Yellow River, The: Water And Life 9789814280969, 9789814280952

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World Scientific

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Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE

British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library.

THE YELLOW RIVER Water and Life Copyright © 2010 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher.

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ISBN-13 978-981-4280-95-2 ISBN-10 981-4280-95-X

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Gregory - The Yellow River.pmd

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Preface

Due to climate change, it has become common knowledge that fluctuations of annual precipitation and precipitation intensity have been larger especially since the 1970s. The 4th Synthesis Report by the Intergovernmental Panel on Climate Change (IPCC) says that global warming is unequivocal and that enduring snow cover and glaciers have been receding, thus torrential rain and serious drought occur more frequently. These phenomena associated with increasing water demand due to an increase in population and rise in living standards and increasing degradation of aquatic environment will give human beings urgent tasks toward maintaining a future sustainable society. Integrated River Basin Management (IRBM) was advocated at least four decades ago. Although we understand the concept of IRBM, research work has been done only on water resources allocation and pollution control of receiving water bodies. IRBM has to include policies, social systems as well as cultural background, such that reduction in water resources allocation to the agricultural sector needs social countermeasures for excess workforce and import of food. This book contains in part, research results on the five-year project on “Efficient and sustainable water use in the Yellow River, China”. The important topics on water and sediments in the Yellow River are presented in six major sections: Profile of the Yellow River Basin, Water Resources and Use, Water Quality and River Ecology, Sediment Yield and Transport in the Middle Yellow River Basin, Modeling and Simulation on Water in the Yellow River, and Projection of Water Supply and Demand with Economy and Food Supply in the Yellow River Basin. All chapters are written by leading experts in our project team, in which the total researchers number 102. Chapter 2 provides the background information necessary to understand the characteristics of the Yellow River. Chapter 3 provides background information on water-use in the river. Direct observation results on water quality in tributaries near Xi’an are presented in Chap. 4. Chapter 5 explains that sediment yield and transport is of importance in the Yellow River where 1.6 billion tons of sediments are annually transported in the Bohai Sea. Chapter 6 provides a hydrological model with high precision and some simulation results.

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The last chapter, Chap. 7, provides some estimation results on water-use based on several economic scenarios. We hope that you will find this book to be full of the latest information obtained by researchers on the Yellow River and that you will be able to grasp the environmental problems on water which China is facing. We gratefully acknowledge the establishment of a basic research promotion program in CREST (Core Research of Evolutional Science and Technology), which is related to water resources and aquatic environment, and the financial support by Japan Science and Technology Agency. I, as a team leader, extend sincere appreciation to all the researchers who had been working for five years from 2002 to 2007. Finally, we thank all research associates and graduate and undergraduate students for being a source of inspiration and encouragement to me. Editor Tetsuya Kusuda Kyushu University, Fukuoka, Japan

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Contents

Preface

v

List of Contributors

xi

List of Images

xiii

1.

Introduction Tetsuya Kusuda

1

2.

Profile of the Yellow River Basin Dawen Yang and Hiroshi Ishidaira

5

2.1.

2.2.

2.3.

Characteristics of the Nature . . . . . . . . . . . . . . 2.1.1. Morphology . . . . . . . . . . . . . . . . . . . 2.1.2. Geology . . . . . . . . . . . . . . . . . . . . . 2.1.3. Climate . . . . . . . . . . . . . . . . . . . . . . Human Activities . . . . . . . . . . . . . . . . . . . . 2.2.1. Population distribution . . . . . . . . . . . . . . 2.2.2. Land use . . . . . . . . . . . . . . . . . . . . . 2.2.3. Urban and rural lives . . . . . . . . . . . . . . . 2.2.4. Agriculture . . . . . . . . . . . . . . . . . . . . 2.2.5. Industry . . . . . . . . . . . . . . . . . . . . . 2.2.6. Production and economics . . . . . . . . . . . . Socio-Economic States . . . . . . . . . . . . . . . . . 2.3.1. Strategic situation of the Yellow River in history 2.3.2. Socio-economic conditions in the basin . . . . . 2.3.3. Policy of development in the basin . . . . . . . 2.3.4. Administration in the basin . . . . . . . . . . . 2.3.5. Social problems on water in the basin . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . .

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3. Water Resources and Use Dawen Yang, Kyoichi Otsuki, Tetsuo Kobayashi, Daisuke Yasutake, Hiroyuki Cho, Masaharu Kitano, Makito Mori, Tugihiro Watanabe, Kuniyoshi Takeuchi, Hiroshi Ishidaira and Changrong Yan 3.1. Water Resources Availability . . . . . . . . 3.1.1. Precipitation/snow melting . . . . . 3.1.2. Potential evaporation . . . . . . . . 3.1.3. Runoff and river flow . . . . . . . . 3.1.4. Water storage . . . . . . . . . . . . 3.1.5. Groundwater resources . . . . . . . 3.2. Water-Use . . . . . . . . . . . . . . . . . . 3.2.1. Forest . . . . . . . . . . . . . . . . 3.2.2. Irrigation . . . . . . . . . . . . . . . 3.2.3. Industrial use . . . . . . . . . . . . . 3.2.4. Consumption of water in urban areas References . . . . . . . . . . . . . . . . . .

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4. Water Quality and River Ecology Tetsuya Kusuda and Osamu Higashi 4.1. Water Quality in the Yellow River Basin . . . . . . . 4.2. Water Quality in the Wei River Basin . . . . . . . . . 4.2.1. Sources of pollutants . . . . . . . . . . . . . . 4.2.2. Pollutant unit loads and loading rates . . . . . 4.3. Water Quality in the Wei River . . . . . . . . . . . . 4.3.1. Observational results . . . . . . . . . . . . . . 4.4. Simulation with an Integrated Model on Water Quality and Quantity . . . . . . . . . . . . . . . . . . . . . . 4.4.1. Integrated model of water quantity and quality 4.4.2. Computational results . . . . . . . . . . . . . 4.4.3. Toward future . . . . . . . . . . . . . . . . . 4.5. River Environment in Xi’an . . . . . . . . . . . . . . 4.5.1. Urban areas . . . . . . . . . . . . . . . . . . 4.5.2. Effects of reservoirs . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . .

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Contents

5.

Sediment Yield and Transport in the Middle Yellow River Basin Haruyuki Hashimoto, Hiroki Takaoka, Takahito Ueno and Byungdug Jun

105

5.1. 5.2.

105 107 107 107

5.3.

5.4. 5.5. 5.6.

6.

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Sediment Yield . . . . . . . . . . . . . . . . . . . . . . . . . . Fluvial Geomorphology . . . . . . . . . . . . . . . . . . . . . 5.2.1. Analytical framework . . . . . . . . . . . . . . . . . . 5.2.2. Analysis of geographic information and satellite images 5.2.3. Comparison of the eight tributaries in the middle reach of the Yellow River . . . . . . . . . . . . . . . . . . . Field Measurements of Flood Flows . . . . . . . . . . . . . . 5.3.1. Rainfall–runoff relationships . . . . . . . . . . . . . . 5.3.2. Sediment particle size in flood flows and on riverbeds . 5.3.3. Relationship between discharge and sediment transport rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.4. Flow resistance . . . . . . . . . . . . . . . . . . . . . Formula for Flow Resistance and Sediment Transport . . . . . Comparison among Theoretically Calculated, Experimental and Observed Results . . . . . . . . . . . . . . . . . . . . . . . . Analysis of Flood and Sediment Runoff . . . . . . . . . . . . . 5.6.1. Rainfall–runoff analysis . . . . . . . . . . . . . . . . . 5.6.2. Riverbed variation analysis . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . .

108 109 109 114 115 117 118 120 122 122 122 124

Modeling and Simulation on Water in the Yellow River Dawen Yang

127

6.1.

127 127 128 131 136 138

Hydrological Model and Simulation . . . . . . . . . . . . . . 6.1.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . 6.1.2. Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.3. Description of the hydrological model . . . . . . . . . 6.1.4. Model calibration and validation . . . . . . . . . . . . 6.2. Analysis of Water Resources in the Last Half Century . . . . . 6.2.1. Spatial and seasonal distributions of water resources for a long-term mean . . . . . . . . . . . . . . . . . . . . 6.2.2. Decadal variation of water resources . . . . . . . . . . 6.2.3. Inter-annual variability of water resources . . . . . . . 6.2.4. Reason for the drying-up in the main river along the lower reach over the last 30 years . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . .

138 142 144 145 148

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The Yellow River: Water and Life

Projection of Water Supply and Demand with Economy and Food Supply in the Yellow River Basin Hidefumi Imura, Hiroaki Shirakawa and Akio Onishi 7.1. Analysis of Current Water-Use Using the Water Resource Supply-Demand Model . . . . . . . . . . . . . . . . . . . . . 7.1.1. Overview of the model . . . . . . . . . . . . . . . . . 7.1.2. Structural changes in water resource supply and demand (1997–2000) . . . . . . . . . . . . . . . . . . . . . . . 7.2. Impacts of Economic Growth and Urbanization on Water Resource Supply-Demand Balance . . . . . . . . . . . . . . . 7.2.1. Regional economic growth scenarios . . . . . . . . . . 7.2.2. Water supply-demand gaps in the Yellow River basin . . 7.2.3. Analysis by watershed . . . . . . . . . . . . . . . . . . 7.3. Impacts of Changes in Food Demand on Water Resources . . . 7.4. Toward the Future . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Index

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153 153 155 159 159 162 163 169 170 172 173

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List of Contributors

1. Introduction Tetsuya Kusuda Kyushu University, Fukuoka, Japan 2. Profile of the Yellow River Basin Dawen Yanga and Hiroshi Ishidairab a Tsinghua

University, Beijing, China University, Yamanashi, Japan

bYamanashi

3. Water Resources and Use Dawen Yanga , Kyoichi Otsukib , Tetsuo Kobayashib , Daisuke Yasutakec , Hiroyuki Chob , Masaharu Kitanoc , Makito Morib , Tugihiro Watanabed , Kuniyoshi Takeuchie , Hiroshi Ishidairaf and Changrong Yang a Tsinghua

University, Beijing, China University, Fukuoka, Japan c Kochi University, Kochi, Japan d Research Institute for Humanity and Nature, Kyoto, Japan e International Centre for Water Hazard and Risk Management (ICHARM), Tsukuba, Japan f University of Yamanashi, Japan g Institute of Environmental and Sustainable Development in Agriculture, CAAS, China b Kyushu

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4. Water Quality and River Ecology Tetsuya Kusudaa and Osamu Higashib a Kyushu b Nagoya

University, Fukuoka, Japan University, Nagoya, Japan

5. Sediment Yield and Transport in the Middle Yellow River Basin Haruyuki Hashimotoa , Hiroki Takaokab , Takahito Uenoc and Byungdug Jund a Kyushu

University, Fukuoka, Japan University, Nagoya, Japan c Sojo University, Kumamoto, Japan d Nagasaki University, Nagasaki, Japan b Nagoya

6. Modeling and Simulation on Water in the Yellow River Dawen Yang Tsinghua University, Beijing, China 7. Projection of Water Supply and Demand with Economy and Food Supply in the Yellow River Basin Hidefumi Imuraa , Hiroaki Shirakawaa and Akio Onishib a Nagoya

University, Nagoya, Japan Institute for Humanity and Nature, Kyoto, Japan

b Research

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List of Images

1. The monument of the head of the Yellow River with local people’s ritual decoration 2. The Eling Lake at the head of the Yellow River 3. Nine Curves in Qinghai Province 4. Liujiaxia Reservoir in Qinghai Province (constructed in 1968) 5. Shapotou (arid zone) in Ningxia Autonomous Region 6. Sanchenggong Weir (right) and intake gate (left) in Neimenggu Autonomous Region 7. Lanzhou City in Gansu Province 8. Hukou Fall in Xiaanxi Province 9. Moding River Basin in Xiaanxi Province 10. Xiaolangde Reseavor (downstream view) in Henan Province 11. Huayuankou Gauging Station in Henan Province 12. Lijin Gauging Station in Shandong Province

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Chapter 1

Introduction

Tetsuya Kusuda Kyushu University, Fukuoka, Japan

The river basin water management is one of the most important global issues. Social demands to water management, such as flood control, water utilization, sediment transport control, navigation, landscape, biotic integrity and recreation, have been increasing yearly, and water management is expected to respond effectively to all of them. Countries located at low latitude have high precipitation through the year. However, other regions have seasonally changing precipitation in general. On the other hand, there are many countries located in arid and semi-arid areas, and people living in the regions have difficulty obtaining water resources. In arid and semi-arid areas, infrastructure, such as reservoirs and water transfer, play a more important role than in the other areas. Water utilization is closely linked to food production. In the world, agricultural water use accounts for 70% of the total water use. Aside from food production, secure employment is a socially expected role for the agricultural sector, especially in developing countries. Therefore, agriculture in the future is of foremost concern for water management. Allocation of water resources to the sectors — agriculture, industry, daily lives, and ecosystem — is an essential part of water management for social stability and sustainability. Water circulation in an open system is seen in the agricultural sector where the amount of water decreases with evapotranspiration. On the other hand, a closed system in the industrial and domestic sectors where only water quality is lowered and the water amount does not decrease, net water consumption is decreased by reuse and/or recycling. Meanwhile, it is possible to produce water by desalination. In developed countries, water can be made with an appropriate cost. But “making water” is not recommended, as it requires a large amount of environmental loading and 1

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fossil-fuel consumption. Groundwater abstraction is increasing in recent years, and it has accelerated ground subsidence and the depletion of natural water resources. Polluted freshwater does not work as water resources. Current wastewater treatment technologies can remove any pollutants from polluted water. However, the applicability of them depends on economics. Even if there is no water pollution in arid and semi-arid areas, much evapotranspiration in the open system causes salt damage. Salt damage is already prevalent in many places in the world, thus, it is not unusual. As a result, some devices to use water efficiently in cultivated areas are needed. Water exists not only for humans, but also for plants and animals. It is difficult to determine economic values of water for them, therefore it is not easy to involve them in water management. Water transports substances, such as sediment. The variability of river discharge makes some important roles for sediment transport as well as living organisms. Keeping a steady state in river water flow is not well for them. The object area of water management is basically a river basin. However, considering that water involved in products and substances, which are not concerned only with water use, the related area of water management may be expanded outside the basin and into the world. At any rate, in arid and semi-arid areas with water shortage problems, a more appropriate allocation of water resources to all sectors has to be considered. The Yellow River basin, located in the semi-arid and arid climate zones in northern China, is confronted with serious problems of water deficit as well as water pollution. The Yellow River basin has about a hundred million in population and 752,000 km2 of catchment area. With regard to increasing human activities and climate changes, the usage of water with high efficiency is a key requirement to the development of the basin. Due to increasing population, rising living standards, increasing pressure of expanding irrigation areas and developing industries in this basin, water resources allocation has been a major issue. This issue may seem domestic, but in reality, it is international, as it impacts other countries through trades of industrial products of food and human activities. Development in the basin is limited by water shortage, salinity damage and pollution. There are many scenarios on the allocation of water resources. One extreme is industry-oriented while the other is agriculture-oriented. If China targets the former scenario, industries in other advanced countries would decline through trade competition. A high unemployment rate would occur, which would be followed by social instability (unless other sectors such as the service sector

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absorbs the unemployed labor power). If China targets the latter, the income of its people would hardly increase, although social stability would be kept. This is an Achilles heel for the Chinese government. Even if the allocation of water resources among the sectors is determined, the allocation between upstream and downstream remains another issue. This book discusses issues like these from the point of water resources and gives several ideas on the countermeasures to be taken. As the contents of this book is based on research results of a five-year project: “improving the sustainability in utilizing and controlling water in the Yellow River basin” sponsored by Japan Science and Technology Corporation (JST), all the content inside is newly obtained and full of new ideas and concepts.

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Chapter 2

Profile of the Yellow River Basin

Dawen Yanga and Hiroshi Ishidairab a Tsinghua

University, Beijing, China University, Yamanashi, Japan

bYamanashi

2.1. Characteristics of the Nature 2.1.1. Morphology The Yellow River basin originates from the Tibetan Plateau, wanders through the northern semi-arid region, crosses the Loess Plateau, passes through the eastern plain, and finally flows into the Bohai Gulf. TheYellow River flows about 5,500 km in distance in the main stream and accumulates water from 753,000 km2 of drainage area (Fig. 2.1).1,2 From the origin to the river mouth, the Yellow River experiences three typical landforms, the Tibet Plateau with elevations from 2,000 to 5,000 m, the Loess Plateau and midstream tributaries with elevations from 500 to 2,000 m, and the alluvial plain in the eastern part. Table 2.1 shows the regions with different characteristics in morphology.3,4 The highest ladder is the Tibetan (the Qinghai-Tibetan) Plateau. The Bayankala Mountain range in the South forms the shed between the Yellow River and the Yangtze River, and the Qilianshan Mountain wandering in the North forms the divide between the Qinghai-Tibetan Plateau and the Inner Mongolia Plateau. The East edge of this ladder is through Qilianshan Mountain, Linxia, Lintan, the Yaohe river, Minxian County and finally the Minshan Mountain from North to South. The highest peak in the Yellow River basin is the Anemaqen Mountain (Jishishan Mountain) with the height of 6,282 m in the middle of this area. Snow 5

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Fig. 2.1. The Yellow River basin. Table 2.1.

The Tibet Plateau The Loess Plateau and midstream tributaries

The alluvial plain

Regions with different characteristics in morphology. Region

Area (km2 )

Elevationa (m)

Upstream of the Lanzhou gauge Between the Lanzhou and Toudaoguai gauges Between the Toudaoguai and Longmen gauges Between the Longmen and Sanmenxia gauges Between the Sanmenxia and Huayuankou gauges Downstream of the Huayuankou gauge

222,551 145,347

3,560 1,418

129,654

1,241

190,869

1,244

41,615

695

21,833

78

a The mean elevation is calculated from the 1-km digital elevation model.

covers there all year round. The Anemaqen Mountain in the direction of northwestsoutheast meets with Minshan Mountain and forces the Yellow River to go around which forms the first of the nine crooks. In the second ladder, there are the Loess Plateau, the Ordos Plateau, the Hetao plain and the Weifen basin, etc. The Taihangshan Mountain is the East edge of this edge. This ladder is the main source for flood and drought and there are a lot of complex issues relating to meteorology and hydrology, as well as sediment eroding. The Inner Mongolia Plateau including the Hetao Plateau and the Ordos Plateau locates the common boundary of Ningxia Province, Shaanxi Province, and Inner Mongolia Province. The Hetao Plateau is from Zhongwei of Ningxia Province in

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the West to Tuoketuo of Inner Mongolia Province in the East with the length of 750 km and the width of 50 km. The Ordos Plateau (platform) is a dry and eroded Plateau, where wind-blown sand is developed well. The Kubuqi desert in the North, the Zhuozishan Mountain in the West, and the Great Wall in the East and the South encircle the Plateau like a valley, which results runoff into the salt lake and forms the water system of inner area with a drainage area of 42,300 km2 . The Loess Plateau is surrounded by the Great Wall in the North, Qinling Mountains in the South, the Qinghua Plateau in the West, and the Taihang Mountain range in the East. Broken-up morphology and channels result from the deep depth, looseness, and bareness of soil, as well as the strong weathering. Here is the main source of sediments in the Yellow River. The Weifen basin including the Guanzhong basin in Shaanxi Province, as well as the Taiyuan and Jinnan basins in Shanxi Province, has been known as a fertile and plenteous place. The Taihangshan Mountain in the East is the shed between the Yellow River basin and the Hai River basin. The Qinling Mountains in the South and the Funiushan Mountain and Songshan Mountain wandering to the East are the divide between the subtropic and temperate climates, the arid and humid regions, and the Yellow River, the Yangtze River and the Huai River. In the third ladder, there is the alluvial plain of the Yellow River basin from the East of the Taihangshan Mountain and Mangshan Mountain to the shore. The area is 250,000 km2 including part of Henan Province, Shandong Province, Hebei Province, Anhui Province, and Jiangsu Province and inclines slightly to the sea. The embankment of the Yellow River is the unstable shed in the topography of the plain, from which the northern and southern parts are called Huang-Huai and Huang-Hai plains, respectively. It has been well recognized that the climate, landscape, and the flow from West to East are determined by the morphology, i.e., the three ladders. The Tibetan Plateau has profound impact on climate and thus hydrology. Each year, the strongly dominating westerly carries the warm and humid vapor over the Indian Ocean, climbs and goes down the Tibetan Plateau, then gradually sinks and turns warmer as a result of the arid and/or semi-arid hydrological conditions upstream and in the middle reach of the Yellow River basin.

2.1.2. Geology The geological conditions control water circulation such as groundwater flow, evaporation, vegetation, etc. The distributions of soil properties, the saturated hydraulic conductivity Ks , and the porosity of soil φ are shown in Figs. 2.2 and 2.3.

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Fig. 2.2. Distribution of saturated hydraulic conductivity (Ks ).

Fig. 2.3.

Distribution of porosity (φ) (volume fraction).

2.1.3. Climate The climate conditions vary from cold to temperate zones and change from arid and semi-arid to semi-humid regions. The mean annual precipitation is 452 mm and is spatially distributed as shown in Fig. 2.4. Rainfall in the Yellow River basin occurs in 7 monsoon months (April to October) and more than 60% of the annual

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Profile of the Yellow River Basin

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Fig. 2.4. The distribution of the mean annual precipitation.

Fig. 2.5.

Distribution of mean temperature.

precipitation during June–September. The precipitation varies greatly within a year and from year to year. The monthly-averaged temperature and precipitation show similar patterns consisting of peaks in July and troughs in January or December. The spatial distribution of the mean temperature is shown in Fig. 2.5.

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Flood and drought were the twin disasters in the long history of the Yellow River basin. The Chinese government spent a great effort in reservoir construction and dike building for water resources and flood management. Flood threats remain but water scarcity becomes more serious.5 The Yellow River has four kinds of floods in a year: peach flood, summer flood, autumn flood and ice-run flood. The summer flood is caused by heavy storms. The autumn flood is caused by an unbroken spell of wet weather during the period from September to October. The summer flood and autumn flood are the most dangerous, usually called (summer and autumn floods). The ice-run flood is caused by ice blocks in winter which make the water level rise suddenly and threaten the safety of the embankments in the sections of Ningxia Province, Inner Monggolia Autonomous District, Henan Province and Shandong Province. The peach flood happens during March and April while peach trees are blossoming, ice and snow melt in the upper reaches, thus causing a water level rise in the lower reach. Regarding the flow condition in the lower reach of the Yellow River, three typical periods were identified during the last half century, which were the period from the 1950s to the 1960s with no drying-up events, the 1970s and the 1980s during the period of which drying up was infrequent, and the 1990s when drying-up event occurred yearly.6,7

2.2. Human Activities 2.2.1. Population distribution Ancient people started to inhabit the Yellow River basin about a million years ago. Stone Age cultural ruins have been widely found in the basin where plenty of systematical cultural relics of the mankind in different periods are preserved. Inscriptions on bones or tortoise shells recording the human history have also been excavated along the Yellow River. The Chinese civilization originated mainly from the middle and lower reaches of this basin about 4,000 years ago. The Yellow River basin is called the “cradle” of the Chinese people.8 According to statistics in 2006, a population of 107 million settled in the Yellow River basin, which was about 8.6% of the total population in China. Water from the Yellow River nurtures about 140 million people, which is 10% of the total population in China. The population distribution in each province in/along the Yellow River is shown in Table 2.2 (Fig. 2.6 on provinces). The population density ranges widely from upstream to downstream. Qinghai Province has the lowest population density (7 persons/km2 ); Shaanxi and Shanxi Provinces are in the middle (175 and 206, respectively); Henan and Shandong Provinces have the highest population density (575 and 590, respectively).

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Table 2.2.

Midstream Downstream

Qinghai Gansu Ningxia Inner Mongolia Shaanxi Shanxi Henan Shandong

Provincial population

Population in the Yellow River*

Total number (million)

Natural growth rate (%)

Density (person/km2 )

Total number (million)

% of province total

% of the basin total

Density (person/km2 )

5.52 26.17 6.10 24.05 37.48 33.93 93.60 93.67

0.88 0.65 0.98 0.45 0.41 0.53 0.49 0.50

7.66 58.15 91.87 20.33 182.81 217.52 560.49 612.22

1.45 9.62 4.90 4.23 26.18 23.01 24.85 83.04

26.25 36.78 80.30 17.60 69.88 67.82 26.56 88.65

0.74 5.46 2.65 2.38 14.61 12.72 14.85 46.59

9.47 67.30 97.97 28.41 196.89 234.83 690.49 5,931.49

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Upstream

Province

Profile of the Yellow River Basin

Region

Demographic characteristics of the Yellow River basin (2007).

Source: (National Bureau of Statistics, 2008).10

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Fig. 2.6.

Provinces and counties along the Yellow River basin.

According to the data from the World Development Indicators,9 the rural population declined continuously in China from the early 1970s through to the 1990s, which was mainly caused by China’s one-child policy. From the mid 1990s, the rural population growth rate became negative and continued to decline progressively. Up to the late 1980s, over three-quarters of China’s population lived in rural areas. During the 1990s, the ratio of rural population to total population has declined progressively, from around 73% in 1990 to 63% in 2001.9 It is also noted that the rural population growth rate was higher than the national growth rate. The female population is larger than males in all provinces in the Yellow River basin.

2.2.2. Land use The drainage area of the Yellow River takes 8.3% of the total country area of China. The cultivated land is 11.93 million ha. The forest land is 10.2 million ha. In addition, about 2 million ha of wasteland is available for cultivation as shown in Fig. 2.7. Approximately 80% of the basin area is dry land. The forest takes about 1.5% of the area, grassland about 60%, cropland 29.5%, and wetland 1.1%. Most of the grazing land is located in the upper reach of the Yellow River, while cultivated land

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Fig. 2.7.

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Land use in the Yellow River Basin.

is mainly in the middle and lower reaches. The irrigated agriculture area accounts for 7.2% of the area, and the urban and industrial areas account for 6%. Agricultural irrigation began more than a thousand years ago in the basin. In ancient times, irrigation occurred mainly in the Wei River basin near Xi’an and downstream of the Qingtongxia dam, but, needless-to-say, neither dam nor weir existed at that time. Vast irrigation projects were developed after 1949, mainly during the period from the end of the 1950s to the beginning of the 1970s in the upstream of the Huayuankou gauge. In the 1970s and 1980s, the irrigation areas were widely expanded to the outside of the basin along the lower reach from the Huayuankou gauge. The irrigation area has increased by nearly a factor of ten during the last 50 years. Large irrigation projects with areas of more than 20,000 ha are managed by the Irrigation Department of the Ministry of Water Resources. These large projects provide irrigation to 7.13 million ha at the present time, sharing about 72% of the total irrigation area. It should be mentioned that most of the irrigation areas along the lower reach (the downstream of the Huayuankou gauge) are not located in the drainage basin because of the suspended river in the downstream. Regarding agricultural irrigation, water was particularly badly misused by over-irrigation during the three years from 1959 to 1961. Salinization became a serious problem in a large portion of the irrigated areas with poor drainage systems, especially in Inner Mongolia and downstream the Huayuankou gauge.

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Farmlands in these areas lost their productive capacity. For this reason, irrigation was even stopped in the Inner Mongolian District and in the downstream from 1962. By improving the drainage system, irrigation in the salinized areas gradually recovered from 1966. Major improvement in the drainage systems was made during the end of the 1970s and the 1980s. With an increasing pressure from population increase, the irrigation areas continuously expanded, especially in the downstream. Consequently, water shortages became more and more serious, and the lower reach dried up during the irrigation season from 1972 to 2000. The duration of the drying up increased rapidly in the 1990s. In the most serious situation encountered in 1997, the main river close to the sea dried up for 226 days, and the no-flow distance reached 704 km from the river mouth.

2.2.3. Urban and rural lives During the recent two decades, urbanization has increased rapidly in the Yellow River basin. In the year of 2000, the urbanization rate was estimated at around 26%. The main urban centers with population exceeding one million include Xining, Lanzhou,Yinchuan, Baotou, Hohehot, Taiyuan, Xi’an, Luoyang and Jinan. Excessive population for agriculture in rural areas, income difference between rural and urban areas and increasing demand for labor in the urban are main reasons for rapid urbanization. Rapid urbanization also increases the water demand and induces serious water pollution. Table 2.3 lists the employed laborers in the basin in 1998. As seen in the table, more than half of the total labor force was for agriculture purposes. Table 2.3. Region

Upstream

Employment by residence in Yellow River basin (by the end of 1998).

Province

Qinghai Gansu Ningxia Inner Mongolia Midstream Shaanxi Shanxi Downstream Henan Shandong

Total labor (million)

2.30 11.76 2.60 10.07 18.02 14.29 50.00 46.57

Source: (National Bureau of Statistics, 1999).10

Urban area

Rural area

Labor number (million)

% of the total labor

Labor number (million)

% of the total labor

0.68 2.69 0.78 4.00 4.46 4.59 9.32 10.61

30% 23% 30% 40% 25% 32% 19% 23%

1.62 9.07 1.81 6.07 13.56 9.70 40.67 35.96

70% 77% 70% 60% 75% 68% 81% 77%

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15

The diets of people in the Yellow River basin have changed as a result of the urbanization, economic development and the supply of food. One major change in diet is an increase in meat consumption. It is reported that the average meat consumption in China has increased from 39 kcal per capita per day in 1961–1963 to 286 kcal in 2000. Increasing meat consumption will enlarge grazing land. The changes in diet are also due to changes in agricultural production. Now, people in China eat more vegetables, fruit, sugar, vegetable oil, and fish. Consequently, much cropland has been converted to orchards, vegetable land, and fish ponds.12 The upstream provinces have a higher ratio of illiterate and semi-literate in China. Using the official poverty definition of per capita income, less than US$625 per year, the average incidence of poverty in the Yellow River basin has been estimated at 11.8%. While official data on poverty incidence in the rainfed areas alone do not exist, some research results suggested an incidence of at least 5% higher than the basin average. Not only are off-farm income opportunities frequently not available to agricultural households in many of the rain-fed areas, but crop diversification opportunities are largely limited by agro-ecological conditions. Agriculture is generally the predominant source of income for households in the Yellow River basin, and, therefore, successful means of increasing agricultural productivity and water use efficiency of agriculture contribute to the improvement of farmers livelihoods. Table 2.4 presents the income, consumption information of rural households in the basin in 2007. Again, the upstream basin was the poorest in the entire country. Urban household consumption was 3 to 4 times higher than in the rural areas in both upstream and midstream regions, while Gansu Province had the highest urban-rural difference of 4.4 times.

Table 2.4. Region

Upstream

Midstream Downstream

Household consumption in the Yellow River basin in 2007.

Province

Qinghai Gansu Ningxia Inner Mongolia Shaanxi Shanxi Henan Shandong

Households value (yuan) All

Rural

Urban

Urban/rural

4,978.0 4,274.0 5,816.0 7,062.0 5,272.0 5,525.0 5,141.0 8,075.0

2,446.5 2,017.2 2,528.8 3,256.2 2,559.6 2,682.6 2,676.4 3,621.6

7,512.4 7,875.8 7,817.3 9,281.5 8,427.1 8,101.8 7,826.7 9,666.6

3.1 3.9 3.1 2.9 3.3 3.0 2.9 2.7

Source: (National Bureau of Statistics, 2008).11

Rank among 31 provinces in 1998 25 29 16 10 21 19 23 8

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2.2.4. Agriculture According to national statistic data in 2000, the population in theYellow River basin is 110 million, which is 8.7% of the total population in China. The urbanization ratio in this basin is 26%, which is lower than the average level of the whole country. There were 810 million people living in the rural areas of the Yellow River basin. The Yellow River basin has been the agricultural zone since several thousands years ago. The Hetao Plain between Ningxia and Inner Mongolia along the upper reach is one of the successful “Irrigation Agriculture” in the semi-arid region. And the basin between the Fen River and the Wei River along the middle reach is one of the major grain (mainly wheat and maize) and cotton production bases, which plays an important role on food production in China. Despite many differences in climatic factors, cropping patterns, infrastructure, and income levels over the Yellow River basin, the rain-fed agricultural areas of the provinces of Ningxia, Inner Mongolia, Henan and Shandong share many similarities. While part of these regions is situated on the highly erodible Loess Plateau, others are on sedimentary deposits. However, the rain-use efficiency is quite low in the whole basin. Dry land area accounts for almost 6.6 million ha or approximately 57% of the cultivated land in the Yellow River basin, although the definition of “dry land” in China also includes areas that have some supplemental irrigation.

