoregressive time series modeling. Shore (15) presented a comprehensive discussion of minimum cross-entropy spectral analysis. The relationship between spectrum W(f ) with frequency f of a stationary process x(t) and entropy H(f ) can be expressed as

 λj gj (xi )

H(f ) = (16)

j=1

where Z is called the partition function and λ0 is the zeroth Lagrange multiplier. The Lagrange parameters are obtained by differentiating Eq. 16 with respect to the Lagrange multipliers:

221

1 1 ln(2 w) + 2 4w




+w

ln[W(f )] df

(18)

w

where w is the frequency band. Equation 18 is maximized subject to the constraint equations given as autocorrelations until log m:
ρ(n) =

+w

W(f ) exp(i2 π fn
t) df ,

m ≤ n ≤ +m (19)

w

∂λ0 = −aj = E[ gj ], ∂λj

j = 1, 2, 3, . . . , m

where
t is the sampling time interval and i = (−1)1/2 . Maximization of Eq. 19 is equivalent to maximizing

∂ 2 λ0 = Var[gj ] ∂λ2j ∂ 2 λ0 = Cov[gj , gk ] ∂λj ∂λk


(17)

3

∂ λ0 = −µ3 [gj ] ∂λ3j where E[.] is the expectation, Var [.] is the variance, Cov [.] is the covariance, and is the third moment about the centroid, all for gj . When there are no constraints, then POME yields a uniform distribution. As more constraints are introduced, the distribution becomes more peaked and possibly skewed. In this way, entropy reduces from a maximum for the uniform distribution to zero when the system is fully deterministic. Parameter Estimation It is desirable to estimate parameters of a distribution in terms of the given constraints. Entropy theory accomplishes precisely that. Singh (11) described POME-based estimation for a number of probability distributions used in hydrology and environmental and water resources. He also discussed a comparison of the POME-based method with the methods of moments, maximum likelihood estimation, and some others. The comparison shows that the POME-based method is comparable to some methods and is better than others.

H(f ) =

+w

ln[W( f )] df

(20)

w

which is known as Burg entropy. The spectrum W(f ) can be expressed in terms of the Fourier series as W(f ) =

∞ 1  ρ(n) exp(i2π nf
t) 2 w n=∞

(21)

Substituting Eq. 21 in Eq. 20 and maximizing lead to MESA. Jaynes (16) has shown that MESA and other methods of spectral analysis, such as Schuster, Blackman–Tukey, maximum likelihood, Bayesian, and autoregressive (AR, ARMA, or ARIMA) models are not in conflict and that AR models are a special case of MESA. Krstanovic and Singh (17,18) employed MESA for long-term stream flow forecasting. Krstanovic and Singh (19,20) extended the MESA method to develop a real-time flood forecasting model. Padmanabhan and Rao (21,22) applied MESA to analyze rainfall and river flow time series. Rao et al. (23) compared a number of spectral analysis methods with MESA and found that MESA is superior. Eilbert and Christensen (24) analyzed annual hydrologic forecasts for central California and found that dry years might be more predictable than wet years. Dalezios and Tyraskis (25) employed MESA to analyze multiple precipitation time series. Regional Precipitation Analysis and Forecasting

Entropy-Spectral Analysis for Flow Forecasting Maximum entropy spectral analysis (MESA) was introduced by Burg (12). It has several advantages over conventional spectral analysis methods. It has short and smooth

The Burg algorithm or MESA can be applied to identify and interpret multistation precipitation data sets and to explore spectral features that lead to a better understanding of rainfall structure in space and time (25).

222

ENTROPY THEORY FOR HYDROLOGIC MODELING

Then, multistation rainfall time series can be extrapolated to develop regional forecasting capabilities. Grouping of River Flow Regimes An objective grouping of flow regimes into regime types can be employed as a diagnostic tool for interpreting the results of climate models and flow sensitivity analyses. By minimizing an entropy-based objective function (such as minimum cross entropy), a hierarchical aggregation of monthly flow series into flow regime types can, therefore, be effectively performed, which will satisfy chosen discriminating criteria. Such an approach was developed by Krasovskaia (26) who applied it to a regional river flow sample for Scandinavia for two different formulations of discriminating criteria. Basin Geomorphology Entropy plays a fundamental role in characterizing landscape. Using entropy theory for the morphological analysis of river basin networks, Fiorentino et al. (27) found that the connection between entropy and the mean basin elevation is linearly related to basin entropy. Similarly, the relation between the fall in elevation from the source to the outlet of the main channel and the entropy of its drainage basin, it was found, is linear and so also was the case between the elevation of a node and the logarithm of its distance from the source. When a basin was ordered following the Horton–Strahler ordering scheme, a linear relation was found between drainage basin entropy and basin order. This relation can be characterized as a measure of basin network complexity. Basin entropy, it was also found, is linearly related to the logarithm of the magnitude of the basin network. This relation led to a nonlinear relation between the network diameter and magnitude where the exponent, it was found, is related to the fractal dimension of the drainage network. Design of Hydrologic Networks The purpose of measurement networks is to gather information in terms of data. Fundamental to evaluating these networks is the ability to determine if the networks are gathering the needed information optimally. Entropy theory is a natural tool for that determination. Krstanovic and Singh (28,29) employed the theory for space and time evaluation of rainfall networks in Louisiana. The decision whether to keep or to eliminate a rain-gauge was based entirely on the reduction or gain of information at that gauge. Yang and Burn (30) employed a measure of information flow, called directional information transfer index (DIT), between gauging stations in the network. The value of DIT varies from zero, where no information is transmitted and the stations are independent, to one where no information is lost and the stations are fully dependent. Between two stations of one pair, the station that has the higher DIT value should be retained because of its greater capability of inferring information at the other side. Rating Curve Moramarco and Singh (31) employed entropy theory to develop a method for reconstructing the discharge

hydrograph at a river section where only water level is monitored and discharge is recorded at another upstream section. The method, which is based on the assumption that lateral inflows are negligible, has two parameters linked to remotely observed discharge and permits, without using a flood routing procedure and without the need of a rating curve at a local site, relating the local river stage to the hydraulic condition at a remote upstream section. CONCLUDING REMARKS Entropy theory permits determining of the least biased probability distribution of a random variable, subject to the available information. It suggests whether or not the available information is adequate and, if not, then additional information should be sought. In this way, it brings the model, the modeler, and the decisionmaker closer. As an objective measure of information or uncertainty, entropy theory allows communicating with nature, as illustrated by its application to the design of data acquisition systems, the design of environmental and hydrologic networks, and the assessment of the reliability of these systems or networks. In a similar vein, it helps better understand the physics or science of natural systems, such as landscape evolution, geomorphology, and hydrodynamics. A wide variety of seemingly disparate or dissimilar problems can be meaningfully solved by using entropy. BIBLIOGRAPHY 1. Shannon, C.E. (1948). A mathematical theory of communications, I and II. Bell System Technical Journal 27: 379–443. 2. Jaynes, E.T. (1957). Information theory and statistical mechanics, I. Physical Review 106: 620–630. 3. Levine, R.D. and Tribus, M. (Eds.). (1978). The Maximum Entropy Formalism. The MIT Press, Cambridge, MA, p. 498. 4. Kullback, S. and Leibler, R.A. (1951). On information and sufficiency. Annals of Mathematical Statistics 22: 79–86. 5. Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. Proceedings, 2nd International Symposium on Information Theory. B.N. Petrov and F. Csaki. (Eds.). Publishing House of the Hungarian Academy of Sciences, Budapest, Hungary. 6. Tribus, M. (1969). Rational Description: Decision and Designs. Pergamon Press, New York. 7. Kaplan, S. and Garrick, B.J. (1981). On the quantitative definition of risk. Risk Analysis 1(1): 11–27. 8. Singh, V.P. and Fiorentino, M. (Eds.). (1992). Entropy and Energy Dissipation in Water Resources. Kluwer Academic Publishers, Dordrecht, the Netherlands. 9. Singh, V.P. (1998). Entropy-Based Parameter Estimation in Hydrology. Kluwer Academic Publishers, Boston, MA. 10. Harmancioglu, N.B. and Singh, V.P. (1998). Entropy in environmental and water resources. In: Encyclopedia of Hydrology and Water Resources. R.W. Hershey and R.W. Fairbridge (Eds.). Kluwer Academic Publishers, Boston, MA, pp. 225–241. 11. Singh, V.P. (1998). The use of entropy in hydrology and water resources. Hydrological Processes 11: 587–626.

EVAPORATION 12. Burg, J.P. (1975). Maximum entropy spectral analysis. Unpublished Ph.D. thesis, Stanford University, Palo Alto, CA, p. 123. 13. Fougere, P.F., Zawalick, E.J., and Radoski, H.R. (1976). Spontaneous life splitting in maximum entropy power spectrum analysis. Physics of the Earth and Planetary Interiors 12: 201–207. 14. Ulrych, T. and Clayton, R.W. (1976). Time series modeling and maximum entropy. Physics of the Earth and Planetary Interiors 12: 188–199. 15. Shore, J.E. (1979). Minimum cross-entropy spectral analysis. NRL Memorandum Report 3921, Naval Research Laboratory, Washington, DC. 16. Jaynes, E.T. (1982). On the rationale of maximum entropy methods. Proceedings of the IEEE 70: 939–952. 17. Krstanovic, P.F. and Singh, V.P. (1991). A univariate model for long-term streamflow forecasting: 1. Development. Stochastic Hydrology and Hydraulics 5: 173–188. 18. Krstanovic, P.F. and Singh, V.P. (1991). A univariate model for long-term streamflow forecasting: 2. Application. Stochastic Hydrology and Hydraulics 5: 189–205. 19. Krstanovic, P.F. and Singh, V.P. (1993). A real-time flood forecasting model based on maximum entropy spectral analysis: 1. Development. Water Resources Management 7: 109–129. 20. Krstanovic, P.F. and Singh, V.P. (1993). A real-time flood forecasting model based on maximum entropy spectral analysis: 2. Application. Water Resources Management 7: 131–151. 21. Padmanabhan, G. and Rao, A.R. (1986). Maximum entropy spectra of some rainfall and river flow time series from southern and central India. Theoretical and Applied Climatology 37: 63–73. 22. Padmanabhan, G. and Rao, A.R. (1988). Maximum entropy spectral analysis of hydrologic data. Water Resources Research 24(9): 1591–1533. 23. Rao, A.R., Padmanabhan, G., and Kashyap, R.L. (1980). Comparison of recently developed methods of spectral analysis. Proceedings, Third International Symposium on Stochastic Hydraulics. Tokyo, Japan, pp. 165–175. 24. Eilbert, R.F. and Christensen, R.O. (1983). Performance of the entropy minimax hydrological forecasts for California water years 1948–1977. Journal of Climate & Applied Meteorology 22: 1654–1657. 25. Dalezios, N.R. and Tyraskis, P.A. (1989). Maximum entropy spectra for regional precipitation analysis and forecasting. Journal of Hydrology 109: 25–42. 26. Krasovskaia, R. (1997). Entropy-based grouping of river flow regimes. Journal of Hydrology 202: 173–1191. 27. Fiorentino, M., Claps, P., and Singh, V.P. (1993). An entropybased morphological analysis of river basin networks. Water Resources Research 29(4): 1215–1224. 28. Krstanovic, P.F. and Singh, V.P. (1992). Evaluation of rainfall networks using entropy: 1. Theoretical development. Water Resources Management 6: 279–293. 29. Krstanovic, P.F. and Singh, V.P. (1992). Evaluation of rainfall networks using entropy: II. Application. Water Resources Management 6: 295–314. 30. Yang, Y. and Burn, D.H. (1984). An entropy approach to data collection network design. Journal of Hydrology 157: 307–324. 31. Moramarco, T. and Singh, V.P. (2001). Simple method for relating local stage and remote discharge. Journal of Hydrologic Engineering, ASCE 6(1): 78–81.

223

EVAPORATION THEODORE A. ENDRENY SUNY-ESF Syracuse, New York

Evaporation of water is a solar energy driven phase change from liquid to vapor that maintains the hydrologic cycle by transferring liquid water at the earth’s surface to water vapor in the atmosphere, where it may lift, condense, and precipitate to earth as liquid water. In this discussion, evaporation is defined to include the closely associated transpiration process as a subcategory. The coupled processes are often called as evapotranspiration, or ET, where transpiration focuses on the transport of liquid water through the plant roots, stem, and leaf prior to evaporation through the leave’s stomata. Further, when the discussion does not make a clear distinction between potential and actual evaporation, potential should be assumed. Potential evaporation refers to the amount of water that available energy and diffusion processes can transfer into atmospheric vapor, which is typically greater then the amount actually transferred due to limits on soil water volumes and resistances in the path.

PHYSICAL CONTROLS ON EVAPORATION Evaporation is effectively a two-step process that first, requires that water changes phase to a vapor state and second, requires that the vapor is transported by advection and/or diffusion into unsaturated air. The phase change alone does not completely satisfy the requirement for evaporation when dynamic equilibrium exists at the boundary between liquid and vapor and condensation of the vapor saturated air returns liquid water to the surface to maintain no net water loss. Transport, therefore, ensures removal of the water vapor and a net loss of heat and mass from the liquid surface. In the vapor state, evaporated water is invisible to the human eye, which detects wavelengths between 0.4 and 0.7 µm, but is detectable in other areas of the electromagnetic spectrum. As such, though clouds are derived from and contain evaporated water, they are not vapor and instead reveal condensed water droplets that geometrically scatter light. The first step in changing the phase of water from liquid to vapor requires an input of solar energy, which is stored at the surface and supports nighttime evaporation. Nearly 52% of solar energy absorbed at the earth’s surface is used for vaporization. This energy is called latent heat of vaporization, or λ, and is a function of water temperature. When the phase changes directly from frozen water to vapor, known as sublimation, a greater amount of energy is required. Phase changes require energy to separate the hydrogen bond based, attractive intermolecular forces holding water molecules in an organized pattern and close proximity. Latent heat is a name that suggests dormant, or invisible, and is used to indicate that, unlike the measurable effect of sensible heat on air temperature, the

224

EVAPORATION

solar energy used in evaporation remains ‘hidden’ from thermometer measurement. As an example, at the standard pressure of 1013.3 milibar (mb), heating liquid water from 0 to 100 ◦ C requires 4186.8 joules (J) of heat per kilogram of water per degree C temperature change and is detectable with a thermometer. In contrast, the latent heat of vaporization converting 100 ◦ C water into 100 ◦ C vapor does not have a measurable impact on water temperature. The latent heat, in megajoules per kilogram (MJ kg−1 ), required per ◦ C of water temperature, T, is given as λ = 2.501 − 0.002361 · T It is apparent that the majority of heat input to evaporate water, whether at 0 ◦ C or 99 ◦ C, is that for the phase change. A relatively constant 1350 Js−1 m−2 stream of solar energy entering the earth’s upper atmosphere provides energy to evaporate water just like a stove can boil and evaporate water. When 50% of this solar constant strikes the earth’s surface after atmospheric attenuation (e.g., scattering and reflection), it requires approximately 1 hour and 10 minutes to generate the latent heat needed to evaporate 1 kg of water at 20 ◦ C. Latent heat, though not detectable as affecting air temperature, is stored with the vapor in greater vibrational, rotational, and translational movement of vapor molecules. The removal of this vapor from the liquid, therefore, causes a measurable loss of energy and temperature from the remaining liquid, producing a cooling effect. A familiar example of this process is that wet skin, from sweat or a shower, cools faster in moving rather than still air because the wind speeds evaporation that takes heat from the body. Knowing that heat is used for evaporation, it is now clear that a covered pot will boil faster than a counterpart uncovered pot do to a lower loss of heat to the net evaporation of water. Heat stored in vapor is later released back into the environment when the vapor vibrational speeds slow, and it condenses into water, called latent heat of condensation. When vapor passes directly to solid frozen water, called deposition, a greater amount of heat stored in rotational, vibrational, and translational molecular movement is released into the environment. The second physical step in evaporation is transport by advection and/or diffusion, which provides the net movement of water molecules from the liquid water surface of soil, plants, or lakes to atmospheric vapor. Vapor and wind gradients exert the principal controls on removal of water vapor beyond the saturated layer of air that maintains condensation–evaporation equilibrium dynamics. Fundamental barriers to transport beyond the layer of dynamic equilibrium include stagnant air and saturated air above the evaporating surface, conditions readily created within and at the surface of soil and plant systems. Net evaporation therefore increases with steeper wind and saturation gradients, which are defined as the change in wind or saturation with distance above the evaporating surface. Work on fluid velocity and turbulence gradients in the mid-1900s by Prandtl and von Karman has been used to estimate momentum, sensible heat, and vapor transport from wind speed measurements.

Estimates of atmospheric wind and vapor conditions above the evaporating surface provide important data for estimating wind and saturation gradients and predicting barriers to vapor transport and net evaporation. Meteorological stations are frequently equipped with anemometers and thermometers at 2 meters (m) above the ground surface to help establish the wind and vapor gradients controlling evaporation. Wind profiles, it is assumed, begin with stagnant air at the noslip boundary, or zero-plane displacement height, and increase logarithmically. In a landscape broken by tree canopies, a 2 m wind measurement may be inadequate to represent observations. Research has shown that dynamic turbulence and eddies created by such forested heterogeneity result in increased wind and evaporation rates that exceed the estimated atmospheric potential. Based on Dalton’s work on individual pressures of multiple atmospheric gases summing to the observed atmospheric pressure, vapor is often reported as a partial pressure and can be derived from measurements of temperature. In the following equation, vapor pressure is reported in kilopascals (kPa) and temperature in ◦ C. Initially dry warm air can absorb more water than initially dry cold air before reaching saturation.  e = 0.6108 exp

17.27 T 237.3 + T



The dry-bulb temperature is used to estimate the total amount of vapor the air could absorb prior to saturation; the dew point temperature represents the temperature to which the air must cool for total saturation. When the dry-bulb and dew point temperatures are equal, the air is fully saturated. The ratio of actual to saturated vapor pressures is the relative humidity. The dew point temperature is estimated by using a psychrometer that measures the difference between dry-bulb and wet-bulb thermometers, called the wet-bulb depression, together with lookup tables relating wet-bulb depression to dew point temperature. The dry-bulb is a normal thermometer measuring air temperature, but a moist piece of cloth typically covers the wet-bulb, and evaporation of the water from the cloth causes the temperature to drop. Chilled mirrors hygrometers, hair hygrometers, and vapor pressure sensors are also used to detect the vapor content in the air. EVAPORATION MEASUREMENT AND ESTIMATION Evaporation is fundamental to both energy and water balances, yet despite the importance of evaporation to hydrologic assessment of the paths, quantities, and quality of water in the lithosphere, biosphere, and atmosphere, the complexity of the process has prevented easy or exact techniques for measuring and estimating it. The relative accuracy of yearly river basin evaporation estimates is high, as the estimate time frame and spatial area become smaller, but the simple application of energy and water balance models to solve for evaporation becomes less tractable. A variety of measurement and estimation techniques have been developed for these smaller scales,

EVAPORATION

such as hourly, daily, and monthly evaporation from reservoirs, farm fields, and single plants. In general, evaporative fluxes from the land surface are more difficult to measure than from open water, given that an immeasurable number of irregular, tiny and unique soil and leaf surfaces are involved in this phase change and that suction gradients draw water to this evaporating interface from unobserved reserves of unknown volume. Fluxes from open water, though relatively homogeneous, still provide challenges when subsurface inflows and outflows are poorly understood and significant and wind and water advected energy influencing evaporation is heterogeneously distributed. Hence, the numerous methods developed for estimating evaporation are categorized based on the type of surface, availability of water, and the importance of stored energy, water-advected energy, and air-advected energy. Actual evaporation can be measured by using a water balance approach, a turbulent-transfer approach, a potential evaporation approach, or a water quality approach. The water balance approach can function with measurements of a mass balance being kept for a water pan, such as a the Class-A Pan of the National Weather Service, a soil and plant system, such as in a weighing lysimeter, or of a small, enclosed atmosphere. Turbulent-transfer methods, which derive evaporation from estimates of momentum or heat flux, can provide estimates for larger heterogeneous areas, but assume that the air sampled by the field instrumentation used for the Bowen ratio or eddy-correlation method is well mixed to represent the upwind land area by a given fetch. Water quality methods include techniques that track concentrations of dissolved solids, which enrich when evaporation removes the water solvent, and isotope tracer studies that show heavier isotopes are enriched by preferred evaporation of lighter isotopes. Sap flow monitoring in trees provides another technique to measure the flux of water from the ground to the atmosphere. Mathematical estimates of evaporation rates have been approached by using an equally wide variety of techniques and include temperature-based, aerodynamicbased, radiation-based, and combination-based methods. Temperature-based methods, such as the monthly timestep Thornthwaite equation, use air temperature and length of day, as well as an assumed humidity, to compute the potential evaporation, and they have been adapted to suit several different climates and regions. Aerodynamic methods assume that solar radiation is not limiting and consider only wind speed and turbulence as controls on the transport of water vapor away from the surface. Radiation-based methods likewise assume that wind turbulence and eddies are not limiting and use measured incoming radiation and the latent heat of vaporization to compute evaporation flux. A popular form of this equation is the Priestly–Taylor, which increased it by a factor of 30% to account for added aerodynamic transfer. The combination method, known most extensively for the Penman–Monteith equation, uses air temperature, net radiation, wind speed, and relative humidity vapor gradients to derive minute by minute and daily evaporation rates.

225

HYDROLOGIC IMPACTS OF EVAPORATION Observations of terrestrial river discharge reveal that more water precipitates on land than evaporates from land and that more water evaporates from oceans than precipitates on oceans. Precipitation totals may vary from year to year, but evaporative demands are rather steady, which creates a greater relative fluctuation in river discharge than in precipitation. This is illustrated by considering a 20% decrease in annual precipitation from 100 to 80 cm, where 50 cm went to evaporation in both years, and discharge dropped by 40% from 50 to 30 cm. Evaporation and its impact on liquid and vapor water volumes and the partitioning of solar energy into latent and sensible heat create and maintain a range of climatic conditions, from microclimates on the scale of a tree canopy to macroclimates that describe the global distribution of plants. The volume of water evaporated from the ocean and land surface is greatest at the meteorological equator, or intertropical convergence zone (ITCZ), and smallest at the poles, which is the result of a similar longitudinal distribution of insolation intensity. Sinking Hadley cell air at the 30◦ latitude belts, which warms to absorb greater amounts of water vapor, is the cause of a belt of deserts in this region. The distribution of incoming solar radiation, which is greatest at the equator and smallest at the poles, is the driving force explaining the meridional (across lines of latitude) distribution of evaporation. Wind transport of this evaporated vapor from the equatorial region to the midlatitudes and poles, where latent energy is released to the atmosphere as sensible heat during condensation, is one of only a few processes that help to maintain the earth’s energy balance. Global water balance numbers reveal that a relatively small volume of evaporated vapor resides in the atmosphere. The earth’s atmosphere has a volume of 12,900 km3 , and contains just 0.001% of all global water. As evaporated vapor, it receives 71,000 km3 yr−1 from land, 1000 km3 yr−1 from lakes, and 505,000 km3 yr−1 from oceans, and this flux rate into its total volume equals a residence time of 8.2 days, or just over a week before evaporated water precipitates. The atmospheric vapor precipitates at a volumetric rate of 577 km3 yr−1 , of which 119,000 km3 yr−1 falls on land. Observation and estimation of river discharge at 47,000 km3 yr−1 was used to deduce the amount evaporated from land, which is 61%

Table 1. Continental Average Estimated Evaporation Continent

Area, km2

Antarctica Europe Asia South America North America Africa Australia Total Land

14,100,000 10,000,000 44,100,000 17,900,000 24,100,000 29,800,000 7,600,000 148,900,000

Evaporation, mm yr−1

Evaporation, %

28 375 420 946 403 582 420 480

17 57 60 60 62 84 94 64

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EVAPOTRANSPIRATION Table 2. Average Estimated Evaporation Based on Studies of Precipitation and Runoff

Watershed by River Name

Continent [Nation(s)]

Brahmaputra Irrawaddy Yangtzekiang Amazon Orinoco Lena Mekong Yenesei Ganges Saint Lawrence Amur Congo Ob Mississippi La Plata Average a

Asia (Tibet/Bangladesh) Asia (Burma) Asia (China) South America (six nations) South America (Venezuela) Asia (Russia) Asia (China) Asia (Russia) Asia (China) North America (Canada, U.S.) Asia (Russia) Africa (7 nations) Asia (Russia) North America (U.S.) South America (five nations) –

Basin Size, km2

Evaporationa , %

589,000 431,000 1,970,000 7,180,000 1,086,000 2,430,000 795,000 2,599,000 1,073,000 1,030,000 1,843,000 3,822,000 2,950,000 3,224,000 2,650,000 2,224,800

35 40 50 53 54 54 57 58 58 67 68 75 76 79 80 60

Evaporation may include basin transfers because it was not directly measured but derived from precipitation and runoff measurements.

evaporating, and this differs from the continental average of 64% reported in Table 1. For the continental United States, which contains deserts in Arizona and rain forests in Washington, the average annual percentage of precipitation converted to evaporation is approximately 62%. This value is similar to global patterns but varies considerably from that measured on other continents (see Table 1) and larger watersheds (see Table 2). The agricultural impact of evaporation is both the cause of nutrient uptake and growth in plants, as well as the loss of soil water and plant stress. Maintenance of optimal water levels in the soil, called field capacity, when gravitational water has drained, is the goal of many irrigation projects. If irrigation causes evaporation to exceed local precipitation, then salts will be drawn to the soil surface, which often creates osmotic gradients at the root interface that kill the agricultural crop. Agricultural irrigation to satisfy the high evaporation demand of sunny agricultural land, such as California’s Central Valley, has become a direct competitor for use as a public water supply. READING LIST Shuttleworth, W.J. (1992). Evaporation. In: Handbook of Hydrology. D.R. Maidment (Ed.). McGraw Hill, New York. Dingman, S.L. (1994). Physical Hydrology. Prentice-Hall, Englewood Cliffs, NJ.

EVAPOTRANSPIRATION JOSE O. PAYERO University of Nebraska-Lincoln North Platte, Nebraska

Liquid water from a surface can be transformed into water vapor by either evaporation or by transpiration.

Evaporation is the process for converting liquid water to water vapor and removing it from the evaporating surface. Transpiration is the vaporization of water contained in plant tissues and the removal of vapor to the atmosphere through leaf stomata (1,2). Evaporation and transpiration occur simultaneously in cropped surfaces, and there is no easy way of quantifying the magnitude of each component. For practical applications, such as irrigation scheduling and irrigation system design, it has been more useful to consider both processes combined. The combination of these two processes is called evapotranspiration. The proportion of each component in a cropped surface is affected by factors such as vegetative cover, available water in the soil, and surface wetness. For an annual crop like corn, evaporation is the dominant component of evapotranspiration at the beginning of the season when the soil surface is exposed to solar radiation. As the crop grows and the canopy covers the surface, evaporation is minimized, and transpiration becomes the dominant component. IMPORTANCE OF EVAPOTRANSPIRATION Evapotranspiration is an important process in agriculture and other natural sciences, such as hydrology, because it is an important component of the hydrologic cycle. It represents the water that is effectively lost from the earth’s surface, and can no longer be controlled by humans. This type of water loss is often called consumptive use. Other types of processes that usually cause water losses from a given area on the earth’s surface, such as runoff and deep percolation, do not involve a change in the physical state of water and therefore, water can still be controlled to some degree by humans. Plants use water as a solvent and transport mechanism for nutrients and other chemicals, as a reagent for the chemical reactions involved in their physiological processes (such as photosynthesis), and as a component of cell cytoplasm, which allows plant tissues to stay

EVAPOTRANSPIRATION

turgid. Most of the water consumed by plants, however, is used in evapotranspiration. Evapotranspiration has the important function of regulating the temperature of plants, keeping them cool within a temperature range that favors growth. When the water supply in the soil is limited, for instance, plants respond by closing their stomata. This restricts the rate of evapotranspiration, and the temperature of the canopy tends to increase (3). This increase in canopy temperature has been used to estimate the rate of evapotranspiration of crops and as a way to detect crop water stress for irrigation scheduling (4). Because most of the water consumed by plants is lost in evapotranspiration, it takes a considerable amount of water for a crop to produce one unit weight of dry matter, as shown for different crops in (Fig. 1). Researchers have shown that crop yield is often linearly related to crop evapotranspiration, up to the point where yield is limited by factors other than water (6). Therefore, if evapotranspiration is limited, yield is usually reduced. For this reason, in regions where rainfall is not sufficient to provide enough water for crops to keep evapotranspirating at a nonlimited rate, irrigation is required to obtain adequate crop yields. The nonlimited rate of evapotranspiration, however, can also be maintained by applying excess water. Application of excess water, however, has been linked to undesired side effects such as drainage problems, salinization of soils, soil erosion, and pollution of surface and groundwaters. In places where irrigation water needs to be pumped, pumping excess water also represents higher production cost. Therefore, it is considered ideal to schedule irrigation according to crop water needs. This requires, among other things, good knowledge of crop evapotranspiration rates. MEASURING EVAPOTRANSPIRATION

Units of water per unit dry matter

Measuring the rate of evapotranspiration of crops and other surfaces is complex and is a subject that has attracted considerable research. Many methods have been devised to measure and estimate evapotranspiration. Methods for measuring evapotranspiration include the use of lysimeters, scintillometers, micrometeorological techniques such as the Bowen ratio and eddy covariance

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Figure 1. Unit weight of evapotranspirated water needed per unit weight of dry matter produced by different crops (adapted from Ref. 5).

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methods, and measurement of sap flow. Methods to measure evapotranspiration usually require expensive instrumentation and specialized training, and therefore have been confined mostly to research applications. Because of this, considerable effort has been devoted to develop methods for estimating evapotranspiration.

ESTIMATING EVAPOTRANSPIRATION Methods for estimating evapotranspiration include the use of different kinds of devices and a variety of equations. Devices such as evaporation pans, atmometers, and soil moisture monitoring devices have long been used to estimate evapotranspiration. The use of equations, however, is by far the most common method to estimate evapotranspiration. A great variety of equations have been proposed though the years, ranging from very simple to very complex models (1,7). Simple models usually try to estimate evapotranspiration based on empirical relationships involving one or several meteorological variables. Complex models consider the physics governing the evapotranspiration process and try to include all factors that significantly contribute to the process (1,8). Complex models can be further divided into single-layer models and multiple-layer models. Singlelayer models, such as the Penman–Monteith model, consider the crop canopy as a ‘‘big leaf,’’ taking into account only processes that occur between the top of the canopy and the atmosphere. Multiple-layer models, on the other hand, also take into account those processes that take place below the crop canopy. Multiple-layer models are more theoretically sound than single-layer models, but their complexity makes them impractical for widespread use. Because a single-layer model is sufficiently accurate for most practical applications and relatively simple to apply, it has been proposed as the recommended method for estimating evapotranspiration (9). Considerable effort has been made to estimate evapotranspiration using inputs obtained from remote sensing platforms, such as satellites or airplanes (1,10,11), and others have even tried to estimate evapotranspiration by measuring the flux of stable isotopes (12). Evapotranspiration, however, is more often estimated from equations that use meteorological data as input, as well as inputs that describe the characteristics of the evaporating surface. This is a convenient method because meteorological data are readily available in most places. Most nations and states support a network of meteorological stations and offer this information to the public in various ways. Meteorological data commonly used to estimate evapotranspiration include solar radiation, air temperature, relative humidity, and wind speed. A detailed procedure for calculating evapotranspiration has been described by Allen et al. (1). The method involves a two-step process. One step consists of calculating the evapotranspiration rate of a reference crop, either clipped grass or alfalfa, which is usually known as reference evapotranspiration. In older literature, this was also called potential evapotranspiration. It represents a measure of the evaporating demand of the atmosphere for a short,

cropped surface that effectively covers the ground, is growing healthily, and is not short of water, that is, a condition in which transpiration is not limited by stress, and the evapotranspiration demand of the atmosphere is met. The second step involves adjusting the reference evapotranspiration to match the conditions of the specific surface or crop being considered. This is done by calculating an adjustment factor, usually known as the crop coefficient. Depending on the accuracy required, calculating crop coefficients can also be a simple or complex process (7,13). Multiplying the reference evapotranspiration by the crop coefficient then results in the evapotranspiration rate for the crop or surface in question. REQUIREMENTS FOR EVAPOTRANSPIRATION Procedures used to estimate evapotranspiration try to simplify the complexities of the physical and physiological processes that affect evapotranspiration to a manageable number of quantifiable variables. They try to recognize that for the evapotranspiration process to take place, it is necessary to have 1. 2. 3. 4.

energy water space in the atmosphere to hold the water vapor a transport mechanism for the water vapor to move from the surface to the atmosphere.

Evapotranspiration is an energy-driven process. It takes approximately 2.45 megajoules of energy to evaporate 1 kilogram of water at 20 ◦ C. The sun supplies the energy needed for evapotranspiration from the earth’s surface. Part of the solar energy that reaches the evaporating surface, however, is reflected back to the atmosphere and cannot be used for evapotranspiration. Of the energy that stays on the evaporating surface, known as net radiation, not all is used in evapotranspiration. The energy balance of a surface also includes energy that is absorbed or released by the soil (soil heat flux), by the air (latent heat flux), and that used in evapotranspiration (latent heat flux). All of these types of heat fluxes take place simultaneously from a given surface, and their proportions depend on the characteristics of the surface and weather conditions. The amount of energy used for evapotranspiration includes short-wave radiation that comes directly from the sun, long-wave radiation or heat that comes from the surface, and advective heat that is transported horizontally by hot wind to the evaporating surface. The amount of energy available for evapotranspiration varies with latitude, day of the year, time of day, atmospheric conditions, and the characteristics of the surface itself. Figure 2 shows how the theoretical clear-sky solar radiation for different latitudes varies throughout the year. Figure 3 shows how measured solar radiation varies during the day and the effect of cloudiness in reducing the amount of solar energy that reaches the surface. As a general rule, the higher the amount of energy available at the evaporating surface, the higher

Clear-sky solar radiation, mm/day

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Figure 2. Theoretical clear-sky solar radiation values for different northern latitudes and day of the year at sea level.

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Figure 3. Measured solar radiation in North Platte, NE, on July 15 and 16, 2001.

the evapotranspiration rate, assuming that all other conditions required for evapotranspiration are met. Water is the next essential requirement for evapotranspiration. If water is not available, the energy available to evaporate water is then used to heat the air and the soil. Under desert conditions, for instance, where energy is usually plentiful, but water is normally very limited, the evapotranspiration rate can be very small. Most of the energy is converted to sensible heat flux, soil heat flux, and a very small portion or none of the energy is converted to latent heat flux. Similarly, when crops are under water stress, the evapotranspiration rate is reduced. Space in the atmosphere to hold the water vapor is also needed for evapotranspiration to proceed. When water is evaporated from a surface, the water vapor will travel to the atmosphere where it will be stored, provided that the atmosphere is not saturated. If the atmosphere is already saturated, it will not be able to store the additional water vapor, and evapotranspiration will be restricted. The drier the air in contact with the evaporating surface, the more evapotranspiration is enhanced. For this reason, the humidity of the air, usually expressed as relative humidity, is an important factor to consider when estimating evapotranspiration. The last requirement for evapotranspiration is a transport mechanism for moving water vapor from the surface to the atmosphere. There are two basic transport mechanisms for water vapor. The first is turbulence.

FOG

Turbulence is created when air moves horizontally over a rough surface. The friction created by the contact of the air with the rough elements of the surface creates a vertical component of the wind speed, which creates eddies of different sizes. The size of these eddies depends on the roughness of the surface and on the magnitude of the wind speed. These eddies carry the water vapor to the atmosphere. The other transport mechanism is buoyancy. Hot air is less dense that cold air; as the air close to the surface becomes hotter than the air above, it tends to ascend, carrying with it the water vapor. Turbulence is the most important transport mechanism in most instances, so wind speed is a very important factor in determining evapotranspiration. The higher the wind speed and the rougher the surface, the more turbulence, and the higher the evapotranspiration rate will be.

Evapotranspiration rates are most commonly expressed in units of water depth per unit time, such as millimeters per day (mm day−1 ) or inches per month (in months−1 ). Since it takes energy to evaporate water, water depths can also be expressed in terms of energy received per unit area. Therefore, evaportranspiration is often expressed in units of energy per unit area per unit time, such as watts per squared meter (w m−2 ), or megajoules per squared meter per day (MJ m−2 day−1 ). It can, however, also be expressed in units of energy per unit area, such as watts m−2 , or MJ m−2 day−1 . Many of the factors affecting evapotranspiration are so dynamic that the magnitude of the evapotranspiration rates for a given surface will vary from day to day, from place to place, and throughout the day. Figure 4 shows the calculated daily evapotranspiration rate for corn in North Platte, Nebraska, during the 2000 growing season. It shows the typical large variations in evapotranspiration rate that can be expected from day to day, as a result of normal daily changes in weather conditions. It also shows a seasonal pattern, as a response to the seasonal changes in available energy and to the changing water demand of the crop during its growing cycle.

Evapotranspiration, mm/day

Corn, North Platte, NE, 2000

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BIBLIOGRAPHY 1. Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. (1998). Crop evapotranspiration—guidelines for computing crop water requirements. Irrigation and Drainage Paper No. 56, FAO, Rome, Italy. 2. Allen, R.G. et al. (2002). Evapotranspiration from a satellitebased surface energy balance for the Snake Plain Aquifer in Idaho. Proceedings of the 2002 USCID/EWRI Conference. July 9–12, San Luis Obispo, CA, pp. 167–178. 3. Gates, D.M. (1964). Leaf temperature and transpiration. Agronomy Journal 56(3): 273–278. 4. Yazar, A., Howell, T.A., Dusek, D.A., and Copeland, K.S. (1999). Evaluation of Crop Water Stress Index for LEPA irrigated corn. Irrigation Science 18: 171–180. 5. Hoeft, R.G., Nafziger, E.D., Johnson, R.R., and Aldrich, S.R. (2000). Modern Corn and Soybean Production, 1st Edn. MCSP Publications, Champaign, IL. 6. Schneekloth, J.P. et al. (1991) Crop rotations with full and limited irrigation and dryland management. Transactions of the ASAE 34(6): 2372–2380.

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7. Doorenbos, J. and Pruitt, W.O. (Eds.). (1977). Crop Water Requirements. Irrigation and Drainage Paper No. 24, FAO, Rome, Italy. 8. Suttleworth, W.J. and Wallace, J.S. (1985). Evaporation from sparse crops—an energy combination theory. Quarterly Journal of the Royal Meteorological Society 111: 839–853. 9. EWRI. (2001). The ASCE Standardized Reference Evapotranspiration Equation. Environmental and Water Resource Institute of the American Society of Civil Engineers. Standardization of Reference Evapotranspiration Task Committee Report. Available: http://www.kimberly.uidaho. edu/water/asceewri/. 10. Moran, M.S. et al. (1989). Mapping surface energy balance components by combining Landsat Thematic Mapper and ground-based meteorological data. Remote Sensing of Environment 30: 77–87. 11. Payero, J.O. (1997). Estimating Evapotranspiration of Reference Crops Using the Remote Sensing Approach. Ph.D. Dissertation, Utah State University, Logan, UT. 12. Yakir, D. and Sternberg, L.daS.L. (2000). The use of stable isotopes to study ecosystem gas exchange. Oecologia 123: 297–311. 13. Wright, J.L. (1982). New evapotranspiration crop coefficients. Proceedings of the ASCE 108: 57–75.

FOG

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ARTHUR M. HOLST

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Philadelphia Water Department Philadelphia, Pennsylvania

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Figure 4. Calculated daily evapotranspiration for corn in North Platte, NE, during the year 2000.

Fog is a cloud that materializes near the ground or over water. It is a reaction that occurs when the temperature near the ground cools to the temperature required to produce dew and causes the water vapor in the air to become visible in the form of a cloud of precipitation. There are different types of fog, which occur when different variables are involved. The two conditions necessary for fog formation are mild or no winds and air

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temperatures that are equivalent to the temperature at the dew point. Mild or no winds are important because obstructions in the way of a strong wind can cause it to blow in an up and down motion, which brings warmer air down and pushes the colder air up. Cool air is a requirement for fog formation so wind prevents it from happening. Fog, like most weather hazards, can cause serious problems for society. The only time this condition is not applicable is when fog forms over water due to the absence of obstructions. In this case, the reverse reaction occurs, and the fog worsens as the wind grows faster. Fall nights are often said to contain the perfect conditions for producing fog. At night, the ground cools which also cools the air directly above it. This reaction causes droplets of water to become suspended in the air resulting in the creation of fog. However, these perfect conditions don’t last forever. By morning, the heat from the sun begins to warm the ground, and the fog evaporates. There are many types of fog, but the four most common are evaporation fog, upslope fog, precipitation fog, and radiation fog which is commonly called ground fog. Evaporation fog is found mostly out at sea, which is why it is also known as ‘‘sea fog.’’ It is the reaction of moist air moving over colder water. The fog conditions worsen as the wind speed increases. Upslope fog is produced by moist air that is sent by a strong wind up into mountainous regions. Precipitation fog is created when precipitation in the form of rain or snow hits drier air and causes water vapor to materialize instantly. Radiation fog is seen at night when the ground is cool. The air that comes in contact with the ground also becomes cool and creates water vapor which soaks the ground and causes the formation of dew. Like most weather hazards, fog can have severe impacts on society. Fog can cause health problems in polluted areas because the water vapor produced can become acidic. Driving through a thick cloud severely reduces a person’s visibility and is a major contributor to car accidents. Even worse than the occasional car accident due to fog are the aircraft and boating accidents that can occur. Throughout history, fog has been known as the silent murderer that has taken hundreds of lives at sea in catastrophic boating accidents.

READING LIST Joseph, P. Weather Wisdom. (2002). Available: http://www.touchtmj4.com/4weather/wxwisdom/fog/fogtypes.asp. (March 19). Malan, J. Weather Wisdom. (2002). Available: http://www.touchtmj4.com/4weather/wxwisdom/fog/fog.asp. (March 19). Malan, J. Weather Wisdom. (2002). Available: http://www.touchtmj4.com/4weather/wxwisdom/fog/fogdisasters.asp. (March 19). Parsons, L. Fog. (2002). Available: http://www.activeangler.com/ articles/safety/articles/lee parsons/fog.asp. (March 19). Understanding Clouds and Fog. USA Today. (2002). Available: http://www.usatoday.com/weather/wcloud0.htm. (March 19). Williams, J. Fall nights often perfect for forming fog. USA Today. (2002). Available:http://www.usatoday.com/weather/wrfog.htm. (March 19).

COASTAL FOG ALONG THE NORTHERN GULF OF MEXICO TIMOTHY ERICKSON National Weather Service New Orleans/Baton Rouge Forecast Office Slidell, Louisiana

INTRODUCTION Coastal fog is a major problem for all traffic along the United States’ coastlines. Lives and large monetary losses have occurred because of coastal fog. These losses have been realized over land, in the air, and on the water. Huge strides have been taken to understand and combat the coastal fog forecasting problem by the National Weather Service. Studies and research continue to improve these fog forecasting techniques. Tens of thousands of people use the Gulf of Mexico as their home or as part of their occupation in many different ways, and billions of dollars in products and property are carried and moved through the channels and river systems to and from the Gulf of Mexico each year. All are affected by coastal fog many times throughout the fall, winter, and spring. This research project took place along the northern Gulf of Mexico from the upper Texas coast to the Mississippi coastline. METHODOLOGY The synoptic and mesoscale patterns used in this research were from the fall, winter, and spring of 1998, 1999, 2000, and 2001. Fog was defined as water droplets suspended in the air reducing visibility to one half-mile or less. Shower and thunderstorm activity reducing visibility to these levels was not used. No records exist for fog contributions to the hydrologic cycle. Water contributions caused by fog are dismissed as false tips in rain gauges. The reference to ‘‘boundary layer’’ in this article will be the layer of atmosphere from the surface to the base of the lowest inversion. Variables used in this research were surface pressure, rainfall, moisture advection, wind direction, wind speed, water temperatures, ambient temperature, and ambient dew point temperature from land observations and production platforms in the northern Gulf of Mexico. Parameters used from previous studies by Johnson and Graschel (1) were air temperature, dew point temperature, wind direction, wind speed, ceiling heights, and visibilities from oil and gas production platforms at an average altitude of 35 ms over the northern Gulf of Mexico. Gulf of Mexico sea surface temperatures were provided by the Tropical Prediction Center oceanographer in Miami, Florida. SCALES OCCURRING WITH COASTAL FOG Mesoscale—Widespread Horizontal range would normally be from 50 to several hundred miles.

COASTAL FOG ALONG THE NORTHERN GULF OF MEXICO

Microscale—Locally Horizontal range could be at a point close to 50 miles. CONDITIONS THAT HELP PRODUCE COASTAL FOG

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there will be plenty of moisture and a strong inversion that may develop some dense coastal fog. Even without a prefrontal trough or rainfall, the subsidence inversion and gulf moisture ahead of a slow-moving cold front will sometimes be enough to provide conditions promoting dense coastal fog.

Radiative Heat is transmitted via long wave radiation (infrared) away from Earth. This radiation causes nocturnal cooling of the ground and subsequent atmospheric boundary layer. Radiational cooling is responsible for developing a stable layer near the surface by cooling the layer of air in contact with the ground while leaving a relatively warmer layer immediately above this cooler layer. This stability by warmer air above cooler air with increasing altitude is called an inversion. This feature is important in forecasting the depth of coastal fog. As the radiative process continues, the layer will cool further until saturation is achieved and fog can be produced, given the pressure does not change much during the process. Coastal Interface. Temperature and moisture gradients are strong where the ocean meets land, especially at night during the fall, winter, and spring. During prime radiational cooling processes, this interface can become moist and stable horizontally from land to water when there is no forcing. These conditions were found when a thin ribbon of fog developed at this interface of land and water. The fog stretched linearly for more than 100 miles and vertically for hundreds of feet. Studies on how this type of fog develops are ongoing but horizontal skew-t sounding-like profiles may be a tremendous help in what is occurring at this land–water junction when this fog forms. No horizontal sounding-like profiles exist, and this is the first mention of such a profile. But if they were available, they could give some valuable insight not only into the coastal ‘‘ribbon’’ fog formation but also where thunderstorms are more likely to develop along with many other variables. Frontal This is another inversion producing process. Coastal fog can be developed with the assistance of cold, warm, or stationary fronts. Cold Frontal. An inversion develops by cooler air displacing warmer air at the surface. The interface where these air masses meet in the vertical is known as a frontal inversion. Coastal fog formation under a frontal inversion is nonexistent with fast-moving cold fronts, because of stronger winds that cause a deeply mixed layer, along with dry, cold air advection behind the front. When warm air is lifted by a cold front, it causes displacement and mid-altitude air ahead of the front becomes subsident. This process causes compressional warming, which forms another inversion well ahead of the cold front. As the surface cools at night, the boundary layer becomes stable well ahead of the front. If there has been rain ahead of the cold front with a prefrontal trough,

Warm Frontal. Relatively cool saturated or nearly saturated air ahead of a warm front is gently displaced by warmer air. The cool air is normally not very deep (100–300 ms) and is topped by warmer air at relatively low altitudes, which causes an inversion to form where the two air masses meet in the vertical. Cooler air cannot hold as much moisture as warm air. As the air ahead of the warm front is already moisture laden, cooler, and stable, water vapor condenses to small particles, which causes fog to form. This result happens frequently along the coast during the cooler months of the year and sometimes far inland. A similar scenario along the coast was also described by Hsu (2). The dynamics of warmer, higher dew point air flowing over cooler waters was described by Kotsch (3) and Mullan (4). Coastal fog can occur behind warm fronts but is not as common. The air is, by definition of a warm front, warmer than the air ahead of it. The warmer air expands and therefore can hold more water vapor, which will normally dissipate any fog behind a warm front if no overwhelming positive moisture flux is occurring in the warm sector. When this flux occurs, it can be far too great for even the warm air to hold and the water vapor will condense, which causes fog to form. During research, this result occurred only when an inversion was still present behind a warm front. Stationary and Slow Moving Fronts. These types of fronts are aggressive at developing coastal fog, which can occur in two ways ahead of a cold front that becomes stationary or slow moving. One is when moisture is not displaced and wind speeds are very light behind the trough preceding the cold front. The second is when the wind fetch is well over the marine environment and it brings warm moist air back over cooler waters or land. Warm frontal fog conditions were explained above. Two unusual fog days occurred as post-cold frontal events. A cold front passed through the southern Louisiana coastal region, and dew points and dry bulb temperatures cooled. Coastal fog then began to develop over many sites from east central Texas to south central Louisiana. The air mass change was more negative for the dry bulb temperature than for the dew point temperature, and the cold front slowed from about 10 knots to less than 5 knots as it reached the coastline. This decrease caused the air behind the front to become saturated. Frontal forcing weakened, and consequently northerly winds weakened and created perfect conditions for coastal fog development. Post-cold frontal fog is rare, but when it does occur, visibilities can plummet to less than one quarter of a mile quickly. Hsu’s (2) description on frontal fog production is similar to this research. Johnson and Gracshel (1) called frontal fog ‘‘mixing fog.’’

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Maritime (Sea Fog) When fog develops via any process over any large marine area, it is called marine or sea fog. Marine fog may be stationary or be advected elsewhere. It is during the advection process that coastal fog occurs. Dormant. As the cooler boundary layer air over land ‘‘drains’’ offshore, it causes stability to decrease, which makes mixing possible. The warm gulf gives off water vapor to the cooler air, which causes the vapor to condense, making water droplets. This process quickly deteriorates when only little ‘‘drainage’’ is occurring. Latent heat released because of condensation warms the marine boundary layer too fast, which makes the stability in this layer neutral. Fog will form in the near shore waters if this latent heating can be exhausted through the top of the maritime boundary layer. Fog development caused by this process does not occur often. When it does, the fog stays near the coast, rarely moving anywhere because of the very slow, almost laminar flow of air moving off land. When this type of fog affects the shoreline, it is also called coastal fog. The other processes mentioned above may produce nonadvective marine fog that stays in the near shore waters. Advancing. This process in which coastal fog is achieved is the most common. The air in the boundary layer is well mixed but does not entrain air from above the inversion. Fog that forms either onshore or offshore by any process and moves elsewhere is an advective fog. When fog advects from one offshore location to another or to the coast, it is said to be advancing. The most common type of advancing fog is found with post-strong cold front events. Winds from these fronts move the top layer of warm shelf water away from the coast. This water is replaced by cooler upwelled water. A strong temperature gradient exists where the cooler upwelled water meets the warm water offshore. When the next cold front produces return flow from the warmer water offshore, moisture-laden air saturates while moving over the cooler water. Extensive areas of fog or very low cloud ceilings form before moving inland, which causes extremely low visibilities stretching for miles along the coast. When the moisture came in the form of low clouds during research, the cloud deck would often descend to the surface producing very dense coastal fog as well. As warm air overlays cooler water, it produces a stable boundary layer. No vertical mixing occurs by air moving up or down. Mixing was produced solely by wind advancing the fog. The wind did not reach through the inversion layer, and therefore, no entrainment occurred. A similar scenario was recorded by Binhau (5) and Hsu (2). Their contributions showed this environment to be stable, with surface winds from the southeast through southwest. This scenario holds true for all locations along the northern Gulf of Mexico. Advective Anytime fog forms elsewhere and is forced to another location, it is a type of advection fog. A well-mixed

boundary layer also exists with advective fog, but again, air from above the inversion is not mixed downward. In some cases, the atmosphere will be capable of supporting fog but it cannot produce it. When this happens, fog may be brought into the area by wind or by the slow movement of an entire layer of air. It is important that this air mass does not mix with air from above the inversion. If this mixture occurs, dry, relatively warmer air will be mixed into the boundary layer, causing the fog to erode. Conglomerate of Two or More Types from Above This fog producer is the most common. Two or more of the above processes usually develop fog that forms almost anywhere on Earth. One major variable may occur at the time of fog formation, but most of the time fog is supported by another equal or weaker variable, for example, frontalinduced marine fog. That is, fog develops over the marine environment by a cold front, which brings warm, moist air back over cooler waters. The fog develops mainly because of the marine environment, where it derives its moisture, but it could only do so as a result of forcing by the cold front. VARIABLES PRESENT DURING COASTAL FOG PRODUCTION Variables Always Present During Coastal Fog Formation Negative or Neutral Omega Within or Just Above the Boundary Layer. When lift occurred during the research, fog would dissipate or simply not form. The lift causes mixing through the inversion, which brings dry, relatively warm air into the boundary layer. Weak or No Positive Vorticity in the Boundary Layer. Coastal fog developed under boundary layernegative vorticity regimes, but it would not develop under moderate-to-strong positive vorticity in the boundary layer. When weak vorticity occurred within or at the top of the boundary layer, fog would lift and become a low-level cloud ceiling. As the vorticity center moved past, the ceiling would once again descend to the surface, which caused coastal fog to form. Inversion. An inversion is always present during any and all fog development and duration. Variables Present During Research for Each Condition Radiation Fog Variables

Winds 0 to 3 Knots. Radiation fog events are created without mixing through the inversion. Wind greater than 3 knots was found to create too much mixing and dissipated coastal fog during radiative events. Moisture Advection or Rainfall Within 36 Hours. Moisture is needed for any fog to develop. With no moisture advection, it was found that moisture input from rainfall would be sufficient inside 36 hours. This field was dependant on several variables. These variables included amount of

COASTAL FOG ALONG THE NORTHERN GULF OF MEXICO

rainfall, ground moisture, insolation, and amount of rainfall coupled with timing. The best results were found with light rain episodes during the early morning with strong insolation during the day.

Neutral or Negative Omega. Neutral or negative lift from some height above down to the top of the boundary layer was always found when coastal fog formed during this research. Positive lift caused mixing through the inversion, which dissipated the fog. Weak-to-No Boundary Layer Positive Vorticity. Coastal fog formed under negative and neutral vorticity regimes. Coastal fog was either displaced or was not present when moderate-to-strong positive vorticity was found within the boundary layer. Coastal fog was also present with weak positive vorticity, but a few interesting findings occurred. As a weak positive vorticity center moved through the boundary layer, coastal fog would lift, which created a low-level ceiling from 100 to 400 feet. When the vorticity maxima passed, the low-level ceiling would descend to the ground, which caused coastal fog to return. This phenomenon was known for creating ‘‘bouncy’’ fog conditions where visibilities would swing wildly from as little as 0 to as much as 4 miles. Clear Skies. Clear skies were the overwhelming majority of sky conditions experienced during radiational coastal fog events. The minority sky condition consisted of very high thin cirrus clouds. No radiational coastal fog events occurred during any other cloud conditions. Outside Downtown Areas. Radiational coastal fog events during this study were found outside the downtown areas of cities. The heat island effect was enough to dissipate any fog trying to form inside these areas. Moisture Advection or Rain Within 36 Hours. The highest frequency of coastal fog during frontal regimes was found when a prefrontal trough passed. Moisture was input by both the front causing return flow from the marine environment and the prefrontal trough causing rainfall. Clear Skies or Very High Cloud Ceiling. High cloud ceilings were noted several times throughout the research when frontal-induced coastal fog developed. Winds of 10 to 20 knots were noted above a shallow inversion, which allowed heat from the boundary layer to escape and be carried away. Surface Winds of 0 to 12 Knots. During radiative conditions, coastal fog only formed when wind speeds were 0 to 3 knots. During advective or advancing conditions, coastal fog was carried to or along the coast when wind speeds were 4 to 12 knots. No coastal fog formed during this research when wind speeds were greater than 12 knots. Onshore Winds of At Least 4 Knots and Not More Than 12 Knots. During marine-induced coastal fog, winds were

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necessary to advance the fog from the marine environment to the coast. But wind speeds greater than 12 knots caused the fog to dissipate by mixing with air above the inversion. When these winds did not reach the top of the boundary layer, no mixing occurred through the inversion and the fog would simply lift, developing a low-level cloud ceiling.

No Moisture Advection. Surprisingly, moisture preconditioning was not necessary when marine fog caused coastal fog. The marine fog was the moisture advection. Clear or Very High Ceilings. Several cases showed coastal fog production via a low-level cloud deck. When heat was capable of radiating through the inversion at the top of the low-level clouds, the cloud deck lowered or deepened toward the surface through the night, finally reaching the ground, which caused coastal fog to form. It was also noted that the lower the cloud deck, the shorter the time frame coastal fog would develop. A very general rule of thumb was realized when the boundary layer was capable of supporting fog. On average, it took about an hour for the cloud ceiling to descend 100 feet. Cloud bases higher than 1000 feet never reached the surface during marine-induced coastal fog events. Temperature. Johnson and Graschel (1) found temperature differences of several variables to be important when maritime fog developed. As indicated in their article, ‘‘Sea Fog and Stratus: A Major Aviation and Marine Hazard In The Northern Gulf Of Mexico,’’ the differences between water and air temperatures, as well as between water and dew point temperatures, were the most important variables producing marine fog when the right atmospheric conditions were in place. The graphs below show these parameters versus relative humidity (RH) values. Johnson and Graschel’s study (1) as well as this project found RH values of 98% or greater always present with coastal fog. Figure 1 shows the continental shelf region along the northern Gulf of Mexico, which is shown at the 200-m depth contour. It is also the region where a cool water temperature of 20 ◦ C (68 ◦ F) or less was found to be critical for marine fog development in the northern gulf during the right atmospheric conditions. These findings may not be the same at other locations around the globe because fog development depends on temperature gradients, over water and/or land, which are relative. Water temperature findings close to these were also accomplished by Binhau (5). Figure 2 shows RH versus (Ta - Tw), where RH is relative humidity and (Ta - Tw) is the difference between the ambient air temperature and the water temperature. In Fig. 3, in regard to the positive (+) numbers, when the water temperature is cooler than the air temperature, the air must be moving between 4 knots to as high as 12 knots for coastal fog to form. During this process, the moisture-laden warmer air loses its heat to the cooler water. As the air cools to its dew point, condensation takes place. Latent heat is released during the condensation process. The air can lose this added heat to the cooler water below and through the top of the boundary layer

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via long wave radiation, so fog can begin to form. This process is efficient and is the main reason for coastal fog developing from advancing marine fog. The positive numbers in Fig. 3 show a stable boundary layer also described by Binhau (5) and Hsu (2). In Fig. 4, in regard to the negative (−) numbers, when the water temperature is warmer than the air temperature, the air must be calm or moving no faster than 3 knots for coastal fog to form. During this process, when coastal tidal marshes exist, a column of cooler dry air will have a net gain of water vapor, which causes the dew point temperature to rise. When the air and dew point temperature are very close, condensation will begin. As a result of condensation, latent heat is released. The column will need to lose this heat through the top of the boundary layer before fog will begin to form. Even though marine fog occurs by this process, it is not an efficient coastal fog producer unless fog initially forms along the coast. Most of the time, fog will develop

over the marine environment and be stationary or drift farther offshore. Negative numbers in Fig. 4 show an unstable boundary layer as described by Binhau (5). Binhau showed that this type of fog may be produced over the marine environment even with northerly winds of 30 knots. But with winds of this magnitude, coastal fog will never develop along the northern gulf coast because the winds would force it out to sea. Figure 5 shows RH versus (Td − Tw), where RH is relative humidity and (Td − Tw) is the difference between the ambient dew point temperature and the water temperature. In Fig. 6, in regard to the positive (+) numbers, it is important to remember that the atmosphere as well as the ocean is always trying to reach a state of equilibrium. When the ambient dew point temperature is higher than the water temperature, water molecules can easily move to and become a part of the ocean surface. Water molecules find it hard to break away from the waters’ surface during these conditions, and therefore, a net moisture flux from air to water occurs. The air temperature is always equal to or greater than the dew point. Hence, there will be a transfer of heat from the air to the water as well. This process cools the air temperature, but saturation is difficult to achieve because there is a net loss of water vapor to the water surface. The air continues to cool and dry until temperatures of the water, the air, and the dew point equal or become very close. This process eventually causes saturation and can, but rarely does, cause coastal fog to form when atmospheric conditions are right and (Td—Tw) is zero or very close. Normal occurrences of fog on the positive side of Fig. 6 are when fog develops elsewhere and advances into the area. In Fig. 7, in regard to the negative(−) numbers, when the water temperature is warmer than the dew point, water molecules can easily break away from the water surface to the air. Regardless of the air temperature,

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Boundary layer top

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the water will try to modify it until the water and air temperatures are equal. Even if saturation is achieved, moisture will continue to be added to the air until the dew point is equal to the water temperature. As moisture is added to the air at saturation, condensation begins and latent heat is released to the air until the temperatures of the water, dew point, and air are equal. This saturation can easily develop fog near or offshore. Normally, marine fog produced by this process occurs with little airflow (0–3 knots). After marine fog forms, it can be easily forced to the coast as winds increase ahead of the next cold front. This coastal fog producer is aggressive. As Fig. 7 depicts, this process occurs with a minimal separation of air, dew point, and water temperatures. When separations are too large, there may be too much

Figure 4. This picture shows a light offshore wind, dew point temperature (Td), air temperature (Ta), and water temperature (Tw).

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Boundary layer top

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Figure 6. This picture shows winds of 12 knots or less, air temperature (Ta), dew point temperature (Td), and water temperature (Tw).

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Figure 7. This picture shows wind speeds less than or equal to 12 knots, dew point temperature (Td), and water temperature (Tw).

dry air to modify before the next system brings this air mass back to shore. If the air is moving more than 3 knots, there will be a continual replacement of dry air and/or air from above the inversion may be mixed into the boundary layer and saturation will not be achieved. Advective Fog Variables

Winds of At Least 4 Knots and Not More Than 12 Knots. Advective fog, which causes coastal fog, is different from advancing marine fog in a couple of ways, i.e., where the fog developed and the wind fetch. Fog that develops onshore and moves to the coast is only known as advective fog. Whenever fog moves to the coast, the wind direction will always be in a direction from the fog to the coastal

Tw = 20 °C

location. All other variables that are needed for marine fog to advance to the coast are also needed for advective fog.

No Moisture Advection. Even though moisture may be in place, advective fog does not need to have a premoistened atmosphere for coastal fog to be produced. Moisture advection can be induced by the fog moving to the coast. Clear or Very High Cloud Ceilings. Cloud conditions were found to be the same as for marine fog. Conglomerate Fog Variables. The variables for each condition associated with coastal fog development have to be present when coastal fog forms under more than one condition.

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SOUNDING PROFILES PRESENT DURING COASTAL FOG A sounding profile similar to Fig. 8 was always present shortly before and during radiative coastal fog events. This actual sounding shows a very shallow (∼100 feet) moist layer capped by three strong inversions. A sounding profile similar to Fig. 9 was always present shortly before and during advective and maritime coastal fog events. This actual sounding shows a very deep (∼1000 feet) moist layer capped by a moderate inversion. Fog rarely develops beneath the type of inversion in Fig. 10. This actual sounding shows a deep moist layer capped by a frontal inversion; coastal fog occurred before the passage of this cold front, but it quickly dissipated by the time this sounding was taken. Frontal-induced and conglomerate fog was found with all three types of sounding profiles. Frontal-induced coastal fog occurred more often under the first and second profile types. Sounding profiles are important for forecasting the depth of coastal fog or any type of fog. Maritime, advective, and frontal-induced coastal fog can only be as deep as the

height from the surface to the base of the inversion. These types of fog produced the deepest fog along the coast as well as inland, and consequently they took longer to dissipate. During research, most radiation-induced coastal fog formed only under a low-level inversion. The inversion could be as high as 100 feet or as low as a few feet from the ground. The inversion was frequently strong. Air parcels were not able to penetrate the inversion, but it would not stop radiative heat transfer from the surface via longwave radiation. Radiative fog did not always follow the depth rule. It could be from the surface to the base of the inversion deep or as shallow as a few inches, even when the inversion was much higher. An interesting find during the project was horizontal stability and moisture profiles during radiative fog formation conditions along the coast. The horizontal profile shown below from the coast along with the radiative vertical profile from inland locations were both present when a thin ‘‘ribbon’’ of fog formed along the coast (see Fig. 11). This fog was found to run linearly along the coast and stretched upward for hundreds of feet. The inland vertical sounding did not support such a high

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Figure 11. This illustration shows a hypothetical representation on how a very thin ribbon of fog develops at the coast.

depth of coastal fog, but this vertical profile may have been different along the coast because strong moisture and temperature gradients existed. Research into this phenomenon is ongoing. CONCLUSION

2. Hsu, S.A. (1988). Coastal Meteorology. Academic Press, New York, p. 52. 3. Kotsch, W.J. (1983). Weather for the Mariners. Naval Institute Press, Annapolis, MD. 4. Mullan, D.S. (1984). Low stratus and sea fog in the North Irish Sea. Weather (GB) 39: 235–239. 5. Binhau, W. (1985). Sea Fog. Springer-Verlag, New York.

Fog has never received the attention it deserves because it does not make for an explosive story like hurricanes and tornadoes. But fog is blamed for large monetary losses as well as property losses. Each year, fog is blamed for indirectly taking more lives than hurricanes in the United States. Fog also donates a small but significant amount of water to the hydrologic cycle. In some places, such as the western high coast region of South America, fog is the only way insects and grasses receive water. When fog develops, there is always an inversion in place, which means the boundary layer is disconnected from the remaining atmosphere above with respect to mixing. This process is called decoupling. When the inversion erodes and mixing resumes through this layer, it is said to be coupled. As a result, pollutants released to the environment will remain in the boundary layer during decoupled conditions and will mix out during coupled conditions. Petrochemical plants and other facilities-producing pollutants that are dispersed to the environment can use fog as an indicator for when not to release waste products. Results during research show there are numerous variables and observations from the microscale environment to consider when forecasting coastal fog conditions. Current National Weather Service numerical models do not solve for microscale conditions, and therefore, forecasters must rely on pattern recognition to resolve these issues. BIBLIOGRAPHY 1. Johnson, G.A. and Graschel, J. (1990). Sea Fog and Stratus: A Major Aviation and Marine Hazard in the Northern Gulf of Mexico.

RAIN FORESTS ALDO CONTI Frascati (RM), Italy

Rain forests are, by definition, those forests that receive more than 2500 mm of rain each year. Rain forests are characterized by very dense vegetation dominated by tall trees and huge biodiversity. Rain forests exist in many parts of the planet, but most of them are along the equator, where the weather is stable throughout the year and there is never a dry season. Rain forests do not have seasons at all. The amount of rain is almost constant during the year, and the temperature seldom dips below 16 ◦ C. Rain forests cover 7% of the earth’s land surface and 2% of its total surface, but are home to more than half of all animal and plant species. Despite the fact that rain forests cover less than 10% of the earth, they support a third of its plant matter. The largest tropical rain forest in the world is the Amazon Rain Forest, which lies in the countries of Brazil, Bolivia, Peru, Ecuador, and Colombia. There are rain forests in Africa, mainly in the Congo, and in Oceania. The large amount of rain also creates some of the biggest rivers and flood plains of the world. Unfortunately, rain forests are in danger. They lie mainly in poor countries, where the economic situation forces people to use all resources, which is why most rain forests have shrunk dramatically in size over the last few decades. What is in danger is their huge biodiversity. Some

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researchers estimate that the Amazon Forest alone might host up to 10 million species of animals, mainly insects. At the rate the forest is disappearing, most of the estimates say that we are losing something like 100 of these species every day, before even being described by science. Most of the animals in rain forests have adapted to live in the upper level of the canopy, where food is really plentiful. The constant weather means that there are flowers and fruits at any time of the year. The largest group of animals is that of insects that can easily climb trees and often have a highly symbiotic relationship with the plant life of the forest. Ants and termites are the most abundant animal of every rain forest. Animals are very important for the survival of the forest. Underneath the canopy, the wind is not strong enough to disperse efficiently the seeds produced by plants. Plants rely therefore on insects, that very often pick up the seeds and drop them some distance away. But the most important animals for seed dispersal are birds. Birds in rain forests eat mainly fruits, and the seeds can pass through their digestive system unscathed. By the time a bird excretes its load of seeds, it has normally flown a long distance from the plant, which ensures a high level of genetic mixing, healthy and helpful for plants. There are even some seeds that do not germinate unless they have gone through the digestive system of birds. More than one-fourth of all bird species in the world today live in tropical rain forests. To have an idea of the importance of rain forests, some figures might be interesting. A single square meter of rain forest supports between 45 and 80 kg of biomass, far more than any other biome. This biomass gains more importance considering that most of it is made of carbon removed from our atmosphere. One hectare of rain forest can contain 200 species of trees and more than 40,000 species of insects. In Panama, scientists discovered fully 80% of the world’s currently known beetle species on only 19 trees. Once, researchers discovered over 600 new species of beetle by studying a single species of tree. Although not as rich in species as their Asian or Amazonian counterparts, African rain forests contain more than half of that continent’s animal and plant species, even though they cover less than 7% of its total land area. Because of the huge biodiversity, most species have evolved to occupy very specialized niches of the environment, which means that many species depend on each other and cannot survive without each other. Deforestation and many other human activities disrupt these complicated relationships. Rain forests could play a crucial role in feeding the whole world’s population. Many vegetables and fruits such as bananas and peppers that we consume come from rain forests. Peanuts come from rain forests, as do many drinks (coffee, tea, cola), oils (palm, coconut), flavorings (cocoa, vanilla), and other foods (beans, grains, fish). And many more vegetables are still there ready to be discovered. Moreover, researchers have identified over 200 plants that produce potential cancer fighting substances. And this considering that only 1% of plants have been intensively screened for such properties. Tropical rain forests do not offer only goods. They are a vital part of the hydrogeologic

cycle of the planet and act as a global air purifier, absorbing huge amounts of carbon dioxide and releasing oxygen. Despite their importance, rain forests everywhere are exposed to huge threats. Often, forests are cleared with fire to make room for cultivation. One plot is used for a few years until the soil is exhausted, and then farmers move on to clear another patch, putting the lushest forests in danger of desertification. But other industrial interests, including timber and mining, are taking advantage of rain forests. Part of the danger comes also from animal and plant species introduced from other environments. All these activities result, every year, in a rather large loss of rain forest. It is difficult to estimate the extent of the damage, as data are not plentiful or reliable. Nevertheless, it is true that in some countries, like Madagascar, the whole forest has almost disappeared in a few decades. As a result, human activities might be inducing the most important mass extinction since the fall of dinosaurs 65 million years ago. According to some research, up to 10% of the world’s species might disappear in the next 25 years. But the truth is that over 50% of the earth’s plants and animal are in danger. Nearly 20% of known endangered vertebrates are threatened by introduced species. Cultures are going extinct, too. Since the turn of the century, 90 tribes of indigenous peoples have been wiped out in Brazil alone. The pace of annihilation is increasing; 26 of those tribes were killed or scattered in the past decade. Everything should be done to halt this loss that many scientists think might affect the earth’s climate, too, on a global scale.

FROST ARTHUR M. HOLST Philadelphia Water Department Philadelphia, Pennsylvania

Essentially, a type of dew, frost is ice formed by the condensation of atmospheric water vapor on a surface. It generally occurs at night, and when frost forms, it can sometimes be seen in patterns of ice crystals. Frost can be extremely damaging to outdoor crops and plants. Researchers and weather services throughout the world monitor the effects of damaging frosts. Frost forms on any surface, including cars, grass, and buildings. Frost forms through one of two processes: the formation of dew that subsequently freezes, or deposition, which is the process wherein a gas changes to a solid. In frost formation, this gas is water vapor, and the solid state is ice crystals. These two processes will occur when the air is saturated. Saturation occurs when the air holds as much water vapor as is possible at its temperature and pressure. The temperature at which frost is deposited is known as the frost point temperature. Condensing water vapor must have something upon which to condense. If the temperature of the ground is below 0 ◦ C, then the deposit will initially be as dew. Over time, this dew will eventually freeze, forming frost. However, if the dew point of the air is below 0 ◦ C, the

FROST DAMAGE

deposit will be hoarfrost, which is ice that forms directly through deposition, without initially forming as dew. Hoarfrost is also known as black frost, because unlike regular frost, it is not visible as white crystals (normal frost is called white frost). It is possible for frost to form even if the air temperature is above freezing. Frost formation depends solely on the air’s dew point. However, the temperature of a surface affects whether or not dew, frost, or hoarfrost form because colder objects radiate less heat into the air surrounding them, keeping that air’s dew point down. The formation of frost is also governed by a process known as radiational cooling. Frost formation requires a surface temperature below 0 ◦ C, so cold surfaces are necessary. At night, certain surfaces will cool much faster than the surrounding air and other surfaces because all objects radiate heat at all times. During the day, objects generally recoup any lost energy from energy received from the Sun. However, at night, objects no longer receive heat radiated by the Sun, and so less energy is generally received, resulting in a rapidly decreasing nighttime temperature. Frost is more likely to form on clear nights because surfaces cool faster when no clouds radiate heat. On cloudy nights, the clouds may radiate enough heat to surfaces to prevent frost from forming. Frost typically forms under conditions of light or no wind and sufficiently cold temperature. Winds cause air turbulence, and this turbulence mixes the air, which inhibits frost formation. Typically, frost will form more easily overnight because temperatures tend to be lower and the air moves more slowly than it does during the day. Due to radiational cooling, frost forms less often in areas where many buildings, trees, and other objects are; it also forms less often near bodies of water. Multiple factors are used by scientists and meteorologists to determine whether or not frost will occur on a given night. One is the general weather of that day/night. The situation most favorable to frost formation is a cloudy day followed by a clear night because clouds prevent the Sun from adequately heating the soil. Humidity is also used. If the dew point is over 5.5 ◦ C at night, frosts are unlikely. If it is below 2.2 ◦ C, a frost is highly probable. In areas where frost forms, local weather services will designate the type of frost that might be deposited in the region. These designations are light, heavy, and killing. A light frost will have no destructive effects on vegetation. A heavy frost is a significant deposit but is not likely to affect the staple vegetation of a region. A killing frost is severely destructive to vegetation and can decimate an entire crop. In the United States, frost warnings will be issued only until October 15th west of a line from Frederick, Maryland, to Charlottesville, Virginia. East of this line, warnings are not issued past November 1st. In the spring, frost warnings are issued only if there is a possibility that crops and other plants could be damaged. Killing frosts are monitored by weather services, as regions attempt to predict possible arrival dates, so that crop producers can better prepare for their arrival. Various methods can be employed to diffuse the effects of a harmful frost, such as placing small heating systems throughout a crop area, continuously sprinkling water on crops

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throughout the night, or, on a smaller scale, placing simple screening cloths around a home garden. Farmers and scientists are continuing to experiment with new methods to avoid the harmful effects of black frost on vegetation. Frost harms plants by forming ice in and around cells. The water around the cells is purer than that inside the cell, so it will usually freeze first. Those plants that have greater quantities of solutes within their cells are more resistant to frost and can withstand cold temperatures more easily than those plants with little solute in their water. Plant damage from frost is determined by the type of plant, the stage of growth of the plant, and the length of time the temperature is low enough for frost formation. READING LIST The Encyclopedia of the Atmospheric Environment on-line. Available: http://www.doc.mmu.ac.uk/aric/eae/Weather/Older/Frost. html. The Weather Doctor. Available: http://www.islandnet.com/∼see/ weather/whys/frost.htm. About Frost by Steve Horstmeyer. Available: http://www.shorstmeyer.com/wxfaqs/frost/frost.html. UCLA Department of Atmospheric Science on-line. Available: http://www.atmos.ucla.edu/web/. Iowa State University—On-line Case Studies. Available: http://www.iitap.iastate.edu/jhodson/idot/frost/jan1/frost1.html. Dew and Frost. Available: http://www.nssl.noaa.gov/∼cortinas/ 1014/112 2.html. ASK—A—SCIENTIST Archive, Argonne National Laboratory. Available: http://newton.dep.anl.gov/askasci/wea00.htm. When Does The Last Frost Usually http://www.crh.noaa.gov/gjt/frost.htm.

Occur?

Available:

How Does Frost Injury Occur? Available: http://www.gov.on.ca/ OMAFRA/english/crops/field/news/croppest/cp0798 w.htm. Sterling Watch/Warning Definitions. Available: http://www.erh. noaa.gov/er/lwx/Defined/. Cooling Air. Available: http://www.doc.mmu.ac.uk/aric/eae/ Weather/Older/Cooling Air.html. Frosty Cars. Available: http://www.weatherwise.org/qr/qry.frostycar.html. Frost Damage, Control, and Prevention—Fruit and Vines. Available: http://www.pir.sa.gov.au/pages/agriculture/horticulture/ frostdamagefs.pdf. Frost Risk Assessment and Damage. Available: http://www.pir.sa. gov.au/pages/agriculture/horticulture/frost risk.htm:sectID =445&tempID =11.

FROST DAMAGE ARTHUR M. HOLST Philadelphia Water Department Philadelphia, Pennsylvania

Frost is ice formed by the condensation of atmospheric water vapor on a surface. When low temperatures are present in a certain region, the potential for frost damage to plant life exists in that region. Frost damage can injure plants permanently or slow plant development. Several

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factors dictate the extent and severity of frost damage to plants in any given region. Frost damage can have profound effects on agriculture and ecosystems. Frost is most likely to form on a cold, clear night that has been preceded by a cold and cloudy day. Lack of wind is vital to a developing frost. The little heat that was stored in the ground during the day will dissipate more quickly overnight. If the dew point has dropped below freezing, the result, is a heavy frost. As conditions change from day to night, an air temperature drop of 1 ◦ C per hour is a signal that a frost is likely to develop. Even if the conditions of freezing temperatures and a calm night are present, some areas will be more susceptible to frost damage than others. Fields that have lighter soils, which dry out faster, fail to insulate the soil below. This will prevent the natural warming by soil radiation of the air directly above the soil surface and increase the likelihood that a heavy frost will form. Recently cultivated fields will suffer the same fate. Low-lying valleys, where cold dense air cannot be affected by winds, can be heavily damaged. Areas of a field that are close to the edge of a crop formation are also susceptible. In these areas, grass near a crop formation acts as a blanket or insulator, preventing warm soil from heating cold air directly above it. Finally, areas that have recently been treated with herbicides are more susceptible to frost damage. Herbicide stress on a plant can be compounded by cold stress from the weather, increasing the possibility of frost damage. Frost damage is evidenced by a variety of symptoms on plants. Plant leaves are the best indicators of frost damage. Frost damage on the youngest leaves of a plant (the top leaves) is often seen as a burn on the tips of the leaves. More severe damage is a darkening of the entire leaf. In the most extreme form, the entire plant takes on a black appearance. This darkening is evidence that the frost penetrated and destroyed cell membranes of the plant. Severe darkening of this kind is sometimes referred to as a ‘‘killing frost.’’ Whether a killing frost has set in on plant life may not be noticeable until a day or two after the frost. If the plant has turned almost completely brown, chances of recovery are not good. However, a closer look may reveal that the lower part of the plant, or the pseudostem, is still green, a good sign that some recovery from the damage may be possible. The three most important factors in determining the ability of plant life to withstand damaging frost are the plant’s maturity, its health prior to a frost, and the weather immediately following the frost. Susceptibility to frost damage increases as plant development increases. As the growing season progresses, the chances of weather conditions conducive to a damaging frost decrease. Young plants are less susceptible to frost damage that will lead to a plant’s death because their growing points are still below ground, insulated from freezing temperatures. However, should frost injury occur at this young stage, it could severely delay growth as the season progresses and affect the overall harvest. More mature plants present more opportunities for frost damage. Mature plants have more exposed leaves and may have growing points above the earth’s surface. Damage to the outside of a mature plant can constrict future growth. Plant health prior to a frost also determines the ability of a plant to recover. If plants

have been continually exposed to cold stress, herbicides, excessive moisture, or disease, even the most minimal frost can be debilitating. Finally, the weather following frost damage plays an important role in the plant’s recovery. If warm temperatures follow frost damage, a plant’s ability to recover increases. Worldwide, 5–15% of all agricultural production is lost to frost damage each year. Frost can also cause a loss of food supplies for an animal species by killing leaves, seeds, and fruits. READING LIST www.epa.gov—United States Environmental Protection Agency—Office of Pesticide Programs. www.sciencedaily.com/releases/2000/10/001017073120.htm— Science Daily Magazine—Climate Change Shifts Frost Seasons & Plant Growth. www.agric.gov.ab.ca/crops—Alberta Agriculture, Food, And Rural Development—Frost Damage to Cereals. www.pioneer.com/usa/crop—Pioneer Hi-Bred International, Inc.—Microclimatic Effects on Frost Damage, Early Season Frost Damage to Corn. www.pir.sa.gov.au/pages/agriculture—PIRSA Agriculture— Frost Risk Assessment and Damage. Carter, P.R. (1995). Late spring frost and post-frost clipping effect on corn growth and yield. J. Prod. Agric.. Kunkel, K.E. and Hollinger, S.E. (1995). Late spring freezes in the central USA: Climatological aspects. J. Prod. Agric. Nielsen, R.L. (1999). Assessing frost damage to young corn. Purdue pest management and crop production newsletter. Purdue Univ., 27 May 1999.

THE GLOBAL WATER CYCLE U.S. Global Change Research Program

USGCRP-supported research on the global water cycle focuses on: (1) the effects of large-scale changes in land use and climate on the capacity of societies to provide adequate supplies of clean water; and (2) how natural processes and human activities influence the distribution and quality of water within the Earth system and to what extent the resultant changes are predictable. Specific areas include:

This article is a US Government work and, as such, is in the public domain in the United States of America.

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identifying trends in the intensity of the water cycle and determining the causes of these changes (including feedback effects of clouds on the global water and energy budgets as well as the global climate system); predicting precipitation and evaporation on timescales of months to years and longer; and modeling physical/biological processes and human use of water, to facilitate efficient water resources management. The USGCRP budget includes $311 million in FY 2003 for research and observations related primarily to the Global Water Cycle. The Global Water Cycle program studies the movements and transformations of water, energy, and water-borne materials through the Earth system and their interactions with ecosystems. The movements and transformations of water are important because they appear to control the variability of the Earth’s climate and they provide an essential resource for the development of civilization and the Earth’s environment. Figure 1 schematically illustrates the movements and transformations. This cycling involves water in all three of its phases—solid, liquid, and gaseous—and exchanges large amounts of energy as water moves and undergoes phase changes. Therefore, the water cycle operates necessarily on a broad continuum of time and spatial scales.

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Water vapor is a greenhouse gas that maintains temperatures in a range required by life on Earth. Many of the uncertainties in the current projections of the effects of the atmospheric buildup of carbon dioxide are related to the feedbacks between the climate and the water cycle. While warmer temperatures enable the atmosphere to hold more water leading to further warming, the complex interactions among changing cloudiness, precipitation patterns, land cover, and decreasing snow and ice cover have limited the quantitative understanding of the links between water and climate warming. Water is not evenly distributed over the globe, nor is it always accessible for human use. Society is becoming more vulnerable to variations in the water cycle as a result of expanding populations and increasing water use. The increasing demands for water accompanied by the growing economic losses from droughts and floods place pressure on the science community to develop the knowledge and tools needed to manage our limited water resources more effectively. There are large potential paybacks from increased investments in scientific research to improve the monitoring and prediction of the global water cycle variations and in water management applications.

Figure 1. Conceptualization of the water cycle.

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On a national basis, near-crisis situations have occurred in several dry southwestern river basins, including the Colorado and Rio Grande, where overallocation has taken place. Recent drought conditions and rapid development in these basins have exposed the intensity of competition that exists over the available water resources. The development of a capability to predict where water management crises will emerge due to a drought or extended flood conditions is a priority for the Global Water Cycle program. The ability to provide probabilistic forecasts of rainfall and snowfall at various time and space scales is at the center of all potential applications of climate change science and climate information systems. The program has research activities directed at developing experimental predictions that will ultimately benefit society through better protection of human health and assets, and more efficient water system management and infrastructure planning. Human activity is an integral part of the water cycle. A recent USGCRP-commissioned report, A Plan for a New Science Initiative on the Global Water Cycle, issued in 2001, concluded that, among other priorities, there is a pressing need to determine the causes of water cycle variations on both global and regional scales, and to what extent these variations are induced by human activities. In view of this emerging link between water science and water resource issues, the USGCRP global water cycle strategic plan addresses two major questions: (1) What are the effects of large-scale changes in land use and climate on the capacity of societies to provide adequate supplies of clean water, and (2) how do natural processes and human activities influence the distribution and quality of water within the Earth system and to what extent are resultant changes predictable? Stakeholders are helping to define the Global Water Cycle program at the catchment and larger river basins scales. Users are interested in better forecasts of precipitation, runoff, and soil moisture. Reservoir management decisions require forecast lead times of up to seasons and, in some cases, years. For planning reservoirs, dam recommissioning, and water control infrastructure, and developing new proposals for water law, projections of water variability are required on the decadal to century timescales. The USGCRP Global Water Cycle program focuses on characterizing, explaining, and predicting variability and long-term changes in the global water cycle and their impacts. To address the issues arising from the intimate role of the water cycle in controlling climate variability on seasonal to multidecadal timescales, the program investigates the pathways of water movement between the biosphere and surface hydrologic systems, the atmosphere, and the oceans, as well as feedback processes between climate, weather, and biogeochemical cycles. Because the biosphere is a substantial regulator of the Earth’s carbon cycle, the global water cycle maintains a considerable influence upon the global pathways of carbon. Globally, the cycling of water and its associated energy and nutrient exchanges among the atmosphere, ocean, and land determine the Earth’s climate and cause much of climate’s natural variability.

A critical contribution of the USGCRP to Federal water activities lies in the benefits that come from drawing together the wide range of programs and expertise from different agencies with the capabilities of the academic community to address these complex issues. The elements of the management structure that the USGCRP has put in place during the past year include: (1) Interagency Global Water Cycle working group, (2) Global Water Cycle scientific steering group, and (3) Global Water Cycle program office. The linkages between the global water cycle, the global carbon cycle, and climate will be explored in the coming year through this strengthened program management structure. SEE ALSO: Water Cycle [also available: PDF Version]. Chapter 5 from the Strategic Plan for the Climate Change Science Program (July 2003). See also the draft white paper, The Global Water Cycle and Its Role in Climate and Global Change [PDF] (posted 27 Nov 2002). Water Cycle. Presentation from Breakout Session 8 of the US Climate Change Science Program: Planning Workshop for Scientists and Stakeholders, 3–5 December 2002, Washington, DC. Climate Variability—Atmospheric Composition— Water Cycle. Presentation from Breakout Session 19 of the US Climate Change Science Program: Planning Workshop for Scientists and Stakeholders, 3–5 December 2002, Washington, DC.

GROUND-BASED GPS METEOROLOGY AT FSL SETH I. GUTMAN KIRK L. HOLUB NOAA Forecast Systems Laboratory

INTRODUCTION Water vapor is one of the most important components of the Earth’s atmosphere. It is the source of precipitation, and its latent heat is a critical ingredient in the dynamics of most major weather events. As a greenhouse gas, water vapor also plays a critical role in the global climate system: it absorbs and radiates energy from the sun and affects the formation of clouds and aerosols and the chemistry of the lower atmosphere. Despite its importance in climate and weather prediction, water vapor has been one of the most poorly measured and least understood components of the Earth’s atmosphere. Researchers at FSL and elsewhere are utilizing recent technology to reverse this situation. The ability to use the Global Positioning System (GPS) to make accurate refractivity measurements under all weather conditions has led to the development of a promising new meteorological observing system for NOAA. The This article is a US Government work and, as such, is in the public domain in the United States of America.

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first and most mature application of ground-based GPS meteorology involves the measurement of integrated (total column) precipitable water vapor (IPW) in the atmosphere. The GPS-IPW technique is more advantageous than conventional water vapor observing systems because of its low-cost, high-measurement accuracy, all weather operability, and long-term measurement stability. Further, GPS-IPW requires no external calibration, operates unattended for long periods with high reliability, and is easily maintained. Since GPS-IPW measurements are compatible with satellite data retrievals, they provide an independent method for calibrating and validating global satellite observations. These positive attributes, however, are accompanied with one major disadvantage: GPS-IPW provides no direct information about the vertical distribution of water vapor in the atmosphere. In an attempt to mitigate this deficiency, researchers at government laboratories and universities around the world are investigating the best ways to use GPS-IPW as a ‘‘proxy quantity’’ for moisture profiles in weather forecasting. In this article we discuss how IPW is now calculated from GPS signal delays and the potential use of slant-path measurements in numerical weather prediction models. Preliminary results of the effect of GPS-IPW on numerical weather prediction, the demonstration network, data and product availability, and plans for the operational network are also described. CALCULATING IPW FROM GPS SIGNAL DELAYS GPS signals are delayed as they pass through the Earth’s atmosphere (Fig. 1). The signal delay caused by the presence of free electrons in the ionosphere makes the largest contribution to the total atmospheric delay. Because the ionosphere is a dispersive medium, the velocity of the GPS signals is frequency dependent and its impact can be effectively eliminated by using dual frequency receivers. Below the ionosphere, in the electrically neutral portion of the atmosphere, refraction (that is, slowing and bending) of the GPS signal is caused by changes in temperature,

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pressure, and water vapor. Most of this delay occurs in the troposphere, which extends from about 9 km at the poles to about 13 km at the equator. The primarily tropospheric delay consists of a hydrostatic (or dry) component caused by the mass of the atmosphere and a wet component (the wet delay) caused by the dipole moment of the water vapor molecule. The contributions of the wet and dry components of the tropospheric signal delay are in the same proportion as the wet and dry components of the atmosphere. FSL currently collects GPS observations from a demonstration network of 55 sites (Fig. 2) and processes them to produce IPW measurements every 30 minutes using the scheme shown in Fig. 3. The first step in obtaining IPW from GPS observations is to determine the zenith-scaled delay caused by the neutral atmosphere. This delay is commonly referred to as the zenith tropospheric delay (ZTD), and is calculated from carrier phase and range observations made by networks of GPS receivers. The calculation is made using GPS analysis software such as GAMIT (GPS At MIT), which in addition to the GPS observations, requires improved satellite orbits and parameters describing the orientation of the Earth in space and time. Next, the ZTD is separated into its wet and dry components using additional observations made by collocated surface meteorological sensors. The zenith- scaled hydrostatic delay (ZHD) is caused by the mass of the atmosphere directly above the site and can be estimated with great accuracy from a surface pressure measurement. The wet signal delay (ZWP) is caused by water vapor along the paths of the radio signals to all satellites in view, about 6 to 8 with the current GPS satellite constellation. ZWP is calculated simply by subtracting the hydrostatic delay from the tropospheric delay. The resulting wet delay can be mapped into IPW with an error of about 5 degrees using a quantity that is proportional to the mean vapor pressure-weighted temperature of the atmosphere (Tm). Tm may be estimated from a climate model, the surface temperature derived from a numerical weather prediction model, or measured directly using remote sensing techniques. FSL is planning to utilize modelderived Tm estimates operationally.

Figure 1. Signal delays caused by the atmosphere.

Figure 2. A map of the NOAA-FSL Global Positioning System Integrated Precipitable Water (GPS-IPW) Demonstration Network (55 sites) as of October 1999.

Figure 3. The FSL-developed data processing scheme used to produce IPW measurements. 246

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Figure 4. Scatterplot of GPS and rawinsonde observations of integrated precipitable water vapor at the ARM CART site near Lamont, Oklahoma, between January 1996 and September 1999.

Integrated precipitable water calculated from GPS signal delays is physically identical to integrated measurements or retrievals made by other upper-air observing systems including rawinsondes, ground-based microwave water vapor radiometers, or satellite microwave and infrared instruments including sounders and interferometers. Comparisons of GPS and radiosonde-derived total column water vapor have been carried out continuously since 1996 under all weather conditions at the DOE Atmospheric Radiation Measurement site near Lamont, Oklahoma. Results from 3600 comparisons (to September 1999) indicate a mean difference of 0.08 mm and a standard deviation of 2.1 mm (Fig. 4). SLANT-PATH SIGNAL DELAY MEASUREMENTS Recent investigations by FSL director A.E. MacDonald and Yuanfu Xie (of the Forecast Research Division) of the potential use of line-of sight estimates of path-integrated water vapor (derived from slant-path GPS signal delay

measurements) to retrieve the 3-D moisture field have been very interesting and potentially significant. The experiments involve assimilating simulated slant-path moisture measurements from a wide area network of closely spaced stations into the Quasi-Nonhydrostatic (QNH) model using variational techniques. In recent research, their simulations indicate that it may be possible to recover the three- dimensional structure of the moisture field from a densely spaced network of ground-based GPS receivers making a single line-of- sight, or slant path, measurement of the signal delay to all satellites in view. The configuration of the GPS satellite constellation as seen from Boulder, Colorado, between 1200 and 1300 UTC on 28 September 1999 is shown in Fig. 5. A GPS satellite moves across the sky at the rate of about 30 degrees per hour. Although 10 satellites are visible above the horizon in this example, six to eight would be more typical at any one time. Making a slant-path signal delay measurement with the same accuracy as a zenith-scaled measurement is

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Figure 5. Configuration of the GPS satellite constellation as seen from Boulder between 1200 and 1300 UTC 28 September 1999.

not trivial. The sources of measurement error that are successfully managed through geodetic modeling of the zenith tropospheric signal delay will have to be dealt with in other ways. Although some of the most important information about the structure of the atmosphere can be obtained from low-angle observations, measurement errors increase significantly along with the negative impact of multipath reflections from nearby obstacles as satellites approach the horizon. One way to mitigate these problems is to utilize advanced GPS receivers and antennas that maximize the ability to track satellites under all conditions and reject multipath reflections. Unfortunately, not all problems can be eliminated through the selection of hardware, and advanced data processing techniques will be needed as well. Research at Scripps Institution and the University of Hawaii into ways to monitor the accuracy of GPS orbit

predictions suggests that these techniques can also be used to reduce systematic errors in slant-path signal delay or refractivity measurements to individual satellites. EFFECT OF GPS-IPW DATA ON THE ACCURACY OF NUMERICAL WEATHER PREDICTION Since 1997, parallel runs with and without GPS have been carried out using the research version of the Rapid Update Cycle (RUC-2) model to assess how GPSIPW data affect the accuracy of numerical weather prediction. Results from the first two years using optimal interpolation techniques have been encouraging despite the fact that the observations came from only a limited number of widely spaced sites. Model runs using data acquired from more sites over a larger area through September 1999 confirm improvements

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Figure 6. GPW-IPW installation at the NOAA Profiler Network site at Platteville, Colorado.

in forecast accuracy, especially under conditions of active weather. Therefore, NOAA meteorologists expect significant improvements in short-term forecasts of clouds, precipitation, and severe weather when high-resolution numerical weather prediction models routinely use data from a nationwide network of GPS-IPW systems in conjunction with data from other observing systems and advanced data assimilation techniques. The decision to implement ground-based GPS Meteorology (GPS-Met) as a next-generation upper-air observing system will be supported in part by promising assessments such as this one. In anticipation of a favorable decision, network design and implementation options for a national network of ground-based GPS- IPW systems are being evaluated at FSL. GPS-IPW DEMONSTRATION NETWORK The rapid development of the GPS-IPW Demonstration Network for meteorological remote sensing has been made possible by a fortuitous synergy with the positioning and

navigational applications of GPS by the U.S. Coast Guard and U.S. Department of Transportation. As of October 1999, the data acquisition component of the demonstration network consisted of 55 GPS-IPW systems operating in the continental United States and Alaska. Thirty-four systems are currently installed at NOAA Profiler Network (NPN) sites, seven at sites belonging to other NOAA organizations or institutions affiliated with NOAA, 11 belong to the U.S. Coast Guard Maritime Differential GPS (DGPS) system, and three are at the Department of Transportation Nationwide Differential GPS facilities. Typical sites from each organization are illustrated in Figs. 6–9. In addition to supporting the assessment of GPS as a possible next-generation upper-air observing system, the GPS-IPW Demonstration Network is designed to help NOAA accomplish the following tasks: • Evaluate the engineering and scientific bases of ground- based GPS-Met, including advanced data acquisition and processing techniques.

