Disaster Risk Reduction for Resilience: Climate Change and Disaster Risk Adaptation 3031221117, 9783031221118

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Saeid Eslamian Faezeh Eslamian   Editors

Disaster Risk Reduction for Resilience Climate Change and Disaster Risk Adaptation

Disaster Risk Reduction for Resilience

Saeid Eslamian  •  Faezeh Eslamian Editors

Disaster Risk Reduction for Resilience Climate Change and Disaster Risk Adaptation

Editors Saeid Eslamian Department of Water Science and Engineering, College of Agriculture Center of Excellence in Risk Management and Natural Hazards Isfahan University of Technology Isfahan, Iran

Faezeh Eslamian Department of Bioresource Engineering McGill University Montréal, QC, Canada

ISBN 978-3-031-22111-8    ISBN 978-3-031-22112-5 (eBook) https://doi.org/10.1007/978-3-031-22112-5 © Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

To Professor Hossein Sedghi (1941–2018), my late master’s supervisor, having more than 100 technical papers on hydrology and climate change Leave the planet to civilized animals. Only the destruction of the human being can save the world. The earth must be freed from human evil (Sept. 8, 2016)

Preface

Disaster risk reduction (DRR) aims to prevent new disaster risks and reduce existing ones, strengthening the resilience of people, systems, and approaches. These disasters mainly include climate change, displacement, urbanization, pandemics, protracted crises, and financial systems collapse. The United Nations System Chief Executives Board for Coordination (CEB), at its 2011 Spring Session, committed to mainstreaming disaster risk reduction in the programs and operations of the UN system through the development of a common agenda, and raise disaster risk reduction to the highest political support. UNISDR (United Nation Office for Disaster Risk Reduction) Strategic Framework 2016–2021 is guided by supporting countries and societies in its implementation, monitoring and review of progress; the prevention of new and reduction of existing disaster risk and strengthening resilience through successful multi-hazard disaster risk management. The Sendai Framework aims to achieve the substantial reduction of disaster risk and losses in lives, livelihoods and health and in the economic, physical, social, cultural and environmental assets of persons, businesses, communities and countries, by 2030. The Sendai Framework includes seven targets and four priorities for action: The Seven Global Targets could be summarized as follows: (a) Substantially reduce global disaster mortality by 2030 (b) Substantially reduce the number of affected people globally by 2030 (c) Reduce direct disaster economic loss in relation to GDP by 2030. (d) Substantially reduce disaster damage to critical infrastructure, among them health and educational facilities (e) Substantially increase the number of countries with local disaster risk reduction strategies by 2020. (f) Substantially enhance international cooperation to developing countries through adequate and sustainable supports (g) Substantially increase the availability of the access to multi-hazard early warning systems by 2030 vii

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Preface

The Four Priorities for Action for Sendai Framework are as follows: Priority 1. Understanding disaster risk Priority 2. Strengthening disaster risk governance to manage disaster risk Priority 3. Investing in disaster risk reduction for resilience Priority 4. Enhancing disaster preparedness for effective response Book series Handbook of Disaster Risk Reduction for Resilience (HD3R) attempts to fill theory and practice gap in the Sendai Framework through publishing the six proposed books. There is a big hope that learning Primary and Secondary Audiences of HD3R helps to meet several Sendai targets and priorities for action; the book series HD3R could be continued beyond publishing these six books up to 2030. For assisting the UN objectives in disaster risk reduction, the 2023 handbook series of Disaster Risk Reduction for Resilience (HD3R–2023) has been contracted by Springer. The handbook’s volume titles are given below: I-Disaster Risk Reduction for Resilience: New Frameworks for Building Resilience to Disasters II-Disaster Risk Reduction for Resilience: Disaster Risk Management Strategies III-Disaster Risk Reduction for Resilience: Disaster and Social Aspects IV-Disaster Risk Reduction for Resilience: Disaster Economic Vulnerability and Recovery Programs V-Disaster Risk Reduction for Resilience: Climate Change and Disaster Risk Adaptation VI-Disaster Risk Reduction for Resilience: Disaster Hydrological Resilience and Sustainability This book is part of a six-volume series titled Disaster Risk Reduction and Resilience: Climate Change and Disaster Risk Adaptation. The series aims to fill in gaps in theory and practice in the Sendai Framework, and provides additional resources, methodologies, and communication strategies to enhance the plan for action and targets proposed by the Sendai Framework. The series will appeal to a broad range of researchers, academics, students, policy makers, and practitioners in engineering, environmental science and geography, geoscience, emergency management, finance, community adaptation, atmospheric science, and information technology. The current volume, titled Climate Change and Disaster Risk Adaptation, is the fifth book of this series and includes 19 chapters as summarized below: This volume focuses on the social-hydrological systems and climate change adaptations, and extreme hydro-meteorological events such as flood, drought, precipitation, and temperature have been investigated. Climate changes, agro-forestry resilience, and water–food security have been finally discussed. Students in all three levels (and also short courses) and instructors, lecturers, and professors are the primary audiences.

Preface

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The secondary audiences include industry members (earthquake industries, pollution control industry, chemical factory, construction industry, transportation industry), policy makers, consulting engineers, researchers (civil engineering, geosciences, natural geography, environmental science and engineering, hydrologic engineering, atmospheric sciences, environmental sanitation, applied sciences, statistics, information technology), national hazard centers, national weather services, IPCC Members, insurance companies, International Bank for Reconstruction and Development, UNDRR, UNEP, community resilience centers, emergency management agencies, and disaster risk managers. Isfahan, Iran Montréal, QC, Canada

Saeid Eslamian Faezeh Eslamian

Contents

Part I Social-Hydrological Systems and Climate Change Adaptation 1

Linkage Between Social and Hydrological Systems to Support Resilience: A Case of Freshwater Wetland in Bangladesh ������������������������������������������������������������������������������������������    3 Md Mahfuzul Haque, Nahrin Jannat Hossain, Newazul Moula, and Saeid Eslamian

2

 Indigenous Approaches to Disaster Risk Reduction, Community Sustainability, and Climate Change Resilience ������������������������������������   37 Christine Kenney, Suzanne Phibbs, Litea Meo-Sewabu, Shaun Awatere, Marie McCarthy, Lucy Kaiser, Garth Harmsworth, Nichola Harcourt, Lara Taylor, Nicki Douglas, and Lani Kereopa

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The Adaptation to Climate Change in Primary Education and Approach from the Social Sciences Textbooks������������������������������   61 Álvaro-Francisco Morote, Jorge Olcina, María Hernández, and Saeid Eslamian

4

Building Climate Change Adaptation and Risk Knowledge in the Arctic Through Preparedness and Contingency Practices��������   77 Gisele M. Arruda and Lara Johannsdottir

5

Ecological Resilience for Transformative Climate Change Mitigation and Adaptation����������������������������������������������������������������������   91 Keith Morrison and Moleen Monita Nand

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Mitigating Disaster Risks and Vulnerabilities Through Climate Finance and Sustainable Water Management: Policy Considerations for Sub-­Saharan Africa and Malawi������������������������������������������������������  117 Dumisani Chirambo

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Contents

Part II Extreme Hydro-Meteorological Events: Flood, Drought, Precipitation and Temperature 7

Assessing Risks and Resilience to Hydro-­Meteorological Disasters����������������������������������������������������������������������������������������������������  143 Never Mujere

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 Flood Resilient Plan for Urban Area: A Case Study����������������������������  161 Anant Patel, Neha Keriwala, Darshan Mehta, Mohamedmaroof Shaikh, and Saeid Eslamian

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Flood and Drought Risk Assessment, Climate Change, and Resilience ������������������������������������������������������������������������������������������  191 Omar-Darío Cardona, Gabriel Bernal, and María Alejandra Escovar

10 Flood  Risk Predictions in African Urban Settlements: A Review of Alexandra Township, South Africa ����������������������������������  215 C. C. Olanrewaju and M. Chitakira 11 Anthropological  Study of a Typical Drought-Prone Village in India: Strategies for Sustainable Rural Habitat ������������������������������  239 Iyer Vijayalaxmi Kasinath and Subham Das 12 Risk  Management of Extreme Precipitation in Mexico: Building Resilience��������������������������������������������������������������������������������������������������  273 Evelia Rivera-Arriaga, Rodolfo Silva, Cesia J. Cruz-Ramírez, Isaac Azuz-­Adeath, Beatriz E. Vega-Serratos, and Gregorio Posada Vanegas 13 Increasing  Temperature Risk and Community Resilience: Urban Aspects������������������������������������������������������������������������������������������  303 Beta Paramita, Andreas Matzarakis, and Prabal Barua Part III Climate Changes, Agro-Forestry Resilience and Water-Food Security 14 Climate  Change Adaptation in Megacities : A Critical Review on the Brazilian Political Context����������������������������������������������������������  319 L. D. Barreto Torres and G. F. Asmus 15 Climate  Change, Food Security, and Resilience: Hydrologic Excess and Deficit Measurement������������������������������������������������������������  333 Omar-Darío Cardona, Gabriel Bernal, and María Alejandra Escovar 16 Climate  Change and Agroforestry Resilience Strategy in West Africa’s Cocoa Supply Chain Dynamics����������������������������������  361 S. A. Igbatayo

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17 Spatial-Temporal  Changes of Water Resources: Associated Impact as a Natural Hazard��������������������������������������������������������������������  387 Yaser Sabzevari and Saeid Eslamian 18 Vulnerability  of Climate Change on Water and Sanitation Sectors and Coping Mechanisms by the Communities of Economically Poor Hard-to-­Reach Areas of Bangladesh����������������  417 Prabal Barua, Anisa Mitra, and Saeid Eslamian 19 Climate  Governance, Resilience and Entrepreneurship in Nigeria: An Empirical Review������������������������������������������������������������  445 Ayodeji O. Ojo and Isaac B. Oluwatayo Index������������������������������������������������������������������������������������������������������������������  455

About the Editors

Saeid  Eslamian  He  completed his PhD in the Department of Civil Engineering, University of New South Wales, Australia, in 1995. He is now Full Professor of Hydrology and Water Resources Sustainability at Isfahan University of Technology, director of the Excellence Center in Risk Analysis and Natural Hazards, and chief of the Specialized Group on Water Resources Policy and Management, Research Center of Water and Wastewater. Formerly, he was a professor at Princeton University, USA; the University of ETH Zurich, Switzerland; and McGill University, Montreal, Quebec, Canada. Recently, he has been awarded World Top 2% Scientist sign from Stanford University and being Award High-level Jury Member and Invited Dialogue Person for the related organizations of United Nations. Prof. Eslamian is the founder and chief editor of the International Journal of Hydrological Science and Technology (Inderscience) and Water Productivity Journal. Prof. Eslamian is also editorial board member or reviewer of more than 150 Web of Science (ISI) journals. He has contributed to more than 1000 publications in journals, books, or technical reports from Elsevier, Springer, Wiley, Taylor and Francis, and IWA.

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Faezeh Eslamian  She holds a PhD degree in bioresource engineering from McGill University, Canada, as well as a bachelor’s and master’s degree in civil and environmental engineering. She has more than 10 years of experience in managing various multidisciplinary projects including soil and groundwater characterization and remediation, hydrogeology, water and wastewater treatment, and numerical modeling. Faezeh has more than 40 publications including journal papers, book chapters, as well as handbooks.

Part I

Social-Hydrological Systems and Climate Change Adaptation

Chapter 1

Linkage Between Social and Hydrological Systems to Support Resilience: A Case of Freshwater Wetland in Bangladesh Md Mahfuzul Haque, Nahrin Jannat Hossain, Newazul Moula, and Saeid Eslamian

Abstract  Conceptualizing water and society is crucial to address hydrological and social challenges and their complex interactions under climate change scenarios and increasing pressure on water resources. Bangladesh is at the forefront of hydro-­ climatic disasters such as flood, cyclone, salinity intrusion, and drought wherein vulnerable people are continuously embracing new socioeconomic systems co-­ opting with water inlaid challenges. Societal actions and policy decisions are also interplaying with the hydrological system to evolve and adapt new paths for building resilience. There are a number of socio-hydrological elements that help the vulnerable community to cope with ever-increasing socio-hydrological challenges. Taking Chalan Beel as an example, which is one of the largest freshwater wetlands in Bangladesh, we analyzed the hydro-climatic disasters such as flood, water scarcity, declining water resources and the impact of such disasters on the livelihood of the community who are heavily reliant on the wetland for their income. The presentations of linked socio-hydrology through documenting disaster management approaches are also crafted, access to common property resources, and adaptation practices of the community to identify small-scale transformational changes that enable them to focus more on disaster preparedness and prevention for building resilience at the large scale.

M. M. Haque (*) · N. Moula Transparency International Bangladesh (TIB), Dhaka, Bangladesh e-mail: [email protected]; [email protected] N. J. Hossain Department of Geography and Environment, Jagannath University, Dhaka, Bangladesh e-mail: [email protected] S. Eslamian Department of Water Science and Engineering, College of Agriculture, Center of Excellence in Risk Management and Natural Hazards, Isfahan University of Technology, Isfahan, Iran e-mail: [email protected] © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_1

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Keywords  Wetland · Socio-hydrological system · Resilience · Chalan Beel · Bangladesh

1 Introduction Socio-hydrology focuses on observing, understanding, and predicting the co-­ evaluation of coupled water human system (Sivapalan et al., 2011). Catchment area, basin and reservoir storage, availability and flow of water in the rivers, wetlands, lakes, groundwater, etc. are hydrological elements (Marshall, 2013). The socio-­ hydrological system refers to social components such as demographic, economic, cultural and educational elements along with technology, norms, and values of the society that interact with the existing hydrological systems (Pande & Sivapalan, 2017; Wesselink, Kooy and Warner 2017). The social and hydrological system is dynamic, and a variety of actors interact with each other. Factors affecting the hydrological system directly are land use, demand and use of water, regulating policies and other demographic elements. Nowadays, climate change has emerged as the major driving force of changing the socio-hydrological landscape. Particularly, the increased frequency of hydro-climatic extreme events such as flooding and drought has profoundly impacted the socioeconomic conditions of the people (IPCC, 2012). Besides, slow-onset events such as uncertainty of rainfall have a great impact on water flow and water availability that in turn negatively impact ecosystem services, food production, food security and livelihood of people dependent on the hydrological systems. Despite climate change impact, the interconnected and coupled socio-hydrological system helps in building resilience, which is constructed by combining absorptive and adaptive capacities. In the coupled system, community people are indeed the most important component where they are impacted by hydrological events, and the hydrological process is impacted by the decisions people make in response to those impacts to develop, manage and use water resources (Sivapalan, 2015). The Intergovernmental Panel on Climate Change (IPCC) defines resilience as the ability of a community or system and its component to anticipate, absorb, accommodate, or recover from a hazardous effect in a timely and efficient manner emphasizing on preservation, restoration, or improvement of the function of the system (IPCC, 2012). Like other disciplines, in socio-hydrology, the system includes individual, community, and organization and their ability to anticipate, prepare for, reduce impacts of, cope with, and recover from the effects of shocks and stress without compromising their long-term prospects. Resilience framing in a socio-­ hydrological system involves three types of human–water coupling: (i) water subsystem with hydrological resilience to anthropogenic hazards that describes human–water interactions with special focus on anthropogenic factors that are impacting water subsystems; (ii) human subsystem with social resilience to

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hydrological hazards that focuses on social resilience with particularly focus on disaster management; and (iii) socio-hydrological system with socio-hydrological resilience that focuses on coupled systems such as ecosystem services management (Mao et al., 2017). This chapter aims to analyze the hydro-climatic disasters on the community heavily reliant on the wetland, and their impact on their livelihood. The chapter also aims to present the linked socio-hydrology through documenting communities’ disaster management approaches, adaptation practices that enable them to focus more on disaster preparedness and prevention for building resilience at a large scale (Eslamian et al., 2020).

2 Socio-hydrological System of Bangladesh Based on hydrological characteristics, Bangladesh is categorized into five hydrological regions: (i) North-Western (ii) South-Western (iii) Central (iv) North-Eastern and (v) South-Eastern (Alam & Sarker, 2014). Considering hydrological hazards, the areas are broadly divided into five categories: (i) flood-prone (ii) drought-prone (iii) coastal (iv) wetlands/haor and (v) eastern hilly regions (Goosen et al., 2018). The hydrological regions and their subsystems are greatly governed by hundreds of crisscrossing rivers that influence the life and livelihood of the people of Bangladesh. Indeed, the rivers are the lifeline to the rural people for their agriculture, transportation, fishing, and aquatic ecosystem services. However, each of the geographical regions faces different hydrological hazards but flood is the major one that inundates almost 20% of the country each year (Ali et  al., 2013). Besides, increased events of flood, cyclone, inundation, and salinity intrusion in coastal areas are adverse effects attributed to climate change (Moula et al., 2019). The anomaly of rainfall and temperature inflates the problem of drought and groundwater scarcity in the northern part of the country (Adhikary et al., 2013). On the other hand, construction of dams, diverting water from transboundary rivers, and pollution are major challenges to protecting freshwater sources of the rivers and wetlands, sustaining alongside their navigability (FAO, 2011; Chan et al., 2016; Sayeed et al., 2014). Being an agrarian country, the wetlands create a vital link among society, land, river, and water that covers about 50% of the total land (Khan et al., 1994). A large portion of the country’s population is dependent on wetland resources for securing food and livelihood (Byomkesh et al., 2009). However, wetland areas are most susceptible to slow-onset events of climate change such as flooding, which causes widespread damage to crops and critical infrastructures with severe impact on livelihood (Kamal et  al., 2018). Particularly, Chalan Beel1 area, which is one of the largest freshwater wetlands in Bangladesh, and supports the lives and livelihood of a huge population (Hossain et  al., 2009), is vulnerable to frequent flood during

 Beel is a lake-like wetland with static water in the Ganges-Brahmaputra flood plain in Bangladesh.

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monsoon (June to October), severe water scarcity during dry season (November to February) and increased human interference in water bodies all around the year for resource exploitation. Despite being affected by frequent hydro-climatic hazards, there are no visible efforts of disaster management to safeguard the lives and livelihood of the people in the area (Paul & Hossain, 2013). During the last one and half centuries, it is estimated that the wetland has shrunk significantly from the southern side due to increased human interference, deposition of silt, and slow-onset events of climate change (Rahman et al., 2010). Usually, the greater part of the wetland dries up during dry season leaving the core water basin of about 25.9–31.08 km2 (Islam, 2015). The core part of the wetland is not covered with an uninterrupted expanse of water, rather many separate dips and depressions. During monsoon, the depressions connect with each other and expand into broad and shallow sheets of water with tortuous channels. The first ring of the wetland falls in between Pabna and Sirajgonj District, where generally the depth of water is 1.53–1.83 m during monsoon (Islam, 2015). The outer rings, particularly, upstream areas of Chalan Beel in Natore and Naogoan districts, narrows down toward northwest, receiving less rainfall during the monsoon than the other parts of the wetland. Nowadays, both rings entirely dry up between December and June. As the adjacent rivers and channels discharge less water along with the higher amount of sediments from the Ganges, deposition occurs in the low-lying areas causing siltation in the wetland (Hossain, 2018). In the context of climatic uncertainties, we conducted research on Chalan Beel in Singra Upazila to understand the resilience of the communities to flooding, increasing temperature, decreasing rainfall, and water shortage. We also tried to grasp the dynamics of declining water resources and increased human interference on the wetland and apprehend its impact on the community as well as on the intermingled hydrological systems that support the livelihood of the communities. Moreover, we examined the practices of the communities to face the disasters and resilience practices to cope with the changing socio-hydrological landscapes.

3 Materials and Method Using the socio-hydrological resilience framings, we analyzed the resilience dynamics in Chalan Beel and identified human–water couplings. Both primary and secondary data are used to identify socio-hydrological resilience. Hydrological settings of the wetland have been analyzed using water discharge, runoff, flood, inundation, rainfall, temperature, and groundwater data for the last twenty-five years. Time series Landsat image of Chalan Beel was analyzed using ArcGIS Image Analyst Tools to identify basin area and extent of perennial water body of the last two decades. A questionnaire survey along with several informal interviews, focus group discussion, key informant interviews and open discussion were conducted in Singra Upazila to identify wetland ecosystem services (provisioning, regulating, cultural, and supporting services) that support building resilience. Using simple

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random sampling, a total of seventy-nine households were surveyed. Collection of past and present socioeconomic information such as occupation, livelihood, land possession, education, household income, earnings from the ecosystem, and yearround activity of family members were analyzed for determining adaptation practices and disaster resilience. The abundance of fish species, local fishing and agricultural practice, land-use pattern, government policies to access to the wetland for fishing by the local fishing community, impact of leasing out the wetland, seasonal activity of the respondents and their adaptation strategy during lean time have been assessed to identify the nexus of water and resilience. We also identified physical assets of the community such as road networks, growth centers, educational institutions, medical facilities, and their access to the facilities during flooding. Major initiatives that are implemented to promote agriculture were identified by reviewing journals and articles. Finally, the linkage of the social and hydrological system that is instrumental to support the resilience of the local people was identified and analyzed.

4 Linkage Between Social and Hydrological System of Chalan Beel Water and human systems change interdependently. Their connection and mutual reshaping evolve and continue over time. Most often, humans alter the hydrological system for their benefit. In return, altered hydrological systems accompanying extreme events shape the society and force them to respond and adapt to extreme events (Mao et  al., 2017). Sivapalan (2015) argued that place-based models are more expedient to identify and establish the human–water coupled systems for building resilience. He also found a profound relationship between human and water in managing aquatic ecosystem services for building social resilience. Taking Chalan Beel as a place-based model, the socio-hydrological condition of the study area is discussed in the next sections.

5 Temperature and Rainfall Fluctuation Localities around Chalan Beel experience interchangeable climatic characteristics of Rajshahi District in terms of rainfall, temperature and other hydrological characteristics (Rahman, 2015). The average temperature and rainfall data of two nearest weather stations (Rajshahi and Ishwardi) of the wetland represents a strong negative correlation. Figures 1.1 (a) and (c) shows declining rainfall with rise of temperature at Rajshahi and Ishwardi stations. At Ishwardi, yearly mean rainfall has declined to 145 mm from 159 mm, while the maximum mean temperature has risen to 31.24 °C from 30.93 °C since 2000. A similar trend is found at Rajshahi, which shows that

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yearly mean rainfall has declined to 144.87 mm from 150.82 mm while the maximum mean temperature has risen to 31.43 °C from 31.03 °C since 2000. Comparing the mean rainfall data between 1962 to 1999  in Fig.  1.1b and 2000 to 2013  in Fig. 1.1d, a gradual decline, as well as a shift of timing in rainfall is observed with the gradual increase of mean temperature. Particularly, mean rainfall is declining gradually during the months of June to September which is the peak monsoon time. In contrast, a slight increase in mean rainfall is observed during the months of October and November since the year 2000. This phenomenon shows an indication of shorter monsoon and a gradual shift of the monsoon period. Such shifts negatively impact the rain-fed agriculture and crop production.

6 River Discharge and Runoff in Ganges and Brahmaputra River Originating from the Padma in Rajshahi, Baral River flows through the Chalan Beel in Pabna and Natore districts and connects with the Jamuna River. Baral River also receives water from Atrai River through Gumani channel.  These Rivers feed the Chalan Beel with their water making the wetland ecosystem more identical and unique. But slow-onset effect of climate change arising from the increased temperature and decreased rainfall has an impact on the water systems and its ecological subsystems. Especially, increasing evaporation and decreasing precipitation and runoff effect in lowering groundwater level (Marcé et al., 2010). In the dry season, the gradual fall of the groundwater table in the Chalan Beel area is the result of a

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short monsoon period characterized by low rainfall and less moisture content (Jahan et al., 2010). As rainfall decreases in the catchment areas, river runoff and discharges further decrease, which contributes to decreasing recharge of groundwater (Kabir & Hossain, 2012). Meanwhile, the mean annual runoff in the Ganges basin near Rajshahi point was 374 mm during the years of 1988–2018. However, the annual runoff has been declining considerably every year and it stands at 141.2  mm in 2018, which is only 38% of twenty years’ average (Fig. 1.2a). On the other hand, the mean annual runoff in the Brahmaputra basin was 1072 mm during the years of 1998–2018 and the annual mean runoff fluctuates between 1379 mm to 767 mm with a minor decreasing trend.

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Due to the withdrawal of water by India from the Ganges and Brahmaputra rivers in the upstream, the supply of water to the Baral and Atrai Rivers has reduced sharply. Though the discharge varies at different points and at different times, from 1998 to 2018, the mean annual discharge of Ganges near Rajshahi point is measured at 11195  m3/s and that value at Brahmaputra River near Kurigram point is 17,216 m3/s (Brakenridge & Kettner, 2019). Figures 1.2a, b shows that maximum annual discharge of the Ganges (Padma River) and the Brahmaputra (Jamuna River) was 86,050 and 58,123 m3/s, respectively in 1998. However, the discharge came down to 26,103 and 47,806 m3/s respectively in 2017. Similarly, the mean yearly discharges of Baral and Atrai Rivers at Singra point are 3413  m3/s and 3168  m3/s, respectively, during 1998–2017. During this period, the maximum annual discharge of Baral and Atrai Rivers fluctuates between 4426 m3/s to 1570 m3/s and 3903 m3/s to 1208 m3/s respectively. Overall, the reduced runoff and discharge in the Ganges and Brahmaputra reduces the supply of water at Baral and Atrai Rivers, which in turn conceals the perennial character of the wetland and creates surface and groundwater stress in the region.

7 Wetland Cultivation and Groundwater Depletion As described above, due to the slow-onset event of climate change, the scarcity of groundwater is noticed throughout the Chalan Beel area during the dry season (Fig. 1.3). The scarcity has been severe with widespread extraction of groundwater for agriculture using deep tube wells. Notably, the Bangladesh Agricultural Development Corporation (BADC) has been promoting agriculture around Chalan

36000

-2

-4

30000

-6

24000

-8 18000

-10

12000

-12

2018-2019

2016-2017

2014-2015

2012-2013

2010-2011

2008-2009

2006-2007

2004-2005

-16 2002-2003

-14

0 2000-2001

6000

1998-1999

A rea o f Bo ro Pro d u ctio n (in Hectare)

0

Area of Boro Cultivation in Singra Upazila (in hectare) Ground Water Depth (Jan-May)

Groundwater Depth in Jan-May ( Meter)

Correlation of Boro Production Area & Groundwater Depth (1988-2018) 42000

Fiscal Year

Fig. 1.3  Correlation of Boro Production Area and Groundwater Depth. (Source: Compiled by author from Yearbook of Agricultural Statistics of Bangladesh and BADC)

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Beel since the 1980s, bringing a total 1,25, 000 hectares of land under cultivation through its Flood Control and Drainage (FCD) project (World Bank, 1981). Figure 1.3 shows the correlation between the steady increase of areas of Boro2 cultivating the land and the gradual decrease of groundwater depth in Chalan Beel from January to May. Currently, a total of 914 power pumps, 2205 electric, 22,240 types of diesel and 57 deep tube wells are in operation in Singra Upazila for irrigating 37,913 hectares of land (BBS, 2016). The Department of Agricultural Extension (DAE) also recorded the highest ever 37,099 hectares of land under Boro cultivation in Singra Upazila in 2019, which was 30,660 hectares in 1999. Notably, the coverage of land under Boro cultivation has increased from 60% to 80% during the period 2000–2018. Thus, uncontrolled withdrawal of groundwater on one side and low recharge rate on the other side has significantly contributed to groundwater depletion in the Chalan Beel area. Over the years, the wetland has lost its perennial character in some core places, making bottom part of the wetland suitable for cultivating rice, wheat, and vegetables (Dilu, 2019; Sayeed et al., 2014). With the increase of cultivable land, pumping groundwater has also increased significantly during the dry winter and summer season. Particularly, for Boro rice cultivation, farmers heavily depend on groundwater during the months of March to May. As a result of over-extraction, the groundwater table has already lowered significantly (Sumiya & Khatun, 2016). On account of this, farmers get insufficient groundwater even after installing deep tube wells in the low-lying areas of Chalan Beel.

8 Reduction of Perennial Waterbody of Chalan Beel The original area of Chalan Beel was 1088 km2 in 1909 (Rahman, 2015). Over the period between 1984 and 1990, the floodplain area and fish production reduced by 47% and 75%, respectively (Zaman et al., 2013). To examine the extent of perennial waterbody of the wetland over the period 1989–2018 at Singra Upazila in Natore District, we employed GIS image analyst tools and calculated the geometry of the basin area using unsupervised classification of Landsat images. Calculating the geometry, the extent of perennial waterbody of the wetland in different years is given in Table 1.1. Table 1.1  Extent of perennial waterbody of Chalan Beel in Singra Upazila (1989–2018) Year 1989 2000 2010 2018

Area (km2) 108.07 79.63 74.60 44.62

Percentage of reduction of perennial waterbody (1989–2018) 100.00 26.31 30.97 58.72

Source: Author  Boro is a variety of rice in Bangladesh. Local Boro is cultivated in March–May and high-yielding Boro in May–June. 2

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Fig. 1.4  Classified Landsat images (a) 11-Nov-1989; (b) 17-Nov-2000; (c) 28-Oct-2010; (d) 27-Nov-2018 reveals the changing pattern of Chalan Beel with predominant water coverage map. (Source: Author)

Analyzing the images of 1989, 2000, 2010, and 2018 (Fig. 1.4), it was found that over three decades, the perennial waterbody of Chalan Beel at Singra Upazila has decreased by 63.39 km2 and the reduction is 58.72% from the base year of 1989. Apart from climate change impact, construction of unplanned water regulatory infrastructures such as dams, embankments, sluice gates, and roads on Baral and

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Fig. 1.5  Locations of water flow obstructing infrastructures in Chalan Beel and adjacent areas. (Source: Author)

Atrai Rivers has been preventing the exchange of water supply to and from the wetland (Fig. 1.5). A study by Hossain et al. (2009) revealed that the mean depths of the wetland were 0.59 ± 0.05 m and 3.90 ± 0.08 m during the dry and monsoon seasons, respectively, in 2009. However, the current depth of the wetland ranges from 0.6 to 1 m during monsoon and remains dry from December to April. Less water flow with less velocity along with excessive silt has helped to accelerate the siltation process in the wetland and transformed some core parts into agricultural land. Leaving aside the above fact, Bangladesh Water Development Board (BWDB) has constructed a total 17 sluice gates and a number of embankments, rubber dams, and gravity drainage regulators on Atrai and Baral Rivers during 1982–1984 to promote agriculture through its FCD project (World Bank, 1981). These water regulatory infrastructures on the rivers are the major obstacles of uninterrupted water supply to the wetland. BWDB handed over the maintenance of the infrastructures to community user groups once they were constructed. However, absence of ownership, lack of knowledge about maintaining the systems, and conflict over controlling flood and saving crops and critical infrastructures from inundation became the bone of contention to the community, which turned the community management system into a major failure (World Bank, 1990). The dysfunctionality of the critical structures arising from the failure of community management has augmented the accumulation of sand and silt in the bed of the wetland. Declined rainfall and the increased temperature have added with it as a new phenomenon. It further reduced the runoff and discharge of water to the wetland from adjacent catchment areas and the Baral and Atrai Rivers.