2.2.5. Industry A number of newly built industrial bases and cities have been set up in the Yellow River basin. Energy industries including coal, power-generation, petroleum and natural gas have obvious superiority in resources. Raw coal production occupies more than half of the nation’s total petroleum production. Non-ferrous metallurgical industries, like lead, zinc, aluminum, copper, molybdenum, tungsten and gold, as well as rare-earth metal industries, also have comparative superiority. According to the strategic layout of China’s economy development in the beginning of the 21st century, there are four special economic centers in the Yellow River basin. The first is the upstream bases of hydropower and non-ferrous metal surrounding Lanzhou City. The second center, Xi’an City, the composite exploit of economy and high technology, aims to be the technique guarantee center of development of the North China. The third center is the base of energy sources in the midstream of the Yellow River. It is one of ten concentrates of mineral sources in the West part of China, containing southern Shanxi, Shaanxi, Inner Mongolia and western Henan. The fourth center is the downstream part aimed at being the base of petroleum exploitation, the ocean and exports.

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Table 2.5. The GDP in the Yellow River basin (2005–2008). Region

Upstream

Midstream Downstream

Province

Qinghai Gansu Ningxia Inner Mongolia Shaanxi Shanxi Henan Shandong

Gross domestic product (100 million yuan) 2005

2006

2007

2008

543.3 1,934.0 606.1 3,895.6 3,675.7 4,179.5 10,587.4 18,516.9

641.6 2,276.7 710.8 4,791.5 4,523.7 4,752.5 12,496.0 22,077.4

783.6 2,702.4 889.2 6,091.1 5,465.8 5,733.4 15,012.5 25,965.9

961.5 3,176.1 1,098.5 7,761.8 6,851.3 6,938.7 18,407.8 31,072.1

Rank among 31 provinces in 1998 30 27 29 16 19 18 5 2

2.2.6. Production and economics Table 2.5 shows economic development in theYellow River basin. The GDP figures show that despite impressive GDP growth during 2005–2008 in the whole basin, the upstream provinces remain economically the most backward region in China, as indicated by their low rankings among the country’s 31 provinces.

2.3. Socio-Economic States 2.3.1. Strategic situation of the Yellow River in history Management of the Yellow River is recorded to have begun in the 20th century B.C. since Yu the Great successfully controlled flood in the Yellow River basin and started developing irrigation. He was the first manager of Chinese waters and later became an emperor of China. Around 2,280 B.C., Emperor Yao asked Yu to construct dams, dikes, and other waterworks along the Yellow River to protect and enhance life for his citizens. Yu the Great was so successful in reclaiming land and controlling floods that after the death of Emperor Shun, Yu became the new emperor of China. The most famous ancient irrigation project, the Zhengguo Canal, was completed in 246 B.C. in the Qin Dynasty. It irrigated some 80,000 ha of farmland in the North of the present Xi’an. This irrigation project made the Qin state become the strongest among the seven states during the ancient civil-war period and finally Qin unified the whole China. Before the Qin Dynasty, water management bureaucracies were relatively small in scale and scope in part of the Yellow River because of the kingdoms, which controlled part of the basin. As a result, early construction and management programs were undertaken largely to serve local, narrowly defined

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purposes. During the Han Dynasty, a new office known as the Director of Water Conservancy (Tu-shui) was created under the Ministry of Public Works. Modern efforts to comprehensively manage theYellow River basin can be traced back to the Chihli River Commission, and later the Hua Bei River Commission, which began the first systematic monitoring of the Yellow River flow in 1922. The Yellow River Water Conservancy Commission (YRWCC) was founded in 1933. The first commissioner of the YRWCC, Li Yi-chih, was perhaps the first person to advocate a basin level agency under the central government control to manage the Yellow River that could avoid China’s historically problematic inter-provincial tensions. Li Yi-chih, while a modern scholar, clearly placed his work within the context of ancient water management principles and Chinese philosophy and is considered one of the great managers in the long history ofYellow River Management. His influence and philosophy are still felt in the YRWCC’s predecessor agency, the Yellow River Conservancy Commission (YRCC), which was founded in 1946 in the Communist-controlled areas of Hebei, Henan and Shandong provinces. In June 1949, the responsibility for managing the whole basin was placed under YRCC and in November of the same year, the Commission was put under the leadership of the Ministry of Water Resources. In early 1950, YRCC was officially made a “basin management institution” under Order Number 1 of the State Council. The founding of the People’s Republic of China in 1949 ushered in fundamental changes in terms of water management and development. The new government changed its view of the Yellow River of it being a threat; projects were undertaken to control flooding and utilize river water to increase agricultural and energy production as well as expand transportation opportunities. There were a lot of irrigation and reservoir constructions in the 1950s. However, the majority of them were not well designed. After the huge engineering failure of Sanmenxia, similar failure of early irrigation projects, and the famine which occurred in the aftermath of the Great Leap Forward, the construction industry cooled down in the 1960s. The Cultural Revolution brought political chaos to China (including the Yellow River basin) while the moderately revised development plans of the 1950s and heavy government investment in the basin continued despite the chaos. The 1990s witnessed a new water era in China based on the reforms and their economic impacts, ushered in by Deng Xiaoping in the later part of the 1970s and the 1980s. While the changes of the 1990s have pushed water management in the Yellow River basin towards an integrated concept, the actual situation there continues to be one of overlapping levels of authority, unclear responsibilities, and competing interests. In 1998, the Ministry of Water Resources and the National Planning Committee issued the “Yellow River Available Water Annual Allocation

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and Main Course Regulating Scheme” and the “Management Details of Yellow River Water Regulating”, leading the way to the first basin-wide main course flow regulation which began the following year. A new water law passed in 2002 may give YRCC increased authority to act as a basin management organization, but the new goals of overall management still need to be met through the combined efforts of national, basin, provincial and local governments with various interests in agricultural, mining, industrial development and other endeavors as well as domestic use. The challenge for the 21st century is for the Chinese society to devise acceptable water management systems in the midst of rapid change, not only in water resource demands and supplies but also in social structures, institutions and thinking on economics, politics, and openness to the outside world.

2.3.2. Socio-economic conditions in the basin From ancient times, the Yellow River basin has been an important agricultural development zone in China. In the upper reach, agriculture was well developed in the Hetao Plain between Ningxia and Inner Mongolia regions. It was regarded as a successful model project of “Oasis Agriculture” in the arid-area. In the middle reach, the basin between the Fen River and the Wei River is one of the major agricultural bases of the country, where wheat, cotton, and corn products play an important role in China’s economy. The basin’s agricultural output is high with grain production surpassing 75 million tons or 16% of the nation’s total in 2000. However, most regions in the Yellow River have poor physical geography and ecological conditions, hence the food yield in the slopping infield is low, and the per capita share of the total grain production is a little lower than the national average. Although urbanization is increasing rapidly, about 75% of the residents in the Yellow River basin are still classified as “rural” and most of them depend on agriculture for their livelihoods. Income levels in the basin are, on average, a little lower than the national average and the basin accounts for some 7% of the national output. In 2007, there are still more than 100 counties in poverty which account for one-third of the counties in the whole basin. The Yellow River basin is at the nexus of important North-South and EastWest trade axes. Historically Xi’an, Lanzhou and other cities in the basin served as important points on the famous “silk road” and the crossing of the Yellow River by the Grand Canal marked an important transport hub. In more recent times, an important North-South and East-West rail junction was sited at Zhengzhou. At present, Lanzhou is a hydropower and non-ferrous metal base-center, Shanxi

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Province is an energy and chemical industry base-center, and Shandong Peninsula, an oil and sea base-center.

2.3.3. Policy of development in the basin The river discharges have been decreasing during the last half-century in theYellow River. In particular, drying-up of the lower reach in the main river has occurred since 1972, and the situation has become more and more serious during the 1990s. The conflicts between decreasing water supplies and rising water demands made water scarcity a more acute challenge than flood threat. The view shifted away from a singular emphasis on flood control toward a comprehensive basin management strategy. And also, an increasing awareness of the ecological value of the river emerged with the drying-up in the downstream. Water allocation policy: In order to allocate water in different provinces in and along the Yellow River basin, the administrative office of the State Council promulgated the Yellow River Water Allocation Plan in 1987. In this plan, all the provinces and autonomous regions are requested strongly to carry out water-saving measures. Based mainly on the “Water-taking Permits Implementation Action”, YRCC is responsible for implementing, supervising and managing the water-taking permits, in charge of the water-taking from the main stream and the major jointtributaries, and allocating the total water to each province and autonomous region along the Yellow River. Water-saving policy: Since 70% of the water consumption was for agricultural irrigation, irrigation water-saving is critical over theYellow River basin. The watersaving project has been made priority over other water development projects. For the water-saving project, National Development Bank and Agricultural Bank gave priority loans to the water-saving projects, while local governments prepared financial sources as the interest deduction for water-saving projects in farmland. The “Policy of Water Resources Industry” made by the State Council has published the guidelines for supporting water-saving irrigation projects. The Chinese government strongly emphasizes the improvement of water-saving technology, and water legislation for water-saving. Water pricing: For a long time, low water price has resulted in much waste of water in irrigation. The “Policy of Water Resources Industry” made by the National Council decreed that water prices should be changed according to the national water price policy and compensation, the rational benefit charge and different purposes, and timely readjustment of the management by changes in water supply cost. At present, the rational water price at the head of the canal on the lower Yellow River has been approved. A different water price and/or a progressive rate

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for excessive quota of water became one of the effective ways of dealing with waste water.

2.3.4. Administration in the basin The head office of YRCC is situated in Zhengzhou, Henan Province, and its branches are scattered in each province along theYellow River. By 1996, theYellow River basin has formed a complete system on management and development of the Yellow River taking YRCC as a unified unit (Fig. 2.8).

2.3.5. Social problems on water in the basin (1) Water Stress Flood control has been the primary issue inYellow River management in its history, now water stress has emerged as the first issue in recent decades. The rise of water stress as a critical issue has been caused by two main factors: a recent decline in water supplies due to dry climate and other factors, and an increase in demand. On the water supply side, the recorded rainfall, runoff and rainfall/runoff ratios were all substantially lower in the 1990s than in previous decades. On the demand side, the total consumption has increased by a significant percent over just a ten-year period. Geographically, this change can be decomposed into a reduction in lower reach consumption more than offset by increases in the upper, and especially, the middle reach. Partially in response to declining supplies and increasing demand, groundwater pumping has also increased dramatically over the past 20 years. Groundwater over-pumping has caused an extension of “funnels” and significant sinks. The outcome of declining supplies and increasing demand has already been the seasonal drying-up along the lower reach since the early 1970s. (2) The Continuing Threat of Floods Floods along the lower Yellow River mainly come from three regions of Hekouzhen-Longmen, Longmen-Sanmenxia and Sanmenxia-Huayuankou. Rainstorms in these three regions are frequent with high intensity and short duration. The formed floods have characteristics of high peaks and short transporting time. Especially the floods formed above the Sanmenxia gauge have very high sediment concentration and caused serious sedimentation on the lower reach. Main flood disasters have always occurred in the lower reach. The Xiaolangdi Reservoir, completed in 2000, plays great functions on flood control and sediment reduction for the downstream of the Yellow River. After Xiaolangdi Reservoir began operation, a flood with discharges from 13,000 m3 /s

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Yellow River Conservancy Commission Ministry of Water Resource P.R. China

22

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Yellow River Henan Bureau

6 district Yellow River divisions

Yellow River Shangdong Bureau

8 district Yellow River divisions

Sanmenxia Project Bureau with River Bureau

Hydrology Bureau

5 district water resource divisions

Yellow River Water Resources Protection

Reconnaissance, Planning, Design and Research Institute

Jindi River Bureau

Soil Conservation Supervision for Shanxi-Shaanxi-Inner

Upper and Middle Yellow

Mongolia contiguous areas

River Bureau 3 soil and water conservation stations Institute of Hydraulic Research

Yellow River Shanxi Division

5 county Yellow River divisions

Information Center

Telecommunication Division

Water Diversion and Irrigation Division

Fig. 2.8. Organization of the Yellow River conservancy commission.

(corresponds to about a hundred-year-return period) to 20,000 m3 /s (corresponds to about a thousand-year-return period) possibly happened between Xiaolangdi to Huayuankou, where the floods mainly occurred from out of the Xiaolangdi Reservoir. At the same time, the amount of water and sediment flowing into the downstream was changed greatly and the scouring and deposition and the river pattern of the lower river are also regulated correspondingly.

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(3) Soil Erosion The Yellow River flows through the Loess Plateau, an area of about 640,000 km2 covered with a thick Loess layer dozens of hundred meters deep. The soil of the Loess Plateau is ripped down in massive quantities into the Yellow River and its tributaries, in particular during the concentrated rainstorms in the summer season. As a result, the Yellow River is estimated to have carried an average of 1.6 billion tons of sediment each year in recent decades. Of the total sediment, only about 25% is carried through to the sea, and the remainder is deposited in the riverbed and flood plains. As a result, the bed of the river has risen at an average rate of 5–10 cm per year, and flood control embankments have been periodically raised in response. Sediment transported and its impact on channel dynamics have made governance of the river in its lower reach very difficult. (4) Water Quality and the Environment Water in the Yellow River has been seriously polluted. Waste water discharge of the whole basin reached 5 billion tons in 2000, which is 2.3 times of the discharge in the 1980s and it will be 6.5 billion tons in 2010, 3 times larger than that of the 1980s. The severe water quality pollution has increased water shortage in the Yellow River basin.

References 1. M. Giordano, Z. Zhu, X. Cai, S. Hong, X. Xhang and Y. Xue, Water Management in the Yellow River Basin: Background, Current Critical Issues and Future Research Needs, CA Research Report 3, China (2004). 2. Z. Zhu, M. Giordano, X. Cai and D. Molden, Yellow River Comprehensive Assessment: Basin Feature and Issues, IWMI Working Paper 57, Colombo, Sri Lanka (2003). 3. Yellow River Conservancy Commission, Yellow River in the 20th Century (Yellow River Water Utillization Publisher, Zhengzhou, 2001). 4. C. Greer, Water Management in the Yellow River Basin of China (University of Texas Press, Austin and London, 1979). 5. Z. Zhu, M. Giordano, X. Cai and D. Molden, TheYellow River basin: Water accounting, water accounts and current issues, Water Int. 29 (2004) 2–10. 6. J. S. Chen, D. W. He and S. B. Cui, The response of river water quality and quantity to the development of irrigated agriculture in the last 4 decades in the Yellow River basin, China, Water Resourc. Res., Vol. 39 (2003). 7. G. Yan-Chun, Analysis on reasons for the Yellow River’s dry-up and its ecoenvironmental impacts, J. Environ. Sci. 3 (1998) 357–364. 8. L. Liang, Water Management and Allocation of the Yellow River Basin, Report to CA/IWMI (2005). 9. World Bank, World Development Indicators (World Bank, Washington DC, 2003).

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10. National Bureau of Statistics, China Statistical Yearbook (China Statistics Press, Beijing, 1999). 11. National Bureau of Statistics, China Statistical Yearbook (China Statistics Press, Beijing, 2008). 12. X. Wang, Grain Production in the Yellow River Basin, Report to CA/IWMI (2005).

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Chapter 3

Water Resources and Use

Dawen Yanga , Kyoichi Otsukib , Tetsuo Kobayashib , Daisuke Yasutakec , Hiroyuki Chob , Masaharu Kitanoc , Makito Morib , Tugihiro Watanabed , Kuniyoshi Takeuchie , Hiroshi Ishidairaf and Changrong Yang a Tsinghua

University, Beijing, China University, Fukuoka, Japan c Kochi University, Kochi, Japan d Research Institute for Humanity and Nature, Kyoto, Japan e International Centre for Water Hazard and Risk Management (ICHARM), Tsukuba, Japan f University of Yamanashi, Japan g Institute of Environmental and Sustainable Development in Agriculture, CAAS, China b Kyushu

3.1. Water Resources Availability Since most of the Yellow River basin is located in arid and semi-arid regions, it is severely suffering from frequent basin-wide droughts. As shown in Fig. 3.1, water resources availability in the basin is much less than in the southern area, and available water resources in the basin are about 1/18 of the Yangtze River basin (Table 3.1) according to the data from Chinese Ministry of Water Resources.1 Conflict between water supply and demand has become more serious in recent years and limited water resources led to dry-up in the lower reach from 1970 to 2000, particularly in the 1990s. Therefore, the availability and variability of water resources is the key element for sustainable development of the basin.

25

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Fig. 3.1. Water resources in China in 2000.1 Table 3.1.

China Yangtze River Huai He Yellow River

Basin-wide water resources in China (2000).1

Precipitaion

Surface water resources (a)

Ground water resources (b)

Double counting in (a) and (b)

Total water resources

6,009.2 1,956.1 306.2 304.3

2,656.2 992.4 87.7 45.6

850.2 251.6 49.9 35.2

736.3 240.8 14.3 24.2

2,770.1 1,003.2 123.3 56.6 Unit: × l09 m3

3.1.1. Precipitation/snow melting Precipitation in the river basin is unevenly distributed in time and space. The headwater and the southern part of the basin receive relatively high precipitation, while the Loess Plateau in the midstream of the basin which is hot and dry in summer receives low precipitation. Figure 3.2 shows the average annual precipitation in the basin from 1972 to 2000 for each sub-basin. The average annual precipitation over the whole basin is about 450 mm. However, precipitation over each sub-basin has large difference ranging from 223 to 648 mm per year. Besides the spatial variability, precipitation in the basin has distinct seasonality. Figure 3.3 shows the seasonal variation of the precipitation over the basin.Approximately 80% of annual precipitation occurs between May and October, partly due to intensive rainstorms.2 The seasonality of precipitation results in large seasonal variation on river discharge. Variability in annual precipitation is remarkable, as shown in Fig. 3.4. The magnitude of inter-annual variability of precipitation is also different in each

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Fig. 3.2.

27

Long-term (1972–2000) averaged annual precipitation.

Precipitation (mm)

120 100 80 60 40 20 0 Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.

Fig. 3.3.

Seasonal variation of precipitation over the Yellow River basin.

sub-basin: relatively high in the upstream (sub-basin 0) and the downstream (subbasin 6, 7), and low in the middle reach. In comparison with inter-annual variation, the long-term trend of precipitation is unclear. In the middle-south part of the basin, (sub-basin 5 and 6), a weak decrease trend is observed (0.8 mm/yr), however the magnitude and trend (positive or negative) are quite different for each gauging station and have no consistency. Upper regions of the basin are covered with snow in winter; snowmelt, in particular, contributes to river flow rate in spring in this region. Despite the importance of snow as a water resource, in-situ observation of snow is not enough to estimate the total amount of snow-water resources in the region. Model simulations and satellite images are only useful tools to understand hydrological conditions on snow. Figure 3.5 shows estimated snow water equivalent (SWE) and snowmelt in the upper region of the basin in terms of a distributed snow accumulation/melt model combined with satellite images.3 Snow accumulation starts from late October to middle November, and the seasonal maximum SWE is observed around late January to early February. The seasonal maximum SWE

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Fig. 3.4. Fluctuation of annual precipitation for each sub-basin. (Location of each sub-basin is shown in Fig. 3.2.)

shows a large inter-annual fluctuation, ranging from 53 mm to 223 mm. Snowmelt occurs mainly during middle of March to late May. However, the amount and timing of snowmelt are different in each year. The inter-annual variation of snows is caused by several factors, and associated with large-scale oscillations such as El Nino and/or La Nina. Based on the satellite image analysis, Kiem et al.4 show that larger snow covers over the upper reach of the river were observed in 1988 and 1999, significant El Nino years. In 1982/1983, a significant La Nina year, snow cover was much less than the normal year.

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0

250

150

1

208

188

200

2

228

139

100

123

124

83

75

57

50

4

0 1989/11

1988/11

1987/11

1986/11

1985/11

1984/11

1983/11

1982/11

1981/11

5

300

0

250

1

200 150 100

176

145

120

2

112

81

94

82

73

3

Fig. 3.5.

1997/11

1996/11

1995/11

1994/11

5 199311

0 1992/11

4

1991/11

50 1990/11

SWE (mm)

3

Snowmelt (mm/d)

SWE (mm)

300

Snowmelt (mm/d)

Water Resources and Use

Fluctuation of annual precipitation for each sub-basin.

3.1.2. Potential evaporation Evapotranspiration and potential evaporation (PET) are the key components of the hydrological cycle. It is difficult to measure them so that they are usually estimated as area average using models. The Penman–Monteith (P–M) equation is used to obtain reference evapotranspiration (RET) under certain conditions due to the recommendation of FAO-56,5 that is, an extensive surface of well-watered green grass with uniform height (0.12 m) (a single uniform cover), actively growing (canopy resistance of 70 s/m), and completely shading the ground (albedo; 0.23), because the real evapotranspiration may change depending on vegetation. PET is the maximum rate of evaporation from the land surface when water is freely available. It is estimated by the Shuttleworth–Wallace (S–W) equation, which takes into consideration dual sources, namely the transpiration from vegetation and the evaporation from underlying soil substrate.6 Using the monthly datasets from 1981 to 2000, the annual average RET and PET in the whole basin were estimated to be 968 mm and 668 mm, respectively as shown in Fig. 3.6. Both the basin-average RET and PET reflect a similar trend, however, the spatial distributions of RET and PET are strikingly different from place to place because of spatial differences in vegetation cover and development (Fig. 3.7). The

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(a)

(b)

Fig. 3.6. Yearly changes of annual (a) RET and (b) PET over the whole basin and at three specific points from 1981 to 2000.

RET reflects the three climatic patterns over the basin: the upper (Zone I), the middle (Zone II) and the lower (Zone III). Over the upper zone, the distribution of the annual-average RET is complicated due to mountainous topography. It is generally high in the central strip and decreases towards the East and the West. In the middle zone, the annual RET is lower in the southwest and increases progressively towards the northeast. On the other hand, these climatic patterns are not so clearly displayed in the PET distribution, as shown in Fig. 3.7(b), but effects of vegetation are obvious. The large grassland area in the upper and middle zones (including some shrub land) is low in PET, and the cropland (including crop and natural vegetation mosaic) and forested areas are high in PET in the middle and lower zones. The average monthly variation in PET and RET are shown in Fig. 3.8 for the whole basin.

3.1.3. Runoff and river flow The available surface water resources are estimated from the naturalized stream flow, which represent the natural flows that would have occurred in the absence

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Fig. 3.7.

Spatial distributions of annual (a) RET and (b) PET averaged from 1901 to 2000.

31

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(b)

Average over whole basin Point1(Grassland) Point2(Forest) Point3(Cropland)

6 5

PET in Yellow (mm/day)

RET in Yellow (mm/day)

(a)

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Average over whole basin Point1(Grassland) Point2(Forest) Point3(Cropland)

6 5 4 3 2 1 0

1

2

3

4

5

6

7

8

9

10

11

12

1

2

3

4

Month

5

6

7

8

9

10

11

12

Month

Fig. 3.8. Seasonal changes of (a) RET and (b) PET over the basin and at three points (Averaged from 1901 to 2000). 100

Runoff (km3)

Huayuankou 80 60 40 20

Lanzhou 0 1920

1930

1940

1950

1960

1970

1980

1990

2000

Fig. 3.9. Annual naturalized runoffs at Lanzhou and Huayuankou (1920–1997).

of water uses and water management facilities.7 The natural flow rates are usually obtained by adjusting the measured flow rates recorded at gauging stations and removing the impacts from the filling/releasing of upstream reservoirs, water diversions, and return flows from both surface and groundwater sources. Figure 3.9 gives the naturalized stream flow sequences for Lanzhou and Huayuankou stations estimated by the Yellow River Conservancy Commission.2 The average annual runoffs at two gauging stations are 32.8 km3 /year and 55.9 km3 /year, respectively. Adding the runoff rate from the tributaries from Huayuankou to the river mouth, it is estimated that the annual runoff in the Yellow River basin is 58 km3 /year. However, the annual runoff has been decreasing since the 1950s, and the estimated runoff in the 1990s is only 43 km3 annually, being 25% lower than long-term average.8 Figure 3.10 shows the calculated naturalized flow rate for each sub-basin from 1972 to 2000. The upper part of the basin (sub-basins 0 and 1) and lower reach

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Fig. 3.10. Fluctuations of the annual runoff in each sub-basin. (Location of each sub-basin is shown in Fig. 3.2.)

(sub-basin) gives 120∼140 mm/year of long-term average annual runoff, and these are the main sources of runoff in the basin. Besides, the long-term averaged value, larger inter-annual variability of runoff is also observed in sub-basins 0 and 7 (lower reach). In other parts of the basin, runoff amount is relatively less and the variability of runoff is also small. The variation of runoff is mainly dependent on precipitation, geological and morphological characteristics. Precipitation elasticity (E) of river flow is used to evaluate the sensitivity of precipitation on variability of runoff, where E is

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300

Sub-basin

Discharge (mm/year)

250

Sub_0 Sub_1 Sub_2 Sub_3 Sub_4 Sub_5 Sub_6 Sub_7 YRB

Sub_0 200

Sub_7 150

Sub_1 100

Sub_5 Sub_6

Sub_4

50

Sub_3

E 2.83 0.46 -0.08 0.48 0.45 0.78 1.20 1.39 0.91

Sub_2

0 0

200

400

600

800

1000

Precipitation (mm/year) Fig. 3.11. Precipitation elasticity of river flow in Yellow River basin. (Location of sub-basin is shown in Fig. 3.2.)

defined as


 QP¯ dQ

, E=
dP P=P¯ P¯

(1)

where dQ and dP are the changes of river flow and precipitation, P¯ is the average ¯ The precipitation in the data period and QP¯ is the discharge corresponding to P. estimated precipitation elasticity of river flow (E) over the whole basin is 0.91 (Fig. 3.11). The value E, greater than unity, means a x% change in precipitation causes > x% change in river flow. In the river, large E values (>1) were observed in sub-basins 0, 6 and 7, in which certain variation in precipitation causes more variation in runoff.9,10 Sankarasubramanian et al.,9 suggested that E becomes lower than unity in the regions with high snow pack depth. Snow storage usually buffers annual stream flow rates by changing stream flow timing. However, Dooge et al.,11 showed that E depends on many factors such as humidity ratio, stochastic characteristics of climate, field capacity of soils, soil moisture, length of soil water depletion, and saturated hydraulic conductivity. Therefore E is particularly useful for approximating the future discharge change due to the change in precipitation. In addition to the natural variation, river runoff is strongly affected by anthropogenic disturbances such as water withdrawal and flow regulation. Figure 3.12 gives a comparison between the measured and naturalized runoffs

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35

60

0

50

20

40

40

30

60

20

80

10

100

0

Runoff (km3)

(b)

(Qn−Qm)/Qn (%)

120 1950s

1960s

1970s

1980s

1990s

12

0

10

20

8

40

6

60

4

80

2

100

(Qn−Qm)/Qn (%)

Runoff (km3)

(a)

120

0

1950s

1960s

Naturalized (Qn)

1970s

1980s

Measured (Qm)

1990s

(Qn-Qm)/Qn

Fig. 3.12. Comparison of the observed and naturalized runoffs, (a) the upstream of Lanzhou and (b) from Sanmenxia to Huayuankou.

in two areas: the river source to Lanzhou and Sanmenxia to Huayuankou. The differences in the upstream reach are small, as shown in Fig. 3.12(a) and, the effect of human activities on stream flow in the middle and downstream reaches would be significant, as shown in Fig. 3.12(b).

3.1.4. Water storage Development of reservoirs alters seasonal patterns of stream flow and increases available water resources during low-flow and dry periods. In the Yellow River basin, nearly 3,000 reservoirs were constructed.12 Table 3.2 lists the large dams built along the main stream. In 2005, the total capacity of the reservoirs in the basin is about 70 km3 , far exceeding the annual stream flow rate (58 km3 ) in the basin.13 The number of dams, storage capacity, population and storage capacity per capita are shown in Fig. 3.13. Only the large reservoirs (the storage capacity is greater than 0.1 km3 ) are shown in the figure. The construction of huge dams (storage capacity greater than 1 km3 ) was started mainly in the lower reach (the downstream of

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Table 3.2.

80 70 60 50 40 30 20 10 0

Basin area (104 km2 )

Dam height (m)

Water level (m)

Total capacity (km3 )

Effective capacity (km3 )

13.1 13.7 18.2 18.3 21.6 22.8 27.5 31.4 39.5 40.4 68.8 69.4

178 165 147 55 33 71 43 9 90 47 106 173

2,600 2,180 1,735 1,619 1,578 1,480 1,156 1,055 980 834 335 275

24.70 1.65 5.70 0.22 0.05 0.09 0.57 0.08 0.90 0.07 9.64 12.65

19.35 0.06 4.15 0.01 0.01 0.06 0.32 0.02 0.45 0.04 6.04 5.05

200 Storage capacity per capita [m3]

150 Population [x 107]

Num. of dams

100 50

Storage capacity [km3]

Population, storage capacity per capita

Storage capacity, Num. of dams

Longyangxia Lijiaxia Liujiaxia Yanguoxia Bapanxia Daxia Qingiongxia Sanshenggong Wanjiazhai Tianqiao Sanmenxia Xiaolangdi

Large reservoirs on the main stream of the Yellow River.

0 1950

Fig. 3.13.

1960

1970

1980

1990

2000

2010

Change of reservoir storage from the 1950s to the 2010s.

Longmen) from the 1960s, and expanded to the middle reach (around Lanzhou area) after the 1980s. After the 1990s, storage capacity has been increasing, but the number of dams has not increased so much. This means that only large dams such as Xiaolangdi were constructed in this period. Reservoirs along the Yellow River play important roles for water supply (agricultural, industrial, and domestic uses), flood control and hydropower generation. On the other hand, there is concern that the reservoirs may alter the flow regime significantly, and the alteration of river flow will result in serious damage on the natural environment, the river channel and riparian zone. As an indicator for representing the impact of reservoirs on basin scale water cycle, the residence time of river water due to reservoir impoundment (RT) is widely used,14 where RT is calculated as the total storage capacity of the reservoirs upstream from a certain point of the basin (V) divided by the annual total river discharge at that point

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(Q). Figure 3.14 shows the increase in river water residence time caused by the reservoirs at Xiaheyuan, Taodaoguai and Sanmenxia. The residence time gradually increased from around 4 in the 1970s to 6 months in 1986. After the construction of Longyangxia Dam, the residence time increased to 1.0 (at Sanmenxia) to 1.5 (at Xiaheyuan and Taodaoguai). The RT value greater than unity means the reservoir storage capacity is larger than the annual runoff volume and these reservoirs affect water cycle in the basin scale significantly.

3.1.5. Groundwater resources In the Yellow River basin, an estimated mean annual volume of available groundwater resources is nearly 40 km3 per year. The largest groundwater contribution comes from the area from the river head to Lanzhou, which is about 15.2 km3 per year. The contribution from the area from Huayuankou to the river mouth is about 2.5 km3 per year, as shown in Fig. 3.15.51

Residence time (year)

2.5

Sanmenxia Taodaoguai Xiaheyuan

2.0 1.5 1.0 0.5 0.0 1970

Fig. 3.14.

1980

1990

2000

River water residence time in the Yellow River basin.

Quantity (km3/y)

50 40

Surface water Water Groundwater

VIII

III II

30

IV V

I

VI

VII

20 10 0 I II

Fig. 3.15.

III

IV

V

VI

VII

Spatial distribution of available surface and groundwater.

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Due to overexploitation of groundwater, serious groundwater table depletion as well as land subsidence occurred in some parts of the Yellow River basin. For example, the groundwater table has annually dropped more than 3.7 m in western Taiyuan City since 1980, and it reached 4.2 m annually from 1984 to 1987. The land subsidence was 2.3 cm annually from 1980 to 1985, and the land surface has subsided 1.23 m in some locations in the city by 1982 from the ancient. Since the 1970s, the groundwater table in Xi’an has been dropping from 1 to 5 m annually, and the area of depression reached more than 300 km2 .15 After considering feasibility for groundwater exploitation, available water resources estimated on the basis of the hydrologic record from 1956 to 1979 is 73.5 km3 in volume.12 In addition, 47.3% of the available water resources are generated from the river head to Lanzhou. In contrast, only 5% and 5.4% of the available water resources are generated from two areas: Lanzhou to Toudaoguai and Huayuankou to the river mouth, respectively. Figure 3.16 shows the amount of water resources withdrawn from the regions in the basin in 2001.16 The region from Lanzhou to Toudaogui diverted the largest amount of surface water (15.8 km3 /yr), accounting for 47.1% of the total amount of surface water withdrawn in 2001. The region from Huayuankou to the river mouth has the second largest share at 25.5% of the total withdrawal for surface water. In contrast, the region from Longmen to Sanmenxia has the largest share of groundwater withdrawal (5.5 km3 /yr) which is 40.7% of the total groundwater withdrawn in 2001. The water resources of 85% is withdrawn from the river head to Lanzhou and Lanzhou to Toudaoguai. The water resources from Huayuankou to the river mouth are also mainly supplied by surface water (71.2% of the total). It should be noted that the above assessment on available water resources are based on a stable climatic condition.