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Figure 7. GPS-IPW installation at the Scripps Institution of Oceanography at La Jolla, California.

• Develop and test strategies to build, monitor, operate and maintain large networks of GPS reference stations for meteorological remote sensing. • Develop techniques to acquire, process, and quality control GPS observations and data products. • Provide observations and derived meteorological products to users (such as forecasters, modelers, researchers) and data archives. • Transfer ground-based GPS-Met technologies to operational use in weather forecasting and climate monitoring. • Other possible applications under investigation include calibration and validation of environmental satellite data and improved positioning and navigation services. All ground-based observing systems in the GPSIPW Demonstration Network consist of dual-frequency GPS receivers and antennas, and collocated surface meteorological sensors. These systems are located at sites where shelter, power, and communications are available to operate and collect

data from the instruments, and transmit these data in real or near real time to one of two locations. The generalized flow of data and products from the network is illustrated in Fig. 10. DATA AND PRODUCT AVAILABILITY GPS and surface meteorological observations from the GPS-IPW Demonstration Network sites are available to the general public in near real time through the NOAA National Geodetic Survey. Information and raw data may be acquired via the Web. Processed data, including GPS signal delays and integrated precipitable water vapor, are available shortly after improved NAVSTAR GPS satellite orbits and Earth Orientation Parameters are available from one of the International GPS Service (IGS) tracking stations. This usually occurs within 24 hours of the close of the day, but efforts to accelerate the process and make improved orbits available within 1–3 hours are well underway. IPW and other products may be acquired from the FSL Demonstration Division, GPS-Met Observing Systems Branch.

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Figure 8. GPS-IPW installation at the U.S. Coast Guard Differential GPS site at Cape Canaveral Air Force Station.

PLANS FOR NETWORK EXPANSION AND IMPROVEMENT Our primary goals in 2000 are to continue to expand the demonstration network, demonstrate distributed data processing using low-cost PCs instead of high-end workstations, and implement real-time data processing. Expansion of the Demonstration Network. Now that all NOAA Profiler Network sites have been equipped with GPS-IPW systems, expansion of the network will mostly proceed by installing GPS Surface Observing System (GSOS) packages at U.S. Coast Guard Maritime DGPS and Department of Transportation NDGPS sites. Depending on the availability of funds and the status of interagency agreements under review, during the next year we hope to install 21 new systems at DGPS sites (mostly in the Mississippi Valley and Great Lakes regions), 11 NDGPS sites, and one at the Department of Energy ARM facility at Point Barrow, Alaska (Fig. 11). Implementation of Real-time Data Processing. We define real-time data processing as acquiring and processing GPS and ancillary observations to

yield signal delay or IPW calculations within a single numerical weather prediction assimilation cycle. In the case of the Rapid Update Cycle, running operationally at the National Centers for Environmental Prediction, this is approximately 75 minutes. Real-time data processing techniques are being tested and evaluated in a collaborative effort involving FSL, the Scripps Permanent Orbit Array Center, and the University of Hawaii at Manoa. Techniques involve acquiring data from a subset of the IGS global tracking network and using these observations to produce an improved retrospective orbit with only about 2-hour latency. An orbit prediction that covers the data gap is also made, and it is this short-term prediction that is used to calculate IPW. In theory, the error in a prediction that spans only 2 or 3 hours will be proportionally less than an error made over an interval of 36–48 hours. Real-time quality control techniques are also under evaluation. The most promising involve continuous monitoring of the relative positions of a number of sites, and using these data to infer changes in orbit

Figure 9. GPS-IPW installation at the DOT National Differential GPS site at Whitney, Nebraska.

Figure 10. Flow of data and products from the GPS-IPW Demonstration Network.

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Figure 11. Planned expansion of the Demonstration Network to about 92 sites during 2000.

Figure 12. Expected configuration of the NOAA/FSL GPS-IPW Demonstration Network by 2005. Sites in Hawaii and the Caribbean Sea are not shown.

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Figure 13. An Automated Surface Observing System (ASOS) installation at Cape Hatteras, North Carolina.

Figure 14. GPS receiver placement on top of FSL’s new office building, the David Skaggs Research Center.

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Figure 15. A map of the AWIPS offices.

accuracy for specific satellites in the constellation. When a problem is encountered, the satellites are removed temporarily from the ephemerides until an updated orbit can be produced. Distributed Data Processing. Recent advances in lowcost PC processor speed and memory will be utilized to perform data processing in a fully distributed environment. During this year we have demonstrated the ability to partition a large network into smaller subnetworks, process each independently in substantially less time with no significant loss of accuracy and precision. Operational GPS-IPW Network Implementation Strategy. The expansion of the GPS-IPW Demonstration Network to about 200 sites, and the transition from retrospective to real-time data processing will enable us to assess the impact of these data on weather forecast accuracy. Based on the results of these studies, a decision to implement ground-based GPS-IPW as a next-generation upper-air observing system for NOAA is expected. The following plan has been developed to expand the demonstration network to an operational network of about 1000 sites with an average station spacing of somewhat less than 100 km (Fig. 12). • Once transition of the GPS-IPW Demonstration Network to operational status has become a reality, receivers and antennas will be upgraded. Communications will transfer from FTS-2000 to the AWIPS [Advanced Weather Interactive Processing System] communications systems via the Internet. • GPS receivers will be added to about 800 Automated Surface Observing (ASOS) sites (sample site shown in

Fig. 13). The reason for collocating GPS at ASOS sites is to take advantage of the surface meteorological data and site infrastructure, including shelter, power, data communications, field maintenance, and logistics support. This will minimize implementation time and life-cycle cost. The GPS antenna installation at a typical ASOS site will resemble the one at FSL’s new location, the David Skaggs Research Center (Fig. 14). • Data processing hardware, software, and training will be provided to all AWIPS offices (Fig. 15). [Editor’s Note: More information on the topics covered here is available by contacting Seth Gutman, who can provide copies of published articles which include a list of references.]

CLIMATE AND WATER BALANCE ON THE ISLAND OF HAWAII JAMES O. JUVIK D.C. SINGLETON G.G. CLARKE University of Hawaii Hilo, Hawaii

INTRODUCTION The island of Hawaii, with a surface area of only 10,455 km, exhibits a spectacular range of climatic This article is a US Government work and, as such, is in the public domain in the United States of America.

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diversity comparable with that found on large continents. Three major factors contribute to this climatic diversity: 1. Topographic relief. The volcanic mountains of Mauna Kea and Mauna Loa reach summit elevations of 4,205 m and 4,168 m, respectively. The attitudinal range provides for a diversity of temperatures, and the mountains themselves are barriers that induce orographic precipitation. 2. Large-scale synoptic wind field. The strong and persistent northeast trade winds interact with the island topography to produce distinctive windward and leeward climates. The associated upper-level trade wind inversion exerts a particularly strong control on mountain precipitation gradients. 3. Local circulation. Differential heating and cooling of the land, water, mountain, and lowland areas on Hawaii give rise to localized wind regimes which add to the island’s climatic diversity. KOPPEN CLIMATIC ZONES Integrating the attitudinal temperature gradients with the annual, seasonal, and spatially variable rainfall

Figure 1. Distribution contours of mean annual rainfall (mm), superimposed on topographic map of the island of Hawaii. (Redrawn from 2,3).

regimes results in a diverse combination of climatic environments. The Koppen climate classification uses monthly temperature and precipitation characteristics in a descriptive system that distinguishes broad regional and global climatic zones. The system has been often criticized for its empirical approach and lack of emphasis on ‘‘dynamic processes’’ (e.g., 1); however, as a ‘‘first approximation’’ the Koppen classification offers useful insights into regional climatic patterns. Four broad Koppen climatic zones are distinguished on the island of Hawaii. They are organized primarily as concentric attitudinal bands on the mountain slopes. Figure 2 illustrates the spatial distribution of these Koppen climatic types on the island. The map was constructed on the basis of temperature (absolute or extrapolated) and precipitation data from 55 island stations. Discussions of the zones follow. Humid Tropical Zone (A climates) Characterized by warm temperatures throughout the year and relatively high annual rainfall, humid tropical climates occupy the lower slopes of the island from sea level to about 450 m (slightly higher in warmer areas of leeward

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Kona). This tropical zone may be further differentiated on the basis of rainfall seasonality. Large-scale synoptic disturbances in winter (mid-latitude cyclonic storms) produce substantial rainfall that is to some extent independent of slope aspect or elevation, and as a result most locations on the island exhibit an absolute winter maximum in rainfall. However, windward areas of Hawaii also receive substantial orographic rainfall throughout the year, with the result that there is no distinct dry season (Af climate). Lowland areas on the island that are transitional in location between windward and leeward receive less orographic rainfall (since they are not oriented normal to trade wind flow) and exhibit a distinctive summer dry season (As climate). Humid summer-dry climates are not common anywhere in the world, since for most tropical locations rainfall is at a maximum in the summer, the result of increased convective instability in the high-sun period. Outside of Hawaii the As climate type occurs only in southern Madras (India) and adjacent northern Sri Lanka. The leeward or Kona coast of Hawaii contains the only extensive area of summer maximum rainfall in the Hawaiian archipelago (Aw, winter-dry climate). Isolated from the prevailing trade wind flow by intervening high mountains, the Kona coast’s dominant circulation pattern is formed by a localized land-sea breeze regime. Increased land surface temperatures in summer strengthen the daily sea breeze regime and increase convective instability, leading to a high frequency of afternoon thundershowers. The vertical structure necessary for thundershower

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development is further assured by the high mountains, which exclude the trade wind aloft and limit the potential for strong vertical wind shear. The presence of a strong shearing force would otherwise tend to destabilize these leeward convectional cells. Although there is generally a summer rainfall maximum throughout Kona, the Aw climate gives way to Af at elevations above 400 m, where, by virtue of general orographic position, there is adequate precipitation in all months. Arid and Semi Arid Zones (B climates) A classic rain shadow desert exists on the leeward side of the Kohala mountains. Smaller and lower (maximum elevation 1,670 m) than Mauna Kea and Mauna Loa, the Kohala mountains are incapable of blocking out trade wind flow to leeward. Having become depleted of moisture during windward ascent, the trades warm adiabatically to leeward, promoting a hot, arid zone. With only 190 mm of annual rainfall, Kawaihae on the leeward Kohala coast is the driest location in the Hawaiian archipelago. The Koppen system distinguishes two climatic subtypes, the true desert (BWh climate) and the semidesert (BSh climate) on the basis of relative aridity. In leeward Kohala the true desert gives way to semi-desert at higher elevations. 1 The Temperate (C) and Polar (E) climates as originally proposed by Koppen were not applied in high-altitude tropical environments, which, because of their orographic complexity,

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Figure 3. ‘‘Walter’’ climate diagrams for four Hawaii island stations (4).

Temperate Zone (C climates)1 Average air temperature in Hawaii decreases with altitude at the rate of about 0.55øC/100 m (Price, 1973). When the criteria of the Koppen classification are used, at elevations above 400–500 m on the mountain slopes, tropical climates grade to temperate as a result of decreasing average temperatures. As a result of the moderating influence of altitude, almost two-thirds of the ‘‘tropical’’ island of Hawaii possesses a temperate upland climate. The majority of this zone is characterized by warm summers and adequate precipitation in all months (Cfb climate). Except for the absence of a stronger season variability the upland Hawaii climates are analogous to those of similar Koppen designation in Pacific coastal areas of North America. Ascending orographic clouds lack of meteorological data, and absence of strong seasonality, were simply designated as highland climates (H). In more recent global and regional climatic maps of the tropics, highland C and E climatic areas are frequently portrayed in order to show approximate attitudinal analogs for these broad latitudinal climatic zones.

compressed between the rising mountain slope and an upper-air temperature inversion produce frequent ground level mountain fog, an important moisture source for upland vegetation (Juvik and Perreira, 1974). At still higher elevations on Mauna Kea and Mauna Loa (above 2,000 m) there is a tendency toward summer drought. The increased strength and frequency of the trade wind inversion in summer (modal elevation 1,800 m) inhibits the vertical penetration of orographic clouds and precipitation to the higher slopes. This summer-dry zone (Gsb climate) also occurs at a lower elevation in leeward Kohala, Mauna Kea, and Mauna Loa, where summer orographic precipitation is largely absent. Above 2,500 m on both Mauna Loa and Mauna Kea the summer-dry regime changes from warm to cool (Gc climate). Alpine (periglacial) Zone (E climates) Above 3,200-m level on Mauna Kea and Mauna Loa all months have a mean temperature below 10 ◦ C, and the climates are classified as periglacial (ET). Nighttime freezing is common throughout the year. Although it

CLIMATE AND WATER BALANCE ON THE ISLAND OF HAWAII

exhibits a winter maximum, annual rainfall is very low (200–400 mm) and variable. Above the 3,500-m level, winter snowfall accounts for a substantial portion of the seasonal precipitation. Koppen used the 10 ◦ C (warmest month) boundary to separate the C and E climates on the basis that trees will not normally grow where mean temperatures fall below this level. Hence E climates characterized the treeless arctic tundra. The upper tree line of Mauna Kea (3,000 m) corresponds fairly closely to the C/E boundary mapped in Fig. 2. On Mauna Loa the tree line is much lower for edaphic reasons (recent lava).

WATER BALANCE The preceding discussion of Koppen climatic zones on Hawaii provides a general overview of the dramatic range in regional climatic diversity found on the island. However, this descriptive approach says little about the direct linkage of climate to physical and biological processes at the earth/atmospheric interface. An integration of seasonal moisture supply (precipitation) with the evaporation and transpiration demands of the environment (determined primarily by solar energy inputs) provides an index of moisture surplus or deficit. Such indices can illuminate direct process/response relationships between climate and the terrestrial ecosystem. In an initial survey of water balance climatology on the island of Hawaii, Mueller-Dombois (4) constructed a series of climate diagrams 21 stations (see Fig. 3). This type of diagram, popularized by Walter and Lieth (5), portrays seasonal curves of mean monthly temperature and precipitation. According to Muller-Dombois (6) an index of precipitation efficiency is built into the diagrams by making one degree of temperature (Celsius) equal to two millimeters of precipitation in the scaling of the two ordinates. This is based on the assumption that monthly potential evapotranspiration (in millimeters) is roughly equal to twice the mean monthly temperature (7). Wherever the precipitation curve drops below the temperature curve, a drought season is indicated. Thus the graph is transformed into a water balance diagram with the temperature curve interpreted as an index of potential evapotranspiration.

259

A serious problem inherent in this graphing technique is the tendency to approximate evapotranspiration with a simple linear function of air temperature (i.e., the 2:1 ratio). Chang (8,9) has reviewed the problems of temperature-based estimations of potential evapotranspiration and points out that solar radiation rather than temperature is the primary forcing function in the evaporative process. Temperature-based estimates of evaporation implicitly assume a strong correlation between temperature and solar radiation. In Hawaii, as a result of advection and the buffering effect of the surrounding marine environment, there is generally poor correlation between solar radiation and temperature. In Hilo, for example, the range in mean monthly air temperature is only 1.4 ◦ C between June (24.2 ◦ C) and December (22.8 ◦ C). By contrast, the receipt of solar radiation in June (563 Ly; see solar radiation data for 1965 from Ref. 10) is more than twice that in December (263 Ly). It is obvious from the above comparison that temperature-based estimates of evapotranspiration cannot be expected to portray realistically the seasonal fluctuations implied in the radiation data. However, in the absence of a dense network of solar radiation monitoring stations on the island, upon which more sophisticated spatial modeling of evapotranspiration might be based, it is necessary to revert to some form of temperaturederived estimation in a ‘‘first approximation’’ of water balance regimes. Thornthwaite (11) has developed perhaps the most widely adopted method of estimating potential evapotranspiration. His empirical formula is based essentially on air temperature: (1) E = 1.6 (10T/I)a . Potential evapotranspiration E is computed from mean monthly temperature T and an empiric ‘‘heat index’’ I, which itself is an exponential function of temperature; a is a constant. To obtain mean monthly evapotranspiration, the values derived from eq. (1) are corrected for mean daylength and number of days in the month. The Thornthwaite equation, although subject to the general limitations of all temperature-based methods, might be expected to give better results than the Walter method in Hawaii,

Figure 4. Monthly estimated potential evapotranspiration and measured pan evaporation for Hilo and Pahala data.

260

CLIMATE AND WATER BALANCE ON THE ISLAND OF HAWAII

since potential evapotranspiration is expressed as an exponential rather than linear function of temperature. In Fig. 4, monthly values of potential evapotranspiration derived by both the Walter and the Thornthwaite methods have been plotted along with class ‘‘A’’ panevaporation data for Hilo and Pahala. It is evident that Walter grossly underestimates pan evaporation (here assumed to be equal to potential evapotranspiration) and also fails to detect the seasonal rhythm apparent in the pan data. Thornthwaite also underestimates pan evaporation but does so in a fairly consistent manner and achieves a strong covariation with the pan data in seasonal rhythm. This suggests that the Thornthwaite method might be useful in Hawaii if a correction factor could be derived to compensate for the consistent underestimation exhibited in Fig. 4. In Fig. 5, monthly values of the Thornthwaite potential evapotranspiration estimate are plotted against pan evaporation for Hilo and Pahala. With a regression coefficient of 0.844, approximately 71% of the observed variation in pan evaporation can be explained by variation in the Thornthwaite estimate. (The regression coefficient is significant at 0.01 level.) Potential evapotranspiration Y can thus be reasonably predicted from the Thornthwaite values X by the linear regression equation Y = 42.8 + 1.016 (X)

(2)

Before eq. (2) can be applied as a general (islandwide) correction factor for the Thornthwaite potential evapotranspiration estimate, it must be verified that the relationship established in Fig. 5 (for two lowland locations) is equally valid for mid- and high-altitude areas of the island. There are no class ‘‘A’’ pan evaporation data for inland mountain areas of Hawaii with which the lowland-derived correction factor might be compared. However, Juvik and Clarke (12) have accumulated limited experimental data on mountain evaporation gradients in Hawaii Volcanoes National Park on the east flank of Mauna Loa.

Figure 6. Constant-level pan evaporimeter. a) field installation with inner tube reservoir; b) evaporimeter detail. Note foam insulation around evaporation pan.

Figure 5. Relationship between monthly class ‘‘A’’ pan evaporation and estimated monthly potential evapotranspiration (Thornthwaite) for Hilo and Pahala data.

These data were obtained by using four constant-level pan evaporimeters (Fig. 6) situated along an attitudinal transect between sea level and 2,000 m. In Fig. 7, measured mean daily evaporative rates (averages from 133 days of simultaneous readings taken from September 1974 through May 1975) are plotted against elevation. There is a clear linear decrease in evaporation over the attitudinal range surveyed (approximately 0.72 mm/day/1,000 m). Figure 7 also shows the corrected (eq. 2) Thornthwaite potential evapotranspiration values (mean of 9 months, September to May) derived from temperature-recording stations that occur near the evaporimeter transect. There is good agreement between the Thornthwaite and the evaporimeter values (differences range from 1% to 12%), largely because air temperature also decreases linearly with elevation. On the basis of the close agreement in Fig. 7, the corrected Thornthwaite estimate was considered acceptable to use for all areas of the island

CLIMATE AND WATER BALANCE ON THE ISLAND OF HAWAII

Figure 7. Relationship between measured and predicted evapotranspiration along an attitudinal transect in Hawaii Volcanoes National Park on the east flank of Mauna Loa (pan data from 12).

in the derivation of monthly and annual potential evapotranspiration from temperature data. Corrected Thornthwaite estimates of monthly and annual potential evapotranspiration were computed from standard tables (13) and eq. (2), for 30 stations on the island of Hawaii. The evapotranspiration data were then integrated with monthly precipitation values to produce seasonal water balance diagrams (Fig. 8). Because some of the water surplus received in the wet season is stored as soil moisture for utilization during dry periods, the computation of seasonal water balance must incorporate a parameter describing the moisture storage capacity of the soil.

261

On the geologically youthful island of Hawaii, soils are not generally well developed except for limited areas where ash deposits occur in high-rainfall zones. Recent lava flows exhibiting little or no soil development cover substantial portions of the island. The average depth to bedrock for 75 different Hawaii island soil types and subtypes has been calculated at 0.89 m with only moderate variation (14), lending quantitative credence to this stated geological youthfulness of the island. Soil moisture storage capacity has not been well studied for most Hawaiian soil types. A value of 125 mm/m is the average moisture capacity for ten different soil types for which data are available. If this is assumed to be representative, then the average soil moisture storage capacity for all Hawaii island locations would be 111.2 mm (i.e., 0.89 × 125). In the construction of water balance diagrams for all island stations this value was rounded off to 100 mm so that standard moisture depletion tables could be employed in water balance calculations (13). The 30 water balance diagrams constructed for the island depict both steep gradients and pronounced regional differences in seasonal moisture surplus and deficit. In Fig. 8 the difference between annual precipitation and potential evapotranspiration has been mapped in four zones: 1. Annual surplus exceeding 1,000 mm. This zone comprises 20% (2,100 km2 ) of the island area and is restricted to the high-rainfall regions of windward Mauna Kea, Mauna Loa, and the summit area of Kohala. The annual moisture surplus in this zone

262

CLIMATE AND WATER BALANCE ON THE ISLAND OF HAWAII

ranges as high as 3,377 mm (station 10) at middle elevations. All stations within this zone (stations 2, 6, 10, 11, 14, and 15) exhibit an absolute winter maximum in precipitation, and a secondary summer maximum also occurs at elevated stations where summer orographic precipitation is exaggerated (e.g., stations 2 and 14). 2. Annual surplus between 0 and 1,000 mm. This zone comprises 21% (2,200 km2 ) of the island area and extends from middle to high elevations on the windward slopes down to sea level in those areas where slope aspect is not oriented perpendicular to prevailing trade wind flow, and thus the orographic rainfall component is diminished. For the windward stations there is typically a moderate summer drought (stations 5, 7, 9, 13, and 17) from 2 to 5 months long. The increased strength of the trade wind inversion in particular limits summer rainfall at higher elevations. The localized core area of high convectional rainfall in Kona also falls within this moisture zone. However, here the deficit period occurs in winter (stations 24, 28, and 29) and is not severe. 3. Annual deficit between 0 and 1,000 mm. This zone comprises 54% (5,600 km2 ) of the island area and occupies a predominantly leeward location on Kohala, Mauna Kea and Mauna Loa. The drought period may be concentrated in either the summer

(on the windward side) or the winter (on the Kona side) and is typically 6 to 12 months long. 4. Annual deficit exceeding 1,000 mm. This zone comprising 5% (550 km2 ) of the island area is restricted to leeward Kohala and north Kona. The annual moisture deficit may exceed 1,900 mm (station 1). SUMMARY The Thornthwaite water balance diagrams and map demonstrate graphically the tremendous climatic diversity on the island of Hawaii. Although the Koppen map (Fig. 2) shows only a relatively small portion of the island to be arid or semi-arid (BWh and BSh), from the water balance analysis it is evident that nearly 60% (zones 3 and 4 above) of the island experiences an annual moisture deficit. Acknowledgments This research was supported in part by grants from the Hawaii Natural History Association and the U.S. Department of Interior, Office of Water Resources Research.

BIBLIOGRAPHY 1. Carter, D.B. and Mather, J.R. (1966). Climatic classification and environmental biology. Publ. Climatol. 19(4): 305–390. 2. Taliaferro, W.J. (1959). Rainfall of the Hawaiian Islands. Hawaii Water Authority, p. 394.

HEAT OF VAPORIZATION 3. State of Hawaii (1970). An inventory of basic water resources ¨ dataAisland of Hawaii. Rep. R34, Dept. of Land and Natural Resources, Honolulu, Hawaii, p. 188. 4. Mueller-Dombois, D. (1966). Climate. Chap. IV. In: Atlas for Bioecology Studies in Hawaii Volcanoes National Park. Maxwell S. Doty and D. Mueller-Dombois. (Eds.). U.S. National Park Service, p. 507. (Republished as Hawaii Agr. Exp. Sta. Bull. 89, 1970.) 5. Walter, H. and Lieth, H. (1960). Klimadiagram-Weltatlas, Jena. 6. Mueller-Dombois, D. (1976). The Major Vegetation Types and Ecological Zones in Hawaii Volcanoes National Park and Their Application in Park Management and Research. In Proceedings of the First Conference in Natural Sciences, Hawaii Volcanoes National Park, edited by S. W. Smith, Department of Botany, University of Hawaii, Honolulu, 149–161. 7. Gaussen. (1954). 8. Chang, J.-H. (1959). An evaluation of the 1948 Thornthwaite classification. Ann. Assoc. Amer. Geogr. 49(1): 24–30. 9. Chang, J.-H. (1968). Climate and Agriculture. Aldine Publishing Co., Chicago, p. 304. 10. Lof, G.O.C., Duffie, J.A., and Smith, C.O. (1966). World Distribution of Solar Radiation. Rep. 21, Solar Energy Laboratory, Univ. of Wis., p. 59. (plus maps). 11. Thornthwaite, C.W. (1948). An approach toward a rational classification of climate. Geogr. Rev. 38: 55–94. 12. Juvik, J.O. and Clarke, G.G. (1976). Topoclimatic Gradients in Hawaii Volcanoes National Park (abstract). In Proceedings of the First Conference in Natural Sciences, Hawaii Volcanoes National Park, edited by S. W. Smith, Department of Botany, University of Hawaii, Honolulu, p. 113. 13. Thornthwaite, C.W., and J.R. Mather (1957). Instructions and tables for computing potential evapotranspiration and the water balance. Publ. Climatol. 10(3): 1–311. 14. Sato, H.H. et al. (1973). Soil Survey of Island of Hawaii, State of Hawaii, U.S.D.A. Soil Conservation Service, p. 115. (plus maps).

READING LIST Juvik, J.O. and Perreira, D.J. (1974). Fog interception on Mauna Loa, Hawaii. Proc. Assoc. Amer. Geogr. 6: 22–25. Price, S. (1973). Climate. In: Atlas of Hawaii. R.W. Armstrong. (Ed.). University of Hawaii Press, Honolulu, pp. 53–60.

Unita mass phase change H2O (liquid) H2O (vapor)

Initial equilibrium state

263

HEAT OF VAPORIZATION NARAINE PERSAUD Virginia Polytechnic Institute and State University Blacksburg, Virginia

HEAT OF VAPORIZATION The heat of vaporization (here denoted as Lv ) is defined as the heat added (or given off) when unit mass undergoes isobaric phase transformation in any closed two-phase, one-component liquid/vapor system. In engineering and meteorology, Lv is used in a restricted sense to mean the heat of vaporization of the two-phase liquid water/water vapor system. Although much of the subsequent discussion focuses on Lv , for this specific system as an example, the concepts covered are universally applicable to all fluid/vapor systems. As illustrated below (Fig. 1), for the liquid water/water vapor system, Lv represents the heat gained when unit mass of water in the system evaporates in the isobaric phase transformation H2 O (liquid) → H2 O (vapor). For the reverse phase change H2 O (vapor) → H2 O (liquid), i.e., condensation, Lv is lost from the system. This seemingly simple phase transition H2 O (liquid) ↔ H2 O (vapor) is the fundamental driving process of the earth’s hydrological cycle, the working principle of the steam engine that ushered humanity into the industrial revolution along with its (often negative) social and environmental pollution consequences, and the physical mechanism that maintains the body temperature of plants and warm-blooded animals. In general, the state of any closed two-phase, onecomponent system is defined by the state variables temperature (T in ◦ K), saturation vapor pressure (P in Pascal), and volume (V in m3 ). The behavior of any such system (generally termed as PVT systems) is usually represented as a family of experimental constant temperature curves (isotherms) on a P-V coordinate plane called an Amagat–Andrews diagram. The general shape of these experimental isotherms is illustrated below (Fig. 2). For the liquid water/water vapor system, the liquid and vapor phases coexist in equilibrium only at P-V coordinates between 2 and 3 along an isotherm, provided

Final equilibrium state

Final volume > Initial volume Water vapor, mass = m v, Pressure = Pvap, Temperature = T Liquid water, mass = m w, Temperature = T

Water vapor, mass = m v + 1 Pressure = Pvap, Temperature = T Liquid water, mass = m w − 1 Temperature = T

Heat in = L v Joules

Figure 1. Liquid Water/Water Vapor System.

264

HEAT OF VAPORIZATION

Vapor Pressure P (Pa)

4

3

2 T1 (°K) 1 Volume V (m3)

Figure 2. Amagat–Andrews Diagram.

that T1 is above the triple point temperature of water (0.01 ◦ C, i.e., the temperature at which ice, liquid water, and water vapor can coexist in equilibrium), and below the critical temperature (374 ◦ C, i.e., the temperature above which it is impossible to produce condensation by increasing the pressure). Between 2 and 1, the system can exist as vapor only, and as liquid between 3 and 4. Thus the liquid-vapor phase transition at a given temperature can only take place at constant pressure or vice-versa. Consequently, as shown in Fig. 1, isobaric liquid vaporization and condensation is necessarily an isothermal process, implying that the triple-point saturation vapor pressure is fixed (it is 611 Pa), and so is the saturation vapor pressure at the critical temperature (it is 2.21 × 107 Pa = 218.2 atm). Similar isotherms and parameters exist for all liquid/vapor systems. This observed behavior of closed two-phase, onecomponent systems is of course predicted by Gibb’s Phase Rule (1), namely F + N = C + 2, where F = degrees of freedom, i.e., the smallest number of intensive variables (such as pressure, temperature, concentration of components in each phase) that must be specified to completely describe the state of the system; N = number of phases, i.e., distinct subsystems of uniform chemical composition and physical properties; and C = the number of components, i.e., the number of independent chemical constituents meaning those constituents whose concentration can be varied independently in the different phases. In a liquid/vapor system P = 2 and C = 1, and therefore F = 1, implying only one intensive variable is needed to specify the state of the system. Therefore, temperature and pressure cannot be fixed independently. For the liquid water/water vapor system, this means physically that at a given temperature between the triple point and critical temperature, water vapor will evaporate or condense to achieve the equilibrium saturation vapor pressure as would be evidenced in a complete Amagat–Andrews diagram for water (2,3). The earth’s atmosphere and oceans can be considered as a vast closed two-phase liquid water/moist air system. Consequently, for most practical engineering and meteorological applications, one is interested in the heat of vaporization of the liquid water/moist air system rather than a pure liquid water/water vapor system. Fortunately, the presence of the other gases (collectively called dry air) in the liquid water/moist air system has negligible effect on the saturation vapor pressure. The reason is that the dry air component in the liquid water/moist air system remains unchanged and is always in the gaseous state

during phase transition at temperatures and pressures of practical interest. Therefore, it can be considered as a closed subsystem as opposed to the open liquid water and water vapor subsystems. Consequently, results obtained from an analysis of the thermodynamics of the pure system are applicable to the natural liquid water/moist air system. Energy conservation required under the first law of thermodynamics implies that heat (Q) exchanged reversibly with the surroundings between equilibrium states of any closed two-phase PVT system is consumed by any internal energy change (
U) of the liquid and vapor phases associated with the mass change from one phase to the other, and any mechanical work (±P
V) realized as the volume of the system increases (positive work) or decreases (negative work). Stated mathematically, Q =
U + P
V, or in a differential form, δQ = dU + pdV. Here, P is the saturation vapor pressure (Pvap in Fig. 1). As entropy (S) is defined as Q/T, then δQ = TdS. The first law can therefore be restated in terms of exact differentials as TdS = dU + PdV. Dividing by dV at constant T and rearranging gives dU/dV = T(dS/dV) − P. Using the Maxwell relation (∂S/∂V)T = (∂P/∂T)V (1), dS/dV can be replaced (for fixed T) by dP/dT. The equation becomes dU/dV = T(dP/dT) − P. At a given pressure and temperature, the internal energy of the system (U in Joules) can be partitioned as mw uw + mvap uvap , where mw , mvap and uw , uvap represent the masses and the specific internal energies (internal energy per unit mass in J kg−1 ) of the water and water vapor in the system. Similarly, the volume (V in m3 ) of the system can be partitioned as mw vw + mvap vvap , where vw , vvap represent the specific volume (volume per unit mass in J kg−1 ) of the water and water vapor in the system. If, as illustrated in Fig. 1, the system internal energy changes by
U from U to U +
U as a result of Lv Joules of heat absorption to convert unit mass of water to water vapor, then U +
U = (mw − 1)uw + (mw + 1)uvap , and therefore
U = (uw − uvap ). Similar reasoning shows that, if the volume changes from V to V +
V in the process, then
V = (vvap − vw ). The mechanical work because of volume change is P
V, where P (the saturation vapor pressure) is a constant at a fixed temperature. Therefore, the heat absorbed (or released) by the system for isobaric phase transition of unit mass in the liquid water/water vapor system (Lv by definition) =
U + P
V. Dividing by
V gives
U/
V = (Lv /
V) − P. Substituting
V = (vvap − vw ) gives
U/
V = [Lv /(vvap − vw )] − P, or in a differential form, dU/dV = [Lv /(vvap − vw )] − P. [It should be noted that because enthalpy (H) is defined as H = U + PV, then
U + P
V =
H, and therefore Lv is the same as the specific enthalpy change (
h =
H per unit mass) for phase transition of unit mass in the liquid water/water vapor system.] Combining the results for dU/dV from the two previous paragraphs gives T(dP/dT) − P = [Lv /(vvap − vw )] − P, and therefore T(dP/dT) = Lv /(vvap − vw ), which can be rearranged to obtain the general forms of the Clapeyron (Emile Clapeyron, 1799–1864) equation dP/dT = Lv /[T(vvap − vw )] =
h/[T(vvap − vw )] or Lv = [T(vvap − vw )]dP/dT.

HYDROLOGIC HISTORY, PROBLEMS, AND PERSPECTIVES

The Clapeyron equation can be used to obtain Lv at a given temperature T for any liquid provided one can obtain values of (vvap − vw ) and an accurate representation of dP/dT. Values of (vvap − vw ) can be obtained from tabulated measurements (3). Alternatively, because vvap vw at the low pressures, (vvap − vw ) can be taken as equal to vvap . Assuming further that at low pressures water vapor behavior closely approximates that of an ideal gas, then vvap = RT/P, where R is the specific gas constant for water = 8.314/0.018 = 461.9 J kg−1 ◦ K−1 . The Clapeyron equation becomes Lv = (RT 2 /P)dP/dT, and this form is referred to as the Clausius–Clapeyron equation (Rudolph Clausius, 1822–1888). Unfortunately, no single function has been shown to adequately represent vapor pressure data for various liquid/vapor systems over wide ranges of T. For the liquid water/water vapor system, values of dP/dT for a given value of T can be obtained by finite differencing of tabulated values. As an example, consider using the above equation to estimate Lv for water at human body temperature of 37 ◦ C. Tabulated values are vw = 1.007 cm3 g−1 = 0.01007 m3 kg−1 , vvap = 22,760 L kg−1 , = 22.760 m3 kg−1 , P = 5.940 kPa at 36 ◦ C and 6.624 kPa at 38 ◦ C, which gives (vvap − vw ) = 22.760 − 0.01007 = 22.75 m3 kg−1 . By finite differencing, dP/dT ≈
P/
T = (6.624 − ◦ 5.940)/(38 − 36) = 0.342 kPa ◦ C−1 = 0.342 kPa K−1 = ◦ −1 ◦ (a temperature difference of 1 C is the 342 Pa K same as a difference of 1◦ K). At T = 37 + 273.16 = ◦ 310.16◦ K, Lv = 310.16◦ K (22.75 m3 kg−1 ) ×342 Pa K −1 = −1 2399 kJ kg . The actual value (tabulated as
h) is 2414 kJ kg−1 , an error of 100 m high and combined waterfalls totaling a height of 300 m (19). The native shrimp, snails, and prawns (Table 1) also have the ability to climb waterfalls (20). Postlarval migration has been found to be directly related to stream discharge (22,23). OTHER ENDEMIC STREAM ANIMALS The native stream organisms have closely related marine relatives, and it is evident that the freshwater species

Amphidromy (Fish, shrimp, snails, prawns)

1. Adults live and breed in the streams 5. Some species use a ventral sucker to climb waterfalls to reach quality breeding habitat

4. Embryos develop into post-larvae in the ocean and begin to migrate back up into the stream mouths

2. Eggs deposited on stream substrate

3. Embroys hatch from eggs and are carried by stream current to the ocean for Growth and development

Figure 2. A schematic depicting the amphidromous life cycle of the native fish, snails, shrimp, and prawns found in Hawaiian streams. The life cycle requires postlarval development in the ocean and a migration back into the streams that is not immediately for breeding.

804

A HISTORY OF HAWAIIAN FRESHWATER RESOURCES

Table 1. The Freshwater Animals of Hawaiian Streams Including the Common Name, Scientific Name, Hawaiian Name, and Geographic Range Taxa Type Fish

Snails

Sponge Crustaceans

Insects

Common Name

Scientific Name

general term for freshwater fishes freshwater amphidromous gobies

Lentipes concolor

freshwater amphidromous eleotrid euryhaline-Hawaiian flag-tail fish euryhaline-striped or gray mullet freshwater amphidromous snail

Sicyopterus stimpsoni Awaous guamensis Stenogobius hawaiiensis Eleotris sandwicensis Kuhlia sandvicensis Mugil cephalus Neritina granosa

estuarine amphidromous snail

Neritina vespertina

brackish/marine neritid snail lymnaeid snails freshwater sponge general term for freshwater shrimp freshwater, mountain srhimp

Theodoxus cariosus Erinna newcombi Heteromyenia baileyi

freshwater prawn anchialine pond shrimp adult dragonfly adult damselfly immature dragonfly or damselfly immature dragonfly or damselfly immature dragonfly or damselfly immature dragonfly or damselfly many other endemic insects

Macrobrachium grandimanus Halocaridina rubra Anas spp. Megalagrion spp. Megalagrion & Anax spp. Megalagrion & Anax spp. Megalagrion & Anax spp. Megalagrion & Anax spp. various species

Atyoida bisulcata

Hawaiian Name ‘o’opu ‘o’opu ’alamo’o ‘o’opu hi’u kole ‘o’opu hi‘u’ula ‘o’opu nu’ukole ‘o’opu nopili ‘o’opu nakea ‘o’opu naniha ‘o’opu ’akupa aholehole ‘ama’ama hihiwai wi hapawai hapakai pipiwai ∗ ∗

’opae ’opaekala’ole ’opae kuahiwi ’opae kolo ’opae ’oeha’a ’opae ’ula pinao pinao ’ula lohelohe lohaloha pua’alohehole ’olopelope ∗

Range endemic

endemic indigenous endemic endemic endemic worldwide endemic endemic endemic endemic indigenous endemic

endemic endemic endemic endemic endemic endemic endemic endemic endemic

*Indicates that a Hawaiian name is not available.

evolved from marine habitats (Table 1) (10,16,24,25). Some examples of this can be found in stream insect communities consisting of midges, Telmatogeton (Chironomidae); beach flies, Procanace (Canacidae); and shore flies, Scatella (Ephydridae), which are thought to have radiated into streams from ancestral intertidal habitats (26–28). The Hawaiian Telmatogeton complex is unique with all five endemic species restricted to freshwater, the only representatives of an exclusively marine intertidal subfamily worldwide (26–29). Another important insect group is the endemic damselflies of the Megalagrion complex. This genus has shown rapid speciation in concert with specific freshwater and terrestrial habitats (30–32). Contrary to many other aquatic insects of Hawaii, the endemic damselflies are thought to have evolved from one freshwater ancestor to Hawaii (31,32). As a result of recent extinctions, numerous research initiatives have been carried out to understand the evolution, biology, and conservation of this unique group of insects (31,32). Other freshwater organisms are reported in Table 1.

fish, snails, shrimp, and some insects) and/or isolated populations that have undergone rapid speciation (e.g., the damselflies). For millennia, these systems connected the mountains to the ocean along what is called in Hawaiian the mauka—makai continuum. The physical connection was the flowing streams supporting the biological connections of the amphidromous species. However, many streams were heavily diverted in the late 1800s for irrigating an expanding sugar cane industry. Stream flow removal and riparian degradation has had the following effects: (a) destroying and eliminating breeding habitat for all stream animals, (b) preventing amphidromous egg and larval drift to the ocean, (c) obstructing postlarval recruitment back into the streams, and (d) facilitating invasive species establishment (9,22,33–35). Water is a critical and limited resource, not only to humans but also to the native stream organisms. Balancing these will take compromise and scientifically based freshwater resource management.

SURFACE WATER REMOVAL

Historic Management

The streams of Hawaii are habitat to relatively recently evolved communities with close marine ancestors (e.g.,

The ahupua’a system was the first freshwater management system in Hawaii. Developed by the ali’i (chiefs) of

FRESHWATER RESOURCE USE AND MANAGEMENT

A HISTORY OF HAWAIIAN FRESHWATER RESOURCES

the first Hawaiians 1500–1600 years ago, it maintained adequate freshwater resources for the entire population of each island. The ahupua’a was what now is considered a watershed and extended from the headwater springs into the ocean. Along this mauka—makai continuum, the land along the stream was divided into pie-like slices called ‘ili kuponos, that were designated to maka’ainana (commoners) and overseen by a chief-appointed konohiki. The commoners did not own the land or water, for they only maintained them for the chiefs. Each konohiki was appointed to a single ahupua’a, and each ‘ili kupono was divided into kalo lo’i (taro patches). Stream water was diverted by pani wai (diversions) and carried through small ‘auwai (ditches) to the lo’i. The lo’i were connected in a stair-step manner by additional ditches maintained by the responsible commoners. If the ditches were not maintained upstream, all downstream lo’i would be affected. Contrary to contemporary freshwater management, the stream water was always returned to the stream before it entered the ocean, and was never carried out of the watershed. Therefore, the water continually connected the highest mountain reaches to the lowland settlements near the sea, maintaining the mauka—makai continuum. The early Hawaiians understood the connectivity of the land, freshwater, and sea. The ahupua’a system maintained adequate freshwater resources for human use while balancing ecological function. Hawaiians also understood the power and importance of water to their culture. For example, the Hawaiian word for water, wai, is the root for wealth (waiwai) and law (kanawai) (36). Over the next 60 years, native Hawaiians would find just how important water could be to foreigners, or haoles—those without breathe, or mana (spirit). The sugar cane industry completely changed freshwater resource management: water would be removed from the ahupua’a, along with much of the native Hawaiian culture. Contemporary Management The influence of western missionaries and merchants shifted the Hawaiian perception of water from a shared resource to a commodity that provided maximum use and greatest reward to plantation owners (37). After the arrival of Captain James Cook in 1778, freshwater management changed little until the The Great Mahele of 1848, enacted by King Kamehameha III under heavy influence by the decedents of original missionaries, the new owners of the sugar cane industry (and pineapple later). The Great Mahele was the first act to privatize land and water in Hawaii. For nearly 25 years the kings of Hawaii attempted to negotiate reciprocity treaties with the United States In 1876, King Kalakaua finally established a reciprocity treaty assuring duty-free exchange between Hawaii and the United States, giving sugar companies a competitive edge in the world market and giving Pearl Harbor to the United States, which was the same year of the first water licenses, the creation of the first private water company, and the construction of the diversionditch systems, which relocated millions of gallons of water from the windward watersheds to leeward sugar cane fields. According to Wilcox (36), one pound of sugar takes approximately 4000 pounds, or 500 gallons, of water.

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The growth of sugar cane and pineapple took over and ‘‘transformed Hawaii from a traditional, insular, agrarian, and debt-ridden society into a multicultural, cosmopolitan, and prosperous one’’ (36). During this time, the number of sugar plantations rose from 5 in 1857 to 90 in 1884 (36). From the late 1870s to the mid1900s, the Hawaiian sugar cane industry continued to grow, in part because of political access to surface and groundwater resources. By the early 1900s, almost every stream on the windward sides of each island was at least partially diverted, and in 1920, the sugar cane industry was diverting >800 mgd and pumping an additional 400 mgd from aquifers (36). Almost 20 years later, the entire city of Boston was only consuming 80 mdg (36). The privately developed surface water of Hawaii was quite different from publicly controlled surface water development of the western United States, which put control of water into the hands of western businessmen, those who would eventually contribute to the overthrow of the last Hawaiian Monarchy. (Several books are available that describe the sequence of events that led to the overthrow (38–40).) With the developing agricultural industry, the population and ethnic diversity expanded as well. A larger labor force was needed to construct the ditches and diversions and work the agricultural fields. For cheap labor, the agricultural companies looked to Japan, China, and other Asian nations. This immigration resulted in several ethnic populations living and working on plantation property, creating mixed nonHawaiian communities that are the roots of the ethnic diversity found in Hawaii today. As the population and successful industries increased, the popularity of the islands grew in the mid-1900s, whereas the sugar cane industry met fierce competition from other nations, and has resulted in the slow demise of the former economic strength. With the buildup and maintained military presence of Pearl Harber from World War II, the economic focus of Hawaii saw a change from agriculture to military establishment to tourism that is now the economic base of the state. Along the southwestern coast of each island, numerous hotels, shopping malls, golf courses, and restaurants have been developed because most people prefer to vacation on the sunny, dry side of the island. However, similar to the sugar cane scenario, water is not readily available on the leeward side. Therefore, water remains diverted from streams, or pumped from dwindling freshwater aquifers, in order to accommodate tourists, water the green lawns, and fill hotel swimming pools and spas. A BRIEF INTRODUCTION TO HAWAIIAN WATER LAW Water Rights The expansion of the sugar industry resulted in many water disputes between sugar companies, various landowners, and native Hawaiians. These disputes helped recognize the following water rights: (a) appurtenant, (b) riparian, (c) prescriptive, and (d) surplus (41). Appurtenant rights developed from ancient rights and were officially declared in the earliest Hawaiian water case,

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A HISTORY OF HAWAIIAN FRESHWATER RESOURCES

Peck vs. Baily (1867). This case determined that if land was entitled by a landowner to cultivate taro, than some stream water was also. Riparian rights permit water use to those who own land next to a stream; however, use must be reasonable and not harmful to other landowners (42). In riparian law, the focus is on maintaining stream integrity while allowing landowner priority uses (e.g., domestic drinking and washing) over nonpriority uses (e.g., irrigation, mining) (41). Both appurtenant and riparian water rights consider water as a common good. Prescriptive and surplus water rights address private ownership of water sources. Prescriptive water rights are granted if a party has proven using water ‘‘belonging’’ to another party for an extended and continuous period of time (e.g., 20 years) (37). Surplus water is defined as the amount of water in a stream not covered by any prior water right (37). In court, cases of surplus water were heard independently, which precluded the establishment of defined standards for future disputes. For example, in the case of Hawaiian Commercial & Sugar Co. v. Wailuku Sugar Co. (1904), the court ruled that surplus water traveling through an ahupua’a belonged to the private land owner, but in Carter v. Territory (1917), the court concluded that surplus water was to be used reasonably according to riparian principles, thus shared among landowners. The inconsistent rulings and absence of an established in-stream flow standard left the status of surplus waters questionable until the state code in 1987. Summary of Case Law From the 1850s to the 1980s, the water rights of Hawaii were evolving according to case law, yet no standard criteria for the allocation, transport, and quantity of freshwater was resolved. There were several political, economical, and social reasons for no established criteria. First, the rise of the sugar cane industry boosted the economy, and with it came political power to the foreign owners. Second, during this period, the Hawaiian Islands shifted from a monarchy to a republic to a U.S. Territory, and finally became a U.S. state, which created an atmosphere of economic and political change that left many native Hawaiians in a state of social and political confusion (36), where they did not resist changes in water law, as it was not in their culture to protest actions of the King. As a result of this, there was difficulty in establishing a cause-effect relationship, and many of the villages most affected were too small to fight the wealthy plantation owners (36,37). In 1978, the Hawaii State Constitution mandated that a water code and commission be established to manage water resources. And in the late 1980s, a Hawaii State Water Code and the Commission on Water Resource Management was passed by the Hawaii State Legislature (37). The State Water Code became a regulatory mechanism for state agencies and counties and required the Commission to monitor and guide water allocation by establishing minimum in-stream flow standards that were to enhance, protect, and reestablish beneficial in-stream uses. Current trends have been developing during the 1990s that are testing the

utility of the Hawaii State Water Code. The first of several cases, and a landmark case for future petitions, was the Waiahole Combined Contested Case Hearing. In this case, the Hawaii Supreme Court ruled for the establishment of minimum in-stream flow standards and than any additional flow secondarily allocated for other uses. In-stream flow standards are currently being investigated. The Waiahole Ditch Case was the first test of the State Water Code, yet many similar cases are being petitioned at the time of this writing. The diminishing sugar industry is opening a new chapter in Hawaiian case law, a chapter that must not only consider economics but also ‘‘traditional and customary Hawaiian rights, protection and procreation of fish and wildlife, ecological balance, scenic beauty, public recreation, beneficial in-stream uses, and public interest’’ (36).

SUMMARY AND SYNTHESIS The history of Hawaiian water resource issues is complex. The system of surface water management went through a dramatic change with the explosion of agriculture and the associated political power of missionary descendents; however, this explosion was inherently dependent on privately developed surface waters—a feedback proliferation of each other. The surface water development from the late 1800s through the mid-1900s drained watersheds of both water and native Hawaiian culture. The efficient removal of water high in the watersheds left a trickle downstream for native taro farmers. With the construction of massive diversion-ditch systems, native Hawaiians emigrated from the ahupua’a to build ditches and work sugar cane fields. At the same time, thousands of immigrants from China, Japan, and the Philippines melted into the sugar cane plantation farms, changing the demographics of Hawaii. The push by sugar businessmen to get an extended reciprocity treaty secured rights of Pearl Harbor to the United States; it also led to the coup of the Hawaiian Monarchy. At the same time, streams were being impacted by water removal and rapid riparian destruction, negatively affecting the native biological communities of the mauka–makai continuum. The degradation of stream habitats in Hawaii has become an increasingly important issue to many native Hawaiians, scientists, private organizations, and individuals. Water resources have been, and will continue to be, a highly debated political issue. Water is necessary for agricultural, industrial, and municipal uses throughout Hawaii; however, in order to maintain the unique biodiversity of the streams, a compromise must be made between continued development and conservation. Thus, the future of the Hawaii’s freshwater ecosystems and economic security is dependent on wise freshwater management and allocation, which should not be made in a scientific vacuum. Objective and sustainable answers can only be achieved with a solid scientific base, one free from political bias that has been the history of Hawaiian freshwater resources.

A HISTORY OF HAWAIIAN FRESHWATER RESOURCES

BIBLIOGRAPHY 1. Culliney, J.L. (1988). Islands in a Far Sea: Nature and Man in Hawaii. University of Hawaii Press, Honolulu, HI. 2. Hazlett, R.W. and Hyndman, D.W. (1996). Roadside Geology of Hawaii. Mountain Press, Missoula, MT. 3. Stearns, H.T. (1985). Geology of the State of Hawaii, 2nd Edn. Pacific books, Palo Alto, CA.

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shrimp postlarvae in two Maui streams. Micronesica 34(2): 243–248. 22. Benbow, M.E., Burky, A.J. and Way, C.M. (2004). The use of two modified Breder traps to quantitatively study amphidromous upstream migration. Hydrobiologia 527: 139–151. 23. Burky, A.J., Benbow, M.E., and Way, C.M. (2004). Two modified Breder traps for quantitative studies of postlarval amphidromy, Hydrobiologia.

4. Juvik, S.P. and Juvik, J.O. (1998). Atlas of Hawaii, 3rd Edn. University of Hawaii Press, Honolulu, HI.

24. Kinzie, R.A.I. (1997). Evolution and life history patterns in freshwater gobies. Micronesica 30(1): 27–40.

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25. McDowall, R.M. (2003). Hawaiian biogeography and the islands’ freshwater fish fauna. J. Biogeogr. 30(5): 703–710.

6. Carlquist, S. (1980). Hawaii: A Natural History. Pacific Tropical Botanical Gardens, Honolulu, HI. 7. Mueller-Dombois, D., Bridges, K.W., and Carson, H.L. (1981). Island Ecosystems: Biological Organization in Selected Hawaiian Communities. Hutchinson Ross, Stroudsburg, PA. 8. Kay, E.A. (Ed.). (1994). A Natural History of the Hawaiian Islands, Selected Readings II. University of Hawaii Press, Honolulu, HI. 9. Way, C.M., Burky, A.J., Harding, J.M., Hau, S., and Puleloa, W.K.L.C. (1998). Reproductive biology of the endemic goby, Lentipes concolor, from Makamaka’ole Stream, Maui and Waikolu Stream, Moloka’i. Environ. Biol. Fish. 51: 53–65. 10. Benbow, M.E. (1999). Natural History and Bioenergetics of an Endemic Hawaiian Chironomid: Fluctuating Stability in a Stochastic Environment. Ph.D. Dissertation. Department of Biology, University of Dayton, Dayton, OH. 11. Benbow, M.E., Burky, A.J., and Way, C.M. (1997). Larval habitat preference of the endemic Hawaiian midge, Telmatogeton torrenticola Terry (Telmatogetoninae). Hydrobiologia 346: 129–136. 12. McDowall, R.M. (1996). Is there such a thing as amphidromy? Micronesica 30(1): 3–14. 13. McDowall, R.M. (1997). The evolution of diadromy in fishes (revisited) and its place in phylogenetic analysis. Rev. Fish Biol. Fish 7(4): 443–462. 14. Radtke, R.L. and Kinzie, R.A. (1996). Evidence of a marine larval stage in endemic Hawaiian stream gobies from isolated high-elevation locations. T. Am. Fish Soc. 125: 613–621. 15. Radtke, R.L., Kinzie, R.A., and Folsom, S.D. (1988). Age at recruitment of Hawaiian freshwater gobies. Environ. Biol. Fish 23(3): 205–213. 16. Benbow, M.E., Burky, A.J., and Way, C.M. (2004). Morphological characteristics and species separation of Hawaiian postlarval amphidromous fishes. Micronesica 37(1): 127–143.

26. Hardy, D.E. and Delfinado, M.D. (1980). Diptera: Cyclorrhapha III, Series Schizophora, Section Acalypterae, Exclusive of Family Drosophilidae. Vol. 13. The University Press of Hawaii, Honolulu, HI. 27. Newman, L.J. (1988). Evolutionary relationships of the Hawaiian and North American Telmatogeton (Insecta; Diptera: Chironomidae). Pacific. Sci. 42(1–2): 56–64. 28. Newman, L.J. (1977). Chromosomal evolution of the Hawaiian Telmatogeton (Chironomidae, Diptera). Chromosoma 64: 349–369. 29. Wirth, W.W. (1947). A review of the genus Telmatogeton Schiner, with descriptions of three new Hawaiian species (Diptera: Tendipedidae). Proceedings of the Hawaiian Entomological Society 13: 143–191. 30. Jordan, S., Simon, C., and Polhemus, D.A. (2003). Molecular systematics and adaptive radiation of Hawaii’s endemic damselfly genus Megalagrion (Odonata: Coenagrionidae). Syst. Biol. 52(1): 89–109. 31. Polhemus, D.A. (1997). Phylogenetic analysis of the Hawaiian damselfly genus Megalagrion (Odonata: Coenagrionidae): implications for biogeography, ecology, and conservation biology. Pacific Science 51(4): 395–412. 32. Polhemus, D.A. and Asquith, A. (1996). Hawaiian Damselflies: A Field Identification Guide. Bishop Museum Press, Honolulu, HI. 33. Englund, R.A. and Filbert, R.B. (1999). Flow restoration and persistence of introduced species in Waikele Stream, O’ahu. Micronesica 32(1): 143–154. 34. Benbow, M.E., Burky, A.J., and Way, C.M. (2003). Life cycle of a torrenticolous Hawaiian chironomid (Telmatogeton torrenticola): stream flow and microhabitat effects. Ann. Limnol. Int. J. Lim. 39(2): 103–114. 35. McIntosh, M.D., Benbow, M.E., and Burky, A.J. (2002). Effects of stream diversion on riffle macroinvertebrate communities in a Maui, Hawaii, stream. River Res. Applic. 18: 569–581. 36. Wilcox, C. (1996). Sugar Water: Hawaii’s Plantation Ditches. University of Hawaii Press, Honolulu, HI.

17. Lindstrom, D.P. (1998). Reproduction, Early Development and Larval Transport Dynamics of Amphidromous Hawaiian Gobioids. Ph.D. Dissertation, University of Hawaii, Honolulu, HI.

37. Mackenzie, M.K. (1991). Native Hawaiian Rights Handbook. Native Hawaiian Legal Corporation, Honolulu, HI.

18. McDowall, R.M. (1992). Diadromy: origins and definitions of terminology. Copeia 1: 248–251.

38. Liliuokalani. (1990). Hawaii’s Story by Hawaii’s Queen. Mutual Publishing, Honolulu, HI.

19. Kinzie, R.A., III (1990). Species Profiles: Life Histories and Environmental Requirements of Coastal Vertebrates and Invertebrates Pacific Ocean Region. Amphidromous Macrofauna of Hawaiian Island Streams. US Army Engineer Waterways Experiment Station, Vicksburg, MS.

39. Daws, G. (1968). Shoal of Time: A History of the Hawaiian Islands. University of Hawaii Press, Honolulu, HI.

20. Kinzie, R.A., III and Ford, J.I. (1982). Population Biology in Small Hawaiian Streams. Water Resources Research Center, University of Hawaii at Manoa, Honolulu, HI, p. 147. 21. Benbow, M.E., Orzetti, L.L., McIntosh, M.D., and Burky, A.J. (2002). A note on cascade climbing of migrating goby and

40. Cooper, G. and Daws, G. (1990). Land and Power in Hawaii. University of Hawaii Press, Honolulu, HI. 41. MacKenzie, M.K. (1991). Water rights, In: Native Hawaiian Rights Handbook. M.K. MacKenzie (Ed.). Native Hawaiian Legal Corporation, Honolulu, HI, pp. 149–172. 42. Schoenbaum, T.J. and Rosenburg, R.H. (1996). Environmental Policy Law: Problems, Cases and Readings. University Casebook Series, Westbury, NY.

CUMULATIVE INDEX NOTE: Page numbers followed by f refer to figures, page numbers followed by t refer to tables. All volume numbers appearing in italics refer to volume subject material as stated in footnote. A2/O process, 1:790 Abandoned channel pools, 3:69 Abandoned mines, alkaline amendment to, 5:3 ABA plant hormone, 3:718 Abiotic redox reactions, 5:413 Abiotic solute transport, 5:527–528 Abiotic transformation, of chlorinated aliphatic compounds, 1:691–692 Abrasion number, of carbon, 1:97 Absolute humidity, 4:269–270 Absolute ownership doctrine, 4:630–631 Absorbed solar radiation, 3:375–376 Absorption, of organochlorine pesticides, 3:643–644 Absorption systems, for odor removal, 1:914 Acanthamoeba, 1:278 Acaricide Dicofol, 3:645 Accelerator mass spectrometry (AMS) technique, 4:418 Acceptable daily intake (ADI), 3:637 Accumulation, of organochlorine pesticides, 3:643–644. See also Bioaccumulation Acequia, defined, 2:541–542 Acetic acid, 2:295 Acetogenesis, in landfills, 1:696 Acid, carbonate scale control with, 4:415–416 Acid deposition, 4:377 control of, 4:380 effects of, 4:378 Acid Deposition Control Program (Title IV), 4:379, 380 Acidic brines, 3:10 Acidic crater lakes, 3:9 Acidic mining lakes, 3:10 Acidic pit lakes, 3:10, 11 Acidic rivers, 3:10 Acidic tailings, from geological deposits, 3:9–10 Acidification. See also Acidization atmospheric, 3:8–9 biological effects of, 3:9 causes of, 3:5 chronic, 3:1–4

episodic, 3:5–7 of freshwater resources, 3:7–13 geogenic, 3:9–10 in Indian lakes, 3:451 industrial, 3:9 soil, 5:377 Acidified soft waters, 3:8 Acidifying substances, life cycle emissions of, 3:548 Acidity negative and positive, 2:424 relationship to pH, 3:8 soil, 3:707 Acidization, 5:28. See also Acidification Acid mine drainage (AMD), 1:609–610; 2:1–2; 3:1, 2, 10–11 active and passive treatment of, 3:11 alkaline amendment to, 5:2 chemical treatment of, 5:3–5 control of, 5:2–3 costs of treating, 5:4–5 geochemistry of, 3:13–15 iron-oxidizing bacteria in, 2:150–151 overburden analyses in, 5:1–2 passive treatment of, 2:423–426; 5:5–7 remediation of, 3:11 in the United States, 5:1–9 Acid mine wastewater, 1:113 Acid-neutralizing capacity (ANC), 3:1, 3 Acidogenesis, separation from methanogenesis, 1:909 Acidophilic iron bacteria, 2:149 Acid oxidation, 2:85 Acid phosphatase (ACP) activity, 2:415 Acid production rate, 3:14–15 Acid rain, 3:1, 8–9, 292–293; 4:184 assessment of, 4:380–381 countermeasures against, 3:9 current conditions related to, 4:380 defined, 4:377–378 effects of, 3:224–225 groundwater acidification due to, 3:10

regulation of, 4:379 social response to, 4:379–378 sources and effects of, 4:378–379 Acids defined, 2:542 of geogenic origin, 3:7 strength of, 2:294 Acid treatment, for scale control, 1:548 Acinetobacter, 2:241 A climates, 4:256–257 Acoustical monitoring, underwater, 4:91–92 Acoustic televiewer, 5:154 Acre-foot, defined, 2:542 Action level, 1:479 Activated alumina (AA), 1:460 for arsenate removal, 5:20–21 Activated alumina sorption, for arsenic removal, 1:638 Activated carbon(s), 2:79–86; 4:507. See also Activated carbon adsorption; Powdered activated carbon (PAC) acid surface functional groups on, 2:81 adsorption capacity of, 4:381–384 applications of, 1:101–102 background of, 2:80 common uses for, 1:105–106 competitive adsorption on, 1:107–121 competitive sorption of inorganics on, 1:110–115 domestic use of, 1:105–106 gas-phase applications of, 1:104–105 methods for developing, 1:93–98 organic micropollutant and metal ion removal by, 4:506–511 physical and chemical properties of, 2:81 precursors of, 2:80 preparation and properties of, 1:94t, 2:82–83 sorption of trace metals onto, 2:83–85 steps in producing, 1:95f surface chemistry of, 1:98–99

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712

CUMULATIVE INDEX

Activated carbon(s), (continued) surface functional groups on, 2:82 types of, 1:92–93 Activated carbon (AC) adsorption, 1:817 domestic sewage and, 1:834 of landfill leachates, 1:707 Activated carbon posttreatment, 5:25–26, 327 Activated carbon samplers, 5:109 Activated carbon technology, 1:351–352 Activated carbon treatment, of radioactive waste, 1:804 Activated sludge, 1:566–567, 568, 861, 862–863. See also Activated sludge process(es) bacteria in, 1:668t floc from, 1:844 Activated Sludge Models (ASMs), 1:733, 739–740. See also International Water Association (IWA) models variables in, 1:740t Activated sludge plants, microbial foaming and bulking in, 1:844–848 Activated sludge process(es), 1:565, 668, 815 biological phosphorus removal in, 1:788–791 denitrification in, 1:667–669 domestic sewage and, 1:832–833 microbial foaming in, 1:728–730 nitrification in, 1:751–755 nutrient deficiencies in, 1:729–730 Activated sludge treatment, POP behavior in, 1:767–769 Activation, 2:80–81. See also Activated carbon entries; Activated sludge entries of carbon, 1:94–96 Active biomonitoring (ABM), 2:33–37 advantages and disadvantages of, 2:33–34 system for, 2:28 Active direct solar water heaters, 1:65 Active disease reporting, 1:185 Active immobilization, of metals, 5:282–283 Active indirect solar water heaters, 1:65 Active isotopes, as groundwater tracers, 5:503–504

Active microwaves, 4:324 Active real-time control, modeling, 3:340–341 Active rock glaciers, 3:174, 175 Active sound detection, 4:570–571 Active storage, 3:259 Acute sediment toxicity tests, 2:351, 385t; 3:51–52 Acute toxicity, categories of, 2:415 Adaptive management, 3:128 Adaptive modified sequential method, of DNAPL migration modeling, 5:669–670 Additives, odor-reducing, 1:912–913 Adenosine triphosphate (ATP), 1:399; 2:42 detection of, 1:85 Adenovirus, 1:279 Adenylate kinase (AK) detection, 1:85 ‘‘Adequate protection by natural means,’’ 1:293 ‘‘Adequate protection by treatment,’’ 1:293 Adiabatic cooling, 4:366–371 Adiabatic ideal gas process, 4:368 Adsorbent dose (Ws ), 3:299–300 Adsorbents characterization of, 4:508–511 for inorganic ion removal, 4:494–495 micropores and mesopores in, 2:79 Adsorbent surface chemistry, 4:491 Adsorption, 1:811; 2:374; 5:184, 186. See also Inorganic adsorption for arsenic removal, 1:638–639 dynamics of, 3:302 effect of pH on, 3:299 of hydrocarbons, 1:577–579 in situ metal/organic, 5:609–610 kinetic formulations for, 5:415 in mine effluent remediation, 1:611–612 models of, 3:300–301 for odor abatement, 1:762 operating variables in, 3:298–300 of organic compounds, 4:384–388 thermodynamics and, 3:301–303 water–rock interaction and, 5:566–568 Adsorption capacity correlation for, 4:382–384 graphs of, 4:382, 383f Adsorption clarifier package plants, 1:516–517

Adsorption equilibrium, of carbon, 1:99 Adsorption isotherms, 3:299; 4:384–385 types of, 1:99–101 Adsorption models, multicomponent, 1:107–110 Adsorption systems, for odor removal, 1:914 Adsorptive colloidal processes, 5:350 Adsorptive columns, sizing, 2:363 Adsorptive filtration, for arsenic removal, 1:639 Advanced impellers, 1:79f Advanced Microwave Scanning Radiometer (AMSR-E), 2:589; 4:194, 216 Advanced Microwave Sounding Unit (AMSU, AMSU-A), 4:216, 351 Advanced nucleic acid analyzer (ANNA), 2:339 Advanced oxidation processes (AOP), 2:318 for vinyl chloride, 5:639 Advanced oxidation technology, 1:579 Advanced wastewater treatment techniques, 1:816–817, 871–876. See also Wastewater entries advanced oxidation processes (AOP), 1:871–872 complexation/flocculation, 1:872 conducting polymers, 1:872 ionizing irradiation, 1:873 membrane/sonication/wet oxidation, 1:873–874 sorption by zeolites, 1:874 supercritical water oxidation, 1:874–875 ultrasonic irradiation, 1:875 Advection, 5:273–274, 278 organic vapor transport via, 5:544–545 transport by, 5:516 Advection fog, 4:232 variables of, 4:236 Advection phenomena, 3:78 Advective-dispersion model, 3:332 Adverse effects assessments, 2:516–517 Adverse social impacts, of water transfers, 4:687 Advisors, international, 1:719 Aeolian valleys, 3:66 Aerated lagoons, 1:704 Aerated static piles, 1:648

Water Encyclopedia: Domestic, Municipal, and Industrial Water Supply and Waste Disposal (Vol. 1) Water Encyclopedia: Water Quality and Resource Development (Vol. 2) Water Encyclopedia: Surface and Agricultural Water (Vol. 3) Water Encyclopedia: Oceanography; Meteorology; Physics and Chemistry; Water Law; and Water History, Art, and Culture (Vol. 4) Water Encyclopedia: Ground Water (Vol. 5)

CUMULATIVE INDEX

Aeration, 1:380, 460; 2:374 in domestic sewage treatment, 1:833 extended, 1:815 groundwater remediation by, 5:426–432 methods of, 1:51–52 pretreatment, 1:323 tapered, 1:815 technology for, 1:352–353; 4:546 wastewater, 1:623–626 Aeration efficiency (AE), 1:623 Aeration systems, 1:623 submerged, 1:624–626 surface, 1:623–624 Aerial natural gamma radiation surveys, 4:338 Aerobic bacteria, 2:20; 5:581 in cooling systems, 2:241 Aerobic biodegradation, optimum, 5:44. See also Aerobic degradation; Biodegradation Aerobic bioremediation, 5:424–425 technologies, 5:40 Aerobic cometabolism, methyl tertiary-butyl ether, 5:388–389 Aerobic degradation, rate of, 5:44. See also Aerobic biodegradation Aerobic digestion of biosolids, 1:647–648 of sludge, 1:865 Aerobic in situ enhanced bioremediation, 5:423–424 Aerobic leachate treatment, 1:704, 709 Aerobic plate count (APC), in dishwater, 2:113, 114 Aerobic stabilization, of sludge, 1:857 Aerobic wastewaters odorants in, 1:911 treatment of, 1:813 Aerobic wetlands, 5:5 Aeromonas, 1:277 Aerosols, atmospheric, 4:371 Aesthetics, algae-impaired, 3:108 Africa unsafe water in, 2:631 monsoons in, 4:304–305 African foods, nitrate levels in, 1:32t Age dating, of groundwater, 4:388–390 Agency management impacts, of water transfers, 4:687 Agenda 21, 3:33, 34 Aggressive metal mobilization, 5:282

Aging impact of water on, 4:455–461 premature, 4:455–456 Agitation, in water treatment systems, 1:76–81 Agrichemical facilities, soil remediation at, 3:651–655. See also Agrochemicals Agricultural activities. See also Agricultural practices contamination from, 1:25 as a nitrate contamination source, 2:571 Agricultural area pollution mathematical models for estimating, 3:658–659 outflow of, 3:657–664 Agricultural areas, impact on groundwater quality, 5:251–252 Agricultural changes, influence on the hydrologic cycle, 4:281 Agricultural districts law, 3:597 Agricultural drainage, 5:94–95 Agricultural drainage ditches, research conducted on, 3:88–89t, 90t Agricultural droughts, 4:208 Agricultural impacts, of waterlogging, 3:741–742 Agricultural irrigation, 1:818 Agricultural land, classification and mapping of, 3:608–609 Agricultural landscape pollutants in, 3:605t water quality management in, 3:604–608 Agricultural land use planning, 3:595–598 issues in, 3:595–596 national, state, and local, 3:596–597 Agricultural Nonpoint Source Pollution Software (AGNPS), 2:325 Model 2001 (AGNPS 2001), 2:251 Agricultural practices. See also Agricultural activities algal control via, 2:3–4 improving, 2:571 Agricultural runoff, as a source of cultural eutrophication, 3:114 Agricultural soils, phosphorus status of, 3:704–705 Agricultural wastewater, constructed wetlands for, 1:896

713

Agricultural water Arab World share of, 2:474f curious uses of, 4:695–699 United States use of, 2:653 Agricultural watershed, organochlorine pesticides in vegetables grown on, 3:643–647 Agricultural water use efficiency (WUE), 3:558–560 Agriculture. See also Crop entries; Farming; Irrigated agriculture in the Arab World, 2:470–471 in China, 2:488–489 frost damage to, 4:242 groundwater role in, 2:392 of hollows, 4:695–697 irrigated, 2:489 nonpoint source pollution from, 2:186 organic, 3:644–646 raised-style, 4:697–698 relation to water security, 1:438–439 sediment from, 3:509 wastewater reuse guidelines for, 3:670 water conservation in, 2:495–496 as a water consumer, 2:489–490, 662 water reuse in, 2:635 water supply for, 2:617–618 Agrochemicals, role of, 3:643. See also Agrichemical facilities Agroforestry systems, 3:551, 568 Agronomic/ecological models, use of field capacity in, 5:126 Agronomic practices, phytoextraction optimization using, 5:372 Agronomic soil conservation methods, 3:551 AIDS, 1:162, 163, 182, 258 Air, cadmium in, 5:617. See also Aeration; Aerobic entries Air aeration systems, fine bubble diffused, 1:626–631 Airborne contaminant sources, 5:433 Air bubbling, 1:594 Air chambers, water hammer and, 1:262 ‘‘Air dry’’ soil, 5:536 Air emissions, 1:413 electric generating plant contaminants in, 1:554–555 Air entrapment effects, 5:536 Air flotation, 3:407

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714

CUMULATIVE INDEX

Air gaps, 1:155 Air-line submergence method, 5:101 Air oxidation, 2:85 Air pollution, 4:379 chemicals in, 3:224 effects of, 4:378 MtBE and, 5:319 Air quality, 1:554 Air sampling techniques, 2:307 AIRS/AMSU/HSB sounding system, 4:351, 352 Air–sea interaction, 4:1–4 Air sparging, 5:39, 428, 440–441. See also Biosparging Air sparring, activated carbon in, 1:105 Air stripping, 1:380, 576–577, 631–632, 816 of landfill leachates, 1:707 for radioactive waste, 1:803 of vinyl chloride, 5:639 Air temperature, determining, 3:563 Air to plant absorption, 3:643–644 Air–water interface, 4:452, 470 GHG fluxes at, 3:205–206 Alaska, in-stream flow protection in, 4:662. See also Glacier Bay Alaskan rain forest, 2:667 Albedo, 4:179 Alfalfa channel tests, 5:392 Algae, 2:269. See also Blue-green algae entries; Periphyton index of biotic integrity (Periphyton IBI); Toxic algae acid-sensitive, 3:4 in cooling water systems, 1:540 excessive growths of, 3:108 health effects of, 1:277 removal using ozone, 1:355 Algal bioremediation, 2:44–45 Algal blooms, 3:114; 4:108 decomposition of, 3:115 harmful, 4:55 Algal growth, 2:241–242 importance of light penetration to, 3:111 Algal nutrients, sources and control of, 3:110–113 Algal populations biomanipulation of, 2:6 chemical control of, 2:5–6 environmental control of, 2:3–5 Algal toxins, 2:387–392

Alice Water Treatment Plant (AWTP), 1:221–226 alum and lime consumption and cost estimation for, 1:222 bacterial monitoring at, 1:222–223, 225 clarifier and filter performance at, 1:222, 224 disinfection at, 1:222, 224–225 DOC and BDOC levels at, 1:225–226 flow rate measurement and control at, 1:222 performance of, 1:222, 225–226 Alicyclic hydrocarbons, degradation of, 1:692–693 Alien species, 3:134 Alignment log, 5:154 Aliphatic hydrocarbons chlorinated, 1:690–692 degradation of, 1:692–693 Alkaline amendment to abandoned mines, 5:3 to acid mine drainage, 5:2 Alkaline leach beds, in acid mine treatment, 5:7 Alkaline phosphatase (APase), 2:231 Alkaline recharge trenches, 5:2 Alkaline stabilization of biosolids, 1:649 of sludge, 1:865 Alkalinity in carbonate geochemistry, 4:409–410 defined, 2:542 effect on corrosion, 1:8 imparted by carbonaceous minerals, 3:14 insufficient, 5:2 in natural waters, 2:394 nitrification and, 1:754 in ozone half-life, 1:359 role in fish growth and production, 3:131 of soil, 3:707 of water, 1:902 Alkalinity addition, chemicals suitable for, 1:755t Alkaloid cyanobacterial toxins, structures of, 3:190f Alkene biodegradation, 1:692–693 Alkenones, 4:93 Allergies, dehydration and, 4:725 Allochthonous inputs, watershed-related, 3:207

Allogenic recharge, 5:236 Allowable exposures, 1:427 Allowable headwater (HW), 3:77 Allowable velocity, 3:77 Alluvial valleys, 3:66 Alluvium, defined, 2:542 Alpha emitters, health risks of, 1:396 Alpine climatic zone, 4:258–259 Alpine hydrochemical model (AHM), 5:298 Alternative collecting systems, 1:840 Alternative cost approach, 4:609 Alternative formulation, in a systems approach, 2:686 Alternative Maximum Contaminant Level (AMCL), 1:479 Alternative stable states theory, 3:272–274 Alternative wastewater treatment systems, 1:840–842 Altitude effect, 4:439 Alum, 1:138 Alum coprecipitation, 5:20 Alumina, activated, 5:20–21 Aluminum (Al) coagulation using, 1:636 episodic acidification and, 3:7 toxicity of, 3:131 Aluminum industry, 1:562–563 Aluminum recovery, from water treatment plant residuals, 1:140f Amargosa Desert, recharge in, 5:74–75 Amazonia region, 4:642 Ambient Groundwater Monitoring and Assessment Program (GAMA) studies, 5:62 Ambient groundwater monitoring network, 5:313–317 monitoring frequency at, 5:317 monitoring measurements and samples for, 5:316 site inventory for, 5:315 site selection for, 5:315 size of, 5:316–317 strategies and designs for, 5:314–315 types of wells for, 5:316t using data from, 5:317 Ambient water quality, optimal level of, 2:129 AMD generation, rate of, 3:13–14. See also Acid mine drainage (AMD)

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CUMULATIVE INDEX

American Farmland Trust (AFT), 3:598 American Meteorological Society, 4:329 American National Standards Institute (ANSI), 1:381 standards of, 1:198 American Rule, 4:631 American Society of Testing and Materials (ASTM), 2:459 Soil Classification Flow Chart, 3:690 American Society of Agricultural Engineers (ASAE) microirrigation standards, 3:615 American Society of Civil Engineers—Environmental Water Resources Institute (ASCE-EWRI), 3:573 American water resource development, 2:498–499 American Water Works Association (AWWA), 1:146, 285–286, 437 standards of, 1:261, 403 survey, 2:91 Americas, transboundary water treaties in, 4:637–641t. See also Latin America; North American Free Trade Agreement (NAFTA) Americium (Am). See Am-humic colloids Am-humic colloids, dissociation kinetics of, 2:105–106 Aminolevulinate dehydratase (ALAD) activity, 2:236 protein, 2:236–237, 238f Aminolevulinic acid (ALA), 2:236 Ammonia, 4:390–394 in acid mine treatment, 5:4 analysis of, 4:393 bromate ion formation and, 1:360–361 cycling of, 4:391 eutrophication and, 4:392 impact on aquatic organisms, 2:123 in inhibition of biological iron removal, 2:153–154 measurement of, 4:393 in ponds, 3:485–486 sources and concentrations of, 4:392 toxicity of, 4:392–393 in urban stormwater runoff, 3:434

Ammonia–ammonium equilibrium, 4:519 Ammonia nitrogen, in recirculating aquaculture systems, 3:544 Ammonia removal, 1:346 steady-state model for, 1:348 Ammonia toxicity, 3:696 water chemistry and, 3:132 Ammonification, 1:893; 4:517–518 Ammonium. See also Ammonia–ammonium equilibrium distribution of, 4:74 environmental pathways of, 3:538 in source waters, 2:226 Ammonium perchlorate, 5:631 Amorphous hydrous ferric oxide, 5:609 Amorphous ice, 4:189 Amoebas, 2:313 Amoebic dysentery, 2:313 Amorphous organic matter domains, sorption in, 4:386 Amperes, 4:442 Amphidromous fish species, in the Hawaiian Islands, 4:803 Amphipods characteristics of, 2:409–410 commonly used, 2:409t Amphipod sediment toxicity tests, 2:408–413 application of, 2:409 experimental design in, 2:410–411 future research related to, 2:411 organism selection in, 2:409 significance of, 2:408–409 Anacapa Island pelican colony survey, 3:517–518 Anadromous fish, 3:127 Anaerobes, 5:581. See also Anaerobic bacteria; Anaerobic microbial transformation Anaerobic-aerobic treatment, for maize processing plants, 1:581–586 Anaerobic attached film expanded bed (AAFEB) system, 1:519 Anaerobic bacteria, 2:20–21. See also Anaerobes iron-reducing, 2:151 oil-field brine and, 2:288 Anaerobic bioremediation technologies, 5:40 Anaerobic biotransformation, of PCE/TCE, 5:584

715

Anaerobic dechlorination, 1:690 Anaerobic decomposition, 1:701 odor from, 1:760–761 Anaerobic degradation pathways, 5:582f. See also Biodegradation Anaerobic digestion, 1:518 of biosolids, 1:647 of sludge, 1:856–857, 865 Anaerobic Digestion Model, 1:733 Anaerobic filter (AF), 1:906 Anaerobic leachate treatment, 1:709 Anaerobic microbial transformation, of methyl tertiary-butyl ether, 5:386–388 Anaerobic reactor systems, 1:906–909 Anaerobic sewage treatment, 1:517–521. See also Anaerobic wastewater treatment examples of, 1:519–520 future of, 1:520 Anaerobic systems, for treating leachates, 1:704. See also Anaerobic reactor systems; Anaerobic sewage treatment Anaerobic wastewater treatment, 1:813, 904–910. See also Anaerobic sewage treatment application of, 1:909–910 separation of acidogenesis from methanogenesis, 1:909 technology of, 1:905–906 Anaerobic wetlands, 2:425; 5:5 Analysis of antimony, 4:591 of colloids, 3:74–75 in fish consumption advisories, 3:119 Analysis of variance (ANOVA) comparison technique, 2:411 systems approach to, 2:685 Analytical modeling, 5:33 Analytical solutions, 5:621 Anatoxin-a, 2:390 Anatoxins, 2:388–389 Ancient lakes, 3:270 Ancient world, water in, 4:726–728 Animal facilities, managing, 2:186 Animal farming, groundwater quality related to, 3:538–540 Animal husbandry, 3:124 Animal manure, nitrogen in, 3:695 Animals, rain forest, 4:240 Anionic organoclay, 1:779

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716

CUMULATIVE INDEX

Anionic polymeric antiscalants, 1:417–418 Anionic surfactants, 1:670 Anions, in seawater, 4:159 Anisotropic heterogenetic flow systems, testing and analysis of, 5:176 Anisotropy, 5:509–510 Annual status reports (EPA), 5:39 Annual water quality report (AWQR), 2:346 Anodic stripping voltammetry (ASV), 2:207 Anomalous propagation (AP), 4:308 Anoxia factors affecting, 4:65–68 quantification of, 4:64–69 variations in, 4:65–67 Anoxic biodenitrification, 5:326–326 Anoxic conditions, 1:667 Anoxic factor (AF) determining, 4:65–67 prediction of, 4:67 Anoxic limestone drain (ALD), 2:424 in acid mine treatment, 5:5–6 Anoxic periods (denitrification), controlled, 1:752t Antarctica, microbial ecosystems in, 3:504 Antecedent moisture conditions, 3:473 Anthra/sand, 1:314 Anthropogenic activities, toxic metals accumulation from, 2:433 Anthropogenic arsenic, 5:18 Anthropogenic CO2 , global partitioning of, 4:85 Anthropogenic compounds, toxic effects of, 2:427 Anthropogenic dammed pools, 3:69 Anthropogenic disturbances, to wetlands, 3:173 Anthropogenic factors, coastal wetland loss from, 3:73 Anthropogenic GHG emissions, 3:204. See also Greenhouse gases (GHGs) duration of, 3:207 political aspects of, 3:208 Anthropogenic load, 2:443 Anthropogenic nonturbulent unit, 3:70 Anthropogenic scour pools, 3:68 Anthropogenic selenium contamination, 5:397–398

Anthropogenic sources of arsenic, 1:82–83 of heavy metals, 5:276 of lead, 2:433 of radioactive contamination, 1:803 of vinyl chloride, 5:635 Anthropogenic tritium, 5:69–70 Anthropogenic turbulent unit, 3:70 Antibiotic resistance, 1:178 Antibiotics, in animal farming operations, 3:540 Antibody technology, for identifying Cryptosporidium, 1:160 Anti-DDT propaganda, 3:513–526 Antidegradation, precautionary principle regarding, 2:601 Antidegradation policy, Great Lakes system, 4:624 Antifluoridationist movement, 1:255–257 Antifoulant design, 1:415–416 Antimony (Sb) abundance of, 4:589–590 analytical methods for, 4:591 in aquatic systems, 4:589–594 atmospheric emission values for, 4:589, 590t concentrations of, 4:592, 593 kinetic issues related to, 4:592–593 maximum contaminant level of, 2:234t solution chemistry of, 4:591 speciation in natural waters, 4:592 uses of, 4:590 Antiscalants, anionic polymeric, 1:417–418 Antoine’s equation, 4:265 AOC (assimilable organic carbon) level, microbial regrowth and, 1:344–345 A/O (anaerobic/oxic) process, 1:790 Apalachicola-Chattahoochee-Flint (ACF) River Basin water allocation dispute, 2:501–502 Army Corps of Engineers role in, 2:506–507 crisis related to, 2:503 role of interest groups in, 2:505 water allocation and, 2:504–505 water marketing proposals related to, 2:506–508 APE surfactants, 1:670–673 Aphotic zone, 3:265, 267 Aplysiatoxin, 2:389 Apoptosis, characterizing, 3:116

Apparent density, 1:96 Apparent soil electrical conductivity (ECa ). See also ECa entries edaphic factors influencing, 5:466 mobile measurement equipment for, 5:467 Apparent temperature effect, 4:439 Appliances, water-saving, 2:497 Application portals, 2:670 Appropriation doctrine, 2:542 Approximate infiltration models, 4:487 Aquacultural facilities separation processes for, 1:683f waste loads in, 1:681 Aquaculture, 3:123, 124, 127–128 defined, 2:542 technology related to, 3:540–545 Aquaculture ponds, 3:540–542 constituents of, 3:541 Aquaculture systems flow-through, 3:542–543 net pen, 3:543–544 recirculating, 3:544–545 Aqua earth observing system (EOS), 4:214–217. See also Aqua spacecraft data processing and distribution related to, 4:216 goals and objectives of, 4:216–217 management of, 4:216 spacecraft and instruments in, 4:215–216 Aquarium fish, 3:123 Aqua spacecraft, 4:194 water cycle and, 4:193–194 weather forecasting and, 4:351 Aquatic animals, harvesting of, 3:123 Aquatic bacteria, 1:639 Aquatic biota. See also Aquatic organisms antimony concentrations in, 4:593 trace elements in, 3:456–457 Aquatic cadmium, 5:614–615 Aquatic colloids, 4:27–32 Aquatic ecosystem resources, Great Lakes region, 3:178–179 Aquatic ecosystems, 2:617. See also Aquatic environments/ habitats availability of nutrients in, 3:109–110 biotic integrity of, 3:36 damage to, 1:555 health of, 3:116 role of macrophytes in, 1:714–715

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CUMULATIVE INDEX

Aquatic environments/habitats. See also Aquatic ecosystems alteration of, 3:134 characteristics of, 3:123–124 classification and environmental quality assessment in, 2:94–98 effect of sediment on, 3:508 effect of urban stormwater runoff on, 3:436 impact of road salt on, 2:320–321 lipophilic contaminant monitoring in, 2:170–172 trace metal pollution in, 2:64–65 Aquatic foodweb, plankton in, 4:157 Aquatic health, assessing, 3:40 Aquatic humic acid, origin, stability, and mobility of, 5:190–191 Aquatic life effects of acidification on, 3:3 environmental contaminants of, 3:115 impact of chronic acidification on, 3:4 Aquatic Life Criterion, 2:355–357 Aquatic life toxicity. See also Aquatic toxicity entries testing, 4:600 of urban stormwater runoff, 3:433 Aquatic macroinvertebrates, effect of road salt on, 2:321–323 Aquatic macrophytes, 3:107. See also Aquatic vegetation; Aquatic weeds; Macrophytes; Submerged aquatic plants as biomonitors, 2:65–66 hyperaccumulation potential of, 2:66 research opportunities related to, 2:66–67 Aquatic nitrogen, 4:518–519 Aquatic organisms. See also Aquatic animals; Aquatic biota; Submerged aquatic plants bioaccumulation of hazardous chemicals in, 3:435 as indicators of aquatic ecosystem health, 3:40 toxicity of lead to, 2:434 Aquatic plants. See also Aquatic vegetation; Aquatic weeds; Submerged aquatic plants excessive growth of, 1:788 in mine effluent remediation, 1:612 Aquatic resources, renewable, 3:121 Aquatic sediments, 2:384

Aquatic systems antimony in, 4:589–594 assessing the quality of, 2:25 impact on, 2:24 water reduction in, 2:465–466 Aquatic toxicity. See also Aquatic life toxicity measures of, 2:381 standardized test protocols for evaluating, 2:278 Aquatic toxicity testing, 2:380–381 microscale, 3:116 Aquatic vegetation, 3:108–109 Aquatic weeds, 3:742–743 biology and ecology of, 3:743–744 types of, 3:743 Aqueducts defined, 2:542 Roman, 4:266 Aqueous electrons, 1:579 Aqueous phase partition, 1:761–762 Aqueous solutions analysis of, 4:443–445 phenol adsorption from, 4:404–408 removal of organic micropollutants and metal ions from, 4:506–511 Aqueous systems, removal of metal ions from, 1:918–920 Aquicludes, 5:10 Aquifer flow, 5:237 Aquifer matrix, sorption and desorption of CFCs from, 4:422 Aquifer parameters, 5:164 steady-state methods of determining, 5:492–496 Aquifers, 5:9–11. See also Artesian aquifers; Coastal aquifers; Confined aquifers; Fossil aquifers; Fractured aquifers; Granular aquifers; Karst aquifers; Limestone aquifers; Metamorphic rock aquifers; ‘‘Native’’ aquifers; River-connected aquifers; Semiconfined aquifer entries; Sloping aquifer; Surficial aquifers; Unconfined aquifers characterization of, 5:10 confined, 4:167–168 contamination of, 3:228–229 defined, 2:542; 5:600 drawdown in, 5:103–104 enhanced flushing of, 5:440 groundwater in, 5:71–72

717

hydraulic head in, 5:171 microbial degradation of CFCs in, 4:422 natural replenishment of, 5:11–12 overpumped, 2:648 properties of, 5:492 remediation of, 4:675 river-connected, 5:677–688 safe yield of, 5:575–576 sensitivity to contamination, 5:56–57 size of, 5:9–10 storativity in, 5:129–130 surficial, 5:80 travel time of water through, 5:65 types of, 5:515 unconfined, 4:168; 5:11, 483, 497 variability of, 5:664–665 water quality and, 5:9 Aquifer–storage–recovery (ASR) systems, 2:515 Aquifer–storage–recovery technique, 5:134 Aquifer test analysis models, 5:663 Aquifer test data, analysis of, 5:183 Aquifer tests, 5:182–183 of hydraulic conductivity/ transmissibility, 5:513–514 steady-state flow, 5:491–497 Aquifer thermal capacity, 5:173 Aquitards, 5:10–11 Arab-Israeli water resources, 4:699–701 Arable farming, 3:568 Arab World conservation and demand management in, 2:472 renewable water resources by state, 2:471t supply and demand in, 2:471–472 water law in, 4:634–636 water management solutions in, 2:472–474 water resources in, 2:470–474 39 Ar age dating method, 4:389 Aragonite, 4:415 Aral Sea basins irrigation in, 3:17t water sharing in, 3:18–19 Aral Sea disaster, 3:15–20 effects of, 3:16 Arbitrary fixed radius (AFR), 1:525 Archaeology, marine, 4:62

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718

CUMULATIVE INDEX

Arctic Ocean metal levels in, 4:100 sea ice in, 4:69 Area method, of base flow separation, 3:26 Argon (Ar). See 39 Ar age dating method Arid areas, sediment production in, 3:31. See also Arid countries/lands; Arid regions Arid climates, soil erosion in, 3:408 Arid climatic zone, 4:257 Arid countries/lands. See also Arid areas; Dry environments; Dry-land agriculture crop irrigation in, 2:549 effluent water regulations in, 2:475–478 wastewater applications in, 1:632–635 water regulation in, 2:478 Arid regions. See also Arid areas defined, 5:409 precipitation and recharge variability in, 5:409–410 precipitation versus evapotranspiration in, 5:410–411 recharge in, 5:72–76, 408–413 subclassifications of, 5:409t Aristotle, 4:352 observations on weather, 4:348–349 Arizona cienegas in, 3:58 in-stream flow protection in, 4:662 overdraft in, 5:341–342 Arizona spillway, 4:733 Armonica, 4:758–762 future of, 4:762 as a healing water instrument, 4:760–761 resurrection of, 4:761–762 Army Corps of Engineers, 4:612, 616 permits issued by, 4:665–666 role in ApalachicolaChattahoochee-Flint River Basin water allocation dispute, 2:501–502 water marketing and, 2:506–507 working relationship with Congress, 2:523 Aromatic compounds chlorinated, 1:688–690 degradation of, 1:693–694

Aromatic hydrocarbon, 2:110 Arrhenius kinetics, 4:565 Arsenates, 2:16, 17. See also As(V) iron coprecipitation of, 5:20 Arsenic (As). See also Arsenic removal entries anthropogenic sources of, 1:82–83 in ash pond water, 1:851–852 common minerals of, 1:81t detecting in drinking water, 1:2 groundwater, 5:17–21 health effects of, 2:15–18 immobilization of, 5:18–19 inorganic, 2:8–11 in situ electrokinetic treatment of, 5:28 maximum contaminant level of, 2:234t metabolism and disposition of, 2:16–17 minerals with, 5:18 natural distribution of, 1:82 in natural waters, 1:81–83 particulate, 2:11 regulations related to, 1:82 role in metal tolerance, 3:612 toxicity mechanisms of, 2:17 treating in water supply wells, 5:22, 23–25 uncharacterized, 2:11 uptake of, 2:217 Arsenic compounds, 2:7–15 methylated, 2:11 Arsenic drinking water crisis, Bangladesh, 1:1–3 Arsenic exposure, acute and chronic, 2:17–18 Arsenic removal from drinking water, 1:2–3 ion exchange for, 5:21 mechanisms for, 1:83 via reverse osmosis, 5:21 Arsenic removal studies, 1:636 Arsenic removal technologies, 1:636–639 adsorption processes for, 1:638–639 coagulation–precipitation processes for, 1:636–637 membrane processes for, 1:637–638 Arsenic species, 2:7t organic, 2:12–13t Arsenic standard (USEPA), 5:17

Arsenic water treatment methods, effectiveness of, 5:20t Arsenite, 2:17. See also As(III) oxidation, 5:19–20 Arsenothiols, 2:11–13 Artesian aquifers, 5:104, 600 Artesian pressure, 5:30 Artesian water, 5:29–30 defined, 2:542 Artesian well, 5:600 Artificial aquatic systems, 3:311 ‘‘Artificial’’ communities, 2:379 Artificial groundwater tracers, 5:504–506 Artificial neural networking (ANN), 4:323 Artificial recharge defined, 2:542 flood spreading for, 3:164–165 of unconfined aquifers, 5:11–17 Artificial valleys, 3:66 Artificial water retention, 1:405 Arumugam Plan, 4:776 As(III), 1:81, 82 oxidation of, 1:639 As(V), 1:83 Asbestos analysis of, 2:310 maximum contaminant level of, 2:234t, 235t Asbestos-containing material (ACM), 2:310 Aseptic meningitis, 1:178–179 Ash, from coal combustion, 1:555–556 Ash percent, of carbon, 1:97 Ash pond water quality, 1:850–853 Asia, urban water resource management in, 2:552–554 Asian cities, flooding in, 3:160–161 Asian plains, developing, 3:16–18 ASM models, 1:739, 740. See also Activated Sludge Models (ASMs) Assays, standardization and reproducibility of, 2:378 Assessment biological impact, 4:111–113 of contaminant sensitivity, 5:57 source water, 1:444–448 underground pipeline, 1:884–887 Asset sale privatization, 1:389 Assimilable organic carbon (AOC), 2:175, 224–225, 244–245 Asthma, dehydration and, 4:725 Astragalus bisulcatus, 3:35