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9 Flooding in Chalan Beel On an average, 22% of Bangladesh is flooded each year (Gupta et al., 2005), damaging crops and properties, destroying agricultural land, homesteads, and displacing communities from home (World Bank, 2015). During monsoon, flood is the major disaster in Chalan Beel, which inundates the surrounding low land (World Bank, 1990). Different hydrological models demonstrate substantial increases in mean peak discharges in the Ganges-Brahmaputra-Meghna (GBM) Rivers under climate change scenario. It is likely to intensify the impact of flooding in the Chalan Beel area leading to more serious disasters (Mirza, 2002). It is also found that the impact of flood and the suffering of the people have already been protracted in the adjacent flood-prone area due to construction of unplanned sluice gates, dams, roads and embankments and failure in maintaining the infrastructures. As such, Fig. 1.6 shows the simulation of major floods, its extent, and inundation area during the period 2000–2012. The image also displays the areas of expanded surface water in Chalan Beel providing the observed history of flooding,

Fig. 1.6  Simulation of major floods that occurred and inundated Chalan Beel during the period  2000–2012. (Source: Dartmouth Flood Observatory, University of Colorado (https:// floodobservatory.colorado.edu/Version2/080E030NSWR.html))

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commencing in the year 2000. The image indicates that communities around Chalan Beel suffer flooding at different degrees every year. Flood causes significant damage to Boro crops. Often, farmers are forced to cut their crops prematurely (bdnews24, 2017; Mridha, 2017). In the Chalan Beel area, flood also destroys houses and displaces people, putting them in more marginal conditions (New Age 2017). Farmers also undergo economic hardship due to slow-onset events of climate change such as unexpected and late rainfall and flood. Generally, small and marginal farmers take loans from NGOs, banks, and local lenders for cropping. Damage of crops due to flood and uncertain rainfall result in farmers failing to repay their loans. They remain overburdened with unpaid loans. Sometimes they even abstain from cultivating in the subsequent year fearing the recurrence of such climatic uncertainty, damage of crops, and financial loss (The Daily Star, 2017). This situation makes them more fragile socially and economically. However, there are too few disaster management initiatives by the government to alleviate the sufferings of the people (Paul & Hossain, 2013).

10 Resilience of Chalan Beel Community to Hydrological and Anthropogenic Hazards 10.1 Indigenous System of Flood Forecasting Early and late flooding often damages the corps and properties in Chalan Beel (The Daily Star, 2017) and there is no early warning system in place to save agricultural crops from flooding (Paul & Hossain, 2013). Nevertheless, increased access to electronic and print media has facilitated local people to access information about floods and rainfall to warn and prepare themselves to protect their crops and properties (Mridha, 2017). Alongside, elderly people also use indigenous, traditional methods of forecasting rainfall and flooding, which is often more accurate. They use existing knowledge that includes monitoring wind and cloud, discharge and velocity of water, muddy smell of water, presence of cultured fish in open water, presence of leaves and other washed-out materials in the river which indicate flooding in the upstream. Sometimes they monitor the water of the river continuously and take precautions and act accordingly. Analyzing all the available information, they take precautionary measures to protect their crops and settlements.

10.2 Normal Flooding The flood in Bangladesh brought by monsoon rains causes widespread damage, yet it delivers prosperity. Floodwaters often brings silt and supports bumper harvest. The life, livelihood, and the economy of the rural people, which constitute about 85% of the total population of Bangladesh, are heavily dependent on rain-fed

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irrigation (Gupta et al., 2005). Silt deposited in agricultural land carried by normal flood water makes it more fertile and augments agriculture (Paul & Routray, 2010). In contrary to drought-like condition, some parts of the wetland inundate regularly during monsoon resulting from spilling of water, localized rainfall, and runoff of water from upstream. During the survey, local people conveyed that the subsequent year following flooding produces good harvest as it brings in silt in large quantities to act as a fertilizer. Besides, moderate rainfall is a blessing to the farmers who cultivate Aman3 and Boro crops as it reduces irrigation cost by reducing the cost of pumping groundwater.

10.3 Regulating Flood Despite criticism about unplanned construction of dams and other infrastructures, a large portion of agricultural land adjacent to Chalan Beel has been protected from flooding by polders (Fig. 1.5) that save crops during monsoon. Besides, controlled flooding, using sluice gates and gravity drainage regulators, construction of secondary drainage system, and construction of channels for gravity irrigation, acts as the main driver of resilience to flooding and protecting agriculture in some parts of the wetland. However, gradual shift and short span of monsoon have emerged as a new challenge that hampers cultivating Aman and Boro crops in some parts. There are a few pockets around the wetland where groundwater table has gone too low to pump water using diesel pumps (The Daily Star, 2012).

10.4 Integrated Approach for Protecting Ecosystem Services Chalan Beel has diverse flora and fauna that have a wide range of ecological, sociocultural, economic, and commercial significance. The flora of the wetland are Hijl, Tamal, Madar, Gab, Jaldumur, Chitki. Shrubs and aquatic vegetation are duckweeds, water hyacinth, lotus, and water lily. Herbs species are varieties of grasses, creepers, such as Thankhuni, Kalmi, Helencha, etc. IUCN reported that a total of 66 fish species are found in the wetland (IUCN Bangladesh, 2015). As water resource is fast decreasing, the number of threatened species of the wetland rose to 64, which is 28.12% of the total threatened fishes of Bangladesh. Among the threatened species, eight are vulnerable, eight are endangered, and two are critically endangered (IUCN Bangladesh, 2015). Some initiatives have been taken by the government and NGOs including the Chalan Beel Fish Development Project to protect the fish  Aman is a variety of rice in Bangladesh. Two types of Aman paddy are grown. One is called broadcast Aman, which is sown in the months of mid-March to April in the low land. Another variety is transplanted Aman, which is planted from late June to August. 3

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species and its biodiversity. The initiatives include excavating pond, dead rivers, small lakes, boropits; establishing fish sanctuaries and fisheries training centers; developing fish landing areas, and beneficiary training. Awareness among resource user groups and pressure from NGOs and civil society also help to preserve the remaining wetland and its biodiversity (The Daily Star, 2016). Monsoon rain and flooding are two important drivers that also help to sustain the hydrological cycle for at least four months in a year in some parts and support the aquatic ecosystem to survive.

10.5 Digging Boropits and Ponds at the Bottom of the Wetland More than 50,000 people, directly and indirectly, are involved with the fishing business in Singra Upazila. Among them, 20,000 are a traditional fishing community. They are at risk of losing their traditional profession due to reduced fish production and low catch of indigenous fish (Jibon, 2009). Notably, total fish production in Chalan Beel in 1982 was 26,990 metric tons, which reduced to 10,885 metric tons in 2012, declining by 45% compared to that of 1982 (Sultana & Islam, 2016). The fish business is also the only means of livelihood for many families. There are 138 villages that have fishing communities living around the wetland whose fishing-­ related occupation, business, and livelihood are at risk due to decreasing perennial waterbody and open fish catch. Meanwhile, the total number of full-time fishermen has fallen in recent days, while the number of part-times has increased due to a decline in open water fish catch (Zaman et al., 2013). Construction of roads and water regulatory infrastructures on rivers and through Chalan Beel prevent fish migration in the upstream and downstream. Climate change characterized by less rainfall also prevents fish from releasing eggs timely. Local people stated that the recurrence of complete drying up of the core part of the wetland is more prevalent since 2000. Not to switch from the traditional fishing profession local people started practicing aquaculture by excavating ponds and boropits at the bottom of the dry wetland. Figure 1.7 reveals how the practice has proliferated since 2000. Expanding aquaculture through digging boropits and ponds brought multiple benefits to the community. It created new job opportunities for the traditional fishing community as well as for day laborers during the lean time. Apart from benefiting the community throughout the year, digging boropits and ponds also plays an important role in preventing degradation of wetland ecology. Particularly, the boropits and ponds act as a sanctuary where endangered indigenous fish species take refuge when the water retreats gradually during summer. It also works as a water reservoir and is often used for irrigation purposes. The practice of integrated fish production, which includes fish culture in the paddy field and boropits, plays a vital role in supporting the traditional occupation of the fishermen community. Notably, annual fish production in the Chalan Beel has increased significantly, reaching 874 metric tons in 2016 from 685 metric tons in

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Fig. 1.7  Digging boropits and ponds in Chalan Beel for fish cultivation. (Source: Author)

Table 1.2  Annual fish production in Chalan Beel 2011–2016 (in metric tons) Fiscal Years 2011– 2012 2012– 2013 2013– 2014 2014– 2015 2015– 2016

Natural (Beel) 575

Nursery (Beel) 110

Total production (Beel) 685

Cultured (floodplain & paddy field) 428

Cultured (boropit) 0

Total production (boropit & paddy field) 428

517

192

709

250

196

446

633

37

670

261

208

469

553

289

842

210

187

397

566

308

874

218

190

408

Source: Compiled from Fisheries Statistical Yearbook of Bangladesh

2011 (Table 1.2). Adaptive fish cultivation also helps to prevent further decline in fish production.

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11 Human Subsystem with Social Resilience: The Role of Chalan Beel in Building Resilience Against Hydrological Hazards Human subsystem with the social resilience to hydrological hazards deals with the impact of hydrological hazards. It also deals with the human response to that particular hazards. The approach of disaster management through capacity building and enhancing knowledge sharing within the affected community is one of the best examples of building resilience from hydrological hazards. As the human system is vast and complex, Meerow et al. (2016) and Ostadtaghizadeh et al. (2015) identified five main domains of the human subsystem for building resilience: social, economic, institutional, physical, and natural. In the study, social resilience in wetlands refers to how the community is able to maintain their livelihood following undesirable shocks such as flooding, scarcity of water, decrease of perennial waterbody, loss of traditional occupation, and agricultural loss. Here resilience includes, for instance, community or individual’s flexibility to make substitutions that lead them to diversify economic activities to offset declining fish production, loss of traditional occupation, and cope with flooding. To assess resilience, we identified their financial and physical assets.

11.1 Access to Physical Assets The soil of Chalan Beel is strongly acidic and composed of heavy clays (BBS, 2016). The village and union roads across the wetland are mostly earthen and few are paved. Boat is the only means of transportation from villages to market places and education centers during monsoon because all the roads go underwater. During monsoon, the waterway plays the most critical role to run daily business. In the study area, 62% of respondents opined that waterway is easy and cost-effective, which increases their connectivity with urban growth centers and nearby markets helping them to step up their businesses. Apart from that, boating is another means of income for day laborers who remain unemployed during the flood. However, an increase in road connectivity and development of a few growth centers has eased transporting agricultural and fisheries resources to the nearby markets in recent days. The opportunity of diversifying economic activities through enhanced penetration to the market helps local people to build their socioeconomic resilience. Aside, the three Unions4 under the study have only seven small markets and only one growth center and most of them remain inundated during monsoon. In these places, the floating market is also a very common practice to continue their daily business.

 Unions are the smallest rural administrative and local government units in Bangladesh.

4

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11.2 Floating Agriculture: An Integrated Adaptation Practice Against Flood Human–flood interaction has two generic options to response: ‘fight’ or ‘adapt’ (Ferdous et al., 2018). To fight and adapt with flood simultaneously in the Chalan Beel, the Government of Bangladesh has implemented some unplanned projects, which include constructing drainage, flood control and groundwater-based irrigation activities (Haque, 1993). However, to deal with flood and inundation, farmers have developed floating agriculture system and transformed the flood hazard into an opportunity. Floating cultivation, raising seedbed and gardening have emerged as the ‘adaptation sensation’ in Chalan Beel—innovated by the NGOs—where flooding and inundation are more prevalent (Ministry of Agriculture, 2012; The Financial Express, 2018; Yadav, 2016). This approach of integrated water resource management is applied to ensure food and livelihood security. It also helps in bringing back the diminishing biodiversity and enhanced ecosystem services (FAO, 2015; Irfanulla et al., 2011). The practice of combined poultry, fishery, and floating agriculture support local communities in earning  additional money. It supports their  economic resilience.

11.3 Floating School: A Means of Adaptation for Building Resilience Against Flood The education system across Bangladesh, particularly in wetland areas, has been greatly affected by climate-change-induced disasters (BANBEIS, 2018). The current literacy rate in Bangladesh is 72.9% (UNESCO, 2019) but it is 56.8% in Singra Upazila, which is much below the national average (BBS, 2017). We found 23.78% literacy rate in the Unions around Chalan Beel, which is much lower compared to the national average or even compared to other Upazilas of the same district. School dropout is high in the villages due to flooding, remoteness, and poverty (Moula et al., 2019). Many of the villages do not have schools or education centers nearby. Connecting roads to the nearby school from the village remains underwater for six months (during monsoon), hampering education. However, the floating school in some areas is an impetus for the pupils to continue education during monsoon. Such schools are supported and run by charities and NGOs (Ahmed et al., 2016). In the floating school system, boats are fitted with a classroom and playing equipment for child education. The floating and mobile school picks students from their villages to help them in attending the classroom, curtailing dropout rate, and lessening detachment period from school. Some NGOs and charities have also come up with new ideas such as introducing solar-powered boats to provide the electricity to enhance the quality of education (ReliefWeb, 2008). Floating bamboo home has also emerged as another coping strategy against flooding (The Daily Star, 2018).

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11.4 Accessing Wetlands Ecosystem Services: A Means of Economic Resilience Aquatic ecosystem services are good examples that attempt to bridge social and hydrological subsystems to build resilience and cope with disasters (Biggs et al., 2015). Aquatic ecosystem services, for instance, the supply of fish, plants, vegetables, etc., are important for human life and livelihood. But these services are subject to change, and need to be sustainable and resilient (Brauman et al., 2007). The floodplains of Bangladesh consisting of hundreds of rivers, channels, and wetlands are home to about 260 fish species and numerous migratory birds. They are an important source of income and nutrition for millions of rural households (Rahman, 1995). A study in 2005 suggested that 80% of rural people of Bangladesh depend on wetlands for fish and other aquatic resources (Halder & Thompson, 2006). To examine the degree to which households living around the Chalan Beel depend on the wetland ecosystem services for their livelihood, we employed the Ecosystem Services (ES) framework. To identify wetland services, we asked people about what supports and services they get from the wetland and analyzed the answers using resilience indicators. The identified ecosystem services from the wetland that the local people tap to sustain their livelihood are shown in Figs. 1.8 and 1.9.

Stapl Aqua Anim e tic al food food food

Fuel & Fodder

Use of water

Source of Li vestoc Handicr k aft farming Means of Constructio material and s rearing Business n materials

Contribution of Provisioning Services (%) Aquaculture and fishing Dry fish Boating Natural levee for rearing livestock Grazing Poultry (Duck farming) Thatching Netting Cane Mat and Mat Vetiver grass Sand & Silt Paddy straw Herbs & shrubs Cropping (Paddy, Vegetables) Household work Transportation (Water way) Irrigation Paddy straw Jungle Jute and Reed Herbs & shrubs Ipomoea carnea Sesvania tree Collect cattle dung Fodder for livestock & poultry Wild bird & fish Fish Waterfowls Water lilies Vegetables Rice

47 1

5 70 71 57 6 15

9 4 28 27 16

43 34 62

53 57 9

13 1 3 16 100

3 94 9

16 29 53

0

10

20

30

40

50

60

70

80

90

Fig. 1.8  Provisioning services that support building resilience. (Source: Field survey 2018)

100

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Supporting (Source of fertilizer)

Cult ura l (Means of Regulating (M oderat ing Cli mat e educati Change Impact) on)

Contribution of Regulating and Supporting Services (%) Floating/boat school

57

Drought control

62

Water purification

15

Flood control

70

Water hyacinth and Sesvania

13

Silt

18

Herbs & shrubs

4

Aquatic plant

5

0

10

20

30

40

50

60

70

80

Fig. 1.9  Regulating and supporting services for building resilience. (Source: Field survey 2018)

11.5 Provisioning Services from the Wetland In the study area, a large number of households live below the poverty line. Based on land possession, 66% of households are landless or marginal farmers. Day laboring, fishing, and subsistence agricultural activities, migrating to cities and pulling rickshaws are their major activities for securing daily income. For households living below the poverty line, the wetlands are an important source of income. Families under the category of landless and marginal earn BDT1233 and BDT1110 per month, respectively, from the wetland ecosystems. The contribution of ecosystem services to their monthly income is 30.67% and 23.94% (Table 1.3). The families extract an average of 11 types of ecosystem services from the wetland. This includes catching fish and wild birds, raising duckling and plucking vegetables and water chestnuts for food and collecting paddy straws, jungle juts, herbs and shrubs for fuel, fodder, crafting and netting (Fig. 1.8). Apart from that, they use natural levee for rearing livestock, grazing during the flood. The vast water body also creates the opportunity of earning through fishing and boating. It is noteworthy that the landless households are fully dependent on the wetland ecosystem services particularly for fuel and fodder and also because they possess no land of their own for cultivating paddy, which is the main source of paddy straw for fuel and fodder. Besides, Beel Kanda5 is also a source of abandoned herbs, shrubs, and trees, which are used as

 Highland on the haors, used for cattle grazing, cropping, or rice threshing. It is also known as homestead land near the waterbody. 5

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Table 1.3  Dependency on Wetland Ecosystem Services Average monthly Average income monthly form Land HH wetland Possession Percentage income ES (Acre) Occupation of HH (BDT) (BDT)a Landless Day labor 42 4051 1233 (< 0.50) fishing agriculture Marginal Agriculture 24 4700 1110 (0.51– Fishing 1.00) Small business Day labor Small Agriculture 23 6722 791 (1.01– Small 3.00) business Fishing Medium Agriculture 11 9966 611 (> 3.00)

% of total HH income from Wetland ES 30.67

Dependency on wetland Number of services ecosystem (based on # services of ES taken form services wetland taken) 11 High

23.94

11

High

12.52

8

Medium

6.41

8

Medium

Source: Field survey (2018) a Economic evaluation is done based on respondent’s estimation, if they buy or sell the services in the market that they collect from the wetland free of cost

fuel. Generally, female members of the household collect herbs and shrubs from the Beel Kanda for cooking. However, those who possess more than one acre are less dependent on the provisioning services of the wetland. This group collects fewer items from wetland ecosystems. Their earnings from the wetland are low compared to the landless and marginal groups. Nonetheless, they tap significant items of ecosystem services in their daily life, which includes fishing and duckling in the wetland, the use of wetland water for irrigation, and use of the natural levee for grazing.

11.6 Duck Farming Duck farming is gaining popularity among the villagers living around Chalan Beel. Hundreds of small farmers and marginal households receive financial benefits from duck rearing in open water bodies (Seraj, 2018; The Daily Observer, 2018). Duck rearing in the wetland is also profitable as ducks take natural food from the open waterbody and farmers do not need to buy extra food from the market for raising them. Female members of the households engage in rearing ducks

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along with male members. Our survey in Dahiya, Satpukuria, and Italy Union identified 57% of households, who are mostly poor and landless, that uses natural levee and wetland for rearing ducks. A large number of eggs are produced every day that has demand in the market. A market system and duck value chain has already developed in the area. Nowadays, a large number of landless households raise ducks throughout the year and some of the households are quite well-off. However, the respondent said that monsoon is the most favorable and profitable season for raising ducks. According to the farmers, raising ducks and fishing followed by agriculture is the main source of their income, which helps to build resilience during monsoon.

11.7 Changing Occupation to Diversify the Means of Livelihood The wetland remains submerged for six months every year. Subsistence fishing is prominent in most of the villagers in the Chalan Beel area. Though most of the people in the area engage in fishing during flooding and monsoon season, it is difficult to identify professional, seasonal and parttime fishermen as many households abstain from being recognized as fishermen for fear of losing their social reputation. The study found that 34% of the respondents’ current occupation is agriculture, while 38% are day laborers and 13% are fishermen. Among farmers, 26% are involved in fishing during monsoon, particularly when their agricultural land gets flooded; 53% of respondents changed their traditional occupation while most of the migration occurred from fishing to day-labor because fish catch, fishing area, and water resources have depleted rapidly in the last few years. Some respondents have changed their occupation from agriculture to business and few of them have become day laborers in the agricultural sector. The change in occupation is shown in a matrix (Table  1.4). Notably, those who have changed their occupations are mostly landless and possess less than 0.45 acres of land.

Table 1.4  Change of occupation Pervious occupation Agriculture Fishing Business Day labor Source: Field survey

Present occupation Agriculture Fishing 0 1 3 0 1 1 0 1

Business 5 2 0 0

Day labor 7 21 0 0

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11.8 Subsistence Activities Based on Wetland Ecosystem Services To cope with the occupational uncertainty and unemployment due to declining fish catch, community people try to explore and engage in other professions alongside their regular occupation. Around 46% of households said that the wetland supports them in fish drying, day laboring in aquaculture and paddy fields as subsistence activities that help them secure their daily livelihood. However, 12% of the total respondents reported that they often migrate temporarily to nearby cities for pulling rickshaws or move to the capital city for seeking jobs in garment factories, etc. However, many of them return to their villages during boro cultivation and harvesting time. For some extra income, household members including children, girls and women also engage in handicraft-related activities such as knitting fish-nets and weaving mats to sell in the local market.

11.9 Controlling Drought and Recharging Groundwater Indiscriminate pumping of groundwater has substantially modified aquifers in Chalan Beel areas (Shamsudduha et  al., 2009; Shamsudduha & Uddin, 2007). Drought-like condition triggered by low rainfall combining with the gradual increase of temperature has laid extra stress on groundwater (Jahan et al., 2010). To address the challenges, the approach of integrated groundwater and surface water management is used in a very limited range in Chalan Beel areas (Paul & Hossain, 2013). Apart from that, the wetland itself plays a crucial role in controlling floods by acting as reservoirs. It retains water from the rivers and catchment areas that has the potential to cause flooding within a very short period in adjacent croplands. The wetland helps in regulating flood by retaining torrential rainwater and modifies drought-like conditions through recharging groundwater table. Farmers reported that in the subsequent year of flooding, the groundwater table rises, which reduces the cost of pumping water for irrigation. However, farmers are concerned about the reduction of water-carrying capacity of the wetland due to siltation and recent occurrences of flooding from localized rainfall. They fear that further siltation will inundate adjacent low-lying areas more quickly and it will shorten their preparation time to save crops.

11.10 Institutional Support As degradation continues, environmentalist and civil society members are concered  about  saving the fragile biodiversity and vulnerable fishing community of Chalan Beel. Local people demand the demolition of all unplanned embankments

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and sluice gates around the wetland (The Daily Star, 2016; Dhaka Tribune, 2014). Maximum exploitation of fish, decrease of fish migration due to construction of dams, sluice gates and roads inside Chalan Beel, excessive use of surface water for irrigation, and destruction of fish breeding places due to use of pesticides in crop field around the wetland are the major threats to extinction of endangered fish species (Halder & Thompson, 2006; Rahman et al., 2010; Zaman et al., 2013). Notably, fish consumption of Bangladesh fell by 11%, and 40% of fish species were classified as species threatened with extinction between 1995 and 2000. However, some community-based initiatives were undertaken in collaboration with donors, NGOs, and the Government of Bangladesh to preserve the biodiversity of the wetland (Halder & Thompson, 2006). The government also introduced policies for ecosystem-based conservation, community-based adaptation, raising awareness among stakeholders, and banned using net gears indiscriminately. These initiatives have played a crucial role to continue the trade-off of benefits between community and water subsystems. Particularly, the approach of co-management of aquatic ecosystem involving community has facilitated the advancement of knowledge and practice such as digging ponds and boropits. In 2011, a review on aquaculture and fish consumption identified that during 2005–2010, fish consumption in rural areas increased by 4.8% (Belton et al., 2011). The co-management approach has also facilitated to prevent loss of indigenous species as well as the aquatic ecosystem.

12 Socio-hydrological System with Socio-hydrological Resilience in a Coupled System The socio-hydrological system with socio-hydrological resilience is a coupled system which is associated with water and society in governance arrangements (Mao et al., 2017; Sivakumar, 2012). Socio-hydrological resilience relates to people and nature as an interdependent system. The interdependent linkage often relies upon policies to access common property resources, regulating systems of common properties and sustainability of socio-hydrological systems, etc. (Dessalegn, 2016).

12.1 Open Access to Wetlands In Bangladesh, local resource users enjoy the customary access to Khas land6 or common property resources such as a wetland. A wetland is considered as nonagricultural Khas land to which the traditional fishing community enjoys open access if it is not formally leased out. Besides, private land adjacent to flood plain becomes  Khas land is government-owned fallow land. It is owned by the government and available for allocation according to government priorities. In a nutshell, nobody has property rights over it. 6

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open access resources for fishing while it is inundated. Historically, the common property resources such as the Chalan Beel provide very important provisioning services to the traditional fishing communities and poor households living around it. Catching fish from the wetland is the lifeline of many traditional fishermen in the study area. Our study identified that 94% of households are dependent on the wetland for fish for their consumption, while 47% of households do fish-related business. However, the government policy of leasing out waterbodies, which is known as “Jalmahal7 Management Policy–2009,” has curtailed the right of traditional fishermen to catch fish in water bodies. It does not effectively safeguard the interest of the actual fishermen. The policy includes local lawmakers and Upazila Chairman, who are political representatives, as advisers on the Jalmahal Management Committee. The committee is the ultimate decision-making body to lease out wetlands. The inclusion of a political person in the committee often politicizes the system of leasing out. As a result, conflict arises between the small fishing community and Fishermen Cooperatives Societies (FCS) supported by vested groups. Depending on the size, the wetlands are administered by a number of government entities who control the access to the waterbody. Critical aspects of the present management policy and administration are presented in Table 1.5. Table 1.5  Management aspects of wetlands Area of water body (acres) 20

Access Access determined by duration Common Indefinite property resource principle

Administered by Local government/ union Parishad (the smallest rural administrative and local government units in Bangladesh) (no specific policy in place) Ministry of Youth and Sports

Access allowed to Poor community around the wetland

Unemployed youth from the localities around the Beel

Tendering process

Waterbody/Jalmahal management committee headed by district deputy commissioner (DC) On behalf of Ministry of Land

Enlisted local fishermen cooperative societies (FCS) that must include two members from FCS

Tendering process

3–5 year for perennial and seasonal bodies For 3 years

Tender process or negotiation

Source: Compiled by author  The open water bodies owned by the Government are commonly known as Jalmahal. These are usually leased out at the beginning of a Bangla year and the money received from the leasing out is deposited into government fund as advance revenue. 7

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12.2 Access to Khas Land (Government-Owned Fallow Land) Under the Land Reform Ordinance in 1984, farmers obtain legal permission to use the wetland/Beel land for agriculture. This is another means of survival of the poor families in Chalan Beel since a large number of them are landless or marginal farmers. Generally, a farmer who has been using the land for 10–15 years goes to the local government office to seek permission for gaining a 99-year lease. As it is a Khas land, landless farmers get priority in securing the lease. However, some farmers inherit the Beel land from their parents and establish control over it through obtaining legal permission for agriculture. As the wetland is drying up gradually, agriculture has emerged as a dominant practice. Three types of farmers are identified in the Chalan Beel area: large farmers who have agricultural land of their own; marginal or small farmers who lease land from others; and landless farmers who use the Beel Kanda. As identified in the survey, 42% of households are landless and 24% are marginal and possessing less than one acre of land including their settlements. Notably, 61% of respondents said that they are mostly dependent on Beel Kanda and lease lands from rich farmers for agriculture to produce rice. Those who are landless and marginal reportedly work as day labor in croplands of the rich farmers. To them, Beel Kanda is a very important means of livelihood. They often use the Beel Kanda to grow vegetables, crops, and grains for their consumption. Apart from that, sometimes they collect wild food and vegetables from the wetland and sell the excess food in nearby markets. Therefore, Khas land plays a very important role for the landless to secure their food and livelihood all around the year. Farmers, possessing agricultural land, often use the surface water of the wetland for irrigation to reduce the cost of pumping groundwater. Flooding also deposits silt in the wetland, which acts like fertilizer. Local people also use aquatic plants, herbs, shrubs, and water hyacinth of the wetland to prepare the beds for floating agriculture and gardening. Particularly, during monsoon, water hyacinth is gathered and compacted into rafts. Herbs and shrubs such as lettuce, duckweed, and Salvinia are used to create layers for beds while the top layer provides the compost. Thus different services from the Khas land support toward building economic resilience of the community.