Water withdrawal (km3)

25 20

Surface Water water Groundwater

VIII

III II

15

IV V

I

VI

VII

10 5 0 I II

III

IV

V

Fig. 3.16. Water withdrawal in 2001.

VI

VII

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Table 3.3. Historical changes of forest coverage in the Loess Plateau. Period

Forest coverage (%)

Xizhou∗ Qin, Han, Nanbei∗ Tang, Song, Ming∗ Qing∗ 1949∗ 1998∗∗

53 40 33 15 6.2 7.2

*Liu and Ni (2002), **Ref. 54.

3.2. Water-Use 3.2.1. Forest Since the forest coverage in China had been decreasing as shown in Table 3.3, the Chinese government has emphasized on an afforestation policy since its foundation. Forest conservation and afforestation have been promoted as one of the most important environmental policies such as Forest Law, Environmental Protection Law, and Soil and Water Conservation Law since the 1970s. Moreover, the government adopted the Great Western Development Plan as one of the National Political Imperatives, in which forest conservation and afforestation were set as the major policies to reduce the economic imbalance between the East and West. Owing to these policies, the forest coverage has been gradually increasing in China. The forest coverage of the Loess Plateau increased from 6.2% in 1949 to 7.2% in 1998. The forest conservation and afforestation policies during the 1950s and 1960s were developed to stabilize the daily lives and production activities of local residents by preventing natural disasters. In addition, eco-environment conservation has become an equally important issue since the 1970s. The catastrophic floods of the Chang Jiang and Songhua Rivers in 1998 made the Chinese forest conservation and afforestation policies the highest priority. A National Eco-environment Construction Plan was promulgated in 1998 and its goal was to increase the national forest coverage from 16.6% in 1998 to at least 19% in 2010, 24% by 2030, and to more than 26% by 2050 (Table 3.4). In the forestry division, eco-environment conservation was reinforced by the Six Great National Key Forestry Projects launched in 2001. The national afforestation area was 9.1 million ha in 2003 and about 90.6% of this area was afforested by these projects. The Natural Forest Resources Protection Project and the Grain to Green Projects have garnered the majority of attention. The mandate

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Table 3.4. Period

b802-ch03

Forest area (mil. ha)

1948

Forest resources in China.17

Forest coverage (%)

Timber volume (bil. m3 )

Remarks

8.6

1973–1976

122

12.7

8.7

1977–1981

115

12.0

9.0

1984–1988

125

12.98

9.1

1989–1993

134

13.92

10.1

1994–1998

159

16.55

11.27

1999–2003

175

18.21

12.46

1999–2010

—

19.0 ∼

—

2011–2030

—

24.2 ∼

—

2031–2050

—

26.0 ∼

—

The 1st National Enumeration of Forest Resources The 2nd National Enumeration of Forest Resources The 3th National Enumeration of Forest Resources The 4th National Enumeration of Forest Resources The 5th National Enumeration of Forest Resources The 6th National Enumeration of Forest Resources Stage controlling eco-environment Stage improving eco-environment Stage sustaining favorable eco-environment

of the Natural Forest Resources Protection Project is to rehabilitate and expand the natural forests. The plans were to protect the 61.2 million ha of the natural forests and afforest 8.67 million ha with native trees during 2000–2010. The mandate of the Grain to Green Project was to convert farmland with slopes greater than 25 degrees into forests and grasslands. The overall goal was to conserve soil and water by planting grasses and trees on waste hills and mountains suitable for revegetation. The plans were to revegetate 6.77 million ha and afforest 8.67 million ha during 2001–2005, and revegetate 8.00 million ha and afforest 8.67 million ha during 2006–2010. The Chinese artificial forest area, which is the largest in the world, was 53.0 million ha in 2003. (a) Climate and forest distribution Many climatic indices on forest depend essentially on the ratio between precipitation and potential evapotranspiration. The Radiative Dryness Index

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(RDI) is one of the climatic indices using net radiation instead of potential evapotranspiration. RDI is the ratio of the net radiation and the energy required to vaporize all precipitation. RDI = Rn / lP,

(2)

where Rn is the net radiation, l is the latent heat to evaporate water, and P is the precipitation. The vegetation classification by RDI and net radiation is shown in Fig. 3.17. It indicates that forests predominate where RDI is between 0.3–1.1. The Loess Plateau, where the annual precipitation is 200–650 mm/y and the annual net radiation is 2.0–2.5 GJ/m2 /y, has a RDI of 1.2–7.0. This indicates that the Loess Plateau may have formed from forest-grassland to desert. The Chinese Academy of Sciences uses an index on accumulated temperature and precipitation, that is, Dryness Index, Ka, for vegetation classification. PET

Ka = i=365 i

PT ≥10◦ C

 TT ≥10◦ C 1.6 i=365 i , = i=365 PT ≥10◦ C i

(3)

where, PET is the potential evapotranspiration (mm/yr), P is the precipitation (mm/yr), T is the average temperature (◦ C), and the subscript T ≥ 10◦ C indicates the daily average temperature being 10◦ C or above. The vegetation in the Loess

Fig. 3.17.

Climate and vegetation.18

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Fig. 3.18.

(a) Annual precipitation and (b) potential vegetation distribution.19

Plateau agrees well with Ka and the annual precipitation (Fig. 3.18). The forests are distributed in the southeast of the 450 mm/yr contour line. The forest-grassland zone belonging to a semi-humid and semi-arid climate is located in the zone of 1,000–1,600 m above the sea level, where P = 450–550 mm/yr and Ka = 1.4–1.8. The forest zone belonging to a temperate semi-humid climate is located in the zone of 800–2,200 m above the sea level, where P = 500–650 mm/yr and Ka = 1.3–1.5. Forest and forest-grassland zones occupy almost half of the Loess Plateau. However, the forest coverage is only 7.2%. Including shrubs, the coverage reaches

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only 11.1%. The artificial forest occupies 25% of the whole forest area in the Loess Plateau, but 40% of the forest is situated in the soil and water degraded regions. The forest and forest-grassland area mainly consist of deciduous broadleaved trees (Quercus, Poplus, Betula, Ulmus, Tilia, Acer, etc.) and are partly mixed with conifers (Pinus tabulaeformis, Pinus armandii, Larix principisrupprechtii). Major afforestation trees are Robinia pseudoacacia, Poplus, Pinus tabulaeformis, and Platycladus orientalis. Black Locust (Robinia pseudoacacia) has been widely planted as a pioneer tree on waste hills and mountains. There are also many kinds of shrubs such as Hippophae rhamnoides, Caragana korshinskii, Xhanthoceras sorbifolia, Lespedeza bicolor, Contoneaster acutifolias, Spiraea mongolica, Ostryopsis davidiana, Prunus davidiana, etc. (b) Vegetation in arid lands A desert greening study has been conducted as a long term ecological research in Shapotou, Ningxia Huizu Autonomous Region.20 Shapotou is situated on a sand dune 1,339 m above the sea level which is located in the South edge of the Tengeli Desert near the upper reach of the Yellow River. The average annual precipitation and potential evapotranspiration are 186 mm/y and 2,900 mm/y, respectively. The minimum monthly air temperature is −6.9◦ C in January. The maximum is 24.3◦ C in July, and the soil temperature reaches around 74◦ C. Drift sand fixation by planting was started in the 1950s to protect the Baolan Railroad, which linked Lanzhou to Baotou, from wind damage. The straw checkerboard method, in which straws are inserted in the sand dunes to form fences in the shape of lattices 1 m × 1 m and 10–30 cm high, was adopted for the fixation. Fences were designed to reduce wind velocity above the dune surface, suppress sand movement, and encourage the growth of shrubs and grasses. After the fences were installed, xerophily shrubs were planted in the lattices. The shrubs grew rapidly after planting and reached 30% of the vegetation coverage and 39.7 kg/100 m2 of dry matter weight 9 years after planting (Fig. 3.19). However, there was a sharp decrease to 9.1% of the vegetation coverage and 18.2 kg/100 m2 of dry matter weight over the next 5 years. The reduction slowed down and the vegetation coverage and dry matter weight declined to 6.6% and 17.1 kg/100 m2 , respectively, 45 years after planting. In contrast, herbs which were not planted in the lattices at the time of drift sand fixation increased slowly and reached 20.1% of the vegetation coverage and 7.6 kg/100 m2 of the dry matter weight 45 years after the fixation. Soil water in the 0–40 cm depth changed corresponding to precipitation regardless of the vegetation status. On the other hand, soil water in 40–300 cm of the depth decreased from about 3% to about 1% during the 10 years after the

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Soil Water (%)

4 Shrub

3 2 1

Dry weight (kg/100 m2) Vegetation coverage (%)

0 40 Shrub

30

Herb 20 10 0 40 Shrub

30

Herb 20 10 0 0

Fig. 3.19.

10

20 30 Years after planting

40

50

Changes in soil water and growth of vegetation in Shapotou.24

fixation.Afterwards, 1.0% of soil water remained steady regardless of precipitation. The results suggest that the shrubs grew smoothly for approximately 10 years after planting, but were limited to the range in which their water requirement and the soil water were balanced. There exist forests of tall trees even in arid lands. However, they are mostly confined to the areas where water collects (i.e., adjacent to lakes or reservoirs, hinterland of rivers or canals, in the valleys of hills or mountains, and irrigated woodlands). (c) Vegetation in semi-arid and semi-humid lands In China, afforestation projects have been promoted mainly in semi-arid and semihumid lands with severe degradation on soil and water. However, even when seedlings are successfully grown in these areas, they often fall into sluggish growth.21 Plantings grow well in humid years but die and gain only stem size in relatively dry years and blight in drought years due to the lack of water and related stresses. Not all precipitation on forest is available for flowing into streams or replenishing groundwater. A portion of precipitation is intercepted by canopies. The rest consisting of throughfall and stemflow is partially intercepted by litters

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on the forest floor. Intercepted water is temporarily stored in canopies and litters but is eventually lost by evaporation. In China, the representative interception by canopies and litters are 20–25% and 10–15%, respectively.22 The remainder of the precipitation is distributed through other mechanisms such as transpiration, soil evaporation, stream flow and infiltration. Evapotranspiration dominates the water budget in semi-arid and semi-humid lands. Table 3.5 shows annual water balances of watersheds in semi-arid and semihumid lands in China. As shown in the table, most of the precipitation over forests located in semi-arid and semi-humid land is consumed by evapotranspiration, which results in a small amount of runoff. Therefore, although the beneficial effects of afforestation to mitigate soil and water degradation are highly desired, the consequences of soil desiccation and reduction of water resources by tree water consumption should be contemplated thoroughly.23−26 In order to lessen adverse effects of afforestation and fulfill multifunctional roles of forest, integrated studies based on the SPAC (Soil-Plant-AtmosphereContinuum) concept have been conducted in China.25−26 The use of Black locust (Robinia pseudoacacia L.), native to North America, has become an important issue. It has been extensively planted in the Loess Plateau since the 1960s and has become the major tree species in the region. Although it has a number of advantages such as fast growth, drought tolerance, symbiotic nitrogen fixation, etc., its expansion has encouraged debate on adverse effects of the deterioration of the native ecosystem and the reduction of stream flow by excessive soil water-use. Table 3.5. Water budget in semi-arid watersheds in China. Precipitation mm y−1

Evapotranspiration mm y−1

Runoff mm y−1

456.9 395.1 506.4 475.5

376.4 360.6 480.1 442.2

80.5 34.5 26.3 33.3

[14]

Xiao Xingan Maershan Maershan Maershan Hebei Longhua Beijing Xishan Qinling Nanpo

716 700 700 666 500 630 672–757

602 554 504 426 465 315 398–630

114 146 196 240 35 315 127–274

Liu et al.52

Yangjiagou Dongzhuanggou Jiuyuangou Peijiamaoguo

526 525.7 521.4 518.7

520.6 515.8 474.9 465

5.4 9.9 46.5 53.7

Mu et al.53

Basin Shanbei Qingyangcha Shanbei Hengshan Puxiyang-Xian Tanghugou Qinghaihuzhu-Xian Junjia

Reference

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3.2.2. Irrigation While the Yellow River basin has a long history of irrigation, the irrigated area has been expanding extensively since the 1950s. At the present, the total effectively irrigated area in the basin is 7.51×106 ha, of which about 60%, that is 4.45×106 ha, is comprised of 70 large scale irrigation districts with larger than 20 × 103 ha of the command area. In 670 districts of the middle scale, from 670 to 20,000 ha, 1.17 × 106 ha is irrigated, which is 15% of the total irrigated area. The remaining 25%, that is about 1.90 × 106 ha, is in the small-scale irrigation districts, of which command area is less 670 ha (Fig. 3.20). Major irrigation canals are shown in Fig. 3.21. According to the expansion of the irrigated area, the total diversion amount from the Yellow River for irrigation has increased rapidly. In 1949, it was 7.9 × 109 m3 /yr and increased to 18.7 × 109 m3 /yr in 1959, 18.9 × 109 m3 /yr in 1969, 27.8 × 109 m3 /yr in 1979, 30.7 × 109 m3 /yr in 1993, and 30.8 × 109 m3 /yr in 1997 (Fig. 3.22).27 Development of the irrigated area and the increase in water use for agriculture have resulted in water shortage in the Yellow River basin, especially in the downstream region. The government has been trying several techniques and measures for water saving including hardware improvement such as canal lining, pipe irrigation, sprinklers and micro-irrigation in fields. Some institutional and economical measures have been applied for water saving as well. Though many policies and work for water saving have been implemented, there are still many problems in the basin, including a) Slow and uneven development of water saving technologies, b) lack of consciousness on water saving, c) insufficient investment for water saving, d) fewer economic incentives for water saving, and e) lack of studies on water saving technologies under the specific conditions of the Yellow River basin such as higher sediment content of diversion water. These problems should be solved compatibly with food security and environmental conservation. To evaluate the agricultural water use and to assess impacts of water saving policies and programs on the hydrological regime of the Yellow River basin, the water balance of the irrigation districts, especially of the larger irrigation districts, should be clarified, assessing the actual water use and the consumption rate in irrigated fields, effects of return flow from irrigated areas, and recent impacts of water saving policies and transfer of water managements from governmental organizations to the water users. (a) Irrigation in Qingdongxia District The Qingtongxia Irrigation District, the fourth biggest irrigated area in China, is located along the upstream of theYellow River, in the North of NingxiaAutonomous

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Major irrigated areas of the Yellow River basin. Fig. 3.20.

47

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Major irrigation canals in the basin. Fig. 3.21.

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x1,000 ha 2,500 Upper Middle Lower

2,000 1,500 1,000 500 0

1950s

1960s 1970s 1980s Irrigated area

1990s

Fig. 3.22. Increase in the irrigated area in the Yellow River basin from the 1950s.27

District. It contains about 35 km2 of farmland. The main landform is alluvial plains created by theYellow River deposits of silt and fine sand. The elevation ranges from 1,080 to 1,154 m, and the surface slope ranges from 1/8,000 to 500. The climate in the area is arid and semi-arid, belonging to the continental monsoon climate. The average annual precipitation is about 200 mm. The seasonal distribution of precipitation is uneven and about 70% of the annual rainfall concentrates in the summer from June to August. The pan evaporation ranges from 1,000 to 1,550 mm/yr, and the dry index is from 4.8 to 8.5. The average annual air temperature and sunshine hours are 8.5◦ C and 2,975 h/yr, respectively. The Yellow River and its tributaries are the main rivers crossing this region in which the flow path of the Yellow River is 275 km. The irrigated area is divided into East and West parts by the Yellow River, their areas are 4,779 and 872 km2 , respectively, and the irrigated areas are 2,493 and 807 km2 , respectively. Now, there are 18 approach channels and 24 drainage ditches in the region, taking about 6.64×109 m3 water from theYellow River and draining 2.54×109 m3 water back to theYellow River annually. All these channels divert water from Qingtongxia hydrojunction (completed in 1964) located in the Yellow River. The Hanyan channel and the Huinong channel, completed 200 B.C. ago, have a long history of more than 2,000 years, and are the main channels in the irrigated area. The Hanyan channel and the Huinong channel with parallel layout, causing serious amount of wastewater, were merged in 2005. This mergence project reduces the length of the trunk channels and the water loss in transport. The total area of this irrigated region is 6,239 km2 of which the farmland is 51.3%, the garden-plot is 3.2%, the woodland is 6.7%, the grassland is 8.5%, and the water area is 15.9%. Low precipitation, high evapotranspiration and low water

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quality are the basic features in the Qingtongxia Irrigation District. The amount of surface water resources is 1.12 × 108 m3 which is 12.9% in Ningxia Autonomous District. The surface water resources are difficult to use because of the flat plain. The amount of underground water resources is 9,877 × 104 m3 in which 64.6% of the whole is recharged by precipitation and 35.4% is recharged by runoff and torrents from the Helan Mountains. The groundwater level, influenced strongly by human activities, rises in the irrigation season and falls in the seasons with no irrigation. The annual change in water level is relatively stable with a periodic variation. In the irrigation season, the average groundwater depth is about 1.0 m with no obvious regional difference. The mineralization degree has decreased since the Qingtongxia hydro-junction was completed in 1964. The area, where the mineralization degree is below 3 g/L, increased from 68% in 1962 to 92% in 1999. Meanwhile, the area, where the mineralization degree is greater than 3 g/L, decreased from 32% in 1962 to 8.5% in 1999. According to the standards of irrigation water quality in China, 80% of the groundwater can be used in Qingtongxia Irrigation District. In the recent 10 years, the surface water resources from the Yellow River is 2.72 × 1010 m3 in volume, the mineralization degree of water is 0.3–0.7 g/L, and pH is 7.5–8.4. The above water quality satisfies the standards on irrigation water. Ningxia is allowed to annually use 40 × 108 m3 of the Yellow River water at most, and now, 25.4 × 108 m3 water is diverged by Qingtongxia Irrigation District. The amount of the water resources is listed in Table 3.6. In 2005, the total water use in Qingtongxia Irrigation District was 72.15 × 108 m3 , of which 66.1 × 108 m3 was used by agriculture. The actual irrigated area is 3.3 × 103 km2 , in which the flow irrigated area is 3.0 × 103 km2 and the pumping irrigated area is 0.31 × 103 km2 . The water transport efficiency on the canal system in flow irrigated area is 0.44, and that in the pumping irrigated area is 0.63. The water efficiency on irrigation in the flow irrigated area is 0.36, and 0.51 in the pumping irrigated area. The irrigation includes summer irrigation (April to June), autumn irrigation (July to September) and winter irrigation (late October to mid November). Dry farming crop needs irrigation 2–5 times in its growth season, with the irrigation Table 3.6. Water resources in Qingtongxia Irrigation District. Irrigated area (km2 )

6,239

Average annual precipitation (108 m3 )

Average annual surface water resource (104 m3 )

Average annual underground water resource (104 m3 )

11,419

12,468

9,877

Water resource Total amount from the of water Yellow River resource (108 m3 ) (108 m3 ) 25.4

27.64

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duty of 4,050–7,950 m3 /ha, and rice needs irrigation 30–34 times in its growth season, with the irrigation duty of 13,500–19,500 m3 /ha. The present irrigation programs in flow and pumping areas are listed in Table 3.7. (b) Hetao Irrigation District The Hetao Irrigation District (HID) in the Inner Mongolia Autonomous District has the largest irrigation scheme in the Yellow River basin. Its irrigated area is about 580,000 ha and total irrigation demand is about 4.5 to 5.2 × 109 m3 per year, which is mainly supplied by the Yellow River water (Fig. 3.23). Its main crops are wheat, maize and sunflower; other vegetables and fruits are grown. Table 3.7. Main crops and their irrigation programs in the flow irrigation area (year of 2005). Items

Plant area Area proportion Annual water use amount Net irrigation duty Average frequency of irrigation

Unit

Mono-cultured Wheat interpolated wheat of another crop Maize

Rice

Oil Sugar plants beet

hm2 % 108 m3

88,867 29.8 12.3

63,800 21.4 11.5

29,200 62,133 15,867 5,067 9.8 20.8 5.3 1.7 3.9 25.2 18 0.6

m3 /ha

4,950

6,450

4,800 14,550 4,050 4,050

Application/ season

5

7

5

Fig. 3.23. Outline of the Hetao Irrigation District.

30

4

4

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The irrigation in this region has a history of more than two thousand years. In the early 19th century, development of irrigated agriculture was undertaken on a larger scale. At the beginning of the 20th century, the irrigated area was 70,000 ha with eight main conveyance canals and then at the middle of that century, it reached 300,000 ha, while the diversion from the Yellow River was difficult in the drought. Then, from 1959 to 1961, the diversion weir was constructed at Sanshenggong to secure stable water supply. However, the expansion of irrigation had resulted in serious soil salinity damage since no drainage system was installed. In 1963, 32% of the irrigated area was salt affected and in 1973, the ratio reached to 50%. To control salinity damage, a drainage improvement project had been implemented in 500,000 ha for 5 years since 1976. The drainage canal to the Yellow River from the terminal lake Wuliangsuhai, which receives all drainage water from HID, was completed in 1981. After these drainage improvements, the salinity damage was controlled, though there are still many salt affected areas. The allocation of the Yellow River water to HID is determined by the national and local governments. The Department of Water Resources in the Yellow River Conservancy Commission allocates available water resources to the provinces and autonomous regions of the basin in every autumn for the next year, and then the government of the Inner Mongolia Autonomous District determines and notifies the water amounts that HID can divert from the Yellow River in the beginning of the irrigation year to the districts. With this amount, HID plans cropping areas and water requirement and distribution in early spring of the year. The plans must be approved by the autonomous district government. Inside the district, each level of management organization makes a water use plan every year with allocated water volume. In recent years, about 5.0 billion m3 is allocated to HID (annual average for the years 1998–2002), even though it can use 5.6 to 5.7 billion m3 , including water, from other small branch rivers. In a normal year, the whole allocated water is diverted, however, in drought years, it might not always be able to secure the allocated amount of water. In 2003, an extremely dry year, its allocation was only 2.6 × 109 m3 , which was 75% of the total allocated water to the Inner Mongolia Autonomous District. It is said that 0.2 × 109 m3 is added to the allocated amount for soil salinity control. In HID as well as other northwest parts of the basin, after harvesting crops in the autumn, the farmland is irrigated to leach out the salt accumulated in the fields during the irrigation season and to store water in soil profile in form of frozen soil water. The autumn irrigation is recognized as a useful measure for leaching out accumulated salt and for on-site water storage, while its evaluation is still needed. Since the water conveyance loss reaches 58%, much loss from the

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60

3000

Evapotranspiration

50

2500

40

2000

Diversion from Yellow River 30

1500

20

Rainfall

1000

Drainage to Wuliangsuhai Lake 10

500

0

0 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Fig. 3.24. Changes in diversion and drainage of the Hetao Irrigation District.

Evapo-transpiration (mm) rainfall (mm)

Diversion from Yellow River (100 Mm3)

Drainage to Wuliangsuhai Lake (100 Mm3)

canals in the process of conveyance and distribution and the autumn irrigation implies that estimation of water requirement and application in the fields during the growing season are considerably less than the total amount of water withdrawn for the HID. The improvement of the conveyance and distribution systems will bring more effective use of water. Based on the precise micrometeorological measurement of evapotranspiration (ET) from some irrigated fields,28 water basically supplied to the field by irrigation and precipitation is mostly consumed by ET and some seeps into groundwater. On the other hand, when precipitation is very little in the growing period, there is the possibility that ET in the field becomes larger than the irrigation and precipitation amount. ET measured and estimated by a model from the field with three major crops, maize, sunflower and wheat, and bare field surrounded by irrigated farmlands proves that ET is the smallest in maize fields and the largest in sunflower fields, as 159 mm, 221 mm, 173 mm, and 159 mm in the field of maize, sunflower and wheat and in bare field, respectively, estimated for a 69-day survey in the 2005 irrigation season with 100 mm of irrigation and 115 mm of rainfall. The measurement showed that the infiltrated water from irrigation ditches into cropped fields is also consumed by ET in the fields. Evaporation in abandoned bare fields surrounded by irrigated fields is estimated to be larger than precipitation, where subsurface soil water is supplied by lateral percolation from surrounding irrigated fields or by groundwater.28 Water saving policies and measures have been applied in HID by the local government and the irrigation district itself. The annual diversion amount from the Yellow River recently has been reduced from 5.2 to 5.5 × 109 m3 to 4.4 to 4.6×109 m3 on average, as the historical changes in diversion amount and drainage

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to the Wuliangsuhai Lake are shown in Fig. 3.24.29 In the district, to leach out the accumulated salt in the topsoil, a large amount of water is needed and diverted to reclaim the farmland. However, it remains debatable as to what will happen after the reduction of the diversion from the Yellow River, and what kind of measures are necessary to realize the reduction of the diversion. While the diversion amount has decreased slightly, the irrigated area has not decreased significantly. Though the detailed changes of the actual area of cropped land and irrigated land are not clear, official agricultural statistics do not report that the farmland area and irrigated area have increased considerably. In the statistics, the increase of the area for cash crop has been increasing gradually since 2000. The basic structure of the water balance seems not to have changed. Due to the reduced diversion from the Yellow River, groundwater use might be increased as is common in other districts. According to the estimation of salt balance, HID is storing 1.8 million tons of salt every year, while irrigation engineers and farmers observe reduced soil salinization in recent years, and the LANDSAT images show the recent decrease in salt damaged area. The analysis of cation composition of irrigation and drainage canal water, groundwater and soils proves that calcium in water applied to the fields percolates through soil profile, and consequently, sodium predominantly moves into the profile and accumulates in the top layer and runs into drains.30 The effect of leaching irrigation on the spatial distribution of soil salinity in poor drainage areas in HID was assessed by the electromagnetic induction method.31 The field measurements in this approach showed that soil salinity in the root zone is reduced temporarily after autumn leaching irrigation, and the lateral flow of groundwater is quite slow and its salinity increases slightly after irrigation water application. The distribution of soil salinity is subject to micro-topography of the field. Based on the detailed field measurements of temporal and spatial salinity distributions, leaching irrigation makes only vertical salt movement in the root zone and uneven distribution of groundwater salinity is not dissolved with leaching irrigation. One of the reasons of this uneven distribution of salinity in the fields is due to uneven distribution of irrigation water because of poor land leveling. The results suggest that in poorly drained areas leaching irrigation is not efficient for eliminating salt damage. Participatory irrigation management is of importance and is being promoted by local governments and irrigation districts. Since 1999, re-structuring the irrigation management institution has been executed extensively in the whole HID. Water users’ associations in tertiary canal areas have been established with farmers’ participation. The water users’ associations are organized basically at each branch canal and /or the tertiary canal level. As of 2003, more than 300 associations of the

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55

branch and the tertiary canal level have been founded. The command area of the established associations covers about 280,000 ha and the largest one covers 5,600 ha. Under the water users’ association, farmers’ associations are established to manage the lower level canal and its beneficial area. The chairperson or other board members are elected with democratic manner, while there are some traditional local community rules affecting decision making and the institution of the associations are being improved. Though the irrigation management transfer in HID is still in a transition stage, some effects are recognized by the HID authority, as listed below. (1) Improved consciousness of the water users and farmers of irrigation and drainage facilities, with increased responsibility for their independent operation and maintenance. (2) Efficient work on irrigation management, with independence from the general rural management, efficient collection of water use fee and improvement of relation between government and farmers. (3) Improved position of farmers, led by self-management of facilities. Lake Wuliangsuhai is a typical shallow weedy lake in arid area that accepts drainage from HID. This lake has serious water contamination and eutrophication problems caused mainly by nutrient and chemical discharge from HID. The present general dimensions of Lake Wuliangsuhai are the following: a) the surface area is 293 km2 , with 35–40 km length from South to North and 5–10 km width from East to West. b) the average depth is 0.7–4.0 m. c) the storage volume is 330 × 106 m3 . d) the mean air temperature is 7.3◦ C, the annual precipitation is 220 mm, and the evaporation rate is 1500 mm. In recent years, the water quality of the lake is getting worse, in terms of concentration of nutrients, DO, COD, BOD, transparency, etc., with the reduction of drainage water from HID, which results from reduced diversion from the Yellow River. In the past, the drainage from HID was about 500 to 800 × 106 m3 /y and in these years, is about only 100 to 400×106 m3 /y. Compared with 330×106 m3 of the total storage volume of the lake, it is easily recognized that the drainage from HID affects water quality of the Lake Wuliangsuhai. To improve the water quality of the lake, theYellow River water was diverted and transferred directly to the lake in 2004. Lake Wuliangsuhai is also a sanctuary to migratory birds. The environment including water quality of the lake is to be conserved consistently with sustainable water management of HID. In HID, there are some diseases caused by a higher concentration of arsenic in drinking water. Development of irrigated agriculture is suspected to be the reason

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of this arsenic pollution. The expansion of irrigation and the rise of the groundwater table are thought to induce changes of arsenic movement and change the arsenic concentration of groundwater. (c) Togtoh irrigation area Togtoh County is located in the Tumochuan Plain, the northeast of theYellow River basin, which is about 1,000 m in elevation and 143,100 ha in size. Agricultural land, including arable land, forest, pasture, and fish-breeding ponds, cover an area of 133,864 ha, 93.5% of the total area of the county. The area of unproductive land is 1,129 ha, 0.8% of the total area; the county contains a number of salt damaged plots in various sizes. The climate in this area is semi-arid and cold during winter so that soil in irrigated fields is frozen from surface to 1 m in depth from late autumn to late spring. The average temperature ranges from −11.7 in January to 23.1◦ C in July and the average from 1961 to 2004 is 7.3◦ C. The annual precipitation is 345 mm/y. The precipitation ranges from 139 mm/y to 663 mm/y and the average from 1961 to 2004 is 345 mm/y and the precipitation of less than 200 mm/y has been recorded. Figure 3.25 shows the seasonal change in precipitation averaged from 1961 to 2004. The area is in a semi-arid continental monsoon climate, with the monsoon arriving in late June and ending in early September.

100 (1961–2004)

Precipitation (mm/month)

80

60

40

20

0 J

F

M

A

M

J

J

A

S

O

N

D

Month

Fig. 3.25.

Seasonal changes in precipitation recorded in Togtoh County.

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Table 3.8.

57

Changes in the planted areas on main crops in Togtoh County (ha).

Year

Wheat

Corn

Millet

Sorghum

Vegetables

Soybean

Others

Total

1988 1993 1998 2001 2002 2003

4,473 4,262 6,657 1,294 1,170 216

1,213 6,016 12,490 14,199 17,616 18,768

7,753 7,630 1,874 1,169 2,501 1,113

487 215 1,348 480 581 325

1,007 455 1,330 1,453 1,474 1,447

1,020 1,243 440 315 538 395

21,740 19,365 17,153 13,398 20,326 21,307

37,693 40,071 41,275 32,308 44,206 43,571

The water resources in Togtoh County comprise rainwater, groundwater, and river water. The annual amount of water used in the county is 1,007 × 106 m3 , of which 506 × 106 m3 is rainwater, 80 × 106 m3 is pumped from wells and 421 × 106 m3 is taken from rivers. The Yellow River flows along the border of the county for a distance of 37.5 km, with a mean annual flow of about 1,500 m3 s−1 . As the other rivers in the county are ephemeral, 415 × 106 m3 of the 420.8 × 106 m3 taken from rivers is drawn from the Yellow River. About 85% of the county’s water resources is used for agriculture. Table 3.8 shows changes in the planted areas on main crops in Togtoh County. Over the past 15 years, the main crops have changed from millet and wheat to corn (maize) and vegetables. Although the area of arable land has varied with the annual precipitation, the area of irrigated fields has increased consistently, from about 20,000 ha (53% of the arable land) in 1988 to about 32,000 ha (73%) in 2003. This expansion appears to be one of the causes of the recent water shortages in the basin. The water balance is an important factor to make water use efficiently. Kobayashi et al., measured the water balance in a field (lat. 40◦ 14 5 N, long. 111◦ 11 0 E, alt. 995 m) in Togtoh from 2003 to 2006. The soil characteristics in the field are alluvial silt loam and around 0.050 mm in average size. Figure 3.26 presents field observation results on the sum of crop transpiration (Tr) and soil evaporation (E) for the 2004 growing season. The estimated daily evapotranspiration (ET dual ) is also shown using the dual crop coefficient approach. The model used for these calculations is referred to Allen et al.,32 Kobayashi et al.,33−35 Iwanaga et al.,36−37 Teshima,38 Yasutake et al.,39 and Teshima et al.40 Over the entire growing season, the cumulative Tr and E were 389 mm and 126 mm, respectively, and the cumulative ET dual amounted to 515 mm; the cumulative ET measured using the Bowen ratio method (ET Bo ) was 512 mm. E considerably exceeded Tr during the initial stage, whereas the reverse was true during subsequent stages.