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CUMULATIVE INDEX

Astrovirus, 1:279 Astrovirus enteritis, 1:179 Atkins, Anna, 4:767 Atlantic Oceanographic and Meteorological Laboratory (AOML), 4:4–6 Atmosphere, 4:179 compressing weight of, 4:360 dynamics of, 4:296 hydrological cycle of, 4:181 long-wave radiation from, 3:192 ocean interaction with, 4:22 pressure and convection in, 4:360–361 vapor conditions in, 4:224 wave propagation in, 4:295–296 weather and, 4:360–362 Atmospheric acidification, 3:8–9 Atmospheric Boundary Layer (ABL), 4:181, 296 Atmospheric cadmium, 5:614 Atmospheric carbon dioxide, increase of, 4:176 Atmospheric Infrared Sounder (AIRS), 4:215, 351 Atmospheric nitrogen, 3:695 Atmospheric/oceanic circulation, changes in, 4:174–175 Atmospheric pollutant deposition, 3:282 Atmospheric scientists, 4:328–330 employment of, 4:328–329 job outlook and earnings for, 4:329–330 responsibilities and working conditions of, 4:328 training, qualifications, and advancement of, 4:329 Atmospheric temperatures, global-scale measurements of, 4:173 Atmospheric tides, 5:498 Atmospheric trace constituents, anthropogenic, 4:176 Atmospheric tritium, production and decay behavior of, 5:65–66 Atomic absorption spectrophotometer (AAS), 4:508 Atomic absorption (AA) spectroscopy, 2:308–309; 4:498 ATP content assays, 2:415 ATP sulfurylase, 5:399, 400 ATP-sulfurylase (APS) gene, 5:288 Atrazine, 2:312; 4:506 Attached growth processes, 1:827

Attainable uses, for surface waters, 2:476–477 Attenuation, as a watershed function, 3:478 Attenuation factor, 5:597 Attenuation processes, phytoremediation enhancement of, 5:374–376. See also Monitored natural attenuation (MNA); Natural attenuation processes Audubon Society, 3:513, 514 Australian Drought Watch System, 4:214 Australian River Assessment System (AusRivAs), 3:40 Australian Water Resources Council (AWRC), 4:449 Authority-polluter negotiations, 4:647–648 Autoanalyzer, 4:514 Autoconvection, 4:366 Autogenic recharge, 5:236 Automated local evaluation in real time (ALERT) systems, 3:148 Automatic model calibration, 2:332 Automation, of microirrigation, 3:623 Autonomous CTD profiler (ACP), 4:71 Autothermal thermophilic aerobic digestion (ATAD), 1:648 Average daily flow (ADF), 3:106 Average water requirement, 1:506–507 Averting behavior water value estimation model, 4:609 Avoided cost water valuation approach, 2:655 Awesome Aquifers science project, 4:714 Axial flow pumps, 3:380 Axial impellers, 1:76, 78f flow patterns induced by, 1:78f Azimuthal resistivity method, 5:147

Backfill, hydrology of, 5:2 Backflow, 1:203 devices, 1:343 prevention of, 1:155–157 Background pollutant concentration, 2:18–20 inorganic pollutants, 2:19–20 organic pollutants, 2:20 water chemistry and, 2:19 Backpressure, 1:155

719

Backscatter, 4:321 Backsiphonage, 1:155 Backup electrical power, 1:303 Backwashable depth filtration, 1:459 Backwater pools, 3:69 Backwater profiles, 1:57 Backyard sewerage, 2:633 Bacteria, 1:903–904; 3:668; 5:580. See also Marine bacteria activated sludge, 1:668t algal control using, 2:6 biofilm-associated, 1:603 chemical transformation via, 5:378 denitrifying, 1:667–668 dissolved oxygen and, 3:445 in domestic sewage, 1:831 effect on bioventing, 5:429 in foaming and bulking, 1:846–847 health effects of, 1:277–278 heterotrophic, 1:567 identification of, 2:21 indicator, 2:293 iron-oxidizing, 2:149–152 luminescent, 2:172–176 MAG tests for, 1:84 on Mars, 4:747–748 metabolite production by, 1:601 metal-resistant, 2:446, 448–449 methanogenic, 5:47–48 molecular and biochemical techniques related to, 2:23–24 motility of, 5:351 nitrifying, 1:753–754 nutrient levels and, 1:598 origins of, 5:463–464 pH and, 3:14 planktonic, 1:596 removal of, 1:485–489 resistance to heavy metals, 2:443 role in heavy metal phytoremediation, 5:376–381 waterborne, 2:20–24 as water quality indicators, 2:23t Bacteria count, 5:184 Bacterial agents, 1:178 Bacterial bioassay, 2:389 Bacterial biofilm, 1:539 formation of, 1:539–540 Bacterial bioluminescence, 2:453 toxicity and, 2:47 Bacterial biosensors availability of, 2:455 constructed, 2:453–454 luminescent, 2:453–458

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720

CUMULATIVE INDEX

Bacterial concentration decreases, dilution equivalent to, 4:104 Bacterial disinfection, 1:469 Bacterial/fecal contamination, indicators of, 2:21 Bacterial growth byproducts of, 5:23 dependence on metal concentration, 2:446f Bacterial growth factor, 1:223 Bacterial infections, 2:371 Bacterial isolates, identification of, 1:664–665 Bacterial monitoring, water treatment plant, 1:222–223 Bacterial neuston, 2:442 Bacterial populations, increase in, 3:114 Bacterial regrowth analysis of, 1:223 BDOC impact on, 1:225–226 Bacterial screening tests, 1:566 Bacterial source tracking (BST), 2:21–22 Bacterial transport factors affecting, 5:351 in groundwater, 5:350–352 in groundwater bioremediation, 5:43–44 in groundwater systems, 5:350–351 Bacteria–plant–contaminant interactions, 5:378–380 Bactericides, drinking water disinfection using, 1:382–387 Bacteriological content, of sludge, 1:863 Bacteriological monitoring, 2:267 Bacteriological parameters, of River Yamuna groundwater, 2:396 Bacteriophages, 3:312 Bacteriophage transport studies, 1:368 Bacterioplankton, 4:155 progression in reservoirs, 3:207f BACTOX test, 2:414 Bad cholesterol, myth of, 4:701–702 Bag filtration, 1:459, 488 Bahls’ periphyton index of biotic integrity, 3:40 Baird, Spencer, 4:141–144 Balanced ecological community, 2:193 Balanced ecosystems, 1:639

Balantidium coli, 2:313–314 Bald eagles, effects of DDT on, 3:519 Ballasted flocculation, 1:454; 4:426 Ballooning, meteorology and, 4:164–166 Balloons, meteorological, 4:164–166, 328 BA-metal complex separation, 1:587 Band-sar, 3:708 Bangkok, flooding in, 3:160 Bangkok Metropolitan Administration rain gauges, 1:124f Bangladesh arsenic drinking water crisis in, 1:1–3 flooding in, 3:160 Bank filtration, 1:486–487 Bank storage, base flow and, 3:22 Baptism, as a water ritual, 4:709–710 Barbiturates, adsorption of, 1:118 Bardenpho process, 1:790–791 Bare metal mode, 4:445 Barium (Ba), maximum contaminant level of, 2:234t Barium sulfate, co-precipitation of radium with, 1:398 Barley straw, in algal control, 2:5–6 Barnacles, 1:541 Barometric efficiency, 4:166–169 Barometric loop, 1:157 Barometric pressure, effect on wells, 5:182 Barrages, 3:201 Bar screens, 1:784 Bartlett–Lewis rectangular pulse model, 3:428 Basalt aquifers, 5:145 Base cation concentrations, 3:3 Base cation depletion, 3:3 Base cation dilution, acidification and, 3:5 Base flow, 3:22–28 defined, 2:542 factors affecting, 3:22 recession of, 3:22–24 Base flow curves, ideal, 3:23 Base flow discharge (Q), 3:23–25 Baseflow hydrograph, 3:476 Base flow index (BFI), 3:27 Base flow recession applications of, 3:26

as auto regressive processes, 3:24 constants determining, 3:24–25 Base flow recession curve, master, 3:25–26 Base flow separation, 3:26–27 graphical methods of, 3:27 Baseline stations, 2:178 Bases defined, 2:542 strength of, 2:294 Basin area, peak discharge per unit of, 3:29 Basin characteristics, role in flooding, 3:143 Basin circularity ratio, 3:94 Basin elongation, 3:29 Basin geomorphology, 4:222 Basins inflow from and outflow to, 5:167–168 retarding, 3:150–151 BASINS. See Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) Basin slope, 3:29 Batch adsorption experiments, 4:508–511 Batch membrane photoreactors, 4-nitrophenol degradation in, 1:793 Batch sorption isotherm studies, 1:112 Batch systems, activated carbons in, 1:101 Bautzen Reservoir, biomanipulation trials in, 2:57t BAX system, 2:140 Bays, 4:25–26 Bazin’s roughness coefficient, values for, 3:196t BBC Water Portal, 2:669 B climates, 4:257 Beaches, 4:26 Beaches Environmental Assessment and Coastal Health (BEACH) Act, 4:39 Beach raking, 4:41 Bear Trap Dam, 3:44 Beaufort Laboratory, coastal fishery and habitat research at, 4:55–57 Beaver dam pools, 3:69 Bed depth-service time model (BDST), 2:363 Bedding, in pipeline repair, 1:889 Bed life, 1:104

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CUMULATIVE INDEX

Bed load, 3:400. See also Bed-material load transport of, 3:418 Bed material, particle size distribution of, 3:420 Bed-material load, 3:397 Bedrock, 5:55 defined, 2:542 dissolution, 5:243–244 Bedrock valleys, 3:66 Bed sediment metal ion adsorption, 3:295–305 experimental methodology for, 3:296–298 operating variables in, 3:298–300 results of, 3:298 river system used in, 3:296 Behavioral endpoints, in sediment toxicity testing, 3:54–55 Behavioral screen fish passage facility, 3:531 Belt pressing, 1:855 Benazolin adsorption isotherms of, 4:510 adsorption of, 4:509 properties and structural formula of, 4:507t Benchmark process, 1:440–441t Bench terraces, 3:550, 567 Bench tests, 5:424 Beneficial use classification, 2:191 Beneficial uses protection of, 2:478 for surface waters, 2:476 Benefit transfer process, 4:610 Benthic algal mats, 3:277 Benthic chambers, 2:352 Benthic environment, in net pen aquaculture systems, 3:543 Benthic nutrient regeneration, 4:6–7 temporal scaling of, 4:11–14 Benthic organisms/species exposure tests with, 2:212 sediment as habitat for, 2:408 surface water metals and, 2:217 Benthic zone, 3:267 Bentonite, 1:771–772, 778 Benzene, 5:427 biodegradation of, 1:693 chemical structure of, 5:626 electrolysis of, 5:122–123 exposure to, 5:627 in groundwater, 5:626–628 hazardous effects of, 5:627

in situ electrokinetic treatment of, 5:116–124 production and uses of, 5:627 remediation of, 5:627–628 Benzene adsorption, on zeolites, 4:406 Benzene-contaminated water, 1:580 Benzene contamination, 5:627 Benzene, toluene, ethylbenzene, and xylene (BTEX), 5:529, 424, 425 plumes, 5:80–81 soil vapor concentration of, 5:552–553 Benzoic acid, adsorption of, 1:117 Berms landside, 3:290 landside seepage, 3:289 stability, 3:288 Bernoulli equation, 3:194, 195; 5:170–171, 180 Berylliosis, 4:394 Beryllium (Be) chemistry of, 4:395 maximum contaminant level of, 2:234t source material for, 4:395–397 in water, 4:394–399 Beryllium concentrations, range of, 4:395–396 Best available control technology (BACT), 1:101 Best available technology (BAT), 1:360, 479, 681, 757 Best conventional pollutant control technology (BCT) standards, 4:656 Best management practices (BMPs), 1:54, 681; 2:192–193; 3:503; 4:669 in aquaculture, 3:542 to minimize groundwater nitrate contamination, 2:571–573 for nitrogen, 3:694, 696–699 for nonpoint source control, 2:187–188 in nutrient runoff control, 3:110–111 riparian buffer, 3:391 solidification/stabilization processes and, 1:838 stormwater management, 3:443 for urban stormwater runoff treatment, 3:432 for water resources, 2:570–573

721

Best practicable control technology (BACT, BPT), 4:596, 656 Best professional judgment (BPJ), 4:656–657 triad weight-of-evidence as, 4:600–601 Beta-gamma radiation, 4:547 Beta emitters, health risks of, 1:396 Better Assessment Science Integrating Point and Nonpoint Sources (BASINS), 2:328, 249–250 BGP carbon, 2:83–85 Bhuj earthquake, 5:478–479 Bible, water symbolism in, 4:786–787 Bicarbonate alkalinity, 4:410 calculation of, 4:410–411 Bilevel drains, falling water table between, 5:96–97 Bingham plastics, 5:556–557 Bioaccumulated metals, 2:421f Bioaccumulation, 2:44, 69; 3:34–36 in assessing sediment quality, 2:426–428 bioassays, 2:351 characteristics of, 2:70t of chemical contaminants, 2:125 of chemicals in edible aquatic organisms, 3:435 in Indian lakes, 3:451 recommendations concerning, 2:431 of selenium, 2:357t use in regulation, 2:429–430 Bioaccumulation Factor (BF), 1:717 Bioaccumulation testing, 4:600 Bioassay batteries, 2:383–384 Bioassays in marine environmental monitoring, 2:443, 444 purpose of, 2:418 sediment toxicity, 2:458–464 subcellular, 2:278–279 use of polychaetes in, 4:42 Bioassessment procedures current, 2:25–26 development of, 2:24–25 preserving biotic integrity and, 2:26 Bioaugmentation, 5:352 Bioavailability, 4:525–526 in aquatic ecosystems, 2:170 metal, 2:235 of zinc and cadmium, 5:370

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722

CUMULATIVE INDEX

Bioavailability biosensors, for arsenic detection, 1:2 Biochemical field surveys, 5:119 Biochemical groundwater parameters, 5:184–185 field testing and analysis of, 5:186–187 Biochemical oxygen demand (BOD), 1:455, 623–624, 639–642, 701–702, 733–735; 2:37–41, 175, 332. See also BOD5 test; Rapid BOD technologies carbonaceous, 1:754t control strategies for, 1:642 historical context of, 2:37–38 of industrial wastewater, 1:569 measurement of, 1:641–642; 2:37 microbes and, 1:640–641 in natural and engineered systems, 1:639–640 operation of, 2:38 uses for, 2:38 Biochemical oxygen demand test, 1:829 Biochemical processes, 5:116–117 Biochemistry, role of dissolved gases in, 4:451–452 BIOCHLOR program, 5:141 Biocides dosage levels of, 1:602t ‘‘environmentally friendly,’’ 1:541 resistance to, 1:602 types of, 2:242 Bioconcentration factor (BF), 3:35 Biocorrosion, 1:600–601 Biodegradable capacity, of soil, 3:706 Biodegradable dissolved organic carbon (BDOC), 2:224–225, 244, 245. See also Biodegradable organics concentration of, 1:226 impact on bacterial regrowth, 1:225–226 Biodegradable dissolved organic carbon analysis, 1:223 Biodegradable organic carbon, control of, 2:224 Biodegradable organics, 1:903. See also Biodegradable dissolved organic carbon (BDOC) Biodegradation, 2:41–45; 3:35; 5:528. See also Aerobic biodegradation acclimation phase of, 2:43 algal bioremediation and, 2:44–45 bioavailability and, 2:43–44

of detergents, 1:672 enrichment cultures and, 2:42 enzymatic mechanisms in, 2:42–43 factors limiting, 2:42 groundwater bioremediation and, 2:44 marine oil spills and, 2:44 mechanisms of, 5:582–586 microbial diversity and, 2:42 modeling, 5:31 naturally occurring processes of, 5:579 nonaqueous phase liquids and, 2:44 of organic vapors, 5:545 recalcitrant molecules and, 2:43 in subsurface systems, 5:415–416 Biodegradation microbiology, anaerobic, 5:40 Biodiversity monitoring in wastewater treatment plants, 1:642–646 precautionary principle regarding, 2:600 in rain forests, 4:240 reducing, 2:637 Biodrainage, 5:98–99 Bioenhancement methods, 5:117 Biofilm(s), 1:205, 576 bacterial, 1:539 channel structures in, 2:230 composition of, 5:36 control of, 1:541–542 detachment of, 2:232 development of, 1:596–598 in distribution systems, 2:244 formation of, 2:228–229 growth curve for, 1:540 heavy, 1:602 metabolic heterogene1ty of, 2:230 microbial dynamics of, 2:228–233 microbial structure and dynamic heterogeneity in, 2:230–232 microbiology of, 3:307–308 nitrification/denitrification, 2:231 oxygen limitation in, 2:231–232 removal of, 1:602 specialized, 3:308 structural heterogeneity of, 2:229–230 sulfate-reducing, 2:231 Biofilm bacteria, 1:539, 597, 601–602 Biofilm formation, boundary layers and, 1:600 Biofilters, for odor abatement, 1:763

Biofouling, 1:415. See also Biofouling monitoring analysis, 1:84–86 caused by iron bacteria, 2:151–152 in a cooling tower, 2:241–242 effects on production efficiency and water quality, 5:35–36 effects on system hydraulic performance, 5:37 evaluating microbial components of, 1:83–87 of industrial cooling water, 1:538–542 in situ electrokinetic treatment of, 5:28 in a membrane water treatment system, 2:242 methods of controlling, 2:242 microbial forms in, 2:239–243 nutrient adsorption in, 2:239 surfaces and, 1:539 symptoms of, 1:83–84 treating in water supply wells, 5:22–23, 27–28 in water wells, 5:35–38 Biofouling microflora, 5:464 Biofouling monitoring practical issues in, 1:86 sampling methods for, 1:86 Biofouling layers, relationship of microorganisms inside, 2:240–241 Biofuel alternatives, 3:545–549 as ‘‘climate neutral,’’ 3:546–547 impacts of, 3:547–548 substance flows from, 3:547–548 Biofuel life cycle, 3:547 Biogas controlling, 1:860 production of, 1:905 in sludge treatment, 1:856–857 Biogeochemical cycling, 3:173 ‘‘Biogeochemical reflux’’ scheme, 2:359f Biogeochemistry, 1:898–899 hydrosphere, 4:284–285 Bioindication approach, to marine environmental monitoring, 2:443–444 Bioindicators, 2:29–30 species used as, 2:34 versus biomonitors, 2:64 Bioleaching, 5:434 Biological Activity Reaction Test (BART ), 1:85

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CUMULATIVE INDEX

Biological agents, 4:295 Biological carbonates, 4:415 Biological contaminants, 2:343–344 detection in surface waters, 2:441 Biological control, of the water hyacinth, 3:482 Biological control systems, for odor removal, 1:914 Biological CSO treatment, 1:787 Biological degradation, of pesticides, 3:648 Biological denitrification, 5:325–326 Biological dual-nutrient removal, 1:816, 834 Biological effects, of acidification, 3:9 Biological filtration, organic removal by, 1:248–249 Biological growth, Monod equation and, 1:735–736 Biological impacts, assessing, 4:111–113 Biological integrity, 2:24 Biologically produced chemicals, 4:400 Biologically stable water, 1:226; 2:224 parameter values that define, 2:224t Biological monitoring, 2:26, 378. See also Biomonitoring with bivalve molluscs, 2:35–36 submitochondrial particle assay as a tool for, 2:376–379 Biological nutrient removal (BNR), 1:399–400. See also Biological dual-nutrient removal Biological nutrients, measurement of, 4:515 Biological phosphorus removal, 1:816, 833 in the activated sludge process, 1:788–791 Biological pollutant removal processes, 3:366 Biological process modeling, 1:735–737 Biological pump, 4:86, 414 Biological reactors POP behavior in, 1:768 sewers as, 3:331–332 Biological samples, of vinyl chloride, 5:637 Biological soil treatment, 5:434 ‘‘Biological supermarkets,’’ coastal wetlands as, 3:72

Biological systems dissolved gases in, 4:451 redox potential ranges in, 1:399 temperature and, 5:174 Biological toxins, in source waters, 1:89 Biological treatment, of landfill leachates, 1:703–704, 709 Biological treatment technologies for odor abatement, 1:762–763 for wastewater, 1:813 Biological wastewater treatment systems, 3:366–367 Biological water-quality parameters, 1:903–904 Biological weed control, 3:746–747 Bioluminescence tests, 2:47–48 Bioluminescence toxicity tests, marine, 2:48 Bioluminescent assay systems, 2:455 Bioluminescent biosensors. See also Recombinant luminescent bacterial biosensors in direct toxicity assessment, 2:47–48 for toxicity testing, 2:45–50 in WWTP monitoring, 2:48 Bioluminescent recombinant bacteria, 2:174, 454 Bioluminescent reporter genes, 2:453 Biomagnification, 3:35 in Indian lakes, 3:451 Biomanipulation, 2:50–58 lake restoration methods and, 2:50 principles of, 2:50–51 Biomanipulation trials, review of, 2:51–58 Biomarkers, 2:28–33; 3:116 in assessing sediment quality, 2:429 classes of, 2:429 metallothioneins as, 2:407 recommendations concerning, 2:431 relevance of, 2:32 use in regulation, 2:429–430 use in sediment toxicity assessment, 2:430t Biomass in foulants, 1:417 of submerged vegetation, 3:276 Biomass immobilization, 2:72 Biomass production, plant nutrients in, 3:548

723

Biomass water productivity, 3:560 Biomonitoring. See also Biological monitoring; Biomonitors developing tools for, 2:62–63 genomic technologies/tools in, 2:58–64 high throughput technologies and, 2:59–62 importance of, 2:67 of polychlorinated biphenyls, 1:715–716 Biomonitors. See also Biomonitoring trace metal, 2:64–68 versus bioindicators, 2:64 Biooxidation stoichiometry, 5:428t BIOPLUME III program, 5:33–34, 141 Bioreactor landfill design, 5:257 Bioremediation, 4:748. See also In situ bioremediation of cadmium, 5:618 of contaminated soil, 3:653 enhanced, 5:319–322, 424 of groundwater, 5:423–424, 442–443 iron-reducing bacteria in, 2:151 of metals, 5:282 of selenium-contaminated waters, 2:355–360 of uranium, 5:642 Bioretention systems, for storm water treatment, 1:868, 869f BIOSCREEN program, 5:141 Bioscreen spreadsheet model, 5:33 Bioscrubber, for odor abatement, 1:763 Biosecurity. See Security; Water biosecurity Biosensors, 1:567–568; 4:525 future development of, 2:455 microbial aminolevulinate dehydratase, 2:236–237 non-toxicant-specific, 2:454t respirometric, 1:565 toxicant-specific, 2:455t Biosolids, 1:646–651, 863 alkaline stabilization of, 1:649 composting of, 1:648–649 digestion of, 1:647–648 as a source of contaminants, 5:433 thermal drying of, 1:649 uses for, 1:649–650 use standards for, 1:650 Biosorbent materials broad-range, 2:69

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724

CUMULATIVE INDEX

Biosorbent materials (continued) comparison of, 2:72t immobilization of, 2:72 Biosorption, 2:69; 4:565 future of, 2:73 of heavy metal anions, 2:72 by living microorganisms, 2:71 mathematical modeling of, 2:71–72 technologies, 2:73 of toxic metals, 2:68–74 Biosorption treatment plants, 2:73 Biosparging, 5:429. See also Air sparging case history of, 5:430–432 technology, 5:41 Biosurfactants, solubilization by, 5:377 Biosurveys, microbial, 2:442–443, 444–451 Biosynthesis, of phytochelatins, 3:610–611 Biota transfer, 4:686 Biotechnology, precautionary principle regarding, 2:600–601 Bioterrorism Act, 2:347, 348 Biotic assemblages, direct measures of, 3:37 Biotic communities, evolution of, 3:36 Biotic diversity, 3:36 Biotic indicators, 3:37 Biotic integrity factors affecting, 3:36 multimetric indexes of, 3:38–40 reasons for using, 3:37 Biotic integrity index, 3:36–41 Biotic interactions, of microorganisms, 3:312 Biotic pollution, 3:134 Biotic processes, effect on solute transport, 5:528–529 Biotic redox reactions, 5:413 Biotoxins, health effects of, 1:277–281 Biotransformation, of chlorinated aliphatic compounds, 1:690–691 Biotreatment(s) of groundwater, 5:120 for methyl tertiary-butyl ether, 5:389 passive, 5:120 Biotrickling filter, for odor abatement, 1:763 Bioturbation, 3:312 Bioventing, 5:428–429 soil, 5:120, 121–122

technology, 5:40–41 versus soil vapor extraction, 5:430 Biovolatilization, 2:359 Birds data related to, 3:514–515 effects of DDT on, 3:513–526 impact of oil on, 4:106 importance of coastal wetlands to, 3:72 toxicity of lead to, 2:434–435 Birth defects, nitrate-related, 1:37 Bivalve assemblages, dense, 4:73 Bivalve-dominated tidal flat, temporal scaling of benthic nutrient regeneration in, 4:11–14 Bivalve excretory activity, coupling with porewater nutrient concentrations, 4:75–76 Bivalve molluscs active biomonitoring of, 2:33–37 biomonitoring with, 2:34–36 chemical monitoring with, 2:35 illnesses associated with, 2:360–361 nutrient excretion by, 4:6–11, 12–13 Bivariate spectral analysis, 4:339 Black Mesa monitoring program, 5:48–51 Blackstone River model, 2:256–260 Blackstone River Watershed, 1:499–500 Blackwater, 1:53, 841 cesspit for, 1:843 coral reef stress and, 4:133–135 MODIS measurements of, 4:134 Blue baby syndrome, 2:219 Blue Book, 2:315 Blue Book of Water Quality Criteria, 4:598 Blue-green algae, toxin producing, 3:190f Blue-green algae blooms control of, 3:189–190 health issues associated with, 3:188–190 toxins in, 3:189 Blue Planet Project, 4:770 Blueprint for Sustainable Development, 2:624 Blue Revolution, 2:627 BOD5 test. See also Biochemical oxygen demand (BOD) components of, 2:39

measurement protocol of, 2:38 problems associated with, 2:40 quality controls for, 2:39–40 quantity measured by, 2:39–40 standards for, 2:39 Body. See also Human body fluid fluctuations in, 4:458 water-regulatory mechanisms of, 4:790 Body concentrations, time-dynamic speciation and, 2:215–219 Body feed, 1:232, 247, 251 Bonding, of toxic metal ions, 1:586–591 Bonding agents, 1:586, 588–589 iron-based, 1:587 Bones, Jim, 4:768 Boreal reservoirs, studies of, 3:180–181 Borehole condition log, 5:153–155 Borehole methods, 5:151–155 Boreholes, amount of gas hydrate in, 4:61 Borehole storage, 4:168 Boron (B) in irrigation water, 2:159 irrigation water quality and, 5:208 isotopes, 5:220–221, 232 Boron-11, 5:218 Boston, extraterritorial land use control in, 1:316 Bottled water, 1:3–5 cost of, 1:5 historical uses of, 1:4 regulation of, 1:4–5 types of, 1:4 Boundary conditions for coupled flow domains, 5:660 flow system, 5:14–16 types of, 5:561 Boundary-dependent shock formation, 3:240–241 Boundary-element method, 5:311 Boundary layer, atmospheric, 4:181 Boundary Waters Treaty of 1909, 4:618, 620, 686 Bowen ratio, 3:193 Box–Cox (BC) transformation, 4:299 Box–Jenkins models, 3:424–425 Boyle’s law, 4:360 Braided channels, 3:32 Brain, lead-induced damage to, 2:435–436 Brakensiek’s flood routing models, 3:255

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CUMULATIVE INDEX

Bransby–Williams formula, 3:471 Brazil, water markets in, 2:568 Br− /DOC ratio, 2:75, 76–78 Breakers, types of, 4:137 Breaking waves, 4:18–19 Break-point chlorination, 1:471 Breakwaters, 4:14–21 floating, 4:20 vertical, 4:17–20 Bridges, 2:568 Bridge slot screens, 5:573 Brilliant Blue FCF, 3:98, 99 Brine(s) acidic, 3:10 deposits, 5:51–54 occurrence of, 5:52 oil-field, 2:284–290 production of, 5:54 products, 5:54 resources, 5:53 types of, 5:52–53 Brine injection technology, 2:285 Brinkman’s equation, 5:659 British Geomorphological Research Group, 4:330 British water companies, 1:305. See also U.K. National Rivers Authority British water management model, 1:389 Bromate ion, 1:358 health effects of, 1:270 minimization strategies for, 1:360–361 removal of, 1:361 Bromate ion formation, 1:358–360 reaction time for, 1:360 Bromide ion, 1:358 concentration of, 1:359 health effects and regulations related to, 2:74 influence on trihalomethane and haloacetic acid formation, 2:74–79 Bromine-containing disinfection byproducts, 1:214 Bromine hydrate, 4:473 Bromoacetic acid, health effects of, 1:266 Bromoacetonitrile, health effects of, 1:267–268 Bromochloroacetic acid, health effects of, 1:266 Bromochloroacetonitrile, health effects of, 1:268

Bromochloromethane, health effects of, 1:264 Bromodichloroacetic acid, health effects of, 1:267 Bromodichloromethane, health effects of, 1:265 Bromoform, health effects of, 1:265–266 Bromomethane, health effects of, 1:264 Brooks and Corey equation, 5:462 Brown pelicans, effects of DDT on, 3:516–518 Brunauer, Emmett, Teller (BET) isotherm, 1:101 Bubble-diffuser contactor, 1:363–364 Bubbler microirrigation, 3:621 Buckingham–Darcy law, 5:126. See also Darcy entries Budgetary models, estuarine, 4:52–53 Buffering capacity, 4:378 Buffering systems, 3:8 Buffer land, 2:168 Buffer mechanisms, 3:273 Buffer solutions, 2:295 Buffer strips, 2:3–4 Buffer zones, 3:476 Build-operate-transfer (BOT) contracts, 1:388 Build-own-operate (BOO) contracts, 1:388 Build-own-[operate]-[train]-[transfer] model, 1:50 Build-own-operate-transfer (BOOT) method, 1:174 Bulk density, 4:484 Bulking. See Microbial foaming and bulking Bulk viscosity, 5:560 Bulk water detention time, 1:205 Buoyancy accelerations, 4:367 Bureau of Indian Standards (BIS), 5:195 Bureau of Reclamation (BOR), 4:687 Burg algorithm, 4:221 Burgers’ flux law, 3:249, 250 Burmister Soil Identification System (BS), 3:690 Bushwalking, 4:788 Business sector, interests of, 2:626 Butler and Ockrent adsorption model, 1:107–108 Bycatch, 3:126

725

Cable-tool water well drilling, 5:105 Cadmium (Cd). See also Cd-resistant bacteria bioavailability in soils, 5:370 dissolution and precipitation of, 5:616 fate and transport of, 5:617 geochemistry of, 5:616 in groundwater, 2:148; 5:613–619 health risks of, 5:615 maximum contaminant level of, 2:234t physical and chemical characteristics of, 5:613–614 phytoextraction of, 5:369–374 precipitation, 5:619 remediation of, 5:617–619 role in metal tolerance, 3:611–612 sorption and desorption of, 5:616–617 sources of, 5:614 species of, 5:616 terrestrial impacts of, 5:615–616 Cadmium hyperaccumulation, molecular basis of, 5:371–372 Cadmium ions, concentration of, 3:298 Cadmium levels, in marine biota, 4:100–101 Cadmium–zinc interactions, 5:370 Caffeine, as a dehydrating substance, 4:724 Caged animals, use at dredged sites, 2:351–352 14 C age dating method, 4:389. See also Carbon (C) Cage farms, 3:580 Caisson sand-abstraction system, 3:417 Calcite, 4:408, 415 solubility of, 4:411–412 solubility products from, 4:408–409 Calcium carbonate coating, formation of, 1:10. See also Lime entries Calcium carbonate scaling indexes, 4:415 Calcium hardness, 4:453. See also Mg/Ca ratio Calcium hypochlorite, 1:457 Calculated fixed radius (CFR), 1:525 Calderon-Sher Safe Drinking Water Act (California), 2:345 Calibration, 1:134–135

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726

CUMULATIVE INDEX

Calibration studies. See Hydraulic network models Calicivirus, 1:279 Calicivirus enteritis, 1:179 California canals in, 3:87–88 coastal wetlands in, 3:72 in-stream flow protection in, 4:662 overdraft in, 5:342 source-water protection in, 2:312 water use in, 2:478–480 California Bay Delta Authority (CBDA) Contaminant Stressors Workshop, 3:371 California Department of Health Services (CDHS), 2:345 California Department of Water, demand forecasting by, 2:530 California Fish & Game Department, 3:518 ‘‘California Rule,’’ 4:631 California Storm Water Quality Task Force, 3:433 California Toxics Rule, 2:356 Caliper log, 5:154 Calorimetry, 4:401 CALVUL statistical method, 5:564–565 Campylobacter, 1:277 Campylobacteriosis, 1:179 Canada. See also Environment Canada (EC) annual precipitation in, 2:660 contamination problems in, 5:604 continental watersheds in, 2:657 flood management in, 2:681–682 hydropower generation in, 3:199 infrastructure in, 2:662–663 water conservation in, 2:660–666 water misuse in, 2:661 water prices in, 2:604 water quality in, 2:663–664 water resources in, 2:656–660 water supply in, 2:661 water use in, 2:661–662 Canadian Environmental Protection Act, 2:319 Canadian households, water consumption in, 1:506f, 507f Canadian landscape, role of water in, 3:507–510 Canadian rivers, suspended sediment load in, 3:509 Canal data, 5:164 Canal irrigation systems, 3:581, 583

Canals, Mekong Delta, 4:748–752 Canal seepage recharge (Rc ), 5:166 Cancer(s). See also Carcinogenic agents; Lung cancer arsenic-related, 1:2 gastric, 1:36–37 vinyl chloride and, 5:636–637 Candida albicans, 2:240–241 Canopy reflectance models, 3:720 Canopy transpiration, 4:346 Capacity building, 1:651–652, 655; 2:628. See also Integrated capacity building (ICB) Capacity to inflow ratio (CIR), 3:409 ‘‘Cap and trade’’ program, 2:133, 134 Capillary action, 2:542 Capillary flow, vadose zone, 5:73 Capillary forces, head and, 5:180–181 Capillary fringe zone, soil samples from, 3:688–689 Capillary lysimeter, 2:340–341 Capillary rise equation, 3:570; 5:180 Capillary rise/pressure, 5:535 Capillary zone, 5:514–515 Capping systems, 5:433–434, 617 Carbon (C). See also Activated carbon entries; 14 C age dating method; Carbon adsorption; Carbons; Coal entries; Dissolved organic carbon (DOC); Organic entries control of, 2:224–225 density, 1:96 effective size, mean particle diameter, and uniformity coefficient of, 1:97 migrating, 3:180–181 uptake capacity of, 2:83t Carbon-13, 5:231 Carbon-14, 5:227, 231. See also 14 C age dating method; Radiocarbon in groundwater tracing, 5:503 Carbonaceous BOD (cBOD), 1:667–668, 754t Carbonaceous material, water adsorption on, 4:402 Carbonaceous minerals, 3:14 Carbon adsorption, 4:381–384 of landfill leachates, 1:707 Carbonate. See also Carbonate geochemistry alkalinity, 3:131 biochemical aspects of, 4:414–415 dissolution and deposition of, 4:414 environmental impact of, 4:416

in natural waters, 4:413–416 as a pH buffer, 4:414 precipitation, 1:705 water treatment and utilization related to, 4:415–416 Carbonate alkalinity, calculation of, 4:470–411 Carbonate aquifers, 5:72 Carbonate geochemistry, 4:408–413 calcite solubility products and, 4:408–409 measured alkalinity and, 4:409–410 saturation index and, 4:409 Carbonate-poor geological regions, 3:8 Carbonate rocks, 5:55 Carbonate scale control, with acid, 4:415–416 Carbonate sediments, 4:415 Carbonate species, 4:411 Carbon bed volume (Vb ), 1:103 Carbon Chloroform Extract (CCE) method, 1:297 standard, 1:288 Carbon cycle, geochemical, 4:414 Carbon dating, 5:231–232. See also C:N ratio Carbon dechlorination, 1:169 Carbon dioxide (CO2 ). See also CO2 production atmospheric, 4:176 as an atmospheric acid, 3:8 global partitioning of, 4:85 ocean storage of, 4:416 residence time of, 4:85 Carbon dioxide uptake, ocean, 4:86 Carbon dioxide water, 4:799 Carbon fluxes, 3:204t Carbon fractionation, 4:502 Carbonic acid, calcite solubility and, 4:412 Carbon isotopes, 5:220. See also Carbon-13; Carbon-14; Radiocarbon Carbonization (charring), 1:94; 2:80 Carbon regeneration, 1:104–105 Carbons, mechanisms of water adsorption on, 4:400–404. See also Carbon (C) Carbon stocks, biogenic, 3:547 Carbon surface chemical composition, effect on phenol adsorption, 4:404–408 Carbon usage rate (CUR), 1:103

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CUMULATIVE INDEX

Carbonyl sulphide (COS), 4:88 Carcinogenic agents, 1:180. See also Cancer(s) arsenic and arsenic compounds as, 2:7, 17–18 luminescent bacteria for determining, 2:174–175 Carcinogenic byproducts, 2:116 Carcinogenic effects, advisories based on, 3:119–120 Carcinogenic responses, 4:674 Cardiovascular effects, of lead, 2:436 Caribbean basin, oil in, 4:99 Carp breeding, origins of, 4:718–722 Carp culture, 3:137–139 Carson, Rachel, 3:514 ‘‘Cartographic anxiety,’’ 4:683–684 Cartridge filters, 1:247–248, 488–489 advantages and disadvantages of, 2:155 for iron removal, 2:152–155 Cartridge filtration, 1:229–230, 232, 459 Cascades, 3:70 ‘‘Cash-for-grass’’ programs, 3:556 Casing, 1:149–150 Caspian Sea level rise, 2:480–484 climate change and, 2:482 hydraulic construction and, 2:482 nature of, 2:481 societal impacts of, 2:482–483 tectonic plate movement and, 2:482 Catadromous fish, 3:127 Catalysis, activated carbon in, 1:105 Catchment management, 3:33 Catchment water quality modeling software, 2:325–326 Catenary grid systems, 1:353 Cathodic protection, 1:154 to limit corrosion, 1:11 Cation exchange, radionuclide removal via, 1:397 Cation exchange capacity (CEC), 1:778; 5:261, 278 Cationic/anionic solubility relationships, 5:281 Cationic organoclay, 1:779, 780t Cationic polymers, adsorption of, 1:118–119 Cationic surfactants, 1:670, 672 Cauchy boundary condition, 5:14 Caustic soda, in acid mine treatment, 5:4 Caustic soda softening, 1:323

Cave formation, 4:412–413 Cave passageways, 5:245 Cavitation, 1:484; 3:489 acoustic, 1:579–580 C climates, 4:258 CDF proteins, 5:286 cDNA libraries, 2:62. See also Complementary DNA (cDNA) cDNA microarrays, 2:63 Cd-resistant bacteria, 2:447. See also Cadmium (Cd) Cell biology, effect of magnetization and water on, 4:456–457 Cell construction, in landfills, 1:697–698 Cell culture-IFA, for measuring inactivation of UV-treated C. parvum oocysts, 1:167–168 Cell culture polymerase chain reaction (CC-PCR), 1:161 Cell lines, in sediment toxicity testing, 3:54 Cell membrane, metal transport across, 2:70 Cells electron stability of, 4:457 heavy metal binding to, 5:378 integrity of, 4:460 passage of water in and out of, 4:458–459 Cell stability, relationship of magnetism to, 4:457–458 Cellular biomarkers, 2:31 Cellular sheet piling, 4:19–20 Cell wall binding, of metals, 5:283 Cement-based binders, 1:836 Cement hydration product leaching, 5:364–365 effect on groundwater pH, 5:365 Cementitious coatings, 1:882 Cementitious liners, 1:883 Cement mortar pipe linings, 1:879, 880 Cement pastes, dissolution of, 5:362–365 Cement replacements, 5:363 Cements, rapid setting hydraulic, 1:882 Center for Watershed Protection, 3:432 Centers for Disease Control (CDC), 2:343 safe water system, 1:26 Central America, transboundary waters in, 4:641–642

727

Central Asian republics recession and social unrest in, 3:19 water disputes among, 3:18 Central Ground Water Authority (CGWA), 2:181 Centralized wastewater treatment, 1:678 Central nervous system, effect of lead on, 2:435–436 Central Pollution Control Board (CPCB), ‘‘designated best use’’ yardstick of, 2:183, 184 Central Valley, California, overdraft in, 5:342 Centrifugal pumps, 1:392–393; 3:380 operation of, 1:394 Centrifugal separation, wastewater, 1:810 Centrifuge, in sludge treatment, 1:855 CE-QUAL-RIV1 software, 2:328 CE-QUAL-W2 software, 2:328 Ceramic membranes, 1:591 Certifying authority, 1:293 Cesspit waste, disposal and agricultural use of, 1:843 CFC dating method versus H–He dating, 5:68–69 versus 85 Kr dating method, 5:249 CH4 , global role and sources of, 4:86–88 Chadha’s diagram, 2:396, 397f Change, equations of, 5:558 ‘‘Changing mean’’ models, 3:215 Channel cross sections, geometric properties of, 3:347t Channel flow routing kinematic wave formulation for, 3:253–254 in unit hydrograph models, 4:358–359 Channel heads, identification of, 3:93 Channels networks of, 3:32 reaches of, 3:31–32, 67 side slopes of, 3:348t slope of, 3:438 systems of, 3:31 terrace systems of, 3:567–568 time of travel in, 3:244–245 Channel structures, in biofilm, 2:230 Channel tests, with alfalfa, 5:392 Channel units, 3:67–70 nonturbulent and turbulent, 3:70 Chara (shrimp grass), 3:276

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728

CUMULATIVE INDEX

Charge neutralization, 4:425 Check dams, 2:550; 3:412 Check valves, 1:482–483 Chelates, synthetic, 5:383–385 Chelating agents, 5:282 synthetic, 5:383–384 Chelation, 3:609; 5:377–378 CHEMFLO-2000 program, 5:141 Chemical adsorption/desorption, 1:725 Chemical agents, 4:295 Chemical analysis, of rainwater, 4:372 Chemical analyzers, 4:514 Chemical carbon activation, 1:95 Chemical coagulants, 4:424 Chemical coagulation process, 2:374 Chemical compounds, use in acid mine drainage, 5:4t. See also Chemicals; Compounds Chemical concentration. See also Concentration techniques information related to, 4:600–601 measurement of, 2:59 Chemical contaminants, 2:344–345. See also Contaminants bioaccumulation of, 2:125 Chemical control, of biofilms, 1:541 Chemical CSO treatment, 1:786–787 Chemical degradation, of pesticides, 3:648 Chemical destabilization, 1:231, 246 Chemical drinking water standards, 1:529–533 Chemical exchange, in heavy water production, 4:465 Chemical factors, in episodic acidification, 3:5 Chemical fingerprinting, 3:169 Chemical-free mussel control, 1:510–514 ‘‘Chemical-free’’ water treatment, 1:330 Chemical industry, activated carbon in, 1:105 Chemical information, incorporating into water quality evaluation, 4:602 Chemically enhanced flushing methods, 5:440t Chemically enhanced primary treatment (CEPT), 1:659–660 Chemical monitoring, 2:267 with bivalve molluscs, 2:35 in situ, 4:514–516

Chemical monitoring reform (CMR), 4:678 Chemical oxidation, 1:370; 2:300. See also Oxidation entries of landfill leachates, 1:706–707 of vinyl chloride, 5:638 Chemical oxidation technologies application practicality of, 5:347–349 Fenton’s Reagent treatment, 5:345–346 for groundwater remediation, 5:344–349 health and safety precautions for, 5:348–349 ozone treatment, 5:347 permanganate treatment, 5:346–347 Chemical oxygen demand (COD), 1:519–520, 623, 701–702, 733–735; 2:40 of dishwater, 2:113, 114 Chemical pollutant removal processes, 3:366 Chemical pollutants pre-1940, 1:529–531 present and future, 1:531–533 Chemical precipitation, 4:586–589 of landfill leachates, 1:705–706 of radioactive waste, 1:804 of uranium, 5:641–642 uses of, 4:586–587 Chemical pretreatment, 1:250 Chemical reactions, as watershed functions, 3:477 Chemical reactors, sewers as, 3:331–332 Chemical regeneration, 1:917 Chemical rehabilitation, 3:125 ‘‘Chemical revolution,’’ 1:286–287 Chemicals. See also Chemical compounds; Compounds in an agricultural landscape, 3:607 bioavailability of, 2:427–428 biodegradation potential for, 3:390–391 effect on corrosion, 1:8t impact of, 2:28 microirrigation and, 3:617–618 odorous, 1:760t partitioning and bioavailability of, 4:521–526 solubility in water, 4:555–559 unregulated, 3:371

uptake and elimination of, 3:35 weed control via, 3:745 Chemical sensors, 4:514 impairment of, 2:283 residence time of, 4:159 Chemical standards, U.S., 2:268 Chemical techniques, for base flow separation, 3:27 Chemical toxicants, mechanisms of action of, 3:117 Chemical treatment of acid mine drainage, 5:3–5 for iron bacteria, 2:151–152 of soil, 5:434 of sludge, 1:857 Chemical wastewater treatment technologies, 1:811–812 Chemigation, 3:623 Chemiometabolic enzyme systems, 3:117 Chemisorption, 1:99 Chemistry of coastal waters, 4:25 marine, 4:57 in transport modeling, 5:31 Chemoautotrophic nitrification, 3:641 Chemograph analysis, 5:239–240 Chemographs, 5:240 Chemosynthetic bacteria, 2:21 Chernaya Bay, underwater weapon tests in, 4:102–103 Chesapeake Bay watershed, nutrient trends in, 3:110 Chezy formula, 3:195 Chicago, Illinois, overdraft in, 5:342–343 Chicago River reversal, 3:41–45 channel work related to, 3:43–44 commission formed for, 3:42–43 Joliet project and, 3:44 South Branch improvements and, 3:44 Chicago Station, SAMSON Database statistics for, 5:79t Chick’s law, 1:193 Chihuahuan Desert, recharge in, 5:74 Children’s Groundwater Festival, 4:713–714 Children’s water rights, 4:771 Chile tradable rights in, 2:645 water markets in, 2:645 water reallocation in, 2:607

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CUMULATIVE INDEX

China legal system in, 2:486–487 policy, laws, and regulations in, 2:487–488 water management financial sources in, 2:487 water management in, 2:484–488 water management institutions in, 2:484–486 water scarcity in, 2:488–489 water symbolism in, 4:786 Chinampas, 4:697–698 Chinese water consciousness, 4:707–708 Chinook, 4:170–171 Chironomids metal concentrations in, 2:421 in sediment-based endocrine disruption, 3:54 in sediment toxicity testing, 3:50–57 species of, 3:51 Chironomus future sediment toxicity testing using, 3:54–55 heavy metal uptake by, 2:215 Chironomus riparius biology of, 3:51 in life cycle testing, 3:52 as a test organism, 2:420 Chironomus tentans biology of, 3:51 in life cycle testing, 3:52–53, 53–54 Chloraminated systems, nitrification in, 2:226 Chloramines, 1:195, 198–199, 457–458, 471; 2:89, 118–119 advantages of, 2:244 Chlorate, health effects of, 1:270 Chlordane, 3:352 residues, 3:649–650 Chloride. See also Chlorine (Cl) brines, 5:52–53 concentration, 5:197 in drinking water, 2:395 levels, 2:321 mass-balance methods, 5:74 Chloride ions, atmospheric, 4:373–374 Chlorinated aliphatic compounds, 1:688; 5:579 degradation of, 1:690–692 Chlorinated alkene cometabolism, 1:690–691

Chlorinated aromatic compounds, 1:689, 691 degradation of, 1:688–690 Chlorinated dibenzofurans (CDFs), 2:107 chemical properties of, 2:109t Chlorinated dibenzo-p-dioxins (CDDs), 2:107 chemical properties of, 2:109t Chlorinated disinfection byproducts (DBPs), 2:115 Chlorinated ethene contaminants, 5:82–83 Chlorinated hydrocarbons, 2:109, 266; 5:322 Chlorinated methanes, 5:529 Chlorinated solvents, 2:317; 5:91–92, 116, 117–118, 581 biodegradation of, 5:584 biotreatment of, 5:117–118 degradation of, 5:587 electrokinetic treatment of, 5:123 Fenton’s Reaction and, 4:446–447 in situ electrokinetic treatment of, 5:116–124 leaking vapors from, 5:552 metabolism of, 5:529 Chlorinated trihalomethanes, 2:77–78 Chlorinated xenobiotic compounds, degradation of, 5:47 Chlorination, 2:88–90, 374 advantages and disadvantages of, 2:398 application and design of, 2:90 break-point, 1:471 carcinogenic byproducts of, 2:398 chemistry of, 2:88–89 domestic sewage, 1:834 Escherichia coli O157:H7 susceptibility to, 2:138–139 factors affecting, 2:89 gas, 1:197–198 for hepatotoxins, 2:390 increasing, 4:524 introduction of, 1:286 products of, 2:89 sodium hypochlorite solution, 1:198 solid calcium hypochlorite, 1:198 systems for, 1:912–913 Chlorination byproducts, 2:91–94 health effects of, 2:92 Chlorinator, 1:197f Chlorine (Cl), 1:127–130. See also Chloride; Chlorine (gas);

729

Chlorine reactions; Cl− contamination; Cl- phenols; Dechlorination; Free chlorine entries compounds of, 2:88 disinfection using, 2:244 dose response of mussels to, 2:401–406 effect on corrosion, 1:8 efficacy as an antifoulant, 2:402 estimating, 1:128 health effects of, 2:92 Chlorine (gas), 1:457. See also Free chlorine in leachates, 1:706 safety of, 2:90 Chlorine-36, 5:232 Chlorine-37, 5:220 Chlorine byproducts, nonoxidizing, 1:129–130 Chlorine demand (CD), 1:128 Chlorine dioxide, 1:194–195, 214, 458; 2:119 Chlorine disinfection, at CSO facilities, 1:786 Chlorine isotopes, fractionation in, 4:502. See also 36 Cl Chlorine-produced oxidants (CPO), 1:128 Chlorine reactions kinetics of, 1:131–132 parameter estimation for, 1:134–135 Chlorine residual modeling, 1:131–137. See also Chlorine transport model dynamic-state, 1:133 steady-state, 1:132–133 within a water distribution system, 1:132 Chlorine residuals, 1:128; 2:398–399. See also Chlorine residual modeling environmental discharge limits of, 1:130 measurement of, 1:130 Chlorine simulation model, 1:136 Chlorine toxicity, factors influencing, 2:402–405 Chlorine transport model, 1:133–134 Chlorite, health effects of, 1:269–270 Chloroacetic acid, health effects of, 1:266 Chloroacetonitrile, health effects of, 1:267

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730

CUMULATIVE INDEX

Chloroanilines, degradation of, 1:689 Chlorofluorocarbons (CFCs), 4:185, 420–424; 5:232 calculating the age of, 4:421–422 concentration of, 4:420–421 dating technique limitations and errors related to, 4:422 effect of, 4:184 in groundwater studies, 4:422–423 measurement laboratories for, 4:423 sampling groundwater for, 4:421 Chloroform, 2:92 health effects of, 1:265 Chloromethane, health effects of, 1:264 Chloro-organics, degradation of, 1:688–692 Chlorophyll absorption in reflectance index (CARI), 3:722 Chlorophyll-α concentrations (CHL), in water quality models, 2:262 Chlorophyll fluorescence (CF), 3:722 Chloropicrin, health effects of, 1:269 Choked flow, 1:484 Cholera, 1:24, 179–180 outbreaks of, 1:283, 290 Cholesterol, vital roles of, 4:702 Cholesterol lowering, role of water in, 4:701–702 Chromated copper arsenate (CCA), 1:83 Chromates, sorption of, 1:581f Chromatographic columns, standard packed, 2:304–305 Chromium (Cr), 5:290. See also Hexavalent chromium in groundwater, 2:147–148 in situ electrokinetic treatment of, 5:28 maximum contaminant level of, 2:234t in soluble oxyanionic complexes, 5:281 treating in water supply wells, 5:22, 25–27 Chromophores, 4:533 organic, 4:530 Chronic acidification, 3:1–4 relationship to episodic acidification, 3:5 waters sensitive to, 3:3 Chronic bioassays, 2:351 Chronic dehydration, 4:722–726

Chronic sediment toxicity testing, 3:52–54 ‘‘Chronic water scarcity,’’ 2:495 Cienega Creek, Arizona, 3:58, 59f Cienega de Santa Clara, Colorado River Delta, 3:58–59 Cienegas, 3:57–60 environmental conditions associated with, 3:57–59 examples of, 3:58–59 hydrologic conditions related to, 3:57 terms related to, 3:59 Ciliated protists, as toxicity assessment test organisms, 2:413–418 Ciliates, 2:313–314 Ciliophora, 2:313–314 Circular Poiseuille flow, 5:654 Circular settling tanks, 1:453–454 Circular water meter register, 1:339 Cities real-time hydrological information system for, 1:121–127 water demand in, 2:490–491 Civilizations decline of, 4:739 irrigation and, 4:737 Civil War, effect on water projects, 2:522–523 36 Cl. See also Chlorine isotopes case studies on, 4:418–419 dating method for, 4:417–418 measurement of, 4:417–418 old groundwaters and, 4:416–420 production of, 4:417 Cladocera, 3:273 36 Cl age dating method, 4:389–390 Clapeyron equation, 4:264–265, 365 Clarification, water treatment plant, 1:224 Clarifiers design of, 1:815 modeling, 1:733 Clathrate hydrates, 4:471–475 in natural and industrial environments, 4:473–474 Clark hydrograph, 3:60, 61 Clark rainfall-runoff transformation, 3:60–65. See also Isochrone spacing methods parameters of, 3:61–63 principles of, 3:60–61 Class ‘‘A’’ pathogen reduction, 1:649

Classification, of agricultural land, 3:608–609 Classification system, for wetlands and deepwater habitats, 3:496–498 Clathrate hydrate structure complex, 4:472–473 Clathrate hydrate structures, 4:471–472 novel, 4:472–473 Clausius–Clapeyron equation, 3:193; 4:366, 369 Clausius–Clapeyron method, 4:272 Clay minerals, trace elements in, 3:455 Clays, in membranes, 1:418. See also Organoclay Clay-supply industry, impact on surface water quality, 3:374 Cl− contamination, 3:2 Clean Air Act Amendments, acid rain under, 4:377 Clean Lakes Program, 2:315 Clean Water Act (CWA), 1:755; 2:96, 194–195, 292, 315; 4:40,4:595–598, 671–672 amendments and water protection laws under, 4:597 effluent limitations and water quality standards under, 1:755–756; 4:596 goals of, 2:127 implementation procedures for, 4:670 improvements under, 2:191 1977 and 1987 amendments to, 4:654–655 nonpoint source control regulations under, 2:185 numeric effluent system of, 1:756–757 plans, grants, and funding under, 4:597 Clean Water Act regulations, early, 4:598–599 Clean water plants, 1:660–661 Clean Water Restoration Act of 1966, 4:653 Clear water zone (CWZ) depth, 1:452 Clepsydras, 4:704, 705 Climate Columbia Basin, 4:293 extremes in, 4:175–176 Great Lakes, 3:177–178 of Hawaii, 4:255–259, 802

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CUMULATIVE INDEX

‘‘normal,’’ 4:187 plankton influence on, 4:157 role of ocean in, 4:21–23 sea level and, 4:117–118 society and, 4:183–186 of the stratosphere, 4:182–183 understanding, 4:169–170 Climate change, 2:600 Caspian Sea level rise and, 2:482 coping mechanisms for, 4:185 detecting, 4:177–178 effect on aquatic environments, 3:124 global, 4:171–172 influence on the hydrologic cycle, 4:282–283 observations of, 4:172–179 water cycle and, 4:193 Climate models, evaluating, 4:172 Climate prediction, long-term, 4:215 Climate-related transboundary issues, 4:185–186 Climate system, 4:179–183 sea ice and, 4:69–70 Climatically-active trace-gas cycles, role of oceans in, 4:85–89 Climatic conditions, in the Mediterranean islands, 2:642 Climatic issues, interest in, 4:92 Climatic zones, lake temperatures and, 3:266–267 Climatologists, 4:328 Climatology, 4:186–187 drought and, 4:187 Clocks early, 4:702–703 elements of, 4:703 Clofibrate, 1:373–375 Clogging, in diffused air aeration systems, 1:630 Close-fit lining, 1:878–879 Closure, of municipal solid waste landfills, 2:168 Cloth-Plate Method (CPM), 4:202–203 Cloud effects, 4:169–170 Clouds, 4:293 long-wave radiation from, 3:192 understanding, 4:169–170 Clouds and the Earth’s Radiant Energy System (CERES), 4:169–170, 194, 216 commercial applications of, 4:170 educational outreach and, 4:170 future missions of, 4:170

Cloud seeding, 4:187–188 effectiveness of, 4:188 future of, 4:188 Cl-phenols, microbial detection of, 2:442 Clumping, 1:667, 668 Cnoidal wave theory, 4:135 C:N ratio, 5:329 CO2 production, 3:181–182 Coagulant dosing, water treatment plant, 1:223–224 Coagulant recovery, from water treatment plant residuals, 1:139–141 Coagulants, 4:425–426 Coagulation, 1:137–138, 370, 370, 811; 2:98; 4:424–429, 586 disinfection byproduct precursor removal by, 2:116–117 efficiency of, 4:427–428 enhanced, 2:120 of landfill leachates, 1:705–706 mechanisms of, 1:138; 4:424–425 ozone effects on, 1:355 particulate matter removal by, 1:137–139 in precursor minimization, 2:116–117 Coagulation/filtration, for arsenic treatment, 5:24 Coagulation–precipitation processes, 1:706 arsenic removal, 1:636–637 Coagulation/sedimentation process, 1:816–817 domestic sewage in, 1:834 Coal ash byproduct contaminants, from electric generating plants, 1:556 Coal combustion, 1:555 contaminants released by, 1:555t Coal extraction, environmental degradation from, 1:553–554. See also Coal mining Coal mining, impact on surface water quality, 3:374. See also Coal extraction Coarse gravel filtration, 1:239–240 Coarse screens, 1:784–785 Coastal aquifers, 5:497 groundwater contamination in, 5:223 Coastal fisheries management, 3:126 research on, 4:55–57

731

Coastal fog. See also Fog along the Northern Gulf of Mexico, 4:230–239 conditions that help, 4:231–232 scales occurring with, 4:230–231 sounding profiles present during, 4:237–239 variables present in production of, 4:232–236 Coastal hurricane forecast system, 4:275 Coastal regions, salt water intrusion in, 3:678 Coastal resources, 2:489 Coastal shelf waters, 4:26 Coastal water pollutants, 4:96–109 Coastal waters, 4:23–27 arsenic in, 2:11 CH4 concentrations in, 4:87 chemical characteristics of, 4:25 importance of, 4:26–27 indicators of organic contamination in, 2:442 physical processes in, 4:23–25 types of, 4:25–26 Coastal watershed, coral reefs and, 4:113–117 Coastal wetlands, 3:71–74. See also Wetlands ecological importance of, 3:72 loss trends related to, 3:72–73 research related to, 3:73 Coastal Wetlands Planning, Protection, and Restoration Act, 3:73 Coastal Zone Act Reauthorization Amendments, 2:185 Coast Guard Maritime Differential GPS (DGPS) system, 4:249 CoastWatch program (NOAA), 4:55 Coatings cementitious, 1:882 pipe, 1:154 protective, 1:882–883 Cobalt (Co) chemical reactions with, 5:611 contamination by, 5:612 fate and transport of, 5:611–612 in groundwater, 5:610–613 health and safety of, 5:612 isolation of, 5:611 physical properties of, 5:611 remediation techniques for, 5:612–613 sources of, 5:610–611

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732

CUMULATIVE INDEX

COD relationships, in modeling, 1:735–737. See also Chemical oxygen demand (COD) Coefficient of storage, 5:492 Coefficient of variation (COV), 5:238–239 Cold cloud seeding, 4:187 Cold fronts, fog and, 4:231 Cold vapor atomic absorption spectrophotometry, 3:119 Cold-water corals, 4:32–38 distribution of, 4:34 Coliform bacteria, 1:661; 5:200–202, 407. See also Escherichia coli in drinking water, 1:661 removal performance for, 1:663, 664f strains of, 1:662t Coliform counts, 1:662, 664f Coliform group, 1:293, 295 as indicator organisms, 2:293 Coliforms, in groundwater, 2:396. See also Escherichia coli; Fecal coliforms (FC) Colitis hemorrhagic, 1:180–181 shigellosis, 1:181–182 Collapsing breakers, 4:137 Collecting systems, alternative, 1:678, 840 Collection, as a watershed function, 3:473–474 Collector wells, horizontal, 5:88–89 Colleges, land-grant, 3:597–598 Collision-induced dissociation (CID) technique, 4:443 Colloidal fouling, 1:415 Colloidal processes adsorptive, 5:350 mechanical, 5:350 Colloidal silica, in membranes, 1:418 Colloidal stability, 4:424 Colloid compounds removal, 1:684 Colloids, 2:99–100 biophysicochemical interactions with filters, 2:100–102 freshwater, 3:74–75 marine, 4:27–32 properties of, 3:74–75 techniques for characterizing, 3:74–75 Colloid science, role of dissolved gases in, 4:451–452 Colloid transport, 5:349–350 models, 1:368

Colluvial valleys, 3:66 Color, water, 1:901–902 Color abatement, using ozone, 1:355 Colorado in-stream protection in, 4:660–661 overdraft in, 5:341 Standardized Precipitation Index use in, 4:210–211 Colorado Drought Plan, 4:213 Colorado River, 2:555. See also Cienega de Santa Clara, Colorado River Delta salinity profile of, 3:680 United States-Mexico conflict over, 4:636–637 Color-coding, in reclaimed water systems, 1:808 Colorimetric assays, 2:415 Colorimetric titration method, 4:453 Colorimetry, in pH measurement, 2:295 Colpidium campylum, as a test organism, 2:413 Columbia River, 2:554, 555 Columbia River Basin, 2:589 climate of, 4:293 Column experiments/studies, 1:723, 772 categories of, 2:103 column preparation in, 2:103–104 in contaminant transport, 2:103–106 examples of, 2:105–106 procedure for, 2:104–105 Columns dimensions of and materials for, 2:104 nutrients in, 3:277 Comanagement, 3:125 Combined chlorine/combined available chlorine, 1:128 Combined chlorine residual, 2:398 Combined sewer overflows (CSOs), 1:496, 497, 748, 782, 799; 3:281, 332. See also CSO entries Combined sewer overflow treatment, 1:782–788 biological, 1:787 chemical, 1:786–787 physical, 1:783–786 Combined sewers, 3:331–332 Combustible watersheds, conflagration prediction for, 3:461–469 Cometabolic oxidation, 2:300

Cometabolic processes, for bioremediation of chlorinated solvents and petroleum hydrocarbons, 5:117–118 Cometabolism, 2:42; 5:584 Comets, water ice in, 4:190 ‘‘Command and control’’ regulation, 2:132 Command area studies, remote sensing and GIS application in, 2:533–534 Commerce, importance of coastal waters to, 4:27 Commercial activated carbon (CAC), 4:495 Commercial fishing, 3:123, 533 Commercial meters, 1:340 Commercial storm water discharges, 1:867 Commercial water use, 2:542 in the United States, 2:652 Comminution, 1:814 domestic sewage, 1:832 Commission on Drainage and Water Supply, 3:42–43 Commissions, inland water, river basin, and lake catchment, 3:293t Committee on the Biological Effects of Ionizing Radiation (BEIR) VI, 4:543 Commodification, 1:42, 216 Common law, 4:630 Common-Pool Resources (CPR), 2:625 Communication, role in fish consumption advisories, 3:120 Community, water conservation in, 2:664–666 Community analysis, molecular probes in, 1:643–645 Community-based fisheries management, 2:636 Community-based organizations (CBOs), 1:655–656 Community-based resource management, 2:629 Community-based water management, 2:628 Community groups, involvement in source water assessment, 1:447 Community involvement in groundwater protection, 2:518–520 strategies for, 2:519

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CUMULATIVE INDEX

Community profiling methods, 1:643 Community water systems (CWSs), 4:676 Community Water Supply Study (CWSS), 1:289 Competing ligand exchange technique, 2:420 Competitive adsorption on activated carbon, 1:107–121 statistical design for, 1:109–110 Competitive sorption of inorganics on activated carbon, 1:110–115 of organics, 1:115–119 Complementary DNA (cDNA), 2:59. See also cDNA entries Complete mix reactor, 1:815, 833 Complexation constants, 2:206 Complexation/flocculation, 1:872 Complexation reactions, 1:725 Complex chlorinated hydrocarbons, 5:43 Complex fluids, 4:448–449 Complexing agents, 5:281–282 Complexing ligands, destruction of, 5:283 Complex waste waters, mercury removal from, 1:722–723 Compliance technologies, 1:457 for the Total Coliform Rule, 1:463t Composite materials, sorption characteristics of, 2:364 Composite programming (CP), 2:521 Composting of biosolids, 1:648–649 of manure, 2:572 of sludge, 1:857, 865 Compost toilets, 1:679 Compound meters, 1:338 Compounds. See also Chemical compounds; Chemicals; Organic compounds in groundwater, 2:316–319 most frequently detected, 5:61f partition variables for, 4:523t Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), 2:96; 5:368 Comprehensive models, 2:272 Comprehensive Soil Classification System (CSCS), 3:690 Computer codes, for geochemical modeling, 5:140–141

Computer models, 1:122. See also Computer simulations water-management, 2:620 Computer simulations, for vulnerability assessment, 5:563–564 Concentrated recharge, 5:236 Concentrates, 1:413 disposal methods for, 1:174t Concentrating solar collector, 1:66 Concentration measurement, 2:59 Concentration techniques, 2:102. See also Chemical concentration ‘‘Concept of Ecotones,’’ 3:292 Conceptual models, 3:328, 337; 5:589 Concession contract model, 1:50 Concessions, private sector, 1:388–389 Concrete caissons, 4:19 Condensation, 4:188–189, 196 defined, 2:542 for odor abatement, 1:762 Condensed organic matter domains, sorption in, 4:386 Conditional entropy, 4:219 Conditioning, of sludge, 1:864 Condominial sewerage, 2:633 Conducting polymers, 1:872 Conductivity, electric, 4:429–433 Conduit flow springs, 5:239 Conduit flow systems, 5:237 Cone penetrometer (CPT) rigs, 5:455 Confined aquifer flows, 5:493–494 Confined aquifers, 5:11, 145, 481–482, 497, 600 barometric efficiency of, 4:167–168 drawdown in, 5:103–104 miscible displacement in, 5:161 storage in, 5:515–516 storativity in, 5:129–130 ‘‘Confined’’ disposal of dredged sediments, 2:124–125 Conflagration prediction, for combustible watersheds, 3:461–469 Conflict management, in the Middle East, 4:755, 756, 757 Conglomerates, 5:55 Conjunctive use management, 4:632 Connate water, 5:54–55 Conservation, 1:509–510 in the Arab World, 2:472 industrial, 2:496 water, 1:307 water cycle and, 4:433–434

733

Conservation aquaculture, 3:128. See also Species and habitat preservation/protection Conservation laws, for fluid flow systems, 5:651 Conservative pollutants, 4:50 Consolidated water-bearing rocks, 5:55–56 Constant-head boundary, 5:419 Constant-rate pumping test, 5:574–575 Constituents of concern (COC), 5:344–345 Constructed wetlands, 1:787, 843, 892–897. See also Wetlands in acid mine treatment, 5:5 advantages and disadvantages of, 3:366 algal control via, 2:3 application of, 1:896 costs of, 1:843 for mine wastewater treatment, 1:897–900 phytoremediation by, 3:364–371 pollutant removal mechanisms of, 3:366–367 types of, 1:894–896; 3:365–366 water quality improvement in, 1:892–894 Constructed wetland systems, for storm water treatment, 1:868 Construction stormwater discharges from, 4:659 well, 5:87–91 Construction activities, stream quality and, 3:442 Construction and operating agencies, federal, 4:650t Construction companies, service concession operation by, 1:390–391 Construction Grants Program, 4:654 Construction materials, for drinking water storage facilities, 1:410 Construction sites, water impacts from, 1:537–538 Consumer confidence reports (CCRs), 1:145–146; 2:346 Consumer information regulations, 4:678 Consumption advisories, 3:118–121 Consumptive use, defined, 2:542 Consumptive water use, 1:561 in the United States, 2:647 Contact angle hysteresis, 5:536

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734

CUMULATIVE INDEX

Contact flocculation, 1:254 Contactor hydrodynamics, role in bromate ion formation, 1:361 Contact precipitation, 4:437 Contact stabilization, 1:815 Contact time (CT), 1:354 Containment as a remediation strategy, 2:357–358 of vinyl chloride, 5:639 Contaminant distributions, vertical characterization of, 5:80–81 Contaminant hydrogeology environmental isotopes in, 5:217–221 isotopes in, 5:216–227 Contaminant mixtures, effects of, 2:429 Contaminant monitoring regulations, unregulated, 4:678 Contaminant movement and transformation information needed for predicting, 5:579t role of perched groundwater in, 5:354–355 Contaminant–plant–bacteria interactions, 5:378–380 Contaminant plumes, 5:47, 255 vertical delineation of, 5:85 Contaminant release, from redeposited sediment, 2:125 Contaminant removal, thermal treatment methods for, 5:441t Contaminants. See also Chemical contaminants; Contamination attenuation of, 5:56 in bioproductivity zones, 4:105 categories of, 5:216–217 characteristics of, 5:57t chemical properties of, 1:54t cometabolism of, 5:379 degradation modes of, 5:581 degradation products of, 5:32 from electric generating plants, 1:553–558 field sampling and monitoring of, 2:263–269 globally distributed, 4:97 groundwater, 2:183 inorganic, 1:463t investigations of, 3:169 lipophilic, 2:170–172 macrophyte uptake of, 1:715 metabolic pathways of, 5:529

microbial processes affecting attenuation of, 5:578–594 microorganism, 1:54 natural, 2:181 radioactive, 5:221 reducing through reverse osmosis, 5:25, 326 reduction processes for, 5:442 regulatory standards for, 2:346t in sediments, 3:50 sensitivity to, 2:409 sewage, 1:829 spills of, 5:439 toxicity of, 5:57 use of biodegradation to remove, 2:42 Contaminant sensitivity assessing, 5:57 limitations of, 5:57–58 Contaminant transport column experiments in, 2:103–106 mathematical model of, 5:517–518 modeling, 5:30–31 Contaminant vapors downward transport of, 5:551–552 transport of, 5:550 transport rates of, 5:550–551 Contaminated groundwater. See also Groundwater contamination in situ bioremediation of, 5:38–42 organoclay/carbon sequence for treating, 1:777t Contaminated sediments, characterizing, 2:460 Contaminated sediment testing, species appropriate for, 2:427t Contaminated soil. See also Soil contamination excavation of, 3:652 land application of, 3:652–653 remediation options for, 3:652–654; 5:432–436 selection of the remedial approach for, 3:654 Contaminated waters, remediation of, 5:278–279 Contaminated water sources, arsenic removal from, 1:636–639 Contamination. See also Contaminants aquifer sensitivity to, 5:56–57 Cryptosporidium, 1:164 drinking water distribution system, 1:342–344 groundwater, 2:182; 5:56–60

karst area, 5:247 mathematical formulation for, 5:663–664 mercury, 1:722–723 prevention of, 1:438 septic system, 1:62 susceptibility to, 1:446–447 technetium-99, 4:580 vulnerability to, 2:313; 5:247 Contamination sources inventory, 1:446 Continental effect, 4:439; 5:230 Continental rifts, 3:20 Contingency planning (CP), 1:527–528 Contingent valuation (CV) method, 2:130 Contingent water valuation method (CVM), 4:607–608 Continually stirred tank reactors (CSTRs), 1:740 Continuity equation, 3:197; 5:481, 558–559, 651 Continuous chlorination, 2:398 Continuous flow analysis (CFA), 4:514 Continuous membrane photoreactors degradation of dyes in, 1:794–795 at high pollutant concentrations, 1:794 4-nitrophenol degradation in, 1:793 Continuous monitoring technique, 3:400 Continuous permafrost, 4:306 Continuous systems, granular activated carbons in, 1:102 Continuous watershed response, modeling, 3:343–344 Continuous waves, 3:248 Continuous wire wrap screen, 5:573 Contour ridging, 3:551 Contour trenches, 2:550 Contracts, private sector participation, 1:389t Control costs, 2:131 Controlled-tension lysimeter, 2:341–342 Control valves, 1:483 Control water, selecting, 2:382–383 Control-water exposures, 2:382 Convection, atmospheric, 4:360–361 Convective storms, forecasting, 4:354 Conventional roof drainage, 1:55 Conventional sanitation, limitations of, 1:677–678

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CUMULATIVE INDEX

Conventional wastewater treatment, 1:840 systems for, 1:678 Convention on Biological Diversity, 3:122 Convergence, 4:716 Convergence pools, 3:68 Conveyance loss, defined, 2:542 Conveyance system structures, 2:568 Co-occurrence-based approaches, 4:601 Co-occurrence-based sediment quality guidelines, 4:601–602 Cooking, without power, 2:529 Cooling, adiabatic, 4:366–371 Cooling tower, biofouling in, 2:241–242 Cooling water contaminants, from electric generating plants, 1:556 Cooling water systems, water treatment for, 1:560 Cooperative agreements, 2:401 Cooperative model, 1:50 Coordinated freshwater fisheries management, 3:134 Coordination and study agencies, federal, 4:650t Copenhagen permeable reactive barrier site, 5:521, 522–523 Copernicus, Nicolas, water theory of, 4:712 Copper (Cu) biocidal effects of, 1:382–383 concentrations, 2:422t dietary, 1:383 in groundwater, 2:147 maximum contaminant level of, 2:234t recovery of, 1:686 role in metal tolerance, 3:612 sorption capacity, 2:83 toxicity to aquatic life, 2:147 Copper industry, 1:563 Copper removal by sorption, 2:362 using polymers, 1:919–920 Copper tolerance, metallothioneins and, 3:612–613 Coprecipitation alum, 5:20 iron, 5:20 Coprecipitation technique, 4:438 Coral decline, causes of, 4:114–115 Coral reefs, 4:113–117 impacts on, 4:114–115

industrial pollution and, 4:107 protecting, 4:115–117 Coral reef stress, from black water, 4:133–135 Corals cold-water, 4:34 deep-water, 4:32–38 impact of oil on, 4:106 Corin Dam catchment fire, 3:466–467 Coriolis effect, 4:24, 361 Corporate Average Fuel Economy ´ 4:479 standards (CAFE), Corporations, American, 2:499 Corporatization, of water, 2:569 Corrective Action, Phase III, 5:437–438 Corrective maintenance, 2:595 Correlative rights doctrine, 4:631 Corrosion, 1:142. See also Corrosion control assessing levels of, 1:9t conditions leading to, 1:544–545 consequences of, 1:7 diagnosing, 1:152–153 factors impacting, 1:7–8 in industrial cooling water, 1:542–545 inhibitors of, 1:10–11, 153–154 measuring, 1:8–9 microbiologically induced, 1:600–601 pipe breaks and, 1:400 process of, 1:5–6 soft water and, 1:324 types of, 1:6, 7t Corrosion cell, 1:5–6 Corrosion control in drinking water systems, 1:5–12 methods of, 1:9–11 microbial regrowth and, 1:345 in pilot systems, 1:11 in small drinking water systems, 1:459 system design and, 1:153 in water distribution systems, 1:152–154 ‘‘Corrosion fatigue cracking,’’ 1:545 Corrosion indexes (indices), 1:9, 10t, 152–153 Cosmic water, 4:189–191 Cosolvation, 5:527 Cost(s). See also Cost estimation; Economics; Life cycle costs;

735

Pricing; Transaction costs; Water pricing of acid mine drainage treatment, 5:4–5 of bottled water, 1:5 of chemical oxidation technologies, 5:347–348 of desalinated water, 1:174 of diffused air aeration systems, 1:630 of droughts, 2:579–580 of fluoridating water systems, 1:256 of in situ bioremediation, 5:42 of irrigation, 3:592–593 of magnetic water conditioning, 1:536 of membrane technology, 1:309 MIEX plant, 1:329–330 of microirrigation, 3:619 of multistage filtration, 1:242 of the 1930s drought, 2:513 point-of-use/point-of-entry system, 1:379t of regulatory compliance, 1:305 of sand abstraction, 3:417 of small-scale wastewater treatment, 1:842–843 of solidification/stabilization, 1:839–840 of sprinkler irrigation, 3:713 of urban flooding, 3:161 of water distribution system design, 1:211–212 of water quality management, 2:369 Cost analysis, for treating disease, 1:427 Cost–benefit analysis, 2:129–130 Cost effectiveness, 4:675 Cost-effectiveness analysis, 2:131 Cost-effective technology, 2:569 Cost estimation as a water conservation measure, 1:147–148 water treatment plant, 1:222 Council of Great Lakes Governors (CGLG), 4:618 Coupled flow domains, boundary conditions for, 5:660 Coupled flows mathematical models for, 5:659 nodal replacement scheme for, 5:660 Coupled free flow, 5:655–661

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736

CUMULATIVE INDEX

Coupled Markov-chain (CMC) model, 5:309 Coupled model, 4:22 Coupled nonconservative pollutants, 4:50, 51 Coupled reaction-transport models, 5:139 Coupon weight loss corrosion measurement, 1:8 Cousteau, Jacques, 4:792–793 Cox, Wim, 4:769 Cr(VI), 4:515, 587. See also Hexavalent chromium instrument development for in situ monitoring of, 4:515–516 Cradle Mountain–Lake St. Clair National Park, 4:788 Craig line equation, 4:439 Crater lakes, acidic, 3:9 CREAMS model, 2:250–251 Creeping flow, 5:654–655 Critical depth, 3:196 Critical period techniques, 3:383 Critical storm period analysis basis for, 4:339 case study in, 4:339–341 management implications related to, 4:341–342 statistical approach to, 4:338–343 Crop coefficient, 2:537 factors affecting, 3:576f values of, 3:578t Crop development stages, lengths of, 3:577t Crop evaporation, 3:720–721 Crop evapotranspiration, 3:571–579 estimates of, 3:572–578 measurements of, 3:572 water table contribution to, 3:570–571 Cropland, pesticides applied to, 3:607 Crop management as a nitrogen best management practice, 3:696–698 techniques of, 2:496 Crop metabolism, 3:721 Crop Moisture Index (CMI), 4:212 Crop phenology, 3:722–723 Crop photosynthesis, 3:721–722 Cropping patterns, 5:164 Crop quality, microirrigation and, 3:618 Crop removal, nitrogen losses from, 3:696 Crop residues, nitrogen in, 3:695

Crops. See also Crop water requirements adaptation to water stress, 3:719–720 microirrigation of, 3:625–626 salt tolerance of, 3:684–635 Crop tolerance, groundwater depth and, 3:601–603 Crop water requirements, 3:557–558 Crop water stress chronic, 3:722 detection using remote sensing, 3:719–724 Crop water stress index (CWSI), 3:719, 720. See also Idso–Jackson crop water stress index (CWSI) Crop yields evapotranspiration and, 4:227 waterlogging and, 3:600–601 Cross-flow ultrafiltration, 4:29 Cross connection control programs, 1:157–158 Cross connections, 1:155, 203, 342 ‘‘Crossing distance,’’ 3:81 Cross-media contamination, from solidification/ stabilization, 1:838–839 Cross-media transfer potential, of pollutants, 1:838 Cross subsidization, 1:216 Crown width, levee, 3:287 Crustaceans. See also Amphipod entries in sediment impact testing, 2:426 stock enhancement of, 4:125–126 Cryosphere, 4:183 Cryptosporidiosis, 1:180 Cryptosporidium, 1:162–165, 278, 522, 523 detection via polymerase chain reaction, 1:160–161 diagnosis of, 1:163–164 epidemiology and prevention, 1:164–165 in karstic aquifers, 1:366–367 life cycle and morphology, 1:163 molecular detection methods for, 1:161t transport of, 1:366–367 treatment of, 1:164 Cryptosporidium parvum, 2:343–344 antibody technology for identifying, 1:160

measuring oocyst inactivation following UV disinfection, 1:165–169 molecular-based detection of, 1:158–162 Crystal Lake, biomanipulation trials in, 2:57t Crystallization, 1:810–811 of heavy metals, 5:378 scale formation and, 1:547 Crystal modification, for scale control, 1:548 CSO retention basins (RBs), 1:783–784 Cubic feet per second, 2:542 Cultivated ponds, 4:697 Cultural diversity, in relation to water, 4:791–792 Cultural eutrophication, 3:114–115 effects of, 3:115 in ponds, 3:486–487 Cultural media, prepackaged, 1:84 Culturing methods, for detecting biofouling, 1:84 Culvert design, 3:75–78 steps in, 3:77 CulvertMaster software, 3:78 Culvert materials, 3:75–76 Culverts, flow velocities from, 3:77 Cumulative absolute relative error (CARE), 2:335 Cumulative probability plots, 2:20 Cured-in-place lining, 1:878 Cured-in-place pipe (CIPP), 1:802, 878 Current circulation, importance of, 3:320–321 Currents, 4:24–25 effect on oceanic dilution, 4:104–105 methods of determining, 3:321 numerical modeling of, 3:320–325 Curved surfaces, shocks on, 3:241 Curve number (CN) method, 3:343 Cutoffs, levee, 3:289 Cyanide analysis, 2:309–310 maximum contaminant level of, 2:234t, 235t Cyanobacteria, 1:277; 2:21; 5:463. See also Blue- green algae entries blooms of, 2:390 toxic, 2:388 Cyanobacterial toxins, structures of, 3:190f

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CUMULATIVE INDEX

Cyanosis, 2:219 Cyanotoxins, 2:387–388 detection of, 2:389–390 health problems related to, 2:388–389 removal of, 2:390 stability of, 2:390 Cycloalkanes, biodegradation of, 1:693 Cyclones/cyclonic storms, 4:194–196 role in flooding, 3:144–145, 146 Cyclospora, 1:278–279 Cyclosporiasis, 1:180 Cylindrical coordinates, groundwater flow equations in, 5:13–16 Cylindrospermopsins, 2:388, 390 CYP1A induction, 2:109–110 Cytochrome P450 enzymes, 2:107–108 Cytochrome P450 monooxygenase as a bioindicator, 2:110 as an indicator of pollutants in fish, 2:110 as a PCB/dioxin-like compound indicator, 2:106–111 Cytotoxicity, 2:413–414

Dahlberg model, 3:455–456 Daily cover practice, 1:698 Dairy cow diets, improving, 2:573. See also Livestock entries Dairy herd size reduction, 2:572 Damavand watershed, 3:157 Dammed pools, 3:67 Dam removal, 3:387–389 engineering considerations related to, 3:388–389 Dams, 2:567–568 adverse effect of, 3:200 ancient, 3:382 hydropower and, 3:199 in the United States, 2:555 Dangerous Substances Directive (EU), 2:267 Daphnia, 3:268 heavy metals in, 2:423f Daphnia magna, as a test organism, 2:420–421 Daphnids, metal concentrations in, 2:421 Darcy–Buckingham law, 3:249, 250 Darcy equation, 5:656. See also Darcy’s Law

Darcy’s Law, 3:249, 453; 4:486; 5:63–64, 507, 515, 525, 554 Darcy–Weisbach formula, 3:195, 197 Dastgheib and Rockstraw adsorption model, 1:108–109 Data collection/gathering for hydraulic network models, 3:316 lake-related, 3:270–271 in a systems approach, 2:685 Dataloggers, 4:71 Data management, following test results, 2:460 Data management model, 2:622 da Vinci, Leonardo, water experiments by, 4:710–711, 717 DBCP (1,2-dibromo-3chloropropane), 5:358t, 359 DDT, 2:600; 5:338. See also Dichlorodiphenyltrichloroethane (DDT) DDT residues, persistence of, 3:515–516 ‘‘Dead chlorine,’’ 4:418 Dead storage, 1:409 ‘‘Dead zones,’’ 4:25 Debris, marine, 4:38–41 Debris dam pools, 3:68–69 Decaying tropical cyclones, role in flooding, 3:144–145 Decay rate estimation, 2:334 Decentralized Sanitation And Reuse (DESAR), 1:520 Decentralized wastewater treatment, 1:678 Dechlorination, 1:169–170; 2:399 domestic sewage, 1:834 reductive, 2:299–300 Decibel scale, 4:570 Deciles, 4:213–214 Decision making flood-management, 2:679–680 participatory multicriteria, 2:681 precautionary, 2:596 risk-informed, 2:599 systems approach to, 2:685 Decision matrix, 2:679 Decision Support System for Evaluating River Basin Strategies (DESERT), 2:328 Decision support systems (DSSs), 2:328, 535, 589 hydroelectric, 2:621–622 river basin, 2:619–624 for pond aquaculture, 3:375–379

737

spreadsheets in, 2:620–621 value of, 2:623 for water resources management, 2:622–623 Decision variables, in a mathematical model, 2:686–687 Deck officers, 4:763 Declining-rate filters, 1:235 Decomposers, 4:152 Decompression sickness, 4:451 Deep-sea shipping, employment in, 4:765 Deep soil-water movement, 5:471–473 forces that control, 5:471 material properties that affect, 5:471–472 water vapor movement in, 5:472–473 Deep-water corals, 4:32–38 distribution of, 4:34–35 threats to, 4:36–37 types of, 4:33–34 Deepwater habitats, classification of, 3:496–498 Deepwater swamps, 3:172 Deep-well turbine pumps, 3:664–667 efficiency of, 3:665–666 tests of, 3:666–667 Definite Enterprise Portal Resource, 2:669 Defluoridation, 4:434–438 Nalgonda process for, 4:437–438 sorption design and, 4:437 testing or metering, 4:438 treatment principles for, 4:436–437 Defluoridation technology, 4:435–436 Degassing fluxes, 3:206 Degradation. See also Pollutant photodegradation of chemicals, 5:262–263 of chloro-organics and hydrocarbons, 1:688–695 of dyes, 1:794–795 4-nitrophenol, 1:793 Degradative enzymes, 2:43 Degree-day factor, 4:337 Degree day (DD) method, 4:197–199 De Groen’s interception method, 3:237 Dehydration, diseases of, 4:723–724 Dehydration toilets, 1:679 Deicers, chemical, 2:319. See also Ice control

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738

CUMULATIVE INDEX

Delaware River Basin Commission drought indicators, 2:581 Delaware River Basin Compact, 2:585 Deleterious organic chemicals, in urban stormwater runoff, 3:435 Delivery system, 5:291–292 Demand (average water requirement), 1:506–507 Demand curve, 4:606–607 Demand management, 1:204 in the Arab World, 2:472 in Canada, 2:662 Demand reduction systems, 2:515 Demersal fish, 3:126 Demineralization, 1:297–301 in small drinking water systems, 1:459–460 Denaturing gradient gel elecrophoresis (DGGE), community profiling using, 1:643 Denil fish passage facility, 3:530 Denitrification, 1:816, 833–834, 893; 3:696; 4:54, 391 in the activated sludge process, 1:667–669 biological, 5:325–326 controlled, 1:752t in soils, 3:539 Denitrification tank, 1:669 Dense nonaqueous phase liquids (DNAPLs), 3:689; 5:340, 439, 603. See also DNAPL entries modeling of, 5:668–672 physical properties of, 5:91–92 Density. See also Filter density (ρGAC ); High density sludge (HDS) process; Silt density index (SDI) of carbon, 1:96 of sludge, 1:862–863 Density currents, 3:412 Density gradients, as forcing factors, 3:322 Dental fluorosis, 4:435 Denver, Colorado, overdraft in, 5:341 Deoxygenation, 3:445 Department of Heath, Education, and Welfare (HEW), 4:652 de Passa, Jaubert, irrigation history by, 4:736–740 Depletion factor, 3:23 Depth filters, 2:99 Depth filtration, role of colloids and dissolved organics in, 2:99–103

Depth-integrating samplers, 3:398–399 Depth profiling, 5:411 Dermatitis, 1:180 Dermatotoxins, 2:389 Desalinated water cost of, 1:174 quality of, 1:173–174 Desalination, 1:170–174; 2:374, 493–494 concentrate management in, 1:174 defined, 2:542 by electrodialysis, 1:171 membrane, 1:171–173 reverse osmosis, 1:171–173 in the United States, 2:650 Desalination market, future of, 1:309–310 Desalination system, wave-powered, 4:46 Desert cienegas, 3:58 Desert ecology, dew in, 4:200 Desertification, 4:184, 199–200 Desert regions, recharge in, 5:72–76 Design municipal solid waste landfill, 2:168 well, 5:87–91 Design discharge for a series of planes, 3:243–244 for a V-shaped basin, 3:245–246 Design flows, in streams/rivers, 3:81–84 Desorption, 2:70 Desorption kinetic tests, 4:568 Desorptive agents, 2:70 Destruction/destructive technologies in situ, 5:441–443 for odor abatement, 1:762 Detachment mechanisms, 1:231, 233, 244, 246 Detailed water quality models, 2:249 Detection molecular-based, 1:158–162 polymerase chain reaction, 1:160–161 of waterborne radon, 1:51 Detection methods, categories of, 1:90 Detection systems, flood-related, 3:148 Detectors, gas chromatography, 2:307–308 Detention facilities, 3:430–432 Detention ponds, 3:430–431 Detention storage, 3:474

Detention systems, for storm water treatment, 1:868 Detergents, 1:669–674 biodegradation of, 1:672 occurrence in wastewater and sewage sludge, 1:671–672 regulatory standards for, 1:672–673 structure and use of, 1:670–671 toxicity of, 1:672 Deterministic approach, to studying sediment transport, 3:401 Deterministic models, 3:337; 5:303 in eutrophication management, 3:111 of sewer water quality, 3:332–333 Deterministic techniques, 2:332 ‘‘Detrending’’ technique, 3:219, 220 Deuterium, 4:438–440. See also Heavy water analyzing water samples for, 4:439 discovery of, 4:464 in the global water cycle, 4:439 as a tracer, 4:440 Developed countries, household water consumption in, 1:506f Developing countries/nations applying existing technologies to, 1:718–719 centralized and decentralized treatment in, 1:720–721 drinking water in, 1:290; 2:630–633 effluent quality and standards in, 1:720 meeting water needs in, 2:643–645 microirrigation in, 3:627 organic agriculture in, 3:645 remedial criteria for, 5:424 safe drinking water in, 1:22t sanitation services in, 1:23t, 661; 2:630–633 wastewater management for, 1:718–722 wastewater treatment technology in, 1:721 water resources planning and management objectives for, 2:683 water supply in, 2:616–617 wetland values in, 3:492 Development managing urban runoff from, 2:187 patterns of, 2:191

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CUMULATIVE INDEX

surface water chemistry and, 3:442–443 water quality and, 3:501 Dew, 4:200–201 duration of, 4:204 measurements of, 4:202 Dewatering, of sludge, 1:854–855, 863, 865 Dew deserts, 4:201–207 Dew point, 4:207–208, 272 Dew point lapse rate (DPLR), 4:369 Dew precipitation, 4:205–206 Diabetes, dehydration and, 4:725–726 Diadromous fisheries management, 3:127 Diarrheal disease, 1:24; 2:371 from drinking water sources, 1:188 Milwaukee outbreak of, 1:184 Diatomaceous earth filters, 1:175f elements of, 1:176 Diatomaceous earth filtration, 1:175, 228, 232, 247, 458 for drinking water, 1:174–177 feed water quality and performance capabilities in, 1:175 monitoring and operating requirements for, 1:176 for small systems, 1:177 types of, 1:176 Dibromoacetic acid, health effects of, 1:266–267 Dibromoacetonitrile, health effects of, 1:268 Dibromochloroacetic acid, health effects of, 1:267 Dibromochloromethane, health effects of, 1:265 Dibromomethane, health effects of, 1:264–265 Dichloroacetic acid, health effects of, 1:266 Dichloroacetonitrile, health effects of, 1:268 Dichlorodiphenyltrichloroethane (DDT), 3:352, 645. See also DDT entries in Argentina, 3:649 beneficial results of, 3:515 biological magnification of, 3:523 breakdown and disappearance of, 3:516

effects on bird abundance and reproduction, 3:513–526 misidentifications of, 3:522 role in saving forests, 3:522–523 versus PCBs, 3:521–522 Dichloroethene (DCE), 5:581 Dichloromethane (DCM), 2:317 Dieldrin, 3:352 Differential scanning calorimetry (DSC), 4:401 Differential settling, flocculation by, 1:252 Diffused aeration, 1:353, 460 Diffused air aeration, 1:625–626 Diffused air aeration systems. See Fine bubble diffused air aeration systems Diffuse double layer (DDL) model, 2:363–364; 5:567 Diffuse flow springs, 5:239 Diffuse flow systems, 5:237 Diffuse recharge, 5:236 Diffuser membrane materials, 1:628t Diffuser systems, mixed, 1:628–629 Diffusion, 5:278 leaching, 5:261 organic vapor transport via, 5:544 transport by, 5:516–517 Diffusion-based groundwater sampling case study of, 5:458–459 equilibration time for, 5:457–458 membrane materials and construction examples for, 5:456–457 methods of, 5:456 Diffusion kinetics, modeling, 4:567–568 Diffusion porometers, 3:717 Diffusion transport, 3:310 Diffusion wave theory, 3:249 validity of, 3:250–252 Digestion, of biosolids, 1:647–648 Digital data, extraction of drainage networks from, 3:93 Digital elevation models (DEMs), 2:531; 3:28, 29, 64, 93, 157, 162 Digital filters, base flow separation using, 3:27 Digital models, 5:241 Digital terrain modelling (DTM), 2:534 Dike and bleeder flow systems, 3:165 Diked fields, 4:696–697 Dilatant fluids, 5:557

739

Dilution in algal control, 2:4 examples of, 3:84 importance of, 3:78–80 as a means of wastewater disposal, 3:79–80 Dilution equivalents, 4:104 Dilution factor, 4:104 Dilution function, 4:104 Dilution-mixing zones, 3:78–81 Dilution water, 2:382 characteristics of, 2:383 Dimensionless cumulative time-area diagram, 3:64 Dimensionless unit hydrograph (DUH), 3:440–441 Dimethyl sulphide (DMS), 4:88 Dimictic lakes, 3:266 Dinitrophenol, adsorption of, 1:118 1,4-Dioxane, 2:317–318 Dioxin exposure, 3:120 Dioxin-like compounds, as environmental toxicants, 2:106–107 Dipole–dipole array, 5:445 Direct current (DC) technology, 5:118 Direct electron transfer, 2:41 Direct filtration, 1:228–229, 231, 235, 246, 458 Direct liquid monitoring techniques, 5:541–542 Direct potable reuse, 2:611 Direct push water well drilling, 5:106 Direct roughing filtration, 1:238 Direct runoff hydrograph (DRH), 3:440; 4:355, 356 Direct runoff plots, 3:26 Direct search method, 2:332 Direct soil moisture measurement, 3:692 Direct soil monitoring techniques, 5:542 Direct toxicity assessment (DTA), 2:46–48 Direct vadose zone monitoring methods, 5:541–542 Direct wastewater reuse, 1:826 Direct water valuation approaches, 4:607–608 Direct water valuation studies, 2:655 Dirichlet boundary condition, 5:14, 15, 561 Disaggregation, 3:306 stochastic, 3:427–428