13 Conclusions A strong linkage between the social and hydrological systems is found in the Chalan Beel. In the area, a large number of families depend on fishing for their livelihood, which is their primary occupation and the impact of slow-onset events of climate change such as shortage of water and extinction of indigenous fish is making their daily life more difficult. On the other hand, most of the vulnerable households have a heavy dependence on ecosystem services, which is also decreasing due to climate change impact. However, a comprehensive approach combining disaster and

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climate risk reduction from the government is absent in the area except for the construction of polders, dams, that is, water regulatory infrastructure. Though government support is limited, communities are adapting and adopting new systems with the changing hydrological condition, which includes focusing more proactively on risk reduction and preparedness activities such as crop and livestock production that are the main drivers of securing livelihood. Despite the critical interface of climate change and disasters such as temperature rise, uncertainty of rainfall, flood, human interference on the wetland, scarcity of aquatic resources, communities are coping with the situation through diversifying occupations, temporary migration, ecosystem services, open access to wetland, aquaculture, and integrated practice of agriculture. To cope with flood and climate-­ change-­driven disasters, local people have developed and adopted new systems such as floating agriculture and integrated and adaptive fish and crop cultivation. Adaptation practice such as running floating schools, markets, and duck farming in the open water helps the community to strengthen households’ ability to respond and prepare them better for upcoming disasters. Despite the occurrence of frequent disasters, much of the localities have scarce access to climate-change-related information. In such areas, they apply indigenous knowledge to forecast flood alongside the information they receive from electronic and print media. To address immediate needs, community members are increasingly focusing on strengthening occupational engagement such as diversifying their occupations. Particularly, family members of the surveyed households often migrate from their localities in search of a job or migrate from their traditional occupations to other occupations. A year-round activity calendar of the household members illustrates the practices of the families to cope with the disasters and changing social and hierological landscape (Table 1.6). Analyzing year-round activity and access to ecosystem services, it is found that the most important nexus of water and human system in the Chalan Beel area lies in ensuring food security and livelihood of poor families. Especially, the traditional fishermen community remains most vulnerable during January to June as the wetland dries out. For social and economic risk management, such vulnerable groups including those who do not have any land often migrate temporarily to the nearest cities and work as day labor or rickshaw puller during the disaster. Some households take up subsistence activities such as duck farming and livestock rearing in the floodwater. Besides, ecosystem services and access to the common property resources is the most sustainable support that community people avail of throughout the year. Overall, Fig. 1.10 outlines the elements, drivers, and the actors that support the resilience of the community from various hazards and disasters and help in building resilience. Finally, local people’s participation and their way of interaction with the wetland are the most important factors that reshape the human–water system. During their interaction in the coupled system, the government policy determines the way of interaction to build the resilience of both systems. Despite efforts for ensuring sustainable interplay, water resource is becoming more vulnerable due to human activities. Therefore, integrated water resource management needs to be realized as a guiding principle. The approach recognizes water as an economic good and

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Table 1.6  Year-round activity of the community people in Chalan Beel Major Activity Responsibility Jan Feb Mar Cultivation Family head Paddy culture time Day labor (plantation (agriculture) & Son Crop harvesting) cultivation Day labor (agriculture) Wife/daughter Day labor (agriculture) Homestead gardening Vegetable & crop cultivation Fishing Family head time Son

Wife/daughter

Lean time

Family head

Son

Wife/daughter

Apr May Jun Jul Aug Sept Oct Nov Dec Harvesting Rice Day labor

Day labor (agriculture)

Netting, fishing Aquaculture/ boating Netting, fishing Boating/ aquaculture Homestead gardening, duckling Firewood & vegetable collection Temporary migration Day labor, aquaculture Temporary migration Day labor, aquaculture, livestock rearing Work to others house Duckling, fish drying Firewood & vegetable collection

recommends the participation of users, planners, and policymakers. Despite some progress in flood management and sharing knowledge and best practices on disaster management, livelihood vulnerability of different fragile groups has been ignored in Chalan Beel. Considering the current state of socio-hydrological criticality, the government needs to be more enthusiastic about long-term, nonstructural management including the ecosystem-based approach to build an effective system for coupled socio-hydrological resilience.

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Open Access to Wetland

Floating School Floating Market Floating Gardening

Integrated Adaptation

Open Access to Land

Common Property Rights

Resilience

Subsistence Activities

Land Use Change Ecosystem Services

Occupational Diversity Day Labor Rickshaw Pulling

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Agriculture

Fishing

Livestock Rearing

Poultry Farming

Fig. 1.10  Elements of building socio-hydrological resilience in the Chalan Beel. (Source: Author)

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The Financial Express. (2018). Floating seedbed technique takes root in Chalan Beel. The Financial Express. 9 September https://today.thefinancialexpress.com.bd/country/floating-­ seedbed-­technique-­takes-­root-­in-­chalan-­beel-­1536411252. Accessed 20 April 2019 UNESCO. (2019). Bangladesh. [Online] Available at: http://uis.unesco.org/country/BD. Accessed 20 April 2019. Wesselink, A., Kooy, M., & Warner, J. (2017). Socio-hydrology and hydrosocial analysis: Toward dialogues across disciplines. WIREs Water, 4(2), e1196. World Bank. (1981). Report and recommendation of the President of the International Development Association to the Executive Directors on a proposed credit to the People’s Republic of Bangladesh for asecond Drainage and Flood Control Project (Report no. P-3127-BD). World Bank. http://documents1.worldbank.org/curated/en/736091468209944242/pdf/multi-­page. pdf. Accessed 19 April 2019. World Bank. (1985). Staff appraisal report Bangladesh: Third flood control and draining. World Bank. http://documents1.worldbank.org/curated/en/379371468209375285/pdf/multi-­page. pdf. Accessed 19 April 2019. World Bank. (1990). Flood control in Bangladesh: A plan of action. World Bank. http://documents1.worldbank.org/curated/en/521601468743379332/pdf/WTP119-­REPLACEMENT-­ PUBLIC-­Flood-­Control-­in-­Bangladesh-­a-­plan-­for-­action.pdf. Accessed 19 April 2019. World Bank. (2015). Consolidation and analysis of information on water resources management in Bangladesh. s.l.: World Bank. https://www.2030wrg.org/wp-­content/ uploads/2016/02/2030-­WRG-­Bangladesh-­Revised-­Final-­Report-­PwC_Nov15_newcover. pdf. Accessed 19 April 2019. Yadav, A. (2016). Resort to heritage. [Online] Available at: https://www.downtoearth.org.in/news/ agriculture/resort-­to-­heritage-­53346. Accessed 4 May 2019 Zaman, M. A., Jewel, M. A. S., Hossain, M. Y., Provhat, S. J., Jasmine, S., Ali, M. M., & Hossain, M.  I. (2013). Impact assessment of sluice gate on fishing activity, fisheries diversity, riverine habitability and livelihood stability of the fishermen in the Northwestern Bangladesh. International Journal of Research in Applied, Natural and Social Sciences (IJRANSS), 1(2), 99–110.

Chapter 2

Indigenous Approaches to Disaster Risk Reduction, Community Sustainability, and Climate Change Resilience Christine Kenney, Suzanne Phibbs, Litea Meo-Sewabu, Shaun Awatere, Marie McCarthy, Lucy Kaiser, Garth Harmsworth, Nichola Harcourt, Lara Taylor, Nicki Douglas, and Lani Kereopa

Abstract  Indigenous forms of science and practices pertaining to disaster risk reduction and climate resilience are increasingly recognized within the disaster resilience sector and drawn on to inform international policy frameworks (reference SFDRR, 2015), government strategies (DPMC, 2019), and the practices of local authorities. The 2015 Sendai Framework for Disaster Risk Reduction specifically highlights the importance of adopting diverse and socially inclusive approaches toward managing emergency contexts, such as harnessing local community risk mitigation practices that are informed by traditional knowledges. Yet, perusal of the research and gray literature, suggests that conceptualizations of indigenous disaster risk reduction concepts and approaches to mitigating the impacts of climate change are primarily developed by policy specialists and researchers using an ‘etic’ gaze informed by the Western European science paradigm. The absence or ‘othering’ of ‘emic’ perspectives regarding the application of Indigenous knowledges and C. Kenney (*) School of Psychology, Massey University, Palmerston North, New Zealand e-mail: [email protected] S. Phibbs Massey University, Palmerston North, New Zealand L. Meo-Sewabu University of Sydney, Sydney, Australia S. Awatere · G. Harmsworth · N. Harcourt · L. Taylor Manaaki Whenua Landcare, Lincoln, New Zealand M. McCarthy Ministry for the Environment, Wellington, New Zealand L. Kaiser GNS Science and Joint Centre for Disaster Research, Massey University, Wellington, New Zealand N. Douglas · L. Kereopa Te Arawa Lakes Trust, Rotorua, New Zealand © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_2

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p­ ractices to reduce disaster risks and address climate change concerns may undermine nations’ abilities to create disaster resilient communities that will endure in the longer term. Epistemological tensions also exist between Western European science and Indigenous understandings of traditional DRR approaches, which may give rise to the misinterpretation of traditional knowledges and practices. Due to ongoing tensions associated with knowledge appropriation, there is also a growing incidence of Indigenous collectives instigating legal challenges in relation to data sovereignty issues. This chapter is solely coauthored by Māori, and Pacifica researchers, and contributes to addressing the literature gap by presenting Indigenous perspectives on disaster risk reduction, climate change adaptation, environmental resilience, and sustainable development. Keywords  Indigenous · Disaster risk reduction · Climate change · Community resilience

1 Introduction There is growing international recognition of the need to draw on Indigenous knowledges and practices pertaining to disaster risk reduction in order to strengthen the disaster management policies and practices of nations (Kelman et al., 2012). The current impacts, and predicted global consequences of climate change have equally contributed to an awareness that community-led emergency management and recovery initiatives are relevant to integrated disaster risk reduction research and governance (Johnson et al., 2014). Further to the ratification of the Sendai Framework for Disaster Risk Reduction in 2015, the United Nations has recommended that inclusive approaches, which promote the engagement of culturally diverse, indigenous collectives in disaster management planning and implementation, be widely introduced (UNISDR, 2015). To date, this recommendation has largely been implemented in policy and practices in an inconsistent manner (Howitt et al., 2012). The lack of knowledge integration may be a consequence of the absence of a substantial body of research literature that reflects emic perspectives on Indigenous approaches to disaster risk reduction and climate change adaptation, which could usefully inform disaster risk reduction policy development. That said, research literature by indigenous scholars (Awatere, 2017a, b, Kenney & Solomon, 2014, King, 2007, Saunders, 2017, Whyte, 2018), which presents insiders’ perspectives on and highlights why Indigenous knowledges and practices are useful for ensuring effective disaster risk reduction and climate change adaptation, is emerging. This chapter contributes to that body of literature by drawing attention to research projects designed by Indigenous researchers in response to concerns

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raised by Indigenous collectives, and implemented in accordance with Indigenous values. In the following sections of the chapter, case studies are used to illustrate Indigenous approaches to addressing disaster risks and facilitating community resilience, to natural hazard events and climate change. Indigenous challenges pertaining to disaster risk reduction are also touched upon. Key among these are challenges associated with inclusivity, such as local government recognition of Indigenous perspectives and stakeholders in DRR planning, aspirations associated with Indigenous science and workforce capability development, and Indigenous knowledge (data) sovereignty. The chapter discussion is framed using a macro to micro approach. Indigenous viewpoints and concerns pertaining to disaster risk reduction and climate change adaptation in the Pacific region are outlined in the case study by Dr. Litea Meo-Sewabu. An argument is advanced that current approaches to donor aid provision in the region have served to undermine local social and economic resilience, through weakening reciprocal support relationships within and between Pacific communities. In contrast, a case study on a Māori-led approach to disaster risk assessment and evaluation of community resilience that highlights the relevance of Māori traditional disaster risk reduction knowledge and practices to contemporary disaster management in New Zealand is articulated by researchers from the New Zealand Crown Agency, Manaaki Whenua (Landcare). Further to this research, Te Arawa Lake’s District Trust and Marie McCarthy representing Scion, the Crown Institute for Forestry Research present a case study that outlines a tribal approach to developing a climate change risk mitigation and adaptation strategy for implementation at the regional level. The final case study outlines the role of marae (Māori meeting centres) as cultural assets that may be drawn on to address broader community needs during disasters and addresses potential enablers and challenges to the mobilization of such resources in New Zealand. More broadly, this case study draws attention to the significance of context specific cultural technologies and ways they may be operationalized to facilitate the well-being and resilience of wider communities in the context of natural hazard and climate change events (Eslamian & Eslamian, 2021). Collectively, these projects illustrate Indigenous community resilience, climate change adaptation as well as capabilities in research and disaster risk reduction policy and practice within the Oceania region. Recommendations and research findings resulting from the case studies will be relevant to other indigenous peoples, developing states, and nations with communitarian approaches to disaster risk reduction. However, unfettered modernization may disrupt the application of indigenous disaster risk reduction knowledges and practices that have traditionally fostered disaster resilience and mitigated the local impacts of natural hazard events. As an exemplar of the ways political practices may influence national disaster risk reduction capabilities, a case study that critically examines the impacts of donor aid targeted at reducing disaster risk in Fiji is introduced in the next section.

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2 Social Capital, Connectedness, and Climate Change in Lau, Fiji 2.1 Introduction Disasters are “increasing in frequency, scale, cost and severity” (Matthewman, 2016 p. 4). Pacific Island Nations have distinctive characteristics including isolation, a limited economic base, vulnerability to global financial crises and environmental impacts from climate change, as well as disasters (United Nations, 2014a). Climate change will impact the economy, “health, coastal infrastructure, water resources, agriculture, forestry, and fisheries” of Pacific Island Nations (World Bank, 2003 p. ix). Sea level rise, combined with increasing cyclone intensity and storm surge events, is expected to result in shoreline erosion as well as land inundation threatening coast infrastructure. Droughts, saltwater intrusion into existing farmland, crop failure, loss of coral reefs and coastal fisheries, as well as the spread of tropical diseases are also predicted impacts of climate change (World Bank, 2003). Demographic shifts within the Pacific point to growing health inequalities (Matheson et al., 2017) as well as climate-induced population movement (World Bank, 2003). Loss of life and livelihoods, economic damages and impacts to GDP from destructive storms are expected to increase. Tropical Cyclone Winston, for example, which made landfall in Fiji in February of 2016 left 44 dead and caused over A$2.5 billion in damage (Armbruster, 2017). Addressing vulnerability through adaptation policies that increase the resilience of Small Island Developing States (SIDS) is a key climate change mitigation strategy (United Nations Climate Change, 2017; World Bank, 2003). This case study draws upon original research to consider the way in which modernization, as well as donor aid, has eroded traditional house and boat building skills and therefore forms of reciprocal exchange in a Fijian village setting. It is argued that this loss of connectedness within and between villages creates vulnerabilities in times of disaster. Fijian initiatives that draw upon cultural strengths and enhance traditional ways of working together are considered as alternative climate change adaption and disaster mitigation strategies.

2.2 Research Design Qualitative focus group research, involving 15 Fijian women, was conducted in the village setting of Nayau, in the Lau group of islands, which are located in the eastern region of Fiji. During the formal sevusevu (welcoming ceremony), male elders explained the purpose of the study to the villagers and collective consent given to enter the village to conduct the research. Following the welcome, senior village women collectively selected participants for the study. The women ensured that the three village clans and their sub-clans were equally represented in the research. Following selection, participants were again provided information about the

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research and individual consent to participate in the research obtained. The focus group research was supplemented by field notes that were based upon observations of village life as well as participation in the day-to-day life of the village. Villagers were aware of the ethnographic nature of the research and ensured that the researcher was included in day-to-day activities within the village. Focus group interviews were manually transcribed and both deductive and inductive analyses were used to organize the data into themes. The themes of cultural displacement and vulnerability that form the basis of this case study were one of the topics that emerged out of the village research. The research was approved by the Massey University Human Ethics Committee as well as the Ministry of Indigenous Affairs, Provincial Development and Multi-Ethnic Affairs in Fiji.

2.3 The International Policy Context and Local Effects In 2015, member states of the United Nations ratified the Sendai Framework for Disaster Risk Reduction (UNISDR, 2015), The Sustainable Development Goals and the Paris Agreement on Climate Change. Taken together these three agreements set out a global strategy for addressing disaster risk, enhancing resilience and encouraging sustainable development. The outcome document from the Third International Conference on Small Islands Developing States (SIDS) held in Samoa in 2014 called for the eradication of poverty, as well as strategies to ensure sustainable development, build resilience and improve quality of life. Paragraph 11 of the S.A.M.O.A pathway recognizes that: [S]ea level rise and other adverse impacts of climate change continue to pose a significant risk to small island developing States and their efforts to achieve sustainable development and, for many, represent the gravest of threats to their survival and viability. (United Nations, 2014b)

Sustainable development is presented as a key platform for building resilience among Pacific nations including Fiji (United Nations, 2014a; World Bank, 2003). However, sustainable development needs to be cognizant of cultural context as well as potential unintended consequences of action (Meo-Sewabu, 2016). Previous initiatives, originally aimed at improving village autonomy, have increased reliance on external resources (Movono et al., 2018), as the following examples related to housing and inter-island transport illustrate. The first example considers the introduction of Western building techniques in Nayau village that were associated with the erosion of traditional building practices. In 1975, a cyclone destroyed the village of Nayau. Following the cyclone, the village was relocated and rebuilt by the State. Cyclone-proof houses were allocated to each tokatoka (family unit). A village elder commented that the cyclone-proof houses had displaced the village matai (carpenters), making traditional building techniques redundant, which impacted the village social structure (Meo-Sewabu & Walsh-Tapiata, 2012, p.  311). In this case, a disaster risk reduction initiative

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“resulted in a loss of identity, bodies of knowledge and skills that could have been harnessed if disaster risk reduction policies had promoted community participation and reflected Indigenous goals of wellbeing” (Meo-Sewabu, 2015 p. 260). The second example focuses upon traditional canoe building, a skill that has been lost following the introduction of motor boats. Canoes are cost-effective as they do not require fuel—a commodity that few villagers can afford. Fuel is vulnerable to supply-line disruption in the aftermath of a disaster, while the cost of gasoline has exacerbated economic dependency creating a new category of impoverished people (Madraiwiwi, 2008) within Fijian village communities. Loss of traditional carpentry and canoe-building techniques has impacted clan identity, disrupted the intergenerational transmission of customary building knowledge, reduced opportunities for villages to work together impacting on social cohesion, and changed the way that canoe- and house-building clans contribute to the village social structure (Meo-Sewabu, 2015). These changes are illustrated in the following field notes: Elders and village members expressed how they used to have so many Island interactions using their canoes. These island interactions included exchanging materials, trading and making connections throughout their group of Islands. During my visit to the village there was only one remaining canoe … [that] was not in use because no one could repair it. Interestingly in both examples the village elder was the only one who identified the loss in traditional roles. (Meo-Sewabu & Walsh-Tapiata, 2012, p. 311)

The introduction of motorized inter-island transport did not take into account cultural heritage loss as well as disruption to formal social systems, as well an informal forms of exchange, within and between Fijian village communities resulting in greater dependency on “the market and formal systems of the state” (Meo-Sewabu, 2015 p. 261). Community attributes that are connected to post-disaster resilience include: place attachment, social connectedness, community participation, reciprocity, local knowledge and expertise, an effective leadership structure, the ability to mobilize human resources, a history of working together, and robust external linkages that are able to be actioned to access resources (Kenney & Phibbs, 2014). Disruption of customary forms of exchange, such as labor or traditional goods for resources such as food, expertise or raw materials, weakens bonds within and between communities, creating social and economic vulnerabilities to the impacts of climate change. The deskilling of village men through unfettered modernization has significant negative social impacts including unemployment as well as substance and domestic abuse (Meo-Sewabu, 2015) suggesting that disaster risk reduction policies need to reflect Indigenous goals for well-being including fostering community participation.

2.4 Sustainability and Mitigation Loss of Indigenous culture is a threat to well-being, while a strong cultural identity is protective (Durie, 2001). In Fiji, the Ministry of Itaukei has developed initiatives to facilitate Indigenous resistance to cultural displacement and loss of cultural

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heritage including cultural mapping, community development, indigenous ethics, and intellectual property rights (Meo-Sewabu, 2015). At the local level, villages have been working to reduce dependence upon external agencies through collective action to ensure sustainability through maintaining extended family links as a basis to building sustainable livelihoods. The concept of solesolevaki or working together for the common good are forms of collective action that are being realized by communities, thus contributing to well-being (Meo-Sewabu, 2015; Movono & Becken, 2018). This can be seen as a form of passive resistance to the models of development and dependence brought in by donor agencies. In a study of Indigenous businesses on customary land (Vunibola, 2018), for example, all businesses that were deemed successful had managed to put aside money from their profits to cater for Vanua or cultural obligations and duties for villagers, Church obligations and education. Once these three areas were taken care of, the businesses were sustained and communities could actually enjoy a good quality of life. Another collective action that has developed for extended family groups is the establishment of “Trusts” where all family assets could be invested and then used for education and family obligations when required. There are no set rules to how these arrangements are organized but setting up extended family trusts provides the capital base needed to then further invest in other businesses to maintain capital with the aim of retaining sustainable livelihoods rather than a dependence on handouts and donor aid. Through investment in education and customary forms of exchange these local initiatives enhance forms of social and cultural capital within communities (Scheyvens et al., 2017) that also work to mitigate immersion into a global economic system that undermines solidarity, exacerbates inequalities, and concentrates risk among the most vulnerable (Phibbs et al., 2018).

2.5 Research Outcome This case study has highlighted the urgent need for Fiji to develop and embed community-­determined responses to the challenges raised by climate change, within social and economic infrastructures, in order to mitigate future hazard risks and facilitate thriving sustainable communities. Fiji’s situation is not unique among Pacific nations. It is equally imperative that neighbor states, whose residents have historically drawn on Indigenous bodies of knowledge and practices when responding to adverse events, implement disaster risk reduction approaches that leverage local and community-specific cultural technologies. A recent exemplar of Indigenous knowledges and values being used to inform development of a culture-based disaster risk identification and assessment framework designed for the New Zealand context is showcased in Sect. 3. Development of the He Arotakenga Manawaroa Framework for hazard risk assessment occurred within the context of a research project on Māori resilience that was conducted under the auspices of the National Science Challenges Research Programme, instituted by New Zealand’s Ministry of Business, Innovation and Employment. Creation of the He Arotakenga Manawaroa

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framework has been heavily underpinned by Māori intergenerational experiences of living with environmental or natural hazard risks, and an overview of that historical context is presented as a foundation for discussing the framework.

3 He Arotakenga Manawaroa: A Māori Framework for Assessing Resilience 3.1 Māori and Disaster Risk Reduction Māori, as the indigenous people of Aotearoa/New Zealand, have lived with risk and natural hazards for centuries, and have amassed knowledge about adaptation and risk management. This knowledge is recorded in oral histories and traditions (King, 2007; Gabrielson et al. 2017), and recognition of environmental indicators learnt from close association with the landscape over time could be utilized to inform decision-making and risk assessment. Yet Māori have had little involvement in their own resilience planning or risk and hazard management for their own enterprises, resources, and assets (Awatere et al., 2017b) or for their local communities. National government, relevant agencies, and local government (as the delegated authority from the Crown) currently lead resilience planning and hazard management in New Zealand, and existing frameworks have been built on Western concepts and criteria. This means that current resilience planning processes do not enable Māori to participate in a meaningful way that would lead to outcomes that are culturally relevant and fit with their own aspirations. The strong interplay between the natural environment and Māori social, cultural, and economic systems means that they are highly vulnerable to natural hazards and risk. These hazards and risks may include: earthquakes, volcanism, fire, floods, landslide events, coastal inundation and damage, tsunami, and the current and anticipated impacts of climate change. Against the context of climate change it is critical that New Zealand communities have frameworks and tools to enable mitigation of risks and best practice responses to hazard events, as well as ensure communites are suitably resilient. Natural hazards manifest as geographic or specific location-based events, and for Māori, risk is represented by harm, loss, or damage to whānau (families), social structures, assets, homes, infrastructure, and resources. In order for disaster managment frameworks and risk mitgation tools to be useful to Māori communities they must also be culturally relevant, through embodying core values as well as cultural knowledge. The Māori research team at the New Zealand crown agency Manaaki Whenua recognized that there was a need to understand how families, communities, and enterprises respond and recover from disaster events, and that engaging Māori in resilience planning, decision-making and management helps to mitigate risks, strengthen disaster responses, and promote the recovery of communities.

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3.2 Research Design Accordingly, a specialized Māori research methodology, kaupapa Māori, that is based on Māori concepts, and values was used to design a Māori-led research project that developed a kaupapa-based disaster risk identification and assessment framework, He Arotakenga Manawaroa,. The primary purpose of the specialized framework has been to provide evidence that will enable Māori participation in resilience planning. Framework development has been informed by both the projects findings and previous research initiatives that developed kaupapa Māori based concepts, and indicators in environmental resilience (Awatere & Harmsworth, 2014; Awatere, Robb et al., 2017,), and applied Māori concepts, in the context of community resilience to natural hazard events (Awatere et al., 2018). Māori group assets that are owned by iwi (tribes) and hapū (extended families), such as farms, forestry, marae (Māori meeting places) and pa (Māori settlements), are the cornerstones of community resilience. He Arotakenga Manawaroa is designed to strengthen the resilience of these assets and to identify their role and importance when planning risk mitigation strategies. In addition to playing a key role in Māori economic development and enterprise (Awatere et al., 2017b), these assets provide critical infrastructure capability within the hazard cycle, supporting social and cultural response and recovery. Kenney and Solomon (2014) observed that the ability for Māori to endure during the 2010/2011 Ōtautahi/Christchurch earthquakes was in part due to the inter-familial and inter-tribal connectivity, which mobilized support in the aftermath. Thus, a core component for Māori is sustaining strong connections (whakapapa) between all things, and the building of social structures and networks. The He Arotakenga Manawaroa framework provides a holistic assessment approach for resilience planning, that is informed by a Māori worldview (Te Ao Māori). Resilience is presented and discussed in this case study within the context of hazards and risks (Kenney & Phibbs, 2015; Procter et  al., 2018). Three core Māori values underpin the tool and these domains form the basis for assessment of how resilient communities, enterprises, resources, assets are to risks and hazards. The three interconnected domains of He Arotakenga Manawaroa include: whakapakari ngā kāinga (sustaining and enhancing the built and natural environment—built, human, cultural, and biophysical capitals), whakaora ngā whānau (resilient and strong families—human and cultural capital), and whakahoki te mauri (ensuring the essence of life and vitality remains intact and connected—cultural and spiritual capital). To enable users to assess resilience within each domain, two āhuatanga (attributes) are assigned to each domain so that indicators and measures can be applied to rank each according to a Likert-type scale (0–4). For example, with regard to the domain: whakapakari ngā kāinga (a resilient built and natural environment), attributes include: kei te ora nga kāinga (to strengthen dwellings, social and cultural capital for long-term well-being); and kei te ora te taiao (developing, restoring, sustaining, and enhancing land, resources, habitats, and taonga (natural assets) as part of flourishing and resilient ecosystems). Users rank each of these attributes

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according to the following measures: nil or distressed resilience (aue) = 0, weak or low resilience (ngoikore)  =  1, resilience is perceived to be okay (āhua pai)  =  2, resilience is becoming stronger (kaha ake)  =  3, assets are strong and resilient (manawaroa) = 4. The use of the Māori language (Te Reo Māori) to convey relative measures of resilience means that the framework resonates with the community that is likely to encourage utilization of the tool by Māori collectives, a critical success factor in its adoption and impact. The same scales are applied to the two attributes assigned to the domain, whakaora ngā whānau (resilient and strong whānau/families), and these attributes include: kia mahi ngātahi (gaining strength and resilience by working together, building relationships, social connections, and networks); and kia puāwaitia ngā whānau (the whānau/family, relationships and networks are strengthened and blossom through collective strategies and actions). Regarding the third domain, whakahoki te mauri (the essence of life and vitality remains intact), the scales are modified to reflect the indicators being scored including: weak and diminished mauri/vitality (mauri noho)  =  1, awakening mauri/vitality (mauri oho)  =  2, connecting mauri/vitality (mauri piki)  =  3, and strong and supporting mauri/vitality (mauri ora) = 4. As scoring of the measures is subjective to the users, the researcher anticipates that future use of the framework will require effective collaboration with user groups such as iwi (tribes), hapū (extended family groups), and Māori resource managers. Strengthening these partnerships will help ensure that the processes, principles, and correct steps (tikanga) are consistent across all assessments, and interpretation of the data that are generated by the tool. Utilization of cultural narratives (e.g., ngā kupu/words, whakatauki/proverbs), and conversation (kōrero), along with specific Māori knowledge (mātauranga Māori), will also support the assessment process, and enable users to utilize the framework effectively.

3.3 Research Outcomes Provision of a culturally relevant tool that enables Māori to connect with the environment and evaluate risks and hazards in ways that facilitate decision-making and the creation of strategies that promote disaster resilience is a critical step toward Māori realization of self-determination (mana motuhake) in the disaster risk reduction and climate change adaptation space. These indicators may be used to assess resilience and well-being prior to or following on from a disruptive event/hazard. The data set obtained from the kaupapa Māori tool can be used alongside economic and science-based data, methods, models and tools for planning. Having only recently been made available for use within planning frameworks, utilization of He Arotakenga Manawaroa has been somewhat limited to date. However, the researchers anticipate that following on from broader uptake and implementation by Māori communities, it will be further refined by users. The structure of the tool itself can also be customized by Māori or enterprises desiring to apply institution-specific values and measures, while the methodology that underpins the framework and

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associated processes for its application remain consistent and generic. Thus, the tool can be refined and adapted for context-specific use both nationally and within regional locales. The development of such kaupapa Māori tools is facilitating Māori capacity and capabilities to undertake culturally relevant hazard risk impact assessments and more broadly inform disaster risk and hazard identification, planning, policy and governance endeavors in a range of settings. In this regard, representatives of Te Arawa, a central North Island Iwi (tribe) are progressing a research project in a regional setting that will inform tribal risk mitigation and adaptation to climate change impacts in the central lakes district of the North Island. An overview of the research, which has been funded by the Ministry of Business, Innovation and Employment’s Vision Mātauranga (Indigenous Knowledge) Capability Development programme, is provided in the next section of the chapter.