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8 ET, Tr, E (mm/d)

b802-ch03

ETdual= Tr ( ) + E ( )

ETBo

6 4 2 0

150 (29 May)

120 (29 Apr)

180 (28 Jun)

210 (28 Jul)

240 (27 Aug)

270 (26 Sep)

Day of the year (2004) Seasonal changes in Tr, E, and ET in an experimental field in Togtoh county.

0

Groundwater level (m)

0 -0.5

10

-1

20

-1.5

30

-2

40

-2.5 27-Apr

Precipitation (mm d-1)

Fig. 3.26.

50 27-May

27-Jun

27-Jul

27-Aug

27-Sep

27-Oct

Date (2004)

Fig. 3.27. Seasonal change in daily precipitation and the level of the water table during the growing season in 2004 in the experimental field.

The soil moisture condition of the root zone is the most important factor to consider the timing of scheduling irrigation.37 As the soil layers are inhomogeneous, irrigation water preferentially flows downward through macropores, and deep percolation contributes to salt leaching. Irrigation requirements are to fill up the soil layer of the root zone and to supply an additional amount of water for salt leaching. Seasonal change in daily precipitation and the level of the water table in the field are shown in Fig. 3.27. The water table rose quickly during irrigation and heavy rains. Irrigation to the field was done on 16 July and 27 October, 2004.

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59

The cumulative precipitation during this period was 295 mm and approximately 150 mm of irrigation water was provided on 16 July, 2004. These results suggest that about 70 mm of the water was supplied to the root zone from the water table during the growing season. In the northern Yellow River basin, a large quantity of water is supplied for irrigation in late autumn, following the harvest, when the flow rate in the Yellow River is high. The purpose of the late autumn irrigation is to ensure that some parts of the irrigated water remain in the soil until the following spring, when there is little rain, and can then be utilized for crop germination and growth. The cold winter in this region results in soil freezing from the surface to a depth of more than 1 m. Kaneko et al.,41 evaluated the evaporation-related water loss at the experimental field over the period from late autumn 2004 to late spring 2005 using the aerodynamic method and the Bowen ratio method. Seasonal changes in the amount of liquid water within the top 100 cm of the soil profile were measured. The hydrologic cycle in the root-zone aquifer system, which is driven by autumn irrigation, is summarized schematically in Fig. 3.28. Kaneko et al.,41 confirmed that a portion of the irrigated water that percolated into the aquifer moved up into the frozen layer and passed the winter in this layer before moving down into the aquifer again when the layer thawed in early spring. Consequently, only about 100 mm of

Fig. 3.28. The movement of irrigated water in the root-zone aquifer system during the period from late autumn 2004 to late spring 2005. (Unit mm)

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more than 230 mm of irrigation water applied in late autumn were utilized for growing corn in this field; that is, the water-use efficiency of the autumn irrigation on a field basis was less than 43%. The current-carrying capacity for accumulated salt is proportional to the concentration of ions in the solution. The specific conductance or electrical conductivity (EC) is the conductivity per unit volume of a solution and is usually expressed in deci-Siemens per meter (dS/m). Kobayashi et al.,42 defined an easily measurable and practical index of soil salinity, ECSAT , which is the electrical conductivity of an extract of a saturated soil. The conductivity is measurable in the laboratory by the dilution extract method. The index can be directly compared to the electrical conductivity of groundwater (ECGW ) when water and salt movements in the soil profile are analyzed. ECSAT represents the amount of soluble salts in soil pores. Figure 3.29 shows a depth profile of ECSAT in the field, measured on 15 July, 2005, before the first period of irrigation. The ECSAT reaches a maximum at the surface and a minimum just below the surface (Kobayashi et al.,43 Kaneko et al.44 ). This is because salt accumulation is the most active in the superficial layer of the soil, while salt leaching is more active below the surface. The ECSAT of the surface soil increases under fine weather conditions and decreases following irrigation and rainfall. ECSAT measured at the soil surface is 11.2, 19.1, 0.6, and 1.5 dS/m on 26 April, 1 July, 23 August, and 1 November, 2004, respectively. As ECSAT is equal to ECGW in the soil layers just above the water table, ECSAT is expected to be less than ECGW in the soil profile, except for

0

Depth (cm)

20

40 Observation well #1 60 Water table depth: 2.79 m EC of groundwater: 2.65 dS/m 80

15 July, 2005

100 1

2

3

4

5

6

ECSAT (ds/m)

Fig. 3.29.

Profile of ECSAT in the field.

7

8

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7

61

(a) 40 cm

6

20 cm 10 cm

ECw (dS m−1)

5 4 3 2 1 0 27-Apr

6

28-May

29-Jun

31-Jul Date (2004)

1-Sep

3-Oct

4-Nov

29-Jun

31-Jul Date (2004)

1-Sep

3-Oct

4-Nov

(b) 40 cm

5

20 cm

3

EC

SAT

(dS m−1)

10 cm

4

2 1 0 27-Apr

28-May

Fig. 3.30. Temporal changes in (a) ECw and (b) ECSAT at 10, 20, and 30 cm in the field over the growing season, 2004.

the top few centimeters, although the soil texture and plant roots may influence its vertical distribution. The electrical conductivity of soil solution (ECw ) represents the salt concentration of the soil solution. Figure 3.30 shows seasonal changes in (a) ECw and (b) ECSAT at depths of 10, 20, and 40 cm in the field, measured in 2004.45 Although the ECw increased as the water content decreased prior to the first period of irrigation (16 July, 2004), the ECSAT remained almost constant. Immediately following the first period of irrigation, the ECw decreased abruptly and then increased over subsequent days at a depth of 20 cm, and over the following months at a depth of 40 cm. In contrast, the ECSAT increased simultaneously at the three measurement depths, and a peak appeared first at 10 cm and then at 20 cm. However, no clear peak appeared at a depth of 40 cm until 20–21 August, when 47.2 mm of rainfall was recorded and the groundwater table rose to a depth of

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NO3− 200

100

PO43− Concentration (mg L−1)

0 300

300

PO43− 200

100

Na 200

100

Yellow Irrigation Ground- Exudate River water water

Ca2+ Concentration (mg L−1)

0 300 +

0

300

2+

Ca 200

100

0

Yellow Irrigation Ground- Exudate River water water

Mg2+ Concentration (mg L−1)

NO3− Concentration (mg L−1)

300

Na+ Concentration (mg L−1)

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K+ 200

100

0 300

Mg2+ 200

100

0

Yellow Irrigation Ground- Exudate River water water

Fig. 3.31. Changes in ion concentrations as water moves from the Yellow River through the irrigation canal and groundwater to corn shoots (17 July, 2005). (Error bars are ± one standard deviation.)

about 1.5 m (Fig. 3.31). The ECSAT at a depth of 40 cm increased abruptly on 21 August. The trend recorded at depths of 60 and 100 cm was almost same as that at 40 cm. However, on the following day (22 August), the value of ECGW measured was 4.87 dS.m−1 , which was almost the same as the ECSAT value. Due to other observed results, groundwater bodies moved slowly in a complicated manner below a depth of about 40 cm when the depth to the water table was about 1.5 m and moved slowly away from the saline plot into the surrounding area. The ECGW value is higher in fine-textured soil profiles than in coarse-textured profiles.43 Salt damaged plots are formed at locations where the soil profiles consist of finer textured soils than those of the surrounding area.46 Salts accumulate in the root zone through evaporation and crop transpiration, and some of the salts are removed from the root zone by plants. As plant roots selectively absorb nutrients and/or ions from the soil solution, the concentrations of ions change as water moves from the irrigation canal through the field soil, and across the roots to the shoots. Xylem sap that exuded from corn stem stumps was collected during the night 3− + + 2+ of 17–18 July, 2005, and the concentrations of ions (NO− 3 , PO4 , K , Na , Ca , 2+ Mg ) were measured using an ion chromatograph system. Similar measurements were taken for samples of water from the Yellow River, irrigation water, and groundwater from the study field (Fig. 3.31).

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The concentration of Na+ in the exudate was very small, indicating that was not actively absorbed by the corn plants. Hence, the Na+ must have accumulated in the groundwater and soil and resulted in sodium-affected soils. It is necessary, therefore, to both leach and reclaim the soil by replacing Na+ with, for example, Ca2+ , in order to continue to cultivate corn in this field. The principle of irrigation management in this area is the traditional one, in which irrigation is applied to replenish the water moisture deficit to the field capacity.47 The concept of field capacity is still vague and necessary water is commonly overestimated, resulting in over-irrigation. In order to avoid overirrigation and increase water-use efficiency, the concept of dynamic field capacity is available. The water-use efficiency of autumn irrigation on a field basis was estimated to be less than 43%. Evaporation from frozen soils is much higher than that from dry soils, and the evaporation is also relatively high during the period between the thawing of the frozen soil and the planting of corn; approximately 50% of the irrigation water added in late autumn is depleted by evaporation. Therefore, it is recommended that an autumn irrigation technique be developed that keeps the soil surface dry during winter. A possible solution may be to advance the date of autumn irrigation.43 Na+

3.2.3. Industrial use The industrial water accounts for about 10–20% of the total water-use in the provinces around the Yellow River (Fig. 3.32). In 2000, the share of industrial

Fig. 3.32.

Industrial water use in China, 2000.

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Table 3.9. Water-use in river basins of China, 2000. Water-use (×108 m3 )

China Yangtze River Huai He Yellow River

Agricultural

Industrial

Domestic

Total

3783.54 (68.8%) 1021.62 (59.2%) 387.84 (70.3%) 302.35 (77.3%)

1139.13 (20.7%) 505.76 (29.3%) 99.56 (18.0%) 56.49 (14.4%)

574.92 (10.5%) 197.54 (11.5%) 64.26 (11.6%) 32.54 (8.3%)

5497.59 1724.92 551.66 391.38

Table 3.10. Water withdrawal from the Yellow River basin (×109 m3 ) (1998–2000). Year

By source Surface water

Groundwater

By sector Total

Agricultural

Industrial

Domestic Urban

Rural

Total

1998 1999 2000

37 38.4 34.6

12.7 13.3 13.5

49.7 51.7 48.1

40.5 42.6 38.1

6.1 5.7 6.3

1.6 1.8 2.1

1.5 1.5 1.6

49.7 51.7 48.1

Average Share

36.7 74%

13.2 26%

49.8 100%

40.4 81%

6 12%

1.8 4%

1.5 3%

49.8 100%

Note: Groundwater withdrawal includes 2.7 bcm pumping in regions lower than Hunyuankou. Source: YRCC, 2002.

water for the whole basin is 14%, and this value is less than the average in China (20.7%) andYangtze River (29.3%), as shown in Table 3.9. However, with a rapidly developing economy in these regions, water demand has been increasing. Industrial water-use in the upper and middle reaches increased from 7.34 × 109 m3 to 13.17 × 109 m3 from the 1950s to 1990s (increased 1.8 times during 4 decades). On the other hand, in the lower reach, industrial water-use in the 1990s is about 5.7 times as in the 1950s. The average annual withdrawal from the Yellow River basin in recent years has been approximately 50 × 109 m3 , of which approximately 74% was from surface water and 26% was from groundwater, as shown in Table 3.10. Most part of the withdrawn water (81%) is utilized for agriculture where only 12% and 7% are consumed by the industrial and domestic sectors, respectively. In 2001, 45.1% of the industrial water comes from surface water and 54.9% from groundwater,16

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65

16

Water-use (BCM)

14 12 10 8 6

Domestic Industry Irrigation

4 2

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

0

Fig. 3.33. Water withdrawal (1980–2000) for each sector in the lower reach of the Yellow River basin.

Table 3.11.

Depletion of the Yellow River water (×109 m3 ), 1988–92 and 1998–2000. Total

1988–1992a 1998–2000b Changes

30.7 37.2 21%

Agricultural

28.4 31.7 12%

Industrial

1.5 3.0 108%

Domestic Urban

Rural

0.5 1.0 96%

0.4 1.5 297%

a Ref. 48 b Ref. 49

although the rate of groundwater use is not as high as that for domestic uses (54.9% versus 62.2%). Figure 3.33 shows the amount of water withdrawal (1980–2000) in each sector (agriculture, industrial and domestic) in the lower reach of the Yellow River basin.21,51 The amount of industrial water withdrawal in 1980 is about 0.67×109 m3 , and it was gradually increased to 1.02 ×109 m3 in 1987. From 1987 to 1990, this amount was rapidly increased and finally reached 1.5 to 1.6 × 109 m3 in the late 1990s. The share of industrial water-use increased from 8.8% to 13.4% during the past 20 years. Table 3.11 shows the Yellow River water depletion in 1988–1992 and 1998– 2000. Here, water depletion is defined as a use or removal of water from a basin that renders it unavailable for further use, for example, evapotranspiration, flows directly to sinks such as evaporation ponds, and pollution.48 The total depletion increased significantly (21%) over the 10-year period. The increase of agricultural water depletion of 12% is partly offset by the growth from the industrial sectors (increased by 108% during the 10-year period).

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[ × 108 m3] 14 12 10

Withdrawal Depletion

VIII

III II

IV V

I

VI

VII

8 6 4 2 0 I II Fig. 3.34.

III

IV

V

VI

VII

Spatial distributions of withdrawal and depletion for industrial water, 2000.

The spatial distribution of the industrial water withdrawal and depletion in 2000 is given in Fig. 3.34. The amounts of withdrawal and depletion is quite different for each sub region (I∼VII), however, the distributions of withdrawal and depletion show a similar pattern from upstream to downstream. The ratio of depletion to withdrawal (D/W) is also different for each sub region; especially in the lower reach D/W becomes nearly 100%. The shift of the economic development from eastern to middle and western China implies that the Yellow River basin would become more critical as a source of water for the growing industries in the future.

3.2.4. Consumption of water in urban areas Domestic water-use includes residential uses as well as water-use by commerce and public institutions such as schools and government offices. It is usually estimated as the product of the water-use per capita and the total population. TheYellow River basin supplies water to more than 100 million people. However, the population is not evenly distributed in the basin. Figure 3.35 shows the spatial distribution of the population density (persons/km2 ) in the Yellow River basin. The highest population density is found in the area from Longmen to Sanmenxia, mainly centered in the Wei River basin, which has been one of the economic, cultural, and political centers for thousands of years. The second-highest area is from Huayuankou to the river mouth in Henan and Shandong provinces. These are also two of the most densely populated areas

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Fig. 3.35.

67

Spatial distribution of population density in 2000.

in China. The headwater from the river source to Longyangxia has low population density (less than 10 persons/km2 ). During the past several decades, urban growth has far outpaced the general growth of population in all countries, both developed and developing.49 China is not an exception. With the growth of population and the development of economy, more people have been moving to urban areas. Rapid urbanization has greatly boosted the domestic water-use. In rural areas, the rising income level has enabled more rural households to turn to piped systems, and the amount of domestic water uses in rural areas has been also increasing significantly. According to Jin and Young,50 the total annual domestic water-use in China was only 1 km3 in 1949. It then increased from 2 km3 in 1965 to 20 km3 in 1993. This amount further increased to 54 km3 in 1998. In the Yellow River basin, the amounts of domestic water-uses were 1.14 and 1.35 km3 in urban and rural areas (including livestock uses) in 1990, respectively. These values have increased to 1.84 and 1.52 km3 in 1993, and further reached to 2.27 and 1.6 km3 in 2001.13 Of the 3.87 km3 of the domestic water-uses withdrawn in 2001, surface water accounts for 37.8% and groundwater for 62.2%.16 Nearly two-thirds of the domestic water resources were supplied by groundwater. In the highly populated lower reach area, the amount of domestic water withdrawal increased from 0.21 to 0.96 × 109 m3 . The increase in the rate of domestic water-use is 0.2% per year, and this rate is almost similar to the increase of industrial water-use (Fig. 3.36). Figure 3.37 gives the spatial distribution of domestic water withdrawal and depletion. As expected, the region from Longmen to Sanmenxia withdrew the highest share of the domestic water for both urban and rural areas. The region from Huayuankou to the river mouth is the second after Longmen to Sanmenxia. The

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16.0%

Industry Domestic

14.0% 12.0%

Share

10.0% 8.0% 6.0% 4.0% 2.0% 0.0% 1980

Fig. 3.36.

1985

1990

1995

2000

Ratio of domestic and industrial water in the lower reach, (1980–2000).

VIII

III

IV V

Urban (×108 m3)

I

VII

VI

8

0.0

6

1.0

4

2.0

2

3.0

0

4.0 I–II

III

IV

Withdrawal (Urban) Withdrawal(Urban) Withdrawal(Rural) Withdrawal (Rural) Fig. 3.37.

Rural (×108 m3)

II

V

VI

VII

Depletion (Urban) Depletion(Urban) Depletion(Rural) Depletion (Rural)

Spatial distributions of industrial water withdrawal and depletion.

area from Lanzhou to Hekouzhen also withdraws much water for urban domestic uses (0.4 km3 per year). Similar to the pattern of industrial water-use, the amount of withdrawal and depletion is quite different for each sub region (I–VII), however, the distributions of withdrawal and depletion show a similar pattern in the basin from upstream to downstream. The ratio of depletion to withdrawal (D/W) is also different for each sub region; the lower reach and rural areas show nearly 100% of D/W.

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References 1. MWR, Water Resources Bulletin, http://www.mwr.gov.cn (2000). 2. X. Y. Zhu and X. C. Zhang, Changes of Water Resources in the Yellow River Basin (Yellow River Water Conservancy Press, Zhengzhou, 1999). (in Chinese) 3. H. Ishidaira, S. Gomi, Y. Matsumoto and K. Takeuchi, Long-term variability of snow cover over the upper Mekong andYellow river basin, Proc. 7th IAHS Scientific Assembly, Foz do Iguacu, 3–9 April 2005, CD-ROM. 4. A. S. Kiem, M. V. Georgievsky, H. A. P. Hapuarachchi, H. Ishidaira and K. Takeuchi, Relationship between ENSO and snow covered area in the Mekong and Yellow River basins, in Regional Hydrological Impacts of Climatic Change — Hydroclimatic Variability, eds. S. Franks et al., IAHS Publication 296 (2005), 255–264. 5. N. Osfcdrh, Office of State Flood Control and Drought Relief Headquarters, Nanjing Water Resources & Hydrology Institute (China’s Flood and Drought Disaster, Water Resources and Hydropower Press, Beijing, 1997). (in Chinese) 6. M. C. Zhou, H. Ishidaira and K. Takeuchi, Estimation of potential evapotranspiration over the Yellow River basin: Reference crop evaporation or Shuttleworth–Wallace?, Hydrol. Process. (in press, Published online in www.interscience.wiley.com, DOI: 10.1002/hyp.6339). 7. R. S. Muttiah and R. A. Wurbs, Modeling the impacts of climate change on water supply reliabilities, Water Int. 27 (2002) 407–419. 8. Z. P. Zhu, M. Giordano, X. M. Cai and D. Molden, The Yellow River basin: Water accounting, water accounts, and current issues, Water Int. 29 (2004) 2–10. 9. A. Sankarasubramanian, R. M. Vogel and J. F. Limbrunner, Climate elasticity of streamflow in the United States, Water Resourc. Res. 37 (2001) 1771–1781. 10. J. C. Schaake, From climate to flow, in Climate Change and U.S. Water Resources, ed. P. E. Waggoner (John Wiley and Sons, New York, 1990), pp. 177–206. 11. J. C. Dooge, M. Bruen and B. Parmentier, A simple model for estimating the sensitivity of runoff to long term changes in precipitation without a change in vegetation, Adv. Water Resour. 23 (1999) 153–163. 12. X. D. Chen, Hydrology of the Yellow River (Yellow River Water Conservancy Press, Zhengzhou, 1996). (in Chinese) 13. Z. Xu, K. Takeuchi, H. Ishidaira and C. Liu, An overview of water resources in the Yellow River basin, Water Int. 30 (2005) 225–238. 14. C. J. Vörösmarty, K. P. Sharma, B. M. Fekete, A. H. Copeland, J. Holden, J. Marble and J. A. Lough, The storage and aging of continental runoff in large reservoir systems of the world, Ambio. 26 (1997) 210–219. 15. Y. S. Qin, Y. H. Zhu, S. L. Cao, G. G. Yu and J. T. Li, Development and Utilization of Groundwater Resources in the Yellow River Basin (Yellow River Conservancy Press, Zhengzhou, 1998). (in Chinese) 16. Yellow River Conservancy Commission (YRCC), The Yellow River Water Resources Bulletin, http://www.hwswj.gov.cn (2003). (in Chinese) 17. W. Z. Lu (ed.), Modern Forestry Management (Northwest A & F University Press, Yangling, 2003). (in Chinese) 18. H. Seino and Z. Uchijima, Global distribution of net primary produtivity of terrestrial vegetation, J. Agr. Meteorol. 48 (1992) 39–48.

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19. Y. K. Hou and H. E. Wan, Vegetation construction and soil and water conservation (China Forestry Publishing House, Beijing, 2002). 20. X. R. Li, F. Y. Ma, H. L. Xiao, X. P. Wang and K. C. Kim, Long-term effects of revegetation on soil water content of sand dunes in arid region of Northern China, J. Arid Environ. 57 (2004) 1–16. 21. X. Jiang, W. Huang, C. Liu and Q. Huang, Water supply need analysis for the lower Yellow River, Water Int. 29 (2004) 415–422. 22. K. Otsuki, Water balance model of forests: Integrated water resource evaluation model and its application to the Yellow River (China Water Resource and Hydro Power Publication, Beijing, 2005). (in Chinese) 23. Q. C. Hou, R. L. Han and H. P. Li, On problems of vegetation reconstruction in Yan’an experimental area III — Significance of native trees in plantation, Research of Soil and Water Conservation 7 (2000) 119–123. (in Chinese with English Summary) 24. Y. S. Li, Effects of forest on water circle on the Loess Plateau, J. Nat. Resourc. 16 (2001) 427–432. (in Chinese with English Summary) 25. K. Q. Wang, Collecting Water Silviculture and Hydro-ecology (China Forestry Publishing House, Beijing, 2001). (in Chinese) 26. P. S. Sun and L. Y. Ma, Research and Application of Tree Water use Characteristic of Water Conservation Forests (China Environmental Science Press, Beijing, 2002). 27. H. Li, Water use and water saving in Yellow River irrigation areas, Proc. 1st Int. Yellow River Forum (2003). 28. H. Oue, T. Toshiyuki, B. He and T. Keiji, Estimation and modeling of evapotranspiration to assess the water balance of the irrigated fields in the Hetao irrigation district, Proc. Int. Symp. Land and Water Management in Arid Area, Hohhot, Inner Mongolia Autonomous Region (2006). 29. H. Shi, Water and Salt Balance in the Hetao Irrigation District, personal communication. (unpublished, in Chinese.) 30. T. Akae, C. Nakao, H. Shi and Y. Zhang, Change in cation composition of water from irrigation to drainage and leaching requirement of the Hetao Irrigation District, Inner Mongolia, Proc. Int. Symp. Land and Water Management in Arid Area, Hohhot, Inner Mongolia Autonomous Region (2006). 31. T. Kume, N. Takanori, K. Hoshikawa, T. Watanabe and Chaolunbagen, Effect of leaching irrigation on the spatial distribution of soil salinity in the Hetao Irrigation District in China, Proc. Int. Symp. Land and Water Management in Arid Area, Hohhot, Inner Mongolia Autonomous Region (2006). 32. R. G. Allen, L. S. Pereira, D. Reas and M. Smith, Crop Evapotranspiration: Guideline for Computing Crop Water Requirements, FAO Irrigation and Drainage Paper 56, Rome (1998). 33. T. Kobayashi, S. Matsuda, S. Nagai and J. Teshima, A bucket with a bottom hole (BBH) model of soil hydrology, in Soil-Vegetation-Atmosphere Transfer Schemes and Large-Scale Hydrological Models, eds. A. J. Dolman, A. J. Hall, M. L. Kavvas, T. Oki and J. W. Pomeroy (IAHS Publication, 2001), pp. 41–45. 34. T. Kobayashi, R. Iwanaga, W. He and W. Wang, Application of the BBH model to water balance analyses, in Water Resource Evaluation Models and their Applications to the Yellow River Basin, eds. D. Yang and T. Kusuda, Beijing, China Shuili Shuidian Publications. (in Chinese)

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35. T. Kobayashi, J. Teshima, R. Iwanaga, D. Ikegami, D. Yasutake, W. He and H. Cho, An improvement in the BBH model for estimating evapotranspiration from cornfields in the upper Yellow River, J. Agric. Meteorol., Vol. 62 (2007). (in press) 36. R. Iwanaga, D. Yasutake, T. Kobayashi, W. Wang and W. He, Growth of corn and hydrological environments in the Togtoh experimental field in the Yellow River basin, China, Kyushu J. Agric. Meteorol. II 13 (2004) 7–12. 37. R. Iwanaga, T. Kobayashi, W. Wang, W. He, J. Teshima, and H. Cho, Evaluating the irrigation requirement at a cornfield in the Yellow River basin based on the “dynamic field capacity”, J. Japan Soc. Hydrolo. Water Resour. 18 (2005) 663–673. 38. J. Teshima, Analyses of field water balance using the BBH model of soil hydrology, Ph.D. Dissertation, Kyushu University (2006). 39. D. Yasutake, T. Kobayashi, D. Ikegami, R. Iwanaga and M. Kitano, Separation of crop transpiration and soil evaporation in a cornfield in the Yellow River basin using the dual crop coefficient approach, J. Agric. Meteorol., submitted. 40. J. Teshima, Y. Hirayama, T. Kobayashi and H. Cho, Estimating evapotranspiration from a small area on a grass-covered slope using the BBH model of soil hydrology, J. Agric. Meteorol. 61 (2006) 65–74. 41. T. Kaneko, T. Kobayashi, W. Wang, W. He and H. Cho, An evaluation of the overwinter loss of the water irrigated in late autumn in the upper reaches of the Yellow River, J. Japan Soc. Hydrolo. and Water Resour. Vol. 19 (2006). 42. T. Kobayashi, W. Wang,Y. Ikawa, H. Cho and W. He, An easily measurable and practical index of soil salinity, J. Japan Soc. Hydrolo. and Water Resour. 19 (2006) 183–188. 43. T. Kobayashi, H. Cho, T. Kaneko, W. Wang and D. Yokoyama, A field survey of the relationship between soil salinization and soil texture, Kyushu J. Agric. Meteorol. II, Vol. 15 (2006). 44. T. Kaneko, D. Yokoyama, T. Kobayashi and H. Cho, A column experiment on the relationship between soil salinization and soil texture, Kyushu J. Agric. Meteorol., II, Vol. 15 (2006). 45. W. Wang, T. Kobayashi, H. Cho and W. He, Simultaneous and continuous measurement of soil water content and solution electrical conductivity in an irrigated cornfield using TDR, J. Japan Soc. Hydrolo. and Water Resour. 19 (2006) 350–359. 46. T. Kaneko, T. Kobayashi, W. Wang, H. Cho and W. He, Characteristics related to the groundwater around a saline plot in irrigated areas, Sci. Bull. Fac. Agr. Kyushu Univ., 2006, p. 58. (in Japanese) 47. L. Wang, Y. Chen and G. Zeng, Irrigation, Drainage and Salinization Control in Neimenggu Hetao Irrigation Area (Shuili Dianli Chubansha, Beijing, 1992). (in Chinese) 48. D. Molden, Accounting for Water Use and Productivity, SWIM Paper 1. Colombo, Sri Lanka, International Water Management Institute (1997). 49. S. J. Helweg, Water for a growing population: Water supply and groundwater issues in developing countries, Water Int. 25 (2000) 33–39. 50. L. Jin and W. Young, Water use in agriculture in China: Importance, challenges, and implications for policy, Water Policy 3 (2001), 216–228. 51. Yellow River Conservancy Commission (YRCC). 1998, 1999, 2000, 2002,Yellow River Water Resources Bulletins, http://www.yrcc.gov.cn/ (2002). (in Chinese)

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52. S. R. Sun, P. S. Sun, J. X. Wang and W. L. Chen, Hydrological functions of forest vegetation in upper reaches of the Yangtze River, J. Nat. Resour. 16 (2001) 451–456. (in Chinese with English Summary) 53. X. M. Mu, X. X. Xu and J. W. Chu, Ecohydrological Studies in the Loess Plateau (China Forestry Publishing House, Beijing, 2001). 54. G. Q. Liu and W. J. Ni, On some problems of vegetation rehabilitation in the Loess Plateau, Proc. 12th ISCO Conf. (2002), pp. 207–222.

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Chapter 4

Water Quality and River Ecology

Tetsuya Kusudaa and Osamu Higashib a Kyushu b Nagoya

University, Fukuoka, Japan University, Nagoya, Japan

4.1. Water Quality in the Yellow River Basin Urban areas in China, especially the areas around megacities, have been suffering from water pollution with damaged ecosystems. Environmental standards on water quality have already been determined in major rivers; most of these rivers do not meet the international standards in quality. In China, the water quality level is divided by 5 classes (Table 4.1), with Class I being the best in quality, and Class V the worst. Current water quality in theYellow River and its tributaries is shown in Fig. 4.1. The length ratio in each water quality level of the evaluated total length of the Yellow River and tributaries (12,511 km) is 12%, 30%, 15%, 12% and 31% for Classes I and II, Class III, Class IV, Class V and under-Class V, respectively. Of under-Class V water quality, 97% is located in tributaries. Water quality problems are serious in tributaries, especially in the Wei River and the Fen River.1

4.2. Water Quality in the Wei River Basin The Wei River is a major tributary of the Yellow River basin, which is 144,000 km2 wide and 818 km long. The Wei River flows through three provinces: Shaanxi, Gansu and Ningxia. Xi’an is one of the largest cities in the central part of China and it is located in the Wei River basin in Shaanxi province. Xianyang, Baoji, Weinan, Tongchuan, and Tianshui are rural hub cities in this basin. The annual precipitation 73

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Table 4.1.

Environmental quality standard for surface water in China (unit: mg/l).

Index

Water quality level Class I

Water temperature

Class II

Class III

Class IV

Class V

Limitation of water temperature change which occurred artificially; • Increase in weekly mean maximum temperature
1◦ C (in summer) • Increase in weekly mean maximum temperature
2◦ C (in winter)

pH

6–9

DO  Permanganate
COD
BOD
NH3 -N
TP
N
T-Cu
T-Zn
F
Se
T-As
T-Hg
T-Cd
Cr (6+)
Pb
Cyanide compound
Phenol
Petroleum
Ion activator
Sulfide
Coliform bacteria count (per liter of water)


7.5 2 15 3 0.15 0.02 0.2 0.01 0.05 1.0 0.01 0.05 0.00005 0.001 0.01 0.01 0.005 0.002 0.05 0.2 0.05 200

6 4 15 3 0.5 0.1 0.5 1.0 1.0 1.0 0.01 0.05 0.00005 0.005 0.05 0.01 0.05 0.002 0.05 0.2 0.1 2,000

5 6 20 4 1.0 0.2 1.0 1.0 1.0 1.0 0.01 0.05 0.0001 0.005 0.05 0.05 0.2 0.002 0.05 0.2 0.2 10,000

3 10 30 6 1.5 0.3 1.5 1.0 2.0 1.5 0.02 0.1 0.001 0.005 0.05 0.05 0.2 0.01 0.5 0.3 0.5 20,000

2 15 40 10 2.0 0.4 2.0 1.0 2.0 1.5 0.02 0.1 0.001 0.01 0.1 0.1 0.2 0.1 1.0 0.3 1.0 40,000

Definitions Class I

• •

The area of national nature reserve Able to use for water resources

Class II

• • •

The area of wildfire refuge that is home to rare creatures Spawning area First-class protection area of surface water resources for domestic sector (Continued)

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Table 4.1.