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740

CUMULATIVE INDEX

Disaster Assistance Act of 1988, 2:578 Disaster management systems, development and, 3:33–34 Disaster supplies, 2:529 Discharge(s), 5:601 defined, 2:542 effects of seasonal changes in, 3:6 to lakes, 3:281–284 mixing behavior of, 3:81 monitoring, 4:317 in regional flow systems, 5:418 as a watershed function, 3:476–477 Disconnected pools, 3:69 Discontinuities first or second order, 3:248–249 order of, 3:239–241 Discontinuous gullies, 3:184–185 Discontinuous heterogeneity, 5:509 Discontinuous permafrost, 4:306 Discrete particle settling, 1:260 Discrete recharge, 5:236 Discrete sampling, 5:455 Discriminant function analysis (DFA), 2:282 Disease(s). See also Disease outbreaks; Infectious diseases arsenic-caused, 1:1–2 endemic, 1:187–189 flooding-related, 3:161 Saratoga Springs waters treatment of, 4:798–801 soft water and, 4:554 wastewater-associated transmission of, 3:669 water-related, 1:23–25; 2:630–631 Disease outbreaks cholera, 1:283, 290 Cryptosporidium, 2:343–344 detection of, 1:186–187 from distribution system deficiencies, 1:341–342 Escherichia coli, 1:430t; 2:344 Milwaukee, 1:184 short-duration, 1:189 Disease pathogens, waterborne, 2:343 Disease pyramid, 1:185f Disease reporting, 1:185 Disease surveillance definitions, 1:185t improving, 1:190–191 Disease surveillance systems, limitations of, 1:185–186

Disease transmission, low levels of, 1:187 Disease treatment, cost analysis for, 1:427 Dishwashing detergent, antibacteriological properties of, 2:114 Dishwater microbiological content of, 2:114 temperature of, 2:113–114, 115 Dishwater quality, 2:112–115 environmental aspects of, 2:114 Disinfectant application, changing the order of, 2:120 Disinfectant residual concentrations, 2:226t Disinfectants, 1:192–196. See also Disinfection chemistry of, 1:194–195 comparison of, 1:197–199 efficacy of, 1:193–194 against food-poisoning bacteria, 1:604 history of, 1:193 microbial regrowth and, 1:344 purpose of, 1:192–193 testing of, 1:602 toxicology of, 1:195 types of, 1:193 Disinfection, 1:196–204, 380. See also Chlorination entries; Disinfectants; Ultraviolet disinfection achievement of, 1:197 byproduct control for, 1:199 at CSO facilities, 1:786–787 dilution equivalent to, 4:104 in distribution systems, 2:244 of domestic sewage, 1:834 after pipeline repair, 1:890–891 POP behavior during, 1:768 regulations related to, 2:92 of rural drinking water, 1:382–387 of sludge, 1:857–858 for small drinking water systems, 1:457–458 surface water treatment rule compliance technologies for, 1:461t using ozone, 1:354–356 water safety and, 1:196–197 water treatment plant, 1:222, 224–225 well, 1:151 Disinfection byproduct precursors

removal by coagulation, 2:116–117 removal from natural waters, 2:115–117 Disinfection byproducts (DBPs), 1:193, 287, 354, 357; 2:398 aspects of, 2:77f in drinking water, 1:213–215 formation and occurrence of, 2:91–92 health effects of, 1:264–277 importance of, 1:214 minimization of, 2:119–120 regulations related to, 2:92 routes of exposure for, 2:92–93 toxicity estimates for, 1:270, 271t Disinfection Byproducts Rule (DBPR), 2:92 Disinfection practices, alternative, 2:118–119 Disinfection wastewater treatment processes, 1:817 Disk infiltrometers, 5:215, 539 Dispersants, for scale control, 1:548–549 Dispersed-air flotation, 1:685 Dispersion, 5:46 leaching via, 5:26 in transport modeling, 5:331 Dispersion phenomena, 3:78 Dispersivity, 5:274 Dissociation kinetics, of Am-humic colloids, 2:105–106 Dissolution in subsurface systems, 5:416 water–rock interaction and, 5:568–569 Dissolution rate (R), for rock, 5:448–449 Dissolved-air flotation (DAF), 1:487, 685–686, 786; 3:407 Dissolved compounds, removal of, 1:684 Dissolved gases, 4:450–452 in biological systems, 4:451 in groundwater, 4:450–451 in the oceans, 4:451 role in colloid science and biochemistry, 4:451–452 role in surface tension of electrolytes, 4:452 Dissolved humic substances (DHS), 1:872 Dissolved inorganic carbon (DIC), effect on corrosion, 1:8 Dissolved ionics, removal of, 1:54

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CUMULATIVE INDEX

Dissolved iron, 4:498–499 Dissolved matter, transport phenomena of, 2:105. See also Dissolved organic matter (DOM) Dissolved metals, role in fish growth and production, 3:131 Dissolved organic carbon (DOC), 1:360; 2:224; 3:1; 4:399–400. See also DOC entries acidification and, 3:5 analysis with, 1:223 chemical structure of, 4:399 Dissolved organic compounds. See also Dissolved organic carbon (DOC); Dissolved organic matter (DOM); Dissolved organics metals and, 1:727 removal of, 1:54 Dissolved organic matter (DOM), 2:212, 213; 4:533–534. See also Dissolved matter; Dissolved organics Dissolved organics, 2:100 biophysicochemical interactions with filters, 2:100–102 Dissolved oxygen (DO), 2:142; 5:431 depletion of, 4:64 effect on corrosion, 1:8, 153 in ponds, 3:485 production of, 2:275 role in fish growth and production, 3:130 in urban stormwater runoff, 3:434 variation in, 3:84 as a water quality parameter, 2:270 Dissolved oxygen concentration fish health and, 3:130 in tidal streams, 4:130 Dissolved phosphorus (DP), 3:704 Dissolved solids, 4:587 Distillation, 1:380, 813; 2:527 in heavy water production, 4:464 multiple effect, 1:170–171 multistage flash, 1:170 Distilled water, 4:441–442 Distributed solar water heaters, 1:64–65 Distribution, regional, 2:615–616 Distribution line breaks, repairing, 1:400–403 Distribution systems, 2:616 control of nitrification in, 2:226 disinfection in, 2:244 microbial nutrients in, 2:244–245

microbiological quality control in, 2:243–247 research on, 2:511 Distribution system water quality, 1:204–207 contamination prevention and control in, 1:205 corrosion control in, 1:206 deterioration factors in, 1:204 maintenance alternatives for, 1:206 modifications to system operation, 1:205 monitoring and modeling in, 1:207 operational factors in, 1:205 structural factors in, 1:204–205 treatment practice in, 1:206 water quality factors in, 1:205 District metering areas (DMA), 1:202 Ditches in industrial areas, 3:87 research on, 3:88–90 Diversion pumped storage development, 3:201 Diversion structures, 2:568; 3:151–152 Diversity measures, 3:37 DNA shotgun sequencing of, 2:63 water and, 4:458, 512 DNA arrays, 2:60 DNA chip technology, 1:161–162. See also DNA microarrays DNA damage, bacterial biosensors for detecting, 2:455 DNA microarrays, in community analysis, 1:644 DNAPL migration, effect of, 5:670–671 DNAPL migration modeling, adaptive modified sequential method of, 5:669–670 DNA probes, in Salmonella, 2:337–338 DNA stable isotope probing, 1:645 DOC exchange mechanism, 1:326f. See also Dissolved organic carbon (DOC) DOC removal, 1:225 ion exchange for, 1:325–330 Dolomite, 4:413 ‘‘Dolphin safe’’ tuna fishing, 2:636 Domain membrane process, 1:139–141 Dombes basin, 4:697

741

Domestic sector, water conservation in, 2:496–497 Domestic sewage, 1:828, 830–835 characteristics of, 1:830–832 treatment technology for, 1:832–834 as a source of cultural eutrophication, 3:114–115 as water pollution, 4:97 Domestic solar water heaters, 1:63–67 distributed solar water heater, 1:64–65 integrated collector/storage solar water heater, 1:63–64 Domestic wastewater constructed wetlands for, 1:896 disposal of, 2:182 Domestic wastewater discharges, control of algal nutrients in, 3:110 Domestic water quality of, 2:371 radon in, 4:542–543 risk assessment of radon in, 4:543–545 Domestic water supply public-private partnerships and, 1:42–51 eutrophication in, 3:107 Domestic water usage, 2:371, 542 average daily, 1:506f in India, 2:565 in the United States, 2:652 Dominant processes concept (DPC), 3:229–230 Dong Nai–Saigon Rivers, wastewater discharge into, 2:552–553 Donnan membrane process (DMP), 1:139, 140f Doppler radar, 4:354 precipitation estimates via, 4:307–308 Dose-response data, 2:381 Dose response of mussels to chlorine, 2:401–406 Double check valve, 1:156 Double-composite landfill liner, 2:165 Double layer compression, 4:425 ‘‘Double low water,’’ 4:24 Downflow roughing filters in series (DRFS), 1:241 Down-hole televising log, 5:153–154 Downstream fining, 3:420

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742

CUMULATIVE INDEX

Downward vapor transport, 5:551–552 Draft from groundwater (Tp ), 5:168 Drainage, 1:498–499 inadequate, 3:603 lysimeters, 5:488 road runoff, 3:498 roof runoff, 3:498–499 status and scope of, 5:99 subsurface, 3:451–454; 5:94–100 vertical, 5:98 Drainage and leachate collection/recirculation/ treatment, for landfills, 1:698–699 Drainage basins, 2:543 bioremediation in, 2:359 climatic characteristics of, 3:31 rock and soil characteristics of, 3:29–30 sediment movement in, 3:185 topographic characteristics of, 3:29 vegetation and land use characteristics of, 3:30–31 Drainage channel, slope of, 3:31 Drainage composition, Horton’s laws of, 3:32 Drainage density, 3:94 of a channel network, 3:32 Drainage design, role of evapotranspiration in, 5:96–97 Drainage ditches, 3:87–92 Drainage divides, 2:657 Drainage layers, levee, 3:290 Drainage measurements, using nonweighing lysimeters, 5:488 Drainage models, urban, 1:125 Drainage networks, 3:93–95, 438 analysis of composition of, 3:32 extraction from digital data, 3:93 statistical properties of, 3:93–94 Drainage works, controversy over, 3:88 Drains, field measurements in, 3:338 DRASTIC assessment methodology, 1:73 DRASTIC ground water vulnerability map, 5:58, 563 DRASTIC index method, 5:57, 358, 595 Drawdown, 5:101–102, 103 defined, 2:543 Drawdown information, importance of, 5:104 Drawdown zone, 3:206

Dredged material acute sediment toxicity tests for, 2:351 characterization of, 2:351–352, 354t disposal at sea, 4:148 uncertainties associated with testing, 2:353t Dredged sediment regulating disposal of, 2:125–126 water quality aspects of managing, 2:122–127 Dredged sites, use of caged animals at, 2:351–352 Dredging, hydraulic, 2:122 Dredging/barge disposal, mechanical, 2:122 Dredging/disposal operations, impact of, 2:122–125 Dresden, Germany, biomanipulation trials in, 2:56t Dried food, nitrite content of, 1:33t Drift currents, 4:24 Drifts, as groundwater tracers, 5:504–505 Drilled wells, 5:572 versus qanats, 5:486 Drilling, gas hydrate sampling through, 4:61 Drilling fluids, specific gravity of, 5:474–475 Drilling sites, Lake Baikal, 3:21–22 Drilling techniques, 5:438 water-jetting, 5:234–235 Drinking water. See also Public health protection aquatic macrophytes as biomonitors of, 2:66 detecting arsenic in, 1:2 in developing countries, 1:290; 2:630–633 diatomaceous earth filtration for, 1:174–177 disinfecting, 1:196–197 disinfection byproducts in, 1:213–215 disinfection byproduct standards for, 2:92t effects of surface water pollution on, 3:445, 446–447t guidelines, 5:324t microbial contaminants and biotoxins in, 1:277–281 microbes in, 2:243 microbiological quality of, 1:225

nitrate limits for, 1:33t nitrates in, 2:219–220; 3:694; 5:198–199, 323 nutrient limitations of bacterial growth in, 2:245 organic compounds in, 2:372–373 pollutants in, 5:262 radioactive contamination in, 1:803 radon in, 4:542 reducing radon in, 1:51–52 removal of arsenic from, 1:2–3 Salmonella detection and monitoring in, 2:337–340 security of, 1:434 toxic chemicals in, 2:371–372 types of organic carbon in, 2:224–225 Drinking Water Contaminant Candidate List, 1:532; 4:678 Drinking water distribution systems etiological agents of outbreaks related to, 1:342 microbial occurrence in, 1:342–344 microbial regrowth in, 1:344–345 microbiological concerns of, 1:341–346 Drinking water equivalent level (DWEL), 4:397 Drinking water filtration, 1:227–230 cartridge, 1:229–230 diatomaceous earth, 1:228 direct, 1:228–229 membrane, 1:229 multistage, 1:237–238 packaged, 1:229 regulatory requirements for, 1:233 slow sand, 1:228 Drinking water protection, EPA Pretreatment Program and, 1:799 Drinking water purification, Br− /DOC changes in, 2:75–76 Drinking water quality, 1:131 Australian framework for managing, 1:428t causes of failure of, 1:221–227 Drinking water quality standards (DWQS). See also Drinking water standards compliance and supervision related to, 1:480–481 future of, 1:481 history of, 1:479–480 setting, 1:480 in the United States, 1:476–481

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CUMULATIVE INDEX

Drinking water regulations, history of, 2:194–198 Drinking water regulations, risk assessments in crafting, 1:422–429 Drinking water standards, 1:2, 293; 2:345–347. See also Drinking water quality standards (DWQS) analytical methods for, 1:297 chemical, 1:529–533 national primary, 2:373t Drinking Water State Revolving Fund (DWSRF), 1:445 Drinking water storage facilities, 1:408–411 construction materials for, 1:410 daily volume use, 1:409 requirements for, 1:408–409 storage reservoir location, 1:410 storage tank shape and volume, 1:410 Drinking water systems corrosion control in, 1:5–12 infrastructure for, 1:883 Drinking Water Systems Center, 1:91 Drinking water treatment household, 1:67–70 MIEX resin in, 1:327–328 ozone–activated carbon, 1:357 Drip irrigation, 2:543; 3:582, 593 in India, 3:625 Dripper tube, 3:623 Driven wells, 5:572 Drop-size distribution rain simulators, 4:331 Drought(s), 4:208–209 climatology and, 4:187 collective action against, 2:579 costs of, 2:513, 579–580 effects of, 4:209 in India, 2:567 internal, 4:725 intracellular, 4:723 legacy of, 2:513 in the Nile Basin, 2:590–591 in the 1930s, 2:511–514 obstacles to planning for, 2:578–579 planning tools for, 2:580 political considerations related to, 2:580 public notification of, 2:583 recovering from, 2:512–513 traditional government approach to, 2:577

water resources management for, 2:576–586 water use curtailment during, 2:583 water-user compliance monitoring during, 2:583 West African Sahel, 4:184 Drought-contingency-plan phasing criteria, 2:582t Drought escape, 3:719 Drought indicators, identifying, 2:580–583 Drought indices, 4:209–214 Crop Moisture Index, 4:212 deciles, 4:213–214 Palmer Drought Severity Index, 4:211–212 percent of normal calculation, 4:209–210 Reclamation Drought Index, 4:213 Standardized Precipitation Index, 4:210–211 Surface Water Supply Index, 4:212–213 Drought management, 2:515–516, 585–586 base flow recession in, 3:26 planning in, 2:514–515 Drought planning, 2:577 specificity of, 2:578 Drought-planning authority, designating, 2:583 Drought programs, federal, 2:578 Drought-related planning and management activities, state, 2:583–585 Drought relief programs, 2:512 Drought-severity index, 2:581 Drought surcharge, 2:583 Drought tolerance, 3:719 Dry adiabatic lapse rate (DALR), 4:368, 369 Dry arm discontinuous valley-floor gully, 3:184f Dry barriers, 5:2–3 Dry-bulb temperature, 4:224 Dry electrolytic conductivity detectors (DELCD), 2:308 Dry environments, disturbance of, 2:516. See also Arid countries/lands Drying, of sludge, 1:860 Drying beds, sludge, 1:854–855 Dry-land agriculture, water conservation in, 2:496

743

Dry monsoons, 4:304 Dry toilets, 1:679 Dry tomb landfilling, 2:163–164 Dual-flush device, 2:665 Dual-nutrient removal, biological, 1:816, 834 Dubinin–Astakhov (DA) adsorption isotherm equation, 4:406 Dublin principles, 2:574 Dublin Statement, 4:611 Dug wells, 3:594; 5:571–572 Dumped wastes, interactions with seawater, 4:148 Duplex PCR, 2:338 Dupuit–Thiem method, 5:492 Durges, Susan, 4:767 Dye introduction trenches (DITs), 5:109 Dyes degradation of, 1:794–795 as hydrological tracers, 3:95–101 sorption to subsurface media, 3:98 testing of, 1:885–886 Dye tracers characteristics of, 3:95 limitations in using, 3:98 measurements of, 3:83f QSAR approach versus screening for selecting, 3:98–101 selecting for specific uses, 3:98–101 structure of, 3:97f for surface water, groundwater, and vadose zone, 3:96–98 Dye tracing, 5:240–241 groundwater, 5:107–111 at waste disposal sites, 5:110 Dynamic data, 2:622 Dynamic modeling, 1:132; 2:272 Dynamic pressure, 5:652 Dynamic roughing filters (DyRF), 1:237, 240 Dynamic roughing filtration, 1:239 Dynamics, reservoir, 3:259–260 Dynamics and instabilities, 4:449 Dynamic-state modeling, 1:133 Dynamic wastewater models, 1:731–732, 733–735

Early civilizations, water in, 4:726–728, 746 Early-closure flush device, 2:665 ‘‘Early warning’’ biomarkers, 2:429 Early warning systems, 3:33

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744

CUMULATIVE INDEX

Earth heat balance of, 4:92 origin of water on, 4:283 water content of, 4:191–192 water resource renewal periods of, 4:278t Earth energy budget, balancing, 4:169 Earth Observing System (EOS), 4:351. See also Aqua earth observing system (EOS) Earth Observing System Data and Information System (EOSDIS), 4:216 Earthquake dewatering, 5:478 Earthquakes, 5:111–115 hydrogeologic responses to, 5:113–114 severity, 5:478t stream, spring, seep, and lake responses to, 5:112–113 water well responses to, 5:111–112 Earth Summits, 2:624, 628 Earth system science, 4:214–215 Earth tides, 5:498 East Asian Seas, dumping in, 4:145–146 Easterly Waves, 4:305 Eastern states, protection of in-stream values, 4:662–663 East Patchogue, New York, plume diving in, 5:80–81 ECa -directed sampling designs, 5:467. See also Apparent soil electrical conductivity (ECa ) ECa -directed soil sampling survey, 5:467 ECa field survey, steps in, 5:469t ECa measurements, limitations and precautions concerning, 5:467–470 Echolocation, 4:571 Echovirus infections, 1:179 E climates, 4:258–259 Ecohydrology, 2:368; 3:292; 4:267 Ecological benefit. See Net ecological benefit concept Ecological effects assessment for water-limited environments, 2:516–518 of pharmaceutical products, 1:373, 376–377 Ecological health, 2:182 human activities as stressors on, 2:625

Ecological impacts, of water transfers, 4:686 Ecological processes, stock assessments and, 4:57 Ecological research, on agricultural drainage ditches, 3:88t Ecological risk assessment (ERA), 3:54 Ecological Risk Assessment Guidance for Superfund (ERAGS), 2:517 Ecological sanitation (EcoSan), 1:675–676. See also EcoSan systems Ecological surveys, 2:30 Ecological wastewater management, 1:675–681 treatment systems in, 1:677–680 Ecological watershed functions, 3:477–478 Economic activity, in India, 2:564 Economic growth, American, 2:499 Economic planning (EP) model, 2:520, 521 Economic productivity, water resources development and, 3:33 Economics. See also Cost(s); Financial performance; Global economy; Investment; Pricing; Stock price performance; Water companies; Water economic analysis; Water prices; Water utilities concepts in, 4:606–607 during the Great Depression, 2:511 of industrial water demands, 1:549–553 of residential water demands, 1:12–16 of water quality, 2:127–135 of water resource allocation, 1:215–218 of water resource valuation, 2:653–654 Economic value of water, 4:605–612 Economic theory, of industrial input demands, 1:550 Economies of scale, public water supply and, 1:501 Ecoregions, environmental management of, 2:667–668 EcoSan systems, 1:675, 676, 680–681 advantages of, 1:680–681 Ecosystem processes, using to treat mine wastewater, 1:897–900

Ecosystems. See also Sensitive ecosystems balanced, 2:667 coral reef, 4:114 effect of water hyacinth on, 3:481 effluent-driven, 2:476–478 Hawaiian, 4:802–803 lake, 3:267–269, 272–274 managing fishery-related, 3:128 sustainable management of, 2:636–637 variability in, 3:124 water and soil conservation, 4:772–780 Ecotoxicogenomic research, developing tools for, 2:62–63 Ecotoxicological assessment, of pharmaceuticals, 1:376 Ecotoxicological effects, of lead, 2:433–435 Ecotoxicological sediment assessment, 2:383 Ecotoxicological testing, 4:42 Ecotoxicology, purpose of, 2:379 Eddy flux method, 3:736 Eddy pools, 3:67 Edgerton, Harold, 4:768 Edible aquatic organisms, bioaccumulation of hazardous chemicals in, 3:435 EDTA method, 4:453 Education, 1:148. See also Public education; Water education strategies CERES-related, 4:170 as a water conservation measure Educational programs, 2:497 Effective contact time, 1:103 Effective porosity, 5:184 analysis, 5:186 Effective rainfall (ER), 4:355, 356, 357 Effective rainfall hyetograph (ERH), 4:355, 356 Effective sediment erosion intensity per unit depth (ESEI), 4:359 Effective viscosity, 5:659 ‘‘Efficient water use,’’ 2:491 Effluent(s). See also Whole effluent toxicity controls defined, 2:543 diversion of, 2:3 industrial, 2:496 mining, 1:609 pond, 3:541–542

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CUMULATIVE INDEX

runoff, 2:516 technetium-laden, 4:580 trading, 2:134 treating, 1:682f Effluent discharges, 2:373 to dry riverbeds, 2:476–477 national primary drinking water standards, 2:373t Effluent-driven ecosystems attainable uses in, 2:476–477 flow regime modification in, 2:477–478 net ecological benefit in, 2:477 water regulation in, 2:478 Effluent limitations, 1:755–760; 4:656–657, 664–665 Clean Water Act and, 1:755–756 by industrial category, 1:757 statutes concerning, 4:664–665 storm water, 1:759 by substance, 1:757 water quality-based, 1:759 under the Clean Water Act, 4:596 Effluent quality, in developing countries, 1:720 Effluent-receiving water systems, pharmaceutical detection in, 1:376 Effluent remediation, for mines, 1:610–612 Effluent treatment of algal populations, 2:3 for flow-through aquaculture systems, 3:543 gully pot, 3:499 Effluent water regulations, in arid lands, 2:475–478 Eggshell thinning, 3:514–515 DDT and, 3:520–521 Egypt irrigation in, 4:739 wastewater applications in, 1:634 water symbolism in, 4:785–786 Egyptian water clocks, 4:705 Egypt-Sudan water dispute, 2:591–592 Eh , 2:464–469 application of, 2:467–468 difficulty in using, 2:467 interpreting, 2:467 measurement of, 2:466–467 Eh/pH conditions, changes in, 5:422–423 Elastic deformation, 5:482 Elastic storage coefficient, 5:482

Electrical charge, 5:184 Electrical conductivity (EC), 3:682; 4:429–433; 5:184, 195 alternative measurement technologies for, 4:432 measurement of, 4:430 of soil solution extracts, 3:673–674 temperature effects related to, 4:430–432 total dissolved solids and, 4:432 Electrical current, 4:442 effect on corrosion, 1:8 Electrical geophysical methods, 5:146 Electrical logs, 5:151–152 Electrical resistance blocks, 5:541 Electrical resistivity (ER), 3:675 Electrical resistivity method, 5:146 Electrical sounding process, 5:446 Electrical tape method, 5:101 Electrical wastewater treatment technologies, 1:812 Electric fields, 4:443 Electric generating plants air emission contaminants from, 1:554–555 contaminant release by, 1:553–558 effects of contaminants from, 1:556 history of, 1:553–554 solid waste and water contaminants from, 1:555–556 Electricity as a fluid, 4:442–443 hydropower-supplied, 3:199 world generation of, 3:199t Electricity generation/production, water use in, 1:552, 561 risk analysis of buried wastes from, 5:448–451 Electric pump motors, 3:380 Electric utilities, wastewater treatment facilities at, 1:850–853 Electrobiochemical oxidation, 5:122 Electrobiochemical processes, engineered, 5:116–118 Electrochemical corrosion measurement, 1:9 Electrochemical oxidation, 5:122 Electrochemical processes, groundwater remediation via, 5:283–284 Electrochemical reactions, for groundwater contaminants, 5:283–284 Electrochemical regeneration, 1:917

745

Electrochemical technology, problems with, 5:284 Electrode configurations, for geoelectrical operations, 5:445 Electrodialysis (ED), 1:219, 297, 300–301, 459–460, 812 for arsenic removal, 1:638 bonding agent regeneration using, 1:590f desalination by, 1:171 Electrodialysis reversal (EDR), 1:218–219, 301 Electrodialysis reversal system, 1:218–221 Electroflotation, 1:687 Electrokinetic enhanced soil bioventing, 5:121–122 Electrokinetic field surveys, 5:119–120 Electrokinetic gradient, 5:184, 186 Electrokinetic parameter testing, 5:186 Electrokinetic processes, 5:118 Electrokinetic remediation technologies, 5:435 Electrokinetic systems, components of, 5:120–121 Electrokinetic treatment, 5:329–330 Electrolysis, 1:812 in heavy water production, 4:464 of MtBE and benzene, 5:122–123 Electrolyte surface tension, role of dissolved gases in, 4:452 Electromagnetic geophysical methods, 5:149–151 Electromagnetic induction (EMI), 3:676; 5:302 Electromagnetic surveys, riverine, 5:679–680 Electromigration, 5:284 Electron acceptors, 1:690, 691 Electron activity. See pe Electron beam irradiation, at CSO facilities, 1:786–787 Electron capture detector (ECD), 2:307–308 ‘‘Electronic circuit-rider,’’ 1:450 Electronic leak testing, 1:887 Electronic nose environmental applications for, 2:283 future of, 2:283–284 for odor monitoring, 2:281–284 user needs for, 2:281–283 Electron transfer (ETr) assay, 2:376

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746

CUMULATIVE INDEX

Electron transfer reaction (ETR) assay, 2:279, 280 Electro-optical wave propagation, 4:296 Electroosmosis technology, 5:284 Electroplating industry, impact on surface water quality, 3:374 Electrospray ionization mass spectrometry (ESI MS), analysis of aqueous solutions using, 4:443–445 Electrospray ionization MS (ESI-MS) quadrupole, 2:61 Elemental mode, 4:445 Elements, water symbolism and, 4:786 Elevation effect, 5:230 Elevation head, 5:171 El NiZo phenomenon, 4:22, 43–44, 91, 184, 185 El NiZo/Southern Oscillation (ENSO), 4:43 index, 4:174 prediction of, 4:23 Eluviation, 5:260 Embankment design, levee, 3:287–288 Embankments, seepage through, 3:290 Embankment slopes, levee, 3:288 Embankment zoning, levee, 3:290 Emergencies, food and water in, 2:526–529 ‘‘Emergency areas’’ policy, 2:526 Emergency line break repairs, 1:401–402 Emergency outdoor water sources, 2:527 Emergency response, coordinating actions for, 1:871 Emergency response plans (ERPs), 1:528; 2:348 Emergency storage, 1:409 Emergency supplies, 2:529 Emergency water purification, 2:527 Emergent aquatic plants, 3:743 Emerging waterborne infectious diseases, 1:177–183 pathogens responsible for, 1:178 specific, 1:178–182 Emission(s), 4:321 greenhouse gas, 3:180–183 Emitters clogging of, 3:618, 626 microirrigation, 3:615–616

Empirical area reduction method, 3:410 Empirical infiltration models, 4:486–487 Empirical methods, for computing time of concentration, 3:471 Empirical models, 3:328, 343 in industrial water demand economics, 1:550–552 Employees, security as a priority for, 1:870–871 Empty bed contact time (EBCT), 1:103, 351, 352, 579 Enabling environment, in the integrated water resources management framework, 2:575–576 Enclosed recirculating systems, 1:558–559 Endangered Species Act (ESA), 4:664 Endemic disease, 1:187–189 Endemic fluorosis, 4:435 Endemic stream animals, Hawaiian Islands, 4:803–804 Endocrine-disrupting compounds (EDC), 1:819 Endocrine disruption (ED), 3:54 Endocrine system, effects of lead on, 2:436 ‘‘End of pipe’’ drainage solutions, 3:498 Endosulfan, 3:646 Endpoint selection in environmental risk assessment, 2:459 for sediment toxicity tests, 2:459 Energy. See also Renewable energies conservation of, 4:264 defined, 5:170 weather and, 4:353–354 Energy balance (EB), 3:561–562 global average, 4:179–180 remotely sensed, 3:562–563 satellite, 3:564 Energy balance equation, 3:535 Energy balance methods, 3:572 Energy budget, balancing, 4:169 Energy characteristics, of rain, 4:331 Energy costs, pumping station, 3:380–381 Energy dissipation, 1:558–560 using enclosed recirculating systems, 1:558–559 using once through systems, 1:559–560

using open recirculating systems, 1:559 Energy equation, 3:197 Energy flow, metabolism and, 5:528–529 Energy industry materials, water use for, 1:562–563 Energy–mass–momentum balances, 5:558 Energy pricing, in India, 2:557 Energy production backup energy and electricity for, 1:563–564 indirect water use for, 1:563 iron-reducing bacteria in, 2:151 material requirements for, 1:562 sediment transport and, 3:508–509 water supply for, 2:618 water use in, 1:560–565 Energy use, for evapotranspiration, 4:228 Enforcement agencies, federal, 4:650t Engineered carbons, 2:82–83, 85 Engineered systems, biochemical oxygen demand in, 1:639–640 Engineering risk index, 2:675 Engineering techniques, ditch-related, 3:88 Engineering works, increasing water supply via, 2:490 English Reasonable Use Rule, 4:628 Enhanced Stream Water Quality Model (QUAL2E), 2:326–327, 329–330, 334 Enhanced biodegradation, of vinyl chloride, 5:638 Enhanced bioremediation, 5:319–322, 424 Entamoeba, 1:279 Enteric microorganisms, 1:821 Enteric viruses, 1:821 Enteritis astrovirus, 1:179 calicivirus, 1:179 Enterococcus group, as indicator organisms, 2:293 Enterohemorrhagic Escherichia coli (EHEC), 1:180–181; 2:138. See also Hemorrhagic Escherichia coli outbreak Enteroviruses, 1:70, 178–179, 279, 522 Entropy defined, 4:218 as a modeling tool, 4:220

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CUMULATIVE INDEX

Entropy-spectral analysis, for flow forecasting, 4:221 Entropy theory, for hydrologic modeling, 4:217–223 Environment(s) anthropogenic impacts on, 5:62 benefits of water recycling to, 2:610–613 contentious issues regarding, 4:717–718 lead movement in, 2:433 pesticide chemistry in, 3:647–651 pharmaceuticals in, 1:372–373 role of small water reservoirs in, 1:403–408 sources of heavy metals in, 5:276–277 water-limited, 2:516–518 Environmental Assessment, Phase I, 5:437 Environmental Assessment (EA) reports, 1:377–378 Environmental contaminants bioaccumulation of, 2:428 using fish cells in toxicological evaluation of, 3:115–118 Environmental Control and Life Support System (ECLSS), 4:572 Environmental Defense Fund (EDF), 3:513, 514, 522 epidemiologic study, 1:289–290 Environmental economics, 2:127 Environmental exposure, to cadmium, 5:614 Environmental flow regimes data required for, 3:167 minimum, 3:166–168 recommendations related to, 3:167 Environmental flows, 3:106–107 objectives of, 3:167 principles of, 3:106–107 Environmental Fluid Dynamics Code (EFDC) model, 2:256 Environmental groundwater tracers, 5:502–504 Environmental health, weather modification and, 4:188 Environmental health programs, 1:799–800 Environmental Hydroscience Discipline Group, 3:231 Environmental impact(s) of carbonate, 4:416 of fish farms, 3:579–580

of flow-through aquaculture systems, 3:542–543 integrating into water resources planning, 2:520–522 of iron in groundwater, 5:608–610 of landfills, 1:696–697 of recirculating aquaculture systems, 3:544–545 tools to evaluate, 2:516–517 of weed control, 3:744 Environmental impact assessment (EIA) model, 2:520 Environmental impact factors (EIF), 2:520–521 Environmental isotopes applications of, 5:232–233 in contaminant hydrogeology, 5:217–221 fractionation of, 4:501 as groundwater tracers, 5:502 in hydrogeology, 5:227–234 practical applications of, 5:221–224 stable, 5:228t Environmental justice, 2:668 Environmental lapse rate (ELR), 4:370 Environmental management, of ecoregions, 2:667–668 Environmental media, arsenic concentrations in, 1:82t Environmental meteorologists, 4:328 Environmental monitoring biosensors as tools for, 2:455 considerations for, 2:263 using submitochondrial particle assay, 2:378 Environmental monitoring programs, data from, 4:113 Environmental photochemistry, in surface waters, 4:529–535 Environmental pollution, from electric generating facilities, 1:553–558 Environmental problems, worldwide, 1:586 Environmental projects, groundwater sampling techniques for, 5:454–456 Environmental Protection Agency (EPA), 1:5; 4:379, 691. See also EPA entries; United States Environmental Protection Agency (USEPA); U.S. EPA Subtitle D dry tomb landfilling

747

coral reef protection by, 4:115–116 criteria for toxics, 4:598–599 lake protection standards, 3:270–271 National Drinking Water Regulations and, 1:480–481 National Primary Drinking Water Standards, 1:478t nonpoint source control and, 2:185 permit programs, 4:666 pharmaceutical release and, 1:377–378 primary and secondary water quality standards of, 2:373 priority pollutants list, 2:19; 4:599 state reporting to, 2:315 water reuse guidelines of, 1:806t water security and, 1:436 Environmental Protection Council, Ho Chi Minh City, 2:553 Environmental quality aquatic-environment assessment of, 2:94–98 standards for, 2:46 Environmental regulations, for fish farms, 3:580–581 Environmental remediation technologies, 3:364 Environmental resources management, 3:492–493 Environmental responsibility, new age of, 4:730 Environmental risk assessment processes (ERAs), 2:459 Environmental samples, of vinyl chloride, 5:637 Environmental science, precautionary principle regarding, 2:599–601 Environmental studies, isotopes used in, 5:218t Environmental toxicants, 2:106–107 Environmental tracer recharge measurement, 5:74–75 Environmental tracers, 5:65 Environmental water quality, evaluation of, 2:450 Environmental water requirements (EWR), 3:166 methods of determining, 3:167 Environmental weed control, 3:747 Environment Canada (EC), 2:321, 459; 3:633, 635 Enzymatic biodegradation mechanisms, 2:42–43

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748

CUMULATIVE INDEX

Enzyme assays, 2:110 Enzyme-linked immunosorbent assay (ELISA), 1:90, 160; 2:139, 337, 390 Eosin, in groundwater tracing, 5:506 EPA National Pretreatment Program, 1:798–801. See also Environmental Protection Agency (EPA) environmental/public health programs and, 1:799–800 future of, 1:800–801 partnerships and, 1:798–799 EPA priority pollutants, 2:305t. See also Environmental Protection Agency (EPA) EPA Regional Ground Water Forum, 5:578. See also USEPA codes EPA Stormwater Management Model (SWMM), 3:256, 337 EPA Superfund, 1:434; 2:517. See also Superfund sites EPA toxic constituent manuals, 2:381 EPDM membranes, 1:627–628 Ephemeral rivers, sand abstraction from, 3:414–415 Ephemeral streams, incisement of, 3:57 Ephemeral waters, 2:475 Epidemics, nineteenth-century, 4:729 Epidemiological studies, 1:187–188 lead-related, 2:438 Epidemiologic data, use of, 1:423 Epidemiology Cryptosporidium, 1:164–165 Escherichia coli O157:H7, 2:137–138 giardiasis, 1:258–259 Epikarst, 5:108–109 Epikarstic dye introduction points (EDIPs), 5:109 Epikarstic zone, 5:236–237, 243 Epilimnetic hypoxia, 4:65 Episodic acidification, 3:5–7 biological importance of, 3:7 causes of, 3:5 modeling of, 3:5–6 regional differences in, 3:6 Epoxy resin pipe linings, 1:879, 880–881 EQ3/6 program, 5:141 Equation of continuity, 5:558–559, 651 Equation of motion, 5:559–561, 651–652

Equalization, 1:814–815 domestic sewage, 1:832 of landfill pollutant loadings, 1:705 storage tanks and, 1:448 Equalizing storage, 1:409 Equations, water quality model, 2:273–278 Equations of change; 5:558 in laminar flow systems, 5:651 Equilibrium kinetic modeling and, 4:565–567 reactive transport models, 5:519 Equilibrium models, 5:414 Equilibrium analysis, 2:71 Equilibrium discharge (Qe ), 3:63 Equilibrium freezing point, 4:585 Equilibrium phase partitioning, 5:549–550 Equilibrium sorption models, 1:368 Equilibrium-tension lysimeters, 5:489 Equilibrium time (t), 3:298–299 Equilibrium vapor pressure, 4:363, 365 Equipment, rain-simulator, 4:330–332 Equipotential line, 5:419 Equipotentials, 5:182 Equity, water quality and, 2:131–132 Equivalent atmospheric concentration (EAC), 4:421 Eroded sediment, deposition of, 3:567 Erosion, 2:543; 5:125. See also Erosion control at construction sites, 1:537–538 gully, 3:183–188 river, 2:657–658 sediment production by, 3:31 Erosion control, 3:697 agronomic methods of, 3:568–569 mechanical methods of, 3:567–568 Erosion cycles, 3:184 Erosion–Productivity Impact Calculator (EPIC), 2:251 Escherichia coli, 1:277–278; 2:21, 22 lux-gene-carrying, 2:174 outbreaks of, 1:341, 430t waterborne transmission of, 1:429–431 Escherichia coli O157:H7, 2:136–142, 344 clinical features and treatment for, 2:136–137 diagnostic procedures for, 2:139–140

epidemiology of, 2:137–138 history of, 2:136 monitoring in water, 2:140 pathogenesis of, 2:137 susceptibility to chlorination, 2:138–139 transmission routes of, 2:138 waterborne transmission of, 2:138 Espy, James Pollard, 4:353 Estuaries, 2:543; 4:25–26, 49–53 budgetary models for, 4:52–53 coastal, 3:72 as disposal sites, 4:50 importance of, 4:49–50 physicochemical processes in, 4:50–51 role of nutrients in, 4:51–52 water quality goals for, 4:54–55 Estuarine coastal wetlands, 3:72 Estuarine microalgal sediment toxicity tests, 4:120–124 Estuarine waters, metals in, 4:29 Ethanol, 3:546 soil vapor concentration of, 5:553 Ethics, in forensic hydrogeology, 3:170 Ethnic community, protecting, 2:667–668 Ethnopolitics, of hydro-borders, 4:681–683 Ethylenediaminetriacetate (EDTA), 1:779 EU Freshwater Fish Directive, 2:267 Eukarya, 2:313 EU Landfill Directive, 1:695 Eulerian coordinate system, 5:558 Eulerian models, 1:133 Euler’s equations, 4:352 EU Nitrate Directive, 3:637 Euphotic zone, 3:265, 267 Europe fish ponds and fish production in, 4:721t land drainage in, 3:490 European Ecological Network (ECONET), 1:404 European Environmental Agency, 3:292 European Food Safety Authority, fish advisories, 3:119 European policy, precautionary principle and, 2:597 European Union (EU), 1:407. See also EU entries flooding directives, 3:162

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CUMULATIVE INDEX

pharmaceutical guidelines of, 1:377 wastewater treatment within, 1:844 water quality standards, 2:267–268 European Union-Water Framework Directive (WFD), 2:638, 639, 640, 641 Eutrophication, 2:2, 181, 269; 3:107–114, 704. See also Cultural eutrophication ammonia and, 4:392 controlling, 3:109 health implication of, 5:334 in Indian lakes, 3:451 in Indian rivers, 3:449–451 lake, 3:283 relation to organic loading, 2:142–143 in surface waters, 3:695, 696, 702 Eutrophication impacts, on water quality, 3:107–109 Eutrophic water bodies, algal control in, 2:2–7 Evacuated-tube solar collector, 1:66 Evaluative criteria, in a systems approach, 2:685–686 Evaporation, 1:812–813; 2:543; 3:192–193; 4:192, 223–226 agricultural impact of, 4:226 average estimated, 4:226t crop, 3:720–721 determining from interception, 3:237–238 estimating, 4:2 in the hydrologic cycle, 4:276 hydrologic impacts of, 4:225–226 mathematical estimates of, 4:225 measurement and estimation of, 4:224–225 physical controls on, 4:223–224 in the water cycle, 4:196 Evaporation/condensation, latent heat of, 3:193 Evaporative rates, mean daily, 4:260 Evaporite mineralogy, 5:52–53 Evaporites, 5:53 Evapotranspiration, 2:543; 3:30, 171, 222, 225; 4:226–229 in arid regions, 5:410–411 concentration effect of, 4:374 crop, 3:557 estimating, 4:227–228 importance of, 4:226–227 magnitude of, 4:229

measuring, 4:227 modeling of, 4:259 remote sensing of, 4:321–322 requirements for, 4:228–229 role in drainage design, 5:96–97 tomato-crop, 3:576–578 in the vadose zone, 5:534 versus transpiration, 3:733 Evapotranspiration estimates, 5:78–80 Chicago Station, 5:79t reference, 3:573t Evapotranspiration from groundwater (Et ), 5:168 Event-based watershed response, modeling, 3:343 Evolution, of water, 4:715–718 Evolutionary algorithms (EAs), 2:333 EXAFS spectroscopy method, 2:207, 208 Excavation, 1:402, 887 levee, 3:288 Excess fishing capacity, 3:127 Excess rainfall intensity (E), 3:63 Excreta, approaches for handling, 1:676f Exhaustion phenomenon, 3:23 Exohydrology, 5:270 Exopolymeric substances (EPS), 4:27, 29 Expanded Granular Sludge Bed (EGSB), 1:906 ‘‘Explosimeters,’’ 2:308 Exponential recession, 3:22–23 Export of virtual water, 2:536 Exposure presence of food during, 2:420–421 use of semipermeable membrane devices for, 5:672–677 to vinyl chloride, 5:635–636 Exposure Analysis Modelling System (EXAMSII), 2:327 Exposure assessments, 1:424 Exposure biomarkers, 2:28–29, 31 Exposure concentrations, 2:422, 423 time-varying, 2:213–215 Exposure methods, 2:420 Exposure tests, sediment or fauna incubation experiment for, 2:418–423 Expressed sequence tag (EST) databases, 2:62 Ex situ physical/chemical treatment, of vinyl chloride, 5:639

749

Ex situ solidification/stabilization processes, 1:837 Ex situ vitrification, 5:618 Extended aeration, 1:815 External mass transfer, 4:567 Extracellular biodegradation, 2:43 Extracellular complexation, of metals, 5:283 Extracellular fluid (ECF), 4:459, 460 Extracellular matrix (ECM) endocrine system and, 4:461 water and, 4:459–461 Extracellular molecules, heavy metal binding to, 5:378 Extracellular polymeric substances (EPSs), 2:229–230 Extraction, of heavy metals, 5:435 Extraction estimates, Chicago Station, 5:79t Extraterritorial land use control, 1:315–317 in Boston, 1:376 choices related to, 1:317 in New York, 1:316–317 in Syracuse, 1:317 Extremely low frequency (ELF) spectrum, 1:513 Exudates, as chemical signals, 5:379 Exxon Valdez oil spill, 2:292; 4:597

Facies concept, 5:52–53 Facultative aerobes/anaerobes, 5:581 Failure defined, 2:675 reservoir, 3:259 Failure region boundary, 2:676 Fairness, public water supply and, 1:501 Fair weather flow. See Base flow Fair weather waterspouts, 4:347 Falling water, between two level drains, 5:96 Falling water table, between two bilevel drains, 5:96–97 Falls, 3:70 ‘‘Fanya juu’’ terrace, 3:550 Far East clock making in, 4:706–707 early clocks in, 4:704 Far Eastern Russia seas biosurveys in, 2:444–451

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750

CUMULATIVE INDEX

Far Eastern Russia seas (continued) evaluation of heavy metal pollution in, 2:447 seawater quality control in, 2:449–451 Farm and Ranch Lands Protection Program (FRPP), 3:596 Farming. See also Agricultural entries; Agriculture; Crop entries; Fish farms; Livestock entries irrigation techniques and, 3:591–594 organic, 3:644–645 Farmland, irrigated, 2:549 Farm runoff, 2:400 Fast atom bombardment mass spectroscopy (FABMS), 2:389 Fate and transport models, 5:589 Fatty acid esters (FES), 1:672 Fatty acids, 2:442 Faucets, low-flow, 2:665–666 Faults, rock, 5:137–138 Feasibility characterization, for in situ electrokinetic treatment, 5:118–120 Fecal bacteria, as water quality indicators, 2:23t Fecal coliforms (FC), 2:293, 344. See also Coliforms in groundwater, 2:396 as indicator bacteria, 2:361–362 modeling, 3:334 Fecal contamination, in Indian rivers, 3:449 Fecal-oral infection route, 1:178 Feces, as a source of infectious agents, 3:668 Federal Emergency Management Agency (FEMA), 2:526, 529; 3:147 Federal Fish & Wildlife Service, 3:518 Federal government. See also Federal regulations; United States; U.S. entries approach to droughts, 2:578 drought-related water quality and, 2:585–586 as waterway decision maker, 2:523 Federal Highway Administration (FHWA), 2:186 model, 2:253 Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), 5:357

Federal lands, reserved water rights for, 4:689–690 Federal law, protection of in-stream values by, 4:663–664 Federal legislation, groundwater, 4:631 Federal regulations. See also Federal government history of, 2:194 Federal-state regulatory interface, 4:671–673 water-quality-related, 2:190 Federal Water Pollution Control Act (FWPCA), 2:125, 194; 4:595, 664, 671, 691 amendments to, 2:195, 314–315 1961 amendments to, 4:652 1972 amendments to, 4:598 Federal water projects, expansion of, 2:522–523 Federal water resource agencies, 4:649 Federal water supply planning, 4:612–616 developments in, 4:612 federal–state cooperation in, 4:612–613, 614–615 multiprogram, 4:613 Water Resources Council and, 4:613–614 Feedback, in hydrologic systems, 3:230 Feeding status, chlorine toxicity and, 2:403–404 Feed water chemistry of, 1:414–415 quality of, 1:175 Feed wells, flocculating center, 1:454–455 Female reproductive system, effects of lead or, 2:436 FEMWATER model, 5:660, 663 Fen draining, 3:88 Fenton process, 1:871–872. See also Fenton’s Reaction Fenton’s Reaction, 4:445–448; 5:441 case studies involving, 4:447–448 delivery options related to, 4:447 equations related to, 4:446–447 history of, 4:446 in situ applications of, 4:447 Fenton’s Reagent, chemical oxidation with, 5:345–346 Fermentation, in landfills, 1:696

Fern Lake, biomanipulation trials in, 2:57t Ferrel, William, 4:353 Ferric hydroxides, 2:363; 5:19. See also Iron entries Ferric iron, 4:496 Ferrobacillus ferrooxidans, 3:14 Ferrous iron, 4:496; 5:609 Fertigation, 3:623 Fertilization, with nitrogen, 3:638–639. See also Eutrophication Fertilizer application methods of, 2:572 rates of, 2:571–572 Fertilizer management, as a nitrogen best management practice, 3:698–699 Fertilizers impact on surface water quality, 3:374 leaching of, 3:651–652 nitrogen in, 3:695 Fiberscopes, 5:402 Fick’s first law, 5:550, 551, 553 Field capacity concept, 5:124–128, 536 applications of, 5:126–127 history of, 5:124–125 measurement deficiencies in, 5:127 relation to water holding properties, 5:125–126 water content predictions and, 5:126 Field investigation, for levee construction, 3:286–287 Field irrigation recharge (Ri ), 5:166–167 Field measurements, 3:321 Fields diked, 4:696 floating, 4:695–696 Field sampling of contaminants, 2:263–269 when and how often to sample, 2:264–266 where to sample, 2:263–264 Field studies on mussels, 1:512 on veliger settling, 1:513 Field surveys biochemical, 5:119 electrokinetic, 5:119–120 Filamentous bacteria, 2:150

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CUMULATIVE INDEX

Filamentous organisms, foam-producing, 1:728–729 Filaments identification of, 1:846–847 isolation and characterization of, 1:847 ‘‘Filming amines,’’ 1:545 Filling time, 3:266 Fill material permits, 4:665 Filter density (ρGAC ), 1:103 Filter effluent turbidity, 1:224 Filtering screens, 3:748–750 Filter operation time (tF ), 1:103 Filter pack, 1:151 Filter performance, water treatment plant, 1:222 Filters, 1:379–380. See also Filtration biofouling of, 2:99–100 biophysicochemical interactions with colloids and dissolved organics, 2:100–102 iron-removal, 2:152–155 large-pore, 2:101 microirrigation, 3:623 rapid granular bed, 1:234 roughing, 1:237–238, 486 slow sand, 1:233–234, 235–236 types of, 1:817; 2:100 Filter underdrain systems, 1:234–235 Filter (linear) velocity (vF ), 1:103 Filtration, 1:227, 817; 2:374. See also Diatomaceous earth filtration; Filters; Filtration systems coarse gravel, 1:239–240 for CSO treatment, 1:786 domestic sewage, 1:834 drinking water, 1:227–230 granular bed, 1:249–251 hydrous manganese oxide, 1:398 of iron and manganese, 1:314 microbial regrowth and, 1:344 multistage, 1:238–243 particulate removal by, 1:243–245 precoat, 1:251 slow sand, 1:239, 249–250, 431–434 for small drinking water systems, 1:458–459 sorptive, 2:362–366 surface water treatment rule compliance technologies for, 1:462t wastewater, 1:810

water treatment plant, 1:224 water treatment via, 1:245–248 Filtration hydraulics, granular media filtration, 1:233 Filtration spectrum, 1:333f Filtration systems comparison of, 1:228–230 package plant, 1:515–517 selecting, 1:230 for storm water treatment, 1:868 Financial performance, of water companies, 1:310–312 Fine bubble diffused air aeration systems, 1:626–631 design considerations for, 1:629–631 diffuser types, 1:626–629 fouling, scaling, and clogging of, 1:630 Fine screens, 1:785 Finfish, stock enhancement of, 4:125 Fingerprint biomarkers, 2:29, 31 ‘‘Fingerprinting’’ analysis, 2:307 Finite differences (FD) method, 5:310–311, 621 Finite element method/modeling (FEM), 5:311, 621–623, 655–661 benefits of, 5:660–661 for incompressible flow problems, 5:657–658 principles of, 5:656 Finite elements (FEs), types of, 5:656–657 Finite volumes (FV) method, 5:311, 623 Fire demand constraints, in water distribution systems, 1:209 Fire flow tests, 3:316. See also Combustible watersheds; Corin Dam catchment fire Fire management, 2:201 Fire storage, 1:409 Firm yield, 3:261 First law of thermodynamics, 5:170 First-order degradation, 5:32 Fiscal solutions, in the Arab World, 2:473 Fish. See also Fisheries entries ambient exposure routes for, 3:116 biomanipulation of, 2:51–58 effect of road salt on, 2:323 herbivorous, 3:746 impacts of PCBs and dioxin-like compounds on, 2:108–109 loss to acidification, 3:9

751

pesticides in, 3:435 Puget Sound Basin, 3:349–362 trace elements in, 3:456–457 vulnerability to pollutant discharge, 3:283–284 worldwide consumption of, 3:123 Fish and Wildlife Service (FWS), 4:691 Fish assemblages, managing, 3:134 Fish cells bioavailability and mode/mechanism of action of, 3:117 in toxicological evaluation, 3:115–118 Fish cell toxicity end point, importance and relevance of, 3:116–117 Fish consumption advisories, 3:118–121 example of, 3:120 history and scope of, 3:118–119 methods associated with, 3:119–120 theory behind, 3:119 Fisheries, 3:121–129. See also Aquatic environments; Fisheries management benefits of, 3:122 defined, 3:122 ecosystem management and, 3:128 effect of sediment on, 3:508 history of, 3:122–123 impact of eutrophication on, 3:108 impact of oil on, 4:106–107 species and habitat preservation and, 3:128 Fisheries management, 3:122. See also Freshwater fisheries management coastal, 3:126 diadromous, 3:127 evolution of, 3:124–125 future of, 3:129 lake, 3:125 open ocean or high seas, 3:126–127 riverine, 3:125–126 scope of, 3:133 sustainable, 2:635–636 Fisheries oceanography, 4:55 Fisheries Oceanography Coordinated Investigations program, 4:90–91 Fisheries resources, current uses of, 3:123 Fishery biology, problem of, 4:143

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752

CUMULATIVE INDEX

Fishery stock assessments, 4:56–57 Fishery sustainability, precautionary principle regarding, 2:600 Fish farms environmental impacts of, 3:579–580 environmental regulations concerning, 3:580–581 waste treatment in, 1:681–684 water pollution from, 3:579–581 Fish growth and production, factors affecting, 3:129–133 Fish habitat, protecting, 3:129 Fish index of biotic integrity (Fish IBI), 3:38–39 Fishing waters, 3:532–533 Fish lift fish passage facility, 3:530, 531f Fish lock fish passage facility, 3:530 Fish models, 3:115 Fish passage facilities, 3:529–532 Fishpond culture, history of, 3:135–141 Fish ponds, water retention potential of, 1:407 Fish populations, serial depletion of, 3:126–127 Fish removal, algal control and, 2:6 Fish species, invasive, 3:284 Fish species richness, anoxic factor and, 4:66 Fixed bed adsorber, 1:102–104 regeneration of, 1:104–105 Fixed-bed sorption, 2:363–364 Fixed bed studies, 1:115 Fixed-film aerobic systems, 1:704 Fixed-film processes, 1:815–816, 833 Fixed fine screens, 1:785 Fixed-tension lysimeters, 5:489, 488 Fjord lakes, 3:269 Flagellates, 2:313 Flame ionization detector (FID), 2:307 Flame photometric detectors, 2:308 Flash flood warning systems, 1:125–126 Flash floods, 3:142 Flashing, 1:484 Flashy streams, 3:104 Flat-plate solar collector, 1:65–66 Flat rate structure, 2:663 Flat roofs, 1:55 Flattop Mountain SNOTEL (SNOw TELemetry) station, 4:334 snowpack at, 4:334–336

Flav-Savr tomato, 3:686 Fleet Numerical Meteorology and Oceanography Center (FNMOC), 4:96 Flexible repair coupling, 1:889 Floatable debris-related legislation, 4:39–40 Floatables control, netting systems for, 1:785–786 Floating agriculture, 4:695–696 Floating breakwaters, 4:20 Floating ice, 4:69–70 Floating-leaved aquatic plants, 3:743 Floating plants, 3:743 Flocculant polymers, 4:588–589 Flocculants, 4:425–426 Flocculant settling, 1:243; 3:404 Flocculating center feed wells, 1:454–455 Flocculation, 1:227, 252–254; 2:98–99, 374; 4:424–429, 586 ballasted, 1:454; 4:426 efficiency of, 4:427–428 mechanisms of, 4:424–425 Flocculation reaction, 5:619 Flood basalts, perched groundwater in, 5:353–354 Flood bypasses, 3:151–152 Flood control reservoir operation for, 3:386 Yellow River Basin, 3:45–50 Flood Control Act of 1944, 2:523; 4:616–617 Flood control engineering system, Yellow River, 3:48 Flood control storage, design of, 3:264 Flood control structures, 3:150–153 diversion structures, 3:151–152 failure of, 3:145–146 levees, 3:152 peak flow reduction using, 3:150–151 Flood conveyance capacity, decreasing, 3:50 Flooded soils, 3:206 Flooded zones, agricultural use of, 4:695 Flood farming practices, 3:164 Flood frequency analysis, 3:46t Flood index, 3:156–157, 159 analysis, 3:158–159 Flooding. See also Floods; Urban flooding causes of, 3:511 Ganga Basin, 3:234–235

general conditions for, 3:45–47 human response to, 3:149 regulation of, 3:382 tolerance for, 3:601 Yellow River Basin, 3:45–46 Flood insurance, 3:147 Flood insurance rate maps (FIRMs), 3:528 Flood irrigation, suitability criteria for, 3:164 Flood management, 3:512 participatory multicriteria, 2:678–683 Red River Basin, Manitoba, Canada, 2:681–682 stakeholder participation in, 2:680 structural and nonstructural, 3:512 Flood managers, Chinese, 3:48 Flood mapping, remote-sensing, 4:322 Floodplains, 2:543; 3:527–529 importance of, 3:527–528 mapping, 3:147 regulatory definition of, 3:528 remote sensing and GIS application in managing, 2:533 Flood prevention, 2:525; 3:510–513. See also Floodproofing Floodproofing, 3:147–148 Flood protection, 1:498–499 levees for, 3:286–291 ‘‘Flood Pulse Concept,’’ 3:292 Flood-related warning systems, 3:148 Flood retardation basins, Yellow River, 3:48 Flood risk, Yellow River, 3:49 Flood risk management, 2:525–526 optimal, 2:526 Flood routing models, Brakensiek’s, 3:255 Floods, 2:543; 3:142–150. See also Flooding defined, 3:142 detection and response warning systems for, 3:148 factors leading to, 3:142–147 forecasting, 1:123–125 human responses to, 3:146 ice jam, 3:511 impacts of, 3:142, 153 in India, 2:566–567 as natural hazards, 3:153–155 rain-on-snow, 3:511 responding to, 3:512 snowmelt runoff, 3:511

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CUMULATIVE INDEX

storm-rainfall, 3:511 structural and nonstructural measures against, 3:146–147 in the United States, 2:523 velocities of, 3:64 Flood source mapping case study in, 3:157 flood index analysis in, 3:158–159 procedure in, 3:156 unit flood response approach to, 3:156–157 in watersheds, 3:155–159 Flood stage, defined, 2:543 Flood storage, reservoir, 3:151 Flood-susceptible land, public acquisition of, 3:147 Flood warning systems, 1:125–126 Floodwater harvesting, 2:550 Floodwater spreading, 3:163–166, 709–710 advantages and problems associated with, 3:165–166 for artificial recharge, 3:164–165 design factors in, 3:165, 711 equations governing, 3:710–711 history of, 3:164 schemes related to, 3:165 Floral/faunal estimates, semiquantitative, 4:93 Florida coral banks in, 4:36–37 coral black water and, 4:133–135 Florida Bay-Everglades National Park, 4:55–56 Flotation, 1:371, 487, 811 sedimentation and, 3:406–408 as a separation process, 1:684–688 Flotation processes, selecting, 3:407t Flotation separation techniques, 1:594 Flow(s). See also Fluid flows; Pressurized flow creeping, 5:654–655 environmental, 3:106–107 laminar, 5:649–655 open channel, 3:195–196 through orifices and weirs, 3:195 steady-state and unsteady-state, 5:491 subsurface, 5:498–501 in pipes, 3:195 in the vadose zone, 5:537–538 viscous, 5:555–561 Flow analysis predictions, 5:63 Flow competence, 3:419

Flow cytometry, 1:160 Flow design, open channel, 3:346–349 Flow direction, identification of, 3:93 Flow-duration curves, 3:102–106 relationship to geohydrology, 3:103–104 shape of, 3:103 variability indexes and, 3:104 Flow equations, 5:310 Flow forecasting, entropy-spectral analysis for, 4:221 Flowforms, 4:795–797 Flowing artesian well, 5:600 Flowing gas–static liquid respirometers, 1:567 Flowing well/spring, 2:543 Flowmeter log, 5:154–155 Flow methods, instream, 3:526–527 Flow monitoring, 1:886 Flow paths, effect on water, 3:5 Flow phenomena, categories of, 3:247 Flow porosity, 5:184 Flow purging, 5:405 Flow rate measurement and control, water treatment plant, 1:222 Flow rates, 1:132 Flow regime modification, 2:477–478 Flow regimes, minimum environmental, 3:166–168 Flow regulation, river, 3:381–382 Flow restrictor showerheads, 2:666 Flow reversal, Chicago River, 3:41–45 Flow routing channel, 3:253–254 HYMO model of, 3:255 kinematic wave, 3:253–259 Kousiss model of, 3:257 model parameters for, 3:257–258 Muskingum–Cunge method of, 3:256–257 Muskingum method of, 3:255 reservoir, 3:255 SSARR model of, 3:255–256 SWMM model of, 3:256 Flowstone, 5:246 Flow systems. See also Fluid flow systems; Fracture flow system boundary conditions for, 5:14–16 one-way, 3:437–439 regional, 5:417–421 topography and, 5:420 Flow-through (FT) aquaculture systems, 3:542–543

753

Flow-through fish farms, 1:681–682 Flow velocities, 1:205–206 from culverts, 3:77 effect on corrosion, 1:8 dye tracers for measuring, 3:96 Flue gas desulfurization (FGD) material, 1:556 Flue gas desulfurization sludge disposal site aqueous behavior of elements in, 1:848–853 FGD scrubber purge water in, 1:849–850 limestone/lime-based desulfurization systems and, 1:849 process description of, 1:848–849 water quality in, 1:850–853 Fluid density, head and, 5:181 Fluid flow equations, 5:309–310 Fluid flows, 3:194–195 Fluid flow systems, conservation laws for, 5:651. See also Flow systems Fluidity, of sludge, 1:862–863 Fluidized bed furnace (FBF), 1:858, 860 Fluid mechanics, 3:197 Fluid momentum equation, 3:198 Fluid Physics Research Program, 4:448 Fluids. See also Gas entries; Liquids consistency coefficient for, 5:557 dilatant, 5:557 non-Newtonian, 5:556–558 pseudoplastic, 5:557 time-dependent, 5:557 time-independent, 5:556–557 Fluorescent dyes, 3:96 in groundwater tracing, 5:108, 505–506 Fluorescent in situ hybridization (FISH), 1:161, 646. See also Whole cell fluorescent in situ hybridization in community analysis, 1:645 monitoring foam-forming bacteria using, 1:847–848 Fluorescent-labeled latex beads (FLLB), 2:415 Fluorescent labeling, 2:59 Fluoridation, 1:254–257 cost of, 1:256 history of, 1:255 worldwide rates of, 1:257

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754

CUMULATIVE INDEX

Fluoride, 1:255, 903 in bottled water, 1:5 control limits on, 1:296t in groundwater, 2:396 maximum contaminant level of, 2:234t safety of, 1:255–256; 4:435 Fluoride concentration, 1:296 safe, 4:435 Fluoride contamination controlling factors in, 5:133–134 in groundwater, 5:130–136 mechanism of, 5:134 remedial measures for, 5:134–135 sources of, 5:132–133 Fluorosis, 5:130–132 Flushing in algal control, 2:4 distribution system, 1:206 enhanced, 5:440 as a watershed function, 3:478 Flushing rate, lake, 3:283 Fluvial lakes, 3:265 Fluvial sediments, movement of, 3:418–419 Fluviogenic areas, 1:404 Flux(es), 5:126 measurement of, 5:545 stoichiometric analysis of, 4:53 Flux chambers, 5:549 Flux-concentration relation, 3:248, 250 Flux laws, 3:249–250 Flux-type natural resources, 2:634 Fly ash production, fluoride contamination and, 5:133 Foam formation, 1:844–845 Foam-forming bacteria, monitoring, 1:847–848 Foaming and bulking. See Microbial foaming and bulking Foam-producing filamentous organisms, 1:728–729 Foci detection method (FDM), 1:160 Focused electrode leak location (FELL) system, 1:887 Fog, 4:229–230, 293 coastal, 4:230–239 maritime, 4:232 Food(s) emergency, 2:526–529 low supplies of, 2:528 nitrate in, 1:31–32, 33–34 shelf-life of, 2:528

short-term supplies of, 2:527–528 storage tips for, 2:528 Food and Agriculture Organization (FAO), 3:573, 619 Food and Drug Administration (FDA), 1:4 pharmaceutical release and, 1:377 Food chain(s), 4:151–152. See also Foodwebs biological magnification of DDT in, 3:523 Food cycle, 4:152 Food processing industry, impact on surface water quality, 3:374 Food production, drainage and, 5:99 Food security, relation to water security, 1:438–439 Food wastes, constructed wetlands for, 1:896 Foodwebs, 4:152–153. See also Food chain(s) microorganisms in, 3:312 properties of, 4:153 Force mains point repairs for, 1:889, 890–891 repairing, 1:888 Forcing factors, current, 3:322 Forecast Systems Laboratory (FSL), ground-based GPS meteorology at, 4:244–255 Forensic hydrogeology, 3:168–170 ethics and standards in, 3:170 issues in, 3:169 tools and approaches for, 3:169–170 Forest(s), 3:170–172 acidic deposition and, 4:378 cutting, 2:200 distribution of, 3:171 regeneration of, 2:200 Forest activities, influence on the hydrologic cycle, 4:282 Forested landscape, water quality management in, 2:199–202 Forested wetlands, 3:172 Forest fire, impact on water quality, 2:201 Forest hydrology research, 2:199 Forest Legacy Program (FLP), 3:596 Forest management, 2:201. See also Forestry Forestry. See also Forest management Great Lakes region, 3:178

nonpoint source pollution from, 2:187 sediment problems related to, 3:508 Forest soil, disturbance of, 2:200 Forest structure hydrologic cycle and, 3:171–172 implications for management, 3:172 FORTRAN Hydrological Simulation Program (HSPF), 2:249–250, 326 Fossil aquifers, 5:294–295 American, 5:295 international examples of, 5:295 Fossil-fuel combustion, contaminants released by, 1:554t Fossil fuel power, greenhouse gas emissions from, 3:182f Fossil fuels, 1:560–561 biofuel alternatives to, 3:545–549 trace elements in, 3:458 use of, 3:546 Foulants, types of, 1:420 Fouling, 1:334. See also Biofouling control of, 1:415 in diffused air aeration systems, 1:630 mussel size and, 2:402 Foundation stability, levee, 3:288 Foundation underseepage, levee, 3:289 Four-electrode measurement, 4:432 Fourier Transform Infra Red (FTIR) spectroscopy analysis, 4:508 Fractal analysis, 5:176 Fractal geometry, 5:301 Fractionation, of colloids, 3:74–75 Fractionation factor, 4:500, 501 Fraction of absorbed photosynthetically active radiation (fAPAR), 3:722–723 Fractured aquifers, 5:600 Fractured igneous rock aquifers, 5:145 Fractured rock systems, groundwater flow in, 5:175–177 Fracture flow system, characterization of, 5:177 Francois formula, 4:19 Franklin, Benjamin, 4:780–785 relationship with water, 4:741–746 swim fin development by, 4:784–785

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CUMULATIVE INDEX

water music instrument of, 4:758–762 weather theories of, 4:784 Franklin/Folger Gulf Stream chart, 4:782–784 Franklin–Gordon Rivers Wild Park (FGRWP), 4:789 Franklin River, 4:788–789 Fredericksborg Castle Lake, biomanipulation trials in, 2:56t Fredericton aquifer case study, 5:678–686 Freeboard, 3:287, 348 Free chlorine, 1:169, 194. See also Chlorine entries bromide oxidation by, 2:74–75 residual, 2:89 Free chlorine/free available chlorine (FC/FAC), 1:128 Free chlorine residual, 1:662, 663; 2:398 Free-floating aquatic plants, 3:743 Free flow, in culverts, 3:76 Free-flowing groundwater, 5:29 Free-formed pools, 3:67 Free Ion Activity Model (FIAM), 2:212; 3:75 Free phase chlorinated solvents, 5:92 Free water knock out (FWKO), 2:285–286 Free-water organisms, 3:310 Free-water surface flow systems, 3:365–366 Free water surface (FWS) wetlands, 1:787 technology for, 1:894–895 Freeze-drying process, 4:344–345 Freeze-thaw sludge conditioning, 1:864 Freezing, of water, 4:585–586 Frenchman’s Cap, 4:788 French water management model, 1:389 Frequency domain electromagnetic induction, 5:149 Freshwater(s), 2:543; 4:449–450 chronic acidification of, 3:1 distribution of, 4:753 in Lake Vostok, 3:506 removing colloids from, 3:74 standard composition of, 3:266 Freshwater colloids, 3:74–75 environmental importance of, 3:75 Freshwater density, 5:181 Freshwater fisheries management

coordinated, 3:134 holistic, 3:134–135 water needs for, 3:133–135 Freshwater head, 5:160, 161, 181 Freshwater net pens, 3:543 Freshwater resources acidification of, 3:7–13 global, 1:437 Hawaiian, 4:801–807 proton concentration, acidity, and dissolved solids in, 3:8 sustainable management of, 2:634–635 Freshwater runoff, effect on nutrient concentrations, 4:81, 82 Freshwater streambed sediment, organic compounds and trace elements in, 3:349–362 Freshwater supply global, 2:548–549 sources of, 2:515 Freshwater swamps, 3:172 Fresno, pesticide assessment in, 5:359 Freundlich adsorption isotherms, 1:101, 113, 114t, 578, 777; 4:566. See also Isotherms Freundlich equation, 2:71, 87 Freundlich model, 3:300–301; 4:385, 386 Friction velocity, estimation of, 4:1–2 Fritz and Schlunder multicomponent adsorption model, 1:108 Frontal fog, 4:231 Fronts, coastal fog and, 4:231 Frost, 4:240–241 damage from, 4:241–242 formation of, 4:241 permanent, 4:305–306 Fugacity, 4:524 Full cost pricing, 2:663 Full privatization model, 1:50 Full reservoir level (FRL), 3:411 Full utility concessions, 1:388–389 Fulvic acid, 4:399; 5:190, 191 Funding, of municipal solid waste landfills, 2:168. See also Cost(s) Fungal biofouling, 2:240 Fungi in cooling water systems, 1:540 health effects of, 1:278 Furrow infiltrometer, 4:487 Fuss, Adam, 4:767 Fuzzy compromise programming (FCP), 2:681

755

Fuzzy criteria, for system performance evaluation, 2:674–678 Fuzzy expected value (FEV), 2:680, 682 Fuzzy inference system, 2:680 Fuzzy membership function, 2:676 Fuzzy reliability–vulnerability criteria, 2:677 Fuzzy resiliency, 2:677–678 Fuzzy robustness, 2:677 Fuzzy sets, 2:675

GAC bed, 1:103. See also Granular activated carbon (GAC) Gage height, 2:543 Gaging station, 2:543 Galerkin weighted residual finite element method, 5:660 Galge site, biomanipulation trials in, 2:55t Galilei, Galileo, 4:349 on water music, 4:758 water observation by, 4:711–712 GAMIT software, 4:245 Gamma attenuation soil moisture measurement, 4:488 Gamma density log, 5:153 Ganga Basin, 3:232–233. See also Ganga–Brahmaputra–Meghna Basin; Ganga River (India); Ganges water dispute hydrology of, 3:233–234 sediment sampling sites in, 3:297f water quality in, 3:235 water resources development projects in, 3:234–235 Ganga–Brahmaputra–Meghna Basin, 2:560 Ganga River (India), 3:232–235 adsorption experiments on, 3:296–300 Ganges water dispute, 4:682–683. See also Ganga entries Gardens floating, 4:695–696 raised, 4:698 Gardens of the war, 4:697 Garrison Diversion Unit (GDU), 4:686 Gas abstraction, from landfills, 1:699 Gas chlorination, 1:197–198. See also Chlorine entries

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756

CUMULATIVE INDEX

Gas chromatography (GC) air sampling techniques in, 2:307 detectors in, 2:307–308 headspace technique in, 2:306 for odor analysis, 2:281 purge and trap procedure in, 2:306 sample introduction in, 2:305–306 solvent extraction in, 2:307 in water analysis, 2:304–308 Gas chromatography/electron capture detection (GC/ECD), 3:119 Gases. See also Greenhouse gases dissolved, 4:450–452 in domestic sewage, 1:831 Gas exchange coefficient, 5:551–552 Gas hydrate mounds, observing, 4:60–61 Gas hydrates, 4:471 amount in boreholes, 4:61 distribution and dynamics of, 4:57–61 formation of, 4:58 origin of gas in, 4:58–59 remote sensing for, 4:59–60 sampling, 4:61 stability of, 4:58 Gas laws, 4:521 Gas–liquid contactor hydrodynamics, 1:361 Gas migration, landfill, 5:256 Gas-phase activated carbon applications, 1:104–105 Gas stripping systems, 1:803 Gastric cancer, nitrate-related, 1:36–37 Gastritis, 1:180 Gastroenteritis, 2:138 Gas-water reactions, isotope exchange in, 4:535–541 GC/mass spectrometry (GC/MS), 3:119 Gelatinous zooplankton, 4:155 GEMS/WATER program, objectives of, 2:177–178 Gene Chips , 2:60 Gene-probe technology, 2:352 General Agreement on the Crisis of the Aral Sea, 3:18–19 General factorial design, 1:110 Generalized autocovariance structure (GAS), 3:426 Generalized likelihood uncertainty estimator (GLUE), 4:299

Generalized Watershed Loading Function (GWLF), 2:252–253 Generating plants. See Electric generating plants Genes, luminescent-marked, 2:453–454 GENESIS genetic algorithm optimization software, 2:327, 334 Genetic algorithm-based techniques, 3:319 Genetic algorithms (GAs), 2:333–335 Genetically modified plants, 3:686 Genetic damage, 1:289 Genetic engineering, 2:48 to advance selenium phytoremediation, 5:399–400 phytoextraction optimization using, 5:372 Genomics, 2:59–61, 429 Genomic technologies in biomonitoring, 2:58–64 high-throughput, 2:59–62 Genomic tools, 2:339 in biomonitoring, 2:63 Genotoxicity assessment, luminescent bacterial biosensors for, 2:455 Genotoxic response, 2:171 Geobacter metallireducens, 2:151 Geochemical carbon cycle, 4:414 Geochemical fixation, of lead, 5:648 Geochemical modeling. See also Geochemical models computer codes for, 5:140–141, 142–145 computer models for, 5:143–144 equilibrium thermodynamics and, 5:143 Geochemical models, 5:138–140. See also Geochemical modeling components of, 5:139 types of, 5:139 validation and usefulness of, 5:139–140 Geochemical processes, in groundwater, 5:32–33 Geochemical silica cycle, 4:550 Geochemical temperature estimation methods, 4:93 Geochemical variations seasonal, 5:684–686 spatial, 5:686 Geochemistry, 5:463 of acid mine drainage, 3:13–15 of arsenic, 1:81–82

cadmium, 5:616 of carbonate, 4:408–413 of carbonate in natural waters, 4:414 of silica, 4:549 Geoelectrical methods, 5:447 Geoelectrical operations, electrode configurations for, 5:445 Geogenic acidification, 3:9–10 Geographic Information System (GIS). See also GIS technology application in water resources, 2:531 in command area studies, 2:533–534 in floodplain management, 2:533 future need for, 2:535–536 ground feature categorization using, 3:363 in groundwater studies, 2:534–535 in hydrologic modeling, 2:535 in land use classification, 2:532 management and research uses of, 4:56 modeling non-point source pollutants using, 5:299–305 in precipitation studies, 2:532 raster-based, 3:28 in reservoir sedimentation, 2:534 role in nonpoint source pollution assessment, 3:658 in snow cover studies, 2:533 in waterlogging and soil salinity, 2:534 in water quality studies, 2:534 in watershed mapping and monitoring, 2:533 Geohydrologic characterization, improvements in, 5:187 Geohydrology differential, 3:103–104 flow-duration curves and, 3:103–104 Geological deposits, acidic tailings from, 3:9–10 Geological fluoride contamination sources, 5:132 Geological formations, resistivities of, 5:444 Geologic deposits, hydraulic conductivity of, 5:508 Geologic settings, setback distances for, 1:72–73 Geologic soil erosion, 3:417

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CUMULATIVE INDEX

Geology effect on trace elements, 3:457 Great Lakes, 3:175–176 Geomicrobiology, 5:463 Geomorphology, basin, 4:222 Geophones , 1:401 Geophysical Fluid Dynamics Laboratory (GFDL), 4:43–44 Geophysical groundwater parameters, 5:184 field testing and analysis of, 5:185–186 Geophysical methods, surface methods, 5:146–151 Geophysical survey design, 5:155–156 Geophysics groundwater, 5:151–155 remote sensing and, 5:145–156 Geopolitics, of South Asia hydro-borders, 4:680–684 Geosorbent domains, sorption in, 4:385–386 Geosorbents, sorption of hydrophobic organic compounds on, 4:384–387 Geostatistics, 5:301 Geotechnical problems, 5:604 Geotextiles, natural fiber, 3:568 Geothermal geophysical methods, 5:151 Geothermal plants, 1:563 Geothermal water, 5:156–158 ‘‘Germicidal’’ radiation, 1:469 Geysers, 2:543; 5:157 GFDL modular ocean model, 4:44. See also Geophysical Fluid Dynamics Laboratory (GFDL) GHG dynamics, in hydroelectric reservoirs, 3:204–207. See also Greenhouse gases (GHGs) GHG emission levels, inter- and intra-reservoir, 3:206t GHG emission processes, 3:205–206 GHG emissions, 3:203, 204–205 from hydroelectric reservoirs, 3:203 GHG fluxes, 3:204t, 205–206 GHG production processes, in hydroelectric reservoirs, 3:206–207 Ghijben–Herzberg equilibrium (GHE), 5:158–162 Giardia, 1:279, 522, 523 in karstic aquifers, 1:367

Giardia lamblia, 1:189, 257 life cycle and morphology of, 1:257 Giardiasis, 1:180, 257–259; 2:543 case clusters of, 1:188t clinical disease related to, 1:257–258 diagnosis and treatment of, 1:258 epidemiology and prevention of, 1:258–259 Gibbs–Duhem equation, 4:364 Gibbs phase equilibrium rule, 4:264, 364 Gilgamesh poem, story of water in, 4:708 GIMRT/OS3D program, 5:141 GIS technology, 2:252 to indicate heavy metal concentrations, 2:448–449 Glacial-interglacial cycles, 4:117–118 Glacial lakes, 3:269–270 Glacier Bay, oceanographic environment of, 4:61–62 Glacier ice, 4:334 Glaciers, 2:543, 660. See also Rock glacier Canadian, 2:660 Glasses, musical, 4:758–762 Glass pH sensor, 2:296 GLEAMS model, 2:251 GLERL instrumentation, 4:70–72 Gliding cell formation, 2:240 Global average energy balance, 4:179–180 Global change detecting, 4:177–178 observations of, 4:172–179 radiative forcing of, 4:176–177 Global climate change, 4:171–172 Global currents, 3:320 importance of, 3:321 Global cycles, of climatically-active trace gases, 4:85–89 Global desalination market, 1:308–312 Global economy. See also Economics pharmaceutical industry in, 1:373 precautionary principle and, 2:596–597 Global Environment Facility (GEF), 4:643 Global Horizontal Sounding Technique (GHOST), 4:166 Global hydrologic cycle, 4:266 Global impacts, of sea-level change, 2:483

757

Globalization of water, 2:536–541 water rights and, 4:770–771 Global Meteoric Water Line (GMWL), 4:439; 5:230 Global partitioning, of anthropogenic CO2 , 4:85 Global Positioning System (GPS), refractivity measurements using, 4:244–245. See also GPS entries Global Positioning System Integrated Precipitable Water (GPS-IPW) data, effect on numerical weather prediction accuracy, 4:248–249 Global Positioning System Integrated Precipitable Water Demonstration Network, 4:249–250 expansion and improvement of, 4:251–255 Global Sea Level Observing System (GLOSS), 4:119 Global search methods, 2:333 Global warming, 4:173, 184–185, 479, 480 Global water balance, 4:225, 279–280 conclusions about, 4:289 crisis, 4:769 Global water availability, prediction of, 1:437–438 Global water cycle, 4:242–244. See also Hydrologic cycle; Water cycle deuterium in, 4:439 Global water market, 1:3 Global water resources, efficient use of, 2:536 Global water use, 2:489–490 Global weather, 4:361–362 Glucose–glutamic acid (GGA) solution, in BOD5 tests, 2:39 Glutathione (GSH), 3:609 role in plant protection, 3:610 Glycerides, 2:442 GOD vulnerability assessment, 5:563 Goff–Gratch function, 4:366 Gold Book, 2:315 Golden Horn Bight, pollution in, 2:446 Golet and Larson wetland classification system, 3:497 Goodness-of-fit statistics, 4:298–299 Gordon River, 4:788–789 Governance, 1:42

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758

CUMULATIVE INDEX

Government. See also British entries; European Union (EU); Extraterritorial land use control; Federal entries; French water management model; Ireland; Mexico; National entries; New Mexico; New York entries; Poland; Public entries; Regulation; Regulations; Regulatory entries; San Diego; South Africa; Sri Lanka; State entries; Syracuse; United States; U.S. entries drought policies of, 2:576, 577–578, 580, 583 market operation and policies of, 2:500–501 public interest water management and, 2:609 structure of American, 2:498 water security and, 1:434–436 Governmental obligations, water rights and, 4:771 Governmental water resource organizations, 4:649–650 GPS-IPW Demonstration Network sites, data and products from, 4:250. See also Global Positioning System Integrated Precipitable Water entries GPS Meteorology (GPS-Met), 4:249. See also Global Positioning System (GPS) GPS orbit predictions, 4:248 GPS signal delays, calculating integrated precipitable water vapor from, 4:245–247 ‘‘Grab’’ groundwater sampling, 5:454–455 Gradients, 3:309–310 Gradient-type flux law, 3:250 Grain size/porosity, 5:535 Granular activated carbon (GAC), 1:92–93, 102, 231, 244, 380, 460, 575; 2:80. See also GAC bed characterization of, 1:96–98 effects of treatment with, 2:76–77 pecan shell-based, 1:110–111 raw materials for, 1:93 technology with, 1:350–352 Granular activated carbon unit, 1:52 Granular aquifers, heterogeneity in, 5:175 Granular bed filtration, 1:231, 249–251

Granular biological activated carbon (GBAC), oil- field brine and, 2:288–289 Granular filtration, high-rate, 1:250–251, 487. See also Granular bed filtration; Granular media (medium) filtration Granular filtration technologies, innovations in, 1:235 Granular media (medium) filtration, 1:230, 233–235, 244, 827 filter classification, 1:233–235 filter media types, 1:233 filter operation and control, 1:235 filtration hydraulics, 1:233 particle removal mechanisms, 1:233 Granulation, 1:906 Granulometric composition, of sludge, 1:862 Graphical method, for determining base flow recession constants, 3:24–25 Grass groundcover, as a living mulch, 3:708 Grassland Reserve Program (GRP), 3:596 Grass plants, root growth in, 3:706–707 Gravimeter surveys, 5:148 Gravimetric method, 5:533 Gravimetric soil moisture measurement, 4:487–488 Gravitational geophysical methods, 5:148 Gravitational potential, 5:532 Gravity-flow units advantages and disadvantages of, 2:155 for iron removal, 2:154 Gravity irrigation methods, 2:495 Gravity screen filters, 3:749 Gravity separation/sedimentation, 1:259–261, 811 Gravity sewers, 1:887–888 point repairs for, 1:888–889 Gravity thickening, of sludge, 1:854, 864 Gray water, 3:557. See also Greywater pollutant concentration in, 1:17t quality of, 1:16t recycling system for, 1:18f removing pollutants from, 1:18f reuse in households, 1:16–19

Grazing, microorganism strategies against, 3:312 Grease, in urban stormwater runoff, 3:435 Great Artesian Basin, 5:30 Great Britain. See British entries; U.K. National Rivers Authority Great Depression, 2:511 development of, 2:512 Great Egg Harbor River, flow-duration curve for, 3:103, 104f Great Lakes, 2:658; 3:175–179 geologic origins of, 3:175–176 hydrologic flows and climate of, 3:177–178 land and water use related to, 3:178–179 physical features of, 3:176t preventing diversion from, 4:618–620 water budgets for, 3:177t water quality guidance for, 4:622–625 water resource management related to, 3:179 water withdrawal from, 3:179t wetlands, 3:71 Great Lakes Charter, 4:618–619 Great Lakes Charter Annex, 4:619 Great Lakes Commission (GLC), 4:618 Great Lakes Critical Programs Act, 4:597 Great Lakes Environmental Research Laboratory (GLERL), 3:274–275 meteorological instrumentation at, 4:72–73 Great Lakes Governors’ Agreement, 4:617–620 Great Lakes Toxic Reduction Effort (GLTRE), 4:625–626 Great Lakes Water Quality Agreement (GLWQA), 3:179; 4:618, 621, 622 Great Lakes Water Quality Initiative, 4:621–627 history of, 4:622 Greece, water symbolism in, 4:786 Greek water clocks, 4:706 Greek water consciousness, 4:708–709 Green accounting, 2:626–627 Green algae, filamentous, 3:115

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CUMULATIVE INDEX

Green Book, 2:315 Green/brown roofs (sloped or flat), 1:55–56 Greenfield contracts, 1:389 Greenhouse gas emissions, from hydroelectric reservoirs, 3:180–183 Greenhouse gases (GHGs), 4:171. See also GHG entries anthropogenic sources of, 3:203–210 state of research on, 3:180–181 temperature increase and, 4:282–283 Greenhouse warming models, 4:22 Greenland ice sheet, 4:118 Green Revolution, 2:617 Greensand filtration, for radium removal, 1:398 ‘‘Green’’ technology, 1:535, 536. See also Environmental entries Grotthuss proton transfer mechanism, 4:483 Ground-based GPS meteorology, at Forecast Systems Laboratory, 4:244–255 Greywater, defined, 2:543. See also Gray water Grid spacing, 3:257–258 Grid-square basin slope method, 3:29 Grit removal, 1:814 from domestic sewage, 1:832 Ground-level pumped storage tanks, 3:316 Ground penetrating radar (GPR), 5:150–151, 402, 541 for pipeline assessment, 1:884 Groundwater, 1:444; 2:95; 4:285. See also Contaminated groundwater; Groundwater assessment; Groundwater quality; Modern groundwaters acidification of, 3:10 active management and regulation of, 4:632 in agriculture, 2:156; 5:205 in Arab states, 2:471 availability of, 5:192 bacteriological analysis of, 5:202–203 benzene in, 5:626–628 beryllium in, 4:396–397 biochemical parameters of, 5:184–185 biotreatment of, 5:120

cadmium in, 5:613–619 Canadian, 2:660; 5:601–602 chemical analyses of, 5:449 cobalt in, 5:610–613 composition of, 4:285 compounds in, 2:316–319 contaminant vapor transport in, 5:551 defined, 2:543; 5:600 dependence on, 5:451 dissolved gases in, 4:450–451 downward vapor transport into, 5:551–552 effect of gas on, 5:256 engineering and, 5:604 EU monitoring of, 2:268 evapotranspiration from, 5:168 flow velocity studying, 3:96 fluoride contamination in, 5:130–136 fluoride content in, 5:199–200 free-flowing, 5:29 geological occurrence of, 5:145 geophysics of, 5:151–155, 184 harvesting of, 2:550 as a hidden treasure, 5:599 high pH, 5:362–365 humic matter in, 2:209–210 hydraulic conductivity of, 5:128 hydraulic properties of, 5:184–188 hydrochemical data on, 2:158t in the hydrologic cycle, 5:601 impact of river water quality on, 2:396 in India, 2:555 injection of, 5:178 ionic strength of, 5:351 iron-oxidizing bacteria in, 2:150 isotopic composition of, 4:576 lead in, 5:645–649 mercury in, 5:642–645 metal organic interactions in, 5:258–260 methane in, 5:293–294 mobility of humic substances in, 5:188–192 ‘‘mounding’’ of, 5:353 movement of, 5:600–601 MtBE in, 5:318, 319 nitrate contamination/content in, 2:156, 570–571; 5:322–323, 628–631 nitrate losses to, 3:642 nitrate pollution of, 3:637 as a nitrate source, 1:33–34

759

nitrogen in, 5:333 organic compounds in, 5:337–340 particulate arsenic in, 2:11 particulate transport in, 5:349–352 perched, 5:352–355 perchlorate in, 5:631–634 permafrost and, 5:601 permeability of, 5:128–129 pesticide contamination of, 5:333 pesticide vulnerability of, 5:357–362 Polydex disinfection of, 1:384–386 problems with, 5:333 pumped, 3:583 reactive solute transport in, 5:524–531 residence time, 4:388–389; 5:601 skimmed, 3:691–692 sodium in, 4:551–552 solute transport modeling in, 5:305–313 as a source of energy, 5:601 specific yield of, 5:129 sulfate content of, 5:197 technetium in, 4:580–581 trace element contamination in, 2:143–148 transmissivity of, 5:129 treatment for nitrates in, 5:323–331 unconfined, 5:662–667 uranium in, 5:640–642 use in irrigation, 3:588 velocities, 5:554–555 vinyl chloride in, 5:634–640 wetlands and, 3:173; 5:605 Groundwater age, 4:388–390. See also Groundwater dating estimating, 5:70 Groundwater arsenic, 5:17–21 chemical character of, 5:17–19 treatment systems for, 5:19–21 Groundwater assessment, 5:313 experimental methodology for, 2:144 recommendations following, 2:148 results of, 2:144–148 using soil sampling techniques, 3:688–691 Groundwater balance, 5:162–169 equation, 5:164 estimation of, 5:163 estimation of components for, 5:164–168

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760

CUMULATIVE INDEX

Groundwater balance study, data requirements for, 5:164 Groundwater bioremediation, 2:44 pump and treat, 5:45–46 Groundwater cleanup, objectives for, 3:652 Groundwater contaminants. See also Groundwater contamination defined, 5:30 movement of, 5:426 sources of, 3:226–229 Groundwater contamination, 1:438, 524, 556; 2:183; 5:603–604. See also Contaminated groundwater assessing and defining, 5:549–550 cost allocation for, 3:169 environmental isotopes in, 5:221–224 leachate releases and, 5:255 from runoff, 5:451–453 sources of, 5:216, 516 from urban runoff, 5:452–453 Groundwater dams, 2:551 Groundwater dating. See also Groundwater age with H–He, 5:65–69 with radiocarbon, 5:64–65 with tritium, 5:69–72 Groundwater depth, crop tolerance and, 3:601–603 Groundwater devolatilization, upward migration of vapors from, 5:553 Groundwater discharge, from karst systems, 5:238–239 Ground Water Disinfection Rule (GWDR), 1:70, 354 Groundwater disputes, 4:632–633 Groundwater divide, 5:419 Groundwater draft, 5:164, 168 Groundwater dye tracing, 3:96. See also Groundwater tracing analytical strategies for, 5:109–110 in karst, 5:107–111 methods of, 5:109 selecting dye introduction points for, 5:109 at waste disposal sites, 5:110 Groundwater Festival, Children’s, 4:713–714 Groundwater flow, 3:96, 453–454; 5:29, 514–518. See also Base flow aquifers in, 5:515–516

effects of recharge and discharge on, 5:83 in heterogenetic sediments and fractured rock systems, 5:175–177 mathematical model of, 5:516 properties of, 5:128–130 system, 5:417 in unit hydrograph models, 4:359 Groundwater flow equations, 5:12–13, 13–16 Groundwater flow models, commercial, 5:660 Groundwater Foundation, The (TGF), 2:518, 519; 4:713 Groundwater geochemistry, 2:19 of river-connected aquifers, 5:684–686 Groundwater Guardian, 2:518, 520 Groundwater impacts, bioreactor landfill design and, 5:257 Groundwater inflow (Ig ), 5:167–168 Groundwater investigations, soil vapor data and, 5:548–554 Groundwater iron, environmental impact of, 5:608–610 Groundwater law, 4:627–634. See also Groundwater disputes legal classifications of groundwater, 4:630 legal rules for groundwater use, 4:630–632 origin and nature of property rights in, 4:629–630 reform of, 4:633 Groundwater modeling, 5:619–626. See also Groundwater models boundary and initial conditions in, 5:620–621 contaminant transport and biodegradation in, 5:30–35 differential equations in, 5:620 discretization in, 5:621–623 parameter estimation in, 5:624–625 results and visualization of, 5:623–624 steps in, 5:623 Groundwater models, 5:77. See also Groundwater modeling Groundwater monitoring, 5:110 for municipal solid waste landfills, 2:165 Phase IV, 5:438

Groundwater monitor wells, 5:404–405 Groundwater outflow (Og ), 5:167–168 Groundwater overdraft, in the Arab World, 2:472f Groundwater pollutants, 3:226–229 from animal farming operations, 3:538 Groundwater pollution, 2:400; 3:282 prevention and remediation of, 5:187 Groundwater pollution studies isotopes used in, 5:219t resistivity methods in, 5:447–448 Groundwater pollution vulnerability characterization, isotope technique for, 5:219t Groundwater protection, 5:599–600 public education and community involvement in, 2:518–520 Groundwater protection area, 1:524 Groundwater purging/surging, low-flow, 5:404–405 Groundwater quality, 2:160, 182–183; 5:406–407, 602–603 in animal farming operations, 3:538–540 common problems with, 5:406 in Hardwar, Uttaranchal, India, 5:192–204 land-use impacts on, 2:183t; 5:250–253 near River Yamuna, India, 2:392–398 Groundwater recession plots, 3:26 Groundwater recharge, 1:818; 2:393; 3:603 to karst systems, 5:236 in karst topography, 5:247 projects, 2:611 regulation of water quality for, 1:291 Groundwater recovery, goals of, 4:675 Groundwater remediation. See also In situ groundwater bioremediation; In situ groundwater remediation activated carbon in, 1:105 chemical oxidation technologies for, 5:344–349 by electrochemical processes, 5:283–284 Fenton’s Reaction and, 4:445–448

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CUMULATIVE INDEX

horizontal wells in, 5:178–180 by injection and problem prevention, 5:421–423 innovative technologies for, 5:438–443 landfill-related, 5:257 by no action (passive), 5:44–45, 423–426 organoclays in, 1:772 project life cycle, 5:436–438 Groundwater resources in India, 2:562–564 quantification of, 5:163 use of, 5:187 vulnerability mapping of, 5:561–566 Ground Water Rule (GWR), 2:195, 345 Groundwater sampling for CFCs, 4:421 diffusion-based, 5:456 for environmental projects, 5:454–456 with passive diffusion samplers, 5:456–460 protocol for, 5:455 purpose of, 5:454 quality control of, 5:455–456 Groundwater scheme, environmental impact assessment for, 2:521t Groundwater sensitivity to contamination, 5:56–60 factors affecting, 5:58t Groundwater sources, high control of, 2:400 Groundwater storage change in (S), 5:168 in karst systems, 5:238 Groundwater storage coefficient, 5:129 Groundwater studies CFCs in, 4:422–423 microbiological methods in, 5:464–465 remote sensing and GIS application in, 2:534–535 Groundwater supply, safeguarding, 5:605 Groundwater systems features of, 5:308–309 fluid dynamic analysis of, 5:498 role of heat in, 5:172–175 subsurface heterogeneity characterization in, 5:308–309

Groundwater tracing, 5:501–507. See also Groundwater dye tracing experiment, 5:506–507 history and goals of, 5:502 ideal tracer characteristics, 5:502 through karst systems, 5:240–241 tracer types, 5:502–507 Ground-Water Treatment Rule, 1:72 Groundwater transport of bacteria, 5:350–352 in karst systems, 5:237–238 processes, 5:516–517 Groundwater University (GU), 4:714 Groundwater vulnerability, 5:561–562 assessing, 5:562 characterization of, 5:563–565 factors in, 5:562–563 models, 5:358 to pesticides, 5:594–599 Groundwater vulnerability assessment (VA), 1:527 Groundwater withdrawal, stages of, 5:576 Group of Experts on the Scientific Aspects of Marine Pollution (GESAMP), 4:109 Grouting, 1:881–882 Growing areas, shellfish, 2:361–362 Growth-linked biodegradation, 2:42 GSTAR computer models, 3:389 Guided random search method, 2:333 Guinea worm, 1:26 Gulf of Mexico, gaseous hydrocarbon seepage in, 4:99 Gulf Stream, discovery of, 4:780–782 Gullies characterization of, 3:183–184 continuous and discontinuous, 3:184–185 initiation of, 3:187 sediment yields from, 3:184–185 Gully erosion, 3:183–188 causes of, 3:185–187 effects of, 3:187–188 processes associated with, 3:184–185 Gully formation, 3:87 deductive model of, 3:185–186 Gully plugs, 2:550 Gully pot effluent treatment, 3:499 Gunite, 1:802, 880 Gutters, 1:56–58 design methods for, 1:57–58