4 Te Urunga O Kea: A Māori Tribal Self-Determining Response to Climate Change Adaptation Planning 4.1 Research Context The 2017 National Climate Change Adaptation Technical Working Group report has indicated that Māori in comparison to other New Zealand stakeholder groups are at the beginning stages of developing targeted strategies and procedures to facilitate climate change adaptation, with one tribal adaptation strategy completed thus far. In the central region of the North Island, although there is local evidence of climate change adaptation responses for local tribal land and business sector groups, there is equally a significant knowledge to practice capability gap and significant tribal capability development in the field of climate change risk mitigation will be necessary to help future-risk proof the region. Te Arawa is an indigenous nation with lands and resources that stretch from Maketu situated on the East Coast of the North Island of New Zealand to the more centrally located Taupo Volcanic Cauldera, lakes and mountains through to the base of the central North Island Mountain Tongariro. Iwi (tribal) concerns regarding the potential consequences of climate change for the central North Island tribe have contributed to the development of a research partnership between the Te Arawa Lakes Trust (TALT) and Scion, the Crown Forestry Research Institute. The partnership’s key purpose is the development of a research evidence-based and region-specific climate change adaptation strategy for the Te Arawa tribe. While development of Te Urunga o Kea: Te Arawa Climate Change Adaptation Strategy has been shaped by the core research partners Scion and Te Arawa Lakes Trust (TALT), consultation with the Te Arawa Climate Change Working Group and associated communities is key to developing a climate change adaptation strategy that is grounded within a localized Māori worldview. Tribal stakeholders anticipate that the emergent strategy will be considered a

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culturally appropriate tool by Te Arawa, for informing development of measures to mitigate climate change-related risks to tribal assets and local communities (Climate Change Adaptation Technical Working Group, 2017). Development and implementation of the finalized strategy will also constitute a significant step in the regional governance arena. In accordance with the Local Authorities Act (2002) and Resources Management Amendment Act (2018) regional councils and legislated bodies must consider the aspirations and objectives noted in tribal management plans when developing urban and rural priorities at the regional level. Therefore, the research process and outcomes in combination may be understood as an exemplar of tribal rangatiratanga (self-determination) as well as agency in regards to regional governance, particularly in relation to residential developments, land use planning, business development, and environmental management matters. More broadly in the global context, this project responds to a range of policy directions from the United Nations. Notable in this regard is the Sendai Framework for Disaster Risk Reduction (2015) that prioritizes an inclusive approach to disaster risk reduction strategies, which endorses the relevance of Indigenous perspectives and promotes acknowledgment of Indigenous knowledges and practices in this regard. In addition, the research addresses the four main points posited in the Indigenous People’s statement to the United Nations (2017), namely: (i) the incorporation of indigenous knowledge and perspectives into DRR planning and programmes; (ii) the development of support that gives voice to indigenous advocates for DRR and DRM (iii) advocating ‘a seat at the table’ for the inclusion of an indigenous perspective in national DRR planning, and (iv) the provision of opportunity to participate at regional and international forums. Further, the project aligns with key tenets in the United Nations General Assembly 2030 Agenda for Sustainable Development (United Nations’ Educational, Scientific and Cultural Organisation [UNESCO], 2015), which promotes a prosperous and equitable life for all (p. 6).

4.2 Research Design Te Arawa tribal nation has stewardship over 14 lakes within the tribal region and owns the majority of land, which are run as businesses. Iwi members recognize their connectedness with regional waters (lakes, rivers, streams, wetlands, swamps, estuaries, springs, and geothermal waters) and lands. The cyclic nature of the relationships between Te Arawa people and their environment is characterized by a seamlessness—a dynamic and fluid relationship. As noted by King et al. (2007), this understanding provides a foundation for progressing the strategy and developing Māori tribal climate change adaptation plans. This project is framed by a kaupapa Māori research methodology (Smith, 1999) that is specific to the Te Arawa tribe, and informed by broader Māori research practices and practices (Cram, 2001; Irwin, 1994) that locates Māori participants, Mātauranga Māori (cultural knowledge), and cultural ways of being as central to the

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research process (Henry & Pene, 2001). Thus, the research is designed for and with Te Arawa, by researchers who are member of the Te Arawa iwi. Kaupapa Māori research projects are invariably underpinned by Māori values and this research project has been shaped by key Te Arawa tribal principles, which are presented in Table 2.1. The research team has adopted a community-led participatory research design (Denzin & Lincoln, 2007) informed by both a Te Arawa worldview and community-­ based action research principles (Fletcher, 2003; Jones et al., 2010). Qualitative and quantitative methods have been applied to gathering and analyzing data. Initial engagement and tribal perspectives on climate change were gained through a series of semi-structured interviews with key stakeholders. Following this process, several tribal hui a wānanga (Barnes, 2000) or knowledge collection and development workshops (Baran et al., 2014) were conducted with research participants, during which, key climate change adaptation themes were identified and discussed by workshop participants. An inductive approach to thematic analysis of participant’s hui talk, generated new cultural insights, which are being drawn on to clarify tribal priorities and refine development of the Te Arawa Climate Change Strategy and recommendations. In phase two of data collection, which began in late 2019, a quantitative survey will be conducted by a collective of professional researchers who are Te Arawa tribal members. The survey will be disseminated online through the tribal listserv. A multi-linear regression analysis will be applied, which will model the relationship between several climate change explanatory variables and individual responses as the dependent variable. The highlighting of selected key variables will occur through hierarchical multilevel regression to ascertain the relationship between various climate change attitudes and behaviors (Rothman et al., 2008). Table 2.1  Te Arawa tribal research principles Principles Wai Waiariki

Waiora

Wai Rua/ Wairua Waiata

Meaning The principle of connectedness to the water (lakes and rivers). This principle acknowledges our own tribal connectedness to each other and to the environment. The principle of acknowledging the status of the Te Arawa ariki (paramount chief). Waiariki literally translates as water from the gods. Water is understood by Te Arawa as having rhythm, fluidity, and flow, which connect tribal members’ narratives back to an eponymous ancestor. This principle of flow and fluidity informs tribal thoughts, behaviours and attitudes. The principle of health and well-being. Improved water conditions enhance the development of food, and income resources as well as strengthens the cultural and social position of Te Arawa. The principle of two waters (internal and external) as acknowledgment of both the body of waters (lakes, rivers) as well as the physicality, spirituality, and cosmogony of Te Arawa and individual tribal members. The principles of rhythm and/or life balance are represented in tribal waiata (songs), whenua (lands), hitori (histories), wahi tapu (sacred sites), kai (food), ngā ingoa (names), ngā korero (stories), ngā pakiwaitara (legends), and taniwha kaitiaki (protectors).

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Analysis results informed finalization of the Te Arawa climate change adaptation strategy in 2020. Since the project’s inception, communication of information pertaining to research progress as well as emergent findings has been ongoing with the tribal reference group (Te Arawa Climate Change Working Party), through both hui (face-to-face engagement meetings) and electronic correspondence. This process is an essential factor when conducting community-led research and fosters trust within the research partnership (Israel et al., 1998). In addition, the tribal climate change working party will be in a key position to facilitate knowledge translation within Te Arawa, and more broadly, through engagement with other tribes and interest groups, upon project completion.

4.3 Research Progress The research has identified that the majority of climate change science information made public to date has not been easily accessible for Te Arawa residents in the Lakes district. Accessing information is recognized as key to risk reduction efforts. Howitt et al. (2012) advance the view that without information indigenous people are made more vulnerable. Thus, developing strategies to be in the ‘information loop’ is central. Bringing together key tribal stakeholders to form a Climate Change Working Party to implement action, for example, has allowed for a collectivized and organized approach to gathering climate change mitigation information, to occur. Working across indigenous and nonindigenous knowledge paradigms is central to uptake and implementation of the emergent strategy. Therefore, developing and strengthening Te Arawa relationships and establishing clear communication lines with government, non-Māori environmental interest groups, other tribal authorities, universities, research institutes, and businesses have also been pivotal. However, while codeveloped research between Māori and research institutions is increasingly promoted and/or a funding requirement in New Zealand, often research is developed that does not necessarily meet tribal aspirations. Additionally, in some cases, researchers have failed to develop the necessary relationships with tribal stakeholders prior to arriving in their lands to seek research engagement. This approach is being less tolerated and within the Te Arawa region.

4.4 Research Outcomes Our project employed a community-based local tribal researcher whose role included the forging of project relations with the broader community. In total, the community researcher has attended approximately 40 climate change forums since early 2019. The information collection process has contributed to the tribal knowledge base, and equally raised the awareness of the developing strategy. Significantly, the iwi-led research has gained public confidence, which has generated invitations

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to join regional climate change groups that exert political influence, present research updates at key national forums, and showcase emergent findings in the media. Collectively, these initiatives have highlighted the tribe’s innovation in the area of climate change and prompted a request from central government to directly contribute to national climate change policy development in New Zealand. Creating social, cultural, and political momentum toward engaging in climate change adaptation practice is considered equally essential to ensure community well-being. To date, the researchers have codeveloped a range of key strategies including (i) the purposeful facilitation of hui (engagements) with key stakeholders across local and central government, nontribal environment and climate change groups; (ii) carving out a place at key decision-making tables; (iii) developing a media presence from which to leverage public confidence including that of tribal members regarding resilience adaptation practices; (iv) engaging opinion leaders who will foster community uptake of the finalized climate change adaptation strategy; and (v) developing relationships with non-Māori leaders who will advocate for the collective in high-level governance forums on disaster risk reduction, climate change, and new Zealand’s resilience to disasters. Although the project has not yet completed, it is likely that the research will generate further recommendations in relation to capacity and capability development within Te Arawa. In summary, this case study provides an outline of the developing Te Arawa-­ centric values framework as an exemplar of Iwi self-determination, touches upon enablers and barriers to climate change adaptation strategy development, and offers insights into the implementation of a tribal approach to developing a climate change adaptation strategy. The completed research will generate potential lessons for other indigenous collectives on effective and efficient ways to utilize cultural attributes (knowledge, values, and practices) to inform the development of culturally congruent disaster risk reduction strategies that are applicable in specific local settings. A key cultural attribute that is regularly mobilized by Māori as a technology for facilitating community disaster resilience in New Zealand, is the marae (community meeting centres). Māori marae (community meeting centres) are material assets that are geographically situated in order to advantage marae members. They are commonly operationalized as welfare hubs in the aftermath of natural hazard events, and offer hospitality (food, clothing, psychosocial support) as well as temporary accommodation to those in need. However, marae are equally social and spiritual spaces that reinforce social connectedness across generations and may be understood as safe and supportive environments for Māori families. As Kawharu (2010) states: Marae are the forums where tikanga or customs are performed, discussed or negotiated… the focal point where values of stewardship and management in relation to the environment and to people are grounded. Meeting houses, symbolise tribal heritage and celebrate ancestors whose deeds or actions … affirm descendants’ ties to an environment and to a group.

Yet, there are a range of infrastructural, economic, and social challenges to the disaster resilience of marae and these risks as well as external factors that influence marae resilience more broadly, are examined in the following case study.

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5 Whakaoranga Marae: Fostering Asset Resilience 5.1 Māori Marae and the National Disaster Response Infrastructure New Zealand has recently experienced a range of natural hazard disasters, including the 2010–2011 Canterbury earthquakes, the 2016 Kaikōura earthquake as well as cyclones Debbie and Cook, in 2017. Following each of these disasters, Māori communities rapidly drew on core assets, and operationalized social networks, deploying emergency responders to assess and address the needs of devastated communities. Research findings (Kenney & Phibbs, 2014; Kenney & Solomon, 2014) suggest that the Māori response to each event was efficient and effective. Subsequent to a ministerial review of the formal responses to the aforementioned disasters, the New Zealand Government has determined that there is an essential role for marae, within New Zealand’s disaster governance infrastructure (Ministry of Civil Defence and Emergency Management, 2019). In addition to formal acknowledgment within the disaster management governance sector, the actions of marae during disasters are being publicly acknowledged by the media (Carter & Kenney, 2018) and are commensurate with wider social acceptance of these cultural assets as focal points for care in disasters (Towle, 2016). Yet risks to marae infrastructure and disaster response workforce capacity, and therefore the capability of marae to support Māori and the wider community during disasters in ways that ensure marae remain resilient, are not well understood (Hudson & Hughes, 2007). Moreover, explorations of the role of marae (and Māori disaster management more broadly) are often through a nonindigenous lens and focused on immediate responses in acute disaster contexts. Such evaluations fail to capture the complexity of the marae responsibilities pertaining to disaster risk reduction and community resilience in Aotearoa/New Zealand. In order to address this knowledge gap, Māori researchers from Massey University have partnered with the Wellington Marae collective Te Piringa o te Awakairangi, to conduct community-­b ased participatory research (Israel et al., 1998) that explores and documents risks to marae resilience, identifies levels of risk and cocreates measures for mitigating risks to marae in disaster contexts. The qualitative research project is funded by New Zealand’s Ministry of Business, Innovation and Employment’s National Science Research Programme: Resilience to Nature’s Challenges. Research findings will be drawn on by Iwi, New Zealand’s emergency management infrastructure, regional councils, and local authorities, to inform disaster risk reduction planning throughout New Zealand.

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5.2 Research Design A Kaupapa Māori research methodology (Irwin, 1994) has ensured that the research is designed by and for Māori, addresses Māori concerns, and is implemented by Māori researchers in accordance with Māori values and research practices. The research was reviewed and received approval from the Massey University Human Ethics Research Committee and has the inclusion of Te Reo (Māori language) as a key consideration. Māori kaumātua (elders) have supported the research through providing ethical, linguistic, and cultural oversight including advice regarding potential hui-a-wānanga research sites with which they have whakapapa (genealogical) links. Participant recruitment has been purposive, and targeted Māori adults aged between 20 and 65, who have relationships with their local marae. Research participation has been supported by Māori leaders, kaumātua, marae networks, and through snowballing methods. The oral tradition of passing down Māori knowledge through conversation, stories, and waiata is a valued aspect of Māori culture, and actioned through two multi-day hui-a-wānanga (workshops). The Māori researchers and research participants have collaborated in documenting key risks to, and developing risk reduction approaches for marae. The hui-a-wananga method of data collection was selected as it is appropriate for obtaining divergent perspectives on risk and resilience as well as gaining insights into Māori collectivized worldviews. Participants’ talk was digitally recorded, transcribed verbatim, and member checked to verify credibility and reliability. Investigator and theoretical triangulation have also been applied to reduce data misinterpretation and emergent themes were checked with participants to ensure accuracy of interpretation.

5.3 Research Outcomes Exploring the complex interface through which risks are identified and mediated by marae requires a framework that is simultaneously territorially grounded and informed by ancestral knowledge. Thus, a holistic perspective has been used to frame risk identification and evaluation, and context has been a key consideration in the assessment of levels of risk. The majority of risks identified during the research can be encompassed in four domains: environmental challenges to marae sustainability, structural integrity issues in built infrastructure, inadequate relationships with key disaster risk reduction stakeholders, as well as the erosion of marae workforce capabilities and cultural skills (Table 2.2). Participants acknowledged that mātauranga Māori (traditional knowledges) and Western European scientific knowledge are progressively being drawn on to facilitate marae sustainability. Applying building codes and innovative seismic engineering to enhance traditional hangatanga (construction) practices (Prendergast & Brown, 2017), constitutes an exemplar. Equally, tools such as the maramataka (the

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Table 2.2  Summary of risks and sub-risks Environmental risks Structural design of marae buildings

Weak agency relationships

Erosion of cultural skills

Seasonal Hazards (e.g., winter storms, king tides) Climate change (e.g., loss of food security) Legalities and building code compliance Access to knowledge of building regulations Funding for building renovations Connections to external agencies Minimal agency engagement with marae Inadequate corporate governance skills Loss of Mātauranga Māori (traditional knowledge) Loss of Te Reo (Māori language) Changes in tikanga (cultural practices) Inadequate human resources Succession planning for DRR Death of Kaumātua (elders and knowledge holders)

Māori lunar calendar), which relies on longitudinal observation and is often a useful predictive tool for Māori regarding natural hazard events. However, community observations regarding the impacts of climate change suggest that the ways lunar calendars may be used to facilitate food security will need to evolve in order to accommodate environmental changes. As one kaumatua stated: The kōrero from my koro you know … if you see the kowhai tree bloom early there’s gonna be floods and you are seeing floods and they’re coming earlier and later and more often … there’s maramataka for each region and that is shifting with the global warming as well.

Traditional methods of determining risks were viewed by participants as being equally valid as Western scientific methods of identification. There was less confidence among participants in regard to marae trustees’ awareness of engineering requirements, safety legislation and building codes; information essential for ensuring the structural integrity of marae buildings. Governance skills were also a concern as well as the strength of working relationships with key agencies, including local councils and regional authorities. Participants emphasized the importance of engaging with actors outside of the marae structure who could provide knowledge that might usefully inform risk mitigation, as evidenced in the following remark: You’d be a fool not to take advantage of this type of thing, we’ve got an archaeologist involved you know, engineers involved.

Participants further commented that contemporary marae are cultural spaces where “outsider” Western European science knowledge is welcomed as long as the cultural foundations and autonomy of marae are respected. While opportunities for combining knowledge and practices to useful effect are documented in urban planning and architectural literature (Hoskins, 2008; Rolleston, 2005), discussions in mainstream disaster management and risk reduction circles need to recognize that some risks to marae can be balanced through mobilizing other resources. Marae may be located in geographical locations that are vulnerable to natural hazards for example, but the ways in which marae function as social spaces ensures strong relational connections to other Māori groups. These layered

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connections foster reciprocal exchanges of support and resources in times of adversity. Therefore, careful stewardship of these relational networks and thus the capacity of marae to manaaki (care for) their communities is a priority. Ultimately, marae values, cultural practices, and governance protocols were seen by participants as interweaving to create a framework for guiding marae-based disaster risk reduction efforts in response to hazard risks and climate change. The cultural foundation of marae is embodied in kaumātua1 (elders) who support the intergenerational transfer of mātauranga (Māori knowledge), and the preservation of language, values, and cultural practices. Kaumātua also manage links between contemporary and ancestral marae networks as well as oversee the development of relationships with the wider community. As long as each marae retains a cohort of resident kaumatua, they may be able to function in a disaster, regardless of damage to built infrastructure. However, the processes of globalization and urbanization have contributed to cultural erosion, with youth leaving marae and fewer individuals being willing to take up kaumātua responsibilities. As the numbers of kaumatua dwindle, there will be significant challenges for marae in regard to retaining useful traditional knowledges, maintaining marae networks, building links to the wider community, and sustaining marae resilience. Within New Zealand government disaster risk reduction policies and plans, marae are referenced as “welfare hubs,” places of physical shelter and accommodation that offer social and potentially health services to communities during adversity  (New Zealand Government, 2002, 2018). In contrast, research participants presented a culturally informed understanding of marae capabilities in disaster contexts that differed to that noted in government documents. It is therefore crucial that agencies who work with (and rely on) marae understand that marae communities will tend to view disaster risks through a holistic lens, and when developing risk mitigation tools, are likely to prioritize measures that address cultural, spiritual, and relational challenges. In addition, Māori collectives may consider infrastructure and built environment issues to be nonurgent or secondary concerns. Therefore, integration of marae into New Zealand’s broader disaster risk reduction infrastructure will be a complex and culturally nuanced process that will require the creation of multiple collaborative partnerships between Māori, and central, regional, and local authorities. Respect for marae autonomy and consideration regarding how agencies may best support kaumātua in managing marae and guiding communities in disasters will be essential. Through building meaningful relationships and partnerships between the central government, local institutions, and Māori organizations, Māori can be enabled to participate in risk and hazard identification, planning, and management, with the key goals being disaster risk reduction and increased levels of community resilience in New Zealand.

 Kaumātua roles may include “speaking on behalf of the people (Iwi, hapū, whānau); resolving conflicts, carrying the culture; protecting and nurturing; and recognizing and encouraging the potential of younger people” (Te Awe Awe-Bevan, 2013). 1

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6 Conclusions Indigenous people comprise 5% of the world’s population, occupy 22% of the word’s land surface and have stewardship over approximately 80% of the planet’s biodiversity. Indigenous peoples have greater exposure to the impacts of climate change because their identity and culture depend upon the natural environment (Galloway McLean, 2010). The case studies presented in this chapter have global relevance for other Indigenous communities as well as international policy agendas in the area of disaster risk reduction and climate change adaptation as recommended within the Sendai Framework for Disaster Risk Reduction (UNISDR, 2015). The value of emic researchers within the field of disaster risk reduction and climate change adaptation has also been highlighted. An emic perspective captures the richness of Indigenous knowledges through positive relationships that facilitate collaboration and transfer of findings to local indigenous communities. Indigenous people in Lau, Fiji shared their concerns regarding how donor aid has created vulnerabilities through deskilling and disrupting traditional forms of exchange as well as ways of working together. At the local level, Indigenous Fijian communities were responding to identified social, cultural, and economic risks through legal arrangements that formalized the solesolevaki tradition of working together for the common good. The Manaaki Whenua project aimed to ensure Māori participation in resilience planning through developing culturally relevant hazard mitigation tools that utilized local tribal knowledges about natural hazard events. The Te Arawa Lakes project focused on building tribal capacity and capability in relation to climate change adaptation strategies. The final case study explored marae as key resources for disaster risk reduction, identified risks to marae, as well as ways to develop practices at the local level to ensure that marae are resilient. In each of the case studies insider researchers, with tribal links to the community, ensured that Indigenous values and ways of knowing informed the collection, representation, and dissemination of information arising from the research. Findings within these projects reflected the identities of the local indigenous communities, their particular histories, relationships to the land as well as physical assets, cultural protocols, and belief systems. The research projects align with key principles within the indigenous data sovereignty movement that calls for indigenous governance over the collection, ownership, storage, access, and application of data related to indigenous peoples, their lifeworlds and territories (Kukutai & Taylor, 2016). Community development and strengthening disaster risk governance are priority areas within the Sendai Framework for Disaster Risk Reduction (UNISDR, 2015). The culturally embedded, community-led nature of the research presented in this chapter addressed problems identified by local communities, reflected community aspirations, with outcomes being used by and for the advancement of indigenous communities in the areas of disaster risk reduction and natural hazard mitigation.

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Movono, A., & Becken, S. (2018). Solesolevaki as social capital: A tale of a village, two tribes, and a resort in Fiji. Asia Pacific Journal of Tourism Research, 23(2), 146–157. Movono, A., Dahles, H., & Becken, S. (2018). Fijian culture and the environment: A focus on the ecological and social interconnectedness of tourism development. Journal of Sustainable Tourism, 26(3), 451–469. New Zealand Government. (2002). Local authorities act. New Zealand, New Zealand Government. New Zealand Government. (2018). Resources Management Amendment Act. New Zealand, New Zealand Government. Phibbs, S., Kenney, C., Rivera-Munoz, G., Huggins, T., Severinsen, C., & Curtis, B. (2018). The inverse response law: Theory and relevance to the aftermath of disasters. International Journal of Environmental Research and Public Health, 15(5), 916. Prendergast, S. T. A., & Brown, D. K. (2017). Architecture as a pathway to reconciliation in post-­ earthquake Christchurch. The Journal of Public Space, 2(3), 143–156. Procter, J., Kenney, C., Black, T., Harmsworth, G., Saunders, W., King, D., Awatere, S., & Potangaroa, R. (2018). Methods to build resilience in indigenous communities: A case study from Maori, New Zealand. EGU General Assembly Conference Abstracts, 20, 13630. Rolleston, S. (2005). Maori perspectives of urban design. Preliminary findings. In Ministry for the environment. Wellington City Council, Ministry for the Environment. Saunders, W. (2017). Setting the scene: The role of iwi management plans in natural hazard management. GNS Science, Te Pū Ao. Scheyvens, R., Banks, G., Meo-Sewabu, L., & Decena, T. (2017). Indigenous entrepreneurship on customary land in the Pacific: Measuring sustainability. Journal of Management & Organization, 23(6), 774–785. Smith L. (1999) Decolonizing Methodologies Research and Indigenous Peoples (2nd ed.). Dunedin: University of Otago Te Awe Awe-Bevan, B. R. (2013). Te reo o ngā kaumātua: A thesis presented in partial fulfilment of the requirements for the degree of Master of Philosophy in Māori studies at Massey University, Palmerston North, New Zealand. Doctoral dissertation, Massey University. Towle, M. (2016). 21st November, We’re here to help, we’ll help anybody. Radio New Zealand. Available at: http://www.radionz.co.nz/news/national/318520/'we're-­here-­to-­help,-­we'll-­help-­ anybody'. Accessed 25 June 2019 UNISDR (United Nations International Strategy for Disaster Reduction). (2015). Sendai framework for disaster risk reduction 2015–2030. The United Nations Office for Disaster Risk Reduction. United Nations. (2014a). Small Islands developing states. Sustainable Development Goals. Available at: https://sustainabledevelopment.un.org/topics/sids. Accessed 11 June 2019 United Nations. (2014b). SIDS accelerated modalities of action [S.A.M.O.A]. United Nations Sustainable Development Goals Knowledge Platform. Available at: https://sustainabledevelopment.un.org/sids2014/samoapathway. Accessed 25 June 2019 United Nations Climate Change. (2017). How Fiji is impacted by climate change. 09 Feb. Available at https://unfccc.int/news/how-­fiji-­is-­impacted-­by-­climate-­change. Accessed 7 June 2019. United Nations Educational, Scientific and Cultural Organisation. (2015). Education for sustainable development goals: Learning objectives. United Nations Educational, Scientific and Cultural Organization (UNESCO), France. Vunibola, S. (2018). “Na i kanakana nodra na tukaqu au bula kina” (My ancestors’ land to feed from and to help me survive): Customary land and economic development: Case studies from Fiji. Paper presented at the International Development Conference (DevNet), University of Canterbury. 5–7 December, 2018. Whyte, K. (2018). Indigeneity in geoengineering discourses: Some considerations. Ethics, Policy and Environment, 21(3), 283–307. World Bank. (2003). Cities, seas, and storms: Managing change in Pacific Island economies. In Adapting to climate change (Vol. IV). World Bank. Accessed 7th June from: http://documents. worldbank.org/curated/en/532221468288338891/Adapting-­to-­climate-­change

Chapter 3

The Adaptation to Climate Change in Primary Education and Approach from the Social Sciences Textbooks Álvaro-Francisco Morote and Saeid Eslamian

, Jorge Olcina

, María Hernández

,

Abstract  The aim of this research is to analyze the adaptation of climate change proposals and solutions that are incorporated in the Spanish Social Sciences school textbooks (Primary Education). Based on the analysis of the main publishers, the books that correspond to the third cycle (5th and 6th grades) have been examined. After the revision of these resources, three categories of solutions have been identified: (1) advice to be followed (collective and individual); (2) activities that students should propose to the solutions; and (3) information about the different international conferences of global warming. Most of the proposals are related to the recommendations, and secondly, with the international conferences. In conclusion, there is a total absence of activities that could make students think more critically about climate change, both about the possible causes and the adaptation actions, specially, at the local and regional scale. Keywords  Climate change · Adaptation · School textbooks · Social sciences · Primary education

Á.-F. Morote (*) Department of Experimental and Social Sciences Education, Faculty of Teaching Training, University of Valencia, Valencia, Spain e-mail: [email protected] J. Olcina · M. Hernández Department of Regional Geographic Analysis and Physical Geography, University of Alicante, Alicante, Spain e-mail: [email protected]; [email protected] S. Eslamian Department of Water Science and Engineering, College of Agriculture, Center of Excellence on Risk Management and Natural Hazards, Isfahan University of Technology, Isfahan, Iran e-mail: [email protected] © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_3

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1 Introduction The greatest of socio-environmental challenges currently facing the world is climate change and its associated effects (Intergovernmental Panel on Climate Change [IPCC], 2022). Therefore, Climatology, now a branch of Geography, and its teaching, has become the focus of great attention (Morote & Olcina, 2021; Olcina, 2017; Sebastiá & Tonda, 2018). However, teaching this subject is highly complex (Chang & Pascua, 2016; Martínez-Fernández & Olcina, 2019). This is due to the connection with the evolution of the climate for the various variables involved, to which must be added the influence of the media with the presence of conceptual errors, stereotypes and the so-called “fake news” (Morote & Olcina, 2020). Research on climate change is an issue that concerns and interests the community and, in particular, the teaching community, since the very future of society depends on raising awareness about this serious problem (Serantes, 2015). In addition, the explaining the phenomena involved acquires greater relevance since it is necessary to treat it differently in different stages of education. Therefore, this represents a challenge in the educational field: the responsibility of training of the younger cohorts in understanding and adapting to climate change (Morote & Olcina, 2020). At the international level, various studies in recent years have highlighted the interest devoted to the study of climate change at school (Eklund, 2018; Li et al., 2021; Sezen-Barrie & Marbach-Ad, 2021). In Spain, in the area of the Didactic of the Geography, despite the notable scientific production on how to teach Climatology (Martínez-Medina & López-Fernández, 2016; Martínez-Fernández & Olcina, 2019; Morote & Moltó, 2017; Tonda & Sebastiá, 2003; Valbuena & Valverde, 2006), to date, there is no the consolidated line of research on this subject (climate change and textbooks). And even less, in relation with the Primary Education stage (Morote & Olcina, 2020, 2021). Besides, regarding school manuals, interest has arisen in educational research since these resources are privileged sources of information that allow us to approach what is taught in the classroom (Bel & Colomer, 2018; Valls, 2008). However, except for some recent works (Morote, 2020, 2021; Morote & Olcina, 2020, 2021), there are few studies that have been devoted to the analysis of how climate change is taught in the Social Sciences and/or Geography from school textbooks. The treatment of climate change in the educational field is not the most appropriate, going by the analysis of the contents of this subject in textbooks. For example, Olcina (2017) highlighted that one of the most negative aspects that is reproduced in the school manuals of Secondary Education and Baccalaureate is excessive extremism and catastrophism found in both written contents and images. The authors verify the association between climate change and desertification as being very frequent, including the striking images of desert landscapes in the Iberian southeast. They are, however, processes that are not directly related. The erosion process (natural process in arid zones) is also confused with that of “creation” of desert landscapes due to the decrease in rainfall predicted in the climate modeling. However, this process is not fully confirmed in the scientific research for the

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Mediterranean area, where there are “regional” or “local” climatic nuances of very different behavior. Olcina (2017) has also found that some educational texts present climate hazards related to climate change when they really are not. For example, the case of tsunamis that have a geophysical origin, which have nothing to do with the current climate-warming process. On the other hand, some textbooks do include explanations of processes having great importance for the functioning of the regional climate, such as the warming of sea waters, with illustrative images. Or, likewise, past climate changes, such as the ice ages, are explained in order to understand that climate changes are an inherent feature of the planet itself since its origins. Another recent work (Morote & Olcina, 2020) has analyzed how climate change is presented in the textbooks of Social Sciences of Primary Education. One conclusion reached by these authors is that the information transmitted in these resources follows the same model as that of the Secondary and Baccalaureate manuals (see Olcina, 2017). In other words, a catastrophic message of the phenomenon is transmitted with: (1) decontextualized images from other areas of the Iberian Peninsula to explain the issues of climate change in Spain; (2) natural phenomena that have little or nothing to do with the climate change (case of the Monsoon); and (3) an excessive presence of the human factor as the cause of this phenomenon. In this sense, most publishers ignore and do not explain the evolution of the climate throughout history. Furthermore, Morote and Olcina (2020) presented the results that, a priori, may be negative. This is the case of the presence in textbooks of water vapor as the main greenhouse gas. Only three out of ten of the consulted books mention it, but, as these authors explain, it should not be presented as something entirely negative because, at present, both in the perception of society and in the media. CO2 is still the main greenhouse gas. This is a mistake. As these authors indicate, it should be qualified, since CO2 is the main greenhouse gas that is increasing due to anthropogenic causes, but its presence in the atmosphere is still much lower than that of water vapor. Therefore, it is an error that is gradually being corrected and qualified in the schoolbooks. Interest in carrying out this work can be attributed to: (1) the current challenge posed by climate change and its effects on society due to the higher frequency of the extreme atmospheric events (IPCC, 2022) and the challenge of achieving greater sustainability of the territory and society; (2) the importance of dealing with climate change in the Primary Education stage as established in the current curriculum (Royal Decree 126/2014, of February 28); (3) the teaching of climate change and its associated risks is a basic action for the achievement of the SDGs (Objective No. 13) (UN, 2015); and (4) education being one of the main actions recommended by the IPCC for the adaptation of society to climate change. In this sense, the IPCC (2014) has stated in its Fifth report that education is one of the fundamental actions for the adaptation of society to climate change since, as indicated, a better-trained society on these issues will be more safe from the consequences of the current planetary thermal heating process. The objectives of this research are to analyze what proposals and activities are included in the current Social Sciences school textbooks (Primary Education) of the Valencian Community (Spain) for the adaptation and/or mitigation of the effects of

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climate change. As a hypothesis, it is established that the adaptation and solutions in these resources would be characterized by being reduced and by their simplicity (advices-decalogues) without practically paying attention to the local and/or regional scale. Regarding study limitations, it should be noted that with the analysis of the textbooks, it is not really known what is taught in the classrooms. However, its results are of notable interest because in Social Sciences they are the main resources used.