(Continued) Definitions

Class III

• • • •

Wintering range of fish Able to farm fish Able to swim Second-class protection area of surface water resources for domestic sector

Class IV

• •

Able to use for industrial water resources Able to use for recreation (People cannot touch)

Class V

• •

Able to use for irrigation Scenic zone

Observation point 1. Houdacheng 2. Yanchuan 3. Hejing 4. Xianyang 5. Tongguan

Index of under-Class V NH3 -N, permanganate index, BOD5 , COD, P, Hg, petroleum NH3 -N, BOD5 , COD NH3 -N, permanganate index, BOD5 , COD, P, Hg, petroleum NH3 -N, permanganate index, BOD5 , COD, P, Hg, petroleum NH3 -N, permanganate index, BOD5 , COD

Fig. 4.1. The distribution of water quality level in the Yellow River basin in 2006.2

75

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Yellow River

Ningxia

Gansu Shaanxi Tongchuan Weinan Xianyang

Tianshui

Baoji

Xi’an

50 km 1 2

3

8 9 4 Weihe

5

67

10 11

12 13

50 km Fig. 4.2. The Wei River basin and field observation points.

and temperature in this basin are about 500 mm and 10◦ C, respectively, averaged over the past five years from 1999 to 2003. The basin’s current population is about 31 million, of which Shaanxi Province contains 68%. Water quality and quantity were observed at 13 locations in the Wei River basin (Fig. 4.2). An object reach for field observation in the Wei River is 500 km long, with the upper boundary at the middle part of the river and the lower boundary at the confluence of the Yellow River.3 The Wei River basin is one of the developing areas in northwest China, and has attracted considerable political attention as an important area of western region development. In recent years, the water demand in this area has been increasing dramatically because of rapid industrial development and population growth. However, infrastructure such as water supply and sewers has not yet been fully established, causing serious problems for both water quantity and quality. For example, excessive groundwater has been extracted for domestic and industrial water supplies in urban areas such as Xi’an, and large quantities of untreated domestic and industrial wastewater are discharged directly into the river. An efficient system for wastewater treatment and water reuse is urgently needed in this region (Figs. 4.3 and 4.4).

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Gansu

Shaanxi

77

Ningxia

People (million)

40 30 20 10

2002

2000

Population growth.

Shaanxi

300

Gansu

250

Ningxia

200 150 100 50

Fig. 4.4.

2002

2000

1998

1996

1994

0 1992

GDP (billions of RMB)

Fig. 4.3.

1998

1996

1994

1992

0

Growth in the gross domestic product (GDP).

4.2.1. Sources of pollutants (a) Land use Land use in the Wei River basin was mainly determined using satellite images taken by the China RSGS (Remote Sensing Satellite Ground) agency in September and October 2001 (Fig. 4.5). Urban areas and the Guanzhong Plain, a large irrigation area, were mostly distributed through the southern area of the basin, so pollutant sources were concentrated in this region, especially around Xi’an. In this basin, almost all cultivated areas are the two-crop area for grains such as wheat in winter and maize in summer.

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Cultivated area

Water

Grass

Forest

Bare area

Urban area

50 km Fig. 4.5.

Fig. 4.6.

Land use in the Wei River basin (Landsat-7; ETM+ , 2000–2002).

Population distribution in the Wei River basin in 2000 (unit: 10,000 people).

(b) Population and industrial facility distributions The distribution of population in the Wei River is indicated in Fig. 4.6. The population is concentrated in Xi’an where the density is highest. Data about the distribution of industries was not available, so the distribution of industries larger than a certain size, i.e., those with an annual production greater than 5 million RMB was assumed to be proportional to the population distribution, and those smaller than the size were assumed to be distributed in the rural areas.

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Table 4.2. Water demand for domestic use (Basic units of water-use and population in the Wei River basin). Year: 2000 Basic units of water use (L/person/day) Population in the basin (unit: 10,000 people)

Shaanxi

Gansu

Ningxia

184 46 1,689 435

73 49 328 792

110 30 12 79

Urban area Rural area Urban area Rural area

Table 4.3. Water demand for industrial use (Basic units of water-use in the Wei River basin). Category

Basic units of water use (m3 /Yuan/year)

Gross industrial output (100 million Yuan/year) Shaanxi

Gansu

Ningxia

Greater than a certain size*

Heavy industry Light industry

0.015 0.005

575 309

81 21

2 3

Less than a certain size

Heavy industry Light industry

0.004 0.004

551 421

36 9

1 1

*The size was determined as those companies with an annual industrial production greater than 5 million RMB (Renminbi).

(c) Water demand distribution Water demand for daily life ranges from 30 to 184 L/person/day in the basin. Irrigation ranges from 4,275 to 9,285 m3 /ha/year. Water demand for industrial use ranges from 4 to 15 L/Yuan/year, depending on the product (Tables 4.2 and 4.3). The total amount of water-use and the water demand distribution in the Wei River basin in 2002 based on the land use, population distribution, and sectoral basic units of water-use (Fig. 4.7). The annual water-use in this region in 2002 was 7 billion tons/year. Water-use is concentrated in the Guanzhong Plain because of its heavy irrigation and large population.

4.2.2. Pollutant unit loads and loading rates (a) Point sources Pollutants discharged from point sources were estimated using basic units of pollutant. Pollutant loads, based on the basic units of biodegradable organic substances (BOD), suspended solids and ammonium nitrogen, are present in domestic and industrial wastewater and treated wastewater (Table 4.4). The basic units for domestic wastewater are observed ones in China. Those for industrial wastewater were from Chinese environmental yearbooks and those

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Fig. 4.7. Water demand distribution in the Wei River basin in 2002.

Table 4.4. Pollutant load in basic units of 5-day biological oxygen demand (BOD5 ), suspended solids (SS), and ammonium nitrogen (NH+ 4 -N).

Domestic wastewater Industrial wastewater Treated industrial water

BOD5

SS

NH+ 4 -N

50 0.2 0.01

14 0.09 0.01

14 0.03 0.005

(g/day/λ) (kg/m3 ) (kg/m3 )

for treated water were based on effluent quality from the Beishiqiao wastewater treatment plant located in Xi’an. Because this plant only treats industrial wastewater, the basic units were relatively low compared with those from domestic and industrial wastewater treatment plants. The proportion of wastewater treated in urban areas was 20% in 2004. The annual loading of BOS in the Wei River basin in 2002 is shown in Fig. 4.8. (b) Non-point sources Pollutant loads from non-point sources such as urban areas, agricultural fields, and forest are conveyed into rivers with precipitation. The amounts of pollutant loads from non-point sources differ widely depending on characteristics of the basin such as land cover and rainfall intensity. There are few observed data of pollutant loads in China. In agricultural fields, pollutant sources are crop residues and run-off fertilizers from cultivated areas and rainwater. Pollutant loads from non-point sources are able to estimate using the soil and water integrated model (SWIM) developed by the Potsdam Institute in Germany. The framework of pollutant discharge estimation from non-point sources is shown in Fig. 4.9. The SWIM consists of four calculation frameworks: hydrological cycle,

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(2.5 km grid;unit: t/year) 0-5 5 - 100 100 - 1,000 1,000 - 5,000 5,000 -

50 km

Weinan

Baoji Xianyang

Xi’an

Fig. 4.8. Annual loading of biodegradable organic substances in 2002.

Fig. 4.9.

Framework of pollutant discharge based on the calculation of non-point sources.

crop and vegetation growth, erosion and nutrient dynamics. It can be used to estimate river discharge and the concentrations of some pollutants in river water with a certain limitation on basin scale. Because a basin such as the Wei River basin is larger than 10,000 km2 , the geomorphology-based hydrological model

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(GBHM) is applicable instead of SWIM (refer to Chap. 6). Crop-based pollutants are estimated using the erosion productivity impact calculator (EPIC) developed by the United States Department of Agriculture (USDA). Input data are sediment conditions, fertilizer application, irrigation, meteorological data and land use. The EPIC precisely simulates the process of crop and vegetation growth and predicts crop yield with high accuracy. Records on fertilizer application and cropping in the Wei River basin are given in China statistical yearbooks. The estimated data were compared with the field data on winter wheat (Fig. 4.10) and maize production (Fig. 4.11). Nitrogen (N) is divided into four parts: mineral N, fresh organic N, active organic N, and stable organic N. Nitrogen dynamics include uptake by the crop, runoff, leaching to groundwater, erosion, ammonia oxidation, and denitrification (Fig. 4.12).

Products (million ton)

Precipitation (mm)

6

500 450

5

400 350

4

300 250 200

3 2

150

Precipitation (mm)

Statistical products (t) Calculated products (t)

100

1

50 0

0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Year

Fig. 4.10. Winter wheat production in the Wei River basin.

Statistical products (t) Calculated products (t) Precipitation (mm)

450

5

400 350

4

300 250

3

200 2

150 100

1

50 0

0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Year

Fig. 4.11.

Maize production in the Wei River basin.

Precipitation (mm)

Products (million ton)

500 6

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Fig. 4.12.

Fig. 4.13.

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Nitrogen dynamics.

Phosphorus dynamics.

Phosphorus (P) is divided into five parts: labile P, active mineral P, stable mineral P, fresh organic P, and organic P. Phosphorus dynamics include uptake by the crop, runoff, leaching to groundwater, erosion, and filtration (Fig. 4.13). The sediment erosion rate is able to calculate with the municipal universal soil loss equation (MUSLE). The total annual amount of sediments eroded in the Wei River basin in 1998 was 0.5 billion tons/year (Fig. 4.14). Most of the sediments are produced in the southern part of the Loess Plateau. The annual load of organic nitrogen in the Wei River basin in 2002 was mainly discharged from livestock and farmlands in the Guanzhong Plain, as well as from humans (Fig. 4.15).

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Fig. 4.14. Annual amount of sediments eroded in the Wei River basin.

Fig. 4.15. Annual load of inorganic nitrogen in the Wei River basin.

4.3. Water Quality in the Wei River 4.3.1. Observational results Water quality and quantity were observed at 13 locations along the Wei River from 2003 to 2007 (Fig. 4.2). About 80% of the wastewater from the domestic and industrial sectors in urban areas are discharged directly into the river, resulting in high concentrations of BOD5 and NH+ 4 -N in the river (Fig. 4.16). Nitrate

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concentrations were relatively high at Sampling Points 1–4, which were located near huge irrigation areas that act as non-point sources (Fig. 4.16). The BOD5 concentration was improved from 2002 to 2006, although the sampling was performed on sunny days. The BOD5 concentration changed drastically at the observation point 7 in Xianyang. In 2003, untreated domestic wastewater was discharged directly into the area, so the BOD5 concentration reached over 200 mg/L during a dry season. In 2006, the flow route was changed, so that the BOD5 concentrations dropped down to low levels. For SS, with the exception of August and November 2003, these measurements were performed under relatively heavy rainfall, and the annually averaged concentrations on suspended solids were similar to each other (Fig. 4.16(c)). For April to November 2005, heavy metals Zn, Cr, Cu, and Pb were measured after (Fig. 4.16(a)) and before (Fig. 4.16(b)) filtration. The concentrations of heavy 2003 .01 2003 .11

2002 .10 2003 .08 0

50

100

[km] 150 200

250

300

350

2003 .04

0

250

50

100

[km] 150 200

250

300

350

300

350

40

200

150

TN (mg/l)

BOD5 (mg/l)

30

100

20

10 50

0

0

50

100

[km] 150 200

250

300

350

0

100

[km] 150 200

W-13

W-11 W-12 250

40

100

80

30 TN (mg/l)

60

40

20

Fig. 4.16.

(a) Observed results on water quality in the Wei River.

W-13

W-11 W-12

W-5 W-6 W-7

W-4

0

W-1 W-2 W-3

W-13

W-11 W-12

W-8 W-9 W-10

W-5 W-6 W-7

W-4

0

W-8 W-9 W-10

10

20

W-1 W-2 W-3

BOD5 (mg/l)

50

W-8 W-9 W-10

2004 .04 2004 .11

W-5 W-6 W-7

W-1 W-2 W-3

2004 .01 2004 .08

W-4

W-13

W-11 W-12

W-8 W-9 W-10

W-5 W-6 W-7

W-4

W-1 W-2 W-3

0

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2005 .01 2005 .11 0

50

100

[km] 150 200

250

300

350

0

100

[km] 150 200

100

[km] 150 200

250

300

350

300

350

30

60

TN (mg/l)

40

20

350

0

20

8

50

100

[km] 150 200

250

300

350

0 10

20

8 NO3--N (mg/l)

25

15

10

W-13

W-11 W-12

W-8 W-9 W-10

0

W-5 W-6 W-7

0

W-4

100

[km] 150 200

250

W-13 300

350

4

2

W-1 W-2 W-3

50

6

5

Fig. 4.16.

2005 .08 2006 .05

2005 .04 2006 .02

(b) Observational results for water quality in the Wei River.

W-13

0

W-1 W-2 W-3

W-13

W-11 W-12

W-8 W-9 W-10

W-5 W-6 W-7

0

W-4

0

W-1 W-2 W-3

2

W-13

4

5

2005 .01 2005 .11

W-11 W-12

6

W-11 W-12

10

250

W-11 W-12

15

50

W-8 W-9 W-10

NO3--N (mg/l)

10

W-8 W-9 W-10

300

W-5 W-6 W-7

250

W-5 W-6 W-7

[km] 150 200

W-4

100

25

W-4

50

W-5 W-6 W-7

W-1 W-2 W-3 2004 .04 2004 .11

2004 .01 2004 .08 0

W-4

0

W-13

W-11 W-12

W-8 W-9 W-10

W-5 W-6 W-7

W-4

W-1 W-2 W-3

0

W-8 W-9 W-10

10

20

W-1 W-2 W-3

BOD5 (mg/l)

50

40

80

NH4+-N (mg/l)

2005 .08 2006 .05

2005 .04 2006 .02

100

NH4+-N (mg/l)

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300

0

350

1200

1200

900

900

SS (mg/l)

1500

600

0

50

100

[km] 150 200

W-13

W-11 W-12

W-8 W-9 W-10

0 W-5 W-6 W-7

0 W-4

300

2005 .04 2006 .02

100

[km] 150 200

250

300

350

600

300

2005 .01 2005 .11

50

W-11 W-12

250

W-8 W-9 W-10

[km] 150 200

W-5 W-6 W-7

100

W-4

50

1500

W-1 W-2 W-3

SS (mg/l)

0

2004 .04 2004 .11

2004 .01 2004 .08

2003 .04

W-1 W-2 W-3

2003 .01 2003 .11

2002 .10 2003 .08

87

W-13

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2005 .08 2006 .05 250

300

350

1500

SS (mg/l)

1200

900

600

Fig. 4.16.

W-13

W-11 W-12

W-5 W-6 W-7

W-4

W-1 W-2 W-3

0

W-8 W-9 W-10

300

(c) Observed results on suspended solids in the Wei River.

metals were very high before filtration. This means that large amounts of heavy metals are adsorbed onto SS. Although the concentrations of heavy metals rarely reached Class V (the worst level) of the China water quality standards, Zn and Cu levels were higher for fishing (Fig. 4.17).

4.4. Simulation with an Integrated Model on Water Quality and Quantity 4.4.1. Integrated model of water quantity and quality The structure of an integrated model on water quantity and quality is shown in Fig. 4.18. The model consists of five parts: a hydrological module, a mathematical module of pollutant discharge from point sources, a mathematical module of pollutant discharge from non-point sources, a sediment erosion module, and a

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Fig. 4.17.

Observed results on heavymetals in the Wei River.

water quality module. The hydrological module, GBHM, is based on a hill-slope model and includes runoff, transpiration, evaporation, infiltration, and groundwater movement processes. Artificial water-use is added to the basic model. Pollutant discharge from point sources was calculated using basic units, and pollutants from non-point sources were derived using the EPIC and SWIM nutrient discharge models. Sediment erosion rates were calculated using the MUSLE. The following − water quality parameters were estimated: SS, BOD5 , DO, NH+ 4 -N, and NO3 -N. Meteorological input data Hourly precipitation was calculated based on daily precipitation and its duration (Fig. 4.19) and the data were distributed to each grid cell of the basin map.

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Fig. 4.18.

89

Structure of the integrated model on water quantity and quality.

Fig. 4.19. Distribution of precipitation observation points in the Wei River basin and daily precipitation in Xi’an in 2002.

Daily averaged temperature data were also obtained at the same observation points. Hourly change in temperature was calculated using a sine curve. Potential daily evapotranspiration was calculated based on the Penman–Monteith method. Evapotranspiration was assumed to occur from 8:00 to 20:00 hrs. Evaporation was assumed to occur only at night. The values of evaporation and transpiration in evapotranspiration were assumed to be the same. Land use input data The land use, population distribution, industrial facilities and irrigation in the Wei River basin were above mentioned.

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Water-use data Only data about the distribution and capacity of large- and medium-scale reservoirs in the Wei River basin were available. The water supply area of each reservoir was assumed to be the nearest city or the nearest irrigation area and adjusted the amount of water supply from each reservoir based on China statistical yearbooks. Hydrological module The hill-slope model element consists of an unsaturated and a saturated layer, and the slope gradient was estimated by averaging the vertical diference within each grid cell. The unsaturated layer was assumed to have a thickness of 4 m, with five sub-layers; the saturated layer was assumed to have a thickness of about 20 m, with one layer. The canopy interception capacity was calculated as Sco = 0.15 LAI, where Sco is expressed in mm, and LAI is the leaf area index. The LAI was determined from NDVI (Normalized Difference Vegetation Index), which was obtained from NOAA satellite images from 1981 to 2000. Actual evapotranspiration was assumed to be 80% of the potential evapotranspiration estimated with the Penman–Monteith method (Fig. 4.20: (2),(3)). The hill-slope surface runoff was generated using the

Fig. 4.20.

Hydrological cycle in the integrated model of water quantity and quality.

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Richard’s equation, which can be interpreted as the Dunne saturated overland flow and the Horton overland flow. Flow routing on a hill-slope surface was treated as a steady flow and was calculated using Manning’s equation (Fig. 4.20: (4)). Water flow in an unsaturated zone can be described using the one-dimensional Richard’s equation. The van Genuchten equation was used for the unsaturated permeability coefficient (Fig. 4.20: (5),(6)). The groundwater level was calculated using relationships with water flow in the unsaturated zone, groundwater runoff, and groundwater absorption in each grid cell. The groundwater runoff between each grid cell or the aquifer in each grid cell was calculated using Darcy’s Law. The sectoral groundwater abstraction in each grid cell was calculated based on China statistical yearbooks (Fig. 4.20: (7)(8)). In urban areas, the amount of domestic drainage was assumed to be equal to domestic water requirements, and the proportion of domestic wastewater treatment was 20%. Hourly domestic drainage volume and basic units of pollutant loadings (Table 4.2) were used to estimate the domestic pollutant discharge into rivers. The amount of industrial drainage takes into consideration on both fresh and recycled water, and the industrial pollutant discharge was estimated using the same method on domestic pollutant discharge. From 1992–2001, the recycle rate of industrial wastewater was 50–60%, and the proportion of wastewater treatment was about 20% in the Wei River basin (Fig. 4.20: (11)(12)). The Wei River basin was divided into a grid with cells of 2.5 × 2.5 km instead of 10 × 10 km. This module is explained in detail in Sec. 6. Water quality module A one-dimensional advection–dispersion equation based on the Streeter–Phelps − model was used to analyze water quality; SS, BOD5 , DO, NH+ 4 -N, and NO3 -N (Eq. (1)). The kinematic wave method was used to compute river discharge.
 ∂ ∂Ci ∂(ACi ) ∂(qflow Ci ) − ADL − Afi + Qin_i = 0, (1) + ∂x ∂x ∂x ∂t where qflow is flow discharge (m3 /day), A is the river’s cross sectional area (m2 ), Ci is the concentration of substance i (kg/m3 ), t is the time step (day), x is the stream distance (m), DL is the diffusion efficient (m2 /day), fi is the substance conversion velocity (kg/m3 /day), and Qin_i is the amount of pollutant inflow (kg/m/day). DL is calculated using Eq. (2), with the assumption that the river is an open channel.  (2) DL = 5.86Rd gRw Rs ,

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where Rd is river water depth (m), g is the acceleration of gravity (m/day2 ), Rw is the hydraulic radius (m), and Rs is the hydraulic gradient. The river width and depth in each grid cell were based on observational data and GIS images. When the shear stress acting on sediment surface exceeds the critical sheer stress, it causes sediment erosion. The SS supplied from sediments were assumed to be unlimited, so sediment erosion could increase exponentially with increments of shear stress. Based on this assumption, Eq. (3) was used to calculate the flux in sediment erosion. 
τe − τce ne , (3) Fe = αe τce where Fe is sediment erosion flux (kg/m2 /day), τe is shear stress (Pa), τce is the critical shear stress for sediment erosion (Pa), τe is a coefficient (kg/m2 /day), and ne is a coefficient. When the shear stress acting on sediment surface is less than the critical shear stress, it causes deposition of SS. The deposition of SS was assumed to increase exponentially with the decreases in shear stress. Based on this assumption, Eq. (4) was used to calculate the flux in SS deposition.
 τcd − τe nd , (4) Fd = αd τcd where Fd is the deposition flux of SS (kg/m2 /day), τcd is the critical shear stress for SS deposition (Pa), αd is a coefficient (kg/m2 /day), and nd is a coefficient. In addition, the critical shear stress for SS deposition was assumed to be 0.8 times the critical shear stress for sediment erosion. When the shear stress is lower than the critical shear stress for sediment erosion and greater than the critical shear stress for the deposition of SS, neither sediment erosion nor deposition occur. The BOD reaction rate was calculated using Eq. (5). fBOD = −(K1L + K3L )CBOD ,

(5)

where fBOD is the BOD reaction rate (kg/m3 /day), K1L is the rate coefficient (day−1 ), and K3L is the deposition and adsorption rate coefficient (day−1 ). The DO consumption rate was calculated using Eq. (6). ∗ fDO = K1L CBOD − K2 (CDO − CDO ) + DB ,

(6)

where fDO is the DO consumption rate (kg/m3 /day), K1L is the rate coefficient (day−1 ), K2L is the re-aeration coefficient (day−1 ), DB is the DO consumption ∗ excluding the biological reactions (kg/m3 /day), and CDO is the saturated DO

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Fig. 4.21.

93

Nitrogen conversion processes that take place in a river.

concentration (kg/m3 ). The re-aeration coefficient was calculated using the O’Connor–Dobbins method. In the nitrogen conversion processes in a river, facultative anaerobic microorganisms and inorganic ions have a relationship based on intake and emission (Fig. 4.21). Intake was assumed to be equal to emission. Facultative anaerobic microorganisms and suspended organic substances have a relationship based on death and intake (Fig. 4.21: (5),(6)). No data were available on the suspended organic substances in the Wei River basin, so we assumed that the suspended organic substances intake of facultative anaerobes was equal to the death of facultative anaerobes. To analyze ammonium nitrogen, the reaction velocity of nitrification is calculated using Eq. (7). RNH4 =

1 YNH ×

µmax.NS · fNS (Temp)

KS.DO KS.DO + CDO

CNH XNS CSS , KS.NS + CNH

(7)

where YNH is the yield coefficient, µmax.NS is the maximum specific growth rate (day−1 ), fNS (Temp) is the reaction efficiency, which is a function of temperature, KS.DO is the saturation constant in DO (kg/m3 ), KS.NS is the saturation constant in bacteria (kg/m3 ), XNS is the bacterial concentration (kg/kg), and the subscript (NS) indicates nitrifying bacteria. Observations indicated that pH in the Wei River was maintained at 7 to 8, the effect of pH on the reaction is ignored. The mass balance equation for nitrifying bacteria that are attached to SS is expressed as: KS.DO ∂XNS = µmax.NS · fNS (Temp) ∂t KS.DO + CDO ×

CNH XNS CSS − Kd.NS fNS (Temp)XNS CSS , KS.NS + CNH

(8)

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where Kd is the death constant (day−1 ). The NH+ 4 -N conversion velocity can be calculated as: fNH4 = −RNH4 ,

(9)

3 where fNH4 is the conversion velocity of NH+ 4 -N (kg/m /day). Some areas of water in the Wei River basin had DO concentrations of less than 1 mg/L during the dry season. This may indicate the occurrence of denitrification. The reaction rate of denitrification can be calculated as:

RD =

1 KD.DO CNO3 µmax.D · fD (Temp) · YD KD.DO + CDO KD.NO3 + CNO3 ×

COS XD CSS , KD.OS + COS

(10)

where the subscript D represents denitrifying bacteria and (OS) represents suspended organic substances. The mass balance equation of denitrifying bacteria attached to (SS) can be expressed as: ∂XD KD.DO CNO3 · = µmax.D · fD (Temp) ∂t KD.DO + CDO KD.NO3 + CNO3 ×

COS XD CSS − Kd.D fD (Temp)XD CSS , KD.OS + COS

(11)

The conversion velocity of NO− 3 -N can be calculated as: fNO3 = RNH4 − RD ,

(12)

3 where fNO3 is the conversion rate of NO− 3 -N (kg/m /day).

4.4.2. Computational results Flow rates at Xianyang (Observation point 7) were reproduced with the “GBHM + artificial” model. The results show better results than did GBHM alone (Fig. 4.22). The GBHM +artificial model included natural water circulation and sectoral water use, reservoir storage and discharge, irrigation intake, water-use in urban areas, and groundwater extraction. − Changes in the concentrations of SS, BOD5 , DO, NH+ 4 -N, and NO3 -N with stream distance on one day in January 2004 were simulated using the one-dimensional advection–dispersion equation (Fig. 4.23). Changes in their concentrations were also simulated throughout the year to clarify seasonal variation. The simulation results agreed with the observations.

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Fig. 4.22.

River water flow rates at Xianyang at Observation Point 7.

20

Baoji

3

Xianyang 8 9

4

5 Weihe

DO(mg/l)

Weinan

1 2

95

12 13 10 11

6 7 Xi’an

50km

cal. obs.

15 10 5

cal. obs.

200 100 0 100 80 60 40 20 0 0

cal. obs.

100 200 300 400 stream distance(km)

NO3- -N(mg/l)

SS(mg/l) BOD5 (mg/l)

300

NH 4+-N(mg/l)

0 400

500

25 20 15 10 5 0 10 8 6 4 2 0 0

cal. obs.

cal. obs.

100 200 300 400 stream distance(km)

500

Fig. 4.23. Changes in the concentration of suspended solids (SS), biological oxygen demand (BOD5 ), − dissolved oxygen (DO), ammonium nitrogen (NH+ 4 -N), and nitrate (NO3 -N) with stream distance on a certain day in January 2004.

The groundwater level has lowered in the Wei River basin (Fig. 4.24). Excessive extraction of groundwater has been performed in Xi’an, Xianyang, and Tianshui for irrigation purposes, as well as domestic and industrial water supplies. In the regions, the annual groundwater level decrease is approximately 1 m (Fig. 4.25).

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3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0

Fig. 4.24.

Fig. 4.25.

06/05

06/02

05/11

05/08

05/05

05/02

04/11

04/08

04/05

04/02

Obs.

03/11

Depth (m)

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Observed groundwater level decrease in XingPing near Xi’an (2003–2006).

Distribution of annual groundwater level decrease in the Wei River basin.

4.4.3. Toward future The Xi’an wastewater treatment plan (Table 4.5) was published in 1995. The goal is to reach a proportion of 55% wastewater treatment in the central area and 35% around the central area by 2010. Wastewater treatment plans for other cities such as Xianyang, Weinan, Tongchuan, Baoji, and Tianshui were not available. However, based on the desired proportion of water treated in Xi’an, the proportion of water treated in these cities will also likely to increase in the near future. Improving the water quality of the Wei River requires reducing pollutant loads. Simulations revealed that lowering the BOD to a level of 20 mg/L requires an 80% reduction in pollutant load from urban areas. One countermeasure is the construction of wastewater treatment plants, but their construction would result

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Table 4.5. Wastewater treatment plan for Xi’an. Unit

Coverage of the wastewater culvert Coverage of the rainwater culvert Wastewater treatment ratio Wastewater recycling

2010

2020

Central area

Around central area

Central area

Around central area

%

85

50

95

70

% % m3 /day

65 55 150,000

40 35 80,000

80 75 370,000

60 55 310,000

in increased water consumption. It takes time to reach a better environment in the basin. Under this circumstance, the installation of bio-toilets in rural areas is another option.

4.5. River Environment in Xi’an Xi’an has two major tributaries of the Wei River, the Zaohe River and the Bahe River. These rivers have completely different roles. Water quality and quantity were observed at six locations along these rivers (Fig. 4.26). In this city, each river serves a clear role.

Fig. 4.26.

Six sampling locations on urban rivers in the city of Xi’an.

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4.5.1. Urban areas The Zaohe River mainly serves as open drainage for regional wastewater. The Zaohe River basin has a 22.3-km reach, with its upper boundary at the west side of Weiqu and its lower boundary at the confluence of the Wei River (Fig. 4.27). The basin is 135 km2 in area. Within this basin, wastewater and treated wastewater flowed into the river from five drainage areas, and tap water for residential and industrial areas is supplied from five water sources. The basin contained three irrigation areas. − The BOD5 , NH+ 4 -N, NO3 -N, and TN concentrations were measured at several sampling locations (Fig. 4.27). About 80% of wastewater from the domestic and industrial sectors flowed directly into the river, resulting in high BOD5 and NH+ 4 -N concentrations. The BOD5 concentrations were particularly high, more than 200 mg/L, during the dry seasons of winter and spring. Although Observation Point Z2 was located very close to the Beishiqiao wastewater treatment plant, the BOD5 concentration at this point was more than 100 mg/L, indicating that the wastewater treatment system in this city had serious problems. In contrast, nitrate concentrations were very low at each point, indicating that irrigation appears to have a small impact on water quality in the Zaohe River (Figs. 4.28 and 4.29).

Fig. 4.27. The Zaohe River basin.

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Fig. 4.28.

Observed results for water quality in the Zaohe River.

99

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Fig. 4.29. Temporal changes in BOS, ammonium discharge and flow rates at Observation point Z1 in the Zaohe River.

Unlike the Zaohe River, the main role of the Bahe River is to provide water − resources, requiring relatively high water quality. BOD5 , NH+ 4 -N, NO3 -N, and TN concentrations were measured at several sampling locations (Fig. 4.30). The discharge of untreated wastewater into this river has been prohibited, so good water quality has been maintained.

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Fig. 4.30.

Observed results for water quality in the Bahe River.

101

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4.5.2. Effects of reservoirs Reservoirs are distributed throughout the Wei River basin (Fig. 4.31). Photos 4.1 and 4.2 show the Baojixia and Jinpen dams, respectively. The former mainly supplies irrigation water for the Guanzhong Plain and the latter supplies tap water for the central area of the city of Xi’an. Neither has a downstream water supply. The current priority for the Wei River basin is to secure water resources for sectorial water use; the goal is to overcome the water shortage and stabilize economic growth. Because the preservation of river ecosystems is not necessarily a high priority, many rivers in the Wei River basin have no downstream water supply.

Fig. 4.31.

Reservoirs in the Wei River basin.

(a) Baojixia reservoir. Photo 4.1.

(b) Downstream of the Baojixia dam. Baojixia dam.

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(a) Jinpen reservoir.

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103

(b) Downstream of the Jinpen dam. Photo 4.2.

Jinpen dam.

However, river water tends to reappear a few kilometers downstream, probably mainly from irrigation drainage and domestic and industrial wastewater.

References 1. Yellow River Conservancy Commission (YRCC), The Yellow River Water Resources Bulletin, http://www.hwswj.gov.cn (2003). 2. Yellow River Conservancy Commission (YRCC), YRCC report of water resources in the Yellow River Basin (2006). 3. T. Kusuda and O. Higashi, Modeling of pollutant load in urban areas, in Integrated Water Resource Evaluation Model and its Application to the Yellow River (China Water Resource and Hydro Power Publication, Beijing, 2005), pp. 141–164.

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Chapter 5

Sediment Yield and Transport in the Middle Yellow River Basin

Haruyuki Hashimotoa , Hiroki Takaokab , Takahito Uenoc and Byungdug Jund a Kyushu

University, Fukuoka, Japan University, Nagoya, Japan c Sojo University, Kumamoto, Japan d Nagasaki University, Nagasaki, Japan b Nagoya

5.1. Sediment Yield Most of the sediments in the Yellow River come from the Loess Plateau, especially from small areas of the plateau with very large sediment yield.1 Generally, the particle size of the sediments is related to the land cover characteristics in the source region. Figure 5.1 shows the type of land-cover for the upper and middle reaches of the Yellow River1 and that derived from LANDSAT images. Only minor differences exist between them, that is, processed LANDSAT images are more detailed. Figure 5.2, which shows the original data from Ref. 1 reveals variations in the median diameter of the Plateau soil. The median particle diameter ranges from 0.045 mm in the northwest to less than 0.015 mm in the southeast. Figure 5.3 indicates maximum sediment yield was 25,000 t/km2 and the minimum sediment yield was 4,000 t/km2 . As for particle diameters, the dominant trend for sediment yield was highest in the North and decreased to the South.