761

flow division within, 1:57 outlet depths for, 1:56–57 GWLF model, 5:298

H2 economy, 4:477–480. See also Hydrogen entries Habitat(s) alterations of, 3:126 coral reef, 4:114 deepwater, 3:496–498 microorganism, 3:310–311 research on, 4:55–57 as a watershed function, 3:477 Habitat conservation, precautionary principle regarding, 2:600. See also Environmental entries; Habitat preservation Habitat preservation, fishery-related, 3:128. See also Habitat conservation Habitat restoration/enhancement, water reuse for, 1:818 Habitats methods, for determining environmental water requirements, 3:167 Hack’s law, 3:94 Hagen–Poiselle formula, 3:195 Haloacetaldehydes, health effects of, 1:268–269 Haloacetic acids (HAAs), 2:91–92 bromide influence on formation of, 2:74–79 brominated, 2:75 health effects of, 1:264, 266–268 Haloacetonitriles, health effects of, 1:267–268 Halocarbons, marine sources of, 4:149–151 Halogenated byproducts, 1:199 Halogenated methanes, measurements of, 4:149–150 Halogenated organic chemicals (HOC), phytoremediation research on, 3:368 Haloketones, health effects of, 1:268–269 Halomethanes, health effects of, 1:264–266 Halophytes, 3:686 Hamoon Wetlands hydraulic-hydrologic system, 3:563–564 Hantush and Jacob method, 5:494–495

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762

CUMULATIVE INDEX

Harbor surveys, New York City, 1:745–751 Hardness, 5:406 of activated carbons, 1:96 defined, 2:543 of drinking water, 2:394 forms of, 4:553 role in fish growth and production, 3:131 Hardness salts, 1:545–546 removal of, 1:548 Hardwar, Uttaranchal, India groundwater contamination in, 5:202t groundwater quality in, 5:192–204 groundwater sampling locations in, 5:206t hydrochemical data from, 5:195t irrigation water quality in, 5:204–210 Hardware development, Marine Instrumentation Laboratory (MIL), 4:70–73 Hard water, 1:144, 322–323, 534–535, 902–903; 4:452–455 definition and specifications of, 4:453–454 forms of, 4:453 softening of, 4:454 worldwide cases of, 4:454–455 Hargreaves method, 3:575–576 Hartree–Fock (HF) method, 4:401 Harvesting, nitrogen losses from, 3:696 Harvest regulation, 3:124 in river fisheries, 3:125 Harvest restrictions, in fisheries, 3:129 Hatchery animals, success of, 4:126 Hathorn Spring, 4:799 Hawaii. See also Hawaiian Islands climate and water balance in, 4:255–263 Koppen climatic zones in, 4:256–259 soil moisture storage capacity for, 4:261 Hawaiian freshwater resources, history of, 4:801–807 Hawaiian Islands. See also Hawaii amphidromous fish species in, 4:803 climate patterns of, 4:802 ecosystems and endemism in, 4:802–803

endemic stream animals in, 4:803–804 freshwater resource use and management in, 4:804–805 geological origin of, 4:802 stream animal communities in, 4:803 surface water removal in, 4:804 water law in, 4:805–806 Hawaiian stream habitats, degradation of, 4:806 Hawaiian streams, freshwater animals of, 4:804t Hawk Mountain Sanctuary Association, 3:518, 519 Hazard assessment critical control point (HACCP) risk assessment approach, 1:425f Hazardous air pollutants (HAPs), 1:555 Hazardous chemical bioaccumulation, in urban stormwater runoff, 3:435 Hazardous solid wastes, solidification/ stabilization of, 1:835–840 Hazardous substance liability, 4:665 Hazardous waste management, bioremediation in, 5:116 Hazardous waste sites, monitoring, 5:587–588 Hazen–William roughness factors, 3:314, 315 Hazen–Williams formula, 3:197 values of C for, 3:198t H (basic) carbons, 1:98–99 Head, 5:180–182. See also Hydraulic head capillary and osmotic forces and, 5:180–181 fluid density and, 5:181 measurement, 5:474 spatial and temporal variation of, 5:181–182 Head loss, in diffused air aeration systems, 1:629 Headspace technique, 2:306 Headwater, 2:543 4 He age dating method, 4:390 Healing, water-instrument, 4:760–761 Health. See also Human health ecological, 2:182 impact of water on, 4:455–461, 722–726, 729

public water supply and, 1:501 soft water and, 4:554 waterborne pathogens and, 1:521–522 Health Advisories, 1:479 Health Assessment on Perchlorate, 2:345 Healthcare reforms, 1:190–191 Health effects of arsenic, 2:15–18 of bromide, 2:74 of chlorine and chlorination byproducts, 2:92 of cobalt, 5:612 of disinfection byproducts, 1:264–277 of lead, 2:432–440 of microbial contaminants and biotoxins in drinking water, 1:277–281 of nitrate, 1:30–42 of polychlorinated biphenyls, 2:107 of uranium, 5:641 of vinyl chloride, 5:636–637 of water pollution, 2:617 Health hazards, 1:293. See also Health risks; Hygienic hazards Health issues. See also Human health algae-related, 3:188–190 iron-related, 4:497 Health precautions, for chemical oxidants, 5:348–349 Health risk reduction and cost analysis (HRRCA), 1:425, 479; 4:541, 546 for radon, 4:546 Health risks. See also Health hazards; Health risk reduction and cost analysis (HRRCA) of cadmium, 5:615 of heavy metals, 5:279t of lead, 5:646–647 of mercury, 5:643–644 of MtBE, 5:318 of nitrate, 5:629 of perchlorate, 5:632 of radionuclides, 1:395–396 of radon, 4:543, 544 reduction of, 1:427 of wastewater reclamation, 1:826 Heat effect on physical properties and reaction kinetics, 5:173–175

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CUMULATIVE INDEX

enhancement, 5:117 role in groundwater systems, 5:172–175 Heat balance formulation of, 3:191 meteorologic driving factors in, 3:191 of open waterbodies, 3:190–194 Heat dissipation soil moisture measurement, 4:488 Heated waters, discharge of, 4:105 Heat flux densities, sensible and latent, 3:563 Heat fluxes of long-wave radiation, 3:192 relationship to meteorologic fields, 3:191–193 Heat of vaporization, 4:263–265 Heat transfer/equipment problems, water treatment and, 1:599–600 Heavy metal anions, biosorption of, 2:72 Heavy metal contamination in situ groundwater remediation for, 5:290–293 prevention of, 5:278 Heavy metal efflux, landfill disposal practices and, 1:726 Heavy metal ion removal, by ion exchangers, 4:494t Heavy metal pollution, 2:407 in Far Eastern Russia seas, 2:447 Heavy metal removal technologies, performance characteristics of, 2:69t Heavy metals, 4:506–507. See also Iron entries; Manganese entries; Mercury removal; Metal entries in an agricultural landscape, 3:607–608 in constructed wetlands, 1:894 disease and, 3:295–296 environmental sources of, 5:276–277 health risks associated with, 5:279t immobilization processes for, 5:378 in Indian rivers, 3:449 management and remediation alternatives for, 5:278–279 microbial biosurvey detection of, 2:442–443, 445, 446 mobility of, 5:277–278 phytoremediation of, 5:376–381 precipitation/crystallization/ mineralization of, 5:378

regulation of, 4:598–599 removal of, 3:368 in river systems, 3:295 risk assessment of, 5:278 soil and water contamination by, 5:275–280 sorption of, 1:111 toxicity, 3:609–610 transfer of, 3:608 uptake and intercellular sequestration of, 5:378 uptake rates of, 2:211–219 in urban stormwater runoff, 3:433 as water pollution, 4:99–100 as water quality indicators, 2:266 Heavy metal sorbents, 1:586 Heavy metal toxicity detection, microbial enzyme assays for, 2:233–238 Heavy oil sorption, 2:363 Heavy water, 4:462–466. See also Deuterium applications of, 4:463–464 behavior of, 4:463 biological and biotechnological applications of, 4:464 characteristics of, 4:462–463 production of, 4:464–465 worldwide production of, 4:465 HEC-HMS hydrologic model, 3:157, 158 Hedonic price model, 4:609 Helley–Smith pressure-difference bed load sampler, 3:400 Helminths, 1:904 in domestic sewage, 1:831 Hematopoietic effects of lead, 2:437 Hemolytic uremic syndrome (HUS), 1:181; 2:136–137 Hemorrhagic colitis (HC), 1:180–181; 2:136 Hemorrhagic Escherichia coli outbreak, 1:341 Henry, William, 4:466 Henry’s law, 1:576, 577; 4:466–467 limitations and application of, 4:467 Henry’s law constants, 1:761; 4:522; 5:428 Hepatitis, 1:181, 341 Hepatitis virus, 1:279 Hepatotoxins, 2:388; 3:189 Heptachlor epoxide, 3:352, 649 Herbicides, 3:482

763

agricultural productivity and, 4:507 in algal control, 2:5 alternative, 4:506 commonly observed, 5:252 tile drainage and, 3:729 weed-control, 3:745t Herbivorous fish, 3:746 Heterogeneity, 5:509 Heterogeneous freezing, 4:585 Heterogeneous photocatalysis, 1:791–792 Heterogenetic sediments, groundwater flow in, 5:175–177 Heterotrophic bacteria, 2:21, 175 Heterotrophic microorganisms/microbes, 2:38, 448t; 3:311 Heterotrophic nitrification, 3:641 Heterotrophic plate count bacteria, 1:222–223 Heterotrophic plate counts (HPCs), 1:86 Hexachlorobenzene (HCB), 3:352 Hexavalent chromium, 4:515–516 samples, 2:309 removal of, 4:587 Hg (II) ion sorption, 4:494 H–He dating, 5:65–69. See also Tritium/helium ratios analytical measurement methods for, 5:68 principles of, 5:66–68 versus CFC dating, 5:68–69 versus 85 Kr dating, 5:68–69,249 Hidden water sources, in the home, 2:527–528 Higee aeration, 1:353 High-density polyethylene (HDPE) landfill liners, 2:164–165 High density sludge (HDS) process, 1:610 Higher-order degradation behavior, 5:32 Higher plants metal tolerance and accumulation in, 5:284–290 trace elements in, 3:456 Higher water retention, 1:406 High level waste, versus average rock, 5:450–451 Highly impacted soil zone (HISZ), 3:688

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764

CUMULATIVE INDEX

High-performance liquid chromatography (HPLC), 2:308, 389 High pH groundwater, 5:362–365 High-precision deuterium analysis, 4:439 High rate anaerobic treatment systems, 1:908t High-rate granular filtration, 1:250–251, 487 High rate treatment systems, 1:841, 842t High-resolution sea floor surveys, 4:77–78 High-salt-content water sources, microirrigation and, 3:618 High seas fisheries management, 3:126–127 High-throughput technologies, biomonitoring and, 2:59–62 High volcanic islands, perched groundwater in, 5:353 High water table, ill effects of, 3:601–602 Himalayas, 2:559 river systems in, 2:560 Hin primers, 2:338 Historic Area Remediation Site (HARS), New York City, 4:77–80 changes in, 4:79–80 images of, 4:78 sea floor of, 4:78–79 H-1i primers, 2:338 Hoarfrost, 4:241 Ho Chi Minh City water environment and pollution in, 2:552–553 water resource management in, 2:552–554 water supply and distribution in, 2:553–554 Hofmeister effects, 4:468–471 explanation of, 4:469 Holistic management, 3:33 of freshwater fisheries, 3:134–135 Holistic methods, for determining environmental water requirements, 3:167 Hollows, agriculture of, 4:695–697 Hollow-stem auger water well drilling, 5:106 Holometabolous insects, 3:51 Holomixis, 3:266, 267 Holoplankton, 4:155

Home hidden water sources in, 2:527–528 water conservation in, 2:664–666 Home aeration methods, 1:51–52 Homeland Security Act, 2:347 Homeland security initiatives, 1:800 Homeostasis, impact of water on, 4:455–461 Homogeneous nucleation, 5:569–570 Hoover Dam, 2:554–555 history of, 4:732–733 Hopper-dredge disposal, 2:123–124 Horizontal collector wells, 5:88–89 Horizontal directionally drilled (HDD) wells, 5:408 Horizontal drainage layers, levee, 3:290 Horizontal drains, design criteria for, 5:97–99 Horizontal drilling, 5:179 Horizontal-flow constructed wetlands, 1:895 Horizontal groundwater flow, 5:511 Horizontal louver screens, 5:572–573 Horizontal pipe drainage systems, 3:731–732 Horizontal profiling, 5:446–447 Horizontal(-flow) roughing filters (HRFs), 1:237–238, 239, 241 Horizontal subsurface drainage, 5:95 Horizontal wells, 5:177–178 advantages of, 5:180 drilling, 5:106 in groundwater remediation, 5:178–180 Hormones, in animal farming operations, 3:540 Horn, Roni, 4:768–769 Horology, 4:704 Hortillonnages, 4:697–698 Hortonian runoff, 3:566 Horton’s double exponential, 3:23 Horton’s laws of drainage composition, 3:32, 93, 438 Hot springs, 5:475–477 Hourly digital product (HDP) rainfall estimates, 4:310 Household drinking water, treatment and safe storage of, 1:67–70 Households, gray water reuse in, 1:16–19 Household wastewater, characteristics of, 1:677t

Household water consumption, developed countries, 1:506f Household water efficiency, 2:635 Household water meters, 1:490–491 HSPFEXP system, 5:297 HSPF model, 5:297, 298, 332 Huayuankou composition of floods in, 3:47t flood frequency analysis at, 3:46t Hubenov Reservoir, biomanipulation trials in, 2:53t Hudson’s formula, 4:15, 16 Huelva coast, storm record on, 4:339–341 Human activities contamination from, 2:489 effect on trace elements, 3:457–458 impacts on groundwater quality, 5:250 influence on the hydrologic cycle, 4:280–283 most water demanding, 2:489 pollution caused by, 3:223–224 role in river water chemistry, 4:374 sedimentation and, 4:107 as a threat to corals, 4:33 in the water cycle, 4:244 Human body, water shortage in, 4:789–791. See also Body Human disturbance, quantifying, 3:39 Human exposure, to reclaimed irrigation, 3:670 Human/fish relationship, history of, 3:122–123 Human health. See also Health entries basic water requirements for, 1:22–23 nitrogen loading and, 3:696 role of water scarcity and stress in, 1:20–22 water and, 1:19–30 Human infections, Escherichia coli shedding patterns in, 2:137–138 Human interference, runoff pollution caused by, 3:225–226 Human rights, water-related, 4:769–772 Humans effect on the hydrosphere, 4:285–286 effects of cadmium on, 5:615–616 marine debris hazard to, 4:40

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CUMULATIVE INDEX

toxicity of lead to, 2:435–437 vulnerability to pollutant discharge, 3:284 Human safety, weed control and, 3:744 Human waste disposal, 1:27 Human water consumption, categories of, 2:370, 614 Humic acid(s), 1:794; 4:399; 5:188 isolation and purification of, 5:189–190 origin, stability, and mobility of, 5:190–191 properties of, 2:205–206; 5:189, 190–191 Humic colloids, 2:105–106 Humic/fulvic acid complexation to, 2:207–208 inorganic colloids stabilized by, 2:208–209 Humic substances (HS), 4:399–400; 5:337 concentrations of, 4:450 mobility in groundwater, 5:188–192 Humidity absolute, 4:269–270 relative, 4:270–274 Humidity indexes, alternative, 4:273–274 Humidity Sounder for Brazil (HSB), 4:216, 351 Humidity statistics, Chicago Station, 5:79t Humid tropical climatic zone, 4:256–257 Humin, 4:399 Hurricane Emily, 4:274f, 275f forecasting, 4:275 Hurricane Research Division (NOAA), 4:5–6 Hurricanes estimating maximum significant wave height during, 4:2–3 estimating maximum sustained wind speed during, 4:2 modeling of, 4:274–275 theory of, 4:353–354 Hurst coefficient, 3:212 Hurst phenomenon, 3:210–221, 261 importance of, 3:215–216 physical explanations of, 3:212–215 stochastic representation of, 3:211–212

time series for reproducing, 3:217–219 Hyallela azteca, 3:51, 52 Hydrant flow data collection table, sample, 3:317t Hydrant flow tests, 3:316 Hydrant-flushing program, 1:401 Hydrants, water distribution system, 1:208–209 Hydrated lime, 5:4 Hydrates, clathrate, 4:471–475 Hydration, 4:475–477 of hydrophobic molecules, 4:475–476 of ions, 4:476 Hydraulic age, 4:389 Hydraulic analysis, 3:431 Hydraulic calculations, in culvert design, 3:77–78. See also Hydraulic methods Hydraulic conductivity (K), 3:172; 4:485; 5:64, 184, 492, 526 conversion factors, 5:509t of groundwater, 5:128 unsaturated, 5:126 in the vadose zone, 5:537 Hydraulic conductivity/transmissibility, 5:507–514 Darcy’s law and, 5:507 effective, 5:510–512 estimation and measurement methods for, 5:512–514 geologic factors influencing, 5:508 permeability and, 5:508 representative values of, 5:508 units of, 5:508 variability in, 5:508–509 Hydraulic conductivity values, statistical treatment of, 5:510–512 Hydraulic construction, Caspian Sea level rise and, 2:482 Hydraulic depth, 3:347 Hydraulic design, of water distribution storage tanks, 1:448–449 Hydraulic dredging, 2:122 Hydraulic flocculation methods, 1:253–254 Hydraulic gradeline (HGL) values, 1:210 Hydraulic gradient, 5:171 Hydraulic habitats, 3:106 Hydraulic head, 5:169–172, 554

765

components of, 5:171 in a 3-D aquifer, 5:171 Hydraulic loading, 1:347–348 Hydraulic methods, for computing time of concentration, 3:470 Hydraulic network models, 3:313–320 calibration data sources for, 3:315–316 calibration model parameters for, 3:314–315 data collection for, 3:316 evaluating results of, 3:316–318 intended use of, 3:314 macrocalibration in, 3:318–319 microcalibration in, 3:319–320 sensitivity analysis in, 3:319 Hydraulic potential, 5:171 hydraulic head and, 5:171 Hydraulic properties characterization, 5:184–188 Hydraulic radius, 3:64 Hydraulic resistance, 5:492 Hydraulic retention time (HRT), 1:753 Hydraulics, 3:194–196 of pressurized flow, 3:196–199 roof drainage, 1:54–61 well, 5:182–183 Hydraulic shock. See Water hammer ‘‘Hydraulic society,’’ 3:587 Hydraulic turbine, 3:487–489 Hydraulic works, origin of, 4:738 HYDRO-35 method, 4:315 Hydroborders ethnopolitics and, 4:681–683 in South Asia, 4:681 Hydrocarbon fuel vapors, leaking, 5:552 Hydrocarbon phytoremediation, selecting plants and microorganisms for, 3:628–637 Hydrocarbon plumes, 5:44 Hydrocarbon remediation, 5:281. See also Hydrocarbon phytoremediation water-jetting drilling technologies for, 5:234–235 Hydrocarbons. See also Alicyclic hydrocarbons; Aliphatic hydrocarbons; Petroleum hydrocarbons; Polycyclic aromatic hydrocarbons (PAHs) adsorption of, 1:577–579; 5:46 classes of, 5:42–43

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766

CUMULATIVE INDEX

Hydrocarbons. (continued) degradation of, 1:692–694 destruction of, 1:579–581 dissolved and adsorbed, 5:46 plants that spur degradation of, 3:629 polycyclic aromatic, 1:571–575 separation of, 1:576–577 solubility in salt water, 4:559–561 solubility in water, 4:561– 564 treatment techniques for, 1:575–581 Hydrochemical classification, 2:396, 397f Hydrochemical models, 5:295–299 parameterization of, 5:297–298 properties of, 5:296–297 used in watershed ecology, 5:297t Hydroclones, 1:683 Hydrodynamic and Water Quality Model for Streams (CE-QUAL-RIV1) software, 2:328 Hydrodynamic dispersion, 5:33, 70, 273–274, 517, 525, 526 Hydrodynamic parameters, determining, 5:526 Hydrodynamic processes, 5:525 Hydrodynamic simulation, 2:256–259 Hydroelectric dams environmental disruptions related to, 4:267 South American, 4:642–643 Hydroelectric decision support system, 2:621–622 Hydroelectricity water use, 1:561–562 Hydroelectric plants, 2:568 Hydroelectric potential, Ganga Basin, 3:234 Hydroelectric power, 3:199–203; 4:729. See also Hydropower entries advantages and disadvantages of, 3:200 dams and, 3:199 generation issues related to, 3:200 in India, 2:565 quantitative facts concerning, 3:199–200 water use for, 2:543

Hydroelectric reservoirs, 3:182. See also Hydropower reservoirs as anthropogenic sources of GHGs, 3:203–210 GHG dynamics in, 3:204–207 GHG emissions from, 3:180–183, 203, 205–206 GHG production processes in, 3:206–207 Hydroelectric storage plants, 3:201 Hydrogen (H), 4:189. See also H2 economy Hydrogen bonds, 4:406, 511–512, 583 Hydrogen ion, 4:480–482 characteristics of, 4:481 importance of, 4:481–482 production in water, 4:481 Hydrogen ion concentration, 2:294–295; 4:482 measurement of, 4:481 Hydrogen isotopes, 4:438–439, 501 as groundwater tracers, 5:503 Hydrogen peroxide, 1:603–604, 913; 4:533; 5:344, 345, 348 bromate ion formation and, 1:361 groundwater remediation and, 4:445–448 health and safety precautions for, 5:348 Hydrogen sulfide, 3:341 gas, 5:407 generation, 1:911 modeling, 3:333–334 Hydrogeologic responses, to earthquakes, 5:113–114 Hydrogeologic settings, effect on viral movement, 1:71–72 Hydrogeology. See also Contaminant hydrogeology effect on natural attenuation, 5:586–587 environmental isotopes in, 5:227–234 forensic, 3:168–170 Hydrographic analysis, 3:26 Hydrographic area, as an operational unit of analysis, 2:613 Hydrograph recession selection algorithm automatic, 3:25–26 Hydrographs

incremental, 3:65 unit, 3:221–222 Hydroids, on surfaces, 1:541 Hydrologic activity, rates of, 4:287 Hydrological information system, real-time, 1:121–127 Hydrological methods, for determining environmental water requirements, 3:167 Hydrological networks, 3:461 Hydrological processes, 3:222–223, 659 peculiarities of, 3:425–426 Hydrological Simulation Program–FORTRAN (HSPF), 2:249–250, 326 Hydrological storage, 3:173 Hydrological tracers, dyes as, 3:95–101 Hydrologic cycle, 2:95, 656; 3:327, 477, 688; 4:275–283, 287–288, 584, 711. See also Global water cycle; Water cycle atmospheric, 4:181 changes in, 4:173–174 components of, 4:276–277 defined, 2:544 forest structure and, 3:171–172 groundwater in, 5:601 history of, 4:191 influences on, 4:280–283 interception process in, 3:236 mathematical representation of, 4:277–280 as a multi-phased journey, 4:192–193 role of aquifers in, 5:9 scales for studying, 4:277 water reserves in, 4:282t Hydrologic data transforming to real-time information, 1:123 uncertainty in, 2:621 Hydrologic drought, 4:208 Hydrologic ensembles, 2:621 Hydrologic equation, 4:279 Hydrologic feasibility assessment and design contaminant distribution characterization, 5:80–81 implications of, 5:85–86 phytocontainment, 5:76–77 phytohydraulic containment and treatment, 5:81–85

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CUMULATIVE INDEX

in phytoremediation, 5:76–87 vadose zone transport, 5:77–80 Hydrologic flow paths, acidification and, 3:5 Hydrologic flows, Great Lakes, 3:177–178 Hydrologic forecasting model, 2:622 Hydrologic history, 4:265–267 Hydrologic impacts, of evaporation, 4:225–226 Hydrologic information, availability of, 2:500–501 Hydrologic modeling (HYMO), 3:255, 533–534. See also Hydrologic models entropy theory for, 4:217–223 macroscale, 3:534–536 remote sensing and GIS application in, 2:535 Hydrologic models, use of field capacity in, 5:126 Hydrologic processes, in arid or semiarid lands, 5:75 Hydrologic networks, design of, 4:222 Hydrologic persistence, 3:210–221 effect of, 3:263 Hydrologic problems and perspectives, 4:267–269 Hydrologic sciences, advancements in, 4:266 Hydrologic soil groups, 3:30 Hydrologic systems engineering decisions concerning, 4:217 modeling of, 4:267 water contamination in, 5:60–63 Hydrologic thresholds, 3:229–232 identification and quantification of, 3:231 interdisciplinary research on, 3:231–232 Hydrologic watershed functions, 3:473–477 Hydrology Ganga Basin, 3:233–234 isotopic, 4:440 use of Mariotte bottle in, 4:503–504 order of discontinuity in, 3:239–241 postmining, 5:2 soil pipe, 5:403 submodel, 5:296 watershed, 3:472–479

Hydrology applications, remote sensing of, 4:319–327 Hydrology research, forest, 2:199 Hydrolysis, 1:518; 5:528 calcite solubility and, 4:412 in landfills, 1:696 in mine effluent remediation, 1:611 Hydrometeorological mechanisms, as a cause of flooding, 3:511 Hydrometer, 5:474 Hydronium ion, 4:482–483 Hydrophilic soil conditioners, 3:552 Hydrophobic bacteria, 5:351 Hydrophobicity, 1:761–762; 4:475–476,523–524 biodegradability and, 1:761–762; 4:524 toxicity and, 4:524 Hydrophobic molecules, hydration of, 4:475–476 Hydrophobic organic compounds (HOCs), 4:384 sorption on geosorbents, 4:384–387 Hydrophobic organic compound sorption, rate considerations in, 4:387–388 Hydroponic solutions, MtBE uptake and, 5:389–391 Hydropower, 2:554–555. See also Hydroelectric power greenhouse gas emissions from, 3:182f major producers of, 3:200t Hydropower potential developed, 3:199t estimating, 3:202 Hydropower projects components of, 3:200–201 load of, 3:202 types of, 3:201 Hydropower reservoirs, 3:202–203. See also Hydroelectric reservoirs Hydropsychology, 4:733–735 research in, 4:735 Hydrosphere, 4:283–286 biogeochemistry of, 4:284–285 effect of humans on, 4:285–286 Hydrostatic equilibrium, disturbance of, 4:367 Hydrostatic forces, 3:194 Hydrosystems, stochastic simulation of, 3:421–430 Hydrothermal phenomena, 5:156–157

767

Hydrous manganese oxide (HMO) filtration, 1:398 Hydroxide alkalinity, 4:410 calculation of, 4:410–411 Hydroxyl free radical, 4:446, 447, 533 Hydroxyl radicals, 5:344 HYDRUS code, 5:564 HYDRUS model, 5:663 Hyetograph analysis, 4:318 Hygienic hazards, sources of, 1:677. See also Health hazards Hygrometers, 4:273 HYMO flow routing model, 3:255. See also Hydrologic modeling (HYMO) Hyperaccumulating plants. See also Hyperaccumulators nutrient requirements of, 5:379–380 phytoextraction using, 5:369–374 Hyperaccumulation, lead, 5:382–383 Hyperaccumulation potential, of aquatic macrophytes, 2:66 Hyperaccumulators, 3:629–630; 5:366–367, 370. See also Hyperaccumulating plants metal, 5:288 selenium, 5:398 Hyperendemic disease, 1:187 Hyperfiltration, 1:631, 810 Hypertension, water intake and, 4:725 Hyperthermophilic bacteria, 3:311 Hypertonic solution, 4:459 Hypochlorites, 1:457; 2:88 Hypolimnetic hypoxia, 4:65 Hypothesis testing, entropy theory and, 4:220 Hypoxia factors affecting, 4:65–68 quantification of, 4:64–69 Hypoxic factor (HF), determining, 4:65 Hypsometric curve, 3:29 Hysteresis, 5:536

Ice, 4:285 floating, 4:69–70 Ice Ages, remains of, 4:305–306 Ice control, alternatives to NaCl for, 2:320t. See also Deicers Ice-covered lakes, heat transfer across, 3:191 Ice-jam floods, 3:45, 46, 511

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768

CUMULATIVE INDEX

Ice-melt recession, 3:24 Idaho source-water protection in, 2:312 stream flow statute, 4:661 Ideal adsorbed solution (IAS), 1:115 Ideal adsorbed solution theory (IAST), 1:109, 119 ‘‘Ideal’’ water tracer, 3:95 Idso–Jackson crop water stress index (CWSI), 3:720–721 Igneous rocks, 5:55 Ignorance, types of, 4:300–301 Illegal discharges, elimination of, 1:867 Illinois, overdraft in, 5:342–343 Immobilization technologies, 5:434, 439–441 Immunodetection methods, 2:109–110 Immunofluorescence assay (IFA), 1:159, 160, 165 Immunohistochemistry, 2:109 Immunologic assays/testing, 1:90–91 for Escherichia coli O157:H7, 2:139 Immunomagnetic separation (IMS), 1:159 Impact reduction, for net pen aquaculture systems, 3:543–544 Impellers, 3:664 advanced, 1:79f characteristics of, 1:80t performance data for, 1:80 types of, 1:76–80 Impermeable layer, 2:544 Impermeable materials, 5:600 Impervious cover, 3:363 Implicit pressure explicit saturation (IMPES) approach, 5:669 Import of virtual water, 2:536 Impoundments, blue-green algae blooms in, 3:188–190 Impregnated activated carbon (IAC), 1:93 Impulse turbines, 3:488 Inactive (dead) storage, 3:259 Inactive rock glaciers, 3:174 In-channel pumped storage development, 3:201–202 Incidental recharge, 5:75 Incineration, of sludge, 1:858–860, 866 Inclined drainage layers, 3:290 Inclined plates, 1:454 Incompressible flow problems, finite element schemes for, 5:657–658

Incompressible fluids, 5:559 Index-and-overlay methods, 5:563 Index models, 5:597 Index of Biotic Integrity (IBI), 2:25; 3:36–41. See also Biotic integrity entries India. See also Indian water markets climate of, 2:559–561 dilution in streams/rivers of, 3:84 floods and droughts in, 2:566–567 fluorosis in, 5:130–132 groundwater resources in, 2:562–564 groundwater quality in, 5:192–204 hydro-borders in, 4:681–683 irrigation water quality in, 2:155–161; 5:204–210 lake water pollution in, 3:451 major rivers in, 3:449f, 450t marginal cost pricing in, 2:558 national identity of, 4:684 promoting self-governing institutions in, 2:558 property rights in, 2:557 regions of, 2:559 river water pollution in, 3:447–451 subsurface drainage in, 5:94 surface water pollution in, 3:445–451 surface water resources of, 2:561–562 trace element groundwater contamination in, 2:143–148 water quantity regulation in, 2:557–558 water resource requirements for, 2:564–566 water resources of, 2:559–567 water stress and water scarcity in, 3:445–447, 448f well-spacing norms in, 2:558 Indian 1-MW OTEC plant, 4:48–49 Indian lands, reserved water rights for, 4:689–690 Indian river basins, assessment of nutrients from, 3:659–660. See also Ganga entries Indian water markets, 2:555–559 economic aspects of, 2:556 extent of, 2:556 legal aspects of, 2:556–557 nature of, 2:555–556 Indian wave energy program, 4:45–46

Indicator forms, harmful characteristics in, 2:443 Indicator groups, response to pollution, 2:441–442 Indicator monitoring, 2:267 Indicator organisms, 2:25, 292–294 coliform group, 2:293 in domestic sewage, 1:831–832 enterococcus group, 2:293 future of, 2:293–294 Indicators biotic, 3:37 efficient, 3:34 Indigenous people, water rights of, 4:771 Indirect potable reuse, 2:611 Indirect search method, 2:332 Indirect soil moisture measurement, 3:692 Indirect vadose zone monitoring methods, 5:539–541 Indirect wastewater reuse, 1:307, 826 Indirect water valuation approaches, 4:608–610 Indirect water valuation studies, 2:655 Indoor residential water use, 2:652 Induced polarization method, 5:147 Induction, of cytochrome P450 monooxygenase, 2:108 Induction logs, 5:152 Inductive conductivity measurement, 4:432 Inductively coupled plasma (ICP), 2:308, 309 Indus River, salinity profile of, 3:679. See also Indus Waters Treaty Industrial acidification, 3:9 Industrial activities, stormwater discharges from, 4:658 Industrial biocides, 1:602–603 Industrial byproducts, disposal of, 5:276 Industrial cooling water biofouling of, 1:538–542 corrosion in, 1:542–545 scale formation in, 1:545–549 Industrial development, Great Lakes region, 3:178 Industrial discharges. See also Industrial effluents Clean Water Act and, 1:755–756 daily toxicity variation of, 1:570t

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CUMULATIVE INDEX

Industrial effluents. See also Industrial discharges evaluation by on-line respirometry, 1:565–571 limits on, 1:552 Industrial environments, clathrate hydrates in, 4:473–474 Industrial field studies on mussels, 1:512 on veliger settling, 1:513 Industrial fluoride contamination sources, 5:132 Industrial hydrocarbons, complex, 5:43 Industrial input demands, economic theory of, 1:550 Industrial ion discharges, 1:752t Industrialized countries, water resources planning and management objectives for, 2:683 Industrial meters, 1:340 Industrial pollutants, 3:281–282 macrophytes as biomonitors of, 2:66 Industrial pollution, impact of, 4:107–108 Industrial Revolution public health during, 1:283–286 sanitation during, 1:282–283 Industrial storm water discharges, 1:867 Industrial wastes as a source of cultural eutrophication, 3:115 as water pollution, 4:97 Industrial wastewaters, 2:375 constructed wetlands for, 1:896 microfiltration of, 1:591–595 nutrient-deficient, 1:729t pretreatment of, 4:586 reuse of, 1:818 toxicity assessment of, 1:566 Industrial water demand economics, 1:549–553 empirical models in, 1:550–552 future research related to, 1:552 Industrial water demands, structure of, 1:551 Industrial water requirement, in India, 2:566 Industrial water use, 2:544 United States, 1:620–622; 2:652 Industry water conservation in, 2:496 water consumption in, 2:370–371

water-efficiency improvement in, 2:635 Indus Waters Treaty, 4:682. See also Indus River Infantile cyanosis (methemoglobinemia), 1:34, 35–36 Infant mortality, 1:27 Infaunal amphipods, 2:409, 410 Infection, fecal-oral cycle of, 2:112 Infection monitoring, versus disease monitoring, 1:189–190 Infectious diseases, waterborne, 1:177–183. See also Disease entries Infectivity assays, C. parvum, 1:166 Infiltration; 5:212 controls on, 4:484–486 defined, 2:544 for estimating stomatal aperture, 3:716–717 estimation of, 4:486–487 excess, 4:316 measurement of, 4:487 modeling, 4:486–487 quantification of, 5:663 soil moisture processes and, 4:484–489 soil water processes and, 5:210–212 storage capacity, 5:125 in the vadose zone, 5:534–535 Infiltration capacity, 3:474; 4:486; 5:212–213 Infiltration-excess overland flow, 3:452 Infiltration galleries, 3:416; 5:89 Infiltration rates, 5:212 on forest soils, 2:199 Infiltration systems, for storm water treatment, 1:868 Infiltrometers, 4:487; 5:214–216, 539 Inflow-outflow method, 5:166 Influent and effluent seepage, 5:167 Informal sector provision model, 1:51 Information concerning water quality issues, 1:509 corrosion control, 1:154 water conservation, 1:148–149 Information portals, 2:670 Infrared propagation, 4:296 Infrared satellite measurements, 4:323 Infrasound, 4:571

769

Infrastructure investing in improvements in, 1:871 in the Nile Basin, 2:593–594 pretreatment programs and protection of, 1:800 Ingested radon diffusion model, 4:544 Inhibition, effect on nitrification, 1:754t Initial and boundary problem, 5:621 Initial dilution, 4:104 Initial public offerings (IPOs), corporatized utility, 1:389 Injection wells, 2:544 drinking water contamination by, 2:286–287 In-lake blue-green algae controls, 3:189–190 Inland waters data, reports, and publications on, 3:11 rain-acidified, 3:8, 292 In-line drippers, 3:622 Inorganic adsorption, ion exchange and, 4:490–496 Inorganic chemical health issues, 1:822 Inorganic chemical monitoring, 2:267 Inorganic chemicals, 5:185 Inorganic coagulants, 4:425 Inorganic colloids, stabilized by humic/fulvic acid, 2:208–209 Inorganic compounds competitive sorption on activated carbon, 1:110–115 in domestic sewage, 1:831 technologies for, 1:463t Inorganic–humic agglomerates, metal ion binding to, 2:208 Inorganic ion removal adsorbents for, 4:494–495 factors affecting, 4:490–493 ion exchangers for, 4:494 Inorganic monomeric aluminum, episodic acidification and, 3:7 Inorganic phosphate corrosion inhibitors, 1:154 Inorganic phosphorus, 3:702 Inorganic phytoremediation verification protocol, 3:633–635 Inorganic pollutants, background concentration of, 2:19–20 Inorganic wastes, inhibitory threshold concentrations of, 1:754t

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770

CUMULATIVE INDEX

Input (forcing) uncertainty, 3:326 Insertion valves, 1:890 In situ biodegradation, 2:44 In situ biological treatment of perchlorate, 5:633 of vinyl chloride, 5:638 In situ bioremediation, 5:442–443 of contaminated groundwater, 5:38–42 costs of, 5:42 technologies for, 5:39–42 In situ chemical monitoring, 4:514–516 In situ chemical oxidation (ISCO), 4:445, 446 In situ chemical oxidation technologies, 5:344 In situ destruction technologies, 5:441–443 In situ dredged material characterization, 2:351–352 In situ electrokinetic remediation, of cadmium, 5:618–619. See also In situ groundwater bioremediation; In situ groundwater remediation; In situ metal remediation In situ electrokinetic treatment, 5:116–124, 329–330. See also In situ electrokinetic remediation; In situ physical/chemical treatment; In situ treatment technology achievable cleanup levels associated with, 5:121 case histories in, 5:121–123 of chromium, arsenic, and biofouling, 5:28 design of, 5:120–121 economics of, 5:121 field feasibility characterization for, 5:118–120 In situ groundwater bioremediation. See also In situ groundwater remediation; Natural attenuation bacterial transport in, 5:43–44 limitations of, 5:42–48 In situ groundwater remediation, 5:423–426. See also Groundwater remediation; In situ groundwater bioremediation by aeration and volatilization, 5:426–432 for heavy metal contamination, 5:290–293

hydrogeologic characterization for, 5:425–426 In situ iron filing curtain treatment, 5:329 In situ lining systems, 1:883 In situ metal/organic adsorption, 5:609–610 In situ metal remediation, biological methods of, 5:292–293 In situ monitoring, of odorous emissions, 2:282–283 In situ physical/chemical treatment, of vinyl chloride, 5:638–639 In situ rate coefficients, 5:523 In situ sediment toxicity assessments/test methods, 2:384; 3:54 In situ soil flushing, 5:435 In situ solidification/stabilization technology, 1:837 In situ treatment technology, 5:291–292 Instantaneous peak demand (IPD) curves, 1:213 Instantaneous samplers, 3:398 Instantaneous unit hydrograph (IUH), 4:356, 357 Instantaneous unit sediment graph (IUSG), 4:359 Institutional solutions, in the Arab World, 2:473–474 Institutional water conservation measures, 2:497 Institutions, irrigation and, 4:739–740 Instream flow incremental methodology (IFIM), 3:526 Instream flow methods, 3:526–527 Instream flows, 3:106 legal protection for, 4:659–664 In-stream values, federal law protection of, 4:663–664 Instream water use, 2:650, 661 Instrumentation CERES, 4:169–170 satellite-borne, 4:311–313 Instrument development, for in situ Cr(VI) monitoring, 4:515–516 Insurance, flood, 3:147 Intake systems, riverbed/seabed filtration, 5:89–91 Intake wells, 5:88–91 vertical, 5:88 Integrated capacity building (ICB) multicapital context of, 1:655–656

operational considerations for, 1:654–655 participatory, 1:652–654 role in watershed planning, 1:655f sanitation-related, 1:651–656 Integrated collector/storage solar water heater, 1:63–64 Integrated Economic and Environmental Satellite Account (IEESA), 2:627 Integrated modeling, 3:340 future of, 3:341–342 Integrated municipal watershed management (IMWM), 1:497–500 Integrated Pollution Prevention and Control (IPPC) Directive, 2:45–46 Integrated precipitable water vapor (IPW), calculating from GPS signal delays, 4:245–247 Integrated Risk Information System (IRIS), 1:426 Integrated treatment systems, 1:684 Integrated water quality modeling software tools, 2:328 Integrated water resources management (IWRM), 1:122; 2:263, 574–576, 627 Integrated watershed management (IWM), 1:651; 2:613, 627 Intensity-depth-frequency (IDF) curves, 4:315 Intensity-duration-frequency (IDF) curve, 3:157 Intensive farm systems, 3:579 Intensive partial molar internal energies, 4:363 Interbasin Water Transfer Act, 4:688 Interception, 3:235–238 consequences of underestimating, 3:238 determining evaporation from, 3:237–238 importance of, 3:236–237 Interdisciplinary research, on hydrologic thresholds, 3:231–232 Interdisciplinary water studies. See SUSTAINIS advanced study course Interfacial phenomena, 4:449 Intergenerational water resources, 4:771 Intergovernmental organizations (IGOs), water rights and, 4:771

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CUMULATIVE INDEX

Intergovernmental Panel on Climate Change (IPCC), 2:640; 3:208; 4:120 Report by, 2:483 Interim Enhanced Surface Water Treatment Rule (IESWTR), 1:233, 428; 2:195, 344 Interlaboratory precision tests, 2:459 Intermittent waters, 2:475 International Bottled Water Association (IBWA), 1:4 ‘‘Internal improvements,’’ American, 2:498–499 International Boundary and Water Commission (IBWC), 4:620, 644 International Coastal Cleanup (ICC), 4:39 International Conference on Freshwater, 3:33 International Conference on Water and the Environment, 4:606 International Coral Reef Initiative (ICRI), 4:115–116 International Decade for Natural Disaster Reduction (IDNDR), 3:153, 154 International experts/advisors, 1:719 International fishing waters, 3:532 International freshwater management, 4:636 International GPS Service (IGS) tracking stations, 4:250 International Humic Substances Society (IHSS), 4:399 International Joint Commission (IJC), 3:179; 4:618, 620–621 International Maritime Organization—London Convention (IMO-LC) ocean dumping reports, 4:144–149 International Network to Promote Household Drinking Water Treatment and Safe Storage, 1:68 International standards, water reuse, 3:670–672 International Strategy for Disaster Reduction (ISDR), 3:154–155 International treaties, 2:473, 597. See also International water treaties International Union for the Conservation of Nature (IUCN), 2:626–627

International Union of Pure and Applied Chemistry (IUPAC), 4:491, 525 International virtual water flows, calculating, 2:540 International Water Association (IWA) models, 1:732–733, 736–738 International water market, trends in, 2:568–570 International water resources management, Great Lakes region, 3:179 International Water Services Association (IWSA), 2:497 International water treaties, 2:618 Internet access gap, 2:670–671 Internet portals, water-related, 2:668–674 Internet sources, for inland-water-related data, reports, and publications, 3:11t Interparticle bridging, 4:425 Interstate commission compacts, drought management by, 2:585 Interstate Commission on the Potomac River Basin (ICPRB), 2:577 Interstate compacts, 4:613. See also Interstate water compact Interstate water compact, 2:503–504 Interstellar space, water in, 4:189–190 Interstitial water, 2:384 Intertidal macrofauna, seasonal coupling with, 4:73–77 Intertropical convergence zone (ITCZ), 4:225 Intestinal parasites, 1:159 Intracellular accumulation, of metals, 5:283 Intracellular biodegradation, 2:43 Intracellular fluid (ICF), 4:459 Intraparticle diffusion, 3:303; 4:567 Intrastate policies, 4:649 Intrastate regional authorities, drought management by, 2:585 Intrinsic permeability, 5:537 Intrinsic susceptibility, 5:595 Inventory agencies, federal, 4:650 Inverse mass balance models, 5:139 Inverse model, for parameter estimation, 1:135–136 Inversion, fog and, 4:239

771

Invertebrate Community Index (ICI), 3:39 Invertebrates, toxicity of lead to, 2:434 Investment, in security and infrastructure improvements, 1:871 In vitro bioassays, 2:280 In vitro cytotoxicity techniques, 2:413 In vitro fish studies, challenges and obstacles in, 3:116 In vitro response tests, 3:116 In vitro toxicology models, 3:117 In vivo bioassays, 2:280 Iodinated trihalomethanes, health effects of, 1:266 Iodine number, 1:98 Ion chromatography, 1:358 Ion discharges, industrial, 1:752t Ion exchange, 1:297–301, 380, 725, 812, 827; 5:527 adsorption mechanism in, 4:493–494 advantages and limitations of, 1:297–298 for arsenic removal, 1:638–639; 5:21 for DOC removal, 1:325–330 inorganic adsorption and, 4:490–496 for iron and manganese removal, 1:315 in landfill leachates, 1:707 potential, 5:185 for radioactive waste, 1:804 for radionuclide removal, 1:397 in small drinking water systems, 1:459–460 Ion exchange resins, 1:413 Ion exchangers for inorganic ion removal, 4:494 removal of heavy metal ions by, 4:494t Ion exchange technology, for arsenic treatment, 5:23–24 Ionic concentration, in groundwater tracing, 5:503–504 Ionization, 5:527 Ionizing irradiation, 1:873 Ion precipitation, kinetic formulations for, 5:416t Ions. See also Hydrogen ion entries hydration of, 4:476 in seawater, 4:159–160

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772

CUMULATIVE INDEX

Ion-selective field effect transistor (ISFET), 2:298–299 IRC International Water and Sanitation Centre websites, 2:669 Ireland, mine wastewater treatment in, 1:897–900 Iron (Fe), 4:496–499. See also Ferric hydroxides; Iron removal arsenic removal using, 1:636 biofouling, 5:36 chemistry of, 4:496–497 complexing, 5:609 concentration of, 4:498 environmental impact of, 5:608–610 forms of, 1:313 in groundwater, 5:406 health and regulatory issues related to, 4:497 levels and solubility in water, 4:497–498 methods for determining, 4:498–499 oxidation, 5:609 oxidation states of, 4:534 problems caused by, 1:313 removing from water, 4:499 Iron acrylate foulant, 1:418t Iron bacteria, 5:22, 407. See also Iron-oxidizing bacteria; Iron-related bacteria (IRB) biofouling and water color caused by, 2:151–152 metabolic activities of, 2:153 Iron-bearing minerals, 5:345 Iron coprecipitation, of arsenate, 5:20 Iron corrosion, 1:544 Iron filing curtain treatment, 5:329 Iron industry, impact on surface water quality, 3:374 Iron oxidation rates, 2:152 Iron oxide coated sand, adsorptive filtration using, 1:639 Iron oxides, 5:609–610 Iron-oxidizing bacteria, 2:149–152. See also Iron- reducing bacteria in acid mining drainage, 2:150–151 in groundwater and surface water, 2:150 Iron precipitation, 5:422 Iron pyrite (FeS2 ), 3:13. See also Pyrite Iron-reducing bacteria, 2:151

Iron-reducing to sulfate-reducing conditions, 5:583 Iron-related bacteria (IRB), 1:84 Iron removal, 1:312–315 alternative treatments for, 1:314–315 ammonia and manganese inhibition of, 2:153–154 cartridge filters for, 2:152–155 common treatment processes for, 1:313–314 using ozone, 1:354–355 Iron removal systems, biological, 2:152–153 Iron salts, coagulation using, 1:636 Iron sulfides, formation of, 5:36 Irradiation, ultraviolet, 1:469–470. See also Ultrasonic irradiation; Ultraviolet entries Irreversible specific toxicity, 2:415 Irrigated agriculture, 2:635; 3:559–560, 673 sustainability and future of, 3:584–585 Irrigated land, maintaining salt balance on, 3:677–681 Irrigated regions, tile drainage in, 3:731 Irrigation. See also Irrigation management; Irrigation performance assessment; Irrigation water; Microirrigation agricultural, 1:818 in the Central Asian plains, 3:17–18 civilization and, 4:737 defined, 2:544 diversions of, 2:617–618 efficiency of, 2:495; 3:555–556 extent of, 3:581 first world history of, 4:736–740 groundwater for, 2:156 in India, 2:565 influence on nitrate content, 3:638 managing, 2:186 methods of, 2:375; 3:581–582 objectives of, 3:582–583 sand abstraction for, 3:413 sprinkler, 3:712–714 trends in, 3:586–587 in the United States, 3:586–594 water management and, 4:771–772 in Western states, 3:587 Irrigation areas, major, 3:581–586

Irrigation management, 3:583–584 Irrigation performance assessment, 3:583 Irrigation practices, reclaimed, 3:669–670 Irrigation regulations, Islamic, 4:635 Irrigation-system maintenance, 3:554 Irrigation techniques, farming and, 3:591–594 Irrigation water, 2:370 annual use of, 2:653 efficiency and management of, 2:572, 617 electrical conductivity for, 2:159t presence of salts in, 3:678 quality of, 2:155–161, 371 use of, 2:544 Irrigation water quality, in Hardwar, Uttaranchal, India, 5:204–210 Irrigation wells, 3:594–595 Islamic law, water management prescriptions in, 2:474. See also Islamic water law Islamic water law, 4:634–636 Island Reports (Mediterranean), 2:640–641 Isochrones, 3:61–62 Isochrone spacing methods, 3:63–64 Isoelectric point (IEP), 4:509, 511 Isohyetal map, 4:291 software, 4:292 Isohyetal method, 4:290–292 Isolation technologies, 5:433 Isoparametric transformation mapping scheme, 5:657 Isotherm models, 4:385t Isotherms, adsorption, 1:99–101. See also Freundlich adsorption isotherms; Langmuir adsorption isotherms; Mathews and Weber multicomponent isotherm model Isotope equilibration, 4:540 Isotope exchange, in gas-water reactions, 4:535–541 Isotope exchange rate, S-state dependence on, 4:537–540 Isotope fractionation, 4:500–503. See also Isotope separation artificial, 4:502 curve, 4:501 Isotope ratio mass spectrometry (IRMS), 1:645

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CUMULATIVE INDEX

Isotopes, 4:499–500. See also Carbon isotopes; Chlorine isotopes; Environmental isotopes; Nitrogen isotopes; Oxygen isotopes; Radioactive isotopes; Radionuclides; Stable isotopes; Sulphur isotopes; Uranium series isotopes in contaminant hydrogeology, 5:216–227 as groundwater tracers, 5:502–504 hydrogen, 4:438–439 hydrology of, 5:217 naturally occurring, 5:232 new applications of, 5:218 stable and unstable, 1:803 strontium, 4:574–578 technetium, 4:578–579 Isotope separation, 4:500, 502. See also Isotope fractionation techniques for, 4:502–503 Isotopic composition, dependencies of, 5:230 Isotopic fractionation, 5:229–230 Isotopic hydrology, 4:440 Isotopic techniques, for base flow separation, 3:27 Israel public works projects of, 4:699 reclaimed water usage regulations in, 3:672 water resources of, 4:699 Israeli-Arab water resources, 4:699–701 Israel–Jordan Treaty of Peace, 4:700 Israel-Syria water conflict, 4:754 IWR-MAIN water demand forecast model, 2:529, 530

Jacob’s well, 4:735–736 Jain and Snoeyink adsorption model, 1:108 Jaffna Peninsula, ancient wells in, 4:775–776 Jakarta, flooding in, 3:160 Jamin effect, 5:421 Japan, research on wave energy in, 4:45 Japan Sea, radioactive contaminant transport in, 3:322–323 Java activated sludge process simulator (JASS), 1:731–732 ‘‘Jet effect,’’ 3:80

Jetting, 5:234–235. See also Water-jetting drilling technologies technology, 5:234, 235 Joint entropy, 4:219 Joints rock, 5:136–137 water distribution system, 1:208 Joint venture water/sewerage contracts, 1:391 Joint Water Committee (JWC), 4:700 Joliet Army Ammunition Plant survey, 5:77–78 Joliet project, 3:44 Jordan Basin, 4:755–756 Jordan River watershed, 4:755–756 ‘‘Joseph effect,’’ 3:211 ‘‘Kair’’ farming, 3:164

Kansas, source-water protection in, 2:312 Karren, 5:244 Karst, 5:600. See also Epikarst; Karst topography defined, 5:108 groundwater dye tracing in, 5:107–111 Karst hydrology, 5:235–243 groundwater discharge in, 5:238–239 groundwater recharge in, 5:236 groundwater storage in, 5:238 groundwater tracing in, 5:240–241 groundwater transport in, 5:237–238 modeling of, 5:241 spring hydrograph and chemograph analysis in, 5:239–240 Karstic aquifers, 1:365–370; 5:237 calculating flow in, 1:368 Cryptosporidium in, 1:366–367 Giardia in, 1:367 Microsporidium in, 1:367–368 parasite fate and transport in, 1:365–370 volume of water in, 5:238 Karst landscapes, 5:236. See also Karst topography vulnerability of, 5:241 Karst topography, 5:243–248 bedrock dissolution in, 5:243–244 development of, 5:243 groundwater recharge in, 5:247

773

setting types in, 5:247 springs in, 5:245 subsurface features in, 5:245–246 surface features in, 5:244 valleys in, 5:245 vulnerability to contamination and pollution, 5:247 Kesterson Wildlife Refuge, heavy metals in, 5:276 ‘‘Keystone’’ predator, 4:153 ‘‘Khaki’’ farming, 3:164 Kick-sampling, 3:39 ‘‘Killer fog,’’ 4:379 Killing frosts, 4:241, 242 Kilowatt-hours, 3:202 Kinematic cascade, 3:249 shocks in, 3:241 Kinematics, 3:247 Kinematic shock, 3:239–242 determining, 3:249 formation of, 3:248–249 Kinematic time to equilibrium, 3:63 Kinematic viscosity, 5:556 Kinematic wave equation, 3:248 Kinematic wave flow routing, 3:253–259 numerical solution for, 3:254–257 Kinematic wave flux laws, 3:249 Kinematic wave method, for storm drainage design, 3:242–246 Kinematic wave model, 3:470 Kinematic wave speed, 3:253 Kinematic wave theory, 3:242–243, 247–249 validity of, 3:250–252 Kinetic analysis, 2:71 Kinetic modeling, 5:414–415 equilibrium and, 4:565–567 Kinetic processes, in water quality models, 2:271 Kinetic reactive transport models, 5:519 Kinetics chlorine reaction, 1:131–132 of metal ion–humic colloid interaction, 2:209–210 multicomponent, 1:119 sorption, 4:564–569 Kinetic studies, 4:565 Kirpich formula, 3:471 Klepsydras, 4:704, 705 Knowledge portals, 2:670 Knowledge transfer, 1:719 Kona coast, rainfall in, 4:257 Koppen climatic zones, 4:256–259

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774

CUMULATIVE INDEX

Koran, water references in, 4:746 Kousiss flow routing model, 3:257 85 Kr anthropogenic sources and atmospheric distribution of, 5:248 detecting modern groundwaters with, 5:248–249 production mechanisms and decay behavior of, 5:248 Krasheninnikov Bay, environmental quality of, 2:451t 85 Kr dating method characteristics of, 5:248–249 versus CFC dating methods, 5:249 versus H–He dating, 5:68–69, 249 Krypton. See 85 Kr entries Kyoto Protocol, 1:560

Labeled substrate probes, 1:645–646 Lability, of metal species, 2:212 Laboratory safety, 2:161–163 Laboratory testing for levee construction, 3:286–287 toxicity, 4:112 Lacustrine valleys, 3:66 Ladyzhenskaya–Babuska–Brezzi (LBB) stability condition, 5:658 Lagergren rate constants, 3:302, 303t Lagooning, 1:324–325 Lagrangian coordinate system, 5:558 Lagrangian drifters, 4:71 Lagrangian models, 1:133 Lake and pond water, 2:95 Lake Baikal climatic variations in, 3:21 environmental and geological settings of, 3:20 future drilling sites in, 3:21–22 Lake Baikal rift system cooperative studies of, 3:20 studies of, 3:20–22 understanding, 3:20 Lake basins, origin of, 3:265. See also Basin entries Lake Bleiswijkse Zoom, biomanipulation trials in, 2:55t Lake Bysj¨on, biomanipulation trials in, 2:54t Lake Cristina, biomanipulation trials in, 2:54t Lake districts, from low altitude glaciations, 3:265

Lake Duiningermeer, biomanipulation trials in, 2:55t Lake ecosystems, 3:267–269 alternative stable states theory regarding, 3:272–274 Lake Feldberger, biomanipulation trials in, 2:57t Lake fisheries management, 3:125 Lake Froylandsvatn, biomanipulation trials in, 2:56t Lake Gjersjøen, biomanipulation trials in, 2:54t Lake Haugatjern, biomanipulation trials in, 2:54t Lake Lilla Stocke-lidsvatten, biomanipulation trials in, 2:53t Lake Mead, 2:555 Lake Michigan, 3:274–275 biomanipulation trials in, 2:53t, 56t NOAA lake level forecast for, 3:274–275 Lake Michigan Wireless Environmental Observatory, 4:72–73 Lake Mosvatn, biomanipulation trials in, 2:54t Lake Number, 3:266 Lake Okeechobee, 3:279 Lake Orta, Italy, industrial acidification of, 3:9 Lake plankton, food chains, filtrators, and size spectra in, 3:268–269 Lake Pontchartrain and Vicinity Hurricane Protection Project, 3:284–285 Lake purification, 2:50 Lake restoration methods, classification of, 2:50 ¨ Lake Rusutjarvi, biomanipulation trials in, 2:56t Lakes, 3:265–272; 4:285. See also Lacustrine valleys acidic hypersaline, 3:9–10 acidified, 3:9, 10 blue-green algae blooms in, 3:188–190 Canadian, 2:658–660 chronic acidification of, 3:3 climatic zones and, 3:266–267 composition of, 4:285 discharges to, 3:281–284 ecosystems of, 3:267–269 glacial, 3:269–270 management of, 3:125

man-made, 3:270, 293 physical characteristics of, 3:282–283 pollutant fate in, 3:283 polluted discharges into, 3:281 programs for protecting, 3:270–271 regional limnology of, 3:269–270 responses to earthquakes, 5:112–113 stratification and mixing in, 3:266–267 submerged aquatic plants in, 3:275–281 trophic state and productivity of, 3:267–268 tropical and ancient, 3:270 water budget and salin1ty of, 3:266 water quality impairment in, 3:275 waves and oscillations in, 3:267 Lake sediments, pollutant deposition into, 3:283 Lake Severson, biomanipulation trials in, 2:53t ˚ Lake SøbygArd, biomanipulation trials in, 2:55t Lake Tenkiller model, 2:260–262 Lake Trummen, biomanipulation trials in, 2:53t Lake Væng, biomanipulation trials in, 2:54t Lake Vostok, 3:503–507 bacterial cell densities in, 3:506 Lake Washington, biomanipulation trials in, 2:53t Lake water(s) degradation of, 3:283 sodium in, 4:552 Lake water pollution, in India, 3:451 Lakewide Management Plans (LaMPs), 3:179 Lake Wolderwijd, biomanipulation trials in, 2:55t Lake Zwemlust, biomanipulation trials in, 2:55t Lambert–Beer law, 3:192 Laminar flow, 3:195; 5:649–655 determination of, 5:63 Laminar flow systems, equations of change in, 5:651 Land and water management agencies, federal, 4:650t Land Data Assimilation System (LDAS), 2:588–589

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CUMULATIVE INDEX

Land degradation processes, remote sensing and GIS application in, 2:534 Land development activities, stream quality and, 3:442 Land disposal, 5:254 Land drainage, 5:99 Land Evaluation and Site Assessment (LESA) system, 3:596 Landfill buffer land, 2:166 Landfill design, bioreactor, 5:257 Landfill disposal practices, influence on metal speciation and mobility, 1:723–728. See also Landfilling Landfill gas collecting, 2:168 from municipal solid waste landfills, 2:165–166 Landfill gas migration, 5:256 controls on, 5:256 Landfilling of sludge, 1:860 using pesticide-contaminated soil, 3:653 Landfill leachates, 1:699–713; 5:277. See also Landfill leachate treatment; Leachate entries characteristics of, 1:701–702 constructed wetlands for, 1:896 contamination by, 5:255 generation of, 1:700–701 recirculation of, 1:708 Landfill leachate treatment activated carbon in, 1:105 biological processes for, 1:703–704 physical–chemical, 1:704–708 selecting processes for, 1:708–713 Landfill pollutant loadings, equalization of, 1:705 Landfill-polluted environments, metal-organic interaction in, 5:259–260 Landfill-polluted water, 5:259 Landfill regulations, 2:166–167 Landfills, 1:695–699 bioreactor technology for, 1:727 components of, 1:700f contamination from, 5:452 degradation cycle of, 1:725 design and construction of, 1:697 environmental impacts of, 1:696–697 groundwater contamination from, 5:253–258

groundwater remediation related to, 5:257 inefficiency of, 1:696 municipal solid waste, 2:163–169 pollution prevention related to, 5:256–257 refuse decomposition microbiology in, 1:695–696 uncontrolled runoff impacts from, 5:256 Landfill system, 1:724f Land-grant colleges/universities (LGUs), 3:597–598 Land improvement works, 1:403 Land management practices, in the 1930s, 2:511–512 Land-ocean-atmospheric system, 3:230 Land–ocean interaction in the coastal zone (LOICZ) methodology, 4:53–54 Land reclamation, in acid mine drainage, 5:2 Land resources. See Poor-quality land resources Land runoff, as a nutrient source, 3:110–111 Landscape irrigation of, 2:651 root zone components of, 3:706 Landscape analysis, 4:315 Landscape plants, 3:706 Landscape process studies, 4:267 Landscape water-conservation techniques, 3:553–557 definitions related to, 3:553 drought or maximum heat-day practices, 3:555 postdrought or maximum heat-day practices, 3:555 predrought/premaximum heat-day practices, 3:554–555 two-track strategy for, 3:554–557 water budget program, 3:554–557 Landscape water management, 3:751 Landside berms, 3:290 Landside seepage berms, 3:289 Landslide dam pools, 3:69 Landslide warning systems, 1:125–126 Land surface, rainfall partitioning at, 4:315–316 Land surface modeling, 3:533–537 evolution of, 3:534

775

framework for, 3:534–536 inputs and outputs related to, 3:536 Land Surface Models (LSMs), 2:588 Land surface precipitation, changes in, 4:173 Land topographic features, influence on waterlogging, 3:742 Land use effect on water quality, 2:169 Great Lakes area, 3:178–179 Land-use activities, as threats to groundwater quality, 2:183t Land-use changes, influence on the hydrologic cycle, 4:280–283 Land use classification, remote sensing and GIS application in, 2:532 Land use control, extraterritorial, 1:315–317 Land use data, 5:164 Land use impacts, on groundwater quality, 5:250–253 Land-use ordinances, flood-related, 3:147 Langelier saturation index (LSI), 1:206; 4:415 Langmuir adsorption isotherms, 1:101, 112, 113, 114t. See also Isotherms Langmuir coefficient, 3:99 Langmuir coefficient QSAR model, 3:99 Langmuir isotherm, 4:567–568 Langmuir isotherm constants, 1:114t Langmuir isotherm equation, 2:87; 4:566 Langmuir isotherm model, 3:300; 4:385 La Paz Agreement, 4:646 La Plata Basin, 4:642 Large area surface energy balance estimation, 3:560–565 data accuracy in, 3:564 Larvae, in marine toxicological testing, 4:42–43 Laser scans, of levees, 3:284–285 LAS surfactants, 1:670–672 Las Vegas, Nevada, overdraft in, 5:343 Latent heat flux, estimating, 4:2 Latent heat flux density, 3:563 Lateral connection repair, 1:888 Lateral radial wells, 5:106 Latin America. See also Americas

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776

CUMULATIVE INDEX

Latin America. (continued) transboundary waters in, 4:636–643 Web use in, 2:671–674 Latitude effect, 4:439 Law, irrigation, 4:739–740. See also Groundwater law; Water law Law of basin areas, 3:94 Law of stream lengths, 3:93–94 Law of the Sea Convention, 3:126 Law of stream numbers, 3:93 Lawrence Livermore National Laboratory (LLNL) report, 4:674 Laws, water sustainability, 2:627. See also Legal entries; Legislation; Regulations Lax–Wendroff scheme, 3:239, 241 Layered heterogeneity, 5:509 L (acidic) carbons, 1:98, 99 Leachate collection and removal, from municipal solid waste landfills, 2:164–165 Leachate composition, in landfills, 1:696–697. See also Landfill leachates Leachate landfill, 5:255 Leachate quality, treatment techniques based on, 1:709 Leachates, subtitle D landfill, 5:258–260 Leachate toxicity evaluation, 2:280 Leachate treatment plant, 1:710f Leach beds, alkaline, 5:7 LEACH code, 5:564 Leaching, 2:544; 5:260–263 of cement hydration products, 5:364–365 of nitrogen, 3:696 Leaching Estimation and Chemistry Model (LEACHM), 5:597 Leaching Potential Index (LPI), 5:597 Leaching practices, control of, 3:679 LEACHM model, 3:680 Lead (Pb). See also Pb bioavailability cardiovascular effects of, 2:436 chemistry, 5:367 ecotoxicological effects of, 2:433–435 effects on central nervous system, 2:435–436 effects on endocrine system, 2:436 effects on peripheral nervous system, 2:436 effects on renal system, 2:436

effects on reproduction, 2:436 as an environmental contaminant, 5:365–366 fate and transport of, 5:647 future research on, 2:437–438 in groundwater, 2:148; 5:645–649 guidelines and standards for, 5:647–648 health effects/risks of, 2:432–440; 5:381, 646–647 hematopoietic effects of, 2:437 intoxication by, 2:435 maximum contaminant level of, 2:234t movement in the environment, 2:433 neurological effects of, 2:435 poisoning by, 2:437 properties and uses of, 5:646 remediation of, 5:648 sources of, 2:433; 5:381 Lead arsenate, 5:646 Lead compounds, insoluble, 5:382 Lead concentration, along the Blackstone River, 2:259 Lead-contaminated soils chemistry of, 5:381–382 phytoextraction for, 5:382–383 phytostabilization for, 5:383 rhizofiltration for, 5:383 Lead phytoremediation, 5:381–385 advantages and limitations of, 5:385 future of, 5:368 plants and mechanisms used in, 5:384t role of synthetic chelates in, 5:383–385 trends in, 5:385 Lead uptake, from sediment pore water, 2:217 Leaf area index, 3:734–735 Leaf level transpiration, 3:735 Leaf stomatal conductance, 3:735 Leakage factor, 5:492 Leak detection and repair, 1:317–320; 2:663, 664–665 benefits of, 1:318 coordinating with other activities, 1:319 strategy for, 1:318–319 as a water conservation measure, 1:146–147 Leaking vapors, 5:552

Leaks. See also Leak detection and repair causes of, 1:318 sealing, 1:881–882 testing, 1:886–887 ‘‘Leaky aquifer,’’ 5:11 Lease contract (affermage) model, 1:50 Least squares method, 2:332 for determining base flow recession constants, 3:25 Lee partitioning array, 5:445 Legal considerations, in water quality management, 2:183 Legal protection, for in-stream flow, 4:659–664 Legal solutions, in the Arab World, 2:473 Legal system, Chinese, 2:486–487 Legendre transformation, 4:363, 364 Legionella, 1:278, 560 Legionella pneumophila, 1:18 Legionnaires’ disease, 1:181 Legislation. See also Federal legislation; Laws; Regulations drought-related, 2:578 extinction-related, 3:128 floatable debris-related, 4:39–40 water, 2:96 water-quality, 2:586 wetlands-related, 4:691 ‘‘Legislative’’ toxicity, 2:47 Le Gray, Gustave, 4:766–767 Legumes, nitrogen in, 3:695 Length heterogeneity PCR (LH-PCR), community profiling using, 1:643 Lentic waters, 2:544 Leptothrix ferrooxidans, 2:149 Levan and Vermeulen adsorption model, 1:109 Levee construction, 3:290 field investigation and laboratory testing related to, 3:286–287 Levee embankments, seepage through, 3:290 Levees, 2:544; 3:152 design of, 3:286–290 embankment design for, 3:287–288 for flood protection, 3:286–291 laser scans of, 3:284–285 rehabilitating, 3:290–291t settlement of, 3:289 stability increase measures for, 3:288–290

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CUMULATIVE INDEX

Level drains, falling water table between, 5:96 Levenberg–Marquardt method, 4:567 Lidar, 3:284–285 Lidar systems, 4:296–297 Life cycle costs, of diffused air aeration systems, 1:630 Life cycle tests, 3:52–54; 4:42 endpoints measured in, 3:53 setup and activity schedule for, 3:53t Life history method, 4:323 Life of a reservoir, sedimentation and, 3:409 Lifting condensation level (LCL), 4:369 Ligand chemicals, 2:236–237 Ligand groups, 2:204 Ligands, colloidal, 4:29 Light, microorganism growth and, 1:606; 3:311–312. See also Photon emitters; Ultraviolet entries Light nonaqueous phase liquids (LNAPLs), 5:216, 340, 439 Light Detection And Ranging (lidar), 3:284–285 Lightning rod experiment (Franklin), 4:742–745 Light penetration, effect on algal growth, 3:111 Light production, measuring, 2:48–49 Lime in acid mine treatment, 5:4 precipitation, 5:20 Lime neutralization, 1:610 Lime–soda ash processes, 1:320–322 chemical reactions of, 1:320–321 implementation and limitations of, 1:322 Lime–soda ash softening plant, 1:315 Lime softening, 1:322–325. See also Softening for arsenic removal, 1:636; 5:24 for corrosion control, 1:153 pretreatment for, 1:323 of radioactive waste, 1:804 radionuclide removal via, 1:397–398 requirements for, 1:323 residuals from, 1:324–325 in small drinking water systems, 1:460–461

Limestone aquifers, 1:365; 5:145 karstic, 1:365–370 Limestone channels, open, 5:6–7 Limestone drains, anoxic, 5:5–6 ‘‘Limited use zone’’ (LUZ), 3:81 Limiting nutrients, 4:52 Limits to Growth, The, 2:625 ‘‘Limnic ratio,’’ 3:269 Limnodrilus, heavy metal uptake by, 2:215 Limnology, 3:291–295 regional lake, 3:269–270 Limnotrissa, 3:269, 270 Linear flux-concentration law, 3:250 Linearization procedures, 5:13 Linear nonthreshold (LNT) model, 4:541, 543–544 Linear polarization resistance (LPR), 1:9 Linear programming techniques, 1:551–552 Linear reservoir storage coefficient, 3:62 Linear shallow water theory, 4:135 Line breaks digging up pipe with, 1:402 emergency repair of, 1:401–402 in laying new pipes, 1:402–403 repairing, 1:400–403 Liners, landfill, 1:698 Lines of evidence (LOEs), 2:353, 429–430 biomarkers and bioaccumulation as, 2:426–432 Line stops, 1:890 Linings close-fit, 1:878–879 cured-in-place, 1:878 pipe, 1:154 spray-on, 1:879–881 Lipids, as indicators of organic contamination, 2:442 Lipophilic contaminants, SPMD-TOX paradigm monitoring of, 2:170–172 Liquid chromatography, high performance, 2:308 Liquid junction, 2:466 Liquid/liquid solvent extraction, 2:307 Liquid monitoring techniques, direct, 5:541–542 Liquid-phase carbon adsorption, 2:364

777

Liquid-phase granular activated carbon adsorption (GACA), 1:101–102 Liquids. See also Fluids dense nonaqueous phase, 5:91–92 properties of, 3:194 Liquid traps, 2:307 Liquid water/water vapor system, 4:263 Litigation, wetlands-related, 4:691 Litter, marine, 4:38–41 Littoral zone, 3:267 Livestock production, impact on surface water quality, 3:374 Livestock grazing, managing, 2:186. See also Dairy entries Livestock safety, weed control and, 3:744 Livestock watering, sand abstraction for, 3:413–414 Livestock water use, 2:544 Living filters, 2:102 Local agricultural land use planning programs, 3:596–597 Local consumption advisories, 3:120 Local currents, 3:320 Local fishing waters, 3:532–533 Local government, approach to droughts, 2:577 Local management agencies, 2:193, 195 Local meteoric water line (LMWL), 4:439, 440 Local search methods, 2:332 Local water resource agencies, 4:649 ‘‘Local water use efficiency,’’ 2:536 Local weather, 4:361 Locus of enterocyte effacement (LEE), 2:137 Logan’s method, 5:495 Logarithmic transformation, 4:299 Logging rain forest, 2:667 Great Lakes region, 3:178 Logistic regression, 5:596 Log Koc , 4:524 Log Kow , 4:523–524 Log removal, 1:249 London Convention (LC), 4:40 ocean dumping reports, 4:144–149 London–van der Waals bonding, 5:18, 21,:350 Longitudinal dispersion, 5:46, 273 Longitudinal scour pools, 3:68

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778

CUMULATIVE INDEX

Long pathlength absorbance spectroscopy (LPAS), 4:515 Long Term Ecological Research (LTER) site, 3:391 Long-term persistence, 3:210, 211, 212–213 Long-term simulation, of pollution, 3:335 Longwave radiation, 4:179 Loop system weight loss corrosion measurement, 1:8–9 Loose sand densification, 3:288 Lophelia pertusa distribution of, 4:34–35 threats to, 4:36–37 Los Angeles County, water withdrawals by, 2:479 Loss trends, coastal-wetland-related, 3:72–73 Lotic aggregates, microbiology of, 3:305–307 Lotic waters, 2:544 Louver screens, horizontal, 5:572–573 Low altitude glaciations, lake districts from, 3:265 Low dosage hydrate inhibitors, 4:474 Lower explosion limit (LEL), 4:561 Low flow. See Base flow Low flow aerators, 2:666 Low-flow groundwater purging/surging, 5:404–406 techniques for, 5:406 Low-flow sampling, 5:455 Low-frequency active sonar (LFAS), 4:571 Low impact development (LID), 2:188 Low-income countries, residential water demands in, 1:14–15 Low level organic waste compounds, water contamination by, 5:60–63 Low rate treatment systems, 1:841, 842t anaerobic, 1:907f Low-tech wastewater reuse system, 5:329 Low-water-solubility compounds, 2:44 ‘‘Low water-use’’ plants, 3:556–557 Luminescent bacteria for determining mutagenic and carcinogenic agents, 2:174–175 for determining nutrients in water, 2:175

in online water toxicity monitoring, 2:174 in water quality determination, 2:172–176 Luminescent bacterial biosensors for genotoxicity assessment, 2:455 recombinant, 2:454 for toxicant detection, 2:453–458 Luminescent-marked genes, 2:453–454 Luminometers, 2:49f Luminometry, 2:48 Lumped modeling approach, in flood studies, 3:156 Lung cancer, cadmium inhalation and, 5:615 luxCDABE reporter system, 2:453 lux genes for determining stress-inducing agents or toxic chemicals, 2:174 in water quality determination, 2:172–176 Lyngbyatoxin A, 2:389 Lysimeters, 3:572; 5:74, 487–491 drainage, 5:488 equilibrium-tension, 5:489 history of, 5:487 installation and sampling procedures for, 5:490 nonweighing drainage, 5:488–489 Lysimeter soil water sampling, 2:340–343 Lysosomes, 2:31

Maar lakes, 3:265 Machine-slotted (milled) screens, 5:573–574 Macroalgae, trace elements in, 3:456 Macroarrays, 2:60 Macrocalibration, 3:318–319 Macrofauna, intertidal, 4:73–77 Macrofaunal communities, 4:11–12 Macrofouling, of surfaces, 1:541 Macroinvertebrate assemblages, 3:40 Macroinvertebrate index of biotic integrity (Macroinvertebrate IBI), 3:39–40 Macroinvertebrates, aquatic, 2:321–323 Macrolite, 1:314 Macrophyte buffer mechanisms, 3:273

Macrophytes. See also Aquatic macrophytes in the aquatic ecosystem, 1:714–715 as biomonitors, 1:716; 2:66 contaminant exposure and uptake by, 1:715 halogenated compounds and, 4:150 as PCB biomonitors, 1:714–718 role of, 1:894 as trace metal biomonitors, 2:64–68 Macropore flow, vadose zone, 5:73 Macropores, 1:97; 3:474 Macropore throughflow, 3:453 Macroscale hydrologic modeling, 3:534–536 Madhya Ganga Canal, 3:234 Magnesium hardness, 4:453. See also Mg/Ca ratio Magnetic geophysical methods, 5:148–149 Magnetic ion exchange (MIEX ) resin, 1:325 for DOC removal, 1:325–330 in water treatment, 1:327–329 Magnetic meters, 1:338 Magnetic water conditioning, 1:141, 534–537 applications for, 1:535–536 scientific support for, 1:536 Magnetism, relationship to cell stability, 4:457–458 Magnetization, effect on cell biology, 4:456–457 Magnetotelluric (MT) method, 5:150 Magnus equation, 4:270 Magnus–Teten function, 4:366 MAG tests, for bacteria, 1:84 Mahakali Treaty of 1996, 4:683 Maintenance, of municipal solid waste landfills, 2:168 Maize processing plants, anaerobic-aerobic treatment for, 1:581–586 Malachite, adsorption of, 1:118 Malaria, DDT use for, 2:600 Male reproductive system, effects of lead on, 2:436 Mammals effects of cadmium on, 5:615–616 marine, 4:57 Management forest, 3:172 municipal watershed, 1:497–500

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CUMULATIVE INDEX

as a remediation strategy, 2:358 of residential water demands, 1:15 of water infrastructure, 2:594–595 of waterlogged lands, 3:603 of water treatment plant residuals, 1:411–413 Management activities, impacts of, 2:248 Management contract model, 1:50 Management issues, Great Lakes region, 3:179 Management measures (MMs), well head protection, 1:527 Management models, 2:369, 620 Manchester, Connecticut, drought-contingency-plan phasing criteria, 2:581, 582t Manganese (Mn). See also Manganese removal; Mn(II) arsenic removal using, 1:636–637 forms of, 1:313 in groundwater, 2:147 in inhibition of biological iron removal, 2:153–154 microbial oxidation of, 2:226 problems caused by, 1:313 Manganese biofouling, 5:36 Manganese greensand, 1:314 Manganese-reducing to iron-reducing conditions, 5:583 Manganese removal, 1:312–315; 2:425 alternative treatments for, 1:314–315 common treatment processes for, 1:313–314 using ozone, 1:354–355 Manhole connection repair, 1:888 Manhole renovation, using trenchless techniques, 1:882–883 Manholes, repair and renewal of, 1:889 Manifold and well points, sand abstraction system, 3:416 Manmade lakes, 3:270, 293 Manmade reservoirs, 2:367 Manning, John C., 4:454 Manning coefficient values, 3:196t, 242, 244, 347t Manning equation, 3:196 Manning roughness, 3:63, 64, 76 Manual valves, 1:482 Manufacturing, water use for, 2:662 Manufacturing processes, effect on corrosion, 1:8

Manure composting/exporting, 2:572 contents of, 3:538 efficient use of, 3:698–699 Manure application, nitrate contamination and, 2:572 Mapping of agricultural land, 3:608–609 parametric, 5:657 ‘‘Marble-in-a-cup’’ theory, 2:50, 52f Marginal cost pricing, in India, 2:558 Margin of safety, 2:676 Mariculture, impact of oil on, 4:106–107 Marine animals debris hazard to, 4:40 mercury levels in, 4:107 Marine bacteria, morphological features of, 2:446–447 Marine bioluminescence toxicity tests, 2:48 Marine biota, cadmium levels in, 4:100–101 Marine chemistry, 4:57 Marine colloids, 4:27–32 physicochemical parameters of, 4:30 residence times of, 4:30 types of, 4:28–29 Marine debris abatement fo, 4:38–41 coral reefs and, 4:114 hazard to humans, 4:40 hazard to marine animals, 4:40 hazard to navigation, 4:40–41 reducing, 4:41 sources of, 4:38–39 Marine ecosystems, cultural eutrophication in, 3:114. See also Marine environment Marine environment. See also Marine ecosystems; Marine habitats gas hydrates in, 4:57–61 heavy metals in, 4:100 monitoring quality of, 2:443–444 monitoring water quality in, 2:447–448 pollutant input into, 4:96–97 Marine habitats. See also Marine environment effects of pollutants on, 4:105–108 impact of oil on, 4:106 Marine Instrumentation Laboratory (MIL), technology and hardware development at, 4:70–73

779

Marine mammals, 4:57 Marine microalgal sediment toxicity tests, 4:120–124 Marine oilers, 4:763 Marine oil spills, 2:44, 291–292 effects of, 4:105–107 Marine organisms, juvenile, 3:72 Marine pollutants, classes of, 4:50–51 Marine pollution, sources and effects of, 4:108–109t Marine Protection, Research, and Sanctuaries Act, 2:125 Marine seeps, as a CH4 source, 4:87–88 Marine sediments, heavy metal concentrations in, 2:448–449 Marine Stewardship Council, 2:636 Marine stock enhancement techniques, 4:124–128 Marine toxicological testing, 4:42–43 Mariotte bottle applications for, 4:504 use in hydrology, 4:503–504 Maritime fog, 4:232 Maritime history, protection of, 4:62–64 Marketable permits system, 2:507–508 Market prices, 4:607 Market-related transaction costs, 2:500 Markovian process, 3:214, 215 MARPOL Convention, 4:40 Mars life on, 4:747–748 megawatersheds on, 5:270 Mars Exploration Rover mission, 4:504–506 Marshes, 1:404 coastal, 3:72 Marsh vegetation, impact of oil on, 4:106 Martin wetland classification system, 3:497 Mass conservation equations, 2:271 Mass curve analysis, 3:261 Mass-flow leaching, 5:261 Mass-flow porometers, 3:717 Massively parallel signature sequencing (MPSS) technology, 2:60–61 Mass–momentum–energy balances, 5:558

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780

CUMULATIVE INDEX

Mass movement events, role in flooding, 3:146 Mass spectrometry, electrospray ionization, 4:443–445 Mass spectroscopic methods, advanced, 2:206 Mass spectroscopy (MS), 2:308, 389 Mass transfer rate constant, 4:568 Mass transport, in saturated media, 5:273–275 Master base flow recession curve, 3:25–26 Master meters, 1:340 Mastigophora, 2:313 Mathematical modeling. See also Mathematical models in artificial aquifer recharge, 5:12–13 of contaminant transport, 5:517–518 for coupled flows, 5:659 of groundwater flow, 5:516 Mathematical models, 2:333. See also Mathematical modeling; Modeling; Numerical modeling for estimating agricultural area pollutants, 3:658–659 leachate metal transport and, 1:725 role in water storage, 2:368 sediment transport, 3:421 in water resources systems analysis, 2:686–687 Mathematical transport modeling approaches, 5:33 Mathews and Weber multicomponent isotherm model, 1:108. See also Isotherms Matlab program, 1:732 Matric potential, 4:485; 5:125–126, 533 Matric tension, 5:180, 462 Matrix-assisted laser desorption ionization time of flight (MALDI-TOF), 2:61, 206 Matrix throughflow, 3:453 Maximum acceptable toxicant concentration (MATC), 2:434 Maximum adsorption QSAR model, 3:99 Maximum basin relief, 3:29 Maximum concentration limit (MCL), of arsenic, 2:15

Maximum contaminant level goals (MCLGs), 1:422, 425–426, 427, 477; 2:195, 268 Maximum contaminant levels/limits (MCLs), 1:70, 82, 291, 312, 378, 422, 477; 2:233, 268, 373; 4:669, 677–678; 5:278 for arsenic, 2:8 defined, 2:544 developing, 1:425–428 identifying, 1:427 judicial review of, 4:678 for perchlorate, 2:345 water contaminants with, 2:234–235t Maximum entropy principle, 4:218–219 Maximum entropy spectral analysis (MESA), 4:221 Maximum extent practicable (MEP) pollution control, 3:432 Maximum permissible concentrations, 1:287 Maximum permissible limits, 1:25 Maximum Residual Disinfectant Level (MRDL), 1:477 Maximum Residual Disinfectant Level Goal (MRDLG), 1:477 Maximum significant wave height, estimating, 4:2–3 Maximum sustained wind speed, estimating, 4:2 Maximum vapor pressure, 4:271 McCarran Act, 4:690 MDL QSAR program, 3:99 Mean basin elevation, 3:29 Mean cell residence time (MCRT), 1:753, 846 Meander wavelength, 3:31, 32 Mean liquor suspended solids (MLSS), 2:48 Mean residence time, 4:287 Mean sea level (MSL), 4:118–120 Measured pollutant loads, 3:223–229 Measurement programs, optimizing, 2:177 Measurement systems, prototype, 4:296–297 Mechanical aeration, 1:353, 460. See also Mechanical surface aeration Mechanical colloidal processes, 5:350 Mechanical dewatering, of sludge, 1:855 Mechanical dispersion of contaminants, 5:517

Mechanical dredging/barge disposal, 2:122 Mechanical flocculators, 1:253 Mechanical move microirrigation, 3:621 Mechanical seals, 1:882 Mechanical soil conservation methods, 3:550 Mechanical submerged aeration systems, 1:624–625 Mechanical surface aeration, 1:624 Mechanical treatment, for iron bacteria, 2:152 Mechanical weed control, 3:744–745 Media filters, for microirrigation, 3:752–754 Median effective concentration (EC50 ), 2:377–378 Mediated sensors, 2:41 Media thickness, 5:184 Medical science, illogical foundations of, 4:723–724 Medications, nitrate-containing, 2:220 Medicinal activated carbon, 1:105 Medicinal properties, of Saratoga Springs waters, 4:797–801 MEDIS project, 2:639–641 Mediterranean islands, sustainable water management on, 2:638–643. See also SUSTAINIS advanced study course Mediterranean Sea, mercury cycling simulation for, 3:323–325 Megawatersheds, 5:266–273 discovery of, 5:267 on Mars, 5:270 Somalia case study of, 5:267–269 Trinidad and Tobago case studies of, 5:269–270 Megawatersheds exploration program, 5:267–270 Mekong Delta ancient settlement of, 4:750 French colonial conquest of, 4:751–752 geology of, 4:749–750 subregions of, 4:749–750 Vietnamese settlement of, 4:750–752 Mekong Delta canals, history of, 4:748–752 Melioidosis, 1:88 Membrane backwashing, 1:334

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CUMULATIVE INDEX

Membrane-based reverse osmosis, 1:308 Membrane bioreactors (MBRs), 1:822 Membrane cleaning choosing cleaners, 1:419–420 control and improvement of, 1:421–422 multistage systems for, 1:421 on-line procedure for, 1:421 in reverse osmosis, 1:419–422 strategies for, 1:420–421 Membrane filtration, 1:229, 232, 247, 295, 331–337, 458–459, 488 of landfill leachates, 1:707–708 for radioactive waste, 1:803 role of colloids and dissolved organics in, 2:99–103 waste stream disposal and, 1:336 Membrane filtration systems, comparing, 1:331, 332f Membrane foulants, in reverse osmosis, 1:416–419 Membrane fouling, 1:301 limiting, 1:594; 2:364 mechanisms of, 1:415 Membrane materials, 1:708 for diffusion-based groundwater sampling, 5:456–457 reverse osmosis, 5:26 Membrane ‘‘package’’ plants, 1:334 Membrane performance, in reverse osmosis, 1:173 Membrane processes, 1:792–793 Membranes. See also Membrane cleaning; Membrane filtration desalination via, 1:171–173 integrity testing of, 1:336–337 pretreatment of, 1:334 reverse osmosis, 1:308, 810 synthetic, 1:591 washing and reuse of, 1:920 Membrane separation processes, 1:791 Membrane/sonication/wet oxidation hybrid system, 1:873–874 Membrane systems, 1:817 domestic sewage, 1:834 Membrane techniques, for perchlorate removal, 5:633 Membrane water treatment system, biofouling in, 2:242 Menhaden research, 4:56 Meningitis, aseptic, 1:178–179

Mercury (Hg). See also Hg (II) ion sorption atmospheric deposition of, 3:282 fate and transport of, 5:644 in groundwater, 5:642–645 health risks of, 5:643–644 maximum contaminant level of, 2:234t poisoning by, 3:118 regulatory guidelines for, 5:645 remediation of, 5:644–645 in urban stormwater, 3:435 Mercury compounds, inorganic and organic, 5:643–644 Mercury cycling, simulation of, 3:323–325 Mercury levels in marine animals, 4:107 in marine biota, 4:101 Mercury removal, from complex waste waters, 1:722–723 ‘‘Merit goods,’’ 1:216, 217 Meroplankton, 4:155 Mesmer, Franz, water healing by, 4:760–761 Mesophilic processes, 1:647 Mesopores, 1:97 Mesopotamia, water symbolism in, 4:785 Mesoscale currents, 3:320 Mesoscale fog, 4:230–231 Mesozooplankton, 4:156 Meta-analysis, 4:610 Metabolic heterogeneity, in biofilms, 2:230 Metabolic pathways, of contaminants, 5:529 Metabolic potential, 2:42 Metabolism crop, 3:721 energy flow and, 5:528–529 Metabolomics, 2:62 Metal accumulation, by plant roots, 3:35 Metal arsenides, 5:22 Metal binding sites, in aquatic biomacromolecules, 4:29 Metal biosorption. See also Metal sorption characteristics of, 2:70t mechanisms of, 2:70–71 Metal cations, 4:444–445 Metal chemistry, 5:283–284 Metal complex formation, 2:204

781

Metal concentration(s) in acid mine drainage, 5:1 dissolved, 2:422 impact on plants, 2:65 pervasiveness of, 2:237 Metal contaminants, toxicity/mobility reduction of, 5:434 Metal-contaminated groundwater, remediation of, 5:283–284 Metal-contaminated soils, remedial approaches for, 5:433–435 Metal detectors, 5:150 Metal discharges, regulations concerning, 2:68 Metal hyperaccumulation, 5:371 Metal hyperaccumulators, 3:35 Metal-induced humic agglomeration, 2:209 Metal ion adsorption, on bed sediments, 3:295–305 Metal ion binding, to inorganic–humic agglomerates, 2:208 Metal ion concentrations, in groundwater, 2:144 Metal ion–humic colloid interaction, 2:205 kinetics of, 2:209–210 mechanisms of, 2:207–209 modeling approaches to, 2:206 speciation methods related to, 2:206–207 Metal ions adsorption of, 4:492 removal by activated carbons, 4:506–511 removal from aqueous systems, 1:918–920 Metal ion speciation, estimating, 2:206. See also Metal speciation Metallic corrosion, 1:154 Metallic ion nitrate treatment, 5:328 Metallothioneins (MTs), 5:287 Metallic salt coagulants, 1:138 Metalloenzymes, microbial, 2:233–235 Metallothioneins (MTs), 3:609 biological function of, 2:406–407 as biomarkers, 2:407 classes of, 2:406 factors affecting levels of, 2:407 as indicators of trace metal pollution, 2:406–408 quantification of, 2:407 role in metal tolerance, 3:612–613

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782

CUMULATIVE INDEX

Metal mining impact on surface water quality, 3:374 pollutants from, 1:897 Metal-organic complexes, stability of, 5:259 Metal-organic interactions in landfill-polluted environments, 5:259–260 in subtitle D landfill leachates and ground waters, 5:258–260 Metal-oxide semiconductor field effect transistor (MOSFET) technology, 2:298 Metal phytoremediation, selecting plants and microorganisms for, 3:628–637 Metal pyrites, 3:13 Metal remediation, 5:290–291 water-jetting drilling technologies for, 5:234–235 Metal removal, role of phytoremediation in, 3:368 Metal-resistant bacteria distribution of, 2:448–449 in Peter the Great Bay, 2:447f in Rudnaya Bight, 2:449f selection for, 5:379 Metal response elements (MREs), 2:407 Metals, 5:280–284. See also Heavy metal entries active immobilization of, 5:282–283 in an agricultural landscape, 3:607–608 in ash and FGD sludge ponds, 1:852 bioavailability of, 2:211–212 bioremediation of, 5:282 chemical binding by colloids, 3:75 detoxification in plants, 5:287 effect on corrosion, 1:8 hyperaccumulation in plants, 5:285–286 immobilization of, 1:836; 5:282 in key enzyme functions, 2:237t microbe-induced reduction of, 5:293 mobility of, 5:281 mobilization of, 5:377 in natural waters, 1:903 passive immobilization of, 5:283–284

permissible concentrations of, 2:235t plant-based remediation of, 5:292–293 plants that accumulate, 3:629–633 precipitation of, 2:70 reduction of, 2:300 removal by constructed wetlands, 3:368 sample preparation of, 2:309 sequestration in vacuoles, 5:287–288 in sewage treatment plant influent, 1:831 simulation, 2:256–259 in streambed sediment, 3:355–356t toxicity of, 5:259 in whole sculpin tissue, 3:361t Metal sorption, 1:111; 2:363. See also Metal biosorption Metal speciation chemical reactions affecting, 2:203–204 measurement of, 2:204 modeling, 2:204 sensors, 2:419t Metal speciation and mobility, landfill disposal practices and, 1:723–728 Metal surface complexes, 4:509 Metal tolerance in plants, 3:609–615 role of phytochelatins in, 3:611–612 Metal treatment, 5:290–291 Metal uptake, mechanism of, 5:286–287 Metamorphic rock aquifers, 5:145 Metamorphic rocks, 5:55 Meta River, 4:642 Meteoric water line, 5:230 Meteorological data, in land surface modeling, 3:536 Meteorological drought index, 4:211 Meteorological droughts, 4:208 Meteorological instrumentation, 4:349 GLERL, 4:72–73 Meteorological measurements, 4:164 Meteorological observation networks, 4:349 Meteorological observation stations, 4:72

Meteorologic conditions, heat balance and, 3:191 Meteorologic fields, relationship to heat fluxes, 3:191–193 Meteorologic variables, southwestern Spanish coast, 4:341 Meteorologists, 4:328 functions of, 4:293 Meteorology, 4:292–294 ballooning and, 4:164–166 ground-based GPS, 4:244–255 scientific progress in, 4:352–353 Meteors, water in, 4:190 Metering, 2:496. See also Water meters in Canada, 2:663 as a water conservation measure, 1:146 Meter yokes, 1:339 Metha, Gita, 4:768 Methane. See also CH4 ; Halogenated methanes in groundwater, 5:293–294 migration of, 5:256 Methane hydrate, 4:473, 474 Methanogenesis in landfills, 1:696 separation from acidogenesis, 1:909 Methanogenic metabolism, 1:689–690 Methanogenic systems, 5:47–48 Methanotrophic bacterial systems, 5:47 Methemoglobinemia, 2:219–223; 4:519; 5:324 diagnosis and treatment of, 2:221 hereditary causes of, 2:220–221 nitrate-related, 1:35–36 susceptibility to, 2:219 water-related and non-water-related causes of, 2:220 Methylated antimony species, 4:592 Methylated arsenic compounds, 2:11 Methylation, of metals, 5:378 Methyl bromide cycling study, 4:80–81 study of sources of, 4:150 Methylene blue number, 1:98 Methyl halides, measurements of, 4:150 Methylmercury exposure, 5:643, 644