2 Sources and Methodology To achieve the proposed objectives, the Social Sciences school manuals of Primary Education (3rd cycle; 5th and 6th grades) of the main publishers used in the Valencian Community (Spain) (Anaya, Bromera, Santillana, SM, and Vicens Vives) have been consulted. Also, these resources coincide with the most representative of the Spanish territory (Sánchez-Fuster, 2017) (see Table  3.1). The choice of this geographical framework is due to several reasons: (1) the Valencian region is one of the areas of the Mediterranean that is most vulnerable to the consequences of climate change (IPCC, 2022); and (2) there are the previous publications in this region both for the revision of History content (Bel & Colomer, 2018; Sáiz, 2011) and content related to Climatology (Morote, 2020), climate change (Morote & Olcina, 2020), and natural risks (Morote, 2021) that have justified the choice of these publishers. Regarding the school textbooks examined (a total of 10; 5 per year), these have been the most current: those published after the approval of the LOMCE (Organic Table 3.1  Social Sciences school textbooks analyzed (3rd cycle of Primary Education) Grade School textbooks 5th Benítez, J.K., Cano, J.A., Fernández, E. and Marchena, C. 2014. Ciencias Sociales 5. Grupo Anaya. Gregori, J. and Viu, M. 2014. Crónica 5. Ciencias Sociales. Ediciones Bromera. García, M. and Gatell, C. 2014. Sociales, 5 Educación Primaria. Aula activa. Vicens Vives. Grence, T. 2015. Ciencias Sociales. 5° de Primaria. Santillana Voramar. Parra, E., Martín, S., Navarro, A. and López, S. 2014. Ciencias Sociales. Comunitat Valenciana. 5° Primaria. SM. 6th Benítez, K., Cano, J.A., Fernández, E. and Marchena, C. 2015. Ciencias Sociales, 6: Primaria. Grupo Anaya. García, M., Gatell, C. and Batet, M. 2015. Sociales 6°. Vicens Vives. Gregori, J. and Viu, M. 2015. Ciencias sociales 6°. Ediciones Bromera. Grence, T. and Gregori, I. 2015. Ciencias Sociales 6°. Ediciones Voramar, Santillana Educación. Martin, S., Parra, E., De la Mata, A. Hidalgo, J.M. and Moratalla, V. 2015. Ciencias Sociales 6°. SM. Source: Own elaboration

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Law 8/2013, of December 9, for the Improvement of the Educational Quality) following the same methodological process of the works mentioned above in relation with the geographical aspects. With regard to these resources and their number, it should be emphasized, as shown by Morote (2021), that they are representative and more than enough, in addition to following a validated methodology as can be seen in other research on textbooks. See, for example, the publications carried out in other Spanish areas such as the Community of Madrid (García-Francisco et  al., 2009) or the Region of Murcia (Sánchez-Fuster, 2017). In relation to the curriculum, it should be noted that in Spain, the State is the one that establishes the minimum teachings for Primary Education (Royal Decree 126/2014 of February 28th). However, the contents are transferred to the autonomous communities, which are the ones who specify it in their own curriculum. In the case of the Valencian Community, in the current curriculum (Decree 108/2014, of July 4th, of the Consell), the contents on climate change in the area of Social Sciences are inserted in Block 2 “The world in which we live.”

3 Results Based on the analysis of Social Sciences books, in relation to the solutions that are proposed to solve the problem of climate change, three types of the proposals have been categorized (n = 13): (1) proposals on recommendations to follow, both collective as well as individual, in connection with the adoption of sustainable environments and efficiency in the use of natural resources; (2) activities in which students must propose solutions; and (3) information on different international summits in which the main actions to solve global warming are collected (see Table 3.2). Table 3.2  Proposals and solutions to climate change that are included in the school textbooks of Primary Education of Social Sciences Grade and publisher 5th Anaya 6th Anaya 5th Bromera 6th Bromera 5th Santillana 6th Santillana 5th SM 6th SM 5th Vicens Vives 6th Vicens Vives

Advices-­ decalogues ✓ ✓ ✓ – – – – ✓ – –

Activities for the students – – – – ✓ –

International climate change conferences – – ✓ ✓ –

✓ –

✓ – –

✓ –

✓ –

Source: own elaboration. Note: in the case of the 6th grade book by the publisher Vicens Vives, no information related to solutions to climate change has been inserted

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Regarding the 5th year (Anaya publisher), the contents related to climate change are included in Unit 4 “The climate.” It proposes information on how the greenhouse gases should be reduced with simple measures: “Using solar panels in homes; using the public transport instead of public transport; showering instead of bathing, and recycle showering water for the other activities; recycling the garbage that we produce at home; leave the heater, television and other electrical appliances plugged in without being reused; and using low consumption light bulbs” (Benítez et  al., 2014: 62). From this same publisher, but in 6th grade (Unit 3 “Environmental problems”), the proposed measures follow the same common thread as advice such as: reducing pollution, saving energy consumption, etc. Especially, it highlights the term commonly known as the 3 “R” to apply both in the domestic sphere and on a global scale: (1) reducing the use of nonrenewable materials (plastics), paper and nonrenewable energy; (2) reusing all possible products; and (3) recycling used materials so that the other products can be manufactured (Benítez et al., 2015). Second, the publisher Bromera has been analyzed. For the 5th year, questions about climate change are included in Unit 2, “Climate and Landscape.” And, in relation to the objectives of this research, the solutions to this phenomenon are includedby way of decaloguing the following instructions: (1) you will take care of water; (2) you will save energy; (3) you will produce less energy; (4) you will use recyclable packaging; (5) you will avoid using chemicals; (6) you will avoid the use of plastic bags; (7) you will reuse paper; (8) you will travel by bicycle or on foot; (9) you will take care of the flora and fauna; and (10) you will think globally and act locally (Fig. 3.1). In this course, it should also be noted that information is collected on the objectives of the different international conferences on climate change that aim to reduce the greenhouse gases. In this case, what is proposed is an activity

Fig. 3.1  Decalogue and advices that are proposed in the Social Sciences school textbook (5th grade of Primary Education) (Bromera Publisher). Source: Gregori and Viu (2014). Own elaboration. (Note: Translation: Title: “To fight global warming.” Text: “If we all became aware; we would help the natural disasters associated with climate change not to occur. Here are some tips to make it possible”)

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where students must investigate these acts and write a report (see Table  3.3). Regarding the 6th year (Unit 2 “The climate and vegetation”), the proposed solutions also refer to the international conferences on climate change organized by the United Nations (UN). Specifically, the 2014 Conference on climate change celebrated in Lima (Peru) is mentioned. In this summit, the presidents of the main countries that pollute the most (China and the United States) agreed to a decrease in the greenhouse gas emissions. Regarding the European Union, it is explained that it committed to reduce its emissions by 40% (Gregori & Viu, 2015). However, it should be noted that the established measures are not explained, only the intentions. Third, the books published by Santillana have been consulted. In the case of the 5th grade (Unit 4 “The atmosphere and the climate”), no proposals are indicated, but the students themselves have to raise them from an exercise that integrates the different activities: Activity (1) involves looking for information on the causes of climate change and completing a table with four main causes. For this, two web links are provided where students can search for the said information (see Fig. 3.2); Table 3.3  Research exercise proposed in the Social Sciences school textbook (5th grade of Primary Education) (Bromera Publisher) Nations are also concerned about the problem and come together to reduce the greenhouse gas emissions. One of these attempts was the Kyoto meeting (1997), and later the XVII Climate Change Conference in Durban (2011). Research these acts and write a short report. Source: Gregori and Viu (2014). Own elaboration

Fig. 3.2  Activity to solve climate change that is proposed in the Social Sciences school textbook of publisher Santillana (5th grade of Primary Education). Source: Grence (2015). (Note: Translation: Title: “Propose actions to adapt to the climate change”; Text: “Climate change is one of the great challenges facing humanity today. Therefore, it is important that we take steps to stop it. The first step in fighting a problem is knowing its causes. Then, you have to analyze what measures can be taken to reduce each of the causes that cause the problem”)

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Activity (2) is related to a reflection of the proposals on what measures could reduce the effects of this phenomenon in relation to the causes mentioned in the previous activity; and Activity (3) is a cooperative work exercise where they first have to discuss in groups the measures of all of the members of the previous activity and develop an action plan (Grence, 2015) (see Fig. 3.3). Regarding the 6th grade textbook, the questions on climate change are included in Didactic Unit 5 (“Human impact on the environment”) and, in connection with the solutions that are explained to mitigate the consequences of climate change, the Kyoto Protocol (1997) is cited. In addition, emphasis is placed, as explained, by industrialized countries, to reduce the greenhouse gases through the use of solar and wind energy (renewable energy). The fourth publisher analyzed was SM. Regarding the measures proposed in the 5th grade manual (Unit 2 “The climate”), these are synthesized in an activity in which the students have to propose the solutions to reduce the effects of climate change. This activity is stated as follows: “Complete the following table on climate change.” For this, three columns, causes, consequences, and solutions, are added. It is also worth highlighting the influence that the catastrophic message that predominates in textbooks may have. In fact, in the preceding pages where this activity is inserted, drawings are illustrated on the causes of this phenomenon based, mainly, by human action (pollution, deforestation, overexploitation of natural resources, etc.), and giving a catastrophic message (see Figs. 3.4 and 3.5). As for the 6th grade (Unit 2 “The landscapes of Europe”), a section entitled “How to practice sustainable development?” is incorporated (Fig. 3.6). It cites the following recommendations to solve the problem of pollution and overexploitation of natural resources: (1) promote sustainable production and consumption; (2) reduce greenhouse gas emissions; (3) raise awareness that natural resources are limited; and (4) build sustainable

Fig. 3.3  Activity to solve climate change that is proposed in the Social Sciences school textbook of publisher Santillana (5th grade of Primary Education). Source: Grence (2015). (Own elaboration). (Note: Translation: “Team work. Explain in class individually the measures you have thought about. Discuss them with everyone and come up with an action plan. First, write down the measurements that seem most appropriate to you on the blackboard. Cross out the proposals whose application is too expensive or too complicated to carry out. Then sort the measures by their level of urgency. Write 1, which you think should be taken up first, and so on. Copy the list neatly in your notebook. Do not forget to give it a title”)

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Fig. 3.4  Images depicting the consequences of climate change presented in the Social Sciences school textbooks of the publisher SM (5th grade of Primary Education). (Source: Parra et al., 2014)

Fig. 3.5  Illustrations depicting the causes of global warming as proposed in the Social Sciences school textbook of the publisher SM (5th grade of Primary Education). Source: Parra et al. (2014). Own elaboration. (Note: it is worth highlighting the sensation of catastrophism that is alluded to in the image that is proposed to explain the causes of climate change. Translation: Title: “What the causes of climate change?”. Bubbles: 1. The use of fossil fuels in factories and vehicles increases carbon dioxide; 2. Agriculture and livestock generate gases from the use of fertilizers and the digestion of animals; 3. Deforestation contributes to the increase of carbon dioxide)

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Fig. 3.6  Illustration about the causes of climate change proposed in the Social Sciences school textbook of the publisher SM (6th grade of Primary Education). Source: Martin et al. (2015). Own elaboration. (Note: Translation: “Climate change is caused by the increase in the emission of gases that rise the greenhouse effect. Sustainable development has made it possible to use the natural resources in such a way that they are not depleted in the long term”)

communities through green spaces and construction of houses that do not involve excessive energy consumption (Martin et al., 2015). Lastly, the publisher Vicens Vives has been analyzed. Regarding the 5th grade (Unit 3 “Climate and vegetation”), the only content that appears about the solutions to this phenomenon is the allusion to the Kyoto Protocol (1997). However, it does not cite it, but it is assumed that it is attributed to that year: “[I]n 1997, leaders from the different countries of the world met and committed to reducing the emissions of gases that cause the greenhouse effect and thus curbing climate change” (García & Gatell, 2014: 53). Regarding this information, an activity is proposed that consists of the students writing a speech to protect the planet and stop climate change. In relation with the 6th grade, it should be noted that no type of information and content is included on the subject under study. The only subject with content in which this global challenge may be linked is Unit 3 “The intervention of the human being in the environment.” This topic deals with human intervention in the environment to show how it degrades, the need for its protection, and contribution to the sustainable development of the planet. Nevertheless, there is no allusion to the phenomenon of climate change.

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4 Discussions This research explores and analyses the proposals and activities related to solutions to climate change that are included in the main Social Sciences school textbooks (Primary Education) used in the Valencian Community. After this review, it has been verified that the hypotheses are fulfilled: Most of the solutions proposed in the textbooks are characterized by being reduced and by their simplicity (in the form of advice-decalogues) and without taking into account the local/regional scale. In relation with the number of activities, these are usually one per Publisher (a total of 13). This, in part, is normal since the section on the explanation of climate change is dedicated between 1 and 2 pages at the end of the unit on climate. Even the 6th grade book (Vicens Vives) does not dedicate the information on this subject. This is something that Olcina (2017) and Martínez-Fernández and Olcina (2019) have recently revealed in their research: a scant attention devoted to the climate change and not very reflective activities that motivate the students to have a more critical and committed to this global problem. Therefore, they would be educational practices that would not promote the critical citizenship in which a relevant socio-­ environmental problem is addressed. After analyzing these resources, 13 proposals have been identified and placed into 3 categories. Most of them have to do with the opinion of councils as a decalogue and allusions to international conferences. Besides, there is an almost total absence of activities that make the students think critically about climate change, both about possible causes and adaptation actions. In this sense, the catastrophic message is abused, already proven in other publications (see Morote, 2021; Morote & Olcina, 2020) and the simple recommendation of good guidelines and behaviors. It should also be noted that these resources have a lack of content and rigorous information on solutions to this global phenomenon, and also few references from the scientific works and academic sources. Recent contributions such as those of Nelles and Serrer (2020) and Masters (2020) are a clear example of the way forward in teaching about climate change with proposals based on scientific evidence according to the age of the student. These are the issues Olcina (2017) already stated a few years ago after reviewing the explanation of the content on climate and weather in Secondary Education. Olcina (2017) and Morote and Olcina (2020) have analyzed that one of the most notorious deficiencies that are reflected in the textbooks is the scant scientific rigor and the excessive reproduction of stereotypes coming from the media, as is the case of catastrophic images. However, Morote and Olcina (2020) highlighted that, compared to a few decades ago, the content on climate change has improved, since now, although with certain errors and stereotypes, this global phenomenon is given more importance in these resources. In relation with the improvement of the teaching of climate change, Martínez-­ Fernández and Olcina (2019) indicated that the contents on this phenomenon should be incorporated into the curricula of Primary, Secondary and Baccalaureate Education gradually and betting on the presentation of the data and real processes, verified by research, avoiding the extremes or striking messages that lack the

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scientific foundation. For example: for the 1st year of ESO, it would be convenient to explain only that climate change is a matter of gas emissions (relating it to air pollution in general); in the 2nd year of ESO, the effects on the main climatic elements (temperatures, rainfall), as well as on the rise in sea level (including illustrative maps) should be explained; and finally, in the 3rd year of Baccalaureate, the explanation of the effects on the economy and the territory of the closest geographical area (Mediterranean coast, for example) should be incorporated. In addition, for the proposal of information and activities in relation to natural risks, the vulnerability factor (the human factor) should be taken into account. This has been recently analyzed in relation to atmospheric risks by Morote and Olcina (2020), who highlighted the absence of this variable in the school textbooks as a factor that increases risk (in this case, those linked to the climate change). These authors have verified that practically none of the analyzed books alludes to the human factor in the assertion of risk, the danger factor being the only one that influences the natural disasters. In other words, to explain climate change, only human action is taken into account, however, when dealing with natural risks, the human factor is forgotten. For their part, Souto et al. (2019) in relation to the risk of flooding and water resources, have verified that in the textbooks of Primary Education practically does not appear or relate how human activities can affect the natural regime of rivers. Regarding the above, as indicated by the various reports on the effects of climate change, there is an urgent need to give a greater dedication and an interest to this factor (vulnerability). It is a matter of first order in the European territory to achieve a greater adaptation to climate change and the foreseeable increase in natural risks until the end of the twenty-first century (European Environment Agency [EEA], 2017).

5 Conclusions In relation with the effects of climate change, it is clear that the most visible are the catastrophic consequences, but the presence of an excessively catastrophic message can be a double-edged sword. On the one hand, it can help raise awareness in younger cohorts about the problems of this phenomenon and the urgency of carrying out a more sustainable and respectful life with the environment. However, on the other hand, this message can lead to error, that is, the transmission of knowledge not based on scientific evidence. Besides, as for the proposals, the public must not be forgotten to whom they are addressed (children 10–12-year-olds). In this sense, the information and activities that should be proposed should not be too complicated and, even for the Primary Education stage, it is positive to incorporate the information on decalogues to complement the issues related to climate change. Nevertheless, activities are lacking in which students have the opportunity to think critically and seek the solutions to this global challenge in their closest environment (local and/or regional scale). Only 3 of the 13 identified proposals have to do with this category. Otherwise, in the absence of this, critical analysis of solutions

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to the effects of climate change will depend on the creativity and imagination of teachers when designing the materials on this subject (something that has not been analyzed in this paper). In this sense, this is a study limitation associated with this type of work that, as the other authors referring to textbooks in Social Sciences (Valls, 2007) have already pointed out, is that the school manuals do not show what teachers really do teach in the classroom. However, as indicated by Bel and Colomer (2018), although the use of these resources in the recent years has decreased, they continue to be the main tool used (if not the only one) in Social Sciences classes. The same has been verified by Martínez-Fernández and Olcina (2019) and stated by Morote and Olcina (2020) for the case of climate and climate change. As a future research challenge, it is proposed to expand and inquire about this subject from the teaching practice (active teachers and in training) and review these same contents in the school manuals for Secondary Education and Baccalaureate. To sum up, it should be emphasized that the transmission of climate change, from the academic world, at educational levels is essential in the context of sustainability to encourage the actions of administrations and social agents in this century (Farzaneh et al., 2014; Maleksaeidi et al., 2017; Treacy & Eslamian, 2021). It is necessary to communicate rigorously, avoid false ideas and impressive headlines that usually contain catastrophic messages. Climate change must be taught as a reality, as an important problem for humanity, but also as an opportunity to do things better, in the use of resources, in energy production, in territorial management, etc. Teaching climate change is a challenge that must be faced from the truth of the facts, with rational messages of solution. Finally, from teachers, an emphasis should be placed for no abuse with the textbook and trying to create their own activities taking into account the “imagination,” “originality” and the “local” territory (IOL) (Morote & Olcina, 2021).

References Bel, J. C., & Colomer, J. C. (2018). Teoría y metodología de investigación sobre libros de texto: Análisis didáctico de las actividades, las imágenes y los recursos digitales en la enseñanza de las Ciencias Sociales. Revista Brasileira de Educação, 23, 1–23. https://doi.org/10.1590/ s1413-­24782018230082 Benítez, J.  K., Cano, J.  A., Fernández, E., & Marchena, C. (2014). Ciencias Sociales 5. Grupo Anaya. Benítez, K., Cano, J. A., Fernández, E., & Marchena, C. (2015). Ciencias Sociales, 6: Primaria. Grupo Anaya. Chang, C.  H., & Pascua, L. (2016). Singapore students’ misconceptions of climate change. International Research in Geographical and Environmental Education, 25(1), 84–96. https:// doi.org/10.1080/10382046.2015.1106206 Eklund, S. (2018). Climate change education with a bright horizon?: Pedagogical reflections on teacher training for climate education that aims to empower students. Doctoral thesis, Stockholm University. European Environment Agency. (2017). Climate change, impacts and vulnerability in Europe 2016. An indicator-based report. https://www.eea.europa.eu/publications/ climate-­change-­impacts-­and-­vulnerability-­2016

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Parra, E., Martín, S., Navarro, A., & López, S. (2014). Ciencias Sociales. Comunitat Valenciana. 5° Primaria. SM. Sáiz, J. (2011). Actividades de libros de texto de Historia, competencias básicas y destrezas cognitivas, una difícil relación: Análisis de manuales de 1° y 2° de ESO. Didáctica de las Ciencias Experimentales y Sociales, 25, 37–64. Sánchez-Fuster, M.  C. (2017). Evaluación de los recursos didácticos utilizados en Ciencias Sociales, Geografía e Historia en Educación Primaria. Doctoral thesis, Universidad de Murcia. Sebastiá, R., & Tonda, E. M. (2018). Enseñar y aprender el tiempo atmosférico y clima. In García de la Vega, A. (Coord.). Reflexiones sobre educación geográfica: revisión disciplinar e innovación didáctica (pp. 153–176). Universidad Autónoma de Madrid. Serantes, A. (2015). Como abordan o Cambio Climático os libros de texto da Ensinanza Secundaria Obligatoria na España. AmbientalMENTEsustentable, 20, 249–262. https://doi.org/10.17979/ ams.2015.2.20.1609.1603 Sezen-Barrie, A., & Marbach-Ad, G. (2021). Cultural-historical analysis of feedback from experts to novice science teachers on climate change lessons. International Journal of Science Education, 43(4), 497–528. Souto, X. M., Morote, A. F., & García, D. (2019). Crisis y riesgos naturales en la educación social. El caso del riesgo de inundación en Educación Primaria. In Asociación Española de Geografía y Universidad de Valencia (Ed.), Crisis y espacios de oportunidad. Retos para la Geografía (pp. 171–185). Universidad de Valencia. Tonda, E., & Sebastiá, R. (2003). Las dificultades en el aprendizaje de los conceptos de tiempo atmosférico y clima: La elaboración e interpretación de climogramas. Revista de Educación de la Universidad de Granada, 16, 47–69. Treacy, J., & Eslamian, S. (2021). Environmental hydrology and climate change. In H. C. W. L. Filho (Ed.), Encyclopedia of the UN Sustainable Development Goals: Climate action. Springer. United Nations (ONU). (2015). Sustainable Development Goals. UNDP, Sustainable Development Agenda. https://www.undp.org/content/undp/es/home/sustainable-­development-­goals/ resources.html Valbuena, M., & Valverde, J. A. (2006). La climatología local. Procedimiento para su enseñanza y aprendizaje. Didáctica Geográfica, 8, 93–108. Valls, R. (2007). Historiografía Escolar Española: Siglos XIX–XXI. UNED. Valls, R. (2008). La Enseñanza de la Historia y textos escolares. Libros del Zorzal.

Chapter 4

Building Climate Change Adaptation and Risk Knowledge in the Arctic Through Preparedness and Contingency Practices Gisele M. Arruda and Lara Johannsdottir

Abstract  Arctic social and ecosystems are experiencing rapid and transformational changes driven by bio-geo-physical changes. These changes pose a widespread risk to safety, health, and well-being of inhabitants including damages to infrastructure, affecting livelihoods and causing economic impacts to many different sectors essential to Arctic societies. In this realm, the concepts of exposure, vulnerability, disaster risk, and resilience are explained. Consequently, the aim of this chapter is to explain how climate change adaptation and risk knowledge can be built, envisaging the future of Arctic landscapes and societies. As a review, it brings together different mechanisms that are evolving and improving. The novelty of the chapter is that it includes management strategies and collaborative systems for crisis management for reduction of daily or chronic risk factors with involvement of various stakeholders, drawing on Indigenous and local knowledge, and building risk knowledge, as well as by strengthening preparedness and contingency practices. The chapter highlights that efforts will be more effective when informed by knowledge, innovation, and education to build a culture of safety and resilience at all levels and mainly at the citizen’s level. In addition, disaster risk management and adaptation can greatly benefit from a far greater synergy with institutional, financial, policy, strategic, and knowledge-intensive environmental measures that current measures do. Keywords  Climate change · Adaptation · Risk · Knowledge · Preparedness · Contingency · Arctic

G. M. Arruda Circumpolar Studies, School of Business and Management, University of Aberdeen, Aberdeen, Scotland, United Kingdom L. Johannsdottir (*) Environment and Natural Resources, Faculty of Business Administration, University of Iceland, Reykjavik, Iceland e-mail: [email protected] © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_4

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1 Introduction The Arctic environment needs to be understood as a highly complex system of continuous interactions. The bio-geo-physical drivers of Arctic change and the social and eco-systemic synergies are evolving at a rapid pace with some indicators changing even faster than previously reported by scientists (Arruda & Johannsdottir, 2022). Key indicators such as temperature, precipitation, snow cover, sea-ice thickness and extent, and permafrost thaw have shown rapid and widespread changes in the Arctic landscape. The increase in Arctic annual surface temperature (land and ocean) recorded between 1971 and 2019 was three times higher than the increase in the global average during the same period, resulting in extreme events increasing in frequency, intensity, and impacts on Arctic ecosystems and communities (AMAP, 2021). Arctic ecosystems and social systems have experienced rapid transformation due to severe changes related to cryosphere anomalies that have affected livelihoods, lifestyles, productivity, seasonality, weather patterns, precipitation, interactions of species in terrestrial, coastal, and marine environments (AMAP, 2021). Changes in the sea-ice extent, snow cover on land, and the rapid loss of perennial ice from the Greenland Ice Sheet are among the causes of fundamental and irreversible impacts affecting the cycling of carbon and greenhouse gases. The unique Arctic ecosystems associated with millennia-old ice shelves are at severe risk and in frank transition (Meredith et al., 2019). Climate change is the dominant driving force and the top stressor of communities, industries, and ecosystems. Arctic climate change is also posing a widespread additional layer of risks to safety, health, and well-being including severe damages to infrastructure affecting livelihoods and causing economic impacts to many different sectors essential to Arctic societies. Natural resources extraction, newly opened trading routes and economic activities like commercial fisheries, aquaculture, and cruise tourism have expanded severely in the Arctic since 2016, with dramatic implications for coastal communities’ livelihoods, vulnerable ecosystems, and an increasing demand for search-and-rescue services (IPCC, 2019; Meredith et al., 2019; Arruda, 2014). The effects of Arctic transformation are also felt far beyond the Arctic at global scale consisting in global sea-level rise, risks and opportunities associated with the opening of new maritime routes and facilitated access to fossil fuel reserves in sensitive area of marine protection with a serious potential for increasing atmospheric greenhouse gas concentrations. It brings a new dimension for the debate on exposure, vulnerability, disaster risk and resilience and further research is still necessary to well-establish more consistently the links between Arctic change, global weather patterns, and how to enhance Arctic environmental standards (IPCC, 2019). Exposure, vulnerability, disaster risk, and resilience are concepts that have been evolving along the last decades and gaining new dimensions according to the latest natural extreme events and findings from scientists and climatologists that have provided an enhanced range of evidence by allowing a better understanding on how to tackle risk and hazards associated to climate change impacts. According to

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Cardona et al. (2012, p. 69), the concept of “exposure refers to the inventory of elements in an area in which hazard events may occur.” Exposure occurs when the presence of people, livelihoods, species, ecosystems, environmental functions, services, resources, infrastructure, economic, social, cultural assets are in places and settings adversely affected (UNISDR, 2004, 2009). In some pieces of literature, it is common to find exposure being used as a synonym of vulnerability, but it is important to emphasize that these are distinct concepts. Exposure and vulnerability are distinct in nature because exposure is a necessary, but not sufficient, determinant of risk. Moreover, it is possible to be exposed but not vulnerable as the modification of structure and behavior can possibly mitigate a potential loss. On the other hand, to be vulnerable to a specific extreme event means to be exposed. Vulnerability can be understood as the propensity or predisposition to be adversely affected and it encompasses the notions of sensitivity or susceptibility to harm and lack of capacity to cope and adapt. Vulnerability and exposure have proved to be dynamic, experiencing variations across temporal and spatial scales, and depending on economic, social, geographic, demographic, cultural, institutional, governance, and environmental factors (UNDRR, 2019; UNDRO, 1980). The effects on natural and human systems are actual impacts, while hazards can be understood as: the potential occurrence of a natural or human-induced physical event or trend or physical impact that may cause loss of life, injury, or other health impacts, as well as damage and loss to property, infrastructure, livelihoods, service provision, ecosystems, and environmental resources. In this report, the term hazard usually refers to climate-related physical events or trends or their physical impacts (Hoegh-Guldberg et al., 2018, p. 178).