105

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Fig. 5.1. Land-cover types published previously (left; source: Wan and Wang1 ) and determined using LANDSAT images (right).

Fig. 5.2. Distribution of sand and soil particle sizes in the upper and middle reaches of the Yellow River. Source: YRCC.2

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107

Fig. 5.3. Distributions of the annual generation for sand (left) and soil (right), (unit: t/km2 /yr). Source: YRCC.2

5.2. Fluvial Geomorphology Tributaries located along the right bank of the middle reach of the Yellow River are the major source of sediments into the Yellow River as shown in Fig. 5.3.

5.2.1. Analytical framework Eight rivers, the Kuye, Tuwei, Jialu, and Dali (a branch of the Wuding River) rivers and four other rivers, are the major sources for sediment generation in this region (Fig. 5.1). Topographic maps (China 1/100,000) are fundamental data sources. It is not easy for foreigners to obtain any topographic maps with elevation in China, thus a set of maps made by USSR (1978–1986) was used instead. The overlaying of other data on the maps such as LANDSAT satellite images was done for the determination of land-cover and vegetation.

5.2.2. Analysis of geographic information and satellite images (a) Analysis of topographic maps Simple image processing of the topographic maps enabled the extraction of water areas (shown in blue) and clear interpretation of river channels. The channel networks of the Kuye and Dali rivers were derived using this method (Fig. 5.4). Watersheds were then determined on the basis of the channel networks. Hand-drawn maps of the watershed surface geology of the Kuye and Dali Rivers (Fig. 5.4) is applicable to determine the extent of watersheds from detailed channel networks.

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Sand Gravel Loess Gauging station

Kuye River basin Fig. 5.4.

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Sand Loess Gauging station

Dali River basin

Geological information on watersheds of the Kuye (left) and Dali Rivers (right). Source: Li.3

(b) GIS image processing GTOPO30 is also available to draw contour lines for the Kuye River and Dali River basins. Figure 5.5 shows contour line maps of the rivers. Figures 5.6 and 5.7 give river-bed gradients and river widths for the eight tributaries under analysis, respectively. The calculated NDVI (Normalized Difference Vegetation Index) image shows the distribution of green land (Fig. 5.8).

5.2.3. Comparison of the eight tributaries in the middle reach of the Yellow River Results of analysis on the eight tributaries are presented in Table 5.1. The Kuye River basin is the largest and 8,713 km2 in area. The New-2 River basin is the smallest and 879 km2 in area. Although the Dali River is a tributary of the Wuding River, it is 3,914 km2 in area and the second-largest. The study area is classified as a gullied-hilly loess district. The eight tributaries have similar NDVI values (Fig. 5.3) and the mean NDVI values range from 0.042 to 0.067. The Tuwei River is the widest and is 112 m in width. The Kuye River is relatively wide at 106 m. The Jialu River is the narrowest at 29 m. The Dali River exhibited the greatest variation in elevation along its course (1,046 m). The land surface conditions between the upper and lower sections of the river basins varied considerably.

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109

Fig. 5.5. Contour line maps of (a) the Kuye River basin and (b) the Dali River basin, extracted from GOTO30 data and DEM GIS database.

5.3. Field Measurements of Flood Flows 5.3.1. Rainfall–runoff relationships The Kuye, Tuwei, Jialu and Dali rivers represent a significant erosion area in the Yellow River basin.3 The major river characteristics are shown in Table 5.2 and current hydrological stations are in Fig. 5.9, where precipitation, flow discharge, sediment discharge, flowing sediment characteristics and so on, have been measured.14

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1600

m

Elevation (m)

1400 Kyue Tuwei Jialu Dali New-1 New-2 New-3 New-4

1200 1000 800 600 400 200 0 0

50

100

150

200

250

km

Distance from the river mouth Fig. 5.6.

300

River bed elevations with distance from the river mouth.

m

Elevation (m)

250

Kyue Tuwei Jialu Dali New-1 New-2 New-3 New-4

200 150 100 50 0 0

50

100

150

200

250

km

Distance from the river mouth Fig. 5.7.

River widths with distance from the river mouth.

Figure 5.10 shows a typical rainfall–runoff relationship at a hydrological station in the Kuye River. Figure 5.11 presents average and peak runoff coefficients. For comparison, those of Japanese river basins are also plotted. The average and peak runoff coefficients for these field data were defined as

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Fig. 5.8.

Table 5.1.

111

Calculated results on NDVI data.

Characteristics of the eight tributaries.

River

Area (km2 )

NDVI (DN*)

Width (m)

Height (m)

Kuye Tuwei Jialu Dali New-1 New-2 New-3 New-4

8,713 3,220 1,138 3,914 3,249 879 1,273 4,083

0.056 0.067 0.048 0.052 0.059 0.042 0.059 0.058

106 112 29 52 40 28 34 49

983 925 968 1,046 955 994 1,038 882

*DN: Calculated Digital Number.

follows: 



Q dt = 10 f0 3

Qp =

1 fp r¯ A, 3.6

 r dt A,

(1) (2)

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Table 5.2.

Characteristics of the Kuye, Tuwei, Jialu and Dali Rivers.

River

Basin area (km2 )

River length (km)

River slope

Kuye

8,713

242

1/510 to 1/290

Tuwei Jialu Dali

3,220 1,138 3,914

130 75 170

1/330 to 1/200 1/220 to 1/100 1/550 to 1/230

Riverbed sediments

Transported sediments in flood flows

Very fine sand to coarse sand

Average annual rainfall (mm) 396

Silt Silt Silt to very fine sand

419

Fig. 5.9. The Kuye River basin. (Open circles indicate current hydrological stations).

 where Q dt = the total volume of flood runoff (m3 ), f0 = the average runoff coefficient, r = the rainfall intensity (mm/h), A = the drainage basin area (km2 ),  r dt = the total rainfall (mm), Qp = the peak discharge (m3 /s), fp = the peak runoff coefficient, and r¯ = the average rainfall intensity. Average runoff coefficients in these river basins were f0 = 0.05–0.62. The peak runoff coefficients (fp ) in the river basins range from 0.05–1.57. The values greater than 1 were caused by high sediment concentrations in flood flows.

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113

Kuye River (Wangdaohengta)

r (mm/h) 50 40 30 20 10 0 1979/8/7 12:00

Q (m3/s) 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 1979/8/7 12:00 Fig. 5.10.

8/8 0:00

8/8 12:00

Kuye River (Wenjiachuan) Flow discharge Sediment concentration

8/8 0:00

Kuye River (Wangdaohengta) Kuye River (Shenmu) Kuye River (Wenjiachuan) Tuwei River (Gaojiachuang) Jialu River (Shengjiawang) Japan

0

2 1.5

8/8 12:00

f

p

2

8/9 0:00

1

0.5

0.5

5,000 A (km2)

10,000

Kuye River (Wangdaohengta) Kuye River (Shenmu) Kuye River (Wenjiachuan) Tuwei River (Gaojiachuang) Jialu River (Shengjiawang)

1.5

1

0

CT 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Rainfall and discharge measured at the Kuye River hydrological station, Wenjiachuan.14

f

0

8/9 0:00

0

0

5,000 A (km2)

10,000

Fig. 5.11. Average and peak runoff coefficients obtained at the Kuye, Tuwei, and Jialu River hydrological stations.

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5.3.2. Sediment particle size in flood flows and on riverbeds In the relationship between a diameter d50 of flowing sediments and the concentration in flood flows, the size of flowing sediment particles change with sediment concentration in flood flows (Fig. 5.12). In the Kuye River, the median diameter d50 is almost constant when CT < 0.01, whereas it increases with sediment concentration when CT > 0.01, where CT is the flux-averaged concentration of sediments. At the highest concentration (CT = 0.5), the median diameter (d50 ) is approximately 0.5 mm. This relationship is similar to that observed in the Wuding River.1 The size of sediment particles in flood flows increases during the increasing stage of discharge, but decreases during the decreasing stage.

1979/8, Wangdaohengta 1979/8, Shenmu 1979/8, Wenjiachuan 1981/7, Shenmu 1981/7, Wenjiachuan

d50(mm) 1 Kuye River

0.1

0.01 0.0001

0.001

0.01 C

0.1

1

T

100

100

Percent finer by weight (%)

Relationship between d50 and CT obtained at the Kuye, Tuwei, and Jialu River hydrological

Percent finer by weight (%)

Fig. 5.12. stations.

80 60 K-1 K-4

40 20 0 -5 10

0.0001 0.001

0.01 0.1 d (mm)

(a) Kuye River

Fig. 5.13.

K-3 K-2

1

10

80 60 D-4 40

D-1 D-3

20

D-2

0 -5 10 0.0001 0.001

0.01 d (mm)

0.1

(b) Dali River

Distribution of particle size in riverbed and riverbank sediments.

1

10

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115

In Fig. 5.13(a), K-1, 2, 3, and 4 refer to sediments taken from the Kuye River (Fig. 5.9 for the locations of sampling stations); in Fig. 5.13(b), D-1, 2, 3, and 4 refer to sediments taken from the Dali River. K-1, K-2, K-3 and K-4 are silt, coarse sand, fine sand and very fine sand, respectively. D-1, 2, and 3 are silt, and D-4 is very fine sand. Because K-1 and D-4 refer to riverbank sediments, the riverbed sediments of the Kuye and Dali Rivers are sand and silt, respectively.

5.3.3. Relationship between discharge and sediment transport rate Figure 5.14 shows the relationship between the sediment discharge, Qs , and the total discharge, Q, of sediments and water observed in the Kuye and Jialu Rivers. When Qw is the discharge of the water phase in flood flow, the total flood flow discharge is defined as Q = Qs + Q w .

(3)

The following relationship in the region of low total discharge comes from Fig. 5.14. Qs = αQn .

(4)

In the region of high total discharge, Qs = kQ. 3

Qs (m /s) 104

(5) Q (m3/s)

Kuye River

s

104

1,000

Jialu River

1,000

100

100

10

10

1

1

0.1

0.1

0.01

0.01

0.001

Wangdaohengta, 1979 Wangdaohengta, 1981 Shenmu, 1979 Shenmu, 1981 Wenjiachuan, 1979

0.0001 10-5 10-6 10-7 0.01 0.1

Wenjiachuan, 1981 1

10

100 1,000 104 105 3

Q (m /s)

Fig. 5.14.

0.001 0.0001 10-5 Shengjiawang, 1979 Shengjiawang, 1980

10-6 10-7 0.01 0.1

1

100 1,000 104 105

10 3

Q (m /sec)

Discharge–sediment transport rate relationships for the Kuye and Jialu Rivers.

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These results agree with those of Cao et al.4 By arranging Eqs. (4) and (5), CT = Qs /Q = αQn−1

(6)

CT = Qs /Q = k

(7)

at low total discharges and

at high total discharges. C

T

Kuye River

1

CT = 0.2

0.1 0.01

Wangdaohengta, 1979 Wangdaohengta, 1981 Shenmu, 1979 Shenmu, 1981 Weijiachuan, 1979 Weijiachuan, 1981

0.001 CT=4 10-4Q

0.0001 0.1

Fig. 5.15.

1

10 100 Q (m3/s)

1,000

104

Relationship between discharge and sediment concentration in the Kuye River.

C

T

Jialu River

1

CT=0.2

0.1 0.01

Shengjiawang, 1979 Shengjiawang, 1980

0.001 0.0001 0.1

Fig. 5.16.

CT = 1 1

10-3Q2.5

10 100 Q (m3/s)

1,000

104

Relationship between discharge and sediment concentration in the Jialu River.

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117

CT , C T 1 0.1 0.01

10-6Q1.3)

Yellow River, Huayuankou (CT = 2

10-5Q )

0.6

Kuye River Tuwei River, Gaojiachuang Jialu River, Shengjiawang Dali River, Qingyangcha Dali River, Lijiahe Dali River, Suide

0.001 0.0001

Yellow River, Huayuankou (CT = 2

0.1

1

10

100

1,000

10 4

3

Q , Q (m /s) Fig. 5.17. Comparison of the sediment concentration–discharge relationships for the tributaries and the main river.

These relationships also apply in tributaries (Figs. 5.15 and 5.16). The data reveal a fair degree of scatter, indicating that the rate of sediment transport is governed by various hydraulic parameters as well as total discharge. The empirical formulae to predict the sediment transport rate are drawn in Fig. 5.17.15 The bars over the CT and Q for the Dali River indicate one day average. These formulae reveal the same upper limit on sediment concentration in flow; CT = 0.2. Sediment concentration, e.g., in debris flow, has an upper limit.5 Experimental investigations on sediment concentration in a laboratory flume reveal that the limit is approximately 0.5 for debris flow. This indicates that debris flow cannot exceed the maximum sediment concentration close to 0.6. It is likely that the upper limit of CT is equal to 0.2 for the tributaries. The formulae based on measurements of the Yellow River’s main stream are also drawn in Fig. 5.17.2 This indicates that the characteristics of sediment transport in the Kuye River differ from those of the other tributaries as well as those of the main stream. Ordinary sediment-laden flow is characterized by the rather approximate relationship CT = αQ,

(8)

where most sediment in a flow is transported as wash load. This formula is applicable to the Kuye River when Q ≤ 500.

5.3.4. Flow resistance Figure 5.18 illustrates the relationship between the friction coefficient f = 8(u∗ /v)2 and the sediment concentration CT in flow, with measurements from

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Laboratory experiments

1

Clear water Silt (d = 0.016 mm) Very fine sand (d = 0.067 mm) Fine sand (d = 0.17 mm)

f 0.1

Field measurements

0.01 0.001 0

Fig. 5.18.

Kuye River Tuwei River Jialu River

0.1

0.2

0.3 CT

0.4

0.5

0.6

Relationship between the friction coefficient and sediment concentration.

laboratory experiments.6,7 Here, u∗ is the friction velocity and v is the average velocity. The friction coefficients in field data were lower than those in laboratory data for CT < 0.3; however, for CT > 0.3, the friction coefficients were similar to each other. Laboratory experiments using silt indicate very large friction coefficient values at CT = 0.369. This may be caused by Bingham fluid-like behavior. However, most field and laboratory data indicate that the flow characteristics differ from those of Bingham fluid and resemble Newtonian or dilatant fluid.

5.4. Formula for Flow Resistance and Sediment Transport As the sediment concentration increases in flows, the fluid type and flow characteristics change. At higher sediment concentrations, the additional stress is caused by intergranular interactions. The stress is referred to as “dispersive” stress in the pioneering work of Bagnold8 and as the “intergranular” stress in the work.5 Using the concept of intergranular stress, Hashimoto and Hirano9,10 and Hashimoto11 derived a non-dimensional parameter to describe the flow behavior of sediment–water mixtures. Based on this non-dimensional parameter, they introduced a two-layer model of mixture flow in which the lower layer is referred to as the “granular sublayer” and the upper layer as the “inertial sublayer”. This model, a so-called non-Newtonian model, is used to obtain formulae for the flow resistance and sediment transport rate of a hyper-concentrated mixture flow. Selecting an elevation z from the riverbed as the length scale in the nondimensional expression, the non-dimensional elevation is written as z Nz = d



ρt , σF(CT )

(9)

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119

where d is the diameter of a sediment particle, F(CT ) is a function of sediment concentration, σ is the density of sediment particles, ρ is the density of water and ρt = σCT + ρ(1 − CT ). Using this non-dimensional elevation and mixing-length theory, Hashimoto and Hirano9,10 obtained the velocity profile in the hyper-concentrated mixture flow as u ξ (10) =√ Nz for Nz ≤ 15 u∗ Kzx and u uδ 1 1 − ln 15 = ln(Nz ) + u∗ κ u∗ κ

for Nz ≥ 15,

(11)

where u∗ is the friction velocity, ξ is the coefficient to consider the effect of concentration distribution, Kzx is the coefficient related to intergranular stress, κ is the Karmen constant and uδ is velocity at the top of the lower layer termed “granular sublayer”. Equations (10) and (11) can be integrated to yield the average velocity, v and the friction coefficient, f as  v 1 ξ 8 = √ = Nh for Nh ≤ 15 (12) u∗ f 2 Kzx and v = u∗

 15 ξ 15 8 = + √ f 2 Kzx Nh



uδ 1 − u∗ κ

 1−

15 Nh

 −

  1 15 ln κ Nh

for Nh ≥ 15, where the non-dimensional flow depth Nh is defined as  ρt h Nh = , d σF(CT )

(13)

(14)

where h is the flow depth. Based on the two-layer model, Hashimoto et al.12,13 derived a unified sediment transport rate formula as follows:     qs τ∗c 1 u¯ δ 3/2 h w0  1− , (15) G If , , = τ∗  u∗ τ∗ d u∗ α − If cos θ sgd 3 where qs is the sediment transport rate per unit width, s = (σ − ρ)/ρ, τ∗ is the non-dimensional shear stress, τ∗c is the critical non-dimensional shear stress, θ is the bed slope angle, If is the friction slope, w0 is the settling velocity of a

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sediment particle in water, α = 0.875, u¯ δ /u∗ = 4.7, and G is a function of If , h/d, and w0 /u∗ .  Non-dimensional sediment transport rate qs / sgd 3 in laboratory experiments with fine sand and in the Kuye River is shown in Fig. 5.19. In this figure, each line was calculated in terms of Eq. (15). The non-dimensional sediment transport rate differs considerably between experimental and field observation data. Laboratory data are in the order of 102 –103 , whereas field observation data in the Kuye River are in the order of 104 –107 . The hydraulic conditions in the laboratory experiments ranged from 110 < h/d < 150, w0 /u∗ = 0.2, and 3 < τ∗ < 5, whereas those in the Kuye River ranged from 3,000 < h/d < 80,000, 0.01 < w0 /u∗ < 0.1, and 4 < τ∗ < 100.

5.5. Comparison among Theoretically Calculated, Experimental and Observed Results Figure 5.19 presents the relationship between the friction coefficient f and the nondimensional flow depth Nh , in which the solid curve indicates theoretical results in Eqs. (12) and (13). Observed results in the Kuye River and experimental ones with fine and very fine sand agree well with the theoretical ones, but observed results in the Tuwei and Jialu Rivers and experimental ones with mixtures of silt and water do not. In experiments, Nh was in the order of 102 –103 , whereas in the rivers, 104 –105 . The difference in f between experimental results in the laboratory flume and observed data in actual rivers is caused by the difference in Nh . The non-Newtonian fluid model (Hashimoto and Hirano9,10 ) is thus applicable to the Kuye River and flow for sand–water mixtures, but neither for the Tuwei and Jialu Rivers nor silt– water mixtures. Measurements of non-dimensional sediment transport rate made in a laboratory flume and in the Kuye River are compared with theoretical curves obtained using Eq. (15) (Fig. 5.20). The non-Newtonian fluid model is able to explain sediment transport both in the Kuye River and in laboratory experiments where the mixtures consist of sand and water, although there was a considerable difference between the hydraulic conditions in the Kuye River and in the laboratory experiments. The non-Newtonian fluid model explains satisfactorily the flow resistance and sediment transport for the sand–water mixture and in the Kuye River. The model is inappropriate, however, for the flow of silt–water mixtures and for the flows in the Tuwei and Jialu Rivers. The Newtonian fluid model is appropriate for cases like these, but is not applicable to estimate the rate of sediment transport. In these cases, the curves in Fig. 5.17 are available to calculate the sediment transport rate.

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Experiments

1

Silt (d = 0.016 mm) Very fine sand (d = 0.067 mm) Fine sand (d = 0.07 mm)

0.1

Field measurements

f

Kuye River Tuwei River Jialu River

0.01

Theory

0.001 10 1

Eqs. (12) and (13)

10 2

10 3

10 4

10 5

10 6

Nh Fig. 5.19.

Sediment transport rates measured in the Kuye River and in laboratory using fine sand.

10 7 10 6 qs sgd 3 10 5 10 4 10 3 10

2

10 1 1 0.1 0.1

1

10

1

10

2

3

10 τ

*

Fig. 5.20. Dependence of the friction coefficient f on the non-dimensional flow depth Nh based on the non-Newtonian fluid model.

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5.6. Analysis of Flood and Sediment Runoff 5.6.1. Rainfall–runoff analysis Flood runoff is predictable in terms of a storage function model; ds = f0 r − q, dt

(16)

s = k1 qp1 + k2

dqp2 , dt

(17)

where t is the time (h), s is the storage depth (mm), f0 is the runoff coefficient, r is the average rainfall intensity over the study basin area (mm/h), q is the runoff depth (mm/h), and k1 , k2 , p1 , and p2 are the coefficients related to the runoff model. The values of p1 and p2 are 0.6 and 0.465, respectively. The average rainfall intensity r is obtained from rainfall measurements in terms of the Thiessen polygon method. In a predicted result in Fig. 5.21, k1 and k2 were determined intentionally for better agreement.

5.6.2. Riverbed variation analysis The basic equations for riverbed variation analysis are: Momentum equation:

 ∂Q ∂vQ ∂(h + z) f + = gBh − − (B + 2h) v2 , ∂t ∂x ∂x 8 3

Q (m /s)

Kuye River (Wangdaohengta)

6,000

(18)

r (mm/h) 0

f0=0.23 k =1,k =5 1

4,000

2,000

2

rainfall

10

20 prediction

0 1979 8/7

measurement

1979 8/8

30 1979 8/9

Fig. 5.21. Comparison between calculated and measured hyper-concentrated flood at Wangdaohengta.

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Continuity equation for water and sediments: B

∂(h + z) ∂Q + = qin , ∂t ∂x

(19)

Continuity equation for sediment: B

∂(Ch + C∗ z) ∂Qs + = 0, ∂t ∂x

(20)

where Q is the total discharge, f is the friction coefficient, h is the flow depth, z is the riverbed thickness, B is the river width, v is the average velocity in the x-direction, C is the sediment concentration in flow, C∗ is the sediment concentration in the riverbed, Qs is the rate of sediment transport, and qin is the lateral inflow rate per unit length. The inflow rate from the riverside is estimated using the rational method, qin =

1

A , f0 r L 3.6

(21)

wheref0 is the runoff coefficient, r is the rainfall intensity (mm/h), and A (km2 ) is the basin area of the riverside in length L(km). The friction coefficient f is calculated with Eqs. (12) and (13), and the sediment transport rate is determined with Eq. (15). The term ∂(Ch)/∂t in Eq. (20) is negligibly small. In the momentum and continuity equations, h, z, and Q are unknowns so they have to be solved numerically. A river reach for numerical calculation is taken from the Shenmu to the Wenjiachuan hydrological stations near the junction of the Kuye River to the Yellow River and is 80 km in distance. The calculation period was from 7 August to 13 August, 1979. The boundary condition was provided by Q (m3/s) 8,000 6,000 4,000

Kuye River (Wenjiachuan) rainfall

0 1979 8/7 8/8

10

measurement calculation

2,000

8/9

r (mm/h) 0

8/10 8/11 8/12 8/13

20 30 40 1979 8/14

Fig. 5.22. Comparison between calculated and observed flow rates on hyper-concentrated flood at Wenjiachuan.

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Q (m3/s) s

Kuye River (Wenjiachuan)

4000 Measurement Calculation

3000 2000 1000 0 1979 8/7 8/8

8/9

1979 8/10 8/11 8/12 8/13 8/14

Fig. 5.23. Comparison between calculated and observed rates of sediment transport on hyper-concentrated flood at Wenjiachuan.

field data measured at Shenmu. The distance increment and the time step for the calculation were assumed as x = 1 km and t = 1 s, respectively. The measured and calculated total and sediment discharges at Wenjiachuan are in good agreement in Figs. 5.22 and 5.23. This analysis method on riverbed variation is therefore applicable to estimate the total discharge and sediment discharge at any location along the river.

References 1. Z. Wan and Z. Wang, Hyperconcentrated Flow, IAHR/AIRH Monograph (1994). 2. Yellow River Conservancy Commission (YRCC), Flood control and development of the Yellow River basin, Kokin Shoin (1989), p. 254 (trans. J. T. Feng and S. F. Kuang). 3. C. Li, Field investigation of soil erosion and sediment yield in the Loess Plateau of China, Sino–Japan Joint Academic Trip Report (2002). 4. R. Cao, E. Fan and Q. Yi, Sediment transport models for small gullies in loess hill and gully regions, Proc. Int. Symp. Hydraulics and Hydrology of Arid Lands (1990), pp. 694–699. 5. T. Tsubaki, H. Hashimoto and T. Suetsugi, Interparticle stresses and characteristics of debris flow, J. Hydroscience Hydraul. Eng. 1 (1983) 67–82. 6. H. Hashimoto, H. Takaoka and K. Park, Sediment discharge formula for steep open channel, Proc. 9th Int. Symp. River Sedimentation, Vol. 3 (2004), pp. 1453–1461. 7. H. Hashimoto, H. Takaoka and S. Ikematsu, Hyper-concentrated flows in tributaries of the middle Yellow River, 1st Int. Conf. Monitoring, Simulation, Prevention and Remediation of Dense and Debris Flows (WIT Press, 2006), pp. 353–362. 8. R. A. Bagnold, Experiments on a gravity-free dispersion of large solid spheres in a Newtonian fluid under shear, Proc. Royal Society of London, Series A, Vol. 25, (1954), pp. 49–63.

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125

9. H. Hashimoto and M. Hirano, Resistance rule of mud flows on movable and fixed beds, Ann. J. Hydraul. Eng. 39 (1995) 495–500. (in Japanese) 10. H. Hashimoto and M. Hirano, A flow model of hyperconcentrated sand-water mixtures, Proc. 1st Int. Conf., Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment (7–9 August 1997), pp. 464–473. 11. H. Hashimoto, Flow characteristics of sediment-water mixtures in an open channel, 20th Multiphase Flow Symp. (2001), pp. 61–68. (in Japanese) 12. H. Hashimoto, K. Park, S. Ikematsu and N. Tasaki, A sediment discharge formula for various types of sediment transport in a steep open channel, Ann. J. Hydraul. Eng. 47 (2003) 571–576. (in Japanese) 13. H. Hashimoto, H. Takaoka, S. Ikematsu, B. Jun and T. Ueno, Field survey of sediments in the middle reach of the Yellow River and experiments of hyperconcentrated flow in an open channel, Ann. J. Hydraul. Eng. 48 (2004) 943–948. (in Japanese) 14. Yellow River Conservancy Commission (YRCC), Data of water and sediment of the Yellow River (1980, 1982). (in Chinese) 15. H. Hashimoto, H. Takaoka and S. Ikematsu, Sediment transport and flow resistance in tributaries of the middle Yellow River, Ann. J. Hydraul. Eng. 51 (2007) 907–912. (in Japanese).

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Chapter 6

Modeling and Simulation on Water in the Yellow River

Dawen Yang Tsinghua University, Beijing, China

6.1. Hydrological Model and Simulation 6.1.1. Introduction Many studies have focused on finding the reason for the drying up of the Yellow River. As a result of these studies, it has been identified that climate change and an increase in artificial water-use are the two main factors leading to the drying up of the river.1,2 In a previous study, the reason for decreasing river discharges in this basin was analyzed qualitatively using historical data.1 However, the details are not clear as to the effects of climate change and human activities over the long term. One reason for this is the lack of long-term data on the water intake by the different water sectors including irrigation intake, industrial and domestic uses and water transfer across basins. In addition, irrigation water is not completely consumed in the field through evapotranspiration (part of it returns back to the river). On the other hand, historical climate data are generally available and provide a reference for studying the impact of climate change on water resources. Trend analysis is commonly employed for this purpose.2–4 From these records, it is found that the annual precipitation decreased by 45.3 mm, and the annual mean air temperature increased by 1.28◦ C in the Yellow River basin in the last half century. Because of the nonlinear behavior of hydrological processes, changes in climate cannot easily be converted into amounts of water resource changes. The natural water resources need to be assessed by hydrological models using historical climate data as the inputs.

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Hydrological models have been used widely for water resource assessment, especially for studying the impact of climate change.5,6 Water balance models are commonly used for such purposes. Arnell7 used a daily water balance model for investigating the impact of climate change on global water resources. Nijssen et al.,8 used a variable infiltration capacity (VIC) conceptual model9 for global runoff and discharge simulations. Middelkoop et al.,10 compared a water balance model and a physically-based model for water resources assessment in the Rhine basin. It was found that both types of models could simulate the general trends of monthly river flows. However, the physically-based model worked better than the water balance model in many cases. The water balance model could not properly simulate snow storage and snowmelt using the monthly mean temperature and precipitation. The water balance model also could not estimate the evapotranspiration correctly without considering the soil water dynamics. Seasonal changes in sub-surface storages could not be simulated properly by the water balance model. In fact, most of the water balance models do not consider changes in the storage in the sub-surface, and can only be used for estimating the long-term mean of the water resources. In this section, 50 years of daily average meteorological data are used. Together with the available geographic information related to the land cover and vegetation, an assessment of the natural river discharge is carried out by applying a distributed physically-based model for simulating the hydrological cycle over the last 50 years in the Yellow River basin. Based on the long-term hydrological simulation, the spatial and temporal characteristics and variability of the natural runoff are analyzed. Incorporating these results with the observed river discharge data, the artificial water consumption is estimated. The vulnerability of water resources due to climate change and artifical uses are discussed.

6.1.2. Data Figure 6.1 presents the current situation of water resources development in the Yellow River basin. The main irrigation projects provide 7.13 × 106 ha of irrigation areas, which consume a large amount of runoff. The large dams on the main river have a total water storage of 60.7 × 109 m3 , which is the same magnitude as the annual runoff of theYellow River. In order to evaluate effects of artificial water-uses and climate changes, it is desired to assess the naturally-available water resources. A distributed model is used here for estimating the natural runoff in this basin over the last half century, in which only natural hydrological processes are included (there is no consideration of irrigation or reservoir control). The model uses a grid system with a 10-km spatial resolution, and runs in hourly time steps. The

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Fig. 6.1. The Yellow River basin (the hydrological simulation area is the upstream of the Huayuankou discharge gauge).

methodology used for constructing this model includes a sub-grid parameterization scheme, a basin subdivision scheme, a physically-based hillslope hydrological simulation and a kinematic wave flow routing method (Sec. 4). The land surface conditions considered in the hydrological simulation include the topography, the land use, the vegetation and the soil. The topography and soil are treated as being constant over time. The model uses the land-cover of the 1990 as the base map and considers annual and seasonal changes in vegetation using remotely-sensed NDVI data. The atmospherical forcing used in the hydrological simulation is taken from a daily historical climate data set. Since there are significantly less drainage areas in the lower reach (Fig. 6.1), most of the runoff is generated from the upstream of the Huayuankou gauge, and therefore, the hydrological simulation covers only this area. The geographical information concerning the Yellow River basin is obtained from a number of global data sets. The digital elevation data of 1-km resolution is obtained from the USGS HYDRO1k data set which is available at: http://edcdaac. usgs.gov/gtopo30/hydro/. Since the model uses a 10-km grid system, the basin base map is regenerated at the same spatial resolution, in which the flow direction of each grid is conceptualized as the main flow direction, and the river basin boundary and the river network are delineated based on this flow direction. The topographical parameters within a grid are calculated using the 1-km DEM. Land cover is obtained from the USGS Global Land Cover Characteristics Data Base Version 2.0 which is available at http://edcdaac.usgs.gov/glcc/ globe_ int.html.11,12 This data has a spatial resolution of 1 km. Based on the USGS

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classification, this land cover has been regrouped into 9 categories, including water bodies, urban areas, bare land, forest, cropland, grassland, wetland, mixtures of bare land and grassland, and ice. The area fraction of each land cover type within a 10 km grid is calculated from the 1 km land cover map. For each vegetation type, a monthly leaf-area-index (LAI) is calculated from the monthly NDVI. A global data set of monthly NDVI with 8 km resolution is obtained from the DAAC of GSFC/NASA at http://daac.gsfc.nasa.gov/DAAC_DOCS/. This data set is available from 1982 onwards. The soil type is obtained from the Digital Soil Map of the World and Derived Soil Properties.13 It is developed at a 5-minute resolution using the FAO-UNESCO soil classification. The effective soil depth is indicated by 6 classes: < 10 cm, 10–50 cm, 50–100 cm, 100–150 cm, 150–300 cm and > 300 cm in this data set. A mean value is specified for each class, and the maximum depth is set as 4 m. According to this information, the depth of the unconfined aquifer is somewhat arbitrarily chosen to be 5–10 times the topsoil depth. The soil properties used for the hydrological simulation including the porosity, the saturated hydraulic conductivity, and the other soil water parameters corresponding to each soil type in this map are obtained from the Global Soil Data Task.14 The waterretention relationship and unsaturated hydraulic conductivity are represented by Van Genuchten’s formula,15 and the parameters are available in this data set. The soil moisture contents at field capacity and wilting point are calculated at matric pressures of −33 kPa and −1500 kPa, respectively. The climate data from 1951 to 2000 were obtained from the China Administration of Meteorology. This data set is available at a daily temporal resolution at 108 gauges inside and close to the Yellow River basin (Fig. 6.1). The meteorological parameters include precipitation, maximum, minimum and mean air temperature, wind speed, relative humidity, and sunshine hours. The required hydrological gridded input is interpolated from the gauge data. Precipitation is interpolated using an angular-distance weighting method.16 In the same way, the wind speed, relative humidity and sunshine hours are also interpolated into each 10 km grid. The temperatures (maximum, minimum and mean) are interpolated using an elevation-corrected angular-direction weighting method. Using the wind speed, relative humidity, sunshine duration and temperature, the daily potential evaporation is calculated.17,18 The discharge data collected before 1990 is from the “HydrologicalYear Book” published by the Hydrological Bureau of the Ministry of Water Resources of China.19 The monthly discharge data after 1990 was documented in an annual report by the Hydrological Bureau, and is available at the web site of the Ministry of Water Resources of China.20 Seven gauges on the main river (Fig. 6.1) are selected for analyzing the change in water resources with respect to river discharges.