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CUMULATIVE INDEX

Methyl-tertiary-butyl ether (MTBE), 2:312, 317, 344–345; 5:318–319 aerobic cometabolism of, 5:388–389 alfalfa channel tests and, 5:392 anaerobic microbial transformation of, 5:386–388 chemical and physical properties of, 5:388t degradation pathway of, 5:387t electrolysis of, 5:122–123 fate in the atmosphere, 5:393–394 field studies involving, 5:394 in situ electrokinetic treatment of, 5:116–124 phytoremediation of, 5:385–397 plumes, 5:80–81 potential biotreatments for, 5:389 properties of, 5:386 soil vapor concentration of, 5:553 uptake by hybrid Populus, 5:389–392 uptake efficiency and toxicity for, 5:391 Metropolitan Washington Council of Governments (MWCOG) ‘‘simple method,’’ 2:253 Mexican National Water Commission (CNA), 1:652 Mexico coastal fog along the northern Gulf of, 4:230–239 wastewater applications in, 1:633; 3:672 Mexico-Guatemala water conflicts, 4:641–642 Mexico–U.S., transboundary waters in, 4:636–641. See also United States–Mexico border waters Mg/Ca ratio, 4:93. See also Magnesium hardness Microalgal sediment toxicity tests, marineand estuarine, 4:120–124 Microarray analysis, 2:60 Microarray experiments, 2:62–63 Microarray Gene Expression Data (MGED) Society, 2:60 Microarray (DNA chip) technology, 1:161–162. See also DNA microarrays Microbes. See also Bacteria; Marine bacteria; Microorganisms biochemical oxygen demand and, 1:640–641

in drinking water, 2:243 plants as energy sources for, 5:378 Microbe transport models, 1:368 Microbial activity aerobic tank, 1:789, 790f in ‘‘dirty water’’ formation, 2:226 disinfection to control, 2:225–226 effect of temperature on, 2:226 in groundwater, 5:32–33 Microbial activity management, 2:223–228 biofilm control, 2:223–226 control of biodegradable organic carbon, 2:224–225 Microbial aminolevulinate dehydratase (ALAD), 2:236–237 Microbial assessments, 2:450–451 historical background of, 2:441–442 for monitoring marine environment water quality, 2:447–448 Microbial biofouling, 1:83–87. See also Microbial fouling direct analysis of, 1:84–86 Microbial biomass, as a sorbent, 2:365–366 Microbial biosurveys in Far Eastern Russia seas, 2:444–451 for heavy metal detection, 2:442–443, 445, 446 for organic pollution assessments, 2:449 Microbial BOD biosensors, 2:40. See also Biochemical oxygen demand (BOD) Microbial communities, 3:306–307 Microbial contaminants, health effects of, 1:277–281 Microbial corrosion, 1:6–7 Microbial detection, of phenols, 2:442 Microbial/direct chemical contamination zone (Zone A2), 1:526–527 Microbial diversity, 2:42; 4:746–747 Microbial dynamics, of biofilms, 2:228–233 Microbial enzyme assays, for heavy metal toxicity detection, 2:233–238 Microbial foaming and bulking in the activated sludge process, 1:728–730, 844–848 bacteria involved in, 1:846–847

783

factors affecting, 1:847 prevention and control of, 1:846 problems caused by, 1:845–846 Microbial forms, in biofouling events, 2:239–243 Microbial fouling, 5:422. See also Microbial biofouling Microbial genes, using in selenium phytoremediation, 5:400 Microbial growth, corrosion and, 1:544 Microbial loop, 3:312; 4:152 Microbially available phosphorus (MAP), 2:245 Microbial metabolism, 2:299 Microbial metalloenzymes, 2:233–235 Microbial motility, 2:228–229 Microbial nutrients, in distribution systems, 2:244–245 Microbial pathogens, 2:371 in aquatic systems, 2:352 Microbial physiology, 5:580–582 Microbial pollutant detection, water quality monitoring and, 2:440–452 Microbial processes in biofilms, 3:307–308 in mine effluent remediation, 1:612 Microbial products, algal control and, 2:6 Microbial quality, of reclaimed irrigation, 3:667–673 Microbial structure, in biofilms, 2:230–232 Microbial transformation of chlorinated aliphatic compounds, 1:690 of chlorinated aromatic compounds, 1:689–690 of petroleum hydrocarbons, 1:692 Microbiological analyses, of rural drinking water, 1:383–384 Microbiological behavior, 1:566 Microbiologically induced corrosion (MIC), 1:596, 600–601 Microbiological mechanisms, 1:596–598 Microbiological methods, in groundwater studies, 5:464–465 Microbiological monitoring, 2:267 Microbiological processes, soil, 3:706 Microbiological quality control, in distribution systems, 2:243–247

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784

CUMULATIVE INDEX

Microbiological standards, U.S., 2:268 Microbiology iron and, 5:609 of lotic aggregates and biofilms, 3:305–308 soil, 5:464 in transport modeling, 5:31–33 Microcalibration, 3:319–320 Microcolumns (MIC), 2:212 Microcontrollers, 4:71 Microcoulometric detectors, 2:308 Microcystins, 2:388, 390; 3:189 Microencapsulation, 1:835 Microfiltration (MF), 1:331–334, 336t, 444, 459, 488, 591, 810 of industrial wastewaters, 1:591–595 Microfiltration and reverse osmosis (MF-RO), 1:218–219, 220 Microflora, lipolytic, 2:442 Microgravity networking, 5:411 Microhabitats, 3:70 Microirrigation, 3:615–620 advantages and disadvantages of, 3:617–619, 621–622 components and system design for, 3:622–624 current irrigated area using, 3:619 development of, 3:620 efficiency of, 3:620–628 expansion of, 3:627 extent of, 3:624–626 future scope of, 3:627 limitations of, 3:626 media filters for, 3:752–754 research trends in, 3:626–627 screen filters for, 3:748–750 strategies for promoting, 3:627–628 types of, 3:620–621 water saving and yield increase related to, 3:617, 622 Microirrigation systems, control station of, 3:617 MicroMac-ToxScreen, 2:174 Microorganism contaminants, 1:54 Microorganisms. See also Bacteria; Lotic aggregates; Microbes; Microbial entries; Single-celled organisms; Protozoa; Viruses abiotic factors related to, 3:311–312 adhesion of, 2:239 biotic interactions of, 3:312

deactivation of, 1:605f dew use by, 4:201–202, 205 genetically modified, 4:525 geochemical ecology of, 2:442–443 in geothermal waters, 5:157 habitats of, 3:310–311 as indicators of oil pollution, 2:441–442 inside biofouling layers, 2:240–241 iron distribution and, 4:497 metabolic diversity of, 2:44–45 monitoring, 3:669 in natural environment, 3:309–313 oil-destroying, 2:449 persistence data for, 1:522 in raw and treated wastewater, 3:670t role in biodegradation, 2:42 role in water vectored diseases, 2:112 selecting for hydrocarbon and metal phytoremediation, 3:628–637 selective binding and absorption of metals by, 2:443 types of, 3:668–669 Microphytobenthos, 4:120 bioassays involving, 4:122 removal from sediments, 4:121 Micropollutants, organic, 4:506–511 Micropores, 1:97; 3:474 Micropurging, 5:455 Microscale currents, 3:320 Microscale flow manifolds, 4:515 Microscale fog, 4:231 Microscale toxicity testing, in natural systems, 2:379–380 Microscopic corrosion measurement, 1:9 Microscopic examination/analysis, of biofouling structures, 1:84 Microscreen filters, 1:683 Microspora, 1:279 Microsporidiosis, 1:367 Microsporidium, in karstic aquifers, 1:367–368 Microstrainers, 1:486 Microthrix parvicella, 1:729 MICROTOX bioassay, 2:171, 172, 173, 278, 351, 413, 453 Microtox-OS Test System, 2:174 Microwave precipitation estimation, 4:323 Microwave soil moisture equations, 4:324

Midchannel pools, 3:68 Middle Ages sanitation during, 1:282–283 water in, 4:728 Middle East conflict and water use in, 4:753–758 international river basins in, 4:754t Midoceanic ridge basalts (MORB), 4:577 Midrange water quality models, 2:248 MIEX resin plant, 1:326f. See also Magnetic ion exchange (MIEX ) resin capital and operating costs of, 1:329–330 Military use of activated carbon in, 1:105 role in prototype measurement systems, 4:296–297 Military applications, research for, 4:295–297 Milled screens, 5:573–574 Mine drainage acidification of surface waters by, 3:10–11 composition of, 1:609f ‘‘Mineral (nitrogen) balance,’’ 3:639 Mineral domain, sorption in, 4:386–387 Mineralization, 2:42 of heavy metals, 5:378 Mineral matrix, 5:172–173 Mineralogy, evaporite, 5:52–53 Minerals, in soil, 3:706 Mineral water, historical uses of, 1:4 Mines, abandoned, 5:3 Mine waste, 1:609–614 acid mine drainage generation, 1:609–610 effluent remediation and, 1:610–612 Mine waters, discharge standards for, 2:425 Minicolumn method, 1:774, 779 Minimum cross entropy principle, 4:219 Minimum environmental flow regimes, 3:166–168 Minimum Information About a Microarray Experiment (MIAME), 2:60

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CUMULATIVE INDEX

Minimum National Standards (MINAS), 2:183 Mining groundwater acidification due to, 3:10 impact on surface water quality, 3:374 ocean water contamination by, 4:100 Mining lakes, acidic, 3:10 Mining water, 1:552 Mining water use, 2:544, 662 in the United States, 2:652 Ministry of Agriculture (China), 2:486 Ministry of Construction (China), 2:486 Ministry of Geology and Mineral Resources (China), 2:486 Ministry of Public Health (China), 2:486 Ministry of Transportation (China), 2:486 Ministry of Water Resources (China), 2:485–486, 488 MINTEQA2/PRODEFA2 program, 5:141 MINTEQ database, 5:144 Minute process, 4:644 Mirror carp, 4:719 Mississippi River Commission (MRC), 4:613 Mississippi River water quality report, 1:289 Mixed clathrate hydrates, 4:471 Mixed-flow impellers, 1:76; 3:664 Mixed liquor suspended solids (MLSS), 1:730, 828 Mixing lake, 3:266–267 in water treatment systems, 1:76–81 Mixing fog, 4:231 Mixing ratio (r), 4:273–274 Mixing zones, 3:80–81 Mixing zones ban, Great Lakes system, 4:624–625 Mixotrophic organisms, 4:152 Mn(II), 5:585. See also Manganese entries MNA monitoring well network, 5:587–588. See also Monitored natural attenuation (MNA) Model calibration, alternatives to, 3:342–343

Modeling. See also Activated Sludge Models (ASMs); Biological process modeling; Chlorine residual modeling; Empirical models; Mathematical models; Models; Residential water use models; Steady-state modeling; Wastewater modeling and treatment plant design adsorption, 3:300–301 COD relationships in, 1:735–737 of contaminant transport and biodegradation in groundwater, 5:30–35 diffusion kinetics, 4:567–568 entropy as a tool for, 4:220 of episodic acidification, 3:5–6 of fecal coliform in sewers, 3:334 finite element, 5:655–661 groundwater, 5:619–626 of hurricanes, 4:274–275 hydrogen sulfide, 3:333–334 infiltration, 4:486–487 integrated, 3:340, 341–342 karst, 5:241 kinetic, 4:565–567 land surface, 3:533–537 of nonconservative pollution, 3:332–333 ocean, 4:22–23 of pond aquaculture, 3:375–378 predictive, 3:40; 5:589 of quasi-conservative pollution, 3:332 rainfall–runoff, 4:297–303, 357–358 real-time, 3:340–341 of salt balance, 3:680 sedimentation, 3:404–405, 421 of sewer water quality, 3:331–337 of solute transport in groundwater, 5:305–313 subsurface redox chemistry, 5:413–417 of transpiration, 3:736–740 of ungauged watersheds, 3:342–345 unit hydrograph, 4:357–359 of unsaturated soil properties, 5:538 of urban drainage and stormwater, 3:337–342 of urban flooding, 3:339–340 water quality, 3:338–339, 341 watershed, 3:327–331

785

Modeling programs, 4:323 Model parameter uncertainty, 3:325 Models. See also Mathematical models; Modeling calibration methods for, 2:332–333; 5:297 comprehensive, 2:255–256 geochemical, 5:138–140 verification/validation of, 5:298 Model sensitivity analysis, 3:318 Model structure (equation) uncertainty, 3:325 ‘‘Model Water Use Act,’’ 2:580, 583 Moderate Resolution Imaging Spectroradiometer (MODIS), 2:589; 4:194, 216, 351 measurements with, 4:134 ‘‘Modern biomass,’’ 3:546 Modern groundwaters, detecting with 85 Kr, 5:248–249 MODFLOW, 1:368; 5:564 packages, 5:33 simulation, 5:84f MODFLOW-RT3D simulator, 5:520–521 Modified chlorophyll absorption in reflectance index (MCARI), 3:722 MODSIM water quantity network flow allocation model, 2:327 Modular groundwater flow (MODFLOW) code, 5:83. See also MODFLOW entries Moffett Federal Airfield permeable reactive barrier site, 5:520, 521 Moist adiabatic lapse rate (MALR), 4:369 Moisture, influence on nitrification, 3:641–642. See also Soil moisture measurement Moisture characteristic curves, 5:462–463, 472 Moisture distribution, using microirrigation, 3:618 Moisture enhancement, 5:117 Mojave Desert, recharge in, 5:73 Molasses, composition of, 1:616t Molasses number, 1:98 Molecular assays, for Escherichia coli O157:H7, 2:139–140 Molecular-based detection, of Cryptosporidium parvum, 1:158–162 Molecular-biological tools, 1:847 for biodiversity monitoring, 1:642–646

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786

CUMULATIVE INDEX

Molecular-biological tools, (continued) community profiling methods, 1:643 labeled substrate probes, 1:645–646 molecular probes, 1:643–645 Molecular-biology-based assays, 1:91 Molecular diffusion, 5:174, 544 Molecular fingerprints, 1:643 Molecular hydrogen, 4:480. See also H2 economy Molecular methods, 2:352 Molecular oxygen, 4:535. See also O2 evolution Molecular probes, in community analysis, 1:643–645 Molecular water network, changes in, 4:513 Molecular weight cutoff (MWCO), 1:331, 334, 335 Mole drains, 5:95 Molluscs. See Bivalve molluscs; Mussel entries; Shellfish growing; Zebra mussel control Momentum balances, 5:558 Momentum–mass–energy balances, 5:558 Monitored natural attenuation (MNA), 5:319–322, 578. See also MNA monitoring well network bioremediation technology, 5:40 degradation rate constant, 5:588–589 modeling as a predictive tool for, 5:589 model of, 5:579–580 statistical validity of data for, 5:588 Monitoring of contaminants, 2:263–269 of municipal solid waste landfills, 2:168 use of semipermeable membrane devices for, 5:672–677 Monitoring parameters, criteria for, 2:266–267 Monochlorophenols, 1:689 Monoclonal antibodies, 1:160 Monod degradation kinetics, 5:32 Monod equation, 1:735–736 Monod rate expression, 5:416 Monohalogenated haloacetic acids, 2:75 Monomictic lakes, 3:266

Monsoons, 4:304 African, 4:304–305 Indian, 2:560 Montana, in-stream flow protection in, 4:662 Monte Carlo simulations, 3:262, 263–264 Monticello permeable reactive barrier site, 5:520–522 Moody diagram, 3:197 Morbidity, from water related diseases, 1:24–25 Morphological changes, studies of, 2:65–66 Mortality, from water-related diseases, 1:24–25 MOSQITO model, 3:339 Mosses, trace elements in, 3:456 Most probable number polymerase chain reaction (MPN-PCR), 1:161 Most probable number (MPN) technique, 2:337 ‘‘Most sensitive species’’ assay, 2:376 Mother–daughter (shedding) cell formation, 2:239 Motion, equation of, 5:559–561, 651–652 Mouse bioassay, 2:389 MOUSE TRAP model, 3:334, 339 Moving bed system, 1:104 Moving water, flow (fall) of, 2:554 MTT assay, 2:415 Mud Dump Site (MDS), 4:77, 79 Mulberry tree dikes, 4:697 Multiangle Imaging SpectroRadiometer (MISR) satellite sensor, 5:479 Multicomponent kinetics, 1:119 Multiconcentration tests, 2:382 Multidimensional pump test analysis, 5:186 Multidrug-resistant tuberculosis (MDRTB), 1:182 Multi-jet meters, 1:338 Multimedia mitigation (MMM) programs, 4:546 Multimetric biotic integrity indexes, 3:38–40 Multimetric periphyton index of biotic integrity, 3:40 ‘‘Multiobjective evaluation’’ concept, 2:595 Multiphase flow and heat transfer, 4:449 ‘‘Multiple-barrier concept,’’ 1:341

‘‘Multiple convergent datasets’’ method, 5:270 Multiple effect distillation (MED), 1:170–171 Multiple-hearth furnace (MHF), 1:858–859 Multiple stage flash (MSF) distillation units, 1:308 Multiple tray aeration, 1:353, 460 Multipurpose reservoirs, 3:382–387 conflicts in, 3:384 flood control storage capacity in, 3:384 operation of, 3:384–386 storage in, 3:383–384 systems engineering for managing, 3:386–387 Multirate meters, 1:493 Multireservoir system, operation of, 3:385–386 Multi-Sector General Permit (MSGP), 4:658–659 Multisite generalized D’Arcy and Watt (MSGDW) model, 4:403 Multispecies Freshwater Biomonitor (MFB), 2:31 Multistage drinking water filtration, 1:237–238 Multistage filtration (MSF), 1:238–243 cost of, 1:242 criteria selection in, 1:239–240 performance of, 1:241–242 roughing filter components, 1:240–241 Multistage flash distillation, 1:170 Multivariate periodic autoregressive order 1 [PAR(1)] model, 3:425–426 Municipal and industrial needs (MAIN) model, 1:15 Municipal landfills, groundwater contamination from, 5:253–258 Municipal multiutilities, 1:390 Municipal Separate Storm Sewer System (MS4), 3:392 Municipal sewage, 1:828–829 Municipal solid waste (MSW), 1:695 Municipal solid waste landfills, 2:163–169. See also Landfill entries cover for, 2:164 dry tomb, 2:163–164 groundwater monitoring for, 2:165 improving, 2:167–168

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CUMULATIVE INDEX

landfill gas from, 2:165–166 leachate collection and removal from, 2:164–165 postclosure monitoring and maintenance of, 2:166–167 reuse, recycling, and reduction related to, 2:167 siting issues related to, 2:167 Municipal Storm Sewer Systems (MS4), 4:659 Municipal storm water management, 1:866–870 evaluating, 1:868–870 monitoring in, 1:870 public participation in, 1:867 Municipal wastewaters, 1:678 analysis of, 1:829t chemical precipitation of, 4:586–587 organic compounds in, 1:766–771 Municipal water cycle, 1:495, 496f Municipal watersheds, 1:495–500 impacts on, 1:495–497 management of, 1:497–500 types of, 1:495 Municipal water supplies disinfection byproducts in, 1:264–277 ozonation of, 1:362–365 in the United States, 2:651–652 Municipal water supply and sewerage corporate strategies in, 1:389–390 private sector participation in, 1:387 Municipal water supply system, 2:371, 544 Municipal water use, 2:662 Munsell Rock Color Chart, 3:690 Mupfure catchment, 3:237–238 Murray River, salinity profile of, 3:680 Musculista senhousia, 4:11–12, 75 excretion rates of, 4:7–9, 12–13 Musical glasses, 4:758–762 Muskingum–Cunge flow routing method, 3:256–257 Muskingum flow routing method, 3:255 Mussels chemical-free control of, 1:510–514 dose-response to chlorine, 2:401–406 industrial field studies on, 1:512 on surfaces, 1:541

‘‘Mussel Watch Program,’’ 2:35 Mutagenic agents, luminescent bacteria for determining, 2:174–175 Mutagenicity assay, 2:175 Mutatox assay, 2:171, 172, 174, 455 MX [3-chloro-4-(dichloromethyl)5-hydroxy-2(5H)- furanone], health effects of, 1:269 Mycobacterium, 1:278 Mylar balloons, 4:165 Mytilus californicus, 4:153 Mytilus galloprovincialis, as a bioindicator, 2:407

N2 O, global role and sources of, 4:86–88 NADH, monitoring, 2:376–377. See also Nicotinamide-adenine dinucleotide (NAD+ ) Naegleria, 1:279 Nalgonda defluoridation process, 4:437–438 Nannoplankton, 4:93 Nanofiltration (NF), 1:333t, 335, 336t, 458–459, 488, 828 effect of, 2:77–78 N aquifer (Black Mesa, Arizona), 5:48–51 NASA Aqua mission, water cycle and, 4:193–194. See also Aqua earth observing system (EOS); National Aeronautics and Space Administration (NASA) Nash model, 4:358 Nashua River Watershed, 1:499–500 National Academy of Science (NAS) Committee on Mitigating Wetlands Loss, 4:693 risk assessment paradigm, 1:423–424 National Acid Precipitation Assessment Program (NAPAP), 4:379 National Aeronautics and Space Administration (NASA), water-flow satellite data from, 2:587–589. See also NASA Aqua mission National agricultural land use planning program, 3:596 National Aquaculture Act, 3:540 National Drinking Water Advisory Council (NDWAC), 1:425

787

National Drinking Water Clearinghouse (NDWC), 1:465 Tech Briefs, 1:151–152, 158, 177, 207 National Drinking Water Regulations (NDWRs), 1:480 National Environmental Policy Act, 2:594 National Environmental Protection Agency (China), 2:486 National Estuary Program (NEP), 2:185 National fishing waters, 3:532 National Flood Insurance Program (NFIP), 3:147, 528 National groundwater nitrate vulnerability assessment, 5:565 National Infrastructure Protection Center (NIPC), 1:451 Nationalist language, 4:681 National Marine Debris Monitoring Program (NMDMP), 4:39, 116 National Oceanic and Atmospheric Administration (NOAA), 2:185; 4:329. See also NOAA entries National Ocean Service (NOS) sanctuaries, 4:62–64 National Park Service (NPS), 4:687 National Policy on Water Management, 2:526 National Pollutant Discharge Elimination System (NPDES), 1:756–757, 798, 866; 2:96, 315; 3:432; 4:595, 655–659, 669. See also NPDES permits pollution control policy of, 2:127, 128 water quality-based limitations and, 1:759 discharge limitations under, 4:656–657 statutes related to, 4:665 National Pretreatment Program (EPA), 1:798–801 National Primary Drinking Water Regulations (NPDWRs), 1:379, 422, 425, 428 National primary drinking water standards, 2:373t National Research Council (NRC), 4:541, 544–545, 599 National Secondary Drinking Water Regulations (NSDWRs), 4:678 National Sedimentation Laboratory, 3:89

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788

CUMULATIVE INDEX

National Shellfish Sanitation Program (NSSP), 2:361 National Stormwater Program, 4:596 National Toxics Rule, 4:599 National Tsunami Hazard Mitigation Program, 4:89–90 National Water Carrier, 4:699, 700 National Water Commission (NWC), 4:614 National water policies, India, 2:556 National Water-Quality Assessment (NAWQA) program, 2:311–312; 5:359–360 National Water Quality Inventory Report, 5:332 National Weather Service, 4:329 Climate Prediction Center (CPC), 4:335 National Wetlands Coalition (NWC), 4:692 National Wetlands Inventory (NWI), 3:72–73; 4:654 National Wildlife Refuge, 4:690 Nationwide Urban Runoff Program (NURP), 3:433 ‘‘Native’’ aquifers, 5:44 NATSGO database, 5:302 Natural aeration, 1:623–624 Natural attenuation processes, 5:424, 443. See also Monitored natural attenuation (MNA); Natural contaminant attenuation effect of pump and treat remediation, 5:45–46 groundwater remediation by no action, 5:44–45 methanogenic systems, 5:47–48 phytoremediation enhancement of, 5:374–376 transverse dispersion, 5:46 Natural bioremediation, of selenium, 2:358–359. See also Bioremediation Natural coagulants, 4:426 Natural contaminant attenuation factors affecting the demonstration of, 5:586–589 microbial processes affecting, 5:578–594 Natural contaminants, 2:181 Natural dams, as a cause of flooding, 3:511–512 Natural disasters economic losses due to, 3:153, 154t

number and economic losses of, 3:153t Natural drainage networks, 3:94 Natural environments clathrate hydrates in, 4:473–474 microorganisms in, 3:309–313 Natural gamma logs, 5:152 Natural gas hydrates, 4:474 Natural groundwater tracers, 5:502–504 Natural hazards, floods as, 3:153–155 Natural heritage, protecting, 2:667 Naturally occurring radioactive materials (NORM), 2:287 Naturally soft water, availability of, 4:554–555 Natural organic material/matter (NOM), 1:248, 335, 357, 358–360, 370; 2:74, 75 reaction of ozone with, 1:359–360 removal of, 2:116 Natural phenomena, pollution caused by, 3:223 Natural resources. See also Natural water resource systems monitoring integrity of, 2:440–452 sustainable management of, 2:633–638 types of, 2:634 Natural Resources Conservation Service, 2:513 Natural Resources Inventory (NRI), 3:72, 73 Natural sources, of runoff pollution, 3:225 Natural retention, 1:404 Natural systems biochemical oxygen demand in, 1:639–640 microscale toxicity testing in, 2:379–380 Natural wastewater treatment, 1:840 systems for, 1:678 Natural water resource systems, 2:586 Natural waters antimony speciation in, 4:592 arsenic in, 1:81–83 carbonate in, 4:413–416 cause of alkalinity in, 2:394 classes of organic compounds in, 5:339t disinfection byproduct precursor removal from, 2:115–117

pollution of, 3:444 silica in, 4:548–551 sodium in, 4:551–553 trace metals in, 2:202 Nature Conservancy, Arizona Chapter, The (TNCA), 3:57, 58 Nature-like fish passage facilities, 3:531, 532f Navier–Stokes equations, 5:560, 561, 652, 656, 659 Navigation, role of sediment in, 3:508 Near-infrared (NIR) domain, 3:719 Negev Desert, dew amounts in, 4:203 Negombo Estuary, Sri Lanka, 4:53–54 Negotiations, authority-polluter, 4:647–648 Neoprene balloons, 4:165 Nephelometric turbidity units (NTUs), 1:236, 599; 2:544 Nernst equation, 1:399 Net ecological benefit concept, 2:477 Net head, 3:201 Netherlands, flood control history in, 2:524–526 Net pen aquaculture systems, 3:543–544 Net radiation, 3:563 Netting systems, for floatables control, 1:785–786 Neumann boundary conditions, 5:14, 561 Neurological effects, of lead, 2:435 Neurotoxins, 2:388–389; 3:189 Neutralization facilities, 1:610 Neutral water, 4:481 Neutrino detector, heavy water as, 4:464 Neutron density logs, 5:153 Neutron moderator, heavy water as, 4:463–464 Neutron moisture probe, 5:539–540 moisture measurement with, 3:692–694 Neutron thermalization soil moisture measurement, 4:488 Nevada in-stream flow protection in, 4:662 overdraft in, 5:343 New development, management of, 1:867 Newfoundland, aquatic habitat and construction in, 3:509 New Madrid, Missouri earthquakes, 5:477, 479

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CUMULATIVE INDEX

New Mexico, wastewater applications in, 1:634–635 New Jersey, source water protection in, 2:312 New Source Performance Standards (NSPS), 4:656 Newton, Isaac, 4:352 Newtonian fluids, 5:556 Newton–Raphson method, 5:142 Newton’s law of viscosity, 5:555–556 New York, extraterritorial land use control in, 1:316–317 New York City Harbor Survey, 1:745–751 physical setting of, 1:746 public policy and, 1:750 sewage treatment infrastructure and programs, 1:748 sociological setting of, 1:746–748 water quality trends, 1:748–750 New York City Historic Area Remediation Site (HARS), mapping the sea floor of, 4:77–80 New York State Department of Environmental Conservation (NYSDEC) criteria, 3:351 NEXRAD observations, 4:307, 309, 310 Nhieu Loc–Thi Nghe Project, 2:553 Niagara Falls, 2:554 dewatering of, 3:345–346 NICA–Donnan model, 2:206 Niche portals, 2:669 Nickel (Ni), in groundwater, 2:147 Nickpoints, 3:184 Nickzones, 3:184 Nicotinamide-adenine dinucleotide (NAD+ ), 2:42. See also NADH Nier/McKinney mass spectrometer, 5:228 Nile Basin solutions to water conflicts in, 2:593–594 transboundary water conflicts in, 2:590–594 water allocation in, 2:591–592 water scarcity in, 2:590–591 water-sharing framework for, 2:592–593 Nile Basin Initiative (NBI), 2:592 Nile civilization, 4:727–728 Nile River basin, 4:756–757 Nile River, salinity profile of, 3:680 Nile valley, recent development of, 4:729–730

Nile Valley Plan, 2:591 Nile waters, management of, 4:756–757 Nile Waters Agreement, 2:591–592 Nile Waters Treaty, 4:757 Nitrate(s). See also NO3 − acidification and, 3:5 anoxic biodegradation of, 5:325 diseases related to, 1:34–39 in drinking water, 2:219–220, 395–396 fate and transport of, 5:629 groundwater and food sources of, 1:33–34; 5:628–631 health effects/risks of, 1:30–42; 5:324, 629 history of, 5:628 innovative in situ treatment for, 5:328–330 ions, 1:668 in ponds, 3:486 population exposed to, 1:34t properties of, 5:628–629 regulation of, 5:629 remediation of, 5:630 reverse osmosis treatment of, 5:326–328 toxicity of, 4:519 treatment for, 5:323–331 in water and foods, 1:31–32 water use criteria for, 5:324 Nitrate concentrations, 5:252 Nitrate-contaminated agricultural runoff, treatment of, 5:329 Nitrate contamination. See also Nitrate pollution of groundwater, 2:570–571; 5:322–323 investigating, 5:630 maximum level of, 2:234t, 235t Nitrate leaching, 2:200 Nitrate Leaching and Economic Analysis Package (NLEAP), 2:252 Nitrate levels high, 5:407 water quality and, 1:32–33 Nitrate-nitrite poisoning, 1:38–39 Nitrate pollution. See also Nitrate contamination prevention of, 3:637–640; 5:325 sources of, 5:323 Nitrate-reducing to manganese-reducing conditions, 5:583

789

Nitrifer studies, 2:231 Nitrification, 1:789–790, 833; 3:640–642; 4:518. See also Nitritification in the activated sludge process, 1:751–755 in distribution systems, 2:226 factors influencing, 3:641–642 forms of, 1:752, 753t management of, 3:642 oxygen consumption during, 1:754t of potable water, 1:346–350 Nitrification/denitrification biofilm, 2:231 Nitrifiers, common species of, 3:640t Nitrifying trickling filters, 1:346–350 effect of support material on, 1:347 influence of recirculation on, 1:347–348 modeling and design of, 1:348–350 Nitrite health effects of, 5:324 maximum contaminant level of, 2:235t in ponds, 3:486 water use criteria for, 5:324 Nitrite ions, accumulation of, 1:752t. See also Nitrate-nitrite poisoning Nitrite-oxidizing bacteria (NOB), 2:231 Nitrite pollution, preventive measures for, 5:325 Nitritification, dynamic model of, 1:349 Nitrobenzene, 4:510 Nitrogen (N), 4:517–520. See also Ammonia nitrogen; C:N ratio; Nonconservative dissolved inorganic P and N fluxes; N/P (nitrogen/phosphorus) ratio; Organic nitrogen in an agricultural landscape, 3:604–605 algal growth and, 3:109 ammonification of, 4:517–518 in animal farming operations, 3:538–539 aquatic, 4:518–519 in constructed wetlands, 1:893 in domestic sewage, 1:831 in domestic wastewaters, 3:110 fixation of, 4:517 forms of, 2:269 fractionation of, 4:502 isotopes of, 4:519–520

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790

CUMULATIVE INDEX

Nitrogen (N), (continued) maximum contaminant level of, 2:234t, 235t as a nutrient of concern, 2:269 retention of, 2:200 sources of, 3:1–2, 695 tile drainage and, 3:729–730 water contamination by, 4:519 Nitrogen availability reporter system, 2:175 Nitrogen balance, 3:639 Nitrogen best management practices (N-BMPs), 3:696–699 Nitrogen cycle, 3:308; 4:517–518 Nitrogen deficiency, 3:694 Nitrogen deposition, 4:380 Nitrogen fertilizer, 2:572; 3:698 Nitrogen fixation, 4:517 Nitrogen fluxes, estuarine, 4:53–54 Nitrogen isotopes, 5:219–220 as groundwater tracers, 5:503 Nitrogen loading effect on human health, 3:696 identifying areas with, 2:571 Nitrogen management, in soil, 3:694–701 Nitrogen species, role in fish growth and production, 3:131–132 p-Nitrophenol (PNP), adsorption of, 1:117 4-Nitrophenol degradation, 1:793 ‘‘Nixtamalization’’ process, 1:582, 583f NO3 − , 3:6. See also Nitrate(s) NOAA Atlantic Oceanographic and Meteorological Laboratory, 4:4–6. See also National Oceanic and Atmospheric Administration (NOAA) NOAA Forecast Systems Laboratory (FSL), ground- based GPS meteorology at, 4:244–255 NOAA Geophysical Fluid Dynamics Laboratory (GFDL), 4:43–44 NOAA lake level forecast, 3:274–275 NOAA methyl bromide cycling study, 4:80–81 NOAA Pacific Marine Environmental Laboratory (PMEL), 4:89–92 NOAA Profiler Network (NPN), 4:249 No-action remediation, 5:44–45. See also Passive groundwater remediation Nocardioforms, 1:728–729

Nodal demands, distribution of, 3:315 Nodal replacement, for coupled flows, 5:660 Nodularins, 2:388, 390 NOEC calculations, 2:411. See also ‘‘No observed effect concentration’’ (NOEC) ‘‘No exposure’’ exclusion, 4:658 No-flow boundary, 5:419 Nonaqueous phase liquids (NAPLs), 2:44; 5:216, 439 Nonbreaking wave, 4:17–18 Nonbiodegradable organics, 1:903 Noncarbonate hardness, 1:323; 4:453 Noncarcinogenic effects advisories based on, 3:120 fish consumption advisories based on, 3:119–120 Noncarcinogenic PAHs, 3:350 Noncarcinogenic responses, 4:674 Noncommunity public water systems (PWSs), 4:676 Nonconservative dissolved inorganic P and N fluxes, 4:53–54 Nonconservative pollutants, 4:50–51 Nonconservative pollution, modeling of, 3:332–333 Nonculturing biofouling analytical methods, 1:85 Nonengineering water conservation interventions, 2:472–473 ‘‘No-net-loss’’ goal, 4:693 Nonexclusion principle, 1:216–217 Nongovernmental organizations (NGOs), 1:655–656 agriculture and land use planning, 3:598 water resource, 4:651 ‘‘Nonhazardous’’ waste management, 2:163 Nonindigenous fish species, 3:128 Nonindustrial leaching, 5:260 Nonionic surfactants, 1:670, 671t Nonlinear recession equation, 3:23 Nonnative species, introduction of, 3:125. See also Nonindigenous fish species Non-Newtonian fluids, 5:556–558 Nonoxidizing biocides, 2:242 Nonoxidizing chlorine byproducts (CBP), 1:129–130 Nonoxygen-based sensors, 2:41 Nonpathogenic microbes, 2:243

Non-point fluoride contamination sources, 5:132–133. See also Non-point source contamination Non-point source (NPS) contamination, 5:603. See also Non-point fluoride contamination sources; Non-point source (NPS) pollution Nonpoint source control, 2:184–189 federal programs for, 2:185–186 regulations related to, 2:185 by source categories, 2:186–187 total maximum daily load and, 2:188–189 Nonpoint source estimation, equations for variables used in, 3:662f Non-point source pollutant model components of, 5:300–303 scale of, 5:303–304 in the vadose zone, 5:299–305 Nonpoint source pollutants, 2:373–374 Nonpoint source (NPS) pollution, 2:181, 184, 544, 614; 3:37, 226t, 228–229, 502; 5:331–337. See also Non-point source (NPS) contamination control of, 4:595–596; 5:333–335 during and after development, 3:501–502 management of, 2:311 terrestrial, 3:282 Nonpoint source pollution assessment, role of Geographical Information System and remote sensing in, 3:658 Nonpoint sources, 2:169, 190 Nonpoint source water quality models, 2:248–249 Nonpolar molecules, hydration of, 4:475, 476 Nonpolar organic compounds, sorption of, 4:385–386 Nonpotable wastewater reuse, 1:821, 826 Nonpriority pollutant petroleum hydrocarbon analyses, 2:310–311 Nonrenewable natural resources, 2:634 Nonrival consumption, 1:216 Nonskeletal fluorosis, 4:435 Nonsparkling water, 1:4

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CUMULATIVE INDEX

Nonsteady state, of drainage water, 3:678 Nonstructural flood adjustment measures, 3:146–148 web pages related to, 3:150 Non-toxicant-specific luminescent biosensors, 2:454t Nontoxic chemicals, 2:278 Nontransient, noncommunity water systems (NTNCWS), 4:676–677 Nonturbulent channel units, 3:70 Nonweighing drainage lysimeters drainage measurements using, 5:488 recent usage of, 5:488–489 Nonyphenol aquatic toxicity, 1:673t No-observable-adverse-effect level (NOAEL), 1:33, 426 ‘‘No observed effect concentration’’ (NOEC), 2:381. See also NOEC calculations ‘‘No observed effect level’’ (NOEL), 2:381 Normalized Phaeophytinization Index (NPQI), 3:722 Normalized Pigment Chlorophyll Index (NPCI), 3:722 North American Free Trade Agreement (NAFTA), 4:645, 646 North Atlantic Oscillation Index, 4:340, 341 Northern Gulf of Mexico, coastal fog along, 4:230–239 Northwest Power Planning Council (NPPC), 4:614–615 Norway, coral reefs in, 4:34–35 ‘‘Not in my backyard’’ (NIMBY), 2:167 NPDES permits, 2:132, 188, 373; 4:655–656. See also National Pollutant Discharge Elimination System (NPDES) N/P (nitrogen/phosphorus) ratio, 2:143 Nramp proteins, 5:286 NSF International listing program, 1:381 Nuclear detonations, underground, 4:102–103 Nuclear fuel reprocessing, 1:561; 4:101–102 Nuclear fuel storage. See Spent nuclear fuel storage Nuclear power water use, 1:561

Nuclear reactors, activated carbon in, 1:105 Nuclear techniques, 5:165–166 Nucleation temperature, 4:585 Nucleic acid probes, 1:161–162 Nucleic acid sequence-based amplification (NASBA), 2:337–338 Nucleic acid testing, 1:85. See also DNA entries; Polymerase chain reaction (PCR) assay Nuisance plants, characteristics of, 3:744 Numerical modeling, 3:321–322; 5:33–35. See also Mathematical models; Numerical models case studies in, 3:322–325 of currents, 3:320–325 dimensions in, 3:321–322 for Orlando Naval Training Center, 5:83–85 verification, calibration, and validation in, 3:322 Numerical models, 2:272. See also Numerical modeling flow condition, 1:58 Numerical solutions, for subsurface drainage, 5:97 Numerical weather prediction (NWP), 4:350, 354 Numeric effluent system, 1:756–757 Nutating disc meters, 1:338 Nutrient adsorption, in biofouling, 2:239 Nutrient availability, in aquatic systems, 3:109–110 Nutrient concentrations in natural environments, 3:311 in sediment column porewater, 4:73–77 tidally mediated changes in, 4:81–85 Nutrient control, 3:111 Nutrient control programs, issues in developing, 3:111 Nutrient deficiencies, in activated sludge processes, 1:729–730 Nutrient excretion, bivalve, 4:12–13 Nutrient excretion rates, bivalve, 4:6–11 Nutrient export coefficients, 3:110 Nutrient load criteria, 3:111 Nutrient loading, 2:3 Nutrient management, 2:571

791

Nutrient/phosphorus load reduction, rate of recovery after, 3:112–113 Nutrient pollution, tile drainage and, 3:729–730 Nutrient-related water quality, 3:111–112 Nutrient research, on agricultural drainage ditches, 3:89 Nutrient runoff control, 3:110–111 Nutrients. See also Microbial nutrients for algal growth, 2:269–270; 3:110–113 biological removal of, 1:399–400 from cage farms, 3:580 in coastal waters, 4:25 control of, 3:483; 5:334 distributional pattern of, 4:81 enhanced biodegradation and, 5:320 enhancement and distribution of, 5:117 in estuaries and bays, 4:26 impact on coral reefs, 4:114 limiting, 3:109 in lotic aggregates, 3:306–307 luminescent bacteria for determining, 2:175 ‘‘luxury uptake’’ of, 3:273 managing, 2:186 in marine environments, 4:51 removal by constructed wetlands, 3:368–369 role in estuaries, 4:51–52 sources of, 3:115 tidal stream variability and, 4:131–132 in urban stormwater runoff, 3:434 in water, 1:903 in water bodies, 2:3 as water pollution, 4:97–98 as water quality indicators, 2:266 Nutrient transformation processes, 2:270 Nutrition, emergency, 2:528

O2 evolution, implications of substrate water binding for, 4:540–541. See also Molecular oxygen Observation wells, characteristics of, 5:496 Obukhov length, 4:1

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792

CUMULATIVE INDEX

Occupational Safety and Health Administration (OSHA) water handling standards, 2:162 Occupations, water-transportation, 4:762–766 Occurrence-based reliability, 3:261 Ocean(s). See also Ocean water(s) capacity to absorb carbon dioxide, 4:86 debris abatement in, 4:38–41 dissolved gases in, 4:451 factor in determining surface temperatures, 4:183 frozen water in, 4:194 interaction with atmosphere, 4:22 measuring, 4:22 modeling, 4:22–23 processes in, 4:21 properties of, 4:21 renewable energies from, 4:44–49 role in climate, 4:21–23 role in climatically-active trace-gas cycles, 4:85–89 salinity in, 4:21 Ocean Acoustics Division (NOAA), 4:6 Ocean-atmosphere models coupled, 4:86 three-dimensional, 4:172 Ocean Chemistry Division (NOAA), 4:6 Ocean CO2 uptake, 4:86 Ocean Conservancy, 4:39 Ocean Drilling Program (ODP), 4:61 Ocean dumping, types of, 4:145 Ocean fishery stocks, overexploitation of, 4:124–125 Oceania, water symbolism in, 4:786 Oceanic chalk, carbonate as, 4:414–415 Oceanic circulation, changes in, 4:174–175 Oceanic processes, 4:104–105 Oceanic sound, fate of, 4:570 Oceanographic environment, Glacier Bay, 4:61–62 Oceanographic processes, stock assessments and, 4:57 Oceanography fisheries, 4:55 GLERL instrumentation in, 4:70–72 physical, 4:95–96 Ocean pollution, response of indicator groups to, 2:441–442

Ocean ranching, 3:128 Ocean shipments/dumping, precautionary principle regarding, 2:600 Ocean surface waters, antimony concentration in, 4:592 Ocean thermal energy conversion (OTEC), 4:47–49 Ocean thermal energy conversion plants, 4:47–48 Ocean waste disposal effects of, 4:103–104 increase in, 4:146 Ocean water(s), 4:285 heating of, 4:584 composition of, 4:285 Octanol–water partition coefficient, 1:574 Oculina varicosa, 4:34 distribution of, 4:35 threats to, 4:36–37 Odor abatement. See also Odor-reducing additives aqueous phase partition and, 1:761–762 biodegradability and, 1:761 biological treatment technologies for, 1:762–763 causes of odor, 1:760–761 choices related to, 1:763 competing technologies for, 1:762 odor measuring systems, 1:760 volatility and, 1:761 in wastewater treatment plants, 1:760–764 Odor analysis, state-of-the-art developments in, 2:281 Odor control, using ozone, 1:355 Odor measurement methods, basis of, 2:281 Odor monitoring, electronic nose for, 2:281–284 Odor-reducing additives, 1:912–913 Odors. See also Odor abatement; Sewerage odors of domestic sewage, 1:830 landfill, 2:166 of water, 1:902 18 O exchange kinetics, 4:538–539, 540. See also 18 O-labeled water rapid, 4:536–537 Off-channel pumped storage development, 3:201

Office of Environmental Health Hazard Assessment (OEHHA), 1:479 Office of Oceanic and Atmospheric Research (NOAA), 4:4–5 Office of Solid Waste and Emergency Response (EPA), 2:517 Off-site sewage treatment systems, 1:830 Offstream reservoirs, 3:411 Offstream storage, 1:486 Offstream water use, 2:650 Ohio River Sanitary Commission (ORSANCO) compact, 4:651–652 Ohm’s law, 4:442 Oil toxic components in, 4:106 in urban stormwater runoff, 3:435 as water pollution, 4:98–99 Oil-destroying microorganisms, 2:449 Oil-field brine (OFB), 2:284–290 controlling by wastewater treatment methods, 2:288–289 historical control practice for, 2:285 impact on water quality, 2:287t pollution aspects of, 2:286–288 use in oil production, 2:285–286 Oil-methylesters, 3:546–547 Oil pollution, 2:290–292. See also Exxon Valdez oil spill; Oil spills microorganisms as indicators of, 2:441–442 Oil Pollution Act, 4:597 Oil price increases, 4:479 Oil recovery, 1:561 Oil-related accidents, 4:99 Oil reservoir monitoring, 5:54 Oil-resistant microorganisms, 2:448t Oil slicks, surface, 4:106 Oil spills. See also Exxon Valdez disaster biggest, 2:291t effects of, 4:105–107 case study of, 2:172 Oklahoma, drought index used in, 4:213 18 O-labeled water, 4:537 Old groundwaters, 36 Cl and, 4:416–420 Olfactometry, 2:281 Oligochaetes, accumulation patterns for, 2:215 Oligotrophic systems, 3:268 Oligotrophy, 1:248 Ombrogenic areas, 1:404

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CUMULATIVE INDEX

Omega equation, 4:354 Once through systems, 1:559–560 One-dimensional numerical models, 3:321–322 One-dimensional transport equations, 5:525–526 One-way flow systems, rivers and streams as, 3:437–439 On-line drippers, 3:622 Online monitors, bioluminescence-based, 2:174 On-line respirometry, 1:565–571 Online water toxicity, monitoring luminescent bacteria in, 2:174 On-site disposal systems, managing runoff for, 2:187 On-site sewage treatment systems, 1:520, 830 OnSite system, 5:81 On-site water quality determination, luminescent bacteria for, 2:173 Open channel flows, 3:195–196 design of, 3:346–349 Open-cut trench construction, 1:876 Open limestone channels, 2:424 in acid mine treatment, 5:6–7 Open ocean fisheries management, 3:126–127 Open ocean N2 O emissions, 4:87 Open recirculating systems, 1:559 Open waterbodies, heat balance of, 3:190–194 Operating storage, 1:409 Operational meteorologists, 4:328, 329 ‘‘Operational storage,’’ 1:202 Operations and maintenance (O & M) contracts, 1:388, 389 Optical pH sensors, 2:299 Optical properties of plant canopies, 3:720 of plant leaves, 3:719–720 Optical televiewer, 5:154 Optimization, science of, 3:386 Optimization algorithms, 4:298 Optimized soil-adjusted vegetation index (OSAVI), 3:722 Optimum sustainable yield, 3:124 Option contracts, 2:607 Option prices, 2:607 ORBAL plant, 1:742 ORCHESTRA program, 5:141 Oregon, in-stream protection in, 4:660 Organic acid anions, 3:2

Organic agriculture, 3:644–646 Organically cultivated vegetables, organochlorine pesticides in, 3:645–646 Organic arsenic species, 2:12–13t Organic binders, 1:836 Organic carbon. See also Carbon (C) control of, 2:224–225 in distribution systems, 2:244–245 types of, 2:224–225 Organic chemical monitoring, 2:267 Organic chemicals/compounds, 5:185, 258–259. See also Organic removal; Organic materials; Organic waste compounds adsorption of, 4:384–388 adsorption on carbons, 4:407 aqueous reactions with ozone, 1:765–766 classes of, 5:339t competitive sorption of, 1:115–119 in domestic sewage, 1:830–831 in drinking water, 2:372–373 in groundwater, 5:337–340 in Puget Sound Basin sediment and fish, 3:349–362 removal by biological filtration, 1:248–249 sorption of, 4:386 transport of, 4:384 in urban stormwater runoff, 3:435 water contamination from, 5:339–340 year first available, 3:170t Organic contaminants, 1:375t. See also Organic wastewater contaminants in Indian rivers, 3:449 metabolism of, 5:529 removal by constructed wetlands, 3:368 Organic contamination, indicators of, 2:442 Organic loading, relation to eutrophication, 2:142–143 Organic materials, sorption onto, 5:5 Organic matter, 2:544. See also Organic soil matter in an agricultural landscape, 3:606 in constructed wetlands, 1:892, 894 degradation of, 1:726; 3:180 flooded, 3:206 in foulant samples, 1:417 microbially mediated oxidation of, 2:464–465

793

oxygen deficiencies and, 3:130 removal of, 4:426–427 in water, 1:903 Organic micropollutant removal, by activated carbons, 4:506–511 Organic nitrogen, 3:538 Organic phosphorus, 3:702 Organic pollutants, microbial indication of, 2:441 Organic pollution assessments, microbial biosurveys for, 2:449 Organic pollution measures, alternative, 2:40 Organic polymers, as coagulants, 4:426 Organic removal, 1:350–353 by organoclays, 1:772 in small systems, 1:351–353, 460 Organic soil matter, nitrogen in, 3:695 Organic vapor analyzers (OVAs), 5:549 Organic vapors, 5:545 biodegradation of, 5:545 sorption of, 5:545 sources of, 5:543–544 transport and fate of, 5:544–545 Organic waste compounds most frequently detected, 5:61t inhibitory threshold concentrations of, 1:754t water contamination by, 5:60–63 Organic wastewater contaminants, in U.S. streams, 5:605–608 Organism assemblage information, 4:600 Organisms. See also Indicator organisms; Microorganisms; Pathogens/pathogenic organisms; Sediment dwelling organisms cadmium in, 5:617 effects of pharmaceuticals on, 1:376–377 hatchery-raised, 4:126 labeled substrate probes for, 1:645–646 selection for sediment toxicity tests, 2:459 trace element concentrations in, 4:111 Organization for Economic Cooperation and Development (OECD) BOD5 standard, 2:39

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794

CUMULATIVE INDEX

Organization for Economic Cooperation and Development (OECD) (continued) eutrophication study data, 3:112 Organizations, water resource, 4:648–651 Organoantimony compounds, 4:592 Organochlorine compounds in Puget Sound Basin sediment and fish, 3:349–350 in sediment, 3:353–354t in tissue, 3:360t Organochlorine pesticides (OCPs), 3:649–650 absorption and accumulation of, 3:643–644 occurrence of, 3:643–647 Organoclay oil removal by, 1:774–776f role in water cleanup, 1:771–781 in treating contaminated groundwater, 1:777t Organoclay indicating partition, 1:773f Organolead, uptake of, 2:434. See also Lead (Pb) Organophosphorous compounds, 1:548t Orifice meters, 1:338 Orifices, flows through, 3:195 ‘‘Orifice’’ type roof drainage, 1:56 Orinoco basin, 4:642 Orlando Naval Training Center feasibility investigation at, 5:81–85 model application for, 5:83 Orthokinetic flocculation, 1:252 Orthophosphate, 1:788, 789 Oscillating water columns (OWC), 4:45 Oscillations, in lakes, 3:267 Oslo process, 4:700 Osmolality, 4:521 Osmolarity, 4:459 Osmosis, 2:544; 4:458, 459, 520–521 Osmotic concentrations, units for, 4:521 Osmotic forces, head and, 5:180–181 Osmotic potential, 5:181, 532 Osprey, effects of DDT on, 3:518–519 OSPREY oscillating water column, 4:45 OSPREY research vessel, 1:748 Ostwald’s experiment, 5:649–650 OTIS program, 5:141

Our Common Future, 2:625–626, 633 Outbreak detection, early, 1:186–187 Outdoor residential water use, 2:652 Outdoor water-conservation measures, 3:553 Outdoor watering equipment, 2:666 Outdoor water sources, emergency, 2:527 Outfall, defined, 2:544 Outflow rate, river, 3:392 Outflow structure design, 3:500 Outgassing, 4:159 Overall existence ranking index (OERI), 2:681 Overburden analyses, in acid mine drainage, 5:1–2 Overcapitalization, during the Great Depression, 2:511 Overdraft, 5:340–343, 604 Overfishing, impact of, 4:107–108 Overland flow (OLF) infiltration-excess, 3:452 saturation-excess, 3:452–453 Overlay and index approach, to pesticide assessment, 5:595 Overtopping, 4:16–17, 19 Oxidants, chlorine-produced, 1:128 Oxidation, 1:380, 811–812 of arsenite [As(III)], 1:639; 5:19–20 chemical, 2:300 cometabolic, 2:300 electrobiochemical, 5:122 electrochemical, 5:122 of iron, 1:313–314; 5:609 of landfill leachates, 1:706–707 in limestone-based FGD systems, 1:849 of manganese, 1:313–314 in mine effluent remediation, 1:611 for odor abatement, 1:762 ozone-induced, 1:765 Oxidation and reduction (redox), 5:185, 527. See also Oxidation–reduction entries; Redox entries of metals, 5:283 potential, 5:321, 584 Oxidation processes, 5:441–442 advanced, 1:871–872 Oxidation–reduction potential (ORP), 2:466. See also Eh ; Oxygen redox potential (ORP); Redox entries Oxidation–reduction potential values, 1:850

Oxidation–reduction (redox) reactions, 1:399, 725; 4:518. See also Redox potentials Oxidation states, of wetlands, 3:367 Oxidative capacity (OXC), 2:468 Oxidative precursor removal, 2:120 Oxidized carbons, sorptive capacity and selectivity of, 2:84 Oxidizing biocides, 1:602; 2:242 Oxygen (O), 4:189. See also Dissolved oxygen (DO); Ozone delivery, 5:424–425 isotopes, 4:501–502 profiles, 4:451 singlet, 4:533 Oxygenated hydrophilic groups, 4:401 Oxygenation, of sludge, 1:857 Oxygen-based sensors, 2:40–41 Oxygen complexes, in activated carbons, 2:81 Oxygen concentration. See also Dissolved oxygen (DO) influence on nitrification, 3:642 in ponds, 3:485 Oxygen demand, 2:544 biochemical, 1:639–642 Oxygen-demanding wastes (ODWs), as water quality indicators, 2:266 Oxygen demand threshold, 5:424 Oxygen depletion, in waterbodies, 2:181 Oxygen enhancement, 5:117 Oxygen fugacity approach, 5:414 Oxygen isotope exchange measurements, 4:536 Oxygen isotopes, as groundwater tracers, 5:503 Oxygen limitation, in biofilms, 2:231–232 Oxygen-reducing to nitrate-reducing conditions, 5:583 Oxygen redox potential (ORP), 2:231. See also Oxidation–reduction potential (ORP); Redox entries ‘‘Oxygen-sag curve,’’ 3:449 Oxygen transfer efficiency (OTE), 1:623 in diffused air aeration systems, 1:629 Oxygen transfer rate (OTR), 1:623 Oxygen uptake rates (OUR), 1:565, 566, 568 Ozonation, 1:199, 458, 817; 2:119, 244, 374. See also Ozone

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CUMULATIVE INDEX

byproducts of, 1:355, 363 domestic sewage, 1:834 municipal water supply, 1:362–365 personnel requirements for, 1:355 process and equipment for, 1:355 Ozone, 1:195, 313, 354–357, 603; 4:270 chemistry of, 1:362–363 at CSO facilities, 1:786 disinfection byproducts and, 1:214 disinfection using, 1:354–356 health and safety precautions for, 5:349 injection, 5:442 organic compound reactions with, 1:765–766 safety of, 1:356 Ozone–bromide interactions, 1:357–362 bromate formation, 1:358–359, 359–360 bromate ion minimization strategies, 1:360–361 bromate ion removal, 1:361 bromide ion, 1:358 Ozone bubble-diffuser contactor, 1:363–364 Ozone contactors, 1:356, 363–364 for odor removal, 1:914–915 Ozone dose, in bromate ion formation, 1:359 Ozone generation, feed gas preparation for, 1:356 Ozone leachate treatment, 1:706 Ozone off-gas destruction, 1:356 Ozone treatment, 5:347

Pacific Fisheries Environmental Laboratory (PFEL), research at, 4:96 Pacific Guano Works, 4:140–141 Pacific Marine Environmental Laboratory (PMEL), 4:89–92 Pacific-North American (PNA) circulation pattern index, 4:174 Pacific Northwest Electric Power Planning and Conservation Act, 4:614 Pacific Tropical Atmosphere Ocean (TAO) array, 4:91 Packaged filtration, 1:229 Package plants, 1:514–517 advantages and limitations of, 1:515

filtration systems for, 1:515–517 operation and maintenance of, 1:517 selecting, 1:515 Packed column aeration (PCA), 1:51, 352–353, 460 Packing cell formation, 2:240 PACT process, 2:87–88 PAH compounds, 1:573, 574, 575. See also Polycyclic aromatic hydrocarbons (PAHs) Pain, thirst and, 4:724–725 Pakistan, national identity of, 4:683 Paleoceanography, seawater temperature estimates in, 4:92–95 Paleoclimatology, 4:93 Palmer Drought Severity Index (PDSI), 4:211–212 limitations of, 4:212 Palmer Hydrological Drought Index (PHDI), 4:211 Palmer Index, 2:581 Pamlico-Albemarle Estuarine Complex, 4:57 Pan American Center for Sanitary Engineering and Environmental Sciences (CEPIS/PAHO), 2:671, 673, 674 Pan American Health Organization (PAHO/WHO), 2:671, 672, 673 Pan evaporation method, 3:573 Pantanal wetland, 4:642 Paper industry, impact on surface water quality, 3:374 Paraguay-Parana River hydro-via, 4:642 Parallel plate electrode arrangement, 4:430 Parallel scour pools, 3:68 Paralytic shellfish poisons (PSPs), 2:389 Parameter calibration, 4:298 Parameter estimation, 4:221 chlorine reaction, 1:134–135 inverse model for, 1:135–136 Parameter optimization, 2:332; 4:299 Parametric mapping, 5:657 Parasites, 3:668–669 in constructed wetlands, 1:894 fate and transport in karstic aquifers, 1:365–370 waterborne, 2:344t Parasitic infections, 1:25

795

Partial private-sector responsibility model, 1:50 Participatory integrated capacity building (PICB), 1:652–654; 2:628–629 Participatory multicriteria flood management, 2:678–683 Particle density, 1:96 Particle settling velocity, 1:259–260 Particle size (dp ), 2:545; 3:300 Particulate arsenic, 2:11 Particulate matter, in wetlands, 1:892 Particulate metal contamination, 5:281 Particulate phosphorus (PP), 3:704 Particulate removal, 1:370–372 by coagulation, 1:137–139 by filtration and sedimentation, 1:243–245 by granular media filtration, 1:233 by high-rate granular filtration, 1:250 Particulate transport, in groundwater, 5:349–352 Partitioning, 4:521–524 properties that determine, 4:522–524 Partnering, 1:42 EPA Pretreatment Program, 1:798–799 Passive biomonitoring (PBM), 2:33 Passive biotreatment, 5:120. See also Passive groundwater remediation Passive diffusion samplers case study of, 5:458–459 groundwater sampling with, 5:456–460 Passive disease reporting, 1:185 Passive filter systems, 1:237 Passive groundwater remediation, 5:423–426. See also No-action remediation; Passive biotreatment Passive immobilization, of metals, 5:283 Passive in situ remediation technologies (PIRT), 5:423 Passive microwaves, 4:324 Passive radioactivity log, 5:152 Passive reactive treatment, of vinyl chloride, 5:638–639 Passive remote sensing, spectral regions used for, 4:320

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796

CUMULATIVE INDEX

Passive sound detection, 4:570 Passive treatment of acid mine drainage, 2:423–426 selecting, 2:425f systems, 2:424f Passive vapor survey, 5:437 Pasteurization, of sludge, 1:858 Pathogenic bacteria. See also Pathogens/pathogenic organisms detection in surface waters, 2:441 removal of, 1:485–489 Pathogenic microorganisms, wastewater-associated, 3:668t Pathogenic pollution, 2:182 Pathogens/pathogenic organisms, 1:903–904; 2:545. See also Pathogenic bacteria in animal farming operations, 3:539–540 in constructed wetlands, 1:894 in domestic sewage, 1:831 drinking water, 1:277 impact on coral reefs, 4:115 opportunistic, 1:342 persistence of, 1:521–523 waterborne, 2:344t as water pollution, 4:97 as water quality indicators, 2:266 Patuxent Wildlife Research Center, 3:519 Paul Lake, biomanipulation trials in, 2:56t Pb bioavailability, microbial aminolevulinate dehydratase as a biosensor for, 2:236–237. See also Lead (Pb) PCB-contaminated sediments, Hudson River, 2:126 PCB/dioxin-like compounds, cytochrome P450 monooxygenase as an indicator of, 2:106–111 PCR-based monitoring, of Salmonella, 2:338–339 Penalty finite element scheme, 5:658 pe, 2:466. See also Eh ; pH Peak discharge, 3:143 Peak flow, 2:545 Peaking plants, 3:202 Pearl River, 4:697 Pedersen–Burcharth formula, 4:17 Pelagic fish, 3:126 Pelagic organisms, 3:310 Pelagic zone, 3:267, 268

Penman–Monteith energy balance equation, 3:574, 576, 721; 5:78 Penman–Monteith model, 4:227 Penneable material, 5:600 Pennsylvania, source-water protection in, 2:312 Pennsylvania Drought Contingency Plan, 2:581 Pens, role in trout hatching, 3:458–460 Penstock, 2:554 Pentachlorophenol (PCP), 1:689 Pentavalent arsenic compounds, 2:11, 16 People’s World Water Forum (PWWF), 1:215 Peracetic acid, 1:604 at CSO facilities, 1:786 Per capita use, 2:545 Percent of normal calculation, 4:209–210 Perceptual model (PM) uncertainty, 3:325 Perched groundwater, 5:352–355 examples of, 5:353–354 hydraulic properties of, 5:352–353 hydrologic conditions related to, 5:353–354 role in contaminant movement, 5:354–355 Perched water table, 5:11 Perchlorate, 2:317, 345 characteristics and persistence of, 5:632 fate and transport of, 5:632 in groundwater, 5:631–634 health risks of, 5:632 physical removal technologies for, 5:633 remediation of, 5:632–633 as an unrecognized pollutant, 3:372 uses for, 5:631 Perchlorate Community Right to Know Act of 2003, 2:345 Perchloroethene (PCE), 5:91 Perchloroethylene (PCE), 2:317 removal of, 2:299–301 ‘‘Percolating’’ groundwater, 4:630 Percolation, 2:545 Percolation tank, 2:551 Perennial flow, artificial, 2:477 Perennially draining epikarsts, 5:237 Perennial streams, base flow and, 3:22 Perennial waters, 2:475

Performance, impeller, 1:80 Performance evaluation, for water resource systems, 2:674–678 Performance failure, 3:259 Performance indicators, for developing countries, 1:721 Perhydroxyl radical, 4:446; 5:345 Perikinetic flocculation, 1:252 Periodicity analysis, 4:338–339 Peripheral nervous system, effects of lead on, 2:436 Peripheral neuropathy, 2:436 Periphyton index of biotic integrity (Periphyton IBI), 3:40 Permanent frost (permafrost), 4:305–306 geography of, 4:306 groundwater and, 5:601 Permanganate salts, health and safety precautions for, 5:348–349 Permanent magnetic water conditioning (PMWC), 1:141, 143, 144 Permanent Service for Mean Sea Level (PSMSL), 4:118–120 METRIC dataset from, 4:119 Permanent spot market, 2:606–607 Permanent water hardness, 4:453 Permanent wilting point, 4:485 Permanganate treatment, 5:346–347 Permeability (k), 2:545; 5:355–357 conversion factors, 5:509t groundwater, 5:128–129 soil, 3:30 values of, 5:356t Permeable reactive barriers (PRBs), 5:518–519, 423, 442 field data sources and model setup for, 5:519–520 technology of, 5:41–42 Permeameters, 5:512–513 Permit statutes, 4:632 Peroxyl radicals, 4:532–533 Persistent organic pollutants (POPs), 4:99 in the activated sludge treatment process, 1:767–769 in the wastewater treatment process, 1:766–771 Personal care products (PPCPs), 1:819–820. See also Pharmaceuticals and personal care products (PPCPs) as unrecognized pollutants, 3:371–372

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CUMULATIVE INDEX

Pertechnetate anion, 4:579 Perturbed continuity modeling scheme, 5:658 Pervious toe drain, 3:290 Pervious toe trench, 3:289 PES capillary membranes, 1:593 Pesticide assessment approaches to, 5:595–598 uncertainty in, 5:358–359 Pesticide-caused toxicity, of urban stormwater runoff, 3:433–434 Pesticide chemistry, 3:647–651 Pesticide-contaminated soil, remediation of, 3:651–655 Pesticide groups, 3:648–649 Pesticide leaching assessment, 5:359t Pesticide research, on agricultural drainage ditches, 3:90t Pesticide Root Zone Model (PRZM), 2:252 Pesticides agricultural, 3:607, 643 behavior of, 3:647–648 biological and chemical degradation of, 3:648 control of, 5:334–335 effect on surface water, 3:374, 650 environmental pathways of, 3:655 groundwater vulnerability to, 5:357–362, 594–599 important, 5:358t managing, 2:186 occurrence/use relationship for, 3:655–657 organochlorine, 3:352, 643–647, 649–650 runoff and leaching of, 3:648, 651–652 sorption to soil components, 3:648 in surface waters, 5:332 tile drainage and, 3:729 transport and transformation processes of, 3:655 as unrecognized pollutants, 3:372 volatilization of, 3:648 water quality and, 2:266, 303 Pesticide-use issues, key, 3:656 Pesticide vulnerability assessment, 5:595 Pesticide vulnerability maps, 5:598 Pest Management Regulatory Agency (PCPA), 1:382

Peter the Great Bay, 2:445 features of marine bacteria in, 2:446–447 heavy metal monitoring in, 2:446 Petroleum hydrocarbons, 5:43, 116, 322, 428 aerobic biodegradation of, 5:320 degradation of, 1:692–694 plants that spur degradation of, 3:629 Petroleum pollution, 2:290–292. See also Oil entries Petroleum products, 2:304 Petroleum residues, 4:98 Pfiesteria, 3:108; 4:108 Pfiesteria piscicida, 3:702 pH, 2:294–299, 544; 5:184. See also High pH groundwater; pH adjustment of acid mine drainage, 2:1 acid-neutralizing capacity and, 3:1 bacteria and, 3:14; 5:321 bromate ion concentration and, 1:360 dishwater, 2:113 effect of carbon on, 1:97 effect on adsorption, 3:299 effect on corrosion, 1:8 impact on DBP concentrations, 2:119–120 influence on nitrification, 3:641 inorganic ion removal and, 4:491–492 measurement of, 2:295–299 microbial growth and, 3:312 organic matter removal and, 4:427 of pond water, 3:487 relationship to acidity, 3:8 research on, 2:352–353 role in fish growth and production, 3:131 soil, 5:367 theory of, 2:294–295 of urban stormwater runoff, 3:434 pH adjustment chemicals used for, 1:10t corrosion control via, 1:9–10, 153 of landfill wastewater, 1:705 Pharmaceutical industry, activated carbon in, 1:105 Pharmaceuticals in animal farming operations, 3:540 characteristics of, 1:374t

797

detection in effluent-receiving water systems, 1:376 effect on human health, 1:377 in the environment, 1:372–373, 376–377 persistence of, 1:375–376 regulations concerning, 1:377–378 in sewage treatment facilities, 1:373–376 in the United States, 1:373 in water systems, 1:372–378 Pharmaceuticals and personal care products (PPCPs), 3:435. See also Personal care products (PPCPs) as unrecognized pollutants, 3:371–372 Pharmaceutical water-for-injection systems, 1:602 Phase I Environmental Assessment, 5:437 Phase I stormwater discharge regulations, 4:657–658 Phase II stormwater discharge regulations, 4:658 Phase II Subsurface Investigation, 5:437 Phase III Corrective Action, 5:437–438 Phase IV groundwater monitoring, 5:438 Phasing practice, for landfills, 1:697–698 pH balance, in the body, 4:456 pH buffer(s), 2:295 carbonate as, 4:414 Phenol adsorption effect of carbon surface chemical composition on, 4:404–408 by organoclay, 1:777f porous structure and, 4:407 on zeolites, 4:406 Phenolic compounds, 1:530. See also Phenols Phenol number, 1:98 Phenology, crop, 3:722–723 Phenol-resistant microorganisms, 2:448t Phenols adsorption of, 1:117, 119 microbial detection of, 2:442 toxicity of, 4:524 pH glass element, 2:296 Phoenix, Arizona, overdraft in, 5:341–342 PhoP primers, 2:338

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798

CUMULATIVE INDEX

Phosphate concentration, 5:199 Phosphate fluxes, estuarine, 4:53–54 Phosphates distribution of, 4:74 inorganic, 1:154 Phospholipid Fatty Acid (PLFA) analysis, 1:85 Phospholipid Fatty Acid Methyl Ester (PL-FAME) analysis, 1:85 Phospholipids, 2:442 Phosphorus (P). See also Nonconservative dissolved inorganic P and N fluxes; N/P (nitrogen/phosphorus) ratio; Phosphates; Phosphorus removal; Soil phosphorus in an agricultural landscape, 3:605–606 algal growth and, 3:109 in animal farming operations, 3:539 in constructed wetlands, 1:893 in distribution systems, 2:245 in domestic sewage, 1:831 forms of, 2:269 in foulant samples, 1:418–419 as a nutrient of concern, 2:269–270 tile drainage and, 3:730 Phosphorus-accumulating organisms (PAO), 1:788 Phosphorus availability indices, 3:703 Phosphorus loading, reduction in, 3:113 Phosphorus precipitation, in algal control, 2:4 Phosphorus removal in the activated sludge process, 1:788–791 biological, 1:816, 833 Phostrip process, 1:790 Photocatalysis, 1:872 heterogeneous, 1:791–792 Photocatalyst, 1:792. See also Photocatalysis Photocatalytic membrane reactors in pollutant photodegradation, 1:793–795 in water purification, 1:791–797 Photocatalytic oxidation, 2:300 Photochemical Reflectance Index (PRI), 3:722 Photochemistry, environmental, 4:529–535

Photography, water in the history of, 4:766–769 Photoionization detectors (PIDs), 2:307; 3:689 Photon emitters, health risks of, 1:396 Photophysical processes, 4:530 Photoreactivation, 1:471 Photospheres, water in, 4:190 Photosynthesis crop, 3:721–722 sensitivity to Pb toxicity, 2:434 Photosynthetic bacteria, 2:21 Photosynthetic O2 evolution, rapid 18 O exchange measurements during, 4:536–537 Photosynthetic water productivity, 3:560 Photosystem II (PSII) enzyme complex, 4:535 Phragmites research, 4:57 PHREEQC geochemical code, 5:33 PHREEQC program, 2:363–364; 5:140, 143 pH reference element, 2:296–297 PHRQCGRF program, 5:140 PHRQPITZ program, 5:140 Physical adsorption, 1:99 Physical barriers, to vinyl chloride, 5:639 Physical carbon activation, 1:94–95 Physical–chemical treatment of landfill leachates, 1:709–713 of leachates, 1:704–708 of vinyl chloride, 5:638–639 Physical control, of biofilms, 1:541–542 Physical CSO treatment, 1:783–786 Physical Habitat Simulation (PHABSIM) models, 3:106, 526 Physical infiltration models, 4:487 Physical intrusion, guarding against, 1:870 Physical meteorologists, 4:328 Physical models, 3:328, 337 Physical oceanography, 4:95–96 Physical Oceanography Division (NOAA), 4:6 Physical pollutant removal processes, 3:366 Physical reactors, sewers as, 3:331–332 Physical recharge measurement, 5:74 Physical screen fish passage facility, 3:530

Physical separation techniques, 5:435 Physical wastewater treatment technologies, 1:809–811 Physical water conditioning, 1:141–145 Physicochemical monitoring, 2:267 Physiologically based extraction test (PBET), 4:526 Physiology, microbial, 5:580–582 Physisorption, 4:386 Phytoaccumulation, of cobalt, 5:612–613 Phytin, 1:788 Phytochelatins (PCs), 2:406; 5:287, 371–372, 376 role in plant protection, 3:610–612 Phytochelatin (PC)-synthase activity, 5:287 Phytocontainment, assessment and characterization of, 5:76–77 Phytodetoxification, 5:399 Phytoextraction, 5:285, 365–369, 399, 434 economic considerations related to, 5:367–368 future of, 5:372 for lead-contaminated soils, 5:382–383 of metals, 5:288 optimization of, 5:372 regulatory considerations related to, 5:368 using hyperaccumulator plants, 5:369–374 Phytoextraction coefficient, 3:35; 5:383 Phytofiltration, 5:399 Phytohydraulic containment, 5:77 Phytohydraulic containment and treatment, feasibility investigation for, 5:81–85 ‘‘Phytolignification,’’ 5:383 PHYTOPET database, 3:628–629 Phytoplankton, 2:142–143, 269; 4:154 estuarine, 4:52 trace elements in, 3:456 PHYTORAD database, 3:635 PHYTOREM database, 3:629–633 contents and update recommendations for, 3:633 fields, description, and access for, 3:632–633t

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CUMULATIVE INDEX

hyperaccumulation and accumulation criteria for, 3:631t Phytoremediation, 5:366. See also Remediation applications of, 3:629 of cadmium, 5:618 components of, 5:377 by constructed wetlands, 3:364–371 of contaminated soil, 3:653–654 genetic engineering of plants for, 5:288 hydrocarbon and metal, 3:628–637 hydrologic feasibility assessment and design in, 5:76–87 of lead, 5:648 of lead-contaminated soils, 5:381–385 of metals, 5:284–285 of methyl tertiary-butyl ether, 5:385–397 need for, 3:739 of selenium-laden soils, 5:397–401 soil, 5:434 types of, 5:375t of uranium, 5:641 Phytoremediation enhancement, of natural attenuation processes, 5:374–376 Phytoremediation reactions, influences on, 3:367 Phytostabilization, 5:365–369, 399, 434 economic considerations related to, 5:367–368 for lead-contaminated soils, 5:383 regulatory considerations related to, 5:368 Phytovolatilization, 5:399 Pick–Sloan plan, 4:616 Piedmont lakes, 3:265, 270 Piezometric head, 5:160 Piezometric surface, 5:600–601 Pilot systems, corrosion control in, 1:11 Pipe bedding, 1:890 Pipe coatings/linings, 1:154 Pipe diameter measuring, 1:401f pipe roughness versus, 3:314–315 Pipeline renovation, using trenchless techniques, 1:876–882 Pipelines. See also Pipes; Underground pipeline

cleaning techniques for, 1:206 inadequate, 1:317 televising of, 1:884–885 Pipeline sediment disposal, 2:124 Pipe materials, microbial regrowth and, 1:345. See also Pipe coatings/linings Pipe repair, problems during, 1:801–802 Pipe roughness values, 3:314 Piper trilinear diagram, 2:396 Pipes. See also Line breaks; Piping examining, 1:153 flows in, 3:195 laying, 1:402–403 steady-state flow in, 5:654 water distribution system, 1:208 Pipe scrapers, 1:880 Pipe throughflow, 3:453 Pipe wall biofilm communities, 2:223 Piping, 5:403–404. See also Pipes leaking, 5:603 Pippin, Steven, 4:768 Pisaster ochraceus, 4:153 Piston meters, 1:338 Pit lakes, 3:270 Pitless adaptors, 1:151 Planar flows, shocks in, 3:241 Plane Couette flow, 5:653 Plane Poiseuille flow, 5:653 Plane series design discharge for, 3:243–244 time of concentration for, 3:243 Planetary boundary layer (PBL) models, 4:322 Planetoids, water in, 4:191 Plankton, 4:154–159 categories of, 4:154–155 collecting and studying, 4:155 food chains, filtrators, and size spectra in, 3:268–269 global importance of, 4:157 impact of oil on, 4:106 seasonal patterns of, 4:156–157 spatial patterns of, 4:155–156 temporal patterns of, 4:156–157 Planktonic algae, 3:107 blooms of, 3:133 Plankton Survey System (PSS), 4:72 Planned water recycling, 2:610 Planning decision support systems and, 2:619–620 for droughts, 2:578–579

799

river basin, 3:33–34 water-infrastructure, 2:594–595 Planning tools, drought-related, 2:580 Plan Puebla-Panama, 4:641 Plant available water, 5:124–125 Plant–bacteria–contaminant interactions, 5:378–380 Plant-based remediation, future of, 3:635. See also Phytoremediation entries Plant biomass, 3:480 Plant biomonitors, 1:716 Plant canopies optical properties of, 3:720 transpiration and, 4:346 Plant growth, tile drainage and, 3:731–732 Plantings, anchored, 3:148 Plant leaves, optical properties of, 3:719–720 Plant metabolites, secondary, 5:379 Plant pathogens, 5:379 Plant nutrients, in ponds, 3:486 Plant root system, augmentation of, 5:380 Plants. See also Higher plants; Phytoextraction; Phytoremediation; Vegetables; Vegetated entries; Vegetation in constructed wetlands, 1:894 detoxification of metals in, 5:287 effects of cadmium on, 5:616 as energy sources for microbes, 5:378 genetically modified, 3:686; 5:288 in heavy metal extraction, 5:279 hyperaccumulator, 5:369–374 metal hyperaccumulation in, 5:285–286 metal tolerance in, 3:609–615 metal uptake mechanism in, 5:286–287 nitrate level in, 3:637 in rocky shores and beaches, 4:26 salt tolerance of, 3:682–683 as sediment traps, 3:277 selenium in, 5:398 symptoms of high salinity in, 3:683 tolerance to soil salinity, 3:676 trace elements in, 3:456 vulnerability to pollutant discharge, 3:283 wave energy, 4:45

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800

CUMULATIVE INDEX

Plant selection appropriate, 3:556 for hydrocarbon and metal; 3:628–637 Plant species, invasive, 3:480–481 Plastic bottles, safety of, 1:5 Plastic filter media, 1:347 Platonic solids, water symbolism and, 4:786 Pleasant Pond, biomanipulation trials in, 2:53t, 56t PLOAD model, 2:253 Plug flow reactor, 1:815, 833 Plumbing, water-saving, 2:497 Plumbism, 2:432–433 Plume behavior, 5:589–590 Plume diving, 5:80–81 Orlando Naval Training Center, 5:82–83 Plume diving calculation, 5:83 Plume movement, 5:579–580 Plunge pool, 3:67 Plunging breakers, 4:137 Plutonium (Pu), in Chernaya Bay, 4:102 p-nitrophenol (PNP), adsorption of, 1:117 Point CIPP, 1:882 Point estimation techniques, 2:381 Point-integrating samplers, 3:398 Point-of-entry drinking water treatment devices, 1:67. See also Point-of-use/point-of-entry (POU/POE) systems Point-of-entry radon removal, 1:52 Point-of-use drinking water treatment devices, 1:68 Point of use/point of entry (POU/POE) devices, for arsenic treatment, 5:24–25 Point-of-use/point-of-entry systems, 1:378–382 operation and maintenance of, 1:380–381 regulations affecting, 1:379 role of, 1:378–379 safety of, 1:381 selecting, 1:381 types of, 1:379–380 Point-of-use treatment methods, 2:343 Point-of-zero charge (PZC), 2:98 Point-pollution sources, 2:265 Point process models, 3:428–429

Point repairs. See also Point source repairs for force mains, 1:889, 890–891 for gravity sewers, 1:888–889 Point source contamination, 5:603 Point-source pollution, 2:545; 3:226–228 control of, 3:133 during and after development, 3:501–502 terrestrial, 3:281–282 Point source repairs, 1:881 Point sources, 2:169, 190 Poland fishpond culture in, 3:135–141 pond fisheries in, 4:718–722 water retention methods in, 1:404, 406, 407 Polarity, 4:523 Polar lipid-derived fatty acid-based SIP, 1:645 Policies, water industry, 1:510. See also Public policy Policy decisions, environmental principles needed to formulate, 3:106 Political solutions, in the Arab World, 2:473 Politics, of wetland management, 4:691–692 Poljes, 5:245 Pollutant concentration, in gray water, 1:17t Pollutant concentration profiles, 3:78 Pollutant dispersal, in estuaries, 4:50 Pollutant loads in groundwater, 3:226–229 measured, 3:223–229 Pollutant photodegradation, using photocatalytic membrane reactors, 1:793–795 Pollutant removal mechanisms, 3:366–367 Pollutants. See also Chemical pollutants; Pollution affinity to suspended particulate matter, 2:384 agriculturally derived, 3:604 background concentration of, 2:18–20 coastal water, 4:96–109 conservative, 4:50 cross-media transfer potential of, 1:838 degradation by wetlands, 3:369

effects on marine habitat, 4:105–108 erosion-related, 1:537 human health and, 4:379 inorganic, 2:19–20 microbial detection of, 2:440–452 nonconservative, 4:50–51 organic, 2:20 in ponds, 3:485 unrecognized, 3:371–373 versus pollution, 2:190 Polluted discharges, into lakes, 3:281 ‘‘Polluted runoff,’’ 3:281 Polluted waters, 1:382. See also Water pollution entries Polluter-authority negotiations, 4:647–648 ‘‘Polluter pays’’ principle, 1:589; 2:597, 638 Pollution, 1:293. See also Pollutants arsenic, 1:1–3 biotic, 3:134 groundwater, 2:182–183 indicator group response to, 2:441–442 large-scale, 4:105 long-term simulation of, 3:335 nitrate, 1:30–34, 39; 3:637–640 nonpoint source, 2:181, 184, 186–187 oil, 2:290–292 from oil-field brine, 2:286–288 pathogenic, 2:182 sediment-attached, 3:333 of surface waters, 3:373–375 trace element, 4:109–113 trace metal, 2:64–65 transformation modeling of, 3:333 urbanization-related, 2:181 vulnerability of karst areas to, 5:247 water, 1:901 water recycling and, 2:612 Pollution control, 2:97 affordable, 2:132 maximum extent practicable, 3:432 in stored water, 2:367 technologies for, 1:554 ‘‘Pollution exclusion’’ clauses, 3:169 Pollution load, Ganga Basin, 3:235 Pollution loading, variations in, 2:264 Pollution management in Ho Chi Minh City, 2:553 tile drainage and, 3:730 in urban landscapes, 2:190

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CUMULATIVE INDEX

Pollution measurement in rainfall, 3:223–225 in runoff, 3:225–226 Pollution monitoring programs, biomarker approach in, 2:429 ‘‘Pollution offsets,’’ 2:133 Pollution outflow, from agricultural areas, 3:657–664 Pollution prevention, 1:143 landfill-related, 5:256–257 Pollution stress, response of biota to, 1:715 Pollution taxes, 2:132–133 Pollution tracers, 5:232 Poltruba backwater, biomanipulation trials in, 2:56t Polybrominated diphenyl ethers (PBDE), as unrecognized pollutants, 3:372 Polychaetes, in marine toxicological testing, 4:42–43 Polychlorinated biphenyl (PCB) compounds, 1:689; 2:545; 3:352 chemical properties of, 2:109t as environmental toxicants, 2:106 fish consumption advisories for, 3:118 macrophyte biomonitoring of, 1:714–718 in streambed sediment, 3:357–359t versus DDT, 3:521–522 Polycyclic aromatic hydrocarbons (PAHs), 1:571–575; 3:352; 4:98–99. See also PAH compounds biodegradation of, 1:693–694 in chironomids, 2:421 detection limits for, 1:573t in Puget Sound Basin sediment and fish, 3:350 in urban stormwater runoff, 3:435 Polycyclic organic matter (POM) compounds, 1:571–572 Polydex bactericidal efficiency of, 1:382–387 test water disinfection using, 1:383 Polymerase chain reaction (PCR), 2:139 relative quantitation of products of, 2:59 Polymerase chain reaction assay, 1:89f, 160–161

Polymer-assisted ultrafiltration (PAUF), 1:916, 917–918 Polymer coagulants, 1:138 Polymer coated activated carbons (POAC), 1:93 in metal ion removal, 1:918–920 Polymeric flocculants, 2:98–99 Polymers copper removal using, 1:919–920 organic, 4:426 water-soluble, 1:919 Polymictic lakes, 3:266 Polynuclear aromatic compounds, 2:310 Polynuclear aromatic hydrocarbons (PAHs), 5:91 Poly-P bacteria, 1:788t Polyphosphates, 1:314 Polypropylene (PP) membranes, 1:592f, 593f Polyurethane (PU) grouts, 1:881 Pond aquaculture, 3:375–379 Pond carp culture, 3:137–139 Pond construction, in Silesia, 3:135–141 Ponded ring infiltrometer, 5:214–215 Pond effluent, 3:541–542 Pond fisheries, in Poland, 4:718–722 Ponding method, 5:166 Ponds blue-green algae blooms in, 3:188–190 classification of, 3:541 cultivated, 4:697 detention, 3:430–431 water quality in, 3:484–487 Pond systems, for aquaculture production, 3:540–542 Pond water, color of, 3:485, 486t Pool and weir fish passage facility, 3:529 Pools, types of, 3:69t Poor people, water for, 4:771 Poor-quality water resources, salt tolerance and management of, 3:685 Population in developing countries, 1:504 effect on coastal wetland losses, 3:73 freshwater availability and, 1:437 Great Lakes region, 3:178 Population growth, 2:574 efficiency and, 2:493–494 impacts of, 4:289

801

in the Nile Basin, 2:590 water scarcity and, 2:495 Population growth impairment, as a sublethal toxic endpoint, 2:414–415 Pore size distribution, of activated carbon, 1:97 Pore spaces, 5:444 Pore water, 2:384 concentrations, 2:421 Porewater nutrient concentrations coupling with bivalve excretory activity, 4:75–76 seasonality of, 4:73–75 Porosity, 2:545; 4:484 soil, 3:30 testing, 5:186 Porosity log, 5:152–153 Porous cup samplers, 2:341 Porous flow, 5:655–661 Porous media, 5:600 Portals general, 2:669 water-related, 2:668–674 Porter-Cologne Water Quality Act, 2:358 Portland cement, hydration chemistry of, 5:362–363 Portland steam ship, exploration of, 4:63 Positive-displacement meters, 1:338 Positive-displacement pumps, 1:393–394 Possible contaminating activities (PCAs), 1:527 Posterior probability distribution, 5:596 Postindustrial Revolution Era, water in, 4:728 Post-treatment sewage treatment systems, 1:519–520 Potable wastewater reuse, 1:821–822 Potable water, 2:545 augmenting supplies of, 1:819 filter design for treating, 1:348–350 inhibition of biological ammonia removal from, 1:348 nitrification of, 1:346–350 regulatory and security requirements for, 2:343–350 reuse of, 1:826 security requirements for, 2:347–348

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802

CUMULATIVE INDEX

Potassium (K) concentration, 5:196–197 in groundwater, 2:395 Potassium perchlorate, 5:631 Potassium permanganate, 1:313; 2:300; 5:346 Potential additional total exposed population (PATEP), 1:36 Potential evapotranspiration (PET), 4:259–260; 5:409 Potentiometric surface, 5:184 Potomac River Low Flow Agreement, 2:585 Powdered activated carbon (PAC), 1:92, 351, 817; 2:86–88. See also Activated carbon(s) advantages of, 2:88 dosages of, 2:87, 88 effect on water adsorption, 4:402 oil-field brine and, 2:288 in water treatment, 2:86–87 Powdered activated carbon contactor, analysis and design of, 2:87 Power generation, technological revolution in, 4:729–730 Power laws, 3:212 Power plants. See Electric generating plants; Hydropower Precautionary principle, 3:125 application to water science, 2:595–603 concerns related to, 2:598 current examples of, 2:599–601 drivers and antidrivers related to, 2:598 global elements of, 2:596–597 global scope of, 2:596–598 interpretation of, 2:596 recommendations for, 2:601–602 relevance to water and environmental science issues, 2:599–601 risk and, 2:601 risk tolerance and, 2:599 Precipitate flotation, 1:686 Precipitating reagents, 1:705 Precipitation, 1:811; 2:516, 545; 4:434. See also Rain entries acid, 3:225 in arid regions, 5:409–410, 410–411 assessment of, 4:290 of cadmium, 5:616 chemical, 4:586–589 forest interception of, 3:171

of heavy metals, 5:378 in India, 2:560, 561f isohyetal method for estimating, 4:290–292 of landfill leachates, 1:705–706 of lime, 5:20 of metals, 5:282–283 remote sensing of, 4:322–323 role in flooding, 3:143–144 Sr isotope ratios in, 4:371 in subsurface systems, 5:416 throughfall of, 3:171 tritium in, 5:67f in the vadose zone, 5:534 variation in, 2:517, 574 versus streamflow, 4:433 in the water cycle, 4:196 water–rock interaction and, 5:569–570 wet-season, 4:304 Yellow River Basin, 3:45 Precipitation analysis, regional, 4:221–222 Precipitation depth, computing, 4:290–291 Precipitation–dissolution reactions, 5:277–278 Precipitation-effectiveness (P-E) index, 3:32 Precipitation estimation from remotely sensed information using artificial neural networks (PERSIANN), 4:323 Precipitation rate effect, 5:230 Precipitation routes, 4:193 Precipitation studies, remote sensing and GIS application in, 2:532 Precoat filters, 1:245 Precoat filtration, 1:251, 488 Precursors, physical removal of, 2:120 Predictive models, 2:26; 3:40, 41 use for, 3:330 Predictive well maintenance, 5:263–264 Prefilters, 1:332 Prehydrolyzed coagulants, 4:425–426, 427 Preliminary wastewater treatment processes, 1:814–815 Presedimentation, 1:323 with coagulation, 1:487 Pressure atmospheric, 4:360–361 dynamic, 5:652

hydrostatic, 3:194 water hammer, 1:891t Pressure compensating drippers, 3:622–623 Pressure constraints, in water distribution systems, 1:209 Pressure contour plotting, 3:318 Pressure filters, 1:176, 247f Pressure head, 5:171 Pressure leak testing, 1:886–887 Pressure relief valves, 1:483 Pressure relief wells, 3:289–290 Pressure supplies, in water distribution system design, 1:212–213 Pressure transducer probe, 5:101–102 Pressure transducers, 5:474 Pressure transients, 1:213, 343 Pressurized filters advantages and disadvantages of, 2:155 for iron removal, 2:154 Pressurized flow, hydraulics of, 3:196–199 Pretreatment, for lime softening, 1:323 Pretreatment effluent standards, 4:665 Pretreatment Program (EPA), 1:798–801 Pretreatment roughing filter, 1:237 Preventive maintenance (PM), 2:595 of wells, 5:263–264 Price elasticity, of water demand, 4:606–607 Pricing, tiered, 2:615. See also Cost(s); Economics; Water pricing Primary raw sludge, 1:861–862 Primary settling tanks, 1:452, 455, 456 design considerations for, 1:455 Primary wastewater treatment, 1:809, 815, 827; 2:545 Primary water quality standard, 2:373 Principle of maximum entropy (POME), 4:217–218, 218–219 Principle of minimum cross entropy (POMCE), 4:219 Prior Appropriation Doctrine, 2:545; 4:628, 631–632 water transfers under, 4:686 Prioritized objectives method, 2:623

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CUMULATIVE INDEX

‘‘Priority elements,’’ effect on fish, 3:131 ‘‘Priority Pollutant’’ list (EPA), 2:304, 305t; 4:599 Priority pollutants, 3:371 Priority system rule, 4:631–632 Private goods, 1:42 Private Participation in Infrastructure (PPI) database, 1:46 Private sector participation (PSP), 1:50–51 extent of, 1:389 forms of, 1:388–389 history of, 1:387–388 in municipal water supply and sewerage, 1:387 Private value of water, 2:653–654 Private well owners, in Arab states, 2:471 Privatization increase in, 1:508–509 of water, 2:569 in the water industry, 1:302 ‘‘Privatization by default,’’ 2:632–633 Proactive groundwater pumping, 5:45 Probabilistic approach, 2:675 to incipient motion, 3:418 to studying sediment transport, 3:401 Probabilistic-topological stream order approach, 3:32 Probability distributions, derivation of, 4:221 Probable effects level (PEL), 3:351 Probable maximum precipitation (PMP) analyses, 4:309–310 Probable maximum precipitation rates, 4:315 Problematic weeds, 3:479–484 Problem definition, in a systems approach, 2:685 Process-based computer simulations, 5:563–564 Process-based pesticide vulnerability models, 5:596–598 Process solid waste, as a source of contaminants, 5:433 Production efficiency, biofouling effects on, 5:35–36 Productivity, lake, 3:267–268 Product testing, 1:381 Professional water resource organizations, 4:651

Profitability measures, 1:312 Profundal, 3:267 Programs, conservation, 2:493 Propeller meters, 1:338 Property rights, 2:500, 506 in India, 2:556–557 Property transfer issues, 3:169 PROSPECT model, 3:720 PROSPER model, 3:738, 739–740 Protection zones, 1:316 Protective coatings, 1:882–883 Protective irrigation systems, 3:583 Protective linings, corrosion and, 1:11 Protein array technologies, 2:61–62 Protein expression analysis, high throughput, 2:61 Protein phosphatase inhibition assay, 2:389–390 Proteins as indicators of organic contamination, 2:442 role in metal transport, 5:286 Proteomics, 2:61–62, 429 Protists, as toxicity assessment test organisms, 2:413–418 Protonation, 5:377 ‘‘Proton reducers,’’ 5:40 Prototype measurement systems, 4:296–297 Protozoa, 1:904; 2:313 in domestic sewage, 1:831 health effects of, 1:278–279 removal of, 1:485–489 Protozoal agents, 1:178 Protozoan parasites, 1:166 PRZM code, 5:564 Pseudomonas, 1:278; 2:241 Pseudoplastic fluids, 5:557 Pseudosolubilization, 2:44 Psychrometers, 5:540 Psychrometry, 5:462 PT benzene (propylene tetramer benzene sulphonate), 1:671 Public. See also Public health entries participation in municipal storm water management by, 1:867 providing real-time hydrological information to, 1:123–125 Public agency activities, effect on storm water pollution, 1:867 Public awareness/concerns, growth of, 1:304 Public concerns, precautionary principle and, 2:599

803

Public education, 3:503 in Canada, 2:663 in groundwater protection, 2:518 strategies for, 2:519 Public goods, 1:42 Public health. See also Public health protection biofouling and, 5:36 programs, 1:799 water reuse research to protect, 1:819–822 Public health goal (PHG), 2:345 Public health protection chemical revolution in, 1:286–287 in developing countries, 1:290 drinking water and, 1:281–292 early water treatment, 1:286 history of, 1:282–286 water as an issue in, 1:283–286 Public Health Security and Bioterrorism Preparedness and Response Act, 1:158, 476–477, 527; 2:347 Public Health Service (PHS), 2:194 Public Law 660, 4:653 Public Law 92–500, 4:653–654 Publicly Owned Treatment Works (POTWs), 1:755, 757, 798, 801; 2:96; 4:596, 597, 670 Public notification, of repairs, 1:891 Public Notification Rule, 2:347 Public outreach, role in fish consumption advisories, 3:120 Public policy, New York City Harbor Survey and, 1:750. See also Policies Public–private partnerships (PPPs), 1:42–51 challenges to, 1:46–47 current, 1:46 defined, 1:43 durable, 1:45 obstacles to forming, 1:45–46 start-up of, 1:43–44 successful, 1:44 trust creation by, 1:47 Public programs, for agricultural land-use planning, 3:596 Public safety, pretreatment programs and, 1:800 Public supply, 2:545 Public trust, water managed in, 2:608–610 Public trust doctrine, 4:661