Risks result from the interaction of vulnerability, exposure, and hazard, configurating the potential for uncertain consequences affecting something of value that is at stake. In this sense, there is a probability of the occurrence of hazardous events or trends that are multiplied by the impacts if these events really occur as per Cardona et al. (2012, p. 69). By considering the fundamental attributes of natural and human systems, adaptation can be understood as the process of adjusting to actual or expected climate effects as well as moderating or avoiding harm by benefiting from the opportunities created by transformation or realigned paradigms and goals based on sustainable development (IPCC, 2014). Finally, resilience can be understood as “the capacity of social, economic, and environmental systems to cope with a hazardous event or trend or disturbance, responding or reorganizing in ways that the essential functions, identity, and structure, can be maintained while also keeping the capacity for adapting, learning, and evolving” (IPCC, 2014; Cardona et al., 2012, p. 70). Disaster risk reduction is defined in the UN International Strategy for Disaster Reduction (UNISDR) terminology as “action taken to reduce the risk of disasters and the adverse impacts of natural hazards, through systematic efforts to analyse and manage the causes of disasters, including through avoidance of hazards, reduced social and economic vulnerability to hazards, and improved preparedness

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for adverse events” (IPCC, 2021, p. 31). It is therefore tailor-made to help counteract the added risks arising from climate change. Adaptation is a fundamental part of this balance towards more resilient systems, and it will imply adjustments in ecological, social, or economic systems in response to actual or expected climatic stimuli and their impacts. It will require changes in processes, practices, and structures to moderate potential damages and, possibly, to benefit from opportunities associated with climate change in a responsible manner. This chapter deals with the means to build climate change adaptation and risk knowledge through preparedness and contingency best practices envisaging the future of Arctic landscapes and societies as they have been urged to adapt to risks and disasters in real time and for the future. Adaptation, risk reduction, and risk management policies and practices will be more successful if they consider the dynamic nature of vulnerability and exposure by including the notion of uncertainty and complexity along the stages of planning and application of coordinated contingency practices among the Arctic nations.

2 Management Strategies for Reduction of Daily Or Chronic Risk Factors Collaborative systems for crisis management take various forms depending upon location and the stakeholders. When designing strategies for managing risk factors for the Arctic, it is important to cover terrestrial and maritime risks based on sustained and coordinated climate ecosystem monitoring at key sensitive locations in combination with community-driven monitoring by applying a more consistent and holistic process of adaptation to climate change based on Indigenous and nonindigenous knowledge and data sets (Arruda & Krutkowski, 2017; Arruda, 2019; Arruda & Johannsdottir, 2022). As human activity increases in the region both on terrestrial and maritime environments, a new working group entitled “Search and Rescue Expert Group Chair of the Emergency, Prevention, Preparedness and Response Working Group” (Arctic Council EPPR, 2021) was created within the Arctic Council to attend to the expanded and expected demand of impacts of increased human activity in the Arctic in the years ahead. The experts’ group is active in tackling risks associated to terrestrial and maritime risk factors and they are categorized into ‘Search and Rescue Expert Group,’ ‘Marine Environmental Response Expert Group,’ and ‘Radiation Expert Group.’ These subgroups dedicate to develop practical preventive and remediation actions to improve preparedness and response to environmental and other emergencies by establishing guidance and risk assessment methodologies, but also by exchanging information and best practices regarding prevention, preparedness, and response to accidents and threats from unintentional releases of pollutants and radionuclides, and to natural disasters.

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The groups also coordinate response exercises and deliver training based on operational guidelines and on legally binding agreements like Search and Rescue (SAR) and Cooperation on Marine Oil Pollution Preparedness and Response (MOSPA) negotiated under the auspices of the Arctic Council (Arctic Council, 2017). These initiatives represent the coordination of shared competence and action for the Arctic risk assessment and management covering emergence preparedness in a maritime radiological/nuclear scenario (RADSAR), Arctic Oil Pollution emergencies, and other events requiring prompt response. Specific reference guides (Arctic Council Secretariat, 2021) were created with the purpose of engaging stakeholders and establishing methodologies for emergence response and these guidelines can be found at: • Radiological/nuclear risk assessment in the Arctic Council’s Emergency Prevention, Preparedness and Response (EPPR) Working Group Consensus Report • RADEX 2019 table-top exercise • Arctic Guardian joint table-top exercise—After Action Report • Arctic Oil Pollution Research and Development Workshop Report • Arctic Marine Risk Assessment Guideline Fact Sheet The representatives from the eight Arctic States have participated in various fora and working groups to mitigate risks and ensure safe, secure, and environmentally responsible activities in the Arctic. Increased maritime activity in the region intensifies the risks of maritime incidents as well as the need to plan and prepare for efficient and rapid pollution responses. The Arctic Coast Guard Forum (ACGF) and the Arctic Council’s Emergency Prevention, Preparedness and Response (EPPR) Working Group specifically address the areas of Maritime Emergence Response (MER) and Search and Rescue (SAR) for the Arctic marine environment by engaging Arctic stakeholders toward the convergence and coordinated action on best practices methodologies and the sharing of data sources to better understand, communicate, and incorporate specific Arctic Risk Influencing Factors (ARIFs) into the risk assessment process (EPPR, 2017). It is an undeniable reality that oil spills are a rising concern in the Arctic (Johannsdottir & Cook, 2019), despite the significant environmental and social impact assessment provided by the most important agencies on vulnerable human communities and animal species (DNV-GL, 2017). The harsh conditions in the region can make oil spill response extremely costly and challenging (Johannsdottir & Cook, 2019). To improve oil spill response in the Arctic marine environment, the EPPR conducted a specific study to amplify the understanding on potential different oil spill response systems based on ‘the Circumpolar Oil Spill Response Viability Analysis (COSRVA)’ that consists of an accurate web-based tool delivering meteorology and oceanography data obtained from climate and ocean models and useful to promptly respond to oil spills in a more consistent and efficient way. This system provides users key information on operational conditions to evaluate ten different oil spill response systems according to contingency and it can inform and orient oil spill planners and operators on how to develop their oil spill response systems in different regions. Systems like COSRVA will be imperative to ensure fast, efficient,

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and customized response to the specific conditions of oil accidents in the region (EPPR, 2017). These programs cover a range of environmental and societal factors that create or exacerbate the risks from natural hazards in the Arctic. Specific measures can also incorporate climate risk-related considerations in the development planning processes, macro-economic projections and sector plans based on environmental and natural resource management, climate risks in infrastructure projects, diversification of livelihoods, and adaptation activities for recovery from specific disasters.

3 Building Risk Knowledge The first step to manage risk is to understand it and to build knowledge about the identified risk. Some of the fundamental risks currently facing humankind are environment- and climate-related. Biodiversity loss, extreme weather, natural hazards, and human-made environmental disasters are examples of some of these risks that have been, lately, observed with more frequency not only in developing countries but in the developed world as well. Risks do not respect countries frontiers nor flags; they occur in a systemic and dynamic way according to the integrated nature of synergic socio-environmental interactions that, indistinctively, represent a continuous movement of coevolvement (Arruda, 2018). Socio-technical systems consist of how technology and social responses evolve together and how their coevolution affects planning, preparedness, and policies. This coevolution is possible when technological and societal responses evolve together and enable the creation and operation of new models of engagement among stakeholders (Arruda, 2018). Recent approaches to resilience of socio-technical systems related to disaster control and prevention include the ability to use nature-based solutions (UNDRR, 2021) and possibly self-organize, learn, and adapt over time to the severe impacts of climate change in sensitive areas of complex socio-environmental interactions. Based on lessons learned and past experiences of disaster risk management and on the new dimension of climate change in the Arctic with all its specificities, greatly improved and strengthened disaster risk management and adaptation is needed, as part of development processes to reduce future risk. Efforts to prevent and control risks in the Arctic are more effective when informed by knowledge, innovation, and education to build a culture of safety and resilience at all levels and, mainly, at citizen’s level. This is part of the concept of Arctic Citizenship (Arruda, 2019; Arruda & Johannsdottir, 2022) showing that all citizens understand and engage, as stakeholders, in an embedded process of adaptation, disaster risk control and reduction through specific actions of collating, exercising, and disseminating good practices in face of contingency case studies by participating in public information programs as well as on local collective and personal actions towards safety and resilience (IPCC, 2012). It is important to publicize community successes, provide culturally intelligible training to local communities in climate-related issues, but also promote change by developing education curricula based on climate adaptation and risk

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reduction principles (IPCC, 2012; Arruda, 2019). Equally important is to support research programs on resilience and risk prevention as well as improving mechanisms for knowledge transfer from science to application for risk management in climate-sensitive sectors based on a feasible and people-centred approach in accordance with the Sendai Framework for Disaster Risk Reduction 2015–2030 (IPCC, 2012; UNDRR, 2021). The application of previous successful programs and experiences in disaster risk management according to improved and customized Arctic standards as well as the appropriate approaches and methodologies for risk identification, reduction, transfer, and disaster management seems to indicate that, in the very near future, with an intensified human presence and industrial activity in the Arctic region, the practices of disaster risk management and adaptation can greatly benefit from a rights-based approach and from people’s active learning experience toward the connections between the environment and disasters. Additionally, practices can also advance when communities understand how to manage and respect the environment to improve well-being through Teaching programs of Eco-Disaster Risk Reduction (UNDRR, 2021). Advances can also be seen from an enhanced synergy among institutional, financial, political, strategic, and knowledge-intensive coordinated initiatives toward strengthening the sustainable use and management of ecosystems for building resilience to disasters.

4 Preparedness and Contingency Practices Modern operational management systems consist of not only identifying risks and hazards accurately, but also establishing the baseline for best practices application and designing well-defined procedures for inspection, monitoring and maintenance of pertinent protective systems (i.e., barriers, vessels, oil platforms, etc.) with the objective of mapping and implementing navigational, shipping, ship traffic risk assessment, oil spill, and general environmental risk assessments. It is a fundamental tool to accomplish Arctic environmental risk analysis based on the potential ecological and socioeconomic consequences of spill-related damage and vulnerability assessment related to different spill types through spill modeling and spill trajectory. To amplify the understanding and to strengthen disaster preparedness for effective response at all levels, it is important to engage Arctic stakeholders to agree on best practice methods, data sharing and availability, optimized communication and incorporation of specific Arctic risk influencing factors (ARIFs) into the risk assessment process. Risk assessments are fundamental for the selection and prioritization of risk reducing measures for safety and emergency preparedness, but the existing risk analysis methods and tools applied worldwide are neither sufficient nor customized enough to approach and address Arctic conditions (harsh weather, remoteness, etc.) (Arctic Council, 2017). EPPR is one of six working groups of the Arctic Council that aims at contributing to the prevention, preparedness, and response to environmental and other

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emergencies, accidents, and Search and Rescue (SAR). EPPR is responsible for conducting projects to address gaps, designing strategies, sharing information with stakeholders, collecting data, and collaborating with relevant partners on building capabilities and research capacity to attend the Arctic operations. It focuses on establishing risk assessment methodologies, coordinating response exercises, and training, and exchanging of information on best practices with regard to the prevention, preparedness and response to accidents and threats from unintentional releases of pollutants and radionuclides, and consequences of natural disasters (Arctic Council, 2017). The ‘Guideline for Arctic Marine Risk Assessment’ reflects a joint effort and collaboration involving EPPR Chair and secretariat, Norwegian Coastal Administration (NCA) and Det Norske Veritas (DNV) to map and evaluate marine hazards (i.e., ship grounding, collision, contact, fire/explosion, and foundering) and predicting the likelihood or frequency of hazardous events, their potential severity and impacts for the environment and local communities. To establish the risk assessment process (Arctic Council, 2017), the Guideline sets six steps of risk management process based on ISO 31000:2018, consisting in delineating scope, context and criteria; risk identification; risk analysis; risk evaluation; risk treatment; risk reports, by applying Arctic customization to fit the scope of mapping and addressing the arctic risk influencing factors. For instance, the Marine Risk Assessment considers the Arctic Risk Influencing Factors (ARIF) such as: • • • • • • • • • •

Ice Topside icing Low temperature Extended periods of darkness or daylight High latitude Remoteness Lack of crew experience Lack of emergency equipment Severe weather conditions The environment

The main challenges approached here as well as the best practices are related to Arctic sensitive environments and specific operational conditions related to maritime environment and land-based activities. In fact, best practices go beyond mandatory requirements described in regulation and policies and sharing best practices related to contingencies can contribute to safer operations, but it is undeniable that events can happen beyond the capacities of most well-equipped nations and institutions. Examples of events beyond the capabilities of agencies happened in the past and populate the vast literature of case studies of maritime accidents such as Torrey Canyon (1967), Piper Alpha (1976), Amoco Cadiz (1978), Erika (1999), Deepwater Horizon (2010) (Johannsdottir & Cook, 2019) and the MV Wakashio (2020). Accidents like these do not have place in the Arctic region due to the natural challenges to contain and remediate them adequately. Best practices in the Arctic need to be associated to the highest possible standards customized for the region on top

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of consolidated international standards as well as based on rigorous risk analysis of operations, reliable information, robust Health Safety and Environmental (HSE) systems, training, continuous improvement monitoring system, building up a strong culture of safety and preventive measures, reporting and data sharing, research, and development as per the criteria described in Table 4.1 (Det Norske Veritas, 2013). The risk assessment process in the Arctic involves specific sub-actions toward the identification of scope, context, risk, analysis, evaluation, treatment and reporting as per details in Table 4.1. Actions for prevention, preparedness, and response are carefully preplanned and adapted to the conditions and remoteness of the Arctic to optimize use of available resources and facilitate international cooperation through agreements and joint action policies developed in cooperation through bilateral and multilateral agreements with the intent of sharing resources and best practices. Such agreements specify how to operate joint response based on Risk Assessment process in specific contingencies across the Arctic as given in Tables 4.1 and 4.2. Moreover, approaches to risk control have been adopted as an attempt to eliminate hazards through inherent safe design of equipment, safety and warning devices, procedures and coordinated training exercises carried on by the Arctic nations in cooperation according to the latest programs of Best Practices in Marine Risk Assessment (ship traffic risk), shown in Table 4.2. The Circumpolar Oil Spill Response Analysis is a system that originated the Best Practices in Marine Risk Assessment (Arctic Council, 2017) (see Table 4.2). It represents the most concentrated efforts among the Arctic nations to perform preventive measures, preparedness plans, and contingency plans to account for the projected changes in existing hazards and new hazards related to maritime activity and oil and gas operations. Other specific measures in place in the Arctic due to the severe impacts of climate change lately relate to preparedness and Risk Exposure in Small and Remote Communities, Circumpolar Wildland Fire Project, Knowledge on New Low-Sulphur Fuels in the Arctic, Maritime Emergencies Potentially Releasing Radioactive Substances, Review of Legal Issues Related to the MOSPA Agreement, Radiological and Nuclear Risk Assessment in the Arctic and Arctic Lessons Learned Arena (Arctic Council, 2017; DNV-GL, 2017; EPPR, 2017). Actions of preparedness in terrestrial systems consist mainly of building evacuation mechanisms, creating shelter facilities and preparedness plans for settlements and livelihoods to manage permanent change and provide support to community-­ based preparedness initiatives. Resilience building and early warning systems are also a priority requiring the use of climate risk-related information in terms of land-­ use planning, water management, environmental and natural resource management systems and coordinated measures to envisage community protection through coastal wave barriers, river levees, flood ways, and flood ponds (DNV-GL, 2017). Designing, architecture, and engineering practices can also create safety nets and efficient adaptation mechanisms, Arctic technological competence, and a culture of safety at citizen’s level.

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Table 4.1  Risk assessment process Scope, context, and criteria Define the objective

Risk identification Define accidental events and describe risks

Define the risk acceptance criteria

Consider Arctic risk influencing factors

Consider the internal and external context

Consider human and technical performance in Arctic conditions

Risk analysis (a) Ship traffic risk Calculate the likelihood of event occurrence and potential consequences Best practice quantitative marine risk calculation tools Best practice on including ARIFs in marine risk calculation

Risk evaluation Risk treatment Assess Risk control acceptable risks and mitigating measures

Polar operational limitations assessment risk indexing system (POLARIS) (b) Environmental risk and sensitivity Best practices for environmental risk assessment Spreading and fate of oil spill Vulnerability assessment Environmental consequence and risk

Cost–benefit analysis in risk reducing measures

Testing efficiency in barriers

Approaches to Parallel activity controlling B: Monitoring risks and review

Applying the ALARP principle

The organizational aspect and chain of responsibility

Contemporary risk management approaches and the managerial review

Considerations toward risk control options Source: Arctic Council (2017)

Recording and reporting Parallel activity A: Communication and consultation

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Table 4.2  Current best practices in the Arctic region Best practices in marine risk assessment (ship traffic risk) OpenRisk (2018) Guideline for regional risk management to improve European pollution preparedness and response at sea AISyRisk model: Be-aware: IWRAP Marin risk SAMSON model: model: model: Barents observer article: Be-aware IWRAP MK2 Area risk assessment Future Governance of summary introduction methodology for ship-source environmental risk report spills in Canadian waters Best practices in environmental risk assessments Assessment of marine oil spill risk and environmental vulnerability for the state of Alaska Risk assessment for marine spills in Canadian waters phase 1: Oil spills south of 60th parallel Risk assessment for marine spills in Canadian waters. Phase 2, part B: Spills of oil and select HNS transported as bulk north of the 60th parallel north Area risk assessment methodology for ship-source spills in Canadian waters Marine environmental risk assessment Greenland Environmental risk assessment of oil spills from shipping activities around Svalbard and Jan Mayen Subregional risk of spill of oil and hazardous substances in the Baltic Sea (BRISK) BE-AWARE II OpenRisk (2018) Guideline for regional risk management to improve European pollution preparedness and response at sea Source: Arctic Council (2017)

5 Conclusions This chapter aimed to explore the ways of building climate change adaptation and risk knowledge through preparedness and contingency practices to engage Arctic stakeholders to identify, assess, and prioritize measures of safety, emergency preparedness, and risk reduction (Farzaneh et al., 2014). It is based on an enhanced framework of existing risk analysis and best practice methods, by optimizing communication and the incorporation of specific Arctic risk influencing factors (ARIFs) and customized standards into the risk assessment process. It is highlighted that the efforts and programs will be more effectively performed locally and regionally when informed by knowledge, innovation, and education to build a culture of safety and resilience at all levels mainly at a citizen’s level as per the realization of the Arctic citizenship (Arruda, 2019) concept. As human activity increases in the region both on terrestrial and maritime environments, new collaborative systems for crisis management engage the stakeholders in specific strategies for managing risk factors by covering terrestrial and maritime risks based on sustained and coordinated climate ecosystem monitoring in combination with community-driven monitoring based on Indigenous and nonindigenous knowledge and data sets. These are active initiatives of coordination of shared competence to provide preparedness and prompt emergence response.

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The systems discussed in this chapter are evolving in terms of preparedness as per the discussion in Sects. 3 and 4. Considering that these systems are evolving, they should be able to adapt to a changing/worsening situation. Recent approaches to resilience of socio-technical systems related to disaster control and prevention include the ability to use nature-based solutions (UNDRR, 2021) and possibly self-­ organize, learn, and adapt over time to the severe impacts of climate change in sensitive areas of complex socio-environmental interactions. Finally, preventive practices can also advance significantly when communities understand how to manage and respect the environment to improve collective well-being through teaching programs of Eco-Disaster Risk Reduction (UNDRR, 2021), but it also can be highly enhanced through the synergy among institutional, financial, political, strategic, and knowledge-intensive coordinated initiatives toward strengthening the sustainable use and management of ecosystems for building resilience to disasters.

References AMAP. (2021). Arctic climate change update 2021: Key trends and impacts. Summary for policy-­ makers (16 pp.). Arctic Monitoring and Assessment Programme (AMAP). Arctic Council. (2017). Guideline Arctic Marine Risk Assessment. Best practice methods and data sources for conducting regional and area-wide risk assessments concerned with ship traffic and operations in Arctic. Available online: https://oaarchive.arctic-­council.org/bitstream/ handle/11374/2549/Arctic-­Marine-­Risk-­Assessment-­Guideline_Fact-­Sheet.pdf?sequence=1& isAllowed=y Arctic Council Secretariat. (2021). Arctic Council Secretariat Annual Report 2020. Available online: https://oaarchive.arctic-­council.org/handle/11374/2568 Arruda, G. M. (2014). Global governance, health systems and oil and gas exploration. International Journal of Law and Management, 56(6), 495–508. Arruda, G. M. (2018). Renewable energy for the Arctic: New perspectives (230 pp.). Routledge. Arruda, G. M. (2019). Sustainable energy education in the Arctic: The role of higher education (1st ed., 278 pp.). Routledge. Arruda, G. M., & Johannsdottir, L. (2022). Corporate social responsibility in the Arctic: The new frontiers of business, management, and enterprise (240 pp.). Routledge. Arruda, G. M., & Krutkowski, S. (2017). Social impacts of climate change and resource development in the Arctic: Implications for Arctic governance. Journal of Enterprising Communities: People and Places in the Global Economy, 11(2), 277–288. Cardona, O. D., van Aalst, M. K., Birkmann, J., Fordham, M., McGregor, G., Perez, R., Pulwarty, R. S., Schipper, E. L. F., & Sinh, B. T. (2012). Determinants of risk: Exposure and vulnerability. In C. B. Field, V. Barros, T. F. Stocker, D. Qin, D. J. Dokken, K. L. Ebi, M. D. Mastrandrea, K.  J. Mach, G.-K.  Plattner, S.  K. Allen, M.  Tignor, & P.  M. Midgley (Eds.), Managing the risks of extreme events and disasters to advance climate change adaptation (A special report of working groups I and II of the Intergovernmental Panel on Climate Change (IPCC)) (pp. 65–108). Cambridge University Press. Det Norske Veritas. (2013) Recommended practices for Arctic oil spill prevention (123 pp.). Det Norske Veritas AS. DNV-GL. (2017). Marine environmental risk assessment  – Concerning waters in and adjacent to Greenland and the Arctic. Marine environmental risk assessment  – Greenland. Defence Command Denmark Report 2014-0951, Rev. E. Document No.: 1C0M8QD-17 (2015-04-17). (191 pp.). Høvik: DNV GL AS DNV GL Oil & Gas.

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EPPR. (2017) Circumpolar oil spill response viability analysis: Technical report (134 pp.). Arctic Council Secretariat. Farzaneh, M. R., Eslamian, S., & Mirnezami, S. J. E. (2014). Climate change: Uncertainty, impact, and adaptation. In S.  Eslamian (Ed.), Handbook of engineering hydrology, Ch. 8, Vol. 2: Modeling, climate changes and variability (pp. 127–146). Taylor and Francis, CRC Group. Hoegh-Guldberg, O., Jacob, D., Taylor, M., Bindi, M., Brown, S., Camilloni, I., Diedhiou, A., Djalante, R., Ebi, K.  L., Engelbrecht, F., Guiot, J., Hijioka, Y., Mehrotra, S., Payne, A., Seneviratne, S. I., Thomas, A., Warren, R., & Zhou, G. (2018). Impacts of 1.5 °C global warming on natural and human systems. In V. Masson-Delmotte, P. Zhai, H.-O. Pörtner, D. Roberts, J.  Skea, P.  R. Shukla, A.  Pirani, W.  Moufouma-Okia, C.  Péan, R.  Pidcock, S.  Connors, J.  B. R.  Matthews, Y.  Chen, X.  Zhou, M.  I. Gomis, E.  Lonnoy, T.  Maycock, M.  Tignor, & T. Waterfield (Eds.), Global warming of 1.5 °C. an IPCC special report on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Cambridge University Press. IPCC. (2012). Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of working Groups I and II of the Intergovernmental Panel on Climate Change (C.B.  Field, V.  Barros, T.  F. Stocker, D.  Qin, D.  J. Dokken, K.  L. Ebi, M. D. Mastrandrea, K. J. Mach, G.-K. Plattner, S. K. Allen, M. Tignor, & P. M. Midgley, Eds.) (582 pp.). Cambridge University Press. IPCC. (2014). Summary for policymakers. In C. B. Field, V. R. Barros, D. J. Dokken, K. J. Mach, M. D. Mastrandrea, T. E. Bilir, M. Chatterjee, K. L. Ebi, Y. O. Estrada, R. C. Genova, B. Girma, E. S. Kissel, A. N. Levy, S. MacCracken, P. R. Mastrandrea, & L. L. White (Eds.), Climate change 2014: Impacts, adaptation, and vulnerability. Part A: Global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change (p. 32). Cambridge University Press. IPCC. (2019). IPCC special report on the ocean and cryosphere in a changing climate (H.O.  Pörtner, D.  C. Roberts, V.  Masson-Delmotte, P.  Zhai, M.  Tignor, E.  Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, N. M. Weyer, Eds.). Cambridge University Press. In press. IPCC. (2021). Summary for policymakers. In V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou (Eds.), Climate change 2021: The physical science basis. Contribution of working group I to the sixth assessment report of the intergovernmental panel on climate change. Cambridge University Press. Johannsdottir, L., & Cook, D. (2019). Systemic risk of maritime-related oil spills viewed from an Arctic and insurance perspective. Ocean & Coastal Management, 179, (1 September 2019), 104853. Meredith, M., Sommerkorn, M., Cassotta, S., Derksen, C., Ekaykin, A., Hollowed, A., Kofinas, G., Mackintosh, A., Melbourne-Thomas, J., Muelbert, M. M. C., Ottersen, G., Pritchard, H., & Schuur, E. A. G. (2019). Polar regions. In H.-O. Pörtner, D. C. Roberts, V. Masson-Delmotte, P.  Zhai, M.  Tignor, E.  Poloczanska, K.  Mintenbeck, A.  Alegría, M.  Nicolai, A.  Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC special report on the ocean and cryosphere in a changing climate. In press. UNDRO. (1980). Natural disasters and vulnerability analysis: Report of Expert Group Meeting, 9–12 July 1979 (48 pp.). Office of the United Nations Disaster Relief Coordinator. UNDRR. (2019) Global assessment report on disaster risk reduction (425 pp.). United Nations Office for Disaster Risk Reduction (UNDRR). UNDRR. (2021). Nature-based solutions for disaster risk reduction. Words into action (259 pp.). United Nations Office for Disaster Risk Reduction. UNISDR. (2004). Living with risk: A global review of disaster reduction initiatives (429 pp.). United Nations Office for Disaster Risk Reduction. UNISDR. (2009). Terminology on disaster risk reduction (30 pp.). International Strategy for Disaster Reduction.