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6.1.3. Description of the hydrological model In order to construct the distributed hydrological model, a GIS of the target basin is first established, in which a digital elevation model (DEM) is used for defining the target area and modeling the topography. Based on this GIS, the model structure is defined and the model parameters are calculated. The model is then coded, incorporating all of the hydrological processes. As shown in Fig. 6.2, in the present model structure, the basin is divided into a discrete grid system 10 km in size, with the grid represented by a number of geometrically-symmetrical hillslopes. The basin is divided into a number of sub-basins and the river network is identified up to the main stream of the minimum sub-basin. The hydrological components, including runoff from the hillslopes and the flow routing in the river network are modeled using physically-based approaches. Taking the meteorological inputs, the model simulates river discharge at different locations in the river network, and

Fig. 6.2. The structure of the hydrological model.

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temporal changes and spatial distributions of soil moisture and evapotranspiration, which provide an inside investigation into water resources in the basin. Since the model uses a 10 km grid, the heterogeneity inside a grid affects the hydrological processes, and therefore, a sub-grid parametrization is necessary. The sub-grid parametrization used here includes representations of the sub-grid variability in land-cover, the sub-grid variability in soil properties, and the sub-grid variability in topography. The distinguishing characteristic of the topographical parametrization is the use of basin geomorphologic properties. In the geomorphology-based hydrological model (GBHM) developed by Yang et al.,21−23 the geomorphologic property of stream-hillslope formation was used for representing the catchment topography. In a similar way, it is assumed that a large grid is comprised of a set of hillslopes located along the streams. From a macro-scale viewpoint, the hillslopes located in a grid are viewed as being geometrically similar. A hillslope with a unit width is called a hillslope element, represented by a rectangular inclined plane (Fig. 6.2). The length of a hillslope element is calculated from the 1 km DEM using the following equation,
l = a(i, j)/2 L, (1)  where a(i, j) is the area of the grid at location (i, j) and L is the total length of streams in the grid, which is calculated using a 1 km DEM. The slope angle is taken as the mean slope of all of the sub-grids in the 1 km DEM. The impermeable bedrock slope is assumed to be parallel to the surface (Fig. 6.2). Considering the land-cover heterogeneity, hillslopes located in a 10 km grid are grouped. The area fraction of each group is calculated from the 1 km land-cover map. The soil within a grid is represented as a single dominant soil type. However, the anisotropy of the soil is modified according to the land-cover. The anisotropy ratio is defined as,24 ra = Ksp /Ksn ,

(2)

where ra is the anisotropy ratio and Ksp and Ksn are the saturated hydraulic conductivities in the directions parallel (p) and normal (n) to the slope, respectively. The soil, especially in forests, is anisotropic with a higher conductivity parallel to the hillslope in the root zone. The anisotropy ratio is only specified for the root zone of forest and grassland in this model which is 3 for forest and 1.5 for grassland, respectively. A vertical distribution of the non-uniform soil hydraulic conductivity of the topsoil is represented by an exponentially-decreasing function,25 namely, Ks (z) = K0 exp(−fz),

(3)

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where Ks (z) is the saturated hydraulic conductivity, z is the (positive) distance taken in the downward direction normal to the surface, K0 is the saturated hydraulic conductivity of the surface soil, and f is a constant coefficient. The value of K0 is obtained from the soil data, and the hydraulic conductivity of groundwater for an unconfined aquifer is a calibrated parameter. The value of f is determined by the saturated hydraulic conductivity of the surface soil and the hydraulic conductivity of the groundwater at known soil depths. The hill-slope is the fundamental computational unit for hydrological simulation. The aggregation of the hydrological fluxes and the state variables in a grid are considered for the model output or future water resources management. The runoff generated from one grid is the sum of the hillslope responses including both the surface and subsurface runoff. The vertical flux, the actual evapotranspiration, is the total evapotranspiration simulated from all hillslopes. The soil moisture content state variable is taken as the area-averaged soil moisture of all hillslopes. A physically-based model is used for simulating the hillslope hydrology. The hydrological processes included in this model are snowmelt, canopy interception, evapotranspiration, infiltration, surface flow, subsurface flow and the exchange between the groundwater and the river.23,26 The upper reach of the Yellow River suffers snow during the winter, and the resulting snowmelt runoff is a major source of river flow. A temperature-based model is incorporated to simulate snowmelt, which is given by M = Mf (T − Tb ),

(4)

h−1 ),

where M is the snowmelt water depth (mm Mf is the snowmelt factor (mm −1 −1 ◦ degree h ), T is the air temperature ( C) and Tb (= 1.5◦ C) is the base temperature at which snowmelt starts. The snowmelt factor is a calibrated parameter in the present model. The canopy interception capacity depends on the vegetation or crop species and differs depending on time and vegetation coverage. The interception capacity SC0 is given as a function of the leaf-area index,27 SC0 = 0.2 LAI,

(5)

where SC0 is expressed in mm and LAI is the leaf area index. The rainfall fills the canopy storage first. The precipitation reaching the ground surface is the excess over the canopy maximum storage. The actual interception is determined according to the rainfall intensity and the deficit of the canopy storage. The actual evapotranspiration is calculated from the potential evaporation by considering seasonal variation of LAI, root distribution and soil moisture availability. This is computed individually from the canopy water storage, root

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zone and soil surface. The actual evaporation rate from the canopy storage Ecanopy is given by Ecanopy = Kc Ep ,

(6)

where Ep is the potential evaporation rate and Kc is the crop coefficient. The vegetation transpiration rate is estimated as the rate of water taken up from the root zone, given by: Etr (zj ) = Kc Ep f1 (zj )f2 (θj )

LAI , LAI 0

(7)

where Etr (zj ) is the transpiration rate from layer j of the root zone; f1 (zj ) is the root distribution function that is given by a triangular distribution with its maximum near the surface; f2 (θj ) is given as a linear function of soil moisture, θj ; and LAI0 is the maximum leaf area index of the vegetation in a year. For the bare soil, the evaporation rate is given by, Es = Kc Ep f2 (θ),

(8)

where Es is the evaporation rate from the soil surface. In ponding conditions, the value of f2 (θ) is unity. The actual transpiration from the root zone and evaporation from the soil surface are treated as sink terms in Richards’equation that is employed to model soil water movement in the unsaturated zone. Infiltration and water flow in the subsurface in the vertical direction and along the hillslope are described in a quasi-two-dimensional subsurface model. The vertical water flow in the topsoil is represented by Richards’ equation and solved by an implicit numerical solution scheme. In this scheme, the topsoil is subdivided into a number of layers. Similar to the common subdivision used in many land surface schemes, the topsoil is divided into a near surface layer of 5 cm, a root zone and a deep zone. The root zone and deep zone are again derived into sub-layers in the present model. The first layer is expected to be saturated during the rainfall period. Therefore, the upper boundary condition is given as a constant soil water content for the rainfall cases. During the non-rainfall period, evaporation from the soil surface exists, and the upper boundary condition is given as a constant flux. The lower boundary condition is given as saturated because the groundwater reaches very high levels during the flood season. The soil water distribution along the hillslope is regarded as uniform. When the soil water content is more than the field capacity, water moves to the stream along the hillslope by gravity. This leads to the sub-surface flow given as qsub = K(θ) sin β,

(9)

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where qsub is the flow rate, K(θ) is the hydraulic conductivity and θ is the soil water content. This should be larger than the field capacity in this case. The slope is represented by β. The surface runoff is from the infiltration excess and saturation excess obtained by solving Richards’ equation. The surface runoff flows through the hillslope into the stream as a kinematic wave. The groundwater aquifer is treated as an individual storage corresponding to each grid. The exchange between the groundwater and the river water is considered as steady flow and is calculated by Darcy’s law.23 For a large river basin, it needs to be subdivided into sub-basins and to simulate the variability of water resources in different sub-basins. For subdividing theYellow River basin, the Pfafstetter basin numbering scheme22,28 was applied. Using the Pfafstetter scheme, the river network is separated into the main river and tributaries. The main river drains a greater area than the tributaries at a junction. Following the main river from the outlet to the upper stream, the four largest tributaries are selected and numbered as 2, 4, 6, and 8; and the inter-basins are numbered 1, 3, 5, 7, and 9. Figure 6.3(a) shows the subdivision of the Yellow River basin at the first level. A sub-basin of Level 1 can be subdivided by repeating the same procedure. In this example, the sub-basin 2 in Fig. 6.3(a) is subdivided into its four largest tributaries numbered 22, 24, 26, and 28, and five inter-basins numbered 21, 23, 25, 27 and 29 at Level 2 (Fig. 6.3(b)). A sub-basin number of Level 2 consists of a number of its mother basins of Level 1 (the first digit) and its Pfafstetter number of Level 2 (the second digit). In the same way, the subdivision of sub-basin 24 of Level 2 is illustrated in Fig. 6.3(c). The subdivided nine sub-basins are numbered 242, 244, 246, and 248 for the tributaries and 241, 243, 245, 247, and 249 for the inter-basins. The three digits of the sub-basin number at Level 3 are composed of a number of their mother catchments at the upper level (i.e., Level 2), which are

Fig. 6.3.

Subdivision of a large basin using the Pfafstetter scheme.

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represented by the first two digits, and its Pfafstetter number at Level 3 (the present level), which is represented by the last digit. In the 10 km grid system used in the hydrological model, the minimum drainage area for identifying a sub-basin is chosen to be 5,000 km2 . In total, 137 sub-basins have been identified in the simulated area, the upstream of the Huayuankou gauge (Fig. 6.1). The flow accumulation sequences of the nine sub-basins of the same level are fixed. Sub-basins 9 and 8 join and flow into sub-basin 7; sub-basins 7 and 6 join at their common outlet and flow into sub-basin 5; sub-basins 5 and 4 join at their common outlet, then flow into sub-basin 3; sub-basins 3 and 2 join at their common outlet and flow into sub-basin 1. The code numbers of the derived sub-basins uniquely define the relationships among these sub-basins and flow sequences in their river networks. Within a derived minimum sub-basin, the river networks are simplified into the main stream on which the simulation of flow routing is carried out using the kinematic wave approach. The lateral inflow is the runoff generated from grids in the same flow interval. The flow distance gives the location of a grid from the outlet. Once the flow routes in the river network, it remains in dynamical connection with groundwater. This is essential for accounting of the flood plain-channel interaction, and has a significant effect on the water cycle. Extractions, diversions, and reservoir operations are not accounted for in the routing model. Consequently, the simulated flows are natural flows and cannot be compared directly to measured river discharges in heavily regulated rivers for model evaluation. However, the simulated river discharges offer a fundamental assessment of the available freshwater resources.

6.1.4. Model calibration and validation A 5-year test run from 1981 to 1985 is carried out for calibrating the model parameters. One of the calibrated parameters in this model is the snowmelt factor in the temperature-based snowmelt equation. Another calibrated parameter, the hydraulic conductivity of the groundwater, is calibrated by checking the base flow in different sub-basins. Model validation is carried out from 1986 to 1990 in the upstream of the Tangnaihai discharge station (Fig. 6.1), where the human activity is insignificant, and snowmelt runoff and groundwater flow are the main sources of river discharge. Figure 6.4 shows a comparison between the simulated and observed daily discharges at the Tangnaihai gauge for both the calibration and validation periods. Based on the daily discharges, the ratio of the absolute error to the mean (R)

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Fig. 6.4. Comparison of simulated and observed daily river discharge at the Tannaihai station for the calibration period (1 January 1981–31 December 1985) and the validation period (1 January 1986– 31 December 1990).

suggested by the World Meteorological Organization29 and the Nash coefficient (R2)30 are calculated for evaluating the model performance (Yang et al., 2002). The values of R and R2 are 19% and 0.88 for the calibration period and 17% and 0.89 for the validation period, respectively. A good agreement between the simulated daily hydrograph with the observed and a consistency of the simulations in both the calibration and validation periods are achieved. The water balance error is –2% in the calibration period and 0.2% in the validation period, which is in an acceptable range for water resources assessment. Figure 6.5 shows the average monthly hydrographs by simulation and observation from 1981 to 1990. It is clear that the major differences between the simulated and observed hydrographs are from January to early July. Overestimations are found from January to April, but underestimations are found in April, May and June. The mean elevation in the upstream of the Tangnaihai gauge is about 4,800 m. The soil is frozen in winter and thaws during the spring and early summer. The active depth of the topsoil is about 2 m. Because the present model has no consideration of the freezing-thawing process, it overestimates the river discharge during the freezing process in the winter and underestimates it during the thawing process in the spring and early summer. In the middle and lower reaches associated with heavy human activities, any observations on the groundwater level cannot be used as the initial condition for simulating the natural water resources. For specifying an appropriate initial

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Fig. 6.5. Comparison of monthly mean hydrographs by simulation and observation from 1981 to 1990.

groundwater level, the present study carries out a 50-year test run from 1951 to 2000 for achieving a stable groundwater level. Then, the groundwater level and soil moisture contents at the end of the test run are used as the initial conditions for the final simulation of the natural hydrological cycle over the past 50 years for the water resources assessment.

6.2. Analysis of Water Resources in the Last Half Century 6.2.1. Spatial and seasonal distributions of water resources for a long-term mean The general characteristics of water resources can be found from a long-term annual water balance. By checking the 50-year average water balance from 1951 to 2000 in the whole simulated area, it is found that the annual precipitation, evaporation and runoff are 439 mm, 362 mm and 77 mm, respectively. The annual runoff consists of only 17.5% of the annual precipitation. High spatial variabilities of the hydrological characteristics are seen in this basin. The annual precipitation ranges from 154 mm to 764 mm, which increases from North to South and from West to East. The annual actual evapotranspiration ranges from 137 mm to 589 mm (Fig. 6.6(a)). The Wei River basin and the downstream of the Sanmenxia Dam are the highest in evapotranspiration. The annual runoff ranges from 0 to 345 mm (Fig. 6.6(b)). The major source areas are located in the upstream of the Lanzhou gauge, the southern part of the Wei River basin and the downstream of the Sanmenxia dam. It shows that this basin is in a chaotic hydrological condition ranging from the semi-humid to semi-arid climates.

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Fig. 6.6. Spatial distributions of the 50-year means in the Yellow River basin: (a) Annual evapotranspiration, (b) Annual runoff.

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Fig. 6.7. Monthly discharges at six gauges from upstream to downstream of the Yellow River.

River discharge is the main indicator of water resources availability. Figure 6.7 shows 50-year averages of the monthly discharges from the hydrological simulations and observations at 6 gauges from the upstream to the downstream. The differences between the simulated and observed discharges are attributed mainly to the artificial control of river flows, such as reservoir regulation and artificial water uses such as irrigation. It is seen that the artificial effect on river discharge becomes more significant from the upstream toward the downstream. For revealing regional characteristics, Table 6.1 gives the average annual water balances from 1951 to 2000 for different sections from upstream to downstream. From the annual runoff simulated under natural conditions, it is seen that the major source areas are the upstream of Lanzhou gauge. This region generates about 53% of the basin total annual runoff with only 30% of the basin total area. The annual runoff generated from the main tributaries in the midstream between the Longmen and Sanmenxia gauges shares about 25% of the basin total, the same proportion of the drainage area. The downstream of the Sanmenxia dam generates about 10%

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Table 6.1.

141

Long-term averaged annual water balances from 1951 to 2000.

Section(1)

Annual precipitation (mm)

Annual actual Annual river flow (mm)(2) Annual artificial evaporation water consumption Simulated Observed (mm) (mm)(3)

Upstream of Lanzhou (I) LanzhouToudaoguai (II) ToudaoguaiLongmen (III) LongmenSanmenxia (IV) SanmenxiaHuayuankou (V) Whole study area

446.5

309.1

136.6

141.4

−4.8

263.5

251.2

12.4

−62.7

75.1

420.2

381.8

42.3

41.3

1.0

548.3

467.5

83.9

45.3

38.6

630.8

510.4

125.5

95.3

30.2

439.5

362.0

77.2

55.2

22.0

Note: (1) The Yellow River basin is divided into 6 sections by the discharge gauges which correspond to different characteristics of hydrology and water-uses (Fig. 6.1); (2) Annual river flow divided by drainage area; (3) The difference between simulated and observed river flows.

of the basin total annual runoff with only 6% of the basin total area. The semi-arid region and the Loess Plateau between the Lanzhou and Longmen gauges, generate less runoff compared to their shared drainage areas. Since there is no consideration on the artificial water-use in the hydrological simulations, the simulated river discharge is able to be viewed as a naturallyavailable runoff. Therefore, the difference between the simulated and observed river discharges can be artificial consumptions of surface water including evaporation into the atmosphere, leakage to groundwater and transfer to other basins, with respect to the reduction in river flow. From these results, it is seen that the region between the Lanzhou and Toudaoguai gauges and the region between the Longmen and Sanmenxia gauges are two major water consumption areas. The negative values of the annual artificial water consumptions are found in the upstream of the Lanzhou gauge. In fact, there is very limited irrigation in this region and the artificial water uses are negligible. This negative value is as a result of errors in the hydrological simulation. At the Tangnaihai discharge station, the river discharge is underestimated for the upstream of the Lanzhou gauge. The observed discharge is the net runoff after the artificial water uses. Comparing the net runoffs generated from the different regions, it is known that the upstream of the Lanzhou gauge contributes the major water source supplying the downstream. Considering seasonal precipitation and water uses, the year is divided into a dry season from November to June and a wet season from July to October in the basin. Table 6.2 shows seasonal characteristics of the water resources in the basin.

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Table 6.2. Long-term average water balances from 1951 to 2000 for the dry season (November–July) and the rainy season (July–October). Section ∗

Uspstream of Lanzhou (I) Lanzhou-Toudaoguai (II) Toudaoguai-Longmen (III) Longmen-Sanmenxia (IV) Sanmenxia-Huayuankou (V) Whole study area

Annual precipitation in mm (%)

Annual actual evaporation in mm

Simulated annual river discharge in mm (%)

Dry

Rain

Dry

Rain

Dry

Rain

173 (39%) 83 (32%) 135 (32%) 204 (37%) 247 (39%) 159 (36%)

274 (61%) 180 (68%) 285 (68%) 344 (63%) 384 (61%) 280 (64%)

121

189

113

139

184

198

238

230

258

253

168

194

57 (42%) 6.6 (54%) 14.8 (38%) 27 (34%) 43.3 (36%) 30 (39%)

79 (58%) 5.6 (46%) 23.6 (62%) 53.7 (66%) 77 (64%) 47 (61%)

∗ The same sections in Table 6.1 are used here.

The highly uneven distribution of the seasonal precipitation is seen from Table 6.2, in which about 64% of the annual precipitation concentrates within the wet season from July to October. This seasonally-uneven distribution of precipitation is more serious in the semi-arid region and the Loess Plateau (between the Lanzhou and Longmen gauges) where precipitation in the wet season accounts for about 70% of the annual total. By the land surface hydrological processes, this seasonally-uneven distribution of precipitation is mediated in the river discharge in the upper regions but is amplified in the lower regions. For the whole simulated area, about 60% of the annual river discharge flows within the wet season from July to October.

6.2.2. Decadal variation of water resources In order to understand the long-term variability of water resources in this basin, decadal averages of the annual water balances are examined. Here, two regions are considered: the upstream of the Lanzhou gauge which is the major source area and the region between the Lanzhou and Huayuankou gauges (Fig. 6.1), which has a considerable amount of artificial water usage. Table 6.3 summarizes the decadal averages of the water balance for the two regions. Regarding the natural runoff generated from the two regions, the decadal variability in the upstream of the Lanzhou gauge is relatively smaller than in the midstream between the Lanzhou and Huayuankou gauges. However, the natural

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Table 6.3.

143

Decadal variations of water resources.

Period

1950s

1960s

1970s

1980s

1990s

The upstream of the Lanzhou gauge Precipitation (mm/yr) Annually mean temperature (◦ C) Actual evaporation (mm/yr) Natural runoff by simulation (mm/yr)

412.5 1.91 290.2 121.0

459.3 2.19 303.0 156.3

456.0 2.57 308.1 149.4

470.0 2.62 319.1 149.3

434.5 3.12 329.0 107.2

The midstream between the Lanzhou and Huayuankou gauges Precipitation (mm/yr) 451.7 468.8 8.03 8.14 Annually mean temperature (◦ C) Actual evaporation (mm/yr) 390.3 395.3 Natural runoff by simulation (mm/yr) 53.8 74.0 Actual runoff by observation (mm/yr) 29 34.1 Artificial water consumption (mm/yr) 24.8 39.9 Ratio of available consumption (%) 46 54

428.0 8.30 382.5 48.3 10.7 37.6 78

436.8 8.39 380.0 55.9 16.1 39.8 71

397.6 9.06 372.8 29.6 −3.1 32.7 110

436.3 6.61 607.1 312.4 51.5

446.6 6.69 648.5 355.1 54.8

408.5 7.31 407.8 273.4 67.1

The whole simulation area Precipitation (mm/yr) Annually mean temperature (◦ C) Natural available water (×108 m3 /yr) Artificial water consumption (×108 m3 /yr) Ratio of available consumption (%)

440.2 6.22 572.3 134.0 23.4

466.0 6.38 763.8 236.4 30.9

runoff decreases significantly in the 1990s in both regions, for which the decrease in precipitation is the main reason. The variability of the natural runoff has a 10-year cycle. The 1950s is a relatively dry period and the 1960s is a high-flow period; another dry period appears again in the 1970s. In a similar way, the natural runoff increases in the 1980s, but does not recover to the same level as in the 1960s. Entering the third dry period in the 1990s, the natural runoff decreases significiantly compared to the 1980s, by nearly 30% in the upstream and nearly 50% in the midstream. Regarding the artificial uses of surface water in the midstream between the Lanzhou and Huayuankou gauges (middle part of Table 6.3), agricultural irrigation is the major sector which was developed mainly during the 1960s and the 1970s. The artificial water consumption in the 1950s is relatively lower than in the other decades. The water consumption was increasing during the 1960s, 1970s and 1980s but decreased in the 1990s. This decrease is caused by a reduction in water availability due to climate change, i.e., decreases in the precipitation and increases in temperature. Looking at the ratio of the artificial water consumption to the natural runoff from simulation (i.e., the available water), there is a continuouslyincreasing trend. This ratio increases from 46% in the 1950s and reaches 110% in the 1990s (Table 6.3). This implies that all of the available water generated

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from the middle basin is completely consumed in the same region in the 1990s. Therefore, the present situation is that the water source flowing in the downstream of the Huayuankou is from the upstream of the Lanzhou. The change in the water cycle in the upstream plays an important role in the flow condition in the lower reaches. Taking the river discharge at the Huayuankou gauge as the available runoff for the whole Yellow River basin because of the suspended river along the lower reaches, and considering all of the water losses from the river as artificial water uses, the basin total artificial consumptions of surface water can be estimated as the difference between the simulated river discharge at the Huayuankou gauge subtracted from the observed river discharge at the Lijin gauge. The decadal change in the runoff availability and the artificial consumption are estimated (lower part of Table 6.3). The artificial consumption of surface water continually increased from the 1960s to the 1980s, but reduced in the 1990s due to a decrease in the amount of runoff available. The ratio of the annual artificial consumption to the annual available runoff increases from 23% in the 1960s to 67% in the 1990s.

6.2.3. Inter-annual variability of water resources The ratio of the maximum value to the minimum value of the annual runoffs during the last 50 years is 3 at the Lanzhou gauge and is 4.5 at the Huayuankou gauge. Figure 6.8 shows the monthly river discharges at the Lanzhou and Huayuankou gauges from 1951 to 2000. The inter-annual variability of the base flow is much smaller than the peak flow. The variability in the monthly peak discharge is about a factor of five between a dry year and a flood year at the Lanzhou gauge. This variability is accentuated at the Huayuankou gauge, reaching more than a factor of ten. The high inter-annual variability of the river discharge determines the likelihood of floods and droughts, and makes it difficult to manage the water resources in this basin. Dams, a major tool for water resources management, have been developed in this basin (Fig. 6.1). Besides the large dams located on the main river, there are several hundred smaller dams constructed in this basin. It is reported that the total capacity of the reservoirs in this basin reaches 70 × 109 m3 . This is nearly the same amount as the annual runoff available in the basin. Comparing the simulated and observed river discharges, the reservoir effect is seen clearly in Fig. 6.8. At the Lanzhou gauge, the simulated hydrograph has a better agreement with the observed before the 1970s since the Liujiaxia dam was completed in 1968, and the dam effect becomes more significant after the construction of the Longyangxia dam in 1986.

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145

Fig. 6.8. Monthly river discharges at the Lanzhou and Huayuankou gauges.

Similarly at the Huayuankou gauge, a reduction in the peak flow and an increase in the base flow by reservoir regulation become more and more significant from the end of the 1950s to the 1990s.

6.2.4. Reason for the drying-up in the main river along the lower reach over the last 30 years From the hydrological simulation, the daily minimum discharge at the Huayuankou gauge is about 360 m3 /s in March of 1958. Taking into account the water leakage from the river to the groundwater along the lower reaches, the river is not expected to dry up naturally. However, in reality, a drying-up of the main river along the lower reach occurred from 1972, the situation continued during the 1980s and became

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worse in the 1990s. It was argued that the increase in the artificial water-use is the main reason for this aggravation of the water shortage in the 1990s, but no clear explanation was given. The mean value of the annually available runoff in this basin over the last 30 years (1971–2000) has been about 55 × 109 m3 , while the annual mean consumption of surface water is 32 × 109 m3 . Figure 6.9(a) compares the annual available runoff and consumption with the no flow duration along the lower reach.

Fig. 6.9. (a) Relationship between the annual available water and the duration of the drying-up, (b) Relationship between the water consumption ratio and the duration of the drying-up.

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It can be seen that the dry-ups occurred in the relatively dry years, especially during the whole of the 1990s, during which time the annual available runoff was less than the 30 year mean of 55 × 109 m3 . However, in contrast to common sense, the “drying-up” years do not correspond to the years of relatively high consumption of surface water. The annual variability in the consumption corresponds to the runoff availability. When less runoff is available, less surface water is consumed. The annual consumption of surface water shows a slightly decreasing trend and is in relation to the annual available runoff. It is concluded here that the aggravation of the drying-up situation in the 1990s is mainly caused by climate change. As discussed above, the upstream of the Lanzhou gauge is a measure of the major water resources area, and the water supplied to the downstream of the Huayuankou gauge in the 1990s is mainly from the upstream of the Lanzhou gauge. The drying up of the main river along the lower reaches in the 1990s is sensitive to the climate change of this region. As shown in Table 6.3, from the 1980s to the 1990s, the annual precipitation decreases by 35.5 mm. The annual mean temperature increases by 0.5◦ C, consequently, the annual evaporation increases by 10 mm, and of course, snowmelt runoff increases. As a result of climate change, the annual runoff at the Lanzhou gauge decreases by 42 mm in the simulation (38.7 mm from the observed river discharge). Comparing the basin averages in the two decades of the 1980s and the 1990s, the annual precipitation decreased by 38 mm (about 8.9%) and the annual mean temperature increased by 0.6◦ C. Consequently, the naturally available annual runoff decreased 24 × 109 m3 (about 36%) in the 1990s. In fact, the annual consumption of surface water in the 1990s decreased by 6.4 × 109 m3 (about 18%) compared to the 1980s. The ratio of the annual water consumption to the annual water available is 55% in the 1980s, but reaches 67% in the 1990s. As the result of both climate change and artificial consumption, the annual runoff flowing into the sea decreases nearly 18 × 109 m3 (43%). Keeping the similar trend of climate change, the Yellow River might cease to flow into the sea in future. Figure 6.9(b) compares the ratio of the annual consumption to the annual available runoff with the duration of no flow along the lower reaches of the main river. The drying-up situation is closely correlated with this ratio. Generally, a higher water consumption ratio means a longer drying-up duration in a given year. In 1997, the drying-up duration is 226 days and this ratio reaches 94%. Not only is the water shortage situation related to the annual water availability but also to the reservoir capacity and operation too. There was no drying-up in some dry years due to reservoir regulations. The reservoir can be used for inter-annual regulation only when sufficient water is available from the previous year. An increase in the reservoir capacity can be helpful for improving the water shortage situation, but

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there is a limitation in the natural runoff availability, and a high dam may result in the problem of river sedimentation. For improving the no flow condition along the lower reaches, there are two urgent countermeasures that should be carried out: (1) protection of the water source areas, especially the upstream of the Lanzhou gauge, and (2) saving water usage along the middle and lower reaches. Protection of the upstream of the Lanzhou gauge should be emphasized here because the Chinese government is now promoting western development.

References 1. D. Yang, C. Li, H. Hu, Z. Lei, S. Yang, T. Kusuda, T. Koike and K. Musiake, Analysis of water resources variability in the Yellow River basin during the last half century using the historical data, Submitted to Water Resources Research (2003). 2. X. Cheng, X. Li and G. Lu, Characteristics of the river dry-up and variation of water resources in the Yellow River basin, Advances in Science and Technology of Water Resources 1 (1999) 34–37. (in Chinese) 3. D. H. Burn and M. A. Hag Elnur, Detection of hydrologic trends and variability, J. Hydrol. 255 (2002) 107–122. 4. X. Zhang, K. D. Harvey, W. D. Hogg and T. R. Yuzyk, Trends in Canadian streamflow, Water Resour. Res. 37 (2001) 987–998. 5. T. Oki, Y. Agata, S. Kanae, T. Saruhashi, D. Yang and K. Musiake, Global assessment of current water resources using total runoff integrating pathways, Hydrol. Sci. J. 46 (2001) 983–995. 6. P. Doll, F. Kaspar and B. Lehner, A global hydrological model for deriving water availability indicators: Model tuning and validation, J. Hydrol. 270 (2003) 105–134. 7. N. W.Arnell, Climate change and global water resources, Global Environmental Change 9 (1999) S31–S49. 8. B. Nijssen, G. M. O’Donnell, D. P. Lettenmaier, D. Lohmann and E. F. Wood, Predicting the discharge of global rivers, J. Clim. 14 (2001) 3307–3323. 9. X. Liang, D. P. Lettenmaier, E. F. Wood and S. J. Burges, A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res. 99 (1994) 14,415–14,428. 10. H. Middelkoop, K. Daamen, D. Gellens, W. Grabs, J. Kwadijk, H. Lang, B. Parmet, B. Schadler, J. Schulla and K. Wilke, Impact of climate change on hydrological regimes and water resources management in the Rhine basin, Clim. Change 49 (2001) 105–128. 11. A. Moody and A. H. Strahler, Characteristics of composited AVHRR data and problems in their classifications, Int. J. Rem. Sens. 15 (1994) 3473–3491. 12. T. R. Loveland, B. C. Reed, J. F. Brown, D. O. Ohlen, J. Zhu, L.Yang and J. W. Merchant, Development of a global land cover characteristics database and IGBP DISCover from 1-km AVHRR data, Int. J. Rem. Sens. 21 (2000) 1303–1330. 13. FAO, Digital soil map of the world and derived soil properties, Land and Water Digital Media Series Rev., Vol. 1, 2003.

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14. IGBP-DIS, Global Soil Data Products CD-ROM, International Geosphere-Biosphere Programme, Data and Information System, Potsdam, Germany. Available from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A. [http://www.daac.ornl.gov], 2000. 15. M. Van Genuchten, A closed-form equation for predicting the hydraulic conductivity of unsaturated soil, J. Soil Sci. Soc. Am. 32 (1980) 329–334. 16. M. New, M. Hulme and P. Jones, Representing twentieth-century space-time climate variability, Part II: Development of a 1961–96 monthly grids of terrestrial surface climate, J. Clim. 13 (2000) 2217–2238. 17. W. Brutsaert, Evaporation into the Atmosphere (D. Reidel Pub. Co., Holland, 1982). 18. W. J. Shuttleworth, Evaporation, in Handbook of Hydrology, ed. D. R. Maidment (McGraw-Hill, 1993). 19. ICW, Hydrological Year Book, Bureau of Hydrology, Information Center of Water Resources, Ministry of Water Resources, China, 1950–1990. (in Chinese) 20. ICW (Information Center of Water Resources, Ministry of Water Resources, China), http://www.hydroinfo.gov.cn/zyysq/index.htm 21. D. Yang, S. Herath and K. Musiake, Comparison of different distributed hydrological models for characterization of catchment spatial variability, Hydrolog. Process. 14 (2000) 403–416. 22. D. Yang, S. Kanae, T. Oki and K. Musiake, Expanding the distributed hydrological modeling to continental scale, IAHS Publication, No. 270 (2001), pp. 125–134. 23. D. Yang, S. Herath and K. Musiake, Hillslope-based hydrological model using catchment area and width functions, Hydrolog. Sci. J. 47 (2002) 49–65. 24. C. Jackson, Hillslope infiltration and lateral downslope unsaturated flow, Water Resour. Res. 28 (1992) 2533–2539. 25. J. Robinson and M. Sivapalan, Instantaneous response functions of overland flow and sub-surface stormflow for catchment models, Hydrolog. Process. 10 (1996) 845–862. 26. D. Yang, S. Herath and K. Musiake, Development of a geomorphology-based hydrological model for large catchments, Ann. J. Hydraul. Eng. 42 (1998) 169–174. 27. P. J. Sellers, D. A. Randall, G. J. Collantz, J. A. Berry, C. B. Field, D. A. Dazlich, C. Zhang, G. D. Collelo and L. Bounoua, A revised land surface parameterization (SiB2) for atmospheric GCMs, Part I: Model formulation, J. Clim. 9 (1996) 676–705. 28. D. Yang and K. Musiake, A continental scale hydrological model using distributed approach and its application to Asia, Hydrolog. Process. 17 (2003) 2855–2869. 29. WMO, Intercomparison of conceptual models used in operational hydrological forecasting, WMO Operational Hydrology Report No. 7, WMO No. 429, World Meteorological Organization, Geneva, Switzerland, 1975. 30. J. E. Nash and J. V. Sutcliffe, River flow forecasting through conceptual models, Part I: A discussion of principles, J. Hydrol. 10 (1970) 282–290.

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Chapter 7

Projection of Water Supply and Demand with Economy and Food Supply in the Yellow River Basin Hidefumi Imuraa , Hiroaki Shirakawaa and Akio Onishib a Nagoya

University, Nagoya, Japan Institute for Humanity and Nature, Kyoto, Japan

b Research

China has been experiencing rapid economic growth in recent years, but a number of factors exist that could constrain future economic development. Major factors among these are its growing population, and the food needed to feed them. Besides concerns on energy and environmental pollution, issues relating to water resources have become important in recent years. There is a special concern that water shortages in northern China will restrict economic growth in the future. Agriculture accounts usually for over 60% of water demand, while the irrigation area has been increasing to boost food production, which increases water demand for agricultural use. In addition, water demand for industrial and urban uses is rising rapidly due to increasing industrial production and urban population. There is a tendency to give priority to allocating limited water resources to industrial and urban uses. Unfortunately, if this trend lasts, the agricultural sector would face a serious situation. To supply food to the growing population, it would be necessary to reduce the amount of water supplied for agricultural purposes. Key issues here include the modernization of the agricultural sector and trade-offs between industry and agriculture. In addition, water shortages and deterioration in water quality adversely affect the quality of urban drinking water (municipal water), and could escalate into serious environmental problems with ecosystem deterioration. 151

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Fig. 7.1.

GDP in the provinces (2000). Note:
indicates provincial capitals (unit: US$).

Each of the regions along the Yellow River — upstream, midstream, and downstream — has their own distinctive circumstances relating to water resources and socio-economic factors. Figure 7.1 shows the gross domestic product (GDP) of each province in the year 2000. The upper and middle regions of the river are associated with the mid-west region of the country, which is relatively less developed than other parts of the country. The local economy in the regions depends mainly on agriculture and population growth. On the contrary, agricultural development has been putting great pressure on the ecosystem. Much of the research on water utilization in the Yellow River basin has focused on specific regions and/or sectors, but only a limited amount of research has examined the supply and demand of water in the entire basin. The balance of supply and demand of water in the Yellow River basin is reported by the World Bank1 that analyzes how water supply and demand will affect regional socio-economic factors in the future. The Chinese Academy of Engineering has also published A Series of Reports on Water Resource Strategies for China’s Sustainable Development.2 The Academy’s reports incorporate the knowledge of many experts on China’s water resource policies, but lots of data that form the basis for their analysis are difficult for foreigners to obtain, and many of the details on their methodologies and models are also not provided. Determining and evaluating the interrelationships between natural and socioeconomic factors inside and outside the river basin that affect water resources, and contributing to rational water resource management policies for the river basin are

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needed to be done in terms of a model on the water supply and demand balance in the basin, simulation, analyses of the special and temporal aspects of the structure of water supply and demand, and impacts of socioeconomic factors on them.

7.1. Analysis of Current Water-Use Using the Water Resource Supply-Demand Model 7.1.1. Overview of the model The demand of water is determined by several socioeconomic factors such as economic growth, urbanization, land use, and population growth in each region. The data on these socioeconomic factors are arranged according to administrative organization unit. Therefore, in order to analyze regional characteristics on water demand it is desirable to use the smallest possible administrative organization units as the basic unit of analysis. The corresponding units used consistently in statistics in China are county and city. There are 305 counties and cities in the river basin as the basic unit of measure. Both counties and cities in the basin are treated as unit cells, and any spatial distributions within the cells are ignored. For the counties and cities, the water resources as well as the amounts of water intake and consumption based on production and economic activities are estimated on the monthly base. The river basin is divided into cells from upstream to downstream.

Fig. 7.2.

Counties and cities along the Yellow River basin.

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The Yellow River basin has 76 Class 1 tributaries (equal and more than 1,000 km2 in basin area) and the Class 2 and Class 3 tributaries (less than 1,000 km2 in basin area). In order to analyze water flow in the counties and cities in the basin, morphological data as well as socio-economical data on the tributaries were used (Fig. 7.2). Since the Fen River and Wei River are two major tributaries, they are expressed separately, different from the other tributaries. The Fen River joins the yellow River at Hangchen City and the Wei River at Tongguan County. A water resource supply and demand model was developed for the water resource supply and demand balance of each county-level city, and estimates were done using the model. Figure 7.3 shows the structure of the water resource supply and demand model. Macro framework for population/economic factors GDP

Population

Industrialization rate Water demand calculation module Agricultural sector

Effective irrigated area

Industrial sector Industrial production

Irrigation constant

Agric. water intake amount Water use per unit of industrial production

Industrial water intake amount

Urbanization ratio Domestic water sector

Population: - Serviced - Not serviced

Water use per capita

Domestic water intakeamount

Water resource flow calculation module Precipitation

Water resource volume

Water consumption rate, by sector Supply / demand balance

Spatial distributes of water demand / supply

Fig. 7.3.

: Actual values : Estimation model

Framework of the model for water supply and demand.

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The model is composed of the macro frame for population and economic factors, the water demand module, and the water resource (supply and demand) module. The macro frame is for estimating industrial activities from population and GDP. The water demand module gives water demand in each sector (agriculture, industry, domestic) based on water demand and per unit activity and GDP per capita, production coefficient in each sector, and the total activities in each cell. The water resource module gives the amount of water resources required in each county and city by multiplying the amount of water used in each sector by each sector’s water consumption ratio.

7.1.2. Structural changes in water resource supply and demand (1997–2000) After drying-up of the river occurred in 1997, the Chinese Ministry of Water Resources made efforts to devise a comprehensive water resource management policy covering many dimensions to reduce it. As a result, between 2000 and 2005 no serious drying-up occurred in the river (although minor drying-up occurred both in 1998 and 1999). Some structural changes were considered to be appeared in water resource supply and demand from 1997 to 2000. Results of the analysis are shown in Fig. 7.4, which indicate: (1) most of the water resources comes from upstream, (2) the volume of water resources was lower in 1997 compared to the other years in the river basin, (3) seasonal variations are large in the amount of water resources, (4) the amount of water consumption is high in the upstream and downstream areas, and the consumption by agriculture is particularly large, (5) there are large seasonal variations in the amounts of water used, (6) in particular, sometimes the amount of water consumption in the downstream regions exceeds the amount of water resources, and (7) imbalance between water resources and consumption is seen in the Fen River basin. Differences between water resources and water consumption in the downstream areas are clear between 1997 with a major drying-up and 2000 without that. It is likely that the 1997 incident occurred on such a large-scale due to excessive water consumption in the downstream with the fact that water resource was less. Figures 7.5, 7.6 and 7.7 show the water supply and demand balance along the rivers. The results are as follows: (1) A large amount of water resources is supplied from the upstream of Lanzhou, and the amount supplied is the largest during the summer. (2) In the downstream regions such as the Weishan irrigation district, the amount of water consumption chronically exceeds that of supplied water resources.

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Fig. 7.4.

Monthly water demand and water resources (1997–2000).

(3) In the downstream areas, because a large amount of water is extracted during the winter, imbalance in water supply and demand is evident throughout the year. (4) Because of abundance of water resources in the upstream, the water supply and demand balance is not so bad as in the downstream from April through August when water consumption increases, the amount of water consumption exceeds water supply in the Hetao irrigation district. (5) The amounts of water consumption in Xian on the Wei River and Taiyuan on the Fen River are particularly large and exceed supplied water throughout the year.

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Monthly water demand and water resources in each county in the YR main channel (1997). Fig. 7.5.

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Fig. 7.6.

Monthly water demand and water resources in Fen River basin (1997).

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Fig. 7.7.

159

Monthly water demand and water resources in Wei River basin (1997).

7.2. Impacts of Economic Growth and Urbanization on Water Resource Supply-Demand Balance 7.2.1. Regional economic growth scenarios The analytical model was used to analyze impacts on increasing water supply and demand caused by urbanization and changes in industrial structure associated with economic growth.

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Economic growth is also likely to expand the economic disparities between regions. Three different scenarios for the growth rate of each county and city are established for future GDP in the basin. The scenarios are the “uniform-growth scenario” in which the economic growth rate is uniform in the counties and cities within a province, the “large-city growth scenario” in which the economic growth of the provincial capital is higher than in the counties and cities, and the “mediumsize-city growth scenario” in which the economic growth in the provincial capitals and municipalities is higher than in other counties and cities. The economic growth rate of the whole basin is set the same in all three scenarios. Figure 7.8 shows the location of each provincial capital and the cells. The GDP projections for each province were established based on existing research results (CAE, 2001. Vol. 4) (Table 7.1). To simplify matters, the population growth rate of the counties and cities is generally set the same as that of the province. The future population projection for each province was established based on a paper (CAE, 2001. Vol. 4). The difference in the industrial sector was calculated with the following equations. Here the industrial ratio indicates the proportion of the total value added by each industry in relation to GDP.
 1 ln − 1 = a · ln(GDP per capita) + b, (1) 1 − 1 primary industry ratio

Fig. 7.8.

Location of each provincial capital and city.

112,956 9,950 1,713 678 1,407 1,467 13 2,341 1,539 339 453

126,583 11,527 2,007 754 1,548 1,695 16 2,698 1,800 386 550

2000 (actual) 140,500 12,427 2,160 834 1,672 1,810 16 2,887 1,962 469 583

2010

156,000 13,921 2,403 944 1,875 2,016 18 3,244 2,203 505 679

2030

155,688 13,886 2,383 953 1,873 2,003 18 3,252 2,208 488 707

2050

1.15 1.53 1.63 1.18 0.98 1.50 1.79 1.47 1.67 2.98 2.03

1990–2000 (actual) % 1.05 0.71 0.74 0.93 0.79 0.65 0.07 0.66 0.80 0.28 0.52

2001–2010 %

0.52 0.57 0.53 0.62 0.57 0.54 0.60 0.58 0.58 0.40 0.77

2011–2030 %

−0.01 −0.01 −0.05 0.04 −0.02 −0.04 0.02 0.00 0.00 −0.18 0.19

2031–2050 %

12:25

China YRB Shanxi Neimengu Shandong Henan Sichuan Shannxi Gansu Qnghai Ningxia

1990 (actual)

Population growth rate (%)

Scenario of population and population growth rate in China and YRB (2000–2050).

Population (10,000 persons)

Table 7.1.

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ln

 1 − 1 = a · ln(GDP per capita) + b, 1−tertiary industry ratio

(2)

Secondary industry ratio = 1(primary industry ratio + tertiary industry ratio).

(3)

The values of water-use for agriculture per unit of activity were based on those of the year 2000. The values of water-use for industry per unit of activity are calculated by a regression formula using GDP per capita of the non-farmer population as an explanatory variable. The values for water-use for domestic use (households) per unit activity come from a future scenario taken from a paper (CAE, 2001. Vol. 2). For water resources, a scenario was established based on the “probability ratio”. This probability ratio (P) indicates the degree of depletion of water resources based on the probability of occurrence of an amount of precipitation per year; in normal years the amount of annual precipitation is set as P = 50%. The lower the amount of annual precipitation is, the closer P gets to 100%, and conversely in rainy years, it approaches 0%. This scenario analysis does not consider the following factors that could possibly have significant effects on water supply and demand: • • • •

Changes in the size of cultivated land areas and cultivation conditions due to climate change, etc. Reduction in farmland due to urbanization Changes in the planting of agricultural crops Reuse of water such as could occur with sewerage system improvements.

7.2.2. Water supply-demand gaps in the Yellow River basin Figure 7.9 shows water supply and demand gap scenarios for the Yellow River basin in the year 2050. It should be noted that these results indicates an assumed probability rate of 90% in drought years. The water supply-demand gap (Rw) is defined as follows: Rw =

n 

(Ci − Wi ),

(4)

i=1

where, C is the volume of water consumption, W is the volume of water supplied, n is the number of province, and i is the index for each province. The gap in water supply and demand (the volume of excess demand) is 14.13 × 109 m3 under the uniform-growth scenario, 13.21 × 109 m3 under the

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Large-city growth scenario

Medium-size-city growth scenario

Uniform-growth scenario

700

700

500

500

300

Water demand 608.2

Water demand 651.9

Water demand 661.1

300 100

100 -100 -300

163

-100 Supply/demand balance -88.5

Supply/demand balance -132.1

Supply/demand balance -141.3

-300

Fig. 7.9. Water supply–demand gap in 2050. Note: P = 90.

medium-size-city growth scenario, and 8.85 × 109 m3 under the large-city growth scenario. It should be noted that the water supply-demand gap indicates the extent to which the potential demand, which increases along with economic growth, exceeds the potential amount of supply, which is determined by natural factors. In reality this gap would have to be mitigated in one way or another. The demands for industrial water and domestic water, which are concentrated mainly in urban areas, increase along with economic growth. Thus the greater the broad and uniform economic growth in urban areas throughout the province is, the greater the amount of water consumption is.

7.2.3. Analysis by watershed In order to examine regional impacts in as much detail as possible, the entire basin is divided into 11 regions: the main river basin of the Yellow River (upstream, midstream and downstream), and the basins of the Wei, Fen, Huang, Tiao, Wuding, Qin, Dahei, and Luo Rivers. Figure 7.10 shows the results of calculations of the water supply-demand gaps, by province. This analysis reveals differences in the scenarios in which the water supply and demand gap is the smallest. More specifically, in the upstream, midstream, and downstream areas of theYellow River, and in the Tiao, Wuding, and Qin river watersheds, this gap is smallest under the large-city growth scenario. In the Huang, Dahei, Luo, and Wei River basins, however, the gap is the smallest under the uniform-growth scenario, and in the Fen River basin, the gap was the smallest under the midsize-city growth scenario. Below is a detailed comparison of results of the scenario analysis. Figures 7.11, 7.12, and 7.13 show the water supply and demand structure in the Yellow River

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Fig. 7.10. Water supply–demand gap in 2050. Note: P = 90%.

28 24 20 16 12 8 4 0 Maduo

Tianzhu

Taole

Pianguan

Eretuoke

Lushi

Puyang

Lijin

50 Water resource amount Water demand

40 30

Upstream

Midstream

Downstream

20

0

Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

10

Fig. 7.11. Water supply and demand in the Yellow River basin in 2050 (uniform–growth scenario). Note: The upper graph shows the total amount of water supply and water demand in each county. The lower graph shows monthly water demand and water supply in each region. P = 90%.

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28 24 20 16 12 8 4 0 Maduo 50

Yianzhu

Taole

Pianguan

Eretuoke

Lushi

Puyang

165

Lijin

Water resource amount Water demand

40

upstream Upstream

30

midstr Midstreameam

downs

Downstream

20

0

Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

10

Fig. 7.12. Water supply–demand in the main channel of YRB in 2050 (midsize-city growth scenario).

28 24 20 16 12 8 4 0 Maduo 50

Tianzhu

Taole

Pianguan

Eretuoke

Puyang

Lijin

Water resource amount Water demand

40 30

Lushi

Upstream

Midstream

Downstream

20

0

Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan. Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

10

Fig. 7.13. Water supply–demand in the main channel of YRB in 2050 (large-city growth scenario).

basin for each scenario. The results obtained through the scenario analyses are as follows: (1) Examination of the relationship between the amounts of water supply and consumption reveals that in the upstream, the amount of water supply exceeds water consumption in most months, although in the uniform-growth scenario

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and medium-size-city growth scenario, the water consumption exceeds water supply in January and December; (2) In the midstream, there is a tendency for the difference between water consumption and supply to be smaller in January, February, March, November, and December, but in the other months, the consumption exceeds the supply and that gap peaks in July; and (3) In the downstream, in all cases and throughout the year, the amount of water consumption exceeds the supply of water. Under the conditions for drought years, in all cases, serious water shortages are predicted, particularly downstream. Figure 7.14 shows the water supply-demand balance in the Yellow River basin in the year 2050, under the uniform-growth scenario. The circles mean drying-up. The net flow falls below zero in some counties and cities from January to August, and there is a possibility that the flow will dry up. Figure 7.15 shows a comparison between the scenarios for annual water consumption in the Yellow River basin. This indicates the following results: (1) The medium-size-city growth scenario compared with the large-city growth scenario, the estimated water consumption is exceptionally large (numbers in parentheses indicate the difference between the scenarios) in midstream cities, Baotou (1.83 × 109 m3 ) and Dongsheng (0.58 × 109 m3 ) and in the downstream city, Binzhou (1.75 × 109 m3 ). Meanwhile, under the mediumsize-city growth scenario, cities where the consumption of water is greater than in the large-size-city growth scenario including Jinan, but even in Jinan, where the difference is the largest, the difference between the scenarios is only 0.48 × 109 m3 . Regarding the water consumption in other counties and cities, the difference between the scenarios is small. (2) In the uniform-growth scenario and the large-size-city growth scenario, the results are similar to the results in No. 1. For counties and cities in the upstream and downstream, however, there is a tendency for the annual amount of consumption to be larger under the uniform-growth scenario than under the large-size-city growth scenario. (3) As for the uniform-growth scenario and the medium-size-city scenario, if one compares the results of No. 1 and No. 2 mentioned above, there is not a large difference in the estimated results on annual water consumption in the counties and cities, but under the uniform-growth scenario, the annual water consumption is larger in the upstream of Lanzhou and in the downstream cities. Meanwhile the amount of water consumption is lower under the medium-size-city growth scenario than under the uniform-growth scenario in cities such as Baotou, Binzhou, and Jinan.

Fig. 7.14.

25 10 -5

25

10

-5

10

25

40

55

70

85

Cumulative water resources-5

Nov.

-5

River flows (unit: 100 million m3)

Dec.

Sept.

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Monthly water demand and supply in the main channel of YRB in 2050 (uniform growth scenario). Note: P = 90%.

40

40

70

85

-5

55

Oct.

25

25

10

40

40 10

55

70

55

55

70

85

85

Aug.

85

85 70 55 40 25 10 -5

10

25

Jun.

Mar.

12:25

70

-5

-5

Jul.

-5

10

10

40

25

55

70

85

40

May

85 70 55 40 25 10 -5

25

70

85

Feb.

40

Downstream

85 70 55 40 25 10 -5

55

Apr.

Upstream Midstream Wei River merges Fen River merges

Jan.2050

55

70

85

-5

85 70 55 40 25 10

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Linhe Dongshen Baotou

Huayang Yijinluohu

Ertuokeqi Wushen

Hancheng Lingbao Yongji Yuncheng

Uniform-growth scenario — Large-city growth scenario

Wuzhong Shizuishan Yinchuan Wuhai

Uniform-growth scenario — Medium-size-city growth scenario

Qingtongxi

Medium-size-city growth scenario — Large-city growth scenario

Baiyin Lanzhou

Shanmenx Yima

(unit: 100 million m3)

Puyang

Feicheng Jinan Taian Xintai Laiwu Binzhou Dongying

Fig. 7.15.

Comparing water demand among the scenario in 2050. Note: P = 90%.

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7.3. Impacts of Changes in Food Demand on Water Resources Water for agriculture accounts for over 60% of the total share of water-use, so changes in food demand can be expected to have a large impact on water resources. The amount of food demand depends primarily upon income and price levels, and the food produced within the river basin satisfies demand not only within the basin, but also outside the basin through trade. Therefore the demand coefficients relating to rice and wheat, etc., are estimated in food demand associated with income and price changes with an assumption; the distribution of food consumption in the year 2000, and then the impacts of changes in food demand are calculated by product on consumption in the basin. Figures 7.16 to 7.19 assume an 8% increase in income and show the amount of increase in water demand for agriculture in nine provinces of theYellow River basin (Shanxi, Inner Mongolia, Shandong, Henan, Sichuan, Shaanxi, Gansu, Qinghai, and the Ninxia Autonomous Region). Also, in order to consider the relationship between production and consumption regions, the amount of increase in water demand is divided into three categories: demands arising from within the province, demands arising from other provinces in the river basin, and demand arising from provinces outside the river basin. The results of the analysis show that large differences arise between crop types in terms of the increase of the amount of water used. Also, the differences between provinces are large. When examined crop by crop, one discovers a large impact on water consumption from increased demand within the river basin for wheat. One reason for this is that the production of wheat is large compared to rice and 600

Within the province

10 thousand m3

500

Other provinces in the river basin

400

provinces outside the river basin

300 200 100 0

x i su a i x ia g li a n an g o d on en a c h u a a n a n i n g h N i n n h G i n H S o S Q M Sha er

a Sh

n

nx

i

Fig. 7.16. Amount of increase in water demand for rice. Note: Income growth rate is set at 8%.

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4,000 10 thousand m3

Within the province Other provinces in the river basin

3,000

Provinces outside the river basin

2,000 1,000 0

x i su a i x ia g li a n an g o d on en a c h u a a n a n i n g h N i n n h G n H Si S o Q M Sha er

a Sh

n

nx

i

10 thousand m3

Fig. 7.17. Amount of increase in water demand for wheat. Note: Income growth rate is set at 8%.

360 320 280 240 200 160 120 80 40 0

Within the province Other provinces in the river basin Provinces outside the river basin

x i su a i x ia g li a n an g o d on en a c h u a a n a n i n g h N i n n h G n H Si S o Q M Sha er

a Sh

n

nx

i

Fig. 7.18. Amount of increase in water demand for maize. Note: Income growth rate is set at 8%.

maize. Meanwhile, for maize, the impact on water resources in the basin by the demand from outside the river basin is larger than for other crops.

7.4. Toward the Future In the upper reach of the Yellow River basin, as well as in Taiyuan on the Fen River and Xian on the Wei River, there were even months in which the net river flow volume was zero. The net river flow was completely depleted from January to July along the main stream of the river, January, February, March, May, November and December in Taiyuan on the Fen River, and January and February in Xian

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200 10 thousand m3

Within the province

160

Other provinces in the river basin Provinces outside the river basin

120 80 40 0

x i su a i x ia g li a n an g o d on en a c h u a a n a n i n g h N i n n G Q n H Si S h o M Sha er

a Sh

In

n

nx

i

Fig. 7.19. Amount of increase in water demand for beef. Note: Income growth rate is set at 8%.

on the Wei River. Most of the areas irrigated by the Yellow River and other areas downstream on the main channel where the river dried up depend on the river flow for water. For example, for the Wei River and Fen River, which depend heavily on groundwater, as in the case of Xian which depends on groundwater for 70 percent of its water use, a tight supply-demand balance in the Wei and Fen River basins causes the problem of falling groundwater levels, rather than river flow stoppages. Over abstraction of groundwater is to be solved not to cause other environmental deterioration toward future. Regarding the relationship between economic growth and water demand, there is a tendency for the water resource supply and demand gap to become greatest under a uniform-growth scenario in which economic growth occurs broadly and uniformly within a given province. However, depending on the conditions in the river basin, this is not always the case. Because this is very dependent on criteria and assumptions, more detailed discussion is necessary. Also, in reality, supplydemand gaps would have to be resolved or mitigated in one way or another. The analysis of how this would be accomplished by policy or technology changes, and how in what ways the burdens would be allocated between regions and between sectors, is a topic for future discussion. Impacts of changes in food demand associated with economic growth on water consumption in a river basin are largest in the case of wheat. If incomes nationwide in China increase by 8%, the total increase in agricultural water consumption in the river basin associated with the increase of grain demand outside the river basin would be about 9×106 m3 . The increase in demand for water for agriculture would be greatest in Henan Province, Shandong Province and Ninxia Autonomous Region

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(in descending order). In these provinces, the greater part of the increase would be caused by demand for wheat from within each province. Meanwhile the increase in water demand due to increases in demand for maize would be smaller than in the case of wheat. Also the water demand associated with production to satisfy demand for maize outside the river basin would be large. In Inner Mongolia, Gansu Province, and Ninxia Autonomous Region, the increase in water consumption originating from the increase in demand for wheat from outside the river basin would be larger than the amount due to demand inside the provinces. Most of the maize is used for livestock feed, and an examination of the type of meat shows that the increase in water consumption for poor production was the greatest, at 7 × 106 m3 . Of this amount, 30% was associated with an increased supply to other provinces within the river basin. For water saving, the National plan for water use is inevitable. To achieve the water supply and demand balance in the entire river basin, it is necessary to consider physical and economic efficiency, while also keeping in mind equity between regions and between sectors. In order to achieve this, it would be necessary to make further improvements in models that make it possible to quantitatively determine the impact of policies, and to use these in various policy simulations. Management in a river basin as vast as that of the Yellow River involves a wide variety of complex interests between regions and between sectors. This type of coordination is being conducted by bodies such as the Yellow River Conservancy Commission (YRCC) and water utilization committees in each province, but the necessary data for debate is not always available publicly, and the issues of what kind of impacts will arise when there are changes in the water allocation plans are not entirely clear to foreigners.

References 1. World Bank, Sinclair Knight Merz and Egis Consulting Australia, the General Institute of Water Resources & Hydropower Planning and Design, China Agenda for Water Sector Strategy for North China, Vol. 1 (2001). 2. Chinese Academy of Engineering, A Series of Reports on Water Resource Strategies for China’s Sustainable Development, Vol.1–9 (Water Publication Company of China, 2001). (in Chinese)

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Index

accumulated salt, 60 advection–dispersion equation, 94 aerodynamic method, 59 agricultural irrigation, 143 alluvial plain, 7 ancient irrigation project, 17 Anemaqen Mountain, 5 angular-distance weighting method, 130 anisotropy ratio, 132 autumn flood, 10 autumn irrigation, 50, 59

electrical conductivity, 60 electrical conductivity of groundwater, 60 electrical conductivity of soil solution, 61 electromagnetic induction method, 54 erosion productivity impact calculator, 82 estimated daily evapotranspiration, 57 evapotranspiration, 53

balance of supply and demand of water, 152 Bingham fluid, 118 BOD, 79 Bowen ratio method, 59

GDP, 17 geomorphology-based hydrological model, 81, 132 granular sublayer, 118 gross domestic product, 152 groundwater flow, 136 groundwater table, 38

flood plain-channel interaction, 136 forest conservation and afforestation policies, 39

canopy interception capacity, 90, 133 comprehensive basin management strategy, 20 critical shear stress, 92 crop coefficient, 134 crop transpiration, 57

Hetao Plateau, 6 hill-slope model, 90 Horton overland flow, 91 household consumption, 15 Huayuankou gauge, 144 hyper-concentrated mixture flow, 118

Darcy’s Law, 91, 135 digital elevation model, 131 drying-up, 10, 20, 147, 155 Dryness Index, 41 dual crop coefficient approach, 57

ice-run flood, 10 income levels, 19 inertial sublayer, 118 infiltration capacity (VIC) conceptual model, 128 Inner Mongolia Plateau, 6 intergranular stress, 118

economic centers, 16 economic disparities, 160 economic growth rate, 160

173

October 3, 2009

13:21

174

9in x 6in

b802-Index

The Yellow River: Water and Life

irrigated agriculture, 13 Irrigation Agriculture, 16

precipitation elasticity, 33 precipitation elasticity of river flow, 34

Karmen constant, 119

Radiative Dryness Index, 40 rain-fed agricultural areas, 16 rain-use efficiency, 16 rainfall–runoff relationship, 110 ratio of depletion to withdrawal, 66 re-aeration coefficient, 93 reference evapotranspiration, 29 reservoir impoundment, 36 residence time of river water, 36 Richards’ equation, 91, 134, 135 runoff coefficients, 112

Lanzhou gauge, 144 large-city growth scenario, 160 leaf area index, 90, 130 Lijin gauge, 144 Loess Plateau, 7, 42, 141 Manning’s equation, 91 medium-size-city growth scenario, 160 mineralization degree, 50 mixing-length theory, 119 municipal universal soil loss equation, 83 naturalized flow rate, 32 Newtonian fluid model, 120 nitrogen dynamics, 82 non-dimensional elevation, 119 non-Newtonian fluid model, 120 non-point sources, 80 Normalized Difference Vegetation Index, 90, 108 O’Connor–Dobbins method, 93 Ordos Plateau, 7 over-irrigation, 13 Penman–Monteith (P–M) equation, 29 Penman–Monteith method, 89 Pfafstetter basin numbering scheme, 135 Pfafstetter number, 136 phosphorus dynamics, 83 physically-based model for water resources assessment, 128 point sources, 79 population density, 10 population distribution, 10 porosity of soil, 7 potential daily evapotranspiration, 89 potential evaporation, 29 potential evaporation rate, 134 potential evapotranspiration, 41

salinization, 13 saturated hydraulic conductivities, 132 saturated hydraulic conductivity, 7 sediment discharge, 124 sediment transport rate, 117, 119 sediment yield, 105 sediment–water mixtures, 118 sediment-laden flow, 117 Shuttleworth–Wallace (S–W) equation, 29 snow water equivalent, 27 snowmelt runoff, 136 soil and water integrated model, 80 soil evaporation, 57 Soil-Plant-Atmosphere-Continuum (SPAC) concept, 45 straw checkerboard method, 43 Streeter–Phelps model, 91 sub-grid parametrization, 132 sub-surface flow, 134 summer flood, 10 summer irrigation, 50 Taihangshan Mountain, 6 temperature-based model, 133 Tibetan (the Qinghai-Tibetan) Plateau, 5 transpiration rate, 134 uniform-growth scenario, 160 unsaturated hydraulic conductivity, 130 urbanization, 14

October 3, 2009

13:21

9in x 6in

b802-Index

Index

Van Genuchten’s formula, 91, 130 water allocation policy, 20 water balance model, 128 water pricing, 20 water quality level, 73 water resource supply and demand model, 154 water stress, 21

175

water supply-demand gap, 162 water transport efficiency, 50 water-retention relationship, 130 water-saving policy, 20 water-use efficiency, 60 winter irrigation, 50 Yellow River Conservancy Commission, 18