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804

CUMULATIVE INDEX

Public water supply. See also Public water systems (PWSs) conflicts and needs related to, 1:503–505 data and indicators related to, 1:505–507 defined, 1:501 disinfection of, 2:118 future of, 1:290–291 global, 1:500–507 national differences in, 1:501 in the United States, 2:651–652 Public water systems (PWSs), 1:201–202, 476, 524; 2:96, 371; 4:669–670 regulation of, 4:676–677 Public water use, 2:545 Puget Sound Basin data collection from, 3:350 organic compounds and trace elements in fish in, 3:349–362 Pulp industry, impact on surface water quality, 3:374 Pulsed bed, 1:104 Pulse microirrigation, 3:621 Pulses, in groundwater tracing, 5:504 Pump and treat technology, 5:41 Pumped storage facilities, 3:201–202 Pumping rates, equalization of, 3:380 Pumping stations, 3:379–381 power in, 3:380–381 pumps in, 3:379–380 water inlet in, 3:379 Pumping tests, 5:185–186, 513–514 practical aspects of, 5:496 Pumping water level, 5:101, 104 Pumps, 1:203 centrifugal, 1:392–393 positive-displacement, 1:393–394 priming of, 1:393, 394 reciprocating, 1:394 rotary, 1:394 safety of, 1:394–395 submersible, 1:393; 3:664 terms related to, 1:392 types of, 1:392–394 vertical turbine, 1:393 water distribution system, 1:208, 391–395 water hammer and, 1:262 Pump samplers, 3:400 Pump-test packages, 5:663 Purchase of agricultural conservation easements (PACE) programs, 3:596, 597

Pure water, 5:602 Purgeable halocarbons, gas chromatogram of, 2:306f Purge-and-bail sampling, 5:459 Purge and trap procedure, 2:306 Purging, low flow groundwater, 5:404–406 ‘‘Put-and-take’’ fisheries, 3:128 PVC repair clamps, 1:889 Pyrites, 1:609–610. See also Iron pyrite (FeS2 ) acid production and, 3:14–15 weathering of, 2:1 Pyrometallurgical extraction technologies, 5:435

Qanats, 5:483–487 constructing, 5:485–486 costs of, 5:486 history and geographic extent of, 5:484–485 statistics of, 5:487 versus drilled wells, 5:486 water regulations and, 5:486 Qochas, 4:696 QSAR approach, in dye tracer selection, 3:98–101. See also Quantitative structure-activity relationships (QSARs) QSAR models soil sorption using, 3:99–101 using triarylmethane dyes, 3:99 Quabbin Reservoir, 1:316 Quality. See also Distribution system water quality; Water quality desalinated water, 1:173–174 feed water, 1:175 gray water, 1:16t irrigation water, 2:155–161 raw water, 1:440 Quality assessment. See Environmental quality assessment; Quality control Quality control in amphipod sediment toxicity tests, 2:410–411 of groundwater samples, 5:455–456 Quality criteria, for raw waters, 3:227t. See also Quality parameters Quality parameters, of water, 1:901–904. See also Quality criteria

Quality standards, drinking water, 1:476–481 Quantitative foodwebs, 4:152–153 Quantitative groundwater law, 4:627–634 Quantitative microautoradiography (QMAR), 1:847 Quantitative reverse transcription polymerase chain reaction (qRT-PCR), 2:59 Quantitative structure-activity relationships (QSARs), 2:415; 3:95. See also QSAR entries Quantity-based reliability, 3:261 Quartz sand, 1:347 Quasi-conservative pollution, modeling of, 3:332 Quasi-Nonhydrostatic (QNH) model, 4:247 Quasi-riparian doctrines, 4:630 ‘‘Quickflow,’’ 5:236

Race-to-pump mentality, 4:632 Radar attenuation of, 4:308 development of, 4:354 ground penetrating, 1:884 polarimetric measurements with, 4:311 reflectivity factor of, 4:322 use in rainfall measurements, 4:306–309, 310–311 Radial impellers, 1:76 flow patterns induced by, 1:77f Radially entrained vapor extraction (REVEX), 2:286 Radial wells, 3:595; 5:407–408 Radiation. See also Ultraviolet (UV) radiation fog and, 4:231 radioactivity and, 1:802 Radiation balance, 3:561 Radiation fog variables, 4:232–236 Radiative forcing, global, 4:176–177 Radiative opacity, 4:190 Radioactive contaminants, 5:221. See also Radioactive contamination Radioactive contaminant transport, numerical modeling of, 3:322–323 Radioactive contamination. See also Radioactive contaminants drinking water limits for, 1:803 manmade sources of, 1:803

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CUMULATIVE INDEX

Radioactive isotopes. See also Radionuclides environmentally important, 5:221t naturally occurring sources of, 1:802–803 sources of, 5:221t Radioactive waste, 1:802–805 activated carbon treatment for, 1:804 air stripping for, 1:803 chemical precipitation of, 1:804 ion exchange for, 1:804 lime softening of, 1:804 membrane filtration processes for, 1:803 treatment technologies for, 1:803 as water pollution, 4:101–102 Radioactivity, 5:184, 186 Radioactivity mapping, 5:186 Radiocarbon, groundwater dating with, 5:64–65. See also Carbon-14; Carbon isotopes Radiocesium levels, 4:103 Radiographic corrosion measurement, 1:9 Radiometric resolution, 4:320 Radionuclide monitoring, 2:267 Radionuclides, 1:395–398, 803; 5:221. See also Radioactive isotopes health risks of, 1:395–396 regulations governing, 1:396t technologies for, 1:465t treatment technologies for, 1:396–398 Radionuclide standards, U.S., 2:268 Radionuclide study, 4:581 Radiosondes, 4:349 Radium (Ra), health risks of, 1:395 Radium–barium sulfate co-precipitation, 1:398 Radon (Rn) case-control studies, 4:544 in domestic water, 4:542–546 fatalities from, 4:544–545 health risks of, 1:395 reducing in drinking water, 1:51–52 as a tracer, 5:683 treatment technologies for, 4:546–547 in water, 4:541–548 Radon risk policies, 4:542 Rain, 4:293

Rain-acidified waters inland, 3:8 regional distribution of, 3:8–9 Rain acidity, neutralization of, 3:7 Rainfall, 4:309–315. See also Rainwater as energy spectrum, 4:307–309 estimation by isohyetal method, 4:292t flooding induced by, 3:160 in India, 2:559–560, 561f intensity–duration relationship for, 3:243 observation and estimation of, 4:315 pollution measurement in, 3:223–225 radar measurement of, 4:310–311 remote sensing of, 4:322–323 runoff and, 4:315–319 satellite monitoring of, 4:311–313 Rainfall data, 5:164 Rainfall estimates, Chicago Station, 5:79t Rainfall measurements errors in, 4:297 radar use in, 4:306–309 Rainfall partitioning, at the land surface, 4:315–316 Rainfall plot, coverage simulation of, 4:331 Rainfall rates, 4:486 computed, 4:308 Rainfall recharge (Rr ), 5:165–166 Rainfall–runoff models, 4:357–358; 5:74 input data and model parameter uncertainties in, 4:298–299 ‘‘lack of knowledge’’ uncertainty in, 4:300–301 observation and model errors in, 4:300 propagation of input errors through, 4:298 residuals in, 4:299 serial dependence in, 4:300 simplification of, 4:297–298 uncertainties in, 4:297–303 Rain-fed agriculture, 3:560 Rain forests, 4:239–240 threats to, 4:240 Rain gages, 4:309–310. See also Rain gauges Rain gauge network density, 4:298

805

Rain gauges, Bangkok Metropolitan Administration, 1:124f. See also Rain gages Rain-on-snow floods, 3:511 ‘‘Rain shadow’’ effect, 4:293 Rain-simulator equipment, 4:330–332 Rain simulators, 4:330–333 rainfall intensity used in, 4:332 types of, 4:330–332 typical measurements by, 4:331–332 Rainsplash, 3:566 Rain terminal velocity, simulation of, 4:331 Rainwater, 2:95; 4:285. See also Rainfall chemistry of, 4:371–372 composition of, 4:285 technetium in, 4:580 Rainwater collection gutters, 1:56–58 Rainwater harvesting, 2:548–552 components of, 2:549–550 defined, 2:549 need for, 2:548–549 structures related to, 2:550–551 techniques for, 2:551 Rainwater systems, conventional, 1:58 Raised agriculture, 4:697–698 Raised gardens, 4:698 Rajarata, ancient ecosystems in, 4:774–775 Ramganga dam, 3:234 Random-coordinate basin slope method, 3:29 Random metering, 1:494 Random search method, 2:333 Range analysis, 3:261 Ranney collector wells, 5:88–89 Rapid Bioassessment Protocols (RBPs), 2:25–26 Rapid BOD technologies, 2:40–41. See also Biochemical oxygen demand (BOD) Rapid granular bed filters, 1:234 Rapid granular bed filtration, 1:244–245 Rapid gravity filter box, 1:371f Rapid gravity filtration, 1:245–246 Rapidly draining epikarsts, 5:236 Rapid 18 O exchange, measurements of, 4:536–537 Rapid rate pressure filters, 1:247

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806

CUMULATIVE INDEX

Rapids, 3:70 Rapid Update Cycle (RUC-2) model, 4:248 Rate increases, 1:147 Rate of time of preference, 4:607 Rating curve, 2:545; 4:222 Rationale wastewater model, 1:731 Raw sewage, 3:445 Raw water, quality and testing for, 1:440; 3:227t rBAT-induced amino acid transport, 2:436 Reaction kinetics effect of heat on, 5:173–175 oxygen demand and, 1:640–641 Reaction-path models, 5:139 Reaction phenomena, 3:78 Reaction turbines, 3:488–489 Reactive intermediates, in the irradiation of natural waters, 4:531–532 Reactive solutes, 5:274–275 Reactive solute transport, in soil and groundwater, 5:524–531 Reactive transport, in the saturated zone, 5:518–524 Reactive transport models equilibrium and kinetic, 5:519 hardware for, 5:34 Reactive transport simulator, 5:519 Reactors, POP behavior in, 1:767–768 Reactor systems, anaerobic, 1:906–909 Real-time control, modeling, 3:340–341 Real-time hydrological information future of, 1:126–127 providing to the public, 1:123–125 urban drainage models and, 1:125 weather radar for, 1:126 Real-time hydrological information system, 1:121–127 Real-time measurements, observations of climate and global change from, 4:172–179 Real-time modeling, 3:340 Real-time polymerase chain reaction, 1:160–161 Real-time reservoir operation, 3:387 Reasonable Use Doctrine, 4:628, 631 Receiving waters, assessment of, 4:103–104 Recession constants, 3:23 base flow, 3:24–25

Receiving water body samples, analyses of, 1:662–663 Recession-selecting algorithms, 3:25–26 Recharge in arid regions, 5:408–413 defined, 2:545 in desert regions, 5:72–76 estimation of, 5:411 flood spreading for, 3:164–165 incidental, 5:75 measurement techniques for, 5:73–75 methods of, 5:12 in regional flow systems, 5:417–418 subsurface, 5:73 of unconfined aquifers, 5:11–17 in the vadose zone, 5:534–535 Recharge areas, 5:601 Recharge capacity, impact of air on, 5:421–422 Recharge coefficient, establishment of, 5:168–169 Recharge/discharge boundaries, 5:184 Recharge interactions, 4:371–372 Recharge zones, 4:670; 5:417 Recharging, excess, 5:12. See also Recharge Reciprocal SSH libraries, 2:62 Reciprocating pumps, 1:394 Recirculating aquaculture systems, 1:683; 3:544–545 Recirculating systems enclosed, 1:558–559 open, 1:559 Reclaimed irrigation human exposure to, 3:670 microbial quality of, 3:667–673 types of practices of, 3:669–670 Reclaimed wastewater, 2:545, 649–650 Reclaimed water, 1:805–808 benefits of, 1:805 constituents of, 1:806, 807t federal guidelines for, 1:806 planning for, 1:807–808 technical considerations related to, 1:808 uses of, 1:805–806 Reclamation in acid mine drainage, 5:3 of waterlogged lands, 3:603

Reclamation Drought Index (RDI), 4:213 Recombinant bacteria, 2:454, 455 bioluminescent, 2:174 Recombinant luminescent bacterial biosensors, 2:454 Recording, of hydrogeologic responses to earthquakes, 5:114 Recovery/removal treatments, for odor abatement, 1:762 Recovery tests, 5:575 Recreation, algae-impaired, 3:108 Recreational fishing, 3:123 Recreational wastewater reuse, 1:818 Rectangular settling tanks, 1:453 Recycled water, 2:545 in the United States, 2:613 Recycling, on the International Space Station, 4:572 Recycling systems, 1:509 Red Book, 2:315 Red edge reflectance-ratio indexes, 3:722 Redeposited sediment, contaminant release from, 2:125 Redfield ratios, 4:52 ‘‘Redfield’’ stoichiometric ratio, 3:109 Redox buffering capacity, 2:468 Redox chemistry, sub-surface, 5:413–417 Redox couple approach, 5:414 Redox gradients, 2:213 Redox phenomena, alternative methods of examining, 2:468–469. See also Oxygen redox potential (ORP); Reduction–oxidation (redox) reaction Redox potentials, use in wastewater treatment, 1:399–400. See also Eh ; Oxidation–reduction (redox) reactions Redox reactions, 5:569, 583f. See also Oxidation and reduction (redox) ranges of Eh for, 2:468 ‘‘Red-rot’’ disease of water, 2:147 Red tides, 4:55, 134 Reduced pressure principle backflow preventer (RPBP), 1:155–156 Reduction chemistry, 5:291 Reduction–oxidation (redox) reaction, 2:464. See also Redox entries Reduction reactions, in mine effluent remediation, 1:611

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CUMULATIVE INDEX

Reductive dechlorination, 2:299–300 Reductive dehalogenation, 1:689 Reed bed, 1:787 Reef breakwater, 4:15 Reef fish research, 4:56 Reference crop evapotranspiration, 2:537; 3:572 estimating, 3:573–574 Reference dose (RfD), 1:426 Reference site criteria, 2:26 Reference toxicant tests, 2:411 Reflectance, 4:321 Reflectivity images, ‘‘real-time,’’ 4:308 Refrigerants, 4:420 Refuse decomposition, microbiology of, 1:695–696 Regional flow systems, 5:417–421 boundary conditions in, 5:418–419 characteristics of, 5:419–420 discharge in, 5:418 recharge in, 5:417–418 Regional precipitation analysis and forecasting, 4:221–222 Regional watershed protection, 2:613–614 Regional water supplies, 2:613–619 Regional water treatment, 2:615–616 Regional water use, 2:489–490 in the United States, 2:646–647 Registry of Equipment Suppliers of Treatment Technologies for Small Systems (RESULTS) database, 1:154, 315, 325, 461–464 Regression methods, 2:253 in odor analysis, 2:282 Regulated riparianism, 4:632 Regulated Riparian Model Water Code, 4:629 Regulated rivers, 3:106, 381–382 Regulation. See also Regulations; Water regulation of bottled water, 1:4–5 groundwater, 4:632 of mercury, 5:645 of nitrate, 5:629 of power plant wastewater discharges, 1:557 of public–private partnerships, 1:44 of public water systems, 4:676–677 of technetium, 4:580 of urban stormwater runoff, 3:432–433

using biomarkers and bioaccumulation for, 2:429–430 of vinyl chloride, 5:637–638 of wastewater treatment, 1:844 of water markets, 2:500 Regulation and enforcement agencies federal, 4:650t Regulations. See also Effluent water regulations; Federal regulations; Laws; Regulation arsenic-related, 1:82 broadening of, 1:508 bromide-related, 2:74 Chinese, 2:487–488 Clean Water Act, 1:756 consumer information, 4:678 detergent-related, 1:672–673 disinfection-related, 1:197; 2:92 drinking water, 1:53, 422–429; 2:194–198, 345–347 enforcement of, 1:508 filtration-related, 1:227 introduction of, 1:287–288 membrane technologies and, 1:331 metal-discharge-related, 2:68 nitrate/nitrite-related, 3:639 nonpoint source control, 2:185 ozone, 1:354 pharmaceutical-related, 1:377–378 point-of-use/point-of-entry system, 1:379 radionuclide, 1:396t risk assessments as, 1:428 Subtitle D, 2:166, 167 sugarcane industry, 1:619t water quality, 1:282; 2:315 water quantity, 2:557–558 water supply degradation and, 2:401 water sustainability and, 2:614, 627 for water treatment plant residuals, 1:413 Regulatory agencies, early, 1:285 Regulatory controls, growth of, 1:305 Regulatory impact analysis (RIA), 1:427 Regulatory interface, federal-state, 4:671–673 Regulatory issues, 4:674–676 iron-related, 4:497

807

Regulatory purposes sediment toxicity tests for, 2:383–387 test development for, 2:458–464 Regulatory requirements, drinking water filtration, 1:233 Regulatory reviews, of NPDWRs, 1:428 Relative humidity, 4:270–274 vapor pressure and, 4:271–273 Relative humidity statistics, Chicago Station, 5:79t Relative risk concept, 1:287 Release fractures, 5:177 Reliability defined, 3:260–261 in reservoir design, 3:259–265 Relief drains. See Tile drainage Relief valves, 1:262 Remedial Action Plans (RAPs), 3:179; 4:622 Remedial investigation/feasibility study (RIFS), 2:318 Remediation. See also Phytoremediation of cadmium, 5:617–619 of contaminated soils, 5:432–436 of fluoride contamination, 5:134–135 of lead, 5:648 limiting geochemical factors in, 5:319–322 of mercury, 5:644–645 of MtBE, 5:319 of metal-contaminated soils, 5:433–435 of selenium, 5:397 of selenium-contaminated waters, 2:355–360 of technetium, 4:581 of uranium, 5:641–642 Remediation injection process (RIP ), 5:234 Remediation target setting, 2:355–357 Remining, 5:3 Remotely sensed data analyzing, 4:319 methodologies for analyzing, 4:319 Remotely sensed energy balance (EB), 3:562–563 Remote monitoring, 1:381 Remote sensing, 5:411 advantages of, 3:561 of algal blooms, 4:55–56

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808

CUMULATIVE INDEX

Remote sensing, (continued) alternative applications of, 4:325–326 application in water resources, 2:531–536 in command area studies, 2:533–534 crop water stress detection using, 3:719–724 of evapotranspiration, 4:321–322 flood mapping via, 4:322 in floodplain management, 2:533 future need for, 2:535–536 in groundwater studies, 2:534–535 in hydrologic modeling, 2:535 of hydrology applications, 4:319–327 in land use classification, 2:532 in precipitation studies, 2:532 of rainfall and snowfall, 4:322–323 in reservoir sedimentation, 2:534 reservoir surveys and, 3:411 resolution and spectral regions in, 4:319–321 role in nonpoint source pollution assessment, 3:658 in snow cover studies, 2:533 in soil moisture assessment, 2:533; 4:323–324, 488 for submarine gas hydrates, 4:59–60 of surface snow, 4:324 terms and equations related to, 4:321 of waterbodies, 4:324–325 in waterlogging and soil salinity, 2:534 in water quality studies, 2:534 in watershed mapping and monitoring, 2:533 of wetlands, 4:325 Remote sensor technologies, 1:147 Remote telemetry units (RTUs), 1:450 Removal processes, 1:485; 5:618 for bacteria, viruses, and protozoa, 1:485–489 principal, 1:487 as a remediation strategy, 2:358 supplemental, 1:488–489 Removal technologies, 5:439–441 Renal system, effects of lead on, 2:436 Renewable aquatic resources, 3:121 Renewable energies, 1:562; 4:44–49 ocean thermal, 4:47–49

tidal energy, 4:46–47 wave energy, 4:45–46 Renewable energy projects, drawbacks of, 4:47 Renewable freshwater resources, 2:634 Renewable natural resources, 2:634 Renewable water resources, in Arab states, 2:471t Repair clamps, 1:889 Repair couplings, 1:889 Repairs point source, 1:881 public notification of, 1:891 Repair systems, structural, 1:883 REPIDISCA Technical Dissemination Sheets, 2:672 Reporter genes, bioluminescent, 2:453 Reporting agencies, 1:293 Reports, consumer confidence, 1:145–146 Representative elementary area (REA), 5:306 Representative elementary volume (REV), 5:306 Reproducing and feeding ecology, classifying organisms by, 3:37 Reproduction, effects of lead on, 2:436 Research on agricultural drainage ditches, 3:88–89t, 90t on aquatic macrophytes, 2:66–67 biodegradation, 2:42 biomarker, 2:30 on coastal fisheries and habitats, 4:55–57 on greenhouse gases, 3:180–181 on hydrologic thresholds, 3:231–232 hydropsychology, 4:735 limnological, 3:291–292 lysimeter, 5:487 on microirrigation, 3:626–627 for military applications, 4:295–297 on phytoremediation, 3:368; 5:285 related to coastal wetlands, 3:73 tsunami, 4:162 on wastewater reclamation and reuse, 1:819–825 Research and inventory agencies, federal, 4:650t

Research on Watering among Ancients, 4:736 irrigation and governance in, 4:737–740 Reserved water rights, 4:689–690 Reservoir design reliability concepts in, 3:259–265 simulation procedure for, 3:263–264 traditional, 3:261–262 Reservoir drawdown, 3:412 Reservoir dynamics, 3:259–260 Reservoir flood storage, 3:151 Reservoir flow routing, 3:255 Reservoir management, 3:408–409 systems engineering for, 3:386–387 Reservoir operations models, 2:623 Reservoirs, 1:405; 2:545, 367, 568; 3:270. See also Multipurpose reservoirs; Small water reservoirs boreal, 3:180–181 classification of, 1:406t ecosystems below, 1:406–407 fisheries management and, 3:125 functions of, 1:408 hydroelectric, 3:180–183, 202–203 locating, 1:410 need for, 3:382–384 priority concept for, 3:386 sediment inflow into, 3:411–412 trap efficiency of, 3:409 tropical, 3:181 Reservoir sedimentation, 3:408–412. See also Reservoir sediments factors influencing, 3:409 loss of storage capacity and, 3:409–410 remote sensing and GIS application in, 2:534 Reservoir sediments distribution of, 3:410 unit weight of, 3:410 Reservoir site, permeability investigation for, 5:356 Reservoir size, inflow characteristics and, 3:262–263 Reservoir storage zones, design of, 3:264 Reservoir surveys, 3:411 Reservoir system, components of, 2:367 Residential meters, 1:340

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CUMULATIVE INDEX

Residential water demands, 1:12–16 in low-income countries, 1:14–15 management of, 1:15 Residential water use categories of, 2:652 models of, 1:13–14 Resident time, 1:103 Residual method of price estimation, 4:608–609 Residual sodium carbonate (RSC), irrigation water quality and, 5:208 Resistance soil moisture measurement, 4:488 Resistivity, measurement of, 5:444–445 Resistivity logs, 5:152 Resistivity methods, 5:443–448 in groundwater pollution studies, 5:447–448 theory and application of, 5:444–447 Resource Conservation and Recovery Act (RCRA), 2:163 Resources. See also American water resource development; Coastal resources; Community- based resource management; Flux-type natural resources; Freshwater resources; Global water resources; Groundwater resources; Integrated water resources management (IWRM); Natural resources; Renewable entries; Water resource entries public–private partnership, 1:45 wastewater, 1:676–677 Respiratory problems, 4:379 Respirographic biosensor, industrial effluent examination using, 1:568–570 Respirometers, 2:40–41 types of, 1:567 Respirometric biosensors, 1:565 characteristics of, 1:570 Respirometric techniques, toxicity assessment using, 1:566–568 Response warning systems, flood-related, 3:148 Response watershed functions, 3:477–478 Restatement rule, 4:631 Retarding basins, 3:150–151 Retention, higher water, 1:406 Retention basins (RBs), 1:783–784

Retention storage, 3:474 Retention systems, for storm water treatment, 1:868 Retention time, 1:103 Retrofitting, 2:665–666 Return activated sludge (RAS), 1:454–455, 456 Return flow, 2:545 Reverse electron transfer (RET) assay, 2:279, 280, 376, 377–378 Reverse osmosis (RO), 1:298–300, 333t, 335–336, 380, 459, 488, 707–708, 810; 2:545–546; 5:326–327. See also Reverse osmosis membranes; Seawater RO plant antifoulant design and, 1:415–416 for arsenic removal, 1:637–638; 5:21 in chromium treatment, 5:25–27 desalination, 1:171–173 efficiency of, 5:327–328 feedwater chemistry and, 1:414–415 membrane materials in, 5:327 oil-field brine and, 2:289 process chemistry of, 1:414–416 radionuclide removal via, 1:398 Reverse osmosis membranes cleaning, 1:416, 419–422 foulants in, 1:416–419 fouling of, 1:415 materials for, 5:26 Reverse osmosis membrane vessel, 1:172f Reverse osmosis systems, 1:297 choosing, 5:27, 328 design of, 5:25–26 efficiency of, 5:26 maintenance of, 5:26–27, 328 for nitrate treatment, 5:326–328 Reverse sample genome probing (RSGP), in community analysis, 1:644–645 Reverse transcription polymerase chain reaction (RT-PCR), 1:161 Reversible nonspecific toxicity, 2:415 Reversibly adhering (rolling) cell formation, 2:240 Revised Universal Soil Loss Equation (RUSLE), 2:251 Reynolds Number (Re), 5:650–651 Rheopectic fluids, 5:557 Rhepoxynius abronius, sediment toxicity tests using, 2:410–411

809

Rhizofiltration, for lead-contaminated soils, 5:383 Rhizofiltration agents, 3:630 Rhodamine WT, 3:96 Ribosome content, cellular, 2:230 Rice, flooding tolerance of, 3:601 Rice growing, floating, 4:696 Richards equation, 4:486; 5:538 Richardson, Lewis Fry, 4:350 Riffles, 3:70 Rights, water-related, 4:769–772 Rigid porous fine bubble diffusers, 1:626–627 Rills, 3:183 Ring infiltrometer, 4:487 Ring tests, 2:459 Rio Grande Basin, 2:589 Rio Tinto, acidity of, 3:10 Riparian buffers, 3:391–392 Riparian buffer zones (RBZs), 3:391. See also Riparian zone Riparian doctrine, water transfers and, 4:686 Riparian habitats. See also River entries wastewater discharge and, 2:475–476 water recycling and, 2:612 Riparian marshland. See Cienega entries Riparian rights systems, transfers under, 4:685. See also Riparian water rights Riparian systems, 3:390–392 inputs, outputs, and transformations related to, 3:390–391 vegetated buffers in, 3:391 Riparian water rights, 2:501, 546 Riparian weeds, 3:743 Riparian zone, 3:172. See also Riparian buffer zones (RBZs) Risk(s). See also Security public perception of, 4:675 of radon in domestic water, 4:543–546 of waterborne transmission of Escherichia coli, 1:429–431 Risk analysis/assessments of buried wastes from electricity generation, 5:448–451 in contaminated groundwater bioremediation, 5:38 in crafting drinking water regulations, 1:422–429

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810

CUMULATIVE INDEX

Risk analysis/assessments (continued) entropy and, 4:220 health risk reduction and cost analysis, 1:427 of heavy metals, 5:278 as regulations, 1:428 Safe Drinking Water Act and, 1:424–425 toxicological methods for, 2:278 Risk-based corrective action (RBCA), 5:586, 587 Risk-based decision making, 4:675 Risk-based fish consumption advisories, 3:119–120 Risk-based screening levels (RBSLs), 4:675 Risk-informed decision making, 2:599 Risk management. See Flood risk management Risk sharing, flood-associated, 3:512–513 Risk tolerance, 2:599 Ritchie second-order equation, 4:566 River and reservoir operations optimization models, 2:623 River basin decision support systems, 2:619–624 River basins, 3:28–33 characteristics of, 3:28–32 Indian, 2:560–561, 562t, 564t influences on, 3:221 as management units, 3:128 planning and coordination related to, 3:33–34 transformation of, 4:729 Riverbed/seabed filtration intake systems, 5:89–91 River chemistry, global, 2:19 River-connected aquifers, 5:677–688 groundwater geochemistry of, 5:684–686 water travel times in, 5:681–684 ‘‘River Continuum Concept,’’ 3:292 River data, 5:164 River discharge measurements, 2:622 River flow, runoff process controls of, 3:454 River flow regime grouping, 4:222 River for Jaffna proposal, 4:776 River health, predictive models for, 3:40 River-induced flooding, 3:160 Riverine ecosystems, ecological integrity of, 3:106

Riverine electromagnetic/seismic surveys, 5:679–680 Riverine fisheries management, 3:125–126 River inflow, as a forcing factor, 3:322 River Invertebrate Prediction and Classification System (RIVPACS), 3:40 River Kali (India), 3:660f nonpoint source nutrients from, 3:661f River mapping, ‘‘cartographic anxiety’’ associated with, 4:683–684 River model development, 2:333–334 River pollution, in India, 3:84, 447–451 River reaches, 3:66–70 identifying and naming, 3:67 River restoration, dam removal as, 3:387–389 Rivers, 3:392–394. See also Regulated rivers; Streams acidification of, 3:10 cadmium-contaminated, 5:615 Canadian, 2:657–658 channel patterns of, 3:31–32 currents in, 3:320 design flow in, 3:81–84 dilution in, 3:84 facts related to, 3:394–397 fluctuations of, 3:134 Indian, 2:560–561, 563f lengths of, 3:397 limnology of, 3:292 as one-way flow systems, 3:437–439 pollution of, 4:268 salinity of, 3:679–680 sediment content in, 3:408 sodium in, 4:552 topography of, 3:392–393 trace elements dissolved in, 4:110–111 velocity of, 3:393–394 water and sediment loads of, 3:393t Rivers and Harbors Act of 1899, 4:595, 651 Riverside blankets, 3:289 Riverside levee slopes, protecting, 3:290 ‘‘River snow,’’ 3:306 River systems, classification of, 3:392 River (stream) water(s), 2:95; 4:285 composition of, 4:160, 285

River water chemistry, 4:371–376 atmospheric inputs into, 4:373–374 contribution of lithology in, 4:374 methodology of studying rocks, 4:371–372 natural and anthropogenic inputs into, 4:373 quantification of marine and terrestrial contributions to, 4:372–373 role of human activities in, 4:374 River water infiltration, stratigraphic controls on, 5:679 River water quality, impact on groundwater, 2:396–397 River water quality model calibration, 2:331–333 genetic algorithms for, 2:333–335 procedure for, 2:334 single optimized parameter set selection in, 2:335 River water quality modeling software tools, 2:325–331 evaluation and selection of, 2:328–330 River watershed, natural and anthropogenic export in, 4:374 River Yamuna, India, ground water quality near, 2:392–398. See also Yamuna River RNA stable isotope probing, 1:645–646 Road construction, managing, 2:187 Road crossing culvert fish passage facility, 3:531 Road runoff drainage, 3:498 Road salt, 2:319–325 alternatives to, 2:320 effects on aquatic macroinvertebrates, 2:321–323 effects on zooplankton and fish, 2:323 field and laboratory studies of, 2:322t impacts on aquatic environments, 2:320–321 indirect effects of, 2:321 loading, 2:321 properties of, 2:320 runoff, 2:321 Robin’s boundary condition, 5:561 Robotic pipe repair techniques, 1:881

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CUMULATIVE INDEX

Rock(s) concentration of trace elements in, 3:457t consolidated water-bearing, 5:55–56 dissolution rate (R) for, 5:448–449 igneous, 5:55 metamorphic, 5:55 methodology of studying, 4:371–372 sedimentary, 5:55 specific yield of, 5:577t squeezing water from, 5:477–480 strontium isotopes in, 4:574–578 Rock glacier, 3:174–175 taxonomy of, 3:175t Rock faults, 5:137–138 Rock fracture, 5:136–138 Rock joints, 5:136–137 Rock systems, groundwater flow in, 5:175–177 Rock samples, analysis of strontium isotopes in, 4:575–576 Rock–water interaction, 5:566–571 Rocky shores, 4:26 ROMAG screen, 1:785 Roman aqueducts, 1:282 Roof drainage, threats to, 1:60–61 Roof drainage hydraulics, 1:54–61 future of, 1:60–61 Roof drainage systems, siphonic, 1:58–59 ‘‘Roofnet’’ model, 1:58 Roof runoff drainage, 3:498–499 Roof surface design, 1:55–56 Rooftop harvesting, 2:551 ‘‘Room for Rivers’’ policy report, 2:526 Root Bioaccumulation Factors (RBFs), 1:717 Root growth, in grass plants, 3:706–707 Root zone, 3:559, 560, 570 components of, 3:706 salt balance of, 3:678–679 Root Zone Water Quality Model (RZWQM), 2:252 Rotary fine screens, 1:785 Rotary kiln furnace (RKF), 1:858, 860 Rotary pumps, 1:394 Rotary water well drilling, 5:105 Rotating biological contactors (RBCs), 1:833 Rotavirus, 1:279 Roughing filters, 1:237–238, 486 components of, 1:240–241

Roughness length, parameterization of, 4:1 Round Lake, biomanipulation trials in, 2:57t Rover mission, Mars exploration, 4:504–506 Rubber membrane fine bubble diffusers, 1:627–628 Rubble-mound structures, 4:15–17 Ruditapes philippinarum, 4:11–12, 75 excretion rates of, 4:7–9, 12–13 Ruhunurata, ancient irrigation works in, 4:775 Rule curves, 3:384–385 Rule of Capture, 4:628 Rule of Constant Proportions, 4:159 Ruminants, effect of nitrates on, 1:38 Runoff, 2:546. See also Roof runoff drainage; Surface runoff contaminated, 3:606 control of, 3:454; 5:256 effluent, 2:516 farm, 2:400 groundwater contamination from, 5:451–453 observation and estimation of, 4:376–317 pollution measurement in, 3:225–226 quantity and quality of, 4:318–319 rainfall and, 4:315–319 recharge from, 5:410 road salt, 2:321 routing of, 4:318 stormwater, 2:190 surface water, 2:516 urban, 2:186–187, 190, 192 use of, 3:164 Runoff estimation, methods for, 4:317–318 Runoff farming, 3:164, 708 Runoff hydrology, special topics in, 4:319 Runoff impacts, from landfills, 5:256 Runoff management, constructed wetlands for, 1:896 Runoff mechanisms, forest, 3:171–172 Runoff pollution caused by human interference, 3:225–226 natural sources of, 3:225 Runoff water, harvesting, 3:708 Run-of-river projects, 3:201

811

Run-of-the-river system, 2:554 Run up phenomenon, 4:16 Rural areas, drinking water disinfection in, 1:382–387 Rural development, in the Nile Basin, 2:593 Rural sanitation, in developing countries, 2:632 Rural small water supply, drinking water quality failure in, 1:221–227 Rural water supply, in developing countries, 2:631–632 Rural water systems, design of, 1:213 Russia. See also Far Eastern Russia seas Lake Baikal studies by, 3:20, 21 marine environmental monitoring in, 2:443–444 SAA (SO4 2− + NO3 − + Cl− ), 3:1 anion concentration in, 3:2 Safe Drinking Water Act (SDWA) of 1974, 1:4, 70, 82, 424, 476; 2:195, 286, 345, 585; 4:597, 676–680 Amendments of 1986, 2:8, 299 definitions related to, 4:669–670 events leading to, 1:288–290 history of, 1:479–480 implementation procedures for, 4:670–671 regulations related to, 4:668–669 risk mandates from, 1:424–425 small drinking water systems and, 1:457 standards and goals of, 4:677–678 statutes related to, 4:667–668 underground injection control under, 4:679–680 variances and exemptions related to, 4:678–679 Safe Drinking Water Hotline, 1:145 Safe Drinking Water Information System (SWDIS), 4:542 database, 1:481 Safe storage, household drinking water, 1:67–70 Safety of chlorine gas, 2:90 of cobalt, 5:612 of ozone, 1:356 of plastic bottles, 1:5

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812

CUMULATIVE INDEX

Safety (continued) of point-of-use/point-of-entry systems, 1:381 pump, 1:394–395 Safety precautions, for chemical oxidants, 5:348–349 Safety valve, 1:484–485 ‘‘Safe yield’’ concept, 2:514 Sailors, 4:763 Saint-Venant (SV) equations, 3:250–251 Saline groundwater, 3:691 Saline lakes, 3:266 Saline seep, 5:453–454 Saline water, 2:546 sprinkler irrigation with, 3:713 Salinity. See also Desalination; Salt entries; Soil salinity; U.S. Salinity Laboratory Classification in animal farming operations, 3:539 biological response to, 3:682 in global oceans, 4:21 of irrigation water, 2:157; 5:207 lake, 3:266 profiles, 3:679–680 research on, 2:352–353 river, 3:679–680 sources of, 5:223–224 of tidal streams, 4:128–129, 130 in water bodies, 2:181 Salinity measurements, wetland, 3:497 Salinity threshold, 3:684 Salinization in Indian rivers, 3:451 soils affected by, 3:571 Salmonella, 1:278; 2:337–340 detecting using molecular tools, 2:337–339 direct detection of, 2:338 DNA probes in, 2:337–338 future options in detecting, 2:339 PCR based monitoring of, 2:338–339 Salmon species, 3:127 Salt(s). See also Road salt; Saline water; Salinity; Salinization; Sea salt effect effect of excess, 3:682 as groundwater tracers, 5:505 ion effects of, 3:682 leaching of, 3:679 in ponds, 3:485

scaling and, 1:545–547 as water quality indicators, 2:266 Salt balance on irrigated land, 3:677–681 measuring and modeling, 3:680 of the root zone, 3:678–679 Salt buildup, using microirrigation, 3:618 Salt loading, 1:633 Salt mines, oil-field brine and, 2:288 Salt stress, 3:683–684 Salt tolerance, 3:681–687 characterization and assessment of, 3:684 of crops, 3:684–685 factors influencing, 3:683–684 of plants, 3:682–683, 686 recent developments in, 3:686 Salt-tolerant plants, breeding, 3:686 Salt water, solubility of hydrocarbons in, 4:559–561 Saltwater contamination, mathematical formulation for, 5:664 Saltwater intrusion, 5:602 Sample contamination, 2:342 Samples. See also Sampling soil vapor, 5:548–549 vinyl chloride, 5:637 Sampling. See also Water sampling aquatic environmental, 2:170–171 of colloids, 3:74 design, 2:265 in fish consumption advisories, 3:119 frequency and time of, 2:179–180 locations and points related to, 2:178 low-flow, 5:406 raw water, 1:440t role in river water chemistry, 4:371–372 of sediment, 3:509 timing of, 2:180 water supply, 1:294–295 Sampling parameters, criteria for, 2:266–267 Sampling site, documenting, 2:162 SAMSON Database statistics, 5:79t Sand abstraction, 3:412–417 advantages and disadvantages of, 3:414 cost effectiveness of, 3:417 from ephemeral rivers, 3:414–415 history and use of, 3:413–4t4

methods of, 3:415–417 sustainability of, 3:415 water quality and, 3:415 Sand and gravel aquifers, 5:145 Sand filters, 3:752–754 Sand filtration, 1:225 San Diego, water supply demands in, 1:218–221 Sandstone, 5:55 Sandstone aquifers, 5:145 Sand wells, 3:413 Sandy media, in column experiments, 2:104 ‘‘Sanitary awakening,’’ 1:283 Sanitary landfilling, 1:699; 2:163 Sanitary quality, of urban stormwater runoff, 3:434 Sanitary sewerage system, design of, 3:434 Sanitary Sewer Overflows (SSOs), 1:799 Sanitary sewers, 3:331 Sanitary surveys, 1:294 Sanitary systems, 5:452–453 Sanitation, 1:661 in developing countries, 2:630–633 ecological, 1:675–676 impact of, 1:25–26 integrated capacity building for, 1:651–656 issues in, 1:518 private sector participation models providing, 1:50–51 sustainable, 1:653–654t wastewater, 1:498 Sanitation Connection Internet resource, 2:669 Sanitation surveys, 2:361 Sanitation systems criteria for, 1:675 implementation of, 1:676 Sanmenxia reservoir, 3:46, 48 Santa Barbara Oil Spill, 3:517 Sap-flow techniques, 3:736, 737–738, 739 Saprotrophic organisms, in ponds, 3:487 Saratoga Springs waters, medicinal properties of, 4:797–801 Sarcodina, 2:313 Satellite-borne instruments, 4:311–313 Satellite data, water-flow-related, 2:587–589

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CUMULATIVE INDEX

Satellite energy balance (EB), sources of, 3:564 Satellite imagery, large area surface energy balance estimation using, 3:560–565 Satellites. See also Aqua earth observing system (EOS) rainfall monitoring using, 4:311–313 water-resource, 4:326t Satellite sensors, for waterbody detection, 4:325 Satellite sensor technology, 4:350–351 Saturated adiabatic lapse rate (SALR), 4:370 Saturated media, mass transport in, 5:273–275 Saturated porous media, modeling of DNAPL migration in, 5:668–672 Saturated river sediment, water from, 3:412–417 Saturated soil, role in flooding, 3:142–143 Saturated zone, 5:514 soil samples from, 3:689 reactive transport in, 5:518–524 Saturating recycle equation, 2:277 Saturation excess, 4:316 Saturation-excess overland flow, 3:452–453 Saturation index, 4:409 Saturation vapor pressure, 3:574; 4:271–272 ‘‘Saturnine gout,’’ 2:436 Saxitoxins, 2:389 SBC (Ca2+ + Mg2+ + Na+ + K+ + NH+ 4 ), 3:1, 2 SBR biological treatment unit, 1:711, 712t SCADA systems, 1:437. See also System Control and Data Acquisition (SCADA) Scale, 5:175 problem of, 1:534–535 Scale formation. See also Scaling entries crystallization leading to, 1:547 in industrial cooling water, 1:545–549 on pipe surface, 1:6 ‘‘Scale modifiers,’’ 1:548 Scaling, 1:415 in diffused air aeration systems, 1:630

Scaling control, in industrial cooling water, 1:547–549 Scanning Doppler lidar, 4:297 Scanning electron microscopy (SEM), 2:310; 4:491 SCARPS, case study of, 5:98 Schauberger, Viktor, 4:794 Schlumberger array, 5:445 Schmutzdecke, 1:234, 235–236, 244, 246 School conservation programs, 1:148 Schwenk, Theodor, 4:768,793–794 Schwenk, Wolfram, 4:796 Science magazine, 3:515 Science Olympiad (SO), 4:714 Scientific fisheries management, 3:124 Scientific water management models, 2:620 Scientists, atmospheric, 4:328–330 Scour hole, 3:67 Scour pools, 3:67, 68 Screened hydraulic probes, 5:405 Screen filters, for microirrigation, 3:748–750 Screening, 1:814 at CSO facilities, 1:784–785 domestic sewage, 1:832 in dye tracer selection, 3:98–101 wastewater, 1:809 Scrubbing, for odor abatement, 1:762 SCS lag equation, 3:471 Sculpin tissue. See also Tissue metals in, 3:361t organochlorine compounds in, 3:349, 350, 360t trace elements detected in, 3:362 Seabed filtration intake systems, 5:89–91 Sea floor gas hydrate observations on, 4:60–61 high-resolution surveys of, 4:77–78 Sea floor mapping, of New York City Historic Area Remediation Site, 4:77–80 Sea fog, 4:232 Seagrass restoration, 4:56 Sea ice, 4:21, 194 Sea ice cycle, 4:70 Sea level, climate and, 4:117–118 Sea-level changes, potential, 4:118 Sea-level rise as a global problem, 2:483 societal impacts of, 2:482–483

813

Seals, mechanical, 1:882 Sea salt effect, acidification and, 3:5. See also Salt entries Seasonal cropping, 4:698 Seasonal crop water requirements, estimating, 3:558 Seasonally draining epikarsts, 5:237 Seasonal tidal stream variability, 4:130–132 Seasonal–vertical solar radiation, distribution equation for, 3:376 Sea Surface Temperature (SST), 4:335 Seattle Water Department, water use reduction plan, 2:581, 582t Sea turtles, 4:57 Sea volume, effects of decrease in, 3:15–20 Seawater, 2:95; 4:285 chemistry of, 1:414 composition of, 4:160, 285 contamination criteria for, 2:450t ions in, 4:159–160 microbial detection of oil pollution in, 2:441–442 microbial detection of phenols in, 2:442 molecular structure of, 4:513 quality control of, 2:449–451 similarity to blood plasma, 4:712 sodium in, 4:552 Seawater brines, 5:52 Seawater CH4 , sources of, 4:87–88 Seawater desalination plant, 5:91 Seawater N2 O, sources of, 4:87 Seawater RO plant, 1:308 Seawater temperature estimates, in paleoceanography, 4:92–95 Seawater temperature information, 4:93 SEBAL (surface energy balance algorithm for land), 3:561 Secondary drinking water regulations, 4:678 Secondary ion mass spectrometry, 1:646 Secondary MCLs (SMCLs), 1:477 Secondary physicochemical monitoring, 2:267 Secondary settling tanks, 1:453, 456 design considerations for, 1:456 Secondary wastewater systems, powdered activated carbon in, 2:88

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814

CUMULATIVE INDEX

Secondary wastewater treatment, 1:809, 815–816, 827; 2:546 Secondary water quality standard, 2:373 Second law of thermodynamics, 5:170 Security prioritizing, 1:870–871 SCADA system, 1:451 of wastewater utilities, 1:870–871 water distribution system, 1:434–437 Security improvements, investing in, 1:871 Security requirements, for potable water, 2:347–348 Security vulnerability checklist, 1:434 Sediment(s). See also Bed sediment metal ion adsorption; Sand abstraction; Sedimentation; Sediment transport; Streambed sediment in an agricultural landscape, 3:606–607 aquatic, 2:384 characteristics of, 3:298t contaminated, 2:426 data and information related to, 3:509–510 defined, 2:546 from forest water, 2:199 heterogeneity of, 2:411 importance of, 3:508 organochlorine compounds in, 3:353–354t physical properties of, 3:417–418 as a pollutant, 3:607 properties of, 2:213t Puget Sound Basin, 3:349–362 routing, 3:412 sampling, 3:509 sealing and removal of, 2:5 sources of, 3:417 trace elements in, 3:455–456 in the Yellow River Basin, 3:46–47 Sedimentary deposits, of continental rifts, 3:20 Sedimentary rock(s), 2:546; 5:55 Sediment assays, sediment or fauna incubation experiment for, 2:418–423. See also Sediment quality assessment/characterization; Sediment toxicity assessment/tests

Sedimentation, 1:227, 370–371, 487, 811; 2:374; 3:401–404; 5:619. See also Reservoir sedimentation analysis and modeling of, 3:404–405 classes of, 3:404 dilution equivalent to, 4:104 domestic sewage, 1:832 flotation and, 3:404–408 general conditions for, 3:45–47 impact of, 4:107 managing, 2:186 particulate removal by, 1:243–245 primary, 1:815 process design and implementation of, 3:406 as a threat to fisheries resources, 3:134 Sedimentation processes, selecting, 3:407t Sedimentation tanks, 1:259f, 260; 2:546 design criteria for, 1:456t Sediment-attached pollution, 3:333 Sediment-based endocrine disruption (ED), 3:54 Sediment bypass, 3:412 Sediment cleanup, dredging for, 2:126 Sediment column porewater nutrient concentrations, 4:73–77 seasonal coupling with intertidal macrofauna, 4:73–77 Sediment cores, 4:92–93 Sediment data, trace element pollution and, 4:112 Sediment detention system, 1:538 Sediment discharge ratio, 3:419 Sediment-dwelling organisms body concentrations in, 2:215–219 exposure tests with, 2:212, 420 heavy metal uptake rates among, 2:211–219 Sediment inflow, into reservoirs, 3:411–412 Sediment load measurements, 3:397–401 Sediment loads, 3:403 river, 3:393t Sediment management alternatives, dam decommissioning and, 3:388t Sediment Or Fauna Incubation Experiment (SOFIE ), 2:212, 418–423

exposure method for, 2:420 results of, 2:421–423 Sediment oxidation, algal control via, 2:4–5 Sediment pollutants, ecotoxicological effects of, 2:428t Sediment production, by erosion, 3:31 Sediment quality criteria for, 2:126 future research on, 2:430–431 Sediment quality assessment/characterization bioaccumulation in, 2:426–428 biomarkers in, 2:429 chronic, bioaccumulation, and sublethal bioassays for, 2:351 future developments in, 2:352–353 historical background of, 2:408 weight of evidence approach to, 2:350–355 Sediment quality criteria/guidelines (SQGs), 2:428, 430; 3:54 co-occurrence-based, 4:601–602 Sediment Quality Triad (SQT), 2:350, 351 Sediment research/studies on agricultural drainage ditches, 3:90t Lake Baikal, 3:21 Sediments antimony concentrations in, 4:592 groundwater flow in, 5:175–177 specific yield of, 5:577t xenobiotic accumulation and, 4:120 Sediment samplers, 4:71 Sediment screening, 4:601 Sediment simulation, 2:256–259 Sediment testing, incentive for, 2:408 Sediment toxicity assessment/testing, 4:122–123 acute, 3:51–52 amphipod, 2:408–413 application of, 2:460–462 behavioral endpoints in, 3:54–55 bioassays checked for use in, 2:462t biological guidelines for, 2:463t biomarkers used for, 2:430t chironomids in, 3:50–57 chronic, 3:52–54 design for, 2:459 development and application of, 2:383–387 development for regulatory purposes, 2:458–464 future, 3:54–55

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CUMULATIVE INDEX

marine and estuarine microalgal, 4:120–124 systems used for, 2:384–385 Sediment transport, 3:49, 401, 417–421; 4:359 downstream fining in, 3:420 functions of, 3:419–420 incipient motion and, 3:418 modeling of, 3:421 modes of, 3:397–400 movement of fluvial sediments, 3:418–419 by size fraction, 3:403 stream aggradation and degradation related to, 3:420 stream capacity for, 3:419 Sediment transport capacity, 3:659 changes in, 3:393 Sediment yield, 3:419 gully, 3:184–185 Seed microorganisms, 2:39 Seepage, 2:546 Seepage control, levee, 3:289 Seepage flow. See Base flow Seepage meter method, 5:166 Seepage meters, 5:74 Seepage velocity, 5:525 Seeps, responses to earthquakes, 5:112–113 Seismic geophysical methods, 5:147–148 Seismic reflection methods, 5:147–148 Seismic refraction method, 5:147 Seismic sea wave, 4:160–163 Seismic surveys, riverine, 5:679–680 Select Committee on Transportation Routes, 2:523 Selective dissemination of information (SDI), 2:672 Selective metering, 1:494 Selenate, 5:398 Selenide, 1:852 Selenium (Se) Aquatic Life Criterion for, 2:355–357 in ash pond water, 1:851–853 bioaccumulation of, 2:357t biogeochemistry of, 2:355 biogeochemical cycling of, 2:356f hyperaccumulators and nonaccumulators of, 5:398 maximum contaminant level of, 2:235t volatilization of, 2:359

Selenium-contaminated waters, remediation and bioremediation of, 2:355–360 Selenium contamination, sources of, 5:397–398 Selenium-laden soils, phytoremediation of, 5:397–401 Selenium transformation mechanisms, 5:398 Self-governing institutions, promoting, 2:558 Self-supplied water, 2:546 users of, 1:551 Semi-arid climatic zone, 4:257 Semi-Arid Hydrology and Riparian Areas (SAHRA) program, 5:72 ‘‘Semiconfined aquifer,’’ 5:11 Semiconfined aquifer flows, 5:494–495 Semi-intensive farm systems, 3:579 Semiperched groundwater, 5:354 Semipermeable membrane devices (SPMDs), 2:170–172; 5:672–677 deployment, processing, and analysis of, 5:675–676 sampling using, 5:674–675 similarity to biomembranes, 5:673–674 Semivolatile organic compounds (SVOCs), 1:838; 5:338 in streambed sediment, 3:357–359t Senec gravel pit, biomanipulation trials in, 2:55t Sensible heat flux, 3:193 Sensible heat flux density, 3:563 Sensitive ecosystems, water recycling and, 2:612 Sensitivity analysis, 3:319, 329 Sensor-based pH measurement, 2:295–299 Sensor drift, 2:283 Sentinel species, 3:116; 4:113 Separate Municipal Storm Sewer Systems (MS4), 4:659 Separation, of hydrocarbons, 1:576–577 Separation processes, flotation, 1:684–688 Septic systems, 5:604. See also Septic treatment systems contaminants from, 3:228 Septic tank, 2:546 systems, 1:34, 61–63 Septic treatment systems, 2:663–664

815

Sequencing batch reactor, 1:815 Sequential sediment samplers, 4:71 Sequential stream flow routing (SSR), 3:202 Sequent-peak analysis, 3:261–262 Sequestering agents, 1:548t Sequestration of iron and manganese, 1:314–315 for scale control, 1:548 Serial analysis of gene expression (SAGE), 2:60 Serological tools, 1:189–190 Serpulid worms, 1:541 Service contract model, 1:50 Service pipes, freezing and clamping of, 1:890 Setback distances, for geologic settings, 1:72–73 Setting velocity, 3:405–406 Settling basins, 1:682–683 Settling pond, 2:546 Settling tanks, 1:452–457 design considerations for, 1:455–456 enhancements to, 1:454–455 types of, 1:452–454 Severe cyclonic storm, 4:195 Sewage, 1:828–830. See also Domestic sewage; Sewage treatment entries; Sewerage odors composition and contaminants, 1:829; 2:182 defined, 1:517 dioxin-contaminated, 2:110 reasons for treating, 1:517–518 treatment plant influent metals in, 1:831 Sewage control, during repairs, 1:888 Sewage liquid, electronic nose analysis of, 2:282 Sewage sludge disposal at sea, 4:147 occurrence of detergents in, 1:671–672 precautionary principle regarding, 2:600 Sewage treatment, 1:829–830 anaerobic, 1:517–521 Sewage treatment facilities, fate of pharmaceuticals in, 1:373–376 Sewage treatment plant, 2:546 Sewage treatment systems off-site, 1:830 on-site, 1:830

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816

CUMULATIVE INDEX

Sewerage, simplified, 2:633 Sewerage odors causes of, 1:911–912 controlling, 1:910–915 preventing, 1:912–913 removing, 1:913–915 Sewer overflows, 2:263 Sewer overflow treatment. See Combined sewer overflow (CSO) treatment Sewer overflow volumes, reduction of, 3:338 Sewer pipeline. See Underground pipeline Sewers field measurements in, 3:338 modeling fecal coliform in, 3:334 as reactors, 3:331–332 Sewer separation, 1:783 Sewer systems, 1:884 holistic analysis of, 3:336 urban, 2:96 Sewer water quality modeling, 3:331–337 challenges in, 3:336 deterministic, 3:332–333 procedure for, 3:334–335 Shaded relief sea floor images, 4:78 Shadow clock, 4:703 Shallow aeration unit, 1:51–52 Shallow groundwater contamination, 5:426 Shallow lake ecosystems, alternative stable states theory regarding, 3:272–274 Shallow lakes, 3:265 Shallow sewerage, 2:633 Shallow tray aeration (STA), 1:460 Shallow water equations (SWEs), 3:710–711; 5:659 Shallow water flow (SWF), 3:710 Shallow water habitat, eutrophication in, 3:108–109 Shallow water theories, 4:135–136 Shallow water waves, 4:135–138 Shannon entropy, 4:218 Shear stress, microbial growth and, 3:312. See also Shields shear stress approach Sheet piling breakwater, 4:19–20 Sheindorf et al. adsorption model, 1:109 Shelf waters, 4:26 Shellfish, vulnerability to pollutant discharge, 3:284

Shellfish growing, water classification for, 2:360–362 Shelterbelts, 3:551, 568–569 Shields shear stress approach, 3:418 Shiga-like toxins, 2:136 Shiga toxin-producing Escherichia coli (STEC), 2:136, 137 Shiga toxins, 2:137 Shigella, 1:278 Shigellosis colitis, 1:181–182 Ship engineers, 4:763 Ship pilots, 4:763 Shoaling, wave refraction and, 4:136–137 Shoaling depth, estimating, 4:3–4 Shock fitting, 3:241–242 Shock formation, 3:239, 248–249 Shocks on curved surfaces, 3:241 first-order, 3:240 in a kinematic cascade, 3:241 in planar flows, 3:241 Shore Protection Act of 1989, 4:40 Short-term persistence, 3:210, 212 Short-wave infrared (SWIR) domain, 3:719, 720 Short-wave radiation, into open waterbodies, 3:191–192 Shotcrete, 1:880 Showerheads, low-flow, 2:665–666 Shuffled complex evolution algorithm (SCE-UA), 4:298 Sieve analysis, 1:96–97 Signal delay measurements, slant-path, 4:247–248 Silent Spring, The (Carson), 4:653 Silesia fishpond culture in, 3:135–141 pond fish farming in, 4:719–720, 721–722 Silica biochemical aspects of, 4:550–551 classification of, 4:549 deposition of, 4:550 geochemistry of, 4:549 in natural waters, 4:548–551 Silica compounds, dissolved, 4:550 Silica cycle, geochemical, 4:550 Silicate corrosion inhibitors, 1:154 Silicate rocks, dissolution of, 4:549–550 Silicates distribution of, 4:74 inorganic, 1:11 Silicic acid, 4:548, 549

Silicon dioxide (SiO2 ), 4:548 Siltation rate, reservoir, 3:410 Silt density index (SDI), 1:418 Silt traps, 3:500 Silvester, Hans, 4:768 Simple clathrate hydrates, 4:471 Simple random groundwater monitoring network, 5:314 Simple Ratio Pigment Index (SRPI), 3:722 Simple water quality models, 2:248 Simulation, long-term, 3:335. See also Stochastic simulation Simulation models, 3:386–387 physically and chemically based, 3:5–6 Simulation of single sludge processes (SSSP) model, 1:731 Simulated oil spill case study, 2:172 Simulator for Water Resources in Rural Basins (SWRRB) model, 2:250 Singh and Stall base flow separation method, 3:26–27 Single-celled organisms, as test subjects, 2:413 Single channel seismic reflection surveys, 5:680 Single-component phase diagram, 4:365 Single dimensional pump test analysis, 5:185–186 Single pass adsorption resins technology, 5:633 Single point resistance log, 5:152 Single-stage samplers, 3:399 Singlet oxygen, 4:533 Sinkhole, 2:546–547 Sinking bowl water clock, 4:705–706 Sinuosity, 3:31 Sinusoidal oscillations, 5:498 SIPHONET numerical model, 1:59 Siphonic roof drainage, 1:55, 56–57 systems, 1:58–59 Site assessment, Orlando Naval Training Center, 5:82–83 Site selection, for wells, 5:88 Site-specific sampling, 2:162 Siting issues, for municipal solid waste landfills, 2:167 Size fractionation procedures, 2:102 Skeletal fluorosis, 4:435 Skimmed groundwater, 3:691–692 Skimming wells, 3:594 Skin cancer, arsenic-related, 2:17

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CUMULATIVE INDEX

Sky emissivities, 3:563 Slant-path signal delay measurements, 4:247–248 Slime layers. See Biofilms Slimes, extracellular, 5:23 Slip coefficient, 5:500 Sliplining, 1:801–802, 877 Slope-area law, 3:94 Sloped roofs, 1:55 Slope protection, riverside, 3:290 Sloping aquifer, groundwater flow equations for, 5:13 Sloping lands, drainage of, 5:97 Slots, 3:70 Slow migratory (spreading) cell formation, 2:240 Slow moving fronts, fog and, 4:231 Slow neutron count ratio (CR), 3:693 Slow neutron detector, 3:692 Slow sand filter pilot, testing, 1:432 Slow sand filters, 1:231, 233–234, 246–247, 432f advantages and limitations of, 1:431–432 design summary of, 1:433t treatment performance of, 1:431t Slow sand filtration, 1:228, 235–237, 239, 249–250, 431–434, 458, 488 monitoring and operation requirements for, 1:433 process of, 1:432 Sludge(s), 1:413. See also Sludge treatment and disposal; Wastewater sludge chemical composition of, 1:862 discharge, 1:324 floc from, 1:844 odors from, 1:850 pharmaceutical products in, 1:375 physical properties of, 1:862–863 quantity and moisture of, 1:862 reuse and disposal of, 1:684 septicity of, 1:455 as a source of contaminants, 5:433 types of, 1:861–862 Sludge age, 1:730 Sludge digestion, persistent organic pollutants and, 1:769 Sludge processing, 1:864–866 system for, 1:682f Sludge separation problems, 1:844–846

Sludge treatment and disposal, 1:687, 853–861 codisposal with municipal solid wastes, 1:861 land application, 1:858 options for, 1:854–858 sewage sludge categories, 1:854 thermal processing, 1:858–860 usable materials production, 1:861 Sludge treatment stream, fate of POPs in, 1:768–769 Slug test, 5:183, 575 Small drinking water systems corrosion control in, 1:459 disinfection methods for, 1:457–458 filtration for, 1:458–459 ion exchange and demineralization in, 1:459–460 lime softening in, 1:460–461 organic removal in, 1:351–353, 460 SCADA and, 1:450 treatment technologies for, 1:457–466 Smallpox, 1:88 Small-scale industry, sand abstraction for, 3:414 Small-scale wastewater treatment, 1:840–844 costs of, 1:842–843 methods of, 1:840–842 requirements for, 1:840 Small water reservoirs, role in environment, 1:403–408 Small water retention, 1:405, 407 Smoke testing, in pipeline assessment, 1:885 SMP reagents, 2:376 SNOTEL snowpack, Flattop Mountain, 4:334–336 Snow, 4:293, 336–337 density of, 4:333–334 remote sensing of, 4:324 Snow control, alternatives to NaCl for, 2:320t Snow course, 4:338 Snow cover studies, remote sensing and GIS application in, 2:533 Snowfall in Canada, 2:660 remote sensing of, 4:322–323 Snowmelt, 4:337 acidic deposition from, 3:225 computing, 4:337 episodes of, 3:5

817

role in flooding, 3:145 runoff floods, 3:511 Snowpack, 4:336–337 Snow surveys, 4:337–338 instruments used for, 4:338 SO3 groups, QSAR modeling and, 3:101 SO4 2− , 3:1, 2, 3, 6. See also Sulfate Social capital, 1:655–656 Social impacts, of water transfers, 4:687 Social justice, in the Arab world, 4:634 Social responsibility, 1:45 Social standards, sharing of, 4:738–739 Social value of water, 2:653–654 Society acid rain and, 4:377–381 benefits of weather forecasting to, 4:351–352 climate and, 4:183–186 impact of urban flooding on, 3:161 importance of water to, 4:289–290 ‘‘Sociological drought,’’ 2:576 Socio-spatial consciousness, 4:680 Soda ash, in acid mine treatment, 5:4 Sodium (Na) exchangeable, 3:682 in groundwater, 2:394 irrigation water quality and, 5:207–208 in natural waters, 4:551–553 treatment of, 4:552 Sodium adsorption ratio (SAR), 5:204 for irrigation water, 2:157–159; 5:207–208, 210 values of, 2:160t Sodium carbonate, in irrigation water, 2:159; 5:208 Sodium chloride, properties of, 2:320t. See also Road salt; Salt entries Sodium concentration, 5:196 Sodium hexametaphosphate (SHMP), 1:419; 4:415–416 Sodium hypochlorite, 1:457 Sodium ion, 4:551 Sodium nitrate, 5:322–323 Sodium perchlorate, 5:632 Sodium pertechnetate, 4:579 SOFIE. See Sediment Or Fauna Incubation Experiment (SOFIE ) ‘‘Soft’’ carbon, 4:386

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818

CUMULATIVE INDEX

Softening. See also Lime softening alternatives for, 1:323–324 benefits and concerns about, 1:324 lime–soda ash, 1:320–321 ‘‘Softening membranes,’’ 1:335 Software. See also Spreadsheet entries analysis, 3:387 catchment water quality modeling, 2:325–326 culvert hydraulic computation, 3:78 drainage/sewer system modeling, 3:161 integrated water quality modeling, 2:328 reservoir-analysis, 3:203 river water quality modeling, 2:325–331 steady-state, 2:326–327 unsteady-state, 2:327–328 wastewater modeling, 1:732 Soft water, 4:553–555 acidified, 3:8 availability of, 4:554–555 health and, 4:554 Soil(s). See also Permanent frost (permafrost); Soil conservation; Soil erosion acidification of, 3:8 acidity and alkalinity in, 3:707 as a biodegradable agent, 3:707–708 cadmium sorption and desorption in, 5:616–617 chemistry of, 5:367 cleanup of, 3:652 detoxification of, 5:380 effective utilization of, 5:466 electrical conductivity of, 3:675–676 forms of nitrogen in, 3:695 infiltration capacity of, 3:171–172; 5:272, 213 lithologic description and interpretation of, 3:689–691 metal burden in, 5:433 mineral components of, 3:706 nitrogen losses from, 3:695–696 nitrogen management in, 3:694–701 pesticide-contaminated, 3:651–655 phosphorus in, 3:110 premining analysis of, 5:1

reactive solute transport in, 5:524–531 redox potential of, 3:599 relationship to water, 3:641 as a semipermeable barrier, 5:532 as a source of contaminants, 5:433 spatial and temporal variability in, 4:488 water issues related to, 3:706–708 water retention properties of, 5:260t,472 zinc and cadmium bioavailability in, 5:370 Soil analysis and improvements, 3:556 Soil and Water Assessment Tool (SWAT), 2:250 Soil bioengineering, flood-related, 3:148 Soil bioventing, 5:120 electrokinetic enhanced, 5:121–122 Soil components, pesticide sorption to, 3:648 Soil conditioners, 3:552, 569 Soil conservation, 3:549–553 approaches to, 3:549–552 implementation and adoption of measures for, 3:552 need for, 3:549 soil management methods of, 3:551–552, 569 Soil conservation ecosystems, ancient Sri Lankan, 4:772–780 Soil Conservation Service (SCS), 2:513 soil group classification, 3:30 Soil contaminants, sources of, 5:433 Soil contamination. See also Contaminated soil causes of, 5:432 by heavy metals, 5:275–280 sources of, 3:651 treatment with Fenton’s Reaction, 4:445–446 Soil disturbance, reducing, 3:552 Soil erosion, 3:565–567 controlling, 3:567–569 impacts of, 3:566–567 nitrogen losses from, 3:696 rates of, 3:566, 567t as a source of sediments, 3:417 Soil fauna, 3:706

Soil fertility, components of, 3:550t Soil flushing, in situ, 5:435 Soil gas, 5:548 Soil groups, 3:30 CEC values for, 5:261t Soil lysimeter, 5:463 Soil management, 4:433, 434 Soil management practices, water quality models for developing, 2:248–255 Soil metals, chemical fate and mobility of, 5:433 Soil microbiology, 5:464 Soil moisture, 5:600 content, 3:600, 692–694; 5:320 controls on, 4:484–486 measurement of, 4:487–488 remote sensing of, 4:323–324 soil capacity to hold, 3:707 Soil moisture assessment, remote sensing and GIS application in, 2:533 Soil-moisture-data-based methods, 5:165 Soil moisture measurement, using neutron probe, 3:692–694 Soil moisture processes, infiltration and, 4:484–489 Soil monitoring techniques, direct, 5:542 Soil nutrients, leaching of, 4:380 Soil phosphorus. See also Phosphorus (P) availability of, 3:702–703 environmental management of, 3:704–705 impact on surface water quality, 3:701–706 transport of, 3:703–704 Soil pipes, 5:401–404 hydrology and erosion of, 5:403–404 initiation and identification of, 5:401–402 morphology of, 5:402–403 Soil-plant systems, variation in, 3:602 Soil salinity, 3:673–677 field methods of measuring, 3:674–676 laboratory methods of measuring, 3:673–674 plant tolerance to, 3:676 remote sensing and GIS application in, 2:534

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CUMULATIVE INDEX

Soil sampling groundwater assessment using, 3:688–691 methods of, 3:689–690 Soil solution extracts, electrical conductivity of, 3:673–674 Soil sorption parameters, 3:99 Soil spatial variability apparent soil electrical conductivity and, 5:466 characterizing, 5:465–471 ECa -directed soil sampling survey to characterize, 5:467 Soil surface, evaporation at, 5:211 Soil tests, to predict available phosphorus, 3:703 Soil texture, influence on water penetration, 3:707 Soil to plant absorption, 3:644 Soil treatment/groundwater treatment boundary, 5:39 Soil vapor concentrations, 5:552–553 Soil vapor data, groundwater investigations and, 5:548–554 Soil vapor extraction (SVE), 5:40, 426, 427–428, 440–441, 628 activated carbon in, 1:105 versus bioventing, 5:43 of vinyl chloride, 5:6390 Soil vapor/groundwater contamination, sources of, 5:550 Soil vapor methods, 5:548–549 Soil vapor samples, collection of, 5:548–549 Soil-vegetation-atmosphere-transfer (SVAT) models, 4:322 Soil venting, 5:426, 430 Soil washing, 3:653; 5:435 for lead, 5:648 Soil water, 5:461–463, 531–532 lysimeter sampling of, 2:340–343 measurement of, 5:533 solute concentration of, 2:340 storage of, 5:124 Soil water balance method, 5:165 Soil-water characteristic curve, 5:535–536 Soil water movement, 5:210, 471–473 principles, 4:486 Soil water potential, 5:532 components of, 5:532–533 factors affecting, 5:532 Soil water processes, infiltration and, 5:210–212

Soil water redistribution, 5:211 Soil water sampling, 5:463 Solar actinic flux, 4:531 Solar and Meteorological Observation Network (SAMSON), 5:78, 79t Solar electric power plants, 4:479 Solar energy, evaporation and, 4:223–224 Solar radiation hydrologic cycle and, 4:277 in shallow stagnant waters, 3:375–378 Solar system, liquid water in, 4:190, 191 Solar thermal plants, 1:563 Solar water heaters, domestic, 1:63–67 Solar water heating collectors, 1:65–66 Solidification process, 5:618 Solidification/stabilization (S/S), 1:837f application and performance of, 1:839 cost of, 1:839–840 defined, 1:835–836 of hazardous solid wastes, 1:835–840 immobilization technologies, 5:434 key features of, 1:838 likelihood of cross-media contamination from, 1:838–839 pollutant cross-media transfer potential after, 1:838 Solid/liquid solvent extraction, 2:307 Solid phase extraction (SPE) technique, 4:508 Solids in domestic sewage, 1:830 role in fish growth and production, 3:130–131 Solids loading rate (SLR), 1:456 Solid state pH sensors, 2:298–299 Solid trap materials, 2:307 Solid wastes. See also Hazardous solid wastes from electric generating plants, 1:555–556 removal of, 1:682–684 Solitary wave theory, 4:135–136 Soligenic areas, 1:404 Solubilization, by biosurfactants, 5:377

819

Solubility of chemicals in water, 4:555–559 of hydrocarbons and sulfur compounds in water, 4:561–564 of hydrocarbons in salt water, 4:559–561 Solubility graphs, 4:556–558f, 559, 560–561f, 562–564f Soluble fatty acids, anaerobic tank, 1:789 Solute mobility, issues involved in, 5:307–308t Solutes, 2:547; 4:458–459 reactive, 5:274–275 Solute transport abiotic, 5:527–528 biotic processes affecting, 5:528–529 equations governing, 5:309–312 physical mechanisms of, 5:525–526 scales of observation for, 5:306–308 in soil and groundwater, 5:524–531 Solute transport models, 5:303–304 groundwater, 5:305–313 Solutions defined, 2:547 freezing of, 4:586 redox potential of, 2:466 Solvent extraction, 1:812 Solvent remediation, water-jetting drilling technologies for, 5:234–235 Solvents, 2:317t, 547 extraction of, 2:306–307 stabilizers for, 2:317 SOLVER function, 2:621 Somalia, megawatersheds exploration in, 5:267–269 Sonar, for pipeline assessment, 1:884 Sonic logs, 5:153 Sorbents, chemically modified, 2:72 Sorbitol-containing media, 2:139 Sorption, 2:362–364; 5:527 in amorphous and condensed organic matter domains, 4:386 arsenic, 1:82 defluoridation and, 4:437 of dissolved chemicals, 5:261–262 fixed-bed, 2:363–364 in geosorbent domains, 4:385–386 of hydrophobic organic compounds, 4:387–388

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820

CUMULATIVE INDEX

Sorption, (continued) kinetics, 2:72 in mineral domain, 4:386–387 of organic vapors, 5:545 rates of, 4:387–388 by zeolites, 1:874 Sorption coefficient, of cadmium onto sea sand, 2:105 Sorption–desorption kinetics, 4:388 Sorption equilibrium, 4:384–388 factors affecting, 4:387 Sorption kinetics, 4:564–569 Sorptive filtration, 2:362–366 combined process in, 2:364–366 Sorptive flotation, 1:588 SOTE, of diffused air aeration systems, 1:629–630 Sound attenuation of, 4:570 oceanic, 4:570 in water, 4:569–571 Sound detection, underwater, 4:570–571 Sounding profiles, present during coastal fog, 4:237–239 Sound waves, frequency and amplitude of, 4:569–570 Source Loading and Management Model (SLAMM), 2:253 Source-pathway-receptor analysis, 5:38 Source water assessment, 1:444–448, 524 area delineation, 1:445–446 contamination inventory, 1:446 determining contamination susceptibility, 1:446–447 releasing assessment results, 1:447 using, 1:447 Source water assessment programs (SWAPs), 1:445, 525 Source-water protection, 2:120, 311–313 Source water quality, degraded, 2:400 Source water quality management, 2:399–401 future of, 2:401 South Africa drinking water disinfection in, 1:382–387 drinking water quality failure in, 1:221–227

inadequate wastewater treatment in, 1:661–667 water quality guidelines in, 1:385, 386 South America cienega in, 3:57 transboundary waters in, 4:642–643 South Asia, hydro-borders in, 4:680–684 South Atlantic Bight Recruitment Experiment (SABRE), 4:55, 57 South Branch Raritan River, flow-duration curve for, 3:103, 104f South Coast Track, 4:788 South Dakota, in-stream flow protection in, 4:662 Southeast, water demands in, 2:501 Southern Arizona, cienegas in, 3:58 Southern Hemisphere circumpolar vortex, strength of, 4:175 Soviet style water management, 3:19 Soxhlet extractor, 2:307 Space Station, water on, 4:572–574 Spain acidic rivers in, 3:10 dredged material characterization in, 2:351–352 permanent spot market in, 2:606 sediment toxicity tests in, 2:460–462 Spanish coast, storm record on, 4:339–341 Sparging, air, 5:428. See also Biosparging Sparging mixers, 1:625 Sparkling water, 1:4 Spate irrigation, 3:709 Spatial grid spacing, 3:257–258 Spatial heterogeneities, 5:308–309 Spatial resolution, 4:319 Spatial variability, 5:472 Spawning season, chlorine sensitivity and, 2:402–403 Speciation, effects of treatment processes on, 2:75–78 Species, taxonomical identification of, 2:459 Species and habitat preservation/protection, 3:124 fishery-related, 3:128 Specific conductance, 2:547 Specific capacity, 5:101, 460–461 tests, 5:102, 183

Specific gravity, 5:473–475 importance of, 5:474–475 measuring, 5:474 Specific heat, 4:367–368, 369 Specific humidity (q), 4:274 Specific storage, 5:129, 481, 482 Specific throughput volume (Vsp ), 1:103 Specific vulnerability, 5:595 Specific yield (Sy ), 5:481, 483, 576–577 of groundwater, 5:129 storage equation, 5:576–578 Spectral actinic flux, 4:531 Spectral analysis, for periodicity identification, 4:339 Spectral expansion method, 5:311–312 Spectral gamma log, 5:152 Spectral libraries, 2:308 Spectral radiance, 3:563 Spectral resolution, 4:320 Spectroscopic methods, 2:207 Spectroscopy, atomic absorption, 2:308–309 Specular reflectance, 4:321 Speleothems, 5:245, 246 Spent nuclear fuel storage, water treatment in, 1:595–608 Spherical activated carbon (SAC), 1:93 Spilling breakers, 4:137 Spillways, 2:568 Spirostomum ambiguum, biotest using, 2:413 Spirostomum teres, as a test organism, 2:414 SPIROTOX test, 2:413 SPMD-TOX paradigm, monitoring lipophilic contaminants using, 2:170–172 Spontaneous potential log, 5:151–152 Spontaneous potential method, 5:146–147 Sporadic disease, 1:187 Spore transmission, Microsporidium, 1:367–368 Sporozoans, 2:314 Spot markets, 2:606–607 Spot repairs, 1:882 Spray aeration, 1:460 Spray aeration unit, 1:51 Spray irrigation, 2:547 Spray microirrigation, 3:621

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CUMULATIVE INDEX

Spray-on linings, 1:879–881 Spreader ditch flow system, 3:165 Spreadsheet models, 2:253 Spreadsheets, decision support system, 2:620–621 Spreadsheet wastewater model, 1:731 Spring discharge, in regional flow systems, 5:420 Spring hydrograph analysis, 5:239–240 Springs geothermal, 5:156 hydrogeologic characteristics of, 5:476 responses to earthquakes, 5:112–113 ‘‘Spring’’ tides, 4:24 Sprinkler infiltrometer, 4:487 Sprinkler irrigation, 3:582, 712–714 methods, 2:495–496 Sprinklers, 2:666 Sri Lanka ancient water and soil conservation ecosystems of, 4:772–780 modern development in, 4:776 water disinfection in, 1:471–476 SSS autocorrelation function, 3:218 S state cycle, substrate water binding during, 4:536 S-state dependence, on isotope exchange rate, 4:537–540 SSURGO database, 5:302 Stability analysis, for levee construction, 3:287–288 Stability length, parameterization of, 4:1 Stabilization, 5:618 of sludge, 1:855–856, 865 Stabilization ponds, 1:704, 816, 833 Stable isotope probing (SIP), 1:645–646. See also Polar lipid-derived fatty acid-based SIP DNA, 1:645 RNA, 1:645–646 Stable isotopes as groundwater tracers, 5:503 in the water molecule, 5:229–231 Stagnant waters, solar radiation and temperature in, 3:375–378 Stakeholder approach, 3:124–125 Stakeholders integration among, 2:575 participation in flood management, 2:680

Standard aeration efficiency (SAE), 1:623 Standard bioassay, as an exposure method, 2:420 Standardized bioassays, 2:419, 420 Standardized Precipitation Index (SPI), 4:209, 210–211 Standard linear operating policy (SLOP) reservoir, 3:384 Standard mean ocean water (SMOW), 5:229 Standard oxygen transfer rate (SOTR), 1:623 Standards disinfection byproduct, 2:92t need for, 1:288 water-handling, 2:162–163 water-quality, 2:302 Standard-state reduction potentials, 2:465t Stand level transpiration, 3:736 Starch, as an indicator of organic contamination, 2:442 Star photospheres, water in, 4:190 State agricultural land use planning programs, 3:596–597 State clean water act programs, exemptions from, 4:673 State consumption advisories, 3:120 State government, approach to droughts, 2:577–578, 580 State groundwater law, 4:630–632 State planning and management activities, drought-related, 2:583–585 State programs, private and market-based augmentation of, 4:661–662 States drought policies of, 2:576 industrial water use by, 1:621–622t protection of in-stream values by, 4:660–663 State treatment capacity, 2:616 State variable interactions, 2:274f State water, allocation laws, 4:673 State water laws, 2:584–585 State Water Pollution Control Revolving Fund, 4:597 State water resource agencies, 4:649 State water supplies, 2:613–619 Static data, 2:622 ‘‘Static head,’’ 3:200, 201f

821

Static level, 5:101 Static wastewater models, 1:731–732 Stationary fronts, fog and, 4:231 Statistical analysis, in amphipod sediment toxicity tests, 2:411 Statistical approaches/methods to pesticide assessment, 5:595–596 to vulnerability assessment, 5:564–565 Statistical methods, for determining base flow recession constants, 3:25 Statistical properties, of drainage networks, 3:93–94 STATSGO database, 5:302 sT clathrate hydrate, 4:473 Steady fluid flows, 3:194 Steady-state calibration, 3:319 Steady-state flow aquifer tests, 5:491–497 Steady-state flows, 5:491 between parallel plates, 5:652–653 in a pipe, 5:654 Steady-state hydraulic theory, 1:58 Steady-state methods, for determining aquifer parameters, 5:492–496 Steady-state modeling, 1:132–133; 2:272 Steady-state nonuniform flow, 3:251–252 Steady-state software tools, 2:326–327 Steady-state subsurface drainage theory, 5:95–96 Steady wastewater model, 1:731 Steam, natural, 5:157 Steam flooding, of oil-field brine, 2:286 Steel industry impact, on surface water quality, 3:374 Steel tape method, 5:101 Stefan–Boltzmann law, 3:192 Stemflow, 3:171 Step-drawdown tests, 5:101, 102, 183, 574 Step feed, 1:815 Step feed reactor, 1:833 Step pools, 3:67 Steps, 3:70 Steric stabilization, 4:424 Stewart and Kantrud wetland classification system, 3:497 Stiff and Davis stability index (S&DSI), 4:415

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822

CUMULATIVE INDEX

Still-water channel units, 3:69t types of, 3:69t St. John’s, Newfoundland, aquatic habitat and construction in, 3:509 Stochastic disaggregation techniques, 3:427–428 Stochastic methods, 2:333 Stochastic models, 3:337; 5:309, 664–665 Stochastic simulation, 3:263–264 Box–Jenkins models in, 3:424–425 components and solution procedure of, 3:423–424 history of, 3:422 hydrologic process representation in, 3:425–426 multivariate stationary model for, 3:426–427 of hydrosystems, 3:421–430 point process models of, 3:428–429 utility of, 3:422–423 Stock enhancement examples of, 4:125–126 goals of, 4:125 optimizing, 4:126–127 problems of, 4:126 Stock enhancement techniques, marine, 4:124–128 Stockholm Convention on Persistent Organic Pollutants (SCOPOP), 2:106 Stock price performance, water company, 1:312t Stoichiometric analysis, of fluxes, 4:53 Stokes Law/Equation, 3:404, 405; 5:560, 561, 652, 654 Stokes wave theory, 4:138 Stomatal aperture, 3:717, 718 Stomatal conductance model, 3:714–715 Stomatal density, 3:714 Stomates, 3:714–719 anatomically explicit models of, 3:716 behavior regulation by, 3:718 diffusion porometers and, 3:717 function of, 3:717–718 mass- or viscous-flow porometers and, 3:717 occurrence and dimensions of, 3:715t study of, 3:715–717

Stone quarrying, impact on surface water quality, 3:374 Stony Brook River, flow-duration curve for, 3:104, 105f Storage off-stream, 1:486 as a watershed function, 3:474–476 Storage capacity, reservoir, 3:409–410 Storage coefficient (SS ), 5:480–483 groundwater, 5:129 Storage facilities, 1:408–411; 3:430–432 ‘‘Storage lag’’ policy, 3:386 Storage reservoirs. See also Storage zoning reservoir classification of, 1:406t functions of, 1:408 locating, 1:410 Storage system, 2:554 Storage tanks, 1:203, 448–449 hydraulic design of, 1:448–449 leaking, 5:603 shape and volume of, 1:410 Storage volume, water quality and, 2:367–368 Storage water quality, 2:367–370 management of, 2:368–369 Storage zoning reservoir, 3:385 Storativity (S), 5:184, 481, 483, 516 in confined and unconfined aquifers, 5:129–130 STORET system, 2:315 Storm-caused floods, 3:45 Storm drainage design, kinematic wave method for, 3:242–246 Storm hydrograph, 3:476 sample, 3:439, 440f Storm peak runoff, predicting, 4:317 Storm period analysis, statistical approach to, 4:338–343 Storm periodicity, southwestern Spanish coast, 4:341 Storm-rainfall floods, 3:511 Storm record, southwestern Spanish coast, 4:339–341 Storm sewers, 2:547; 3:331 Storm statistics, Chicago Station, 5:79t Storm surge, estimating, 4:3–4 Storm water. See also Storm water management effluent limitations, 1:759

preliminary treatment of, 3:500 treatment, 1:867–868 Storm water discharges, 4:657–659 industrial/commercial, 1:867 Storm water management, 1:499, 799–800; 2:192 constructed wetlands for, 1:896 municipal, 1:866–870 Storm Water Management Model (SWMM), 2:325–326; 3:256, 337 Stormwater management practices, 3:443 Storm water pollution, public agency activities and, 1:867 Stormwater pollution prevention plans (SWPPPs), 4:658 Stormwater runoff, 2:190 Stormwater systems, 3:498 modeling, 3:337 Stormwater–wastewater collection system, 1:748 Strahler stream order system/method, 3:32, 93 Straight water meter register, 1:339 Strategic analysis, 2:629 Stratification, lake, 3:265–267, 282 Stratified lakes, oxygen depletion in, 4:65 Stratified random groundwater monitoring network, 5:314 Stratigraphic controls, on river water infiltration, 5:679 Stratosphere, climate of, 4:182–183 Straw, in algal control, 2:5–6 Stream animal communities, Hawaiian Islands, 4:803 Stream-aquifer interaction, 4:359 Streambed sediment metals in, 3:355–356t organic compounds detected in, 3:352 polycyclic aromatic hydrocarbons in, 3:352t semivolatile organic and polychlorinated biphenyl compounds in, 3:357–359t trace elements detected in, 3:362 Stream classification, 3:65–71. See also River reaches valley segment level of, 3:66 watershed level of, 3:66 Streamflow, 2:547; 3:439–441 base flow contribution to, 3:22 versus precipitation, 4:433

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CUMULATIVE INDEX

Streamflow recession, 3:22 plots, 3:26 Stream-flow records, synthetic, 3:422 Stream-flow runoff, vegetative cover and, 3:30–31 Stream-flow simulation and reservoir regulation (SSARR) flow routing model, 3:255–256 Streamflow source zone, 4:670 Streamflow variability, quantitative measure of, 3:104 Streamflow variability indexes, 3:104 Stream gaging, 5:74 Stream health human impacts on, 3:39 using fish index of biotic integrity to measure, 3:38 Streamlines, 5:182 Stream order, 3:32 StreamPlan (Spreadsheet Tool for River Environmental Assessment Management and Planning), 2:328 Stream/river dilution capacity, 3:80 Streams. See also Rivers aggradation and degradation of, 3:420 chronic acidification of, 3:3 design flow in, 3:81–84 dilution in, 3:84 downstream fining in, 3:420 as one-way flow systems, 3:437–439 responses to earthquakes, 5:112–113 sorting processes in, 3:420 transport capacity of, 3:419 versus gullies, 3:183 Streamside Management Areas (SMAs), 2:187 STREAMS resource centers, 2:670 Streamwater, acidification of, 3:4 Stress-inducing agents, lux genes for determining, 2:174 Stressor-based assessments, 2:516 Stress tensor, 5:560, 652 Stripping, 1:707 Strontium isotopes case studies of, 4:576–577 in water and rock, 4:574–578 Strontium isotope systematics, 4:373 Structural changes, influence on the hydrologic cycle, 4:282 Structural failure, 3:259

Structural flood adjustment measures, 3:146–147, 148 Structural repair systems, 1:883 Structure Intensive Pigment Index (SIPI), 3:722 Study agencies, federal, 4:650t Sturgeon species, 3:127 Stx-producing Escherichia coli, 2:137. See also Escherichia coli O157:H7 Subchronic toxicity tests, sediment, 2:385t Subcutaneous zone, 5:243 Subglacial lakes life in, 3:506, 507 sampling of, 3:506 Subglacial Lake Vostok, 3:503–507 Sublethal bioassays, 2:351 Sublimation, 4:192, 343–345 Submarine gas hydrates, remote sensing for, 4:59–60 Submerged aeration systems, 1:624–626 Submerged aquatic plants, 3:743 biomass and extent of, 3:276 lake water quality and, 3:275–281 processes in, 3:276–278 promoting, 3:278–279 types of, 3:276 Submerged flow, in culverts, 3:76 Submerged pens, role in trout hatching, 3:458–460 Submersible pumps, 1:393 Submitochondrial particle (SMP) assay, 2:278–280 as a biological monitoring tool, 2:376–379 environmental monitoring with, 2:378 literature review of, 2:377–378 sensitivity of, 2:377 variants of, 2:378 Subparametric transformation mapping scheme, 5:657 Subsidence, 2:547 Substrate angle, dew amounts and, 4:204 Substrates, microbial growth in, 3:311 Substrate water binding, implications for O2 evolution, 4:540–541 Subsurface, contaminant attenuation in, 5:578–594 Subsurface barriers, 5:434, 617–618

823

Subsurface brines, 5:53 Subsurface contaminants, 5:579 Subsurface contaminant vapor, transport in, 5:550 Subsurface ‘‘dimples,’’ 5:92 Subsurface drainage, 3:451–454; 5:94–100 history of, 5:94–95 horizontal, 5:95, 97–99 numerical solutions for, 5:97 status and scope of, 5:99 theories of, 5:95–97 Subsurface drip irrigation (SDI), 3:621 advantages of, 3:622 extent of, 3:626 systems, 3:615 Subsurface flow combined free and porous, 5:498–501 governing model equation for, 5:499–500 Subsurface-flow constructed wetlands, 1:895–896 Subsurface flow systems, 3:365 Subsurface-flow wetlands, 1:787 Subsurface flushing methods, chemically enhanced, 5:440t Subsurface intake system, well, 5:87 Subsurface Investigation, Phase II, 5:437 Subsurface pipe drainage. See Tile drainage Subsurface recharge, 5:73 Subsurface redox chemistry, 5:413–417 Subsurface virus transport, 1:70–73 Subsurface water, vertical distribution of, 5:514 Subsurface water quality, soil nitrogen management and, 3:694–701 Subtitle D landfill leachates, metal organic interactions in, 5:258–260 Subtitle D landfill regulations, 2:166, 167 Suburban watersheds, water quality in, 3:441–444 Subwatersheds, ranking of, 3:158–159 Successive alkalinity producing system (SAPS), 2:424 Suction cups, 2:341 Suction lift, 3:380

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824

CUMULATIVE INDEX

Sudan-Egypt water dispute, 2:591–592 Sugar, water use, wastewater generation, and treatment proposals for, 1:617f Sugarcane industry effluent characteristics of, 1:619t ethanol production in, 1:618f raw materials, products, and byproducts of, 1:616f regulations in, 1:619t wastewater treatment in, 1:614–620 Sulfate. See also SO3 groups; SO4 2− acidification and, 3:5 as an electron acceptor, 1:691 in groundwater, 2:395 Sulfate assimilation pathway, manipulation of, 5:399 Sulfate-reducing bacteria (SRB), 1:84, 601 reactors, 5:5 Sulfate-reducing biofilm, 2:231 Sulfate-reducing to methanogenic conditions, 5:583–584 Sulfate transporter, 5:398 Sulfur-based reductants, 5:291 Sulfur compounds, solubility in water, 4:561–564. See also Sulphur compounds Sulfur deposition, 4:380 Sulfur dioxide dechlorination, 1:169 Sulfur fractionation, 4:502 Sulfur gases, 4:378 Sulfur mining, impact on surface water quality, 3:374 Sulfur-oxidizing bacteria, 2:241 Sulfur removal, 1:913 Sulphur compounds, volatile, 4:88. See also Sulfur compounds Sulphur isotopes, 5:220 as groundwater tracers, 5:503 Sumerian water consciousness, 4:708 Sun clocks, 4:703 Sun-powered water cycle, 4:584 Sun Valley, water conservation in, 2:635 Supercooling, of water, 4:585–586 Supercritical water oxidation (SCWO), 1:579, 874–875 Superfund. See EPA Superfund Superfund sites adsorptive filtration at, 2:365 groundwater treatment at, 5:39

Supermicropores, 1:97–98 Superoxide, 4:532 Superparametric transformation mapping scheme, 5:657 Supervisory Control and Data Acquisition (SCADA) system, 2:510 Supplies, disaster, 2:529 Supply equation, 2:615 Supply side groundwater management, 4:632 Supported capillary membrane sampler (SCMS), 4:515–516 Suppression subtractive hybridization (SSH) libraries, 2:62 Surface aeration, 1:623–624 Surface area, of porous solids, 1:97 Surface complexation models, 2:363 Surface drainage, 5:94 Surface emissivities, 3:563 Surface-flow constructed wetlands, 1:894–895 Surface flow systems, free-water, 3:365–366 Surface-flow wetlands, 1:787 Surface functional groups, on activated carbons, 2:82 Surface geophysical methods, 5:146–151 Surface mines, abandoned, 5:3 Surface runoff, 3:451–454 nitrogen losses from, 3:696 overland flow and, 3:452–453 river flow control and, 3:454 throughflow and, 3:453–454 Surfaces biofilm, 3:311 biofilm formation on, 2:228 biofouling and, 1:539 macrofouling of, 1:541 Surface snow, remote sensing of, 4:324 Surface stagnation stress due to, 3:602–603 from waterlogging, 3:600–601 Surface supplies, variability in, 2:400–401 Surface temperature, 3:563 Surface tension, 2:547 of chlorinated solvents, 5:92 Surface tension of electrolytes, role of dissolved gases in, 4:452

Surface trickle microirrigation, 3:621 Surface water(s). See also Surface water acidification; Surface water pollution algal-prone, 1:444 beryllium concentration in, 4:395–396 constructed wetlands for, 1:897 defined, 2:547 detection of pathogenic bacteria and biological contamination in, 2:441 effect of pesticides on, 3:650 environmental photochemistry in, 4:529–535 EU monitoring of, 2:267 form of iron in, 4:497–498 impacts on, 4:266 iron-oxidizing bacteria in, 2:150 metals in, 3:443 nitrate losses to, 3:642 Polydex disinfection of, 1:384 problems with, 5:332–333 quality of, 2:585–586 relationship to groundwater, 2:396–397 retention of, 1:405 technetium in, 4:580 typical analysis of, 3:373t use-based classification of, 2:184 Surface water acidification, 3:1–2, 10–11; 4:286 problem areas, 3:8–9 research on chronic effects of, 3:4 Surface water DDT, effects on bird abundance and reproduction, 3:513–526 Surface water pollution, 3:373–375, 444–451 effects on drinking water, 3:445 in India, 3:445–451 sources of, 3:374–375, 444–445, 657 treatment of, 3:445 Surface water quality impact of soil phosphorus on, 3:701–706 soil nitrogen management and, 3:694–701 tile drains and, 3:729–730 Surface water resources Ganga Basin, 3:233 Great Lakes, 3:177 of India, 2:561–562

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CUMULATIVE INDEX

Surface water runoff, 2:516 from construction sites, 1:538 in the vadose zone, 5:534 Surface water sources, high control of, 2:399–400 Surface Water Supply Index (SWSI), 4:212–213 Surface water tracers, dyes as, 3:96 Surface Water Treatment Rule (SWTR), 1:70, 175, 196, 197, 244, 457; 2:140, 195 Surface water treatment rule compliance technologies for disinfection, 1:461t for filtration, 1:462t Surface water use, in arid lands, 2:476 Surfactants, 1:670–671; 5:377 analysis of, 1:671 biodegradation of, 1:672 water-soluble, 1:111 Surficial aquifers, characteristics of, 5:80 Surges, 1:202 Surge tanks, 1:262 Surging breakers, 4:137 Surveys electromagnetic, 5:680 gravimeter, 5:148 high-resolution sea floor, 4:77–78 reservoir, 3:411 riverine electromagnetic and seismic, 5:679–680 single channel seismic reflection, 5:680–681 snow, 4:337–338 soil vapor, 5:548, 549 Survey sampling, 2:161 Susceptibility assessment, 1:527 Suspended growth biological treatment systems, 1:703 Suspended growth processes, 1:827 Suspended particles, chemical precipitation of, 4:588 Suspended sediment, 2:547 concentration of, 2:547 discharge, 2:547 in urban stormwater runoff, 3:435 vertical, lateral and temporal distribution of, 3:397–400 Suspended sediment load, 3:398–400, 418 Suspended sediment samplers, types of, 3:398–400