Chapter 5

Ecological Resilience for Transformative Climate Change Mitigation and Adaptation Keith Morrison and Moleen  Monita Nand

Abstract  Ecological resilience enables the transformation of social-ecological systems (SES). The transformation of SES currently needs both adaptation to and mitigation of climate change. The transformations that ecological resilience enables emerge through evolutionary adaptation. With SES, evolutionary adaptation includes the processes whereby regulatory, governance, and economic structures, as well as technologies are selected. Ecological resilience within SES means there is sufficient diversity and flexibility of these structures and technologies to ensure institutional and technological choices are proactively made to avoid the occurrence of disasters—to enhance disaster risk reduction (DRR). Through this process of proactively seeking DRR, appropriate transformations of SES incrementally emerge. This chapter outlines a framework for DRR developed over three decades of research in the South Pacific on sustainable development and climate change adaptation. The framework conceptualizes the various processes that nurture ecological resilience in SES, from communities that are guided by cultural traditions, to institutions and regulatory authorities, to political processes of governance. The processes are modeled as nested recursive soft system methodologies (Bazrkar et al., Urbanization and climate change, handbook of climate change adaptation, Springer, 2015). The chapter starts by outlining and developing SES theory to show how ecological resilience enables necessary transformations to incrementally emerge. Then the chapter develops how the catastrophes being brought by climate change can avoid becoming disasters, through the development of ecological resilience; how ecological resilience enables DRR in face of climate change. It is also shown how the possible transformations that ecological resilience entails, will enable mitigation of climate change as well as adaptation to climate change. Moreover, it is also shown how the possible transformations potentially also enhance well-being, and hence sustainable development. It is shown that the causes of climate change are also the causes of social ill-being: the socioeconomic and ecological crises are linked, as are K. Morrison (*) Sustainable Community Development Research Institute, Aotearoa, New Zealand M. M. Nand The University of Adelaide, Adelaide, Australia © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_5

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the solutions. The chapter ends by exploring paradigms of ecological engineering and ecological economics, which can be used within the overarching framework for DRR, to guide the development of possible transformations of SES, for ecological resilience. Keywords  Climate change · Ecological resilience · Mitigation · Adaptation · Socioeconomic

1 Introduction There is near unanimous recognition of the need for an urgent focus on ways to mitigate climate change, as well as developing means for climate change adaptation because of climate change that has already started, and future change that is now inevitable. The science is clear, even in its imprecision and uncertainty. The challenge is no longer one of modeling what can or is likely to happen. Rather the challenge is how to use the knowledge to mitigate climate change, and to progress adaptation to climate change that is already underway. It is commonly and correctly stated that the issue is one of political will. But such statements can easily take on an air of cynicism unless the nature of political will is understood. The notion of political will is concerned with leadership. It is also concerned with processes of social transformation. There are many ways that this is being addressed. It has already captured the political imagination of creatives and youth worldwide. This intuitive response is indicative of dynamics at play that need to be understood. In this chapter, we frame an analysis of the dynamics in terms of socialecological systems (SES). It is an analysis that draws upon interdisciplinary approaches, to find a place for the humanities as well as sciences. In particular, the role of cultural traditions, as analyzed by anthropology, is incorporated, along with the central role of civil society as analyzed by political science. But also included are insights from psychotherapy, philosophy, economics, the mathematics of catastrophes, management decision-making theory, and, of course, human ecology. The interdisciplinary study uses the transdisciplinary approach of systems theory, covering the emergence of SES through complexity theory, as well as recursive adaptive human activity systems through soft systems methodology. A systems approach to coevolutionary theory is used to frame the dynamics, to provide some pointers as to what can be done to enhance the political will needed to ensure the climate emergency is addressed, to avoid disastrous events as much as possible. A nested soft system framework is provided, which emphasizes the role of ecological resilience, but also how it is inseparable from psychological resilience and social resilience, if ecological resilience is to be fine-tuned to be most effective. The optimal opportunity is outlined, providing an ideal framework to aspire to. This is in keeping with a general systems theoretical approach. The dynamics are outlined,

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thus giving opportunities to seek optimal solutions. This is the best that can be offered. This chapter provides such a framework to offer hope and opportunity. The hope is that incremental coevolutionary adaptation provides a pathway to optimize DRR for climate change mitigation, climate change adaptation, as well as social well-being. It can provide a reference point from which to plan and to act, for everyone. The role of leadership is addressed, and emphasized that it is something any and everyone has a role to play in.

2 Resilience and Social-Ecological Systems (SES) Resilience is a concept that is used by different disciplines to mean different things. There is nevertheless a common thread to what is referred to, which can be recognized by discussing the potential resilience of SES. This is carried out through interdisciplinary discussion of resilience and SES, as they are differently understood by the disciplines of engineering, ecology, and psychology, among others. First, however, it is necessary to define SES. A SES refers to human social activity that is recognized as participating within ecological processes, of interacting with other species. What is unique about such human activity systems, in contrast to that of other species, is the degree of variability and flexibility that the influence of social organization has on the activity of individuals, of phenotypes. An SES refers to the analysis of social organization as an ecological entity. Therefore, social organization can be analyzed as coevolving with its environment, according to ecological theory. This gives a particular framing of theory for change in socialized human activity, its adaptation and transformation, termed SES theory (Chaffin & Gunderson, 2016). There are also multiple frameworks and methodologies that have been developed that implicitly implement principles pertaining to SES theory. An early one was soft systems methodology (SSM), first developed by Checkland (1982). Implementation of SSM over several decades among communities in the South Pacific for sustainable community development and climate change adaptation, has resulted in the development of the tri-SSM framework (Morrison, 2021), in explicit recognition of the nested hierarchical and complex processes of change in human activity systems (HAS), to use Checkland’s (1982) term, within ecological processes. There has been and remains widespread use of SSM, especially in the fields of education and health care, for example, Sankaran et  al. (2008), Zeleznik and Vosner (2017), Augustsson et al. (2019), and Morrison (2021). Other more recently developed frameworks that implicitly include principles of SES theory include Transition Management (Loorback, 2010; Morrison, 2019). Resilience is a key ecological principle that is essential to analysis of SES. Indeed, the moniker for a dedicated group of academics researching SES is the Resilience Alliance (Cote & Nightingale, 2012). The overarching concept of resilience that is referred to in relation to SES is that of ‘ecological resilience.’ Gunderson (2000) defined ‘ecological resilience’ and did so to contrast it to what they defined as ‘engineering resilience.’ They recognized that there were two different yet related uses of

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the term resilience, by ecologists and engineers respectively. Both are relevant for SES analysis, especially in relation to disaster risk reduction (DRR). But there are also other types of resilience that have been defined, which are also relevant to analysis of SES. Psychological resilience (Hone, 2017; Ong et al., 2006; van der Kolk, 2014), which addresses how it is human persons who participate in and make change to adapt and transform SES, and who suffer disasters. Associated with this is social resilience (Goleman, 2006, Keck & Sakdapolrak, 2013), which refers to the collective manifestation of psychological resilience to ensure social cohesion and coherent activity, or lack of it.

2.1 Ecological Resilience Compared to Engineering Resilience There are clear features to all four types of resilience: ecological, engineering, psychological, and social. Engineering resilience is perhaps the most straightforward and intuitive. It refers to the ability to bounce back to the original form. The link between engineering resilience and ecological resilience can be understood by the process of design, which is emblematic to engineering. Engineering resilience comes from designing to ensure that stress that is put onto components of a system does not cause trauma to the components. In other words, deformation that occurs due to stress on the components is reversible. The system bounces back to how it was originally. But often engineering design also ensures that certain components suffer trauma and deform irreversibly before other components, enabling the overall system to remain safe, to avoid a disaster, even though the engineered structure, for example a building, is no longer functional. In such cases, while disaster has been avoided, bouncing back has not been possible. Engineering resilience is not present. Of course, failure to remain functional may avoid a disaster in the short term, but it may help initiate another one in the longer term. Therefore, it is necessary to also consider how to maintain functionality for DRR. This is where ecological resilience comes in. To ensure ongoing functionality, alternative structures must coexist to replace the function of the safely failed structure. Hence, diverse structures must coexist so that there is a sufficient range of structures able to cope with the range of possible environmental impacts. In other words, there must be sufficient redundancy in the overall system for it to remain functional, as well as avoiding disasters as they potentially arise, by ensuring that each component that does fail does not by itself result in either disaster or loss of functionality. Such a system has ecological resilience. It enables bouncing back, but to something different, and if done well, it can be to something better, to make an opportunity out of adversity. But the question begging to be asked is: Why and when is a composite system of sufficient redundancy, comprised of diverse systems, superior to a single structure that has the engineering resilience to be able to weather all possible environmental impacts? The answer is that it is usually more efficient, and is more efficient wherever and whenever recursive or repeated processes are participated in. If repeated

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reconstruction of systems occurs, there is the opportunity to efficiently coevolutionary adapt to transform systems in response to environmental change, with even opportunity to enhance functionality through the process. This is more efficient than constructing an unchanging system able to weather all possible environmental change over the period of concern. Also, if the period of concern is open-ended, then a composite system will not only be more efficient, it is necessary to avoid eventual disaster. It is then necessary for DRR. Sustainable development has an open-ended period of concern, as the aim is to not compromise the well-being of future generations. Therefore, concern for DRR as a feature of sustainable development, requires design of systems with composite structures for requisite redundancy to be effective, while also being the most efficient. Ecological resilience is required. Fortunately, there is an exemplar par excellence for how to do so. Biological composite structures have coevolved over billions of years to form ecologically resilient systems. Ecological resilience is necessary for biological systems. Ecological resilience is selected for by biological coevolution of endless repeated processes of reproduction. The need for efficiency is due to the evolutionary pressure driven by selection in a situation of long-term limited resources. The same applies with SES. The evolutionary pressure on SES is due to the limited structures that can be designed, and even less constructed. The same applies to policies, programmes, and projects that are developed and implemented. There is also an intrinsic limit to laws that can be implemented by regulatory authorities, and in technical design, because functionality requires lack of ambiguity. Where SES and biology differs is in the mechanism for growth. In biology it is reproduction. In SES it is the design and construction of technology, institutions, and institutional arrangements, to increase the implementation of specific HAS. In SES, it is carried out partly through the implementation of rules in policies, programmes, and projects. It is also partly carried out by use of scientific laws, for use by regulatory authorities, and for technical design of engineered physical and digital structures. Learning to develop ecological resilience from understanding the exemplar given by biological systems can minimize selection through disasters that force change in HAS. Such learning can assist DRR. Ecosystem-based disaster risk reduction (ecoDRR) is partial recognition of this (UNDRR, 2020). The promotion by eco-DRR through use of ecosystem services to carry out DRR does help enhance ecological resilience. But it does not get to the essence of ecological resilience; not least because it is debatable whether reliance on ecosystem services is always the most economically efficient engineering solution. The community-based, integrative and collaborative interdisciplinary approaches also promoted by eco-DRR are closer to the essence of what has to be understood. The reason can be seen from considering the roles of psychological and social resilience in SES. But first, the general principle that drives the need for efficiency has to be understood. The general principle that drives the need for efficiency is also what drives coevolution. What needs to be emphasized is that it is not growth, whether biological reproduction or replication of rules and laws. Rather, it needs to be recognized that growth is a necessary derivative feature of how to maintain functionality.

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Growth is not an end in itself. It is tautological to consider that it is. Moreover, functionality can be appreciated in multiple ways. It is perceived differently when considering ecological resilience, psychological resilience, and social resilience. When considering ecological resilience, the underlying principle for functionality can be understood in terms of the 2nd Law of Thermodynamics. The 2nd Law of Thermodynamics can be stated as recognition that the most statistically likely future states are ones that are a result of the fastest dissipation of an energy differential. Furthermore, in far-from-equilibrium situations, dissipative structures emerge to increase the rate of dissipation. The simplest emergent dissipative structures are circulation patterns. Biological structures are dissipative structures, which emerge to most rapidly dissipate the energy differential across the biosphere. So clear is this principle that a measure of ecosystem health can be gained by infrared reading of energy radiating from ecosystems (Swenson, 1997). The lower the radiated energy, the higher is the ecosystem health. Given that the 2nd Law of Thermodynamics refers to what is statistically most likely, ecosystem health, inevitably emerges long term. Ecosystem health refers to what is most likely to emerge on planet Earth due to the biosphere. The movement toward ecosystem health is a deep direct emergence that coevolutionary processes manifest. This is significant because current anthropogenic climate change is increasing the energy differential across the biosphere. Therefore, ecosystem health is the inevitable process that will dissipate the energy causing increase in climate temperature, and so what will eventually inevitably mitigate climate change. Even though degradation of ecosystems is currently part of the process causing anthropogenic climate change, to be able to continue to do so can be expected to become an increasingly unlikely human activity. It is not a resilient activity. Rather, what will become increasingly more likely HAS, will be ones that increase ecosystem health, as these are more resilient and more likely to be selected for by coevolution. They are what are most likely, and so planning for them is more likely to avoid disastrous coevolutionary events of collapse that select against it. It is the best opportunity for DRR. Planning for other events is more likely to increase the chance of disastrous events. The generational change in attitudes and values toward the natural environment, already found in societies worldwide, indicate a manifestation of this. But the changes in attitudes and values are only part of a process that transforms SES to enhance rather than degrade ecosystem health. To understand how transformation of SES occurs to increase ecosystem health, first of all reproduction, as a necessary derivative of increasing ecosystem health and ecological resilience, has to be understood. Functionality for ecological resilience is ecosystem health. For psychological resilience it is well-being. For social resilience it is civil society. What is common to all these three types of resilience is that they entail participation in coevolutionary processes that maximize the dissipation of the energy differential across the biosphere. To maximize dissipation requires for the emergent dissipative structures to be able to change. This is carried out through use of indirect emergence (Sharpe, 2003). Indirect emergence uses information as code with which to make copies of emergent dissipative structures. Variation in the code produces changes in the

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emergent structures. The code for biological coevolution is genetic. For SES it is symbolic language. But also, for indirect emergence to operate to enable change, a recursive process involving discontinuity is required. In biological processes, it is death. Death is necessary for development of new genotypes. In SES, the discontinuity is the need to make decisions anew, through re-symbolizing to reconstruct HAS. For coevolutionary selection to enable changes in biological structure to emerge there has to be the ability to reproduce potential adaptations, or new forms of genotypes. Similarly, for coevolutionary selection to enable change in SES, there has to be the ability to produce potential adaptations, or transformations, of HAS. Then resource limitations on the natural ability to reproduce genotypes and HAS, provide coevolutionary selection with the necessary pressure for adaptation to emerge, and for this to be encoded genetically and by symbolic language, respectively.

2.2 Psychological Resilience and Social Resilience Psychological and social resilience both contribute to the ecological resilience of SES. Both psychological resilience and social resilience are features of recursive processes that enable the transformation of SES. But the human nature comprising SES is not purely biological. Therefore, human nature is not fully immersed in coevolution. It is composite, comprised of biological nature as well as nature that engages with symbols, and usually termed noetic or spiritual nature. In terms of DRR, composite (noetic and biological) human nature enables human persons in face of biologically naturally occurring catastrophes, to experience disasters, and to avoid them. Humans are able to be proactive in face of natural processes, because of the ability to symbolize natural processes, to understand them. But, to the extent there is interaction with natural processes, including natural catastrophes, human persons and societies still participate in coevolutionary processes, which select for ecosystem health. Nonetheless, because humans constituting SES are able to proactively enhance ecosystem health, SES are able to transcend to some degree coevolutionary selection. Unlike purely biological structures and the coevolution of species, transformations of SES are not made possible by recursive process constituted by biological death and biological reproduction. Rather they are made possible by temporary intervals transcending socialized thinking. This means that the symbols used to think with to code the structure of human socialized activities, are temporarily relinquished. These intervals create a recursive process of moments of innovative creative free-will, where decisions are made, to think differently, to symbolize anew, to code new possible HAS. There are levels of depth to these decisions. At their most shallow, they are consumer choices between various utilities. At their deepest, they are periods of liminality, of creativity and innovation, facilitated by religious rituals to consider anew what is of essential and ultimate meaning and purpose.

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Both psychological resilience and social resilience require participation in the deepest level of decision-making. The characteristics of psychological resilience are threefold: hope and faith to be continually learning to discover meaning; connection with others, including with the natural environment; and discernment to coexist with good and bad, whilst choosing the good (Hone, 2017; Morrison, 2021; van der Kolk, 2014). These three facets enable a person to avoid getting stuck in a rut. They provide adaptive capacity to discover opportunities to enhance well-being, while simultaneously avoiding the possibility of maladaptation, to avoid participation in disasters. They empower freedom to be proactive to enhance well-being through meaningful participation with others. It is the ability to move toward engagement with others in shared well-being. It has long been argued by prominent cultural anthropologists that the role of religious rituals is to regularly facilitate this creative liminal experience and communitas1 (Turner, 1969). But human nature is still partly biological. Therefore, the biological coevolutionary process still selects for SES structures enhancing ecosystem health. Enhancing ecosystem health requires coherent solidarity of human persons’ socialized activities within an SES. Coherent solidarity of persons in an SES is what communitas nurtures. It is not merely an emotional state, but a dynamic process of continual learning and implementation to ensure the collective needs of all in the SES are met, through utilizing ecosystem services, which are sustained by simultaneously providing ecosystem services to other species. Enhancing ecosystem health is a consequence of this mutual provision of ecosystem services within an SES’s ecosystem. Therefore, because human psychological resilience nurtures mutual provision of ecosystem services as an intrinsic aspect of maintaining human social well-being, psychological resilience in humans is selected for by biological coevolution. Ecosystem health is therefore congruent to maximum opportunities to access resources for the well-being of all. The thinking and activities entailed by psychological resilience are open-ended to ever increase new possibilities. The reason why decisions made with psychological resilience are open-ended is that they are cocreated through engagement with others in dialogue, including attentiveness to the needs of other species and the ecosystems services they can provide. Hybridity of thought occurs, increasing new possibilities and the potential diversity of decisions to be chosen from and implemented. This contrasts with maladaptation due to loss of psychological resilience, which is characterized by frustration at, and desperation in face of, the limiting of opportunities, which increases psychological stress until trauma is experienced, and a disaster is caused (Hone, 2017; Morrison, 2021; van der Kolk, 2014). Social resilience is inseparable from psychological resilience. They complement each other. Social resilience refers to maintaining coherent solidarity of human persons in a community of well-being. Social resilience refers to the maintaining of a set of SES meta-structures that both nurture psychological resilience and well-being, and hence also ecosystem health. The set of SES meta-structures can be characterized as civil society, where the foundation is provided by cultural

 Communitas refers to experience of empathy and compassion for others.

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traditions. Cultural traditions include religious rituals that nurture the recursive liminal intervals necessary for the deep decision-making necessary to maintain psychological resilience. There are two pillars sitting on the foundation, which hold up civil society. On one side, there are institutions implementing laws and rules of regulatory processes, for education and health care, conservation, and research generally, including for technological innovation. On the other side, there are economic processes that ensure the needs of all in the society are met through various intersecting forms of reciprocity, from markets to charities, to mutual gift-giving, to state provision of services. The various forms of reciprocity are engaged in by a range of economic institutions, from tech businesses to NGO charitable trusts, to hospitals and schools. A civil society is the emergence of a coherent and integrated SES maintaining social well-being, and hence ecosystem health. They are held up by these two pillars on the foundation of cultural traditions. Like cultural traditions nurturing psychological resilience, the two pillars of civil society also maintain recursive processes to maintain social resilience. Institutions implementing laws and rules recursively carry out monitoring of indicators of human needs, and of natural processes that provide resources (ecosystem services) to satisfy human needs. The recursive monitoring provides a continuous update of needs needing to be addressed, and also of opportunities to be able to satisfy needs. Linking the recognition of human needs and the means by which to satisfy them, are economic institutions, or to use the term of economists Max-Neef et  al. (1991), ‘satisfiers.’ Monitoring is also carried out to analyze how effective and how efficiently satisfiers are at fulfilling needs, given the resources (ecosystems services) that are available. Monitoring provides information, and hence opportunities to adapt the means used by an SES, to satisfy the needs of all for social well-being. Social resilience is achieved to the extent monitoring regimes discover pathways for adaptation within coevolution to enhance well-being. Monitoring enables participation in natural processes to fulfill the needs of all, while, and through enhancing ecosystem health. By doing so, monitoring enables DRR and avoidance of disastrous loss of well-being.

2.3 Transformation of SES Through Coevolutionary Adaptation Psychological resilience and social resilience maintain freedom for open-ended exploration of opportunities for adaptation, through regular participation in cultural traditions, and by coherent monitoring of human needs, natural processes, and the effects of human activities on natural processes. The freedom, however, is not absolute, to avoid overconfidence that interferes in the recursive reevaluations that are continually required. Regular participation in cultural traditions and monitoring regimes are designed to enable regular intervals of unknowing to break overconfidence, to insist upon the need to be careful and cautious by regularly looking at

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things afresh. It is a means to adapt, in face of natural variability and catastrophic change. But it is just as importantly, also an opportunity for learning, to gain meaning and hope, whereby the composite human nature of a person has the growth of its noetic component nurtured through attentiveness to its biological component’s participation in natural material and biological processes. The variability, including catastrophic changes intrinsic to natural material and biological processes, provide the opportunity for the noetic component of human nature to grow in understanding, and hence to empower creative freedom of the noetic component of human nature. But the freedom remains ironically bound by natural material processes. This is because the empowerment of the freedom of the noetic component of human nature leads potentially to human interpretations and activities that are potentially maladaptive as well as adaptive. For example, the development of modern science has been utilized to create technologies causing global ecological degradation and anthropogenic climate change, as well as learning how to enhance ecosystem health and to mitigate and adapt to climate change. There is a requisite empowerment of freedom, which is a stable expression of freedom, that provides the maximum possible sustained level of freedom. Requisite freedom is maintained to avoid unwitting, through overconfidence, undermining of the freedom of the noetic component of human nature. Constraints are put on freedom, for the sake of freedom. This is what psychological resilience and social resilience ensure, through insistence on regular humble participation in cultural traditions, and continual regular carrying out of monitoring of human needs, natural processes, and the effect of human activities on natural processes. That there is a requisite level of freedom is a principle well known in a different guise by psychotherapy, where it is recognized that optimal pleasure comes from a requisite level of pleasure, maintained by placing limits on pleasure, through constraints provided by civil society (Santner, 2001; Verhaeghe, 2014). Or in other words, by moderation. Civil constraints are a means of avoiding the experience of natural constraints that brings greater loss of pleasure, due to disastrous changes that will otherwise naturally occur. The constraints provided by civil society, both by cultural traditions, and by rules and laws, provide scaffolding that maintains a stable empowerment of requisite freedom and moderation. The scaffolding is maintained by what unites the biological and noetic components of human nature, namely, emotions. Emotions provide a bodily experience that is reflective of noetic experience, and so provide a center, the heart, for both a person’s noetic perceptions and physical bodily perceptions. Emotions provide sensitivity to both natural variability and natural catastrophic change, as well as noetic hope of what is possible, to guide adaptation to maintain and nurture psychological resilience. Emotional intelligence is key to discerning between maladaptation and adaptation (Nussbaum, 2001; Damasio, 2003; Goleman, 2009). That which is emotionally experienced as peaceful is stable and balanced adaptation. It is the optimal state of freedom, and inseparable from noetic hope of what is possible. Moreover, because emotional intelligence is nurtured by participation in cultural traditions where communitas inspires seeking opportunities for the well-being for all, emotional intelligence nurtures social well-being. Emotional intelligence unites heart and mind to be

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peaceful with proactive purpose to explore opportunities for adaptation to enhance social well-being. Emotional intelligence is the bridge ensuring authentic personal growth, by ensuring it is also community development. Emotional intelligence engages with communities to receive feedback. This is what monitoring operationalizes. Feedback about social well-being is sought, and recursively coupled with feedforward defining goals, indicators, and monitoring regimes, whereupon social resilience is bootstrapped into existence. Whereas hope is a horizon opening to opportunities for adaptation that maintain and enhance social well-being, maladaptation is discerned as a horizon of increasing closure and experienced emotionally as frustration. It is an experience that degenerates into desperation and traumatic stress. But with discernment between adaptation and maladaptation, through becoming centered in the heart in peace with emotional intelligence, and with the mind hopeful, the cause of maladaptation is perceived. It is caused by a misinterpretation of the horizon of impermanence; of mortality or death in biological life; and of institutional limitations in SES. Maladaptation is caused by an intrinsically doomed attempt to gain permanence in biological life and social esteem and identity within SES. It is expressed by overconfidence. But once the doomed overconfidence is let go, and adaption is discovered as an ongoing recursive process, the horizon of impermanence can be embraced and accepted. Then the glimmer of a horizon of absolute hope shines in midst of it. Adaptation is intrinsically temporary, and so in need of being continually repeated anew. But also, because adaptation is also in response to experience of communitas, impermanence and limitations, including biological death, are seen as a necessary part of the process of nurturing new life of others, for future generations, for sustainable development. Emotional intelligence recognizes that adults learn to live and die to nurture and protect the life of their offspring, and others. This emotional intelligence gives absolute meaning and a horizon of absolute hope, transcending impermanence and intrinsic limitations to social esteem and identities, and ultimately biological death. This glimmer of an eternal golden thread linking inseparably all life together inspires meaning and absolute hope, and locks in the peace of psychological resilience and the meaningfulness of social resilience. The peace, meaning and absolute hope that emerge are experience of noetic consolation, and transcend biological life. They are experiences of eternal well-being (Morrison, 2021). But paradoxically, eternal well-being only emerges as an experience when social well-being is first sustained by careful and cautious requisite freedom, by moderation constraining short-term freedom seeking short-lived pleasure and comfort, and by rejecting doomed and selfish attempts to seek permanence through material objects or institutional roles. Noetic consolation bringing eternal well-being and transcendence of biological life is not escape from biological life. Rather it is the consequence of fulfilling the responsibilities of biological life. Noetic consolation makes both psychological resilience and social resilience stable, as well as heightens them both to optimal levels. Traumatic experiences due to maladaptation are avoided, and healing of the effects of previous participation in

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maladaptation, and resulting trauma, also occurs (Hone, 2017; Morrison, 2021; van der Kolk, 2014). Furthermore, as well as eternal well-being transcending biological life, noetic consolation transcends coevolutionary selection, because natural constraints are forestalled through use of cultural constraints. By doing so, disasters are avoided. All aspects of civil society that establish and maintain the emergence of noetic consolation support DRR. Civil society is therefore pertinent to the global pursuance of DRR in face of climate change. This can be seen by analysis of communities’ vulnerability to climate change, and their resilience. The IPPC (2014) through its comprehensive research literature review summarizes vulnerability as proportional to both sensitivity and exposure of communities to climate change, and inversely proportional to the adaptive capacity of communities. In the same broad-brush summary, the IPPC (2014) defines the resilience of communities in face of climate change as inversely proportional to their vulnerability to climate change. This global consensus can be built upon by understanding the various facets of resilience and their interaction, as well as their reliance upon sociocultural processes constituting civil society. This understanding provides insights into how to practically use the comprehensive and trustworthy summaries provided by the IPCC (2014). Otherwise, it is possible to misinterpret the summaries provided by the IPCC (2014), resulting in counterproductive consequences. It is possible, if not likely without further understanding, to conclude from the summaries provided by the IPCC (2014) that vulnerability to climate change should be minimized and that this results in maximizing resilience in face of climate change. Such a misinterpretation is compounded if it is sought to be done by reductively seeking to minimize sensitivity to climate change, in the expectation that this will increase resilience. Just as there is a need for careful and cautious requisite freedom, and moderation of pleasure-seeking, if freedom and pleasure are to become stable, there is a need for requisite vulnerability (Morrison, 2019, 2021). Requisite vulnerability brings optimal resilience and is necessary for noetic consolation to emerge to bring transcendence from biological life and its limitations. This can be understood by considering how exposure and sensitivity to climate change, and adaptive capacity in face of climate change, interact. The feedbacks between exposure, sensitivity, and adaptive capacity in relation to climate change indicate that there is a requisite vulnerability for optimal resilience. There is a positive feedback uniting sensitivity and adaptive capacity because of how both are related to a focus on what is essential to psychological resilience, social resilience, and ecological resilience of SES (see Fig. 5.1). Sensitivity to climate change is necessary to be able to discern between personal adaptive and maladaptive responses, and to have the ability to engage in monitoring regimes to facilitate adaptation for social well-being. Sensitivity is enhanced by maintaining what is essential to psychological resilience, social resilience, and ecological resilience for SES, namely, interpersonal relationships, and critical collegial dialogue. Also, adaptive capacity to discover opportunities to adapt in face of climate change is enhanced by sensitivity. But it is precisely interpersonal relationships and critical collegial dialogue that constitute adaptive capacity, as well as constituting what is

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Sensitivity

Adaptive capacity

Inter-personal relationships, and critical collegial dialogue

Fig. 5.1  Very resilient self-reinforcing system. (After Morrison, 2019, p. 472)

essential to psychological resilience, social resilience, and ecological resilience for SES. Therefore, there is a reinforcing positive feedback loop that potentially resonates into a stable state of vulnerability, as negative feedbacks from exposure to climate change come to equal positive feedbacks. Resonance is stable and maximized when noetic consolation emerges, producing requisite vulnerability for optimal resilience. This occurs when careful and cautious requisite freedom is responsive to negative feedback produced by civil constraints to forestall catastrophic natural constraints. The stable state of resonance of sensitivity and adaptive capacity does not come due to simply minimizing sensitivity. Rather, stable resonance of vulnerability can potentially occur wherever the increase in sensitivity also increases adaptive capacity, to effectively cancel each other out. Sensitivity is required to maintain psychological resilience through responsiveness to communitas. It is also required for emotional intelligence for social resilience, so should not be sought to be minimized. There is a requisite vulnerability that potentially resonates, which has to be learnt and gained through careful and cautious requisite freedom, moderation, and participation in civil society to maintain social well-being. Then DRR is maximized, as continual adaptation occurs and ecological resilience for SES is fine-tuned and optimized. Disastrous changes are then able to be avoided, even in face of natural catastrophic changes wrought by climate change. The stability and moderation that psychological resilience and requisite vulnerability maintain have a profound consequence on the coevolution of SES. It results in evolutionary adaptation, or transformation of the structures of SES. It is due to a little recognized dynamic in coevolution. What drives evolutionary adaptation is that which cannot change and is therefore essential, and hence unable to adapt. It is precisely that which can change, which is flexible, because it is not essential. For example, the positive feedback loop coupling sensitivity and adaptive capacity emerges due to the process of coevolutionary adaptation, which is driven by what is essential and cannot change, namely, interpersonal relationships, and critical collegial dialogue. The dynamic of evolutionary adaptation, determined by what is essential and cannot adapt, is operationalized through reproduction of blocks of code (genes and symbolic language) as feedforward within indirect emergence. Blocks of code essentially include what cannot change, but also include other aspects that can

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change. Therefore, as long as the reproduced block of code includes the code for what cannot change, there are always potentially multiple plausible adaptations produced during any reproduction, due to differing inessential code. Reproduction through use of blocks of code ensures the emergence of diversity, which potentially increases each generation. The potential multiple viable adaptations are then put under evolutionary pressure, in face of limited resources, whereupon evolutionary adaptation or transformation occurs. What are essential in SES, because they cannot change, are the maintenance of psychological resilience and social resilience. In other words, what is essential is the potential emergence of noetic consolation, and hence moderation and careful and cautious requisite freedom maintaining social well-being and ecosystem health. What this means is different at different levels within SES. For individual persons it is eternal well-being of noetic consolation. For families and communities, it is the integrity and well-being of the family and community. At the level of institutions, it is the integrity of an institution to provide the services to fulfill the needs for wellbeing and ecosystem health that it is mandated to do. At the level of governance of a society, it is maintenance of the foundation and pillars of civil society. The blocks of code also differ at the different levels within SES, as well as in how they are constructed and reproduced. For individual persons they are worldviews implicit in a mode of life, which visualization implements and critically modifies. They are constructed and reproduced through both formal and informal education, and personal reflection on experience, whereupon socialized behavior becomes modified. For families and communities, blocks of code are constituted by sets of emotional bonds forming interpersonal relationships, and cultural activities, including religious protocols, that nurture communitas and liminality. They are constructed and reproduced through participation in cultural traditions and other sociocultural influences, including from the media. For institutions, blocks of code are formed by sets of social roles, protocols, and rules. They are constructed and reproduced through dialogue to critically engage in policy and procedural development, including collaborative approaches with other institutions to develop integrative approaches through community engagement. For governance, blocks of code are sets of laws that structure institutional arrangements of civil society. They are constructed and reproduced through democratic processes operating in the separation and balancing of powers between the government, parliament, and judiciary, or failing that, through power struggles between competing sectors. The common thread between all levels is that humans are the active agents. Whether purely as individuals in their personal development, as members of a family and community, or within institutions and the institutional arrangements of SES, or actively participating in the governance of SES within the executive (government), in parliament, or in the judiciary, the code that is active in the coevolutionary process is human thought utilizing symbolic language, resulting in decision-making, and leading to actions. Theory of decision-making provides an overarching understanding of how this common thread operates at all levels (see Fig. 5.2). The model of Triple-loop learning, first developed by Argyris and Schon (1996) provides a useful framework. But because of the explicit reference to cultural

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Heart

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Discernment

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Concepts, metaphors & narratives

Worldview

Science: Policymaking, regulation, and technology

Rules/laws

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Noec insight & light of hope

Diverse Dive rse creative cre ative syntheses synthe se s Double-loop learning Ecological resilience

Application of rules/laws

Mind Insight, Insigh concepts, concep imagina imagination

Multiple Multiple M ultipleadaptations adaptations adaptations ns

Emoonal intelligence

Feeling, emotions

Triple loop learning Triple-loop Social resilience Fine-tuned ecological resilience

Fig. 5.2  Emotional intelligence and triple-loop learning

traditions, here it is cross-referenced with the environmental anthropology of Rappaport (1999), in particular the hierarchical model of cultural knowledge. This linkage has already been previously made in reference to understanding climate change adaptation (Morrison, 2016, 2019, 2021), but is developed further here. A model that includes the roles of emotional intelligence and noetic consolation in decision-making, and how they relate to the different facets of resilience is emphasized. As already pointed out, emotions unite the noetic and biological natures of human persons, and so have a key role in both providing feedback to the noetic faculty from the biological reality, and in enabling feedforward constructed from noetic faculties to modify human behavior in the biological realm. What has not yet been clarified is how noetic consolation does this, and how it assists emotional intelligence. It is necessary to understand the distinction between feelings and emotions, and also the role of liminality nurtured, along with communitas, by cultural traditions. Feelings have an overarching integrative role associated with horizons, within which particular emotions, metaphors, and concepts are experienced and the content of their information understood (Nussbaum, 2001; Damasio 2003). Feelings are directly affected by noetic consolation. Noetic consolation inspires peace and joy to feelings. But noetic consolation also has cognitive content within a horizon of infinite openness, whereupon long-term possibilities are laid out in broad brush, along with discernment of closure, and hence maladaptation. This cognitive content of inspired insight is the experience of liminality that emerges along with communitas when participating in cultural traditions. The effect of this insight is to inspire hope as opportunities are perceived, and created by information provided by emotions, concepts, and metaphors.

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Rappaport’s (1999) model of the hierarchy of cultural knowledge defines the various cognitive facets of decision-making as it is practically implemented. Here it is linked to emotional intelligence and noetic consolation (see Fig. 5.2). Four types of cognitive activity are involved. The overarching one is the noetic discernment of horizons, namely, both of noetic consolation with infinite openness to possible opportunities for adaptation, and of closure and frustration due to maladaptation. In the middle two levels are concepts and metaphors, which provide understanding, both scientifically and poetically. These are what produce worldviews that frame the creation of opportunities, as well as the rules and principles applied to develop technology, and the laws that define institutional structures and institutional arrangements, and governance. To apply the rules and laws, however, requires visualization within a particular context. This is the grounding level that enables the design of adaptations. It is the process of using imagination within emotional intelligence for visualization to design adaptations in particular contexts. Emotional intelligence is tied to concrete visualization implementing both scientific and poetic knowledge. But, as theorists of emotional intelligence have pointed out, emotional intelligence, along with imagination and knowledge, can be used to nurture either well-being or ill-being (Goleman, 2006). It can be a source of maladaptation as well as adaptation. Whether it nurtures well-being or ill-being depends on whether noetic consolation providing the horizon of absolute hope and eternal well-being and stable psychological resilience is present. If not, maladaptation is inevitable as imagination is unlinked to the reality of possible opportunities. Delusions become imagined as possibilities. But as has already been pointed out, the process of discerning adaptation is not simply a cognitive choice, but rather an experience that emerges as requisite freedom and moderation are practically lived and grown into through participation in the hermeneutic spiral of learning (Morrison, 2019, 2021). It is a process of recursive practical learning, of praxis, of continual reinterpretation and adaptation to reach a stable and very resilient resonance of noetic consolation, which is then kept on a stable pathway of continual adaptation (Morrison, 2019, 2021). The inspired hermeneutic spiral of continual reinterpretation and adaptation is a practical one of implementation in particular contexts, of triple-loop learning, which includes use of emotional intelligence. Triple-loop learning has double-loop learning nested within it, and double-loop learning has single-loop learning nested with it. Single-loop learning occurs when there is a defined goal and conceptual model to guide activity (Morrison, 2012; Morrison & Singh, 2009). Single-loop learning deals with what Checkland (1982) termed hard systems analysis, and enables engineering resilience to be achieved when conceptual models are used within visualization for design of engineered systems. Double-loop learning provides multiple paradigms with which to frame knowledge, and hence approaches to visualization and design of potential SES structures and monitoring regimes. Requisite diversity of paradigms provides ecological resilience, and hence assurance of transformation emerging through evolutionary adaptation from continual recursive adaptations based on blocks of knowledge and multifaceted visualizations.

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Triple-loop learning fine-tunes ecological resilience through psychological resilience inspired by noetic consolation to use emotional intelligence for social resilience. Triple-loop learning ensures that transformation occurs without disasters. Triple-loop learning is how DRR is mainstreamed through all decision-making, at all levels, for individual persons, to families and communities, to institutions and to institutional arrangements, and to democratic governance structures maintaining civil society.

3 Sidestepping Natural Catastrophes to Avoid Socially Constructed Disasters Natural processes are variable, and often inevitably involve catastrophic change. This is the case irrespective of anthropogenic influences. Anthropogenic influences can however, for example on climate change, and global ecological degradation, exacerbate the variability and likelihood of catastrophic change. In face of naturally variable processes, including catastrophic changes, for example anthropogenic climate change, monitoring of natural processes, can however also enable DRR to avoid disasters. Monitoring enables determination of what scope there is to modify a pathway of participation within a particular set of natural process and ecosystems, to avoid catastrophic change. Monitoring of natural processes is a type of cultural constraint, which helps avoid natural constraints on SES that would otherwise be provided by catastrophic change. Natural coevolutionary processes on average move to enhance ecosystem health. Natural processes that SES participate within, namely coevolutionary processes, select for SES that maintain requisite diversity of potential HAS, or in other words, select for requisite diversity of structures within an SES. Moreover, however, each HAS that involves monitoring is also given the optimal opportunity of avoiding participation in catastrophic change, through use of cultural constraints. Therefore, monitoring fine-tunes ecological resilience by increasing the flexibility of SES, because more structures within an SES can be fine-tuned to avoid participation in catastrophic change, and hence avoid being selected against by coevolution. Therefore, the risk of disasters can be minimized. The characteristics of psychological resilience and social resilience indicate how disasters can be avoided. It is by avoiding participation in catastrophic changes. Catastrophic changes are phenomena intrinsic to complex natural processes. This is because of the topology of maximizing or minimizing processes indicate that if there are three or more state variables, folds in the possibility surface exist, which result in discontinuities in some pathways on the possibility surface (Morrison, 2021; Thom, 1989; Thompson, 1979). A discontinuity causes catastrophic change, because from one direction it is a collapse in a particular state, while a cave and wall in opposite direction. The 2nd Law of Thermodynamics shows that such processes are all pervasive. The rate of dissipation of energy across a gradient is maximized.

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This means that catastrophic changes are intrinsic to all complex natural processes characterized by three or more state variables. It is the maximization of a natural flow that both psychological resilience and social resilience temper, not the complexity. Psychological resilience tempers the maximizing self-interest. Social resilience tempers the maximization of social esteem and conformity. Now it can be understood why psychological resilience requires discernment of adaptation and maladaptation, and why moderation provides optimal well-being through enabling stability and balance. Stability and balance and hence well-being requires the avoidance of catastrophic change, and to do so requires to be able to discern the pathways of maladaptation, which are those that lead to catastrophic change. Moderation is not simply an averaging out of activities. Rather it is discerning intuition with emotional intelligence to stay within the bounds of what avoids breakdown in emotional bonds of good will and peace. The intuition of emotional intelligence is topological perception of the possibility surface of emotional wellbeing, hence perception of how to avoid the potential pathways that risk entering into discontinuities that break apart emotional bonds. The bounds of freedom are defined by where there is risk of entering into a pathway of such discontinuity. Simply maximizing self-interest and pleasure, and encouraging others to do so, inevitably creates breakages in emotional bonds. Monitoring for social resilience is equally complex because there are multiple needs that contribute to well-being. Each need for well-being is a state variable pertaining to social well-being (Morrison, 2019). Various researchers have produced lists: Raworth (2017) produced a list of 12 essential needs, Weil (1952) produced a list of 14, Max-Neef et  al. (1991) produced a matrix of 36, and Bossel (1998) a matrix of 42. The complexity is manifest in the challenge of developing integrated approaches to DRR (Gero et al., 2011). The challenge is that multiple institutions are involved, with each likely to have their own monitoring and evaluation processes. Multiple collective alignments of various institutions facilitating the provision of various needs are possible. Flexibility to modify social roles and responsibilities and mandates are necessary to cocreate institutional collective alignment that is equitable and holistic in ensuring all needs are met. This requires emotional intelligence to develop social resilience. Multiple accommodations between varying mandates and expectations are possible and necessary for flexibility, so that discontinuities in collaboration are avoided. Once again it shows the need for triple-loop learning.

4 Framework for Resilience and DRR A nuanced analysis of the various types and facets of resilience has shown that a common thread across all levels is that human persons are making decisions. This is central to any framework for DRR. Moreover, it is a strength not a weakness. The human dimension should not be misinterpreted as a source of error. Rather, by embracing and understanding that the human dimension is the essential dimension,

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driving the evolutionary adaptation and hence transformation of SES, enables DRR to be understood in both its coherence and complexity. It enables understanding of how DRR operates throughout all processes of decision-making to enable adaptation to climate change as well as mitigation of climate change. To clarify and to emphasize how the human dimension is central, and what are the essential aspects of SES that need to be maintained for successful coevolutionary adaptation or transformation, the link between leadership and resilience needs to be made explicit. Essentially, leadership is something everyone potentially has, and it is manifest in every person wherever and whenever they gain and maintain psychological resilience. It is psychological resilience that enables anyone and everyone to express their potential leadership for the benefit of civil society, for social resilience, and ecological resilience of SES, and hence for DRR, including climate change adaptation and climate change mitigation. Leadership can be defined in two ways, transactional leadership and transformative leadership (Marinova et  al., 2015; Montuori & Donnelley, 2018; Morrison, 2021), which is reflective of the distinction between hard system analysis and soft system analysis, and also between engineering resilience and ecological resilience. If a goal and means to obtain it are clearly defined and able to be monitored, then transactional leadership uses hard system analysis to achieve the defined goals through linear directives. Such goals are, however, always only nested within a need for ecological resilience and accompanying flexibility and diversity enabling adaptive management of goals that even though broadly defined, can change in how they are characterized. Such soft systems require transformative leadership, where collaboration to complement and support the potentially unique leadership of all others is manifest as a recursive never-ending process of adaptive learning and transformation. This is precisely what psychological resilience maintains, and what enables social resilience to be achieved, so that fine-tuned ecological resilience can be sustained for SES to ensure socially constructed disasters are avoided. An adequate framework for DRR therefore needs to ensure democratization of leadership, while allowing for the appropriate expression of transactional leadership when nested hard systems analyses are appropriate. The democratization of leadership needs to explicitly recognize the levels at which the human dimension is expressed, namely, as an individual, in family and community, in institutions and institutional arrangements, and in governance structures of SES for civil society. These levels are not arbitrary. They manifest necessary and essentially different aspects that have to be maintained for adaptation of SES to occur. If there is failure at any level, maladaptation is the result. Maintenance of what is essential at each level is what ensures that blocks of code are successfully reproduced, and so adaptation continues and so transformation emerges to successfully avoid disasters and to adapt to climate change and to mitigate it, while and through maintaining civil society and social well-being. Each level is a soft system with its own SSM operating to implement triple-loop learning (see Fig. 5.3). Therefore, a hierarchical structure of SSM is an appropriate framework to maintain what is essential for adaptation, and hence for

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Multiple Stakeholders' worldviews & rules/laws

Nested hard system analyses

Single-loop learning

SSM Diverse adaptations that accommodate all stakeholders

Horizon of hope & social resilience

Potential adaptations

Double-loop learning

Triple-loop learning

Fig. 5.3  Soft systems methodology (SSM) and triple-loop learning

Civil society

Economic processes

Judiciary

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SSM2

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Parliament

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SSM1 Families & communities

Cultural Traditions Fig. 5.4  Tri-SSM and civil society

DRR. Tri-SSM is one such framework that has been developed to model the interactions of the essential features of each level (Morrison, 2021) (Fig. 5.4). Tri-SSM is composed of three levels. SSM1 refers to the level of family and community. SSM2 refers to the level of institutions and institutional arrangements. SSM3 refers to the level of governance. The foundational level of the individual person is present in SSM1, SSM2, and SSM3, as human persons are who make the decisions at all levels. But the essential characteristics of SSM1, of families and communities have a specific interaction with SSM2 and SSM3, as does the interaction between SSM2 and SSM3.

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The interaction between SSM1 and SSM2 is that institutions must engage with families and communities to serve them to fulfill their needs. Families and communities are the intrinsic end, and institutions are the utilitarian means. This relationship defines how monitoring regimes need to be constructed, and the way in which triple-loop learning is required to be participated in by members of families and communities and institutions. Often families and community members have to learn not to accept to be patronized, and likewise members of institutions have to learn not to patronize. The interaction between SSM2 and SSM3 is that institutions follow the directives of those with governance. SSM3 directs SSM2. SSM3 is required to structure the coordination and collaboration of institutions and hence SSM2, so that civil society is maintained. But the top-down direction is tempered in several ways. It is not simply transactional. The separation and balancing of powers between government, parliament, and the judiciary is how it is sought to be maintained by civil society. Firstly, there is the interaction between SSM1 and SSM3. Governance does not dictate over families and communities. Rather, families and communities decide who governs through reelecting recursively, and hence adaptively, parliament. This is what democratic processes facilitate, however imperfectly. That it is a continual recursive process just proves the point that it is an essential relationship that must be maintained in coevolutionary adaptation of SES.  Therefore, because SSM2 is directed by governance through the executive of the government, while engaging to serve families and communities, there is an intrinsic tension, but it is a creative tension because essentially all are attuned, because it is families and communities that choose governance, and it is families and communities that institutions serve. Moreover, to underline the creative tension, the institution of the judiciary can for constitutional matters, direct the executive of government. A role of personnel in institutions, and hence an essential role of SSM2, is to seek to align what is being heard from their monitoring regimes and what is being directed to them from the executive of government. This is an act of triple-loop learning. It is also an example of SSM (see Fig. 5.3). The use of emotional intelligence within critical collegial dialogue in the process assists both families and communities, and governance so that the integrity of civil society is maintained, and social well-being and DRR are enhanced. Moreover, at the most fundamental level, that of coevolutionary processes to fulfill the 2nd Law of Thermodynamics, all three levels of tri-SSM are intrinsically attuned as one movement to increase ecosystem health, to dissipate the energy differential across the biosphere at the fastest rate. What holds the whole dynamic process of tri-SSM, and each SSM process within it, is a common decision-making process that all persons at all levels use. Tripleloop learning is necessary for everyone at all levels, whether within SSM1, SSM2, or SSM3. This is achievable due to the possibility of psychological resilience by all, which enables all to manifest their unique leadership, which can be equally expressed in SSM1, SSM2, and SSM3. What is different at the different levels, and what differs SSM1 from SSM2 and SSM3, and SSM2 from SSM3, is the scale of the contexts that visualization is carried out within. Entailed in this are diverse disciplines and paradigms of knowledge that are likely to be used. But there is full

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flexibility within tri-SSM for interdisciplinary development of knowledge, and syntheses of the sciences and humanities at all levels. The blocks of code that are constructed are due to dialogue, which is essentially open, including to diverse cultural symbols and rituals used to facilitate communitas and liminality. What is common, however, is the same peace and joy of heartfelt noetic consolation, and also the same horizon of hope opening to ever-increasing opportunities, ultimately transcending biological life into eternal infinite noetic possibilities. Tri-SSM is like a symphony played in three keys that are nevertheless in harmony at a higher more fundamental and ultimate level, which enhances the appreciation of the unique and necessary contributions of each of the three keys. This can be seen by how the source of the flows in tri-SSM shown in Fig. 5.3, all come from SSM1, which rests upon the foundation of civil society, which are cultural traditions. Cultural traditions are where psychological resilience and the skills of emotional intelligence necessary for social resilience are learnt. Metaphors such as this musical can help communicate tri-SSM and the nested dynamics within it. They form a necessary part of narratives that help constitute cultural traditions that form the foundation of civil society. Such narratives are not ideological and fixed. They are diverse and continually being developed modified, synthesized, and hybridized. They are a continual poetic exploration of effective communication, always transcending itself in peace and joy into the noetic horizon of hope where any number of narratives and opportunities are possible. Identities defined by the narratives are fluid and diverse, but not arbitrary, because they constitute the careful and cautious requisite freedom of civil society. The identities support responsible roles within civil society. This is necessary for DRR to be enhanced, through all decision-making by all roles and leadership at all levels. The phenomenon is readily apparent in how climate change has captured the imagination of the humanities and youth creatives as much as the sciences and technologists (Johns-Putra, 2018, 2019; Poray-Wybranowska, 2020). These diverse expressions and intense dialogues indicate that learning within the hermeneutic spiral is underway to transform SES globally to mitigate climate change and adapt to what is now inevitable.

5 Conclusions DDR is an organic process operating within SES. DRR emerges from the nurturing of resilience by civil society. DRR is a fruit of the flexibility that a civil SES maintains. The flexibility is nurtured by democratic transformative leadership pervasive throughout all levels of civil society, where there is mutual interaction and creative tension prompting responsible, careful and cautious continual learning at all levels within society. Transformations of SES emerge as inspired expressions of this learning in peace and joy and hope. Transformations of SES emerge from repeated cocreated incremental adaptations, in response to clear insight of open-ended creative

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opportunities ahead. Civil society nurturing psychological resilience for all, through social resilience to fine-tune ecological resilience of SES, keeps this horizon alive. There is a unity to diverse decisions that enhance DRR, which is also the essential unity of SES. It is unity inspired by the one noetic consolation that emerges for all as they choose to align to the pathway of adaptation maintained by the constraints of civil society, the knowledge maintained by educational institutions, and communitas nurtured by cultural traditions. It is unity that not only unites families and communities in their close communion, but also the integrity of institutions, the coherence of their collaborative arrangements, and of good governance. The power of governance has as its source the same unity as that which maintains the love within a family and community, and functional work culture within institutions. DRR is optimal when it is pervasive throughout all decision-making within civil society, to include all knowledge, both scientific and poetic, and monitoring of the biological and ecological processes. Civil society ensures that an SES acts to optimally enhance the ecosystem health of ecosystems which it is part of. In doing so, a civil society is implementing optimal DRR to optimally mitigate climate change, while also providing a clear pathway for climate adaptation for its families and communities.

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Chapter 6

Mitigating Disaster Risks and Vulnerabilities Through Climate Finance and Sustainable Water Management: Policy Considerations for Sub-Saharan Africa and Malawi Dumisani Chirambo

Abstract  The economic losses from climate-related disasters have been increasing rapidly; hence, there is a likelihood that disasters will engender poverty and constrain the development aspirations of many countries. Approximately a third of Africa’s population lives in drought-prone areas, and there are threats that climate change induced such as increases in the frequency and severity of hydrological extremes (droughts and floods), which will affect access to water and agricultural productivity. These issues suggest that the attainment of the Sustainable Development Goals (SDGs) in sub-Saharan Africa (SSA) could be closely hinged to how disaster management policies augment hydrological resilience and climate change adaptation. Currently, there are prospects for the Paris Agreement and Nationally Determined Contributions (NDCs) to increase climate finance disbursements to Africa. This chapter therefore presents an assessment of how climate finance can augment disaster risk management policies and processes in SSA. The methodology for this exploratory study included academic literature reviews, case study analyses and reviews of project reports. The study discovered that the inability of fiscal reforms in SSA countries to significantly improve the mobilisation of domestic taxes to fund socio-economic development programmes and the weak integration of SDG 6 (sustainable management of water) aspirations in NDCs can constrain efforts to simultaneously mitigate disaster risks and reduce vulnerabilities. The study concluded that climate finance can augment SSA’s disaster risk management policies by facilitating investments in entrepreneurship and non-farm enterprises in order to reduce water stress attributed to agricultural industries and financing processes to enable frequent and systematic policy reviews so as to improve policy coherence across sectors.

D. Chirambo (*) Seeds of Opportunity, Blantyre, Malawi © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_6

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Keywords  Disaster risk management · Integrated water resource management · Nationally Determined Contributions · Paris Agreement · Sustainable Development Goals

1 Introduction Africa is arguably the continent that will be the most adversely affected by climate change despite having contributed the least to the global greenhouse gas emissions that lead to global warming (Forcella et al., 2016). Additionally, Africa is forecasted to continue to have the highest rate and depth of poverty of all regions of the world beyond 2030; hence, the region is already at risk of not being able to achieve the Sustainable Development Goals (SDGs) (World Bank, 2015a). As it stands, about one-third of the African population lives in drought-prone areas (Muller, 2014); hence, there are concerns that climate change and climate variability can engender poverty, food insecurity and gender inequality in the region (Wong, 2016; Filho et al., 2019). Moreover, most African communities are characterised by a heavy reliance on agriculture for income; the concentration of populations in hazard zones; and climate change adaptation deficits as caused by a lack of institutional, financial or technological capacity to adapt effectively to climate change (Bowen et al., 2012; Schumacher & Strobl, 2011); hence, most communities are still very vulnerable to economic shocks and disasters. What is unfortunate is that the Paris Agreement’s target to galvanise countries to make commitments to collectively keep the global temperature increase to well below 2 °C has not been achieved (Bak et al., 2017); hence, there are concerns that climate change impacts might be expected to become more severe, and the adaptation costs could increase (Nakhooda & Norman, 2014; Zhang & Pan, 2016). Similarly, the economic losses from the climate-related disasters have been increasing rapidly over the past decades, and the frequency and magnitude of natural hazards triggered by climate change has been increasing globally, leading to US$1.5 trillion in economic damages from 2003 to 2013 (Micale et al., 2018). These factors therefore highlight that a failure for African countries to reduce climate change vulnerability and enhance resilience to disasters can thwart Africa’s efforts to achieve the SDGs. Many communities in Africa experience droughts, and Africa has the highest mortality-related vulnerability indicators for drought (Muller, 2014). This arguably means that as many African countries are charting different paths to achieve sustainable development, there is a need for a greater understanding on how the climate change and water nexus can influence the livelihoods of various communities, mainly through water stresses and disasters. For example, some contemporary studies are suggesting that in current times, 90% of natural hazards have been related to water, and this might even get worse as climate change will cause hydrological extremes (droughts and floods) to occur more frequently and in greater severity

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(Gan et al., 2016). On the other hand, 41% of the world population lives in waterstressed river basins, but it is projected that the population living in water-­stressed river basins will increase to 48% by 2025 (Kumambala, 2010). In the case of North Africa, water stress is anticipated to increase as some projections have shown that the region will experience up to a 12% decrease in water supply coupled with approximately 50% increase in water demand due to a combination of climate change, population growth and economic development (Schilling et  al., 2020). Despite these hazards, it has been noted that the investments in the water sector are decreasing as it has been reported that the Official Development Assistance (ODA) funding commitments to the water sector have dropped by more than 25% between 2012 and 2016 (UN, 2018). Moreover, climate change and variability have the potential to impose additional pressures on water availability, water accessibility and water demands, and these issues can directly impact efforts to eradicate poverty and promote sustainable development globally (Al-Gamal et al., 2009). However, since the United Nations Framework Convention on Climate Change (UNFCCC), Paris Agreement, SDGs and South–South Climate Change Cooperation modalities are all advocating for greater collaborations to improve climate change adaptation and enhance disaster risk resilience, there have been greater efforts to mobilise and disburse larger amounts of climate finance to developing countries (Tenzing et al., 2016; Abramskiehn et al., 2017; Banga, 2019). It may therefore be argued that there is a high likelihood that the climate finance disbursements to Africa will be increasing significantly in terms of the size, source and distribution. Arguably, with greater amounts of climate finance being available to African countries, there are also greater prospects for climate finance modalities to take a greater part in financing Africa’s disaster risk management policies and processes that have a relevance to climate change. Many countries in sub-Saharan Africa (SSA) have developed and implemented Nationally Determined Contributions (NDCs) and climate change policies to harmonise and enhance the planning, development, coordination, financing and monitoring of climate change initiatives and programmes with policies from other sectors such as the water sector. Despite this progress, it has been noted that several SSA countries such as Malawi, Uganda and Tanzania are unable to effectively implement their policies leading to conflicts amongst institutions and the unsustainable utilisation of both financial and natural resources. Factors such as insufficient consultation of stakeholders; communication disconnects between national, district and community levels; and budgetary constraints and problems of cross departmental coordination are cited as the aspects that contribute to the ineffective policy implementation (Mpaire et al., 2017; Pardoe et al., 2018). Arguably, the aforementioned challenges demonstrate that for SSA to effectively use climate finance modalities as a means for enhancing hydrological resilience and achieving the SDGs, there is a need to improve knowledge on how policy convergence in SSA can be achieved across the climate change, disaster risk management and water resources management sectors. This chapter therefore aims to improve the knowledge on policy coherence issues in SSA’s disaster risk management frameworks by providing analyses of how climate finance modalities can be utilised to reduce climate change

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maladaptations and to reduce hydrology-based climate change vulnerabilities and disasters. The chapter is structured as follows: Sect. 2 follows with the methodology and conceptual framework for the study. Section 3 presents a narrative on the dynamics of the climate change and water issues in Malawi and SSA. Section 4 focuses on providing insights into the important climate finance, disaster risk management and hydrological resilience issues for consideration in SSA’s policies. In Sect. 5, investments in non-farm enterprises are presented as measures for reducing economic vulnerabilities and hydrological stress. The discussion in Sect. 6 focuses on how NDCs and climate finance can mitigate disasters by augmenting SDG 6 (sustainable management of water) programmes. The paper concludes in Sect. 7 with some suggestions on how climate finance can help to address the crucial immediate-term and long-term climate change vulnerability and disaster risk management issues.

2 Methodology and Conceptual Framework This chapter presents an exploratory assessment focusing on how various policies can be developed to enable climate finance to enhance disaster risk management in SSA in spite of the challenges from climate change, urbanisation and rapid population growth. Some current studies on climate finance, disaster risks and climate change vulnerability include Shiferawa et al. (2014) who made an assessment of the policy options for managing vulnerability to droughts and enhancing livelihood resilience. Shiferawa et  al. (2014) concluded that managing drought and climate variability will call for the implementation of proactive approaches that combine the technological, institutional and policy solutions to manage the risks within vulnerable communities. Van Asselt (2016) looked at the roles that non-state actors can play in improving the implementation of the Paris Agreement and concluded that regardless of many non-state actors not having any formal roles in the UNFCCC process, they can support the implementation of the Paris Agreement by playing an essential role in holding national governments accountable for meeting their commitments and putting pressure on them to raise their ambition. Chirambo (2017) undertook an assessment of how global policymakers can increase the mobilisation of climate finance from a variety of sources, instruments and channels to complement public sources. This assessment discovered that Africa can mobilise more climate finance by increasing government engagement with various non-state actors such as Africa’s diaspora and by developing bankable climate change infrastructure projects to which the diaspora and private sector can be the main stakeholders. Ngongondo et al. (2015) analysed the observed and simulated changes in the water balance components over Malawi, during 1971–2000, and concluded that the decline in rainfall coupled with temperature increase suggests that Malawi became more water limited during 1971–2000. Northrop et al. (2016) undertook an assessment of the extent to which the Paris Agreement and SDGs are aligned and discovered that regardless of the high degree of alignment between the SDGs targets and

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climate targets in NDCs the successful implementation of both agendas will principally depend on the ability of national governments to develop and implement different sets of national targets to serve agenda, optimise benefits and reconcile trade-offs. Despite such studies, there is still a lack of