Suspended solids, 1:901; 2:547; 4:587–589; 5:421 removal of, 1:54 Sustainability concepts related to, 2:625–627 defined, 2:633 imperatives and preconditions related to, 2:626t of irrigated agriculture, 3:584–585 in the Nile Basin Initiative, 2:592 practices in, 2:628–629 thermodynamic aspects of, 2:626 water resource, 2:624–630 Sustainable development, 1:651; 2:624 precautionary principle regarding, 2:601 of water resources, 5:163 Sustainable flood-management decision making, 2:678–679 Sustainable management. See also Sustainable water management; Water resource sustainability of ecosystems, 2:636–637 of fisheries, 2:635–636 of freshwater resources, 2:634–635 of natural resources, 2:633–638 ‘‘Sustainable urban drainage systems’’ (SUDS), 1:54 Sustainable wastewater management, in developing countries, 1:721 Sustainable water management. See also MEDIS project on Mediterranean islands, 2:638–643 practices in, 2:639–641 Sustainable water supply, elements in, 1:653–654t SUSTAINIS advanced study course, 2:641–642 Su Sung water clock tower, 4:704 Swamps, 4:690 freshwater and deepwater, 3:172 SWAP model, 3:680 Sweep coagulation, 4:425 Sweep-floc coagulation, 1:138 Swirl settlers (hydroclones), 1:683 Swirl/vortex technologies, 1:784 Switching tensiometer, 3:725–726 SWMM model, 5:298 SWRRB model, 5:298 Symbolism, water, 4:785–788 Symmetrical moving average (SMA) scheme, 3:219, 426

825

Symmetry boundary, 5:419 SYMTOX4 (Simplified Method Program–Variable Complexity Stream Toxics Model) software, 2:327 Synoptic meteorologists, 4:328 Synthetic chelates, role in lead phytoremediation, 5:383–385 Synthetic dilution water, 2:383 Synthetic organic chemicals/compounds (SOCs), 1:248, 350; 2:268; 5:250 elimination using ozone, 1:355 technologies for, 1:464t Synthetic polymers as coagulants, 4:426 in foulants, 1:417 Syntrophism/syntrophy in landfills, 1:696 microorganisms and, 3:312 Syracuse, extraterritorial land use control in, 1:317 Syria-Israel water conflict, 4:754 Syrup-pan flow system, 3:165 System Control and Data Acquisition (SCADA), 1:449–452. See also SCADA systems buying, 1:451 components and terminology, 1:451 security and, 1:451 small water systems and, 1:450 water operations enhancement with, 1:450 System hydraulic performance, biofouling effects on, 5:37 System performance evaluation, fuzzy criteria for, 2:674–678 System problems, from corrosion, 1:152 System response data uncertainty, 3:326 Systems analysis, 2:683–687 techniques, 3:384 Systems approach, 2:685–686 Systems engineering, for reservoir management, 3:386–387

Talbot, William Henry Fox, 4:766 Tamankaduwa, hydrography of, 4:778f Tampa Bay water program, 1:309 Tank data, 5:164 Tank recharge (Rt ), 5:167

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CUMULATIVE INDEX

Tanks diffused air aeration system, 1:629–630 settling, 1:452–457 water distribution system, 1:208 Tanzania, ‘‘privatization by default’’ in, 2:632–633 Tapered aeration, 1:815 Tapproge system, 1:542 Tara Mines treatment wetlands, 1:898 success of, 1:899–900 ‘‘Target concentration,’’ 2:357 Tariffs, water delivery, 2:473 Tasmanian Wilderness World Heritage Area (TWWHA), 4:788–789 Taste, of water, 1:902 Taste control, using ozone, 1:355 Taxa richness, 3:37 Taylor–Galerkin time-stepping technique, 5:659 Taylor–Hood modeling scheme, 5:658 Taylor’s series expansion, 4:365 TCA, 2:317, 318t Tech Briefs, 1:151–152, 158 for drinking water treatment, 1:177, 207 Technetium (Tc) chemistry of, 4:579–580 regulatory standards for, 4:580–581 remediation of, 4:581 in water, 4:578–583 Technetium-99, 4:578–579 Technical Cooperation Committee for the Promotion of the Development and Environmental Protection of the Nile Basin (TECCONILE), 2:592 Technical treatment system, 1:842 Technocracy, irrigation before, 4:740 Technologies applying to developing countries, 1:718–719 desalination, 1:170 high-throughput, 2:59–62 for inorganic contaminants, 1:463 new, 1:509 public–private partnerships and, 1:47 for radionuclides, 1:465t role in water markets, 2:568–569 solidification/stabilization, 1:836

for synthetic organic compounds, 1:464t telemetry, 1:147 for volatile organic contaminants, 1:464t wastewater treatment, 1:808–814 water reclamation, 1:806–807 Technology-based effluent limitations (TBELs), 4:656–657 variances from, 4:657 Technology development, Marine Instrumentation Laboratory, 4:70–73 Technology standards, 1:381 Technology transfer, 1:719 Tectonic lakes, 3:265 Tectonic plate movement, in the Caspian basin, 2:482 Telemetry, 1:202 data, 3:316 technologies, 1:147 Televising, pipeline, 1:884–885 Tempe pressure cells, 5:462 Temperature. See also Thermal entries bromate ion formation and, 1:360 chlorine sensitivity and, 2:404–405 of domestic sewage, 1:830 effect on corrosion, 1:8 effect on microorganisms, 1:522 effect on nitrification, 1:753 in groundwater tracing, 5:504 hydrocarbon degradation and, 5:320–321 influence on nitrification, 3:642 logs, 5:155 microbial growth and, 3:311 microbial regrowth and, 1:344 organism growth and, 1:605–606 of pond water, 3:486 profiling, 5:411 role in fish growth and production, 3:130 in shallow stagnant waters, 3:375–378 time-vertical distribution of, 3:377 Temperate climatic zone, 4:258 Temperature effect, 5:230 inorganic ion removal and, 4:492–493 Temperature fluctuation, of tidal streams, 4:129–130 Temperature of crystallization, 4:585 Temperature statistics, Chicago Station, 5:79t

Temperature stratification, in open waterbodies, 3:190 Temperature variability, interannual, 4:175 Temporal discretization, 5:658–659 Temporal fluctuations, 3:310 Temporal grid spacing, 3:258 Temporal resolution, 4:319–320 Temporary water hardness, 4:453 10-d survival and growth assay, 3:51–52 Tennessee Valley Authority (TVA), 4:613 Tensiometer readings, interpreting, 3:726t Tensiometers (TE), 2:341; 5:180, 533, 540 with electronic reader, 3:725–726 installing, servicing, and troubleshooting, 3:727–728 limitations of, 3:728–729 preparing for field use, 3:727 vacuum gauge, 3:724–729 working principle of, 3:726–727 Tensiometric soil moisture measurement, 4:488 Tension disk infiltrometers, 5:215 Tension-free lysimeter, 2:340 Tension infiltrometers, 4:487; 5:539 Tensionless column lysimeters, 5:488 Tension lysimeters, 2:341 installation and sampling procedures for, 5:490 Tension-saturated zone, 5:354–355 Terminal electron acceptor (TEA), 5:319–320, 528, 580, 581 Tentatively identified compounds (TICs), 2:308 Ten Thousand Islands estuary, 3:72 Terminal electron-accepting processes (TEAPs), 2:469; 5:585 Terminal electron acceptor (TEA), 1:640 Terminal restriction fragment length polymorphism (tRFLP), community profiling using, 1:643 Ternary complexes, 2:208 Ternary effluent tests, 1:775–777 Terraces, soil-conservation, 3:550 Terrestrial bacteria, luminescent marking of, 2:453–454 Terrestrial cadmium, 5:615 Terrestrial nonpoint source pollutants, 3:282

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CUMULATIVE INDEX

Terrestrial organisms, toxicity of lead to, 2:434 Terrestrial point source pollutants, 3:281–282 Terrorism point-of-use/point-of-entry systems and, 1:381 valves and, 1:484–485 water security and, 1:158 Terrorist threats, against wastewater utilities, 1:870–871 Tertiary wastewater treatment, 1:827; 2:547 Test development, for regulatory purposes, 2:458–464 Testing of aquifers, 5:182–183 of meters, 1:340 of pipelines, 1:888 for point repairs, 1:889 raw water, 1:440 of repaired pipe, 1:890 waterborne radon, 1:51 water meter, 1:491–492 Test kits, commercial, 2:384 Test organisms, ciliated protists as, 2:413–418 Test ruggedness, 2:459 Test systems, for sediment toxicity assessment, 2:384–385 Test validation, 2:459–460 Tetrachlorodibenzo-p-dioxin (TCDD), 2:108–109 Tetrachloroethene (PCE), 5:581 Tetrachloroethylene. See Perchloroethylene (PCE) Tetrahymena, in laboratory research, 2:413 Tetrahymena pyriformis, as a test organism, 2:413, 414 Tetrahymena termophila, in toxicity assessment, 2:413 TETRATOX test, 2:414 Texas vulnerability assessment case study, 5:565 Thales’ water theory, 4:708–709 Thallium (Tl), maximum contaminant level of, 2:235t The Groundwater Foundation (TGF), 2:518, 519; 4:713 Theis equation, in aquifer test data analysis, 5:183 The Nature Conservancy, Arizona Chapter (TNCA), 3:57, 58 Thermal carbon activation, 1:94–95

Thermal conductivity, 5:173 Thermal conductivity detectors, 2:308 Thermal cycles, fish production and, 3:134 Thermal desalination, 1:170 Thermal diffusivity, 5:173 Thermal drying of biosolids, 1:649 of sludge, 1:865–866 Thermal infrared (TIR) domain, 3:720 Thermal in situ groundwater treatment, 5:440 Thermalization process, 3:692 Thermal kinetic window (TKW), 3:719, 721 Thermal oxidation systems, for odor removal, 1:915 Thermal pollution, 2:547 as a water quality indicator, 2:266 Thermal power generation, water use for, 2:662 Thermal processing, of sludge, 1:858–860 Thermal properties, of water, 4:583–584 Thermal regeneration, 1:918 Thermal theory of cyclones, 4:353 Thermal velocity–groundwater velocity ratio, 5:173 Thermal wastewater treatment technologies, 1:812–813 ‘‘Thermochemical cycle,’’ 4:477 Thermodynamics effect on adsorption, 3:301–303 entropy in, 4:218 laws of, 5:170 Thermoelectric power water use, 2:547 in the United States, 2:653 Thermoelectric water use, 1:560–561 Thermometer, first, 4:711–712 Thermophysical characteristics, of sludge, 1:863 Thermosiphon solar water heaters, 1:65 Thessaloniki Industrial Area, wastewater values from, 1:569t θ time-stepping method, 5:659 THF hydrate, 4:473 Thickening, of sludge, 1:854, 864 Thiem method, Ernst’s modification of, 5:495 Thiem’s equilibrium equation, 5:493

827

Thiobacillus ferrooxidans, 2:149, 150; 3:14 Thiol-containing peptides, roles of, 3:609–615 Thirst, pain and, 4:724–725 Thixotropic fluids, 5:557 THM formation potential (THMFP), 2:117. See also Trihalomethanes (THMs) THM precursor removal, 2:116–117 Thornthwaite potential, 4:260 Thornthwaites index, 3:32 Thornthwaite water balance diagrams, 4:262 Threat agents, 1:87–92 monitoring water for, 1:89–91 nature of, 1:87–88 rapid detection of, 1:91 survival in water, 1:88 water-supply, 1:88 Threat contaminant (TC), 2:348 Threats, to water resources, 1:438 Three-component base flow separation, 3:26 Three-dimensional numerical models, 3:322 3-Dimensional voltage distribution, 4:443 ‘‘Three measures on river treatment (flood management),’’ 3:47–48 Threshold bromide ion concentration, 1:359 Threshold dose, 4:674 Threshold effects level (TEL), 3:351 Threshold limit value (TLV), 4:555, 561 Threshold odor number (TON), 1:355, 760 Threshold treatment, for scale control, 1:548 Thrombotic thrombocytopenic purpura (TTP), 2:137 Throughfall, precipitation, 3:171 Throughflow, 3:453–454 Throughput bed volume (BV), 1:103 Throughput volume (Vt ), 1:103 Thu Duc Water Station, Ho Chi Minh City, 2:553 Thunder Bay National Marine Sanctuary and Underwater Preserve, 4:64 Thunderstorms, 4:362 role in flooding, 3:145 Tidal currents, 4:24 Tidal efficiency, 5:497–498

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828

CUMULATIVE INDEX

Tidal energy, 4:46–47 Tidal stream variability physical and chemical, 4:128–133 seasonal, 4:130–132 short-term, 4:128–130 Tidal wetlands, 3:72 Tides, 4:24 as a forcing factor, 3:322 Tiered testing, 2:430, 460, 461f Tigris–Euphrates River Basin, 4:754–755 Tigris–Euphrates waters, conflicts over, 4:755 Tijuana River waters, allocating, 4:645 Tile drainage, 3:729–731, 742 impacts of, 3:731–732 pollutant management and, 3:730 Tillage traditional, 3:650 wind erosion and, 3:552 Timber Culture Act of 1873, 2:512 Timber harvesting, managing, 2:187 Time-area curve (TAC), 3:62 Time-area (TA) diagram, 3:62 dimensionless cumulative, 3:64 Time-area histogram (TAH), 3:60–62, 64, 65 constructing, 3:61–63 total hydrograph derived from, 3:62t Time-dependent fluids, 5:557–558 Time-dependent models, 2:272 Time-dependent partial differential equations, 5:517–518 ‘‘Time-discharge’’ histogram (TDH), 3:65 Time-domain electromagnetic induction, 5:150 Time-domain reflectometry (TDR), 3:676; 4:488; 5:533, 540–541 devices using, 5:461 Time-dynamic speciation, body concentrations and, 2:215–219 Time immemorial water rights, 4:690 Time-independent fluids, 5:556–557 Time of concentration (Tc ), 3:61 methods and formulas for computing, 3:470–471 for a series of planes, 3:243 in watersheds, 3:469–472 Time of travel, in a channel, 3:244–245

Time-resolved laser fluorescence spectroscopy (TRLFS), 2:207–208 Time series analysis, 3:422, 423; 4:339 Time-variable isochrone method, 3:64–65 Time-varying exposure concentrations, 2:213–215 Tissue. See also Sculpin tissue metals in, 3:361t organochlorine compounds in, 3:352, 360t, 362f trace elements detected in, 3:362 Tissue analysis, for trace metal concentration, 2:65 Tissue quality guidelines (TQGs), 2:428 Tissue quality values (TQVs), 2:351 Title IV. See Acid Deposition Control Program (Title IV) TMDL plan, 2:188. See also Total maximum daily load (TMDL) Tobago, megawatersheds exploration in, 5:269–270 Toe drain, pervious, 3:290 Toe trenches, pervious, 3:289 Toilet dam, 2:665 Toilet flushing, water quality criteria for, 1:17t Toilet leaks, 2:664–665 Toilet retrofits, 2:665 Toilets, water-free, 1:678–679 Tolerance measure, 3:37 Tomatoes, genetically engineered, 3:686 Tool development, for ecotoxicogenomic research and biomonitoring, 2:62–63. See also Software tools Tooth decay, 1:254–255. See also Fluoridation Topogenic areas, 1:404 Topographic impacts, of waterlogging, 3:741–742 Topography regional flow systems and, 5:420 role in flooding, 3:143 Topologically distinct channel networks (TDCN), 3:32 Tordon 75D investigation, 2:280 Tornadic waterspouts, 4:347 Tort claims, contamination-related, 3:169

Tory Lake, biomanipulation trials in, 2:57t Total ammonia nitrogen (TAN), 3:131 Total available chlorine (TAC), 1:128 Total chlorine residual, 2:399 Total Coliform Rule, 2:140 compliance technology for, 1:463t Total dissolved inorganic carbon (TDIC), 5:224 Total dissolved solids (TDS), 1:538, 810, 812, 902; 2:157; 5:281 effect on corrosion, 1:8 electric conductivity and, 4:432 in freshwater, 4:449 in groundwater, 2:394 salinity and, 5:207 Total load, 3:418–419 Total Maximum Daily Loads (TMDLs), 1:305, 759, 801; 2:21, 185, 188, 233; 4:596–597, 598, 671 cost-effectiveness analysis for, 2:131 of impaired waters, 2:476 implementation of, 4:599–600 programs, 2:127, 128, 188–189 Total maximum daily load program, 4:663–664 Total oil and grease analysis, 2:311 Total organic carbon (TOC), 2:40 in urban stormwater runoff, 3:435 Total petroleum hydrocarbon (TPH) oil and grease, 2:311 Total phenolics analysis, 2:309–310 Total residual chlorine/total residual oxidant (TRC/TRO), 1:128 Total suspended solids (TSS), 1:455, 538, 599, 683, 739, 830 along the Blackstone River, 2:258 Total water hardness, 4:453 ‘‘Total Water Management,’’ 2:587 TOXcontrol-BioMonitor, 2:174 Toxic agents/chemicals/substances, 2:29 in drinking water, 2:371–372 lux genes for determining, 2:174 precautionary principle regarding, 2:600 Toxic algae, 3:108 Toxicant detection, luminescent bacterial biosensors for, 2:453–458 Toxicant exposure, forms of, 3:117

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CUMULATIVE INDEX

Toxicants defined, 2:170 in sediment, 2:426 Toxicant-specific luminescent biosensors, 2:455t Toxic chemicals, in sediment, 3:508 Toxic constituent manuals (EPA), 2:381 Toxic cyanobacteria, ecology of, 2:388 Toxic elements, in biodegradation processes, 5:321 Toxicity. See also Aquatic toxicity arsenic, 1:1–2; 2:15 bacterial bioluminescence and, 2:47 chlorine, 2:402 of detergents, 1:672 of industrial effluents, 1:565–571 nitrate, 4:519 numbers associated with, 2:47 persistence of, 2:381 predicting, 2:415 uranium, 5:641 Toxicity assays, of SPMD dialysates, 2:171. See also Toxicity assessment; Toxicity bioassays; Toxicity testing; Toxicological assays Toxicity assessment, 4:602. See also Toxicity testing ciliated protists in, 2:413–418 direct, 2:46–47 of industrial effluents, 1:566–568 of industrial wastewaters, 1:566 new approaches in, 2:414–415 quantitative structure–activity relationships in, 2:415 use of semipermeable membrane devices for, 5:672–677 Toxicity-based effluent limitations, 4:657 Toxicity/bioaccumulation testing, 4:600 Toxicity bioassays, 2:453. See also Toxicity assays Toxicity biomarkers, 2:29, 31 Toxicity Characteristic Leaching Procedure (TCLP), 1:853 Toxicity consents, 2:46 Toxicity controls, whole effluent, 2:382–383 Toxicity identification and evaluations (TIEs), 2:380–382, 383,411; 4:602

‘‘Toxicity reduction evaluation’’ (TRE), 2:381 Toxicity testing. See also Sediment toxicity testing; Toxicity assays; Toxicity assessment bioluminescent biosensors for, 2:45–50 environmental quality standards and, 2:46 legislative drivers for, 2:45–46 of sediment, 2:351, 383–387 trends in, 3:116 use of fish species in, 3:116 variations in, 3:117 Toxic metal biosorption, 2:68–74 mechanisms of, 2:70–71 Toxic metal ions, bonding of, 1:586–591 Toxic metals, persistence in the water environment, 2:233 Toxicogenomic experiments, 2:62–63 Toxicological assays, problems with, 2:415. See also Toxicity assays; Toxicological evaluation Toxicological database, 2:409 Toxicological evaluation, using fish cells in, 3:115–118. See also Toxicological assays Toxicological methods, 2:278 Toxicological testing. See Marine toxicological testing; Toxicity testing; Toxicological assays Toxicology, of disinfectants, 1:195 Toxic pollutants, 4:670 in Indian rivers, 3:449 pursuant to Clean Water Act, 4:596t Toxic Release Inventory (TRI), 1:799; 5:381 Toxic sediments, transport of, 3:15–16 Toxic Substances Control Act, 1:531 Toxic Substances Hydrology Program study, 5:605–608 Toxin-producing blue-green algae, 3:189 Toxins algal, 2:387–392 in blue-green algae blooms, 3:189 Toxoplasma, 1:279 Toxoplasmosis, 1:182 ToxScreen test, 2:173–174 Trace element contamination, in groundwater, 2:143–148 Trace element pollution, 4:109–113

829

Trace elements, 3:454–458 abundance, distribution, and behavior of, 4:110–111 in aquatic biota, 3:456–457 effects of geology on, 3:457 effects of human activity on, 3:457–458 in Puget Sound Basin sediment and fish, 3:349–362 in River Yamuna groundwater, 2:396 in sediments, 3:455–456 sources of, 4:111 in streambed sediment and whole sculpin tissue, 3:362 toxic effects of, 4:111 in water, 3:455 Trace gases atmospherically active, 4:85t fluxes of, 4:149 Trace metal biomonitors, macrophytes as, 2:64–68 Trace metal pollution in the aquatic environment, 2:64–65 metallothioneins as indicators of, 2:406 Trace metals, sorption onto activated carbon, 2:83–85 Trace metal speciation, 2:202–205 chemical reactions affecting, 2:203–204 measurement of, 2:204 modeling, 2:204 Trace substances, health implications of, 1:289 Tradable permits system, 2:133–134 Tradable rights issues related to, 2:643–644 market allocation of water and, 2:644 meeting water needs with, 2:643–645 security of tenure and, 2:644–645 ‘‘Tragedy of the Commons, The,’’ 2:556,580,625 Transaction costs, water market, 2:499–500 Transboundary diagnostic analysis (TDA), 4:643 Transboundary water conflicts, Nile Basin, 2:590–594 Transboundary waters in Central America, 4:641–642 in Latin America, 4:636–643

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830

CUMULATIVE INDEX

Transboundary waters (continued) managing, 4:643 Mexico–U.S., 4:636–641 in South America, 4:642–643 Transboundary water treaties, in the Americas, 4:637–641t Transcription factor overexpression, in selenium phytoremediation, 5:400 Transect groundwater monitoring network, 5:314–315 Transfer functions, 4:93 Transfer of development rights (TDR) programs, 3:596, 597 Transfer rules, 2:501 Transient analysis, of rapid flow changes, 1:213 Transinformation, 4:219 Transitional subunit groundwater monitoring network, 5:315 Translocation factor (TF), 3:35 Transmembrane pressure (TMP) pulsing, 1:594–595 Transmissibility, ground water, 2:547 Transmission electron microscopy (TEM), 2:310 Transmissive media systems, biofilms in, 5:36 Transmissivity (T), 5:507 of an aquifer, 5:492 groundwater, 5:129 Transpiration, 2:547; 3:718, 732–741; 4:192, 345–347, 434 controls on, 3:733–735 effects of, 4:346 effects on contaminant movement, 5:378–379 estimates of, 3:738–739 factors affecting, 4:345 fast versus delayed, 3:237 leaf level, 3:735 measuring, 3:737–740; 4:346–347 modeling, 3:736–740 quantification methods for, 3:733, 735–737 soil characteristics and, 3:735 stand level, 3:736 tree level, 3:735–736 vegetation characteristics and, 3:734–735 in the water cycle, 4:196 Transpiration rate (Tr), 4:345 Transport of cadmium, 5:617

of contaminant vapors, 5:550 from groundwater to human stomachs, 5:449–450 of lead, 5:647 of mercury, 5:644 of MtBE, 5:318 of nitrate, 5:629 particulate, 5:349–352 of perchlorate, 5:632 of uranium, 5:640 through the vadose zone, 5:77–80 of vinyl chloride, 5:635 Transport equations, one-dimensional, 5:525–526 Transport mechanisms, 1:246; 3:181 fish as, 3:283–284 Transport modeling, basic concepts in, 5:31–33 Transport phenomena, of dissolved matter, 2:105 Transport simulation programs, 5:34t Transversal flow membrane (TFM) modules, 1:593 Transverse dispersion, 5:46–47, 273 Transverse scour pools, 3:68 Trash, in urban stormwater runoff, 3:435 Trash-Trap system, 1:785 Travel cost method, 4:609–610 Travel cost models, 2:130 Travel time(s) variation in, 3:64 in watersheds, 3:469–472 Travel time (Tw ) formula, 3:63 Travel-time map, cumulative, 3:65 Tray aerator, 1:313 Treated effluent, characteristics of, 1:819 Treated water contaminants in, 5:421 reinjection of, 5:421–423 Treaties, transboundary water, 4:637–641t Treatment effect on assimilable organic carbon and biodegradable dissolved organic carbon, 2:225 dilution equivalent to, 4:104 effect on speciation, 2:75–78 loss of, 2:48 as a remediation strategy, 2:358 Treatment practices, for wastewater reuse, 3:670. See also Treatment technique entries

Treatment processes domestic sewage, 1:832–834 fate of POPs throughout, 1:769 Treatment systems. See also Integrated treatment systems alternative, 1:678, 679–680 stressed, 2:663 Treatment technique (TT), 1:477–479 Treatment techniques/technologies. See also Treatment practices; Treatment technique (TT) developing, 1:425–428 for hydrocarbons, 1:575–581 for small drinking water systems, 1:457–466 Treatment Work Construction Grants, 4:664 Treaty of Guadalupe Hidalgo, 4:643–644 Tree crops, microirrigated, 3:625 Tree level transpiration, 3:735–736 Trees, transpiration of, 5:85 Trenches, alkaline recharge, 5:2 Trenchless repair and rehabilitation techniques, 1:876–883 manhole renovation using, 1:882–883 pipeline renovation using, 1:876–882 Trench pools, 3:67–68 Trench shoring, 1:402 Trending heterogeneity, 5:509 Trend stations, 2:178 Triarylmethane dyes, QSAR case study using, 3:99 Tribal reserved rights, 4:689–690 Tribromoacetic acid, health effects of, 1:267 Tributary, 2:547 Trichloroacetaldehyde monohydrate, health effects of, 1:269 Trichloroacetic acid, health effects of, 1:267 Trichloroacetonitrile, health effects of, 1:268 Trichloroethene (TCE), 5:581 cometabolism of, 5:584 Trichloroethylene (TCE), 2:317 aerobic degradation of, 5:43 biotransformation of, 1:691 Fenton’s Reaction and, 4:446–447 removal of, 3:368 2,4,6-Trichlorophenol (TCP) adsorption, 1:116

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CUMULATIVE INDEX

Trickling filters, 1:833 advantages and disadvantages of, 2:155 for iron removal, 2:154–155 Trihalomethane formation potential (THMFP), 1:139. See also THM formation potential (THMFP) Trihalomethanes (THMs), 1:129, 313; 2:91–92, 115, 116, 268. See also THM entries bromide influence on formation of, 2:74–79 brominated, 2:74–75 health effects of, 1:264 precursors of, 1:432 Trimethylbenzene (TMB), 5:587 Trinidad, megawatersheds exploration in, 5:269–270 Trinitrotoluene (TNT) plumes, 5:77 Triolein-containing SPMDs, 5:672 Tritium, 5:231 anthropogenic, 5:69–70 concentration of, 5:70 groundwater dating with, 5:65–69, 69–72 in groundwater tracing, 5:503 measurement methods for, 5:68 in precipitation, 5:67f production and decay behavior of, 5:65–66 Tritium/helium ratios, dating young groundwater using, 5:71–72. See also H–He dating Tritium units (TU), 5:66 Trondheim Biomonitoring System (TBS), 2:28, 30–33 ‘‘Trophic-dynamic system,’’ 3:269 Trophic levels, disaggregation of, 4:151–152 Trophic state, of lakes, 3:267–268 Trophic state classification, 4:66 Trophic upsurge, 3:206–207 Tropical cyclone activity, 4:176 Tropical cyclones, role in flooding, 3:144–145 Tropical lakes, 3:270 Tropical Ocean–Global Atmosphere (TOGA), 4:22 Tropical Rainfall Measuring Mission (TRMM), 4:305, 309, 312 Tropical reservoirs, studies of, 3:181 Tropospheric lapse rate, 4:370 Trout, innovative hatching program for, 3:458–460 Trout farms, in Poland, 4:722

‘‘Tsunameters,’’ 4:90 Tsunami Hazard Mitigation Program, 4:89–90 Tsunamis, 4:160–163 research on, 4:162 Tsunami simulations, 4:162 Tsunami Warning System, 4:160–161, 162 Tuberculation, 1:400 Tuberculosis (TB), 1:182 Tube-type clarifier package plants, 1:515 Tube well, 3:594 Tubewell drainage, 3:732; 5:98 Tucson, Arizona, overdraft in, 5:341–342 Tucson Basin, perched groundwater in, 5:353 Tumen River Economic Development Area Project (TREDA), 2:444 Tumorigenicity, of arsenic, 2:8 Turbidity, 1:485, 599, 901 defined, 2:547 inorganic, 3:108 lake, 3:278–279 measurements of, 2:344 removal of, 1:250 of urban stormwater runoff, 3:435 Turbidity tube, 1:599 Turbine design, 3:199 Turbine meters, 1:338, 340 Turbine pumps, deep-well, 3:664–667 Turbine spillways, degassing fluxes at, 3:206 Turbulence in estuaries and bays, 4:25–26 interaction with propagation, 4:296 thermal and mechanical, 4:1–2 Turbulent channel units, 3:70 Turbulent Eddy Profiler, 4:296 Turbulent vertical convection, 4:367 Turf areas, practical, 3:750 Turfgrass, 3:706, 707 benefits of, 3:750–751 reducing irrigation of, 3:751 selecting, 3:751–752 sod, 3:557 xeriscape principles, 3:751 Turf watering, 3:556 Turkish South East Anatolia Project (GAP), 4:754–755 Turnover number (TON), 1:791 Two-dimensional numerical models, 3:322

831

2DLEAF model, 3:716 Two-electrode measurement technique, 4:432 Two-moment information theory, 4:476 Type II diabetes, dehydration and, 4:725–726 Typhoid fever, 2:337 Typhoid rates, 1:286t Typhoons, 4:194 Typhoon wave, 4:139

U.K. National Rivers Authority, water supply categories used by, 2:614, 615t. See also British entries Ultrafast vibrational energy, 4:513 Ultrafiltration (UF), 1:333t, 334–335, 336t, 459, 488, 707, 810, 817, 828, 916–922. See also Polymer-assisted ultrafiltration (PAUF) history of, 1:916–917 pore sizes for, 2:101–102 Ultrafiltration methods, 4:29 Ultrafiltration tests, 1:919–920 Ultrahigh purity (UHP) nitrogen, 4:421 Ultra-low-volume (ULV) toilets, 2:665 Ultramicropores, 1:97 Ultrasonic irradiation, 1:875 Ultrasonic meters, 1:338 Ultrasound, 4:571 Ultraviolet (UV) radiation, 1:199, 458; 2:119, 244, 374. See also UV entries at CSO facilities, 1:786 technology of, 1:471–472 water disinfection using, 1:471–476 Ultraviolet disinfection, 1:165–169, 380, 466–468, 523, 604–605, 817, 834. See also Ultraviolet irradiation advantages and limitations of, 1:466–467, 472 domestic sewage, 1:834 experiments in, 1:167, 168 monitoring and operation requirements for, 1:468 process of, 1:467–468

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832

CUMULATIVE INDEX

Ultraviolet irradiation, 1:469–470. See also Ultraviolet (UV) radiation Unaccounted-for water (UFW), calculating, 1:318 Unaccounted for water indicator, 2:492, 496 Uncertainty, 2:599 in hydrologic data, 2:621 participatory multicriteria decision-making under, 2:681 in pesticide assessments, 5:358–359 in pesticide vulnerability assessment, 5:598 in rainfall–runoff modeling, 4:297–303 sources of, 2:674–675; 3:325–326 types of, 2:680 Uncertainty analysis, 3:117 approaches to, 3:326 in watershed modeling, 3:325–327 Unconfined aquifer flows, 5:492–493 Unconfined aquifers, 5:11, 88, 145, 483, 497 artificial recharge of, 5:11–17 barometric efficiency of, 4:168 drawdown in, 5:103–104 storage in, 5:515–516 storativity in, 5:129–130 water flow in, 5:662–663 Unconfined groundwater, 5:662–667 case study of, 5:665 Underground injection control (UIC), 4:679–680 Underground pipeline, 1:883–891 assessment of, 1:884–887 repair and renewal of, 1:887–891 Underground water storage, 3:164 Undersea ‘‘windmills,’’ 4:24 Underwater acoustical monitoring, 4:91–92. See also Underwater sound detection Underwater light, availability of, 3:276 Underwater sound detection, 4:570–571. See also Underwater acoustical monitoring Underwater volcanoes, 4:90 Underwater weapon tests, as water pollution, 4:102–103 Undeveloped areas, impact on groundwater quality, 5:250 Ungauged watersheds, modeling, 3:342–345

Uniform fluid flows, 3:194 ‘‘Uniform numeric limitations,’’ 1:755–756 Unilateralism, in water management, 3:19 Un-ionized ammonia concentrations, 3:131 United Nations, public trust guidelines of, 2:609 United Nations Framework Convention on Climate Change (UNFCCC), 3:208 United Nations Industrial Development Organization (UNIDO), planning analysis objectives, 2:683 United Nations World Water Development Report, 2:548, 549 United Soil Classification System (USCS), 3:689–690 calculation, 3:61t United States. See also Federal entries; U.S. entries; Western United States acid mine drainage in, 3:10–11; 5:1–9 ambient standards for waters of, 1:755 aquatic environment clean up by, 2:184 classification of wetlands and deepwater habitats in, 3:496–498 disinfectant use in, 1:195 distribution of pharmaceuticals in, 1:373 drinking water quality in, 2:373 evolution of water use in, 2:646t flood damages in, 3:146 groundwater contamination from municipal landfills in, 5:253–258 history of Water Pollution Control Act in, 4:651–655 irrigation in, 3:586–594 Lake Baikal studies by, 3:21 new water sources in, 2:649–650 1990 industrial water use in, 1:620–622 nitrate concentrations in, 1:31–32 nitrate data for, 1:32t percentage of precipitation in, 4:226 pesticide use in, 3:655

selenium containment strategy in, 2:358 source-water protection in, 2:312–313 total water withdrawals in, 2:646t water consumption patterns in, 2:651 water markets in, 2:500 water quality management in, 2:193–198 water quality policy in, 2:127–128 water quality standards in, 1:476–481; 2:268 water saving measures in, 2:649 water use in, 1:805; 2:645–650, 650–653 wetlands in, 3:493; 4:690–694 United States Environmental Protection Agency (USEPA), 1:33, 145, 287, 531–533. See also Environmental Protection Agency (EPA); USEPA entries drinking water standards, 1:183–184 fish advisories, 3:119 maximum contaminant levels, 2:233 water quality standards, 2:373 water reuse guidelines, 2:611 United States–Mexico border waters, 4:636–641 binational agreements related to, 4:645–646 current developments regarding, 4:646 treaties and conventions regarding, 4:643–645 United States Weather Bureau, 4:347–348 Unit flood response approach, 3:156–157 Unit hydrograph (UH), 3:221–222 dimensions of, 4:356 Unit hydrograph models, 4:357–359 Unit hydrograph theory, 4:355–360 limitations of, 4:356 mathematical representation in, 4:356–357 Univariate spectral analysis, 4:339 Universal metering, 1:494 Universal soil loss equation (USLE), 2:535 Universities, land-grant, 3:597–598 Unloading fractures, 5:177

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CUMULATIVE INDEX

Unplanned water recycling, 2:610 Unrecognized organic chemicals, in urban stormwater runoff, 3:435 Unrecognized pollutants, 3:371–373 Unregulated Contaminant Monitoring Rule/ Regulations (UCMR), 2:345; 4:678 Unsaturated hydraulic conductivity, 5:126, 471–472 Unsaturated soil properties, modeling, 5:538 Unsaturated zone, 2:548; 5:600 vapor transport in, 5:543–548 water in, 5:531–533 Unsteady-state flows, 5:491 Unsteady-state software tools, 2:327–328 Unsteady-state subsurface drainage theory, 5:96 Unsteady-state uniform flow, 3:251 Unsustainable water supply systems, 1:505 Upflow anaerobic sludge bed (UASB), 1:906 Upflow anaerobic sludge bed reactor, 1:518, 519, 618f Upflow filtration, 2:366 Upflow roughing filters, 1:237, 239, 240–241 Upland-‘‘confined’’ dredged sediment disposal, 2:124–125 Upper Mississippi River Source Water Protection Initiative, 2:312 Upward contaminant vapor flux, 5:553 Upward vapor migration, from groundwater devolatilization, 5:553 Upwelling, 4:24–25 Uranine, 3:96 in groundwater tracing, 5:505–506 Uranium (U), 4:542 fate and transport of, 5:640 in groundwater, 5:640–642 health risks of, 1:395–396; 5:641 processing of, 5:640–641 remediation of, 5:641–642 uses of, 5:641 Uranium series isotopes, 5:232 Urban creeks, 3:432 water quality in, 3:433 Urban Drainage and Sewer Master Plan, Ho Chi Minh City, 2:553

Urban drainage models, 3:337–338 calibration and verification of, 3:338 future of, 3:341 real-time hydrologic information and, 1:125 Urban drainage systems, modeling real-time control and active real-time control of, 3:340–341 Urban flooding, 3:159–163 causes of, 3:160 cities that experience, 3:339–340 extent of, 3:160–161 future perspectives and challenges related to, 3:162 impact on society, 3:161 modeling, 3:161–162, 339–340 understanding and reducing, 3:161–162 Urbanization effects of, 3:430 influence on the hydrologic cycle, 4:281–282 pollution due to, 2:181 Urban landscape, water quality management in, 2:189–193 Urban land use, impact on groundwater quality, 5:250–251 Urban river sites case study, 2:172 Urban runoff, 2:190, 192; 3:498–501. See also Urban stormwater runoff causes of, 5:451 groundwater contamination, 5:452–453 gully pot effluent treatment and, 3:499 indicator parameters of, 2:192t managing, 2:187 nonpoint source pollution from, 2:186–187 as a source of cultural eutrophication, 3:115 into urban watercourses, 3:499–500 Urban services, efficiency of, 2:491–492 Urban stormwater runoff evaluating impacts of, 3:433–436 regulating, 3:432–433 water quality issues in, 3:432–437 Urban wastewater reuse, 1:817 Urban Wastewater Treatment Directive, 2:45

833

Urban water demand, 2:490–491 Urban water distribution systems, modeling chlorine residuals in, 1:131–137 Urban water resource management, in Asia, 2:552–554 Urban watershed protection approach, 2:191 Urban water studies, 3:501–503 Urban water supply, in developing countries, 2:632 Urinals, water-free, 1:678–679 Urine separation, 1:843 U.S. Agency for International Development, 2:489 U.S. Army Corps of Engineers. See Army Corps of Engineers U.S./Canadian Boundary Waters Treaty, 4:620–621 U.S. coastal waters, oil spills in, 2:291t U.S. Constitution, water planning and, 4:604–605 U.S. Department of Agriculture (USDA), 2:186. See also United States agricultural land use planning program, 3:596 U.S. Department of Agriculture Natural Resource Conservation Service (USDA NRCS), agricultural drainage ditch research, 3:88–90 U.S. Department of the Interior (DOI), 2:186 U.S. Department of Transportation (DOT), 2:186 USEPA codes, 5:141. See also Arsenic standard (USEPA); EPA Regional Ground Water Forum USEPA ‘‘priority elements,’’ effect on fish, 3:131t U.S. EPA Subtitle D dry tomb landfilling, 2:163–164 USEPA Test and Evaluation (T&E) Facility, 2:509–510 U.S. Geological Survey (USGS), 2:311, 312; 3:349 codes, 5:140–141 contaminant study, 5:60–62 U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program, 3:608–609 U.S. National Environmental Policy Act (NEPA), 2:624

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834

CUMULATIVE INDEX

U.S. Public Health Service (USPHS), 1:287 1962 standards of, 1:288, 292–297 U.S. Salinity Laboratory Classification, 2:159–160, 161t; 5:208–210 USS Monitor, discovery of, 4:62–63 U.S. streams, organic wastewater contaminants in, 5:605–608 U.S. waterways, contamination of, 2:122 UV dosage, 1:469. See also Ultraviolet (UV) radiation UV light components, 1:467–468 U-V-P finite element scheme, 5:658 UV sources, 1:470 UV treatment system, 1:470

Vacuoles, sequestration of metals in, 5:287–288 Vadose models, 5:77 Vacuum breakers, 1:156–157 Vacuum compression, 1:171 Vacuum filters, 1:176 Vacuum flotation, 3:407 Vacuum gauge tensiometers, 3:724–729 handling of, 3:728 response time of, 3:725 Vacuum toilet systems, 1:679 Vadose zone, 5:105 averaged transport through, 5:77–80 capillary flow in, 5:73 contaminant vapor transport through, 5:551 flow processes in, 5:537–538 hydrology, 5:533–538 macropore flow in, 5:73 materials, 5:535–537 modeling non-point source pollutants in, 5:299–305 processes in, 5:534–535 soil samples from, 3:688 Vadose zone gas monitoring, direct, 5:542 Vadose zone monitoring techniques, 5:538–543 direct, 5:541–542 indirect, 5:539–541 Vadose zone tracers, dyes as, 3:96–98 Vaiont Dam collapse, 3:147 Valley-floor gullies, 3:183 Valley-floor slope, 3:187

VALIMAR monitoring project, 2:31, 32 Valtin, Heinz, 4:789–791 Valuation approaches, direct, 4:607–608 ‘‘Value-added’’ ocean observations, 4:23 Value estimation methodologies, 4:607 ‘‘Valvecard’’ software, 1:484 Valve-exercising program, 1:401 Valves, 1:482–485 common problems with, 1:483–484 control of, 1:483 double check, 1:156 high velocities through, 1:484 insertion, 1:890 operation and maintenance of, 1:484 safety of, 1:484–485 types of, 1:482–483 water distribution system, 1:208 water hammer and, 1:262, 263f, 484 Van der Meer expressions, 4:16 van der Waals forces, 1:99; 4:387, 469 Vaporization, heat of, 4:263–265 Vapor migration, from groundwater devolatilization, 5:553 Vapor pressure, 4:271–272, 366, 522, 528–529 determining, 4:272–273 Vapors, leaking, 5:552 Vapor sampling, 5:545 Vapor transport, in the unsaturated zone, 5:543–548 Variability indexes, streamflow, 3:104 Variable uncertainty, 3:325–326 Variance technologies, 1:457 Vegetable crops, microirrigation of, 3:625 Vegetables nitrate and nitrite levels in, 3:639 organochlorine pesticides in, 3:643–647 Vegetated riparian buffers, 3:391 Vegetated submerged bed (VSB) systems, 1:787 Vegetated systems, for storm water treatment, 1:868 Vegetation. See also Plant entries acid deposition and, 4:378 concentration of MtBE released through, 5:394

submerged, 3:275–281 use in water erosion control, 3:551 water stored in, 3:475 Vegetation index (VI), 3:722 Vegetation Index/Temperature (VIT) trapezoid, 3:721 Vegetation survey, 5:78 Vegetative filter strips (VFS), 3:391 Veliger settling, industrial field studies on, 1:513 Velocities, vector plots of, 5:624 Velocity approach, to incipient motion, 3:418 Velocity constraints, in water distribution systems, 1:209 Velocity meters, 1:338, 340 Vendor-supplied systems, for storm water treatment, 1:868 Venezuela, flooding in, 3:142 Ventilation, sewer system, 1:912 Vents, underwater, 4:90 Venturi meters, 1:338 Vertical auger mixing, 1:837 Vertical breakwaters, 4:17–20 Vertical drainage, 3:732; 5:98 Vertical-flow constructed wetlands, 1:896 Vertical flow pond, 2:424 Vertical flow wetlands, in acid mine treatment, 5:6 Vertical hydraulic conductivity analysis, 5:186 Vertical intake wells, 5:88 Vertical mixing, 3:81 Vertical roughing filters, 1:237 Vertical slot fish passage facility, 3:530 Vertical soil vapor, 5:550 Vertical turbine pumps, 1:393 Very low frequency induction, 5:149–150 Veterinary pharmaceuticals, 1:377 Vibrio, 1:278 Vibrio fischeri luminescent bacterium, 2:453 Vietnam, water treatment in, 2:553 Vietnam War era, ecoterrorism during, 4:653 Vinasses, composition of, 1:619t Vinyl chloride (VC), 2:266–267 characteristics and production of, 5:634–635 detection of, 5:637 disposal of, 5:635 exposure to, 5:635–636

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CUMULATIVE INDEX

fate and transport of, 5:635 in groundwater, 5:634–640 health effects of, 5:636–637 regulation of, 5:637–638 remediation of, 5:638–639 Viral agents, 1:178 Viral disease, 2:371 Viral threat agents, 1:89 Virtual Library on Environmental Health (VLEH), 2:671–674 difficulties with, 2:673–674 Virtual temperature, 4:369 Virtual water, 2:536–537; 4:787 import and export of, 2:538–540t importation in the Nile Basin, 2:593 Virtual water balance, 2:537f national, 2:540 Virtual water content, calculating, 2:537 Virtual water flows calculating, 2:537–540 global, 2:540–541 Viruses, 1:343–344, 904; 3:669 in domestic sewage, 1:831 health effects of, 1:279 movement of, 1:71–72 removal of, 1:249, 485–489 sources of, 1:71 Virus transport modeling, 1:72–73 subsurface, 1:70–73 Viscoelastic fluids, 5:557–558 Viscosity, 5:649–650 Newton’s law of, 5:555–556 Viscous floc, 1:730 Viscous flow, 5:555–561 Viscous-flow porometers, 3:717 Visibility degradation, 4:378–379 Vitamin D metabolism, effects of lead on, 2:436 Vitotox assay, 2:175, 455 Vitrification, 1:836–837; 5:434 VLEACH code, 5:564 Void volume (α), 1:103 Volatile aromatic compounds, 2:310 Volatile fatty acids (VFA), 1:701, 702 Volatile organic chemicals/compounds (VOCs), 1:105, 353, 760, 761; 2:268, 343; 4:378; 5:543. See also Odor abatement; Perchloroethylene (PCE) adsorption of, 1:117 detection of, 2:283

occurrence of, 5:250 options for treating, 1:762f removal of, 3:368 soil vapor extraction of, 5:121–122 as water quality indicators, 2:266–267 Volatile organic contaminants, technologies for, 1:464t Volatile sulphur compounds, 4:88 Volatilization, 5:528 groundwater remediation by, 5:426–432 of heavy metals, 5:378 of nitrogen, 3:696 of persistent organic pollutants, 1:768 Volcanic activity, as a source of acidity, 3:7 Volcanic emissions, 4:159 Volcanic islands, perched groundwater in, 5:353 Volcanic water, acidification of rivers and lakes by, 3:10 Volcanoes, underwater, 4:90 Vollenweider–OECD eutrophication model, 3:110, 111, 112 Voltage, 4:442 Voltage difference, 4:442 Volume Imaging Lidar, 4:296–297 Volumetric flow rate (Q), 1:103 Volumetric reliability, 3:261 Voluntary metering, 1:494 Vortex technologies, 1:784 Vortex-type CSO solids separation unit, 1:784 VS2D model, 5:663 V-shaped basin, design discharge for, 3:245–246 Vulnerability assessment (VA), 1:424; 2:347–348 groundwater, 1:527 limitations of, 5:565 verification and postaudits of, 5:566 Vulnerability Index (VI), 5:597–598 Vulnerability mapping, of groundwater resources, 5:561–566. See also Groundwater vulnerability

Walawe basin development, 4:779f ‘‘Walking clocks,’’ 4:704 Walk-through, role in pipe assessment, 1:886

835

Warm cloud seeding, 4:187 Warm fronts, fog and, 4:231 Warning systems for flooding, flash floods, and landslides, 1:125–126 Washington State in-stream flow protection in, 4:661, 662 source-water protection in, 2:311, 312 Wash load, 3:397 Waste, aquaculture, 3:541 Waste activated sludge (WAS), 1:456, 862–863 Waste deposits model, 1:726 Waste disposal, from arsenic treatment, 5:25 Waste disposal sites, dye tracing at, 5:110 Waste loads allocation of, 3:81–84 transport mechanism for, 3:79 Wasteload allocations (WLA), 2:188 Waste management practices, 2:374–375 revising, 1:900 Wastes, from electricity generation, 5:448–451 Waste stabilization ponds (WSP), 1:518 Waste stream disposal, 1:336 Waste treatment, in fish farms, 1:681–684 Wastewater(s), 1:656–659. See also Complex waste waters; Wastewater management; Wastewater modeling and treatment plant design; Wastewater reclamation and reuse entries; Wastewater treatment entries aeration of, 1:623–626 analyses of, 1:657t, 658t biological characteristics of, 1:658–659 characteristics of, 1:677, 900–904 chemical characteristics of, 1:657–658 chemically enhanced primary treatment of, 1:659–660 concentration of microorganisms in, 3:670t contaminants of, 1:829t defined, 2:548 direct reuse of, 1:306–307 disposal practices for, 3:79

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836

CUMULATIVE INDEX

Wastewater(s), (continued) EU monitoring of, 2:267–268 land applications of, 1:632–635 occurrence of detergents in, 1:671–672 from oil production, 2:285–286 physical characteristics of, 1:657 pollution by, 3:292 pollution in, 4:507 reclamation of, 2:497 as a resource, 1:676–677 sample analyses of, 1:662–663 toxic evaluation of, 1:565–566 Wastewater-associated pathogenic microorganisms, 3:668t Wastewater bacteria, poly-P-containing, 1:788t Wastewater biofilms, 2:230 Wastewater contaminants, in U.S. streams, 5:605–608 Wastewater discharge numeric limitations, industry sectors subject to, 1:758t Wastewater discharge permits, 1:755–756 Wastewater discharges. See also Wastewater effluents from power plants, 1:556 regulatory controls on, 1:557 Wastewater effluents, 3:80 Wastewater management. See also Ecological wastewater management centralized and decentralized, 1:720–721 for developing countries, 1:718–722 Wastewater modeling and treatment plant design, 1:730–738 applications of, 1:738–745 biological process modeling, 1:735–737 information gathering step, 1:738–739 input and output file preparation step, 1:744–745 International Water Association models, 1:732–733, 736–738 laboratory and data organization step, 1:742–744 model compilation and setup step, 1:744 model parameter initialization step, 1:745

model selection step, 1:739–740 parameter adjustment step, 1:745 reactor hydraulics step, 1:740– 742 static and dynamic models, 1:731–732, 733–735 Wastewater quality, for developing countries, 1:719–720 Wastewater reclamation and reuse, 1:825–826 treatment technology related to, 1:826–828 Wastewater reclamation and reuse research, 1:819–825 future needs for, 1:823–824 to protect public health, 1:819– 822 public perception and, 1:823 in wastewater treatment technologies, 1:822–823 Wastewater reuse, 3:667–668. See also Wastewater reclamation and reuse entries guidelines and treatment practices for, 3:670, 671t, 672t Wastewater reuse system, low-tech, 5:329 Wastewater sanitation, enhancement of, 1:498 Wastewater sludge, 1:861–864. See also Sludge Wastewater streams, pollutants in, 4:506–507 Wastewater toxicity, biotests for, 1:566 Wastewater treatment, 1:814–817. See also Advanced wastewater treatment techniques; Small-scale wastewater treatment; Wastewater treatment plants (WWTPs); Wastewater treatment technologies anaerobic, 1:904–910 biofilm in, 2:230–232 centralized versus decentralized, 1:678 disinfection, 1:817 fate of persistent organic pollutants in, 1:766–771 inadequate, 1:661–667 powdered activated carbon in, 2:87–88 preliminary, 1:814–815

primary, 1:815 regulation of, 1:844 removal of microorganisms by, 3:669 secondary, 1:815–816 sugarcane industry, 1:614–620 use of redox potentials in, 1:399–400 Wastewater treatment facilities, Ho Chi Minh City, 2:553 Wastewater treatment industry, 4:654 Wastewater treatment methods, oil-field brine control by, 2:288–289 Wastewater treatment plants (WWTPs), 1:565, 623, 766, 767 monitoring biodiversity in, 1:642–646 odor abatement in, 1:760–764 performances of, 1:663, 664f Wastewater-treatment return flow, 2:548 Wastewater treatment technologies, 1:808–814 biological, 1:813 chemical, 1:811–812 electrical, 1:812 physical, 1:809–811 thermal, 1:812–813 Wastewater use studies, site characteristics of, 1:633t Wastewater utilities, security of, 1:870–871 WATEQ4F program, 5:140 WATEQ database, 5:144 Water. See also Aquatic entries; Drinking water; Heavy water; Natural waters; Raw water; Reclaimed water; Wastewater entries; Water conservation measures; Water distribution system entries; Water industry; Waterlogging; Water quality; Water resource entries; Water supply entries; Water treatment entries; Water use absolute (dynamic) viscosity of, 4:527 algal toxins in, 2:387–392 bacteria, viruses, and pathogens in, 2:303 as a better medication, 4:724 balancing the need for, 2:574 beryllium in, 4:394–399

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CUMULATIVE INDEX

between Arabs and Israelis, 4:699–701 biological structure and function of, 4:512 bottled, 1:3–5 cadmium in, 5:617 characteristics of, 1:900–904 chemistry of, 4:711 as a cholesterol-lowering medication, 4:701–702 clarity/turbidity of, 1:599; 3:108 classification of, 2:95; 4:449t competing uses for, 2:613 complex dynamics of, 4:512–513 cosmic, 4:189–191 crystals in, 4:712–713 density of, 4:527 discovery of, 4:711 distilled, 4:441–442 distribution and quantity of, 4:283–284 economic value of, 4:605–612 effect on cell biology, 4:456–457, 458 electric generating plant contaminants of, 1:555–556 emergence as a public health issue, 1:283–286 emergency, 2:526–529 evolution of, 4:715–718 extracellular matrix and, 4:459–461 facts related to, 3:394–397 freezing and supercooling of, 4:585–586 future of, 4:713 globalization of, 2:536–541 gross value of, 4:608 heat capacity of, 4:529 in history, 4:726–731 in the history of photography, 4:766–769 impact on health and aging, 4:455–461, 729 impurities accumulated by, 1:900–901 in interstellar space, 4:189–190 as key to health and healing, 4:722–726 kinematic viscosity of, 4:527 ‘‘magical’’ properties of, 4:583–585 man’s history and, 4:745–746 market allocation of, 2:644 marketing proposals for, 2:506–508

measurement of, 2:658–660 measurement of 36 Cl in, 4:417 microbial growth in, 3:311 modulus of elasticity of, 4:529 molecular network dynamics of, 4:511–513 monitoring for threat agents, 1:89–91 nitrate in, 1:31–32 nitrogen pollution of, 3:605 oil removal from, 1:774–776f organic matter contamination of, 3:606 origin of, 4:283 osmotic movement of, 4:520–521 oxidation of, 4:535–536 passage in and out of cells, 4:458–459 prescriptive use of, 4:798 pricing, 3:585 production of hydrogen ion in, 4:481 protozoa in, 2:313–314 radon in, 4:541–548 regulatory standards for, 1:576 relationship to soil, 3:641 as a renewable resource, 2:661 role in enzyme functioning, 4:512 role in the Canadian landscape, 3:507–510 solubility of chemicals in, 4:555–559 solubility of hydrocarbons and sulfur compounds in, 4:561–564 as a solvent, 4:725 sound in, 4:569–571 as a source of wisdom, 4:793–797 on the Space Station, 4:572–574 specific gravity of, 4:527 specific weight of, 4:527 speed of sound of, 4:529 squeezing from rock, 5:477–480 storing, 2:527 strontium isotopes in, 4:574–578 surface tension of, 4:528 survival of threat agents in, 1:88 technetium in, 4:578–583 trace elements in, 3:455 in the unsaturated zone, 5:531–533 varieties of, 4:462 vinyl chloride in, 5:637

837

Water accounting, as a water conservation measure, 1:146–147 Water Act of 1974, 2:183 Water adsorption on carbons, 4:400–404 studies of, 4:400 Water allocation, 2:504–506. See also Water distribution authority over, 4:660–65 efficient, 2:6436 Water allocation law, 2:558 Water allocation system, 2:644 Water allotments, purchasing, 2:508 Water analysis, 1:86 corrosion measurement and, 1:9 tests for, 2:178, 180t trace element pollution and, 4:112 Water analysis methods, 2:304–311 gas chromatography, 2:304–308 Water assessment and criteria, 2:24–28 biotic integrity and, 2:26 current, 2:25–26 development of, 2:24–25 institutional arrangements for, 3:34 reference sites and biocriteria, 2:26 Water audits, 1:401; 2:492 Water availability, impact of biofuels on, 3:547 Water availability index, 1:404f Water balance, 1:202 global, 4:279–280 in Hawaii, 4:259–262 Water balance equation, 3:259 Water balance method/techniques, 3:572; 5:163 Water balance/modeling, recharge measurement, 5:74 Water Bank Act, 4:691 Water-bearing rocks, consolidated, 5:55–56 Water biosecurity, 1:87–92 future directions for, 1:91 Waterbodies. See also Open waterbodies advancements in understanding, 4:730 anoxia and hypoxia in, 4:64–69 effluent-based, 2:475 excessive fertilization of, 3:107, 108 ‘‘impaired,’’ 2:476

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838

CUMULATIVE INDEX

Waterbodies. (continued) impact of cadmium on, 5:615 remote sensing of, 4:324–325 Waterborne bacteria, 2:20–24 identification of, 2:21 Waterborne disease outbreaks, 2:293 Waterborne disease surveillance, 1:183–192 background of, 1:184–185 early outbreak detection, 1:186–187 endemic disease and, 1:187–189 improving, 1:190–191 of infection versus disease, 1:189–190 limitations of, 1:185–186 Waterborne infectious diseases. See Emerging waterborne infectious diseases Waterborne pathogens health and, 1:521–522 persistence of, 1:521–523 Waterborne radon, 1:51–52 Waterborne transmission of Escherichia coli, 1:429–431 of Escherichia coli O157:H7, 2:138 Water budget, 2:507; 3:222–223 lake, 3:266 program, 3:554–557 Water ‘‘carriage,’’ 1:510 Water chemistry factors determining, 2:19 in regional flow systems, 5:419–420 Water cleanup, organoclay in, 1:771–781 Water clocks, 4:703–707 Water color, caused by iron bacteria, 2:151–152 Water column bacterial activity in, 3:181 heat flux into, 3:192 Water companies, financial performance of, 1:310–312 Water conditioners, magnetic, 1:144 Water conditioning magnetic, 1:534–537 physical, 1:141–145 Water conflicts. See also Water disputes in the Nile Basin, 2:590–594 over scarce water, 2:502–503 Water consciousness, evolution of, 4:707–713

Water conservation, during a drought, 4:209 Water conservation ecosystems, ancient Sri Lankan, 4:772–780 Water conservation interventions, nonengineering, 2:472–473 Water conservation measures, 1:53, 146–149, 510; 2:489–494, 495–498. See also Landscape water-conservation techniques; Water saving technologies; Water use in Canada, 2:660–666 costing and pricing, 1:147–148 efficiency and, 2:492–493 in the home, community, and workplace, 2:664–666 information and education, 1:148 in integrated water resources management, 2:575 metering, 1:146 water accounting and leak repair, 1:146–147 Water Conservation Plan Guidelines (EPA), 1:146 Water-conserving toilets, 1:679 Water consumption, 2:370–371 metering coverage and, 1:494f reducing, 1:678–679; 2:664 rise in, 2:375 Water contamination by heavy metals, 5:275–280 by low level organic waste compounds, 5:60–63 sources of, 3:651 Water content measuring, 5:461–462 predicting, 5:126 Watercraft discharges, 3:281 Water crisis, global, 4:769 Water cycle, 2:548; 4:191–194, 196–197. See also Global water cycle; Hydrologic cycle climate change and, 4:193 conservation and, 4:433–434 deuterium in, 4:439 NASA Aqua mission and, 4:193–194 sun-powered, 4:584 Water debts, 2:617 Water Deficit Index (WDI), 3:719, 721 Water demand derived, 4:608 estimation of, 1:496 management of, 1:146

price elasticity of, 4:606–607 residential, 1:12–16 urban, 2:490–491 Water demand forecasting, 2:529–531 cases of, 2:530 model, 2:622–623 Water dependency, global, 2:538–540t Water discharge permits, 5:3 Water disinfection, using UV radiation, 1:471–476 Water disputes. See also Water conflicts averting, 2:501–510 constitutional solutions to, 2:503–504 water allocation and, 2:504–506 Water distribution, fair, 2:491–492. See also Water allocation entries Water distribution storage tanks, hydraulic design of, 1:448–449 Water distribution system design, 1:207–213 constraints on, 1:209 iterative method for, 1:210–211 Water distribution systems (WDSs) chlorine residual modeling within, 1:132 components of, 1:208–209 corrosion control in, 1:152–154 desirable operating conditions for, 1:201 elements of, 1:201 maintenance and repair functions of, 1:203 operation, maintenance, and design of, 1:200–204 prevention and safety functions of, 1:203 principal operations of, 1:201–202 public relations and management functions of, 1:203–204 pumps in, 1:391–395 risk reduction for, 1:436–437 securing, 1:434–437 urban, 1:131–137 water delivery and monitoring by, 1:202 Water distribution system simulators (DSS), 2:509–510 Water dowsing (witching), 5:92–94 Water dwellers, exposure method using, 2:420

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CUMULATIVE INDEX

Water economic analysis, components of, 2:128–129 Water education impacts on, 4:714–715 strategies for, 4:713–715 Water efficiency, technological options for, 2:493 Water efficient residential technology, 2:663 ‘‘Water emergency price schedule,’’ 2:583 Water engineering technology, development of, 4:728 Water environment, persistence of toxic metals in, 2:233 Water Environment Federation (WEF), 1:863 Water erosion, 1:537–538; 3:566 control of, 3:551, 568 Water Erosion Prediction Project (WEPP), 2:251–252 Water facilities, capital investment in, 2:594 Water filtration, 1:230–233 Water flow, in unconfined aquifers, 5:662–663 Water holding properties, field capacity and, 5:125–126 Water flow patterns, using dyes to delineate, 3:96–98 Water flow rates, biofilm growth and, 1:598 Water-flow satellite data, from NASA, 2:587–589 Water-flush toilets, 1:678–679 Waterfowl, lead toxicity to, 2:434–435 Water-free toilets, 1:678–679 Water Framework Directive (EU), 2:45; 3:292 Water/graphite model potentials, 4:401 Water habitat, eutrophication in, 3:108–109 Water hammer, 1:261–264, 401 causes and effects of, 1:261, 891–892 computation of, 1:891–892 control of, 1:892 solutions to, 1:261–263 valves and, 1:484 Water hardness, 4:413 Water harvesting choosing techniques for, 2:551 components of, 2:549–550

defined, 2:549 forms of, 2:550 need for, 2:548–549 and reuse, 3:557 structures related to, 2:550–551 Water heaters, solar, 1:63–67 Water hyacinth control of, 3:481–483 as a problematic weed, 3:479–484 Water impacts, from construction sites, 1:537–538 Water industry, 2:587 companies with interests in, 1:302t consolidation of, 1:509 future of, 1:307 key trends in, 1:508–510 market drivers of, 1:304–305 market size and growth characteristics of, 1:304 policies and approaches of, 1:510 privatization of, 1:306 state of, 1:301–307 trends in, 1:305–307 Water infrastructure, 2:567–568 planning and managing, 2:594–595 Water Infrastructure Network, 1:303 Watering equipment, outdoor, 2:666 Water-jetting drilling technologies, 5:234–235 Water Law of China, 2:486 Water laws/legislation, 2:96 Hawaiian, 4:805–806 Islamic, 4:634–635 state, 2:584–585 water transfers and, 4:686 Water-level drawdown, 5:102–105 in aquifers, 5:103–104 information related to, 5:104 Water-level oscillation, 5:112 Water levels, in wells, 5:572 Water-limited environments, ecological effects assessment for, 2:516–518 Water loads, river, 3:393t Waterlogged areas, types of, 1:404 Waterlogged lands, management and reclamation of, 3:603 Waterlogging, 3:599–604, 741 causes of, 3:599–600 effects of, 3:600 field measurement assessments for, 3:599 impacts of, 3:741–742 losses due to, 3:601t

839

problem identification observations related to, 3:599 remote sensing and GIS application in, 2:534 surface stagnation and crop yields from, 3:600–601 Water loss controlling, 1:317–320 tracing, 1:401 Water mains, 1:203 Water management, 4:433 in the Arab World, 2:472–474 British and French models of, 1:389 in China, 2:484–488 computer models for, 2:620 institutional structure of, 2:614–615 irrigation and, 4:771–772 lessons related to, 4:268 in the Mediterranean islands, 2:642 in the public trust, 2:608–610 Soviet style, 3:19 Water management agencies, federal, 4:650t Water-management plans, drought strategy in, 2:581 Water management problems, severity of, 4:289 Water markets, 2:499–501. See also International water market; Spot markets Chilean, 2:645 in India, 2:555–559 institutional options related to, 2:500–501 reform of, 2:508 regulation of, 2:500 transaction costs of, 2:499–500 Water meters, 1:337–341, 489–495 classes of, 1:492 compound, 1:338 densities, costs, and impacts of, 1:494 history of, 1:489–490 household, 1:490–491 installation of, 1:338–339 operating principles of, 1:493f positive displacement, 1:338 precision tests for, 1:491–492 reading, 1:339–340 selecting and sizing, 1:340, 492–493 technical aspects of, 1:493–494

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840

CUMULATIVE INDEX

Water meters, (continued) testing and maintenance of, 1:340–341 as tools for management and charging, 1:490 types of, 1:338 velocity, 1:338 Water molecules, 4:527 stable isotopes in, 5:229–231 Water music instrument, 4:758–762 Water needs for freshwater fisheries management, 3:133–135 tradable rights and, 2:643–645 Water networks, behavior of, 4:511 Water oxidation, supercritical, 1:874–875 Water penetration, soil texture and, 3:707 Water phase diagram, 4:344f Water philosophy, evolution of, 4:708–711 Water pipeline. See Pipeline entries; Underground pipeline Water planning, U.S. Constitution and, 4:604–605 Water policies, supply-oriented, 2:574 Water pollution, 1:901; 2:95–96. See also Polluted waters; Surface water pollution causes of, 4:519 from fish farms, 3:579–581 health risks of, 2:617 reducing, 4:647 tests used for measuring, 2:180t types and forms of, 4:97–105 Water Pollution Control Act of 1948, 4:652–655 history of, 4:651–655 before the mid-1960s, 4:652 Water pollution control plants (WPCPs), 1:747, 748, 750 New York City, 1:746, 748t Water Portal of the Americas, 2:669 Water portals, 2:668–674 types of, 2:669 Water Poverty Index, 1:439 Water pressure, Space Station, 4:573 Water pressure reduction, 1:157 Water prices, rise in, 1:508 Water pricing, 1:215, 216; 2:497, 603–606. See also Cost(s); Option prices assessment of, 2:605–606 in Canada, 2:663

components of, 2:603 functions of, 2:604–605 global, 2:603–604 increase in, 2:604–605 Water problems awareness of, 4:606 current, 2:574 Water productivity (WP), 3:558–560 improving, 3:585 Water project operations, 2:621 Water projects, federal, 2:522–523 Water protection laws, 4:597 Water provision, private sector participation models for, 1:50–51 Water purification, 4:441–442 adsorption capacity of activated carbon for, 4:381–384 emergency, 2:527 photocatalytic membrane reactors in, 1:791–797 Water purification machines, Space Station, 4:573 Water quality, 2:96–97, 301–304, 314–316; 5:602. See also Sewer water quality; Storage water quality; Water quality management; Water quality modeling; Water supply quality aquifer, 5:9 ash pond and FGD sludge pond, 1:850 biofouling effects on, 5:35–36 in Canada, 2:663–664 chemical parameters, 1:902–903 chronology of events related to, 2:314 complaints concerning, 1:152t of constructed wetlands, 1:892–894 costs and benefits of, 2:129 criteria for, 2:315 data on, 2:192 defined, 2:302, 548 in distribution systems, 1:204–207 in dredged sediment management, 2:122–127 early pollutant detection and, 2:440–452 economics of, 2:127–135 effect of human activities on, 2:303 effect of natural processes on, 2:302–303 effect of scale on, 2:190 electronic nose applications related to, 2:282, 283 ethic for, 2:315

evaluating, 2:368 federal regulations regarding, 2:190 in forested land, 2:199 Ganga Basin, 3:235 guidelines for, 2:337 impacts of eutrophication on, 3:107–109 impacts on, 1:496–497 impaired, 2:663; 3:111 incentive-based mechanisms for improving, 2:132–134 in India, 2:566 information about, 2:303–304 issues related to, 2:181–182 land use effects on, 2:169 microbial criteria for controlling, 2:449–451 in municipal solid waste landfills, 2:163–169 in net pen aquaculture systems, 3:543 nitrate levels and, 1:32–33 nitrogen loading and, 3:696 nutrient-related, 3:111–112 oil-field brine and, 2:287 parameters of, 1:901–902; 2:180t in ponds, 3:484–487 problems with, 1:304 protection measures for, 2:120 public awareness of, 2:194 regulation of, 4:671–672 sand abstraction and, 3:415 soil pipe erosion and, 5:403–404 in suburban watersheds, 3:441–444 in urban stormwater runoff, 3:432–437 uncertainties in analyzing, 2:369 in urban areas, 5:250 using luminescent bacteria and lux genes for determining, 2:172–176 variations in, 2:179–180 in watersheds, 3:460 wetlands and, 3:491 Water Quality Act of 1965, 2:194, 314 Water Quality Act of 1987, 4:654–655 Water Quality Analysis Simulation Program (WASP5), 2:327, 329–330 Water quality assessment, classification and mapping of agricultural land for, 3:608–609

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CUMULATIVE INDEX

Water Quality Assessment program (USGS), 5:386 Water Quality Association (WQA), 1:381 Water quality-based effluent limitations (WQBELs), 1:557; 4:657 Water quality constraints, in water distribution systems, 1:209 Water quality criteria Great Lakes system, 4:623–624 for toilet flushing, 1:17 Water Quality Criteria and Standards Plan (EPA), 3:436 Water quality evaluation, incorporating chemical information into, 4:602 Water quality goals, for estuaries, 4:54–55 Water quality impairment, urban-landscape-related, 2:191t Water Quality Index (EPA), 2:368 Water quality indicators, 2:266–267 Water quality indices, 2:368 Water quality issues, major, 4:286t Water quality ‘‘ladder,’’ 2:655 Water quality management, 2:176–184, 188; 5:334 in an agricultural landscape, 3:604–608 approach to, 2:183–184 determinants related to, 2:178 in a forested landscape, 2:199–202 Great Lakes region, 3:179 legal considerations in, 2:183 nonpoint source control and, 2:184–189 in the United States, 2:193–198 in an urban landscape, 2:189–193 Water quality modeling, 3:338–339. See also Water quality models case studies in, 2:255–263 of Lake Tenkiller, Oklahoma, 2:260–262 software tools for, 2:325–328 future of, 3:341 Water quality models, 2:248–255. See also Water quality modeling; Water quality simulations Agricultural Nonpoint Source Pollution Model 2001, 2:251 chemical principles related to, 2:269–273 CREAMS and GLEAMS, 2:250–251

detailed, 2:249 equations for, 2:273–278 Erosion–Productivity Impact Calculator, 2:251 Generalized Watershed Loading Function, 2:252–253 hydrologic simulation program, 2:249–250 kinetic parameters used in, 2:276t mathematical framework of, 2:273–278 midrange, 2:248 Nitrate Leaching and Economic Analysis Package, 2:252 Pesticide Root Zone Model, 2:252 regression methods and spreadsheet models, 2:253 review of, 2:249–253 Revised Universal Soil Loss Equation, 2:251 Root Zone Water Quality Model, 2:252 selecting, 2:255–256 simple, 2:248 Soil and Water Assessment Tool, 2:250 Source Loading and Management Model, 2:253 variables in, 2:270–272 Water Erosion Prediction Project, 2:251–252 Watershed Modeling System, 2:250 Water quality monitoring, 2:177–180 Water quality parameters, 4:325t Water quality policy, 2:127–128 economic instruments for informing, 2:129–131 instruments of, 2:132–134 Water quality programs, 2:315 Water quality protection, integration of, 4:672–673 Water Quality Protection Center, 1:91 Water quality regulations, 2:314–315; 4:665–667 Water quality simulations, 2:261–262 Water quality standards (WQS), 2:267–268, 302; 4:657; 5:324 Clean Water Act, 4:596 violations of, 3:107–108 Water quality statutes, 4:664–671 Water quality studies, remote sensing and GIS application in, 2:534

841

Water quality trends, in New York City, 1:748–750 Water quality variables, notations and source terms for, 2:275t Water quantity allocation of, 4:671 impacts on, 1:495–496 Water quantity constraints, in water distribution systems, 1:209 Water quantity regulation, in India, 2:557–558 Water recovery/reclamation, 1:53. See also Water reuse achievable treatment levels for, 1:807t technologies for, 1:806–807 Water recycling defined, 2:610 environmental benefits of, 2:610–613 future of, 2:613 increased focus on, 1:306–307 pollution reduction and, 2:612 for sensitive ecosystems, 2:612 technologies for, 1:808–874 for wetlands and riparian habitats, 2:612 Water reduction methods, in Arab states, 2:472 Water regulation, history of, 2:193–198 Water-related diseases, 1:23–25; 2:111–112 global morbidity and mortality from, 1:24 Water requirements average, 1:506–507 for human health, 1:22–23 Water resource development, American, 2:498–499 Water resource development projects, Ganga Basin, 3:234 Water resource health, measuring, 3:37 Water resource integrity, evaluation using biotic integrity index, 3:36–41 Water resource management, 2:586–587; 4:267–268 in America, 2:608 Chinese laws related to, 2:488 decentralization of, 2:473 decision support system for, 2:622–623 for drought conditions, 2:576–586

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842

CUMULATIVE INDEX

Water resource management, (continued) Great Lakes area, 3:179 structures for, 2:567t Water resource organizations, 4:648–651 governmental, 4:649–650 nongovernmental, 4:651 professional, 4:651 Water resource remote sensing, 4:321 Water resource requirements, for India, 2:564–566 Water resources, 2:370; 4:288–289. See also Poor- quality water resources anthropogenic threats to, 3:37 in the Arab World, 2:470–474 best management practices for, 2:570–573 Canadian, 2:656–660 depletion of, 4:289–290 economics of allocating, 1:215–218 Geographic Information System and remote sensing in, 2:531–536 health indicators for, 3:37 in India, 2:559–567 intergenerational, 4:771 management of, 1:303 protection of, 2:374–375 satellites useful for, 4:326t stress on, 2:495 sustainable development of, 5:163 threats to, 1:438 Water Resources Development Act of 1986, 4:619 Water resources planning, integrating environmental impacts into, 2:520–522 Water resources systems, 2:586 components of, 2:619 performance evaluation of, 2:674–678 Water resources systems analysis, 2:683–687 defined, 2:684 mathematical modeling in, 2:686–687 Water resource sustainability, 2:624–630 concepts related to, 2:625–627 practices in, 2:628–629 stages of, 2:629f

Water resource valuation, 2:653–656 economic perspective on, 2:653–654 empirical estimates of, 2:654–655 Water retention. See also Retention of fish ponds, 1:407 maintaining and increasing, 1:406 in river valleys, 1:406–407 Water retention characteristic, 4:486 Water reuse, 1:53–54, 817–819. See also Water recovery/reclamation in agriculture, 2:496 increase in, 1:509 in industry, 2:496 international standards for, 3:670–672 technologies applicable to, 1:54 Water rights, 2:500–501; 4:769–772 declarations of, 4:770 distribution of, 2:643–644 Hawaiian, 4:805–806 issues related to, 4:770–771 reserved, 4:689–690 security of, 2:644–645 Water rituals, 4:709–710 ancient, 4:709–710 Water–rock interaction, 5:566–571 adsorption and, 5:566–568 dissolution and, 5:568–569 precipitation and, 5:569–570 Water safety, precautionary principle regarding, 2:600 Water sampling, 2:161–163. See also Water samples security and integrity of, 2:162 Water samples. See also Water sampling analysis of strontium isotopes in, 4:575 analyzing for deuterium, 4:439 Water savings, using microirrigation, 3:617 Water-saving techniques, domestic, 2:497 Water-saving technologies, in the Nile Basin, 2:594 Water scarcity, 1:304; 2:181, 490 conflicts over, 2:502–503 global, 2:538–540t human behavior and, 4:733–734 in India, 3:445–447, 448f in the Nile Basin, 2:590–591 role in human health, 1:20–22 Water science. See also Water studies issues and risks related to, 2:602t

precautionary principle regarding, 2:595–603 terms related to, 2:541 Water security, 1:437–439. See also Water resources global water availability, 1:437–438 government actions regarding, 1:434–436 relation to food security and agriculture, 1:438–439 terrorism and, 1:158 Water self-sufficiency, global, 2:538–540t Water service(s) data and indicators related to, 1:505–507 valuation of, 4:607 Watershed(s), 2:548; 3:460–461. See also Combustible watersheds; Megawatersheds; Suburban watersheds allochthonous inputs from, 3:207 assessments of, 2:264–265 changes in, 4:280–281 flood potential of, 3:460–461 flood source mapping in, 3:155–159 municipal, 1:495–500 processes related to, 3:327–328 in stream classification, 3:66 time of concentration and travel time in, 3:469–472 water control in, 2:567 Watershed approach, 2:189; 4:115–116 Watershed ecology, hydrochemical models used in, 5:297t Watershed functions, 3:473–478 Watershed hydrogeomorphologic index, 3:63 Watershed hydrology, 3:472–479 modeling of, 3:342 role of wetlands in, 3:172–173 terminology related to, 3:472–473 units used in, 3:473 Watershed lands, conversion to agriculture, 3:36 Watershed management, 2:192, 248; 3:502–503 plan for, 2:629; 5:335 Watershed mapping/monitoring, remote sensing and GIS application in, 2:533 Watershed modeling, 3:327–331. See also Watershed models

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CUMULATIVE INDEX

procedures in, 3:328–330 uncertainty analysis in, 3:325–327 Watershed Modeling System (WMS), 2:250 Watershed models. See also Watershed modeling calibration of, 3:329f classification of, 3:328 Watershed nutrient export coefficients, 3:110t Watershed outlet, travel time to, 3:63 Watershed response continuous, 3:343 event-based, 3:343 Watershed restoration plans, 4:596–597 Watershed spatial scale, 2:613 Watershed water balance, forest quality and, 3:172 Water shortage, in the human body, 4:789–791 Water shortage planning tools, Palmer Index, 2:581 Water-shortage plans, state, 2:583 Water softening, 4:454. See also Magnetic water conditioning for scale control, 1:548 Water, Soil and Hydro-Environmental Decision Support System (WATERSHEDSS), 2:328 Water solubility, correlations for, 4:382t Water solubility graphs, 4:556–558f, 559, 560–561f, 562–564f Water source emergencies, planning for, 2:401 Water sources groundwater supplies variability in, 2:400–401 little control of, 2:400–401 Waterspout, 4:347 Water spreading, 3:163, 708–712 methods of, 3:164–165 Water stocks, improving, 2:635 Water storage, technological revolution in, 4:729–730 Water stress crop adaptations to, 3:719–720 in India, 3:445–447, 448f Water-stressed countries, health in, 1:20–22 Water studies, interdisciplinary, 2:641–642 Water subsidies, 1:217

Water supplies. See also Water supply improvement for agricultural production, 2:617–618 bacteriological quality of, 1:294–295 chemical characteristics of, 1:295–296 in developing countries, 2:616–617 effect of sediment on, 3:508 for energy production, 2:618 enhancement of, 1:497–498 failures in, 2:514 indicators of, 1:505–507 meeting demands for, 1:218–221 physical characteristics of, 1:295 political and legal impacts on, 2:618 privatization of, 4:770 radioactivity of, 1:296–297 source and protection of, 1:294 state and regional, 2:613–619 treatment of, 2:374 types of, 2:371 uncertainty of, 2:400–401 value of, 1:500–501 Water supply allocation, 2:569 Water supply improvement impact of, 1:25–26 metering and, 1:490 Water supply planning/management, 2:515–516, 614–615 federal, 4:612–616 Water supply protection, extraterritorial land use control for, 1:315–317 Water supply quality, 2:370–376 factors affecting, 2:373–374 Water supply subsystems, 2:515 Water-supply threat agents, 1:88 Water supply–wastewater sanitation cycle, 1:651f Water supply wells, 5:22–28 treatment of arsenic in, 5:22, 23–25 treatment of biofouling in, 5:22–23, 27–28 treatment of chromium in, 5:22, 25–27 Water surface, long-wave radiation from, 3:192 Water Survey of Canada, 2:658 Water symbolism, 4:785–788 in art and nature, 4:787 postmodern metaphors and, 4:787

843

Water system operation, decisions about, 2:595 Water systems components and evolution of, 1:501–503 iron and manganese removal from, 1:312–315 pharmaceuticals in, 1:372–378 rural, 1:213 Water table, 2:548; 5:600. See also Falling water table constant, 3:602 contribution to crop evapotranspiration, 3:570–571 data, 5:164 ‘‘perched,’’ 5:11 studies, 3:601–603 Water table levels, tile drainage and, 3:731–732 WaterTechOnline portal, 2:669 Water temperature tracer technique, 5:681–683 Water testing, frequency of, 5:325 Water towers, 1:410 Water tracing, 5:240 Water transfers, 4:685–689 disputes over, 4:687–688 impacts of, 4:686–687 motives and issues in, 4:685 return flow and, 4:685 riparian doctrine and, 4:686 Water transportation, inefficiency in, 2:492 Water transportation occupations, 4:762–766 employment in, 4:764 job outlook and earnings in, 4:765 nature of, 4:762–763 training, qualifications, and advancement in, 4:764–765 working conditions in, 4:763–764 Water travel times, in river-connected aquifers, 5:681–684 Water treatment. See also Drinking water treatment; Package plants beginning of, 1:286 for cooling water systems, 1:560 filtration, 1:245–248 microbiological mechanisms and, 1:596–598 ozone in, 1:362 powdered activated carbon for, 2:86–87 rationale for, 1:599–601

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844

CUMULATIVE INDEX

Water treatment. (continued) in recirculating aquaculture systems, 3:544 regional, 2:615–616 in spent nuclear fuel storage, 1:595–608 Water treatment methods, 1:601–607. See also Water treatment processes advantages and efficacy of, 1:194t Water treatment plant residuals aluminum recovery from, 1:140f categories of, 1:411–413 coagulant recovery from, 1:139–141 management of, 1:411–413 regulations governing, 1:413 Water treatment processes, 1:412t. See also Water treatment methods selection guide for, 1:439–444 Water treatment systems mixing and agitation in, 1:76–81 stages in, 2:616 Water treatment technology, selecting, 1:242–243 Water turbine, 3:487–489 specific speed of, 3:489 Water turnover, 4:276 Water use in California, 2:478–480 categories of, 2:651–653 defined, 2:548 economic efficiency in, 2:575 efficient, 1:307, 509–510 for energy industry materials, 1:562–563 in energy production, 1:560–565 excessive, 2:492–493 in flow-through aquaculture systems, 3:542 forecasting, 1:15 global and regional, 2:489–490 Great Lakes area, 3:178–179 hydroelectricity, 1:561–562 impact of biofuels on, 3:547 indirect, 1:563 in the Middle East, 4:753–758 national trends in, 2:650–651 nuclear power, 1:561 in recirculating aquaculture systems, 3:544 regulatory mechanisms regarding, 2:490 thermoelectric, 1:560–561 in the United States, 2:645–650

Water use categories, regional, 2:615t Water use curtailment, during droughts, 2:583 Water use efficiency (WUE), agricultural, 3:558–560 Water use management, in the United States, 2:647–649 Water-use-priority system, 2:583 Water-user compliance, monitoring during droughts, 2:583 Water users, categories of, 2:587 Water-use sectors main, 2:495–497 water demand forecasting for, 2:530 Water utilities charging practices for, 1:490 initial public offerings (IPOs) of, 1:389 Water valuation application of, 4:610 estimation methodologies for, 4:607 as an intermediate good, 4:608–609 motivation for, 4:605–606 studies, 2:655 Water valuation approaches direct, 4:607–608 indirect, 4:608–610 Water vapor, 4:243, 244, 362 changes in, 4:174 condensing, 4:240 distribution of, 4:270–271 effects of, 4:170 importance of, 4:717 Water vectored disease, 2:112 ‘‘Water wars,’’ 2:649 Water washed diseases, 2:112 Water waves, 4:138–139. See also Waves characteristics of, 4:138–139 Waterways gross pollution of, 2:314 South Asian, 4:681 Water well drilling techniques, 5:105–107 cable-tool drilling, 5:105 direct push drilling, 5:106 hollow-stem auger drilling, 5:106 horizontal drilling, 5:106 rotary drilling, 5:105 wire line coring, 5:105 Water wells. See also Well entries biofouling in, 5:35–38 deterioration of, 5:23

earthquake responses in, 5:111–112 for groundwater sampling, 5:455 installation of, 5:106 Water withdrawal(s), 2:478; 3:582t. See also Withdrawal in Canada, 2:661 by country, 2:648t global, 2:538–540t Great Lakes, 3:179t for public supplies, 2:651–652 in the United States, 2:645–650; 3:588–591 worldwide, 3:381 Water year, 4:318–319 Wave breaking, 4:137–138 Wave celerity, 3:258 Wave energy, 4:45 Wave height, estimating, 4:2–3 Wave overtopping, 4:16, 19 Wave-powered desalination system, 4:46 Wave reflection, 4:17 shoaling and, 4:136–137 Wave theory, 4:45 Waves in coastal waters, 4:23–24 continuous, 3:248 in lakes, 3:267 shallow water, 4:135–138 Wave theory, 3:246–253 Wave transmission, 4:17, 19 Weak add respiratory uncoupler (WARU), 4:524 Weapon tests, as water pollution, 4:102–103 Weather atmosphere and, 4:360–362 energy and, 4:353–354 extremes in, 4:175–176 local and global, 4:361–362 Weather balloons, 4:164–166, 328 Weather Bureau, United States, 4:347–348 Weather forecasting advances in, 4:354 Aqua spacecraft and, 4:351 benefits to society, 4:351–352 foundations of, 4:352–353 history of, 4:348–352 modern tools of, 4:350–351 numerical prediction in, 4:350 Weather modification health concerns related to, 4:188 uses of, 4:188

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CUMULATIVE INDEX

Weather patterns, Great Lakes region, 3:177 Weather prediction accuracy, effect of GPS-IPW data on, 4:248–249 Weather radar, for hydrologic real-time information, 1:126. See also Weather Surveillance Radar 1988 Doppler (WSR-88D) Weather Surveillance Radar 1988 Doppler (WSR-88D) observations, 4:310, 311 radar stations, 4:307 Weather systems, 4:352–355 understanding, 4:353 Wedderburn Number, 3:266 Weed control strategies, 3:742–748 alternative, 3:747 biological, 3:746–747 chemical, 3:745 environmental, 3:747 factors affecting, 3:744 mechanical, 3:744–745 Weeds, problematic, 3:479–484 Weighting factor, 3:258 Weight of evidence (WOE) approach, 2:381, 429; 4:600–601, 602–603 to sediment quality characterization, 2:350–355 Weir and orifice fish passage facility, 3:529–530 Weirs, flows through, 3:195 ‘‘Weir’’ type roof drainage, 1:56 Welland Canal, 3:177 Well-being, water and, 4:791–793 Well casing perforated in place, 5:574 Well contamination, in developing countries, 2:631 Well contamination prevention, 1:149–152 casing, 1:149–150 disinfection procedures, 1:151 filter pack, 1:151 pitless adaptors, 1:151 site selection, 1:149 well design for, 1:149 well screen, 1:151 well seals, 1:151 Well drawdown, 5:101–102 Wellhead protection (WHP), 1:524–529. See also WHP zones (WHPZs) delineation criteria and methods for, 1:525–526 management measures for, 1:527 Wellhead protection area (WHPA), 1:524

Wellhead protection plan (WHPP), 1:524 developing, 1:525 Well hydraulics, 5:101, 182–183 Well installation, water-jetting drilling technologies for, 5:234–235 Well jetting, 5:234 Well logs, studying, 5:81 Well maintenance, 5:263–266 data collection intervals related to, 5:265t methods, 5:264t predictive and preventive, 5:263–264 records and, 5:264 Wells. See also Intake wells; Irrigation wells; Water supply wells; Water well entries defined, 2:548 design and construction of, 5:87–91 horizontal, 5:177–178 installation of, 5:106 monitoring, 5:586–587 performance characteristics of, 5:87 radial, 5:407–408 site selection for, 5:88 types of, 5:571–572 water levels in, 5:572 Well screens, 3:415–416; 5:88, 572–574 lateral, 5:407 Well site control zone (WSCZ), 1:526 Well-spacing norms, in India, 2:558 Well test, 5:574–575 Well water analysis of, 5:407 blue baby syndrome and, 2:219 Well yield, 5:101 Welwitschia mirabilis, 4:200–201 Wenner array, 5:445 West Antarctic ice sheet, 4:118 Western blotting, 2:109 Western United States irrigation in, 3:587 protection of in-stream values, 4:660–662 water markets in, 2:500 water rights adjudications and permit proceedings in, 4:672 water use in, 2:646–647 Wet ash discharges, 1:556 Wet covers, 5:3 Wet desulfurization processes, 1:849

845

Wetland ecosystems, 3:57–58, 59 productivity of, 3:490 Wetland hydrology, 4:577 Wetland management, politics of, 4:691–692 Wetlands, 3:489–493. See also Coastal wetlands; Constructed wetlands benefits of, 3:364 characteristics of, 4:695 classification of, 3:496–498 constructed, 5:5 EPA protection of, 3:494 federal agencies involved in protecting, 4:692t forested, 3:172 functions of, 3:490–492 Great Lakes region, 3:177 groundwater and, 5:605 N and C transformations in, 5:329 organic acidity in, 3:4 overview of, 3:496 passive treatment of, 2:423–426 physicochemical properties of, 3:367 protecting and restoring, 3:494–496 remote sensing of, 4:325 role in watershed hydrology, 3:172–173 sanitary impact of, 1:404 support of flora and fauna, 3:492 terms related to, 3:59 tidal, 3:72 values attributed to, 3:492–493 vertical flow, 5:6 water recycling for, 2:612 Wetlands loss, 3:73, 173 precautionary principle regarding, 2:600 Wetlands policy conservation- and restoration-related, 4:693 legislation and litigation related to, 4:691 in the United States, 4:690–694 Wetland treatment, 5:328–329 Wet periods, role in flooding, 3:144 Wet signal delay (ZWP), 4:245 Wet sluicing, 1:851–852 Wet soils, 5:461 Wetted steel tape method, 5:101 Wet thermometer, 4:273 Whole cell fluorescent in situ hybridization, in community analysis, 1:645

Water Encyclopedia: Domestic, Municipal, and Industrial Water Supply and Waste Disposal (Vol. 1) Water Encyclopedia: Water Quality and Resource Development (Vol. 2) Water Encyclopedia: Surface and Agricultural Water (Vol. 3) Water Encyclopedia: Oceanography; Meteorology; Physics and Chemistry; Water Law; and Water History, Art, and Culture (Vol. 4) Water Encyclopedia: Ground Water (Vol. 5)

846

CUMULATIVE INDEX

Whole effluent toxicity controls, 2:382–383 Whole effluent toxicity testing protocols (EPA), 2:382 Whole pipe repair and renewal, 1:887–888 Whole water exchange rates, 4:540 WHO water reuse guidelines, 3:670–672 WHP zones (WHPZs), 1:524, 526–527 Wick lysimeter, 2:340 Width function, 3:94 Wiener–Khintchine theorem, 4:339 Wildlife, vulnerability to pollutant discharge, 3:284 Wilkes, 4:John, 794–796 Willis sand zone, 3:67 Wind creation of, 4:293 as a forcing factor, 3:322 Windage, 1:559 Windermere humic aqueous model (WHAM), 2:206 version 6 program, 5:141 Wind erosion, 3:566; 5:125 control of, 3:551, 568–569 Windmills, 1:73–75 history of, 1:74 Wind pumps, 1:74–75 advantages and disadvantages of, 1:75 Windrow piles, 1:648, 649 Wind speed, estimating, 4:2 Wind turbines, 1:75 Wind wave forecasting, 4:139 Wire line coring technique, 5:105 Wire wrap screen, 5:573 Wisconsin Department of Natural Resources wastewater model, 1:731 Wisdom, free flowing water as a source of, 4:793–797 ‘‘Wise use’’ policy, for wetlands, 3:492 Witching, 5:92–94 Withdrawal. See also Water withdrawal(s) defined, 2:548 uses for, 2:661–662 Women’s water rights, 4:771 Woods Hole as base of the fisheries service, 4:143 financial disaster in, 4:141 fishing activity at, 4:142

history of, 4:139–144 as a scientific center, 4:141–142 zoological work at, 4:144 Worker safety, pretreatment programs and, 1:800 Workplace, water conservation in, 2:664–666 Works Progress Administration (WPA), 2:511, 513 World Bank Water Research Team, 1:14–15 World Health Organization (WHO), 1:20, 23, 31. See also WHO water reuse guidelines arsenic-related guidelines, 2:8 basic water requirement of, 1:497 radioactive contamination guidelines of, 1:803 water quality standards, 2:267 World Meteoric Water Line (WMWL), 4:439 World Ocean Circulation Experiment (WOCE), 4:22 World public water supply, 1:500–507 World Water Council, 1:387 World water industry, key trends in, 1:508–510 Wortley, Stuart, 4:766 WWTP monitoring, 2:48 XANES spectroscopy method, 2:207 Xanthates, 1:686 Xenobiotic industrial compounds, 5:43 Xenobiotics, 2:42 Xeriscape design, 3:750–752 benefits of turfgrass in, 3:750–751 challenge of, 3:752 practical turf areas in, 3:750 principles of, 3:751 Xeriscape landscaping, principles of, 3:555 Xeriscaping, 2:548 Xiaolangdi Reservoir, 3:48, 49 X-ray photoelectron spectroscopy (XPS), 4:491 Yamuna River, 3:234. See also River Yamuna, India Yangtze River, flooding of, 3:143 Yarra River, Australia, water quality software for, 2:328–330 Yarra River Water Quality Model (YRWQM), 2:334, 335

linking with genetic algorithm software, 2:334 Yellow River current flood control in, 3:48–49 flood analysis in the lower reach of, 3:49–50 historical flood management in, 3:47–48 reducing flood risk for, 3:49 Yellow River Basin flood control in, 3:45–50 sediment in, 3:46–47 Yersinia enterocolitica, 1:278 Yield, 2:548 water productivity, 3:560 Young groundwater, dating using tritium/helium ratios, 5:71–72 Zebra mussel control, chemical-free, 1:510–514 Zenith-scaled hydrostatic delay (ZHD), 4:245 Zenith tropospheric delay (ZTD), 4:245 Zeolites, sorption by, 1:874 Zero matric potential, 5:533 Zero-order degradation, 5:32 Zero-pressure balloons, 4:165 Zero-tension lysimeters, 2:340; 5:488, 489 Zero valent metals (ZVMs), 2:300 Zero Waste America, 4:148 Zinc (Zn) bioavailability in soils, 5:370 in groundwater, 2:148 phytoextraction of, 5:369– 374 uptake of, 2:217 Zinc hyperaccumulation, molecular basis of, 5:371–372 Zinc ions, sorption of, 1:588f ZoBell solution, 2:466–467 ‘‘Zone of noncompliance,’’ 3:81 ‘‘Zone of passage,’’ 3:81 ‘‘Zone’’ settling, 3:404 Zoogloeal growth, 1:730 Zoonoses, 1:178 Zooplanktivorous fish, algal control and, 2:6 Zooplankton, 4:154–155 effect of road salt on, 2:323 trace elements in, 3:456 Zooxanthellae, 4:33 Zwitterionic surfactants, 1:670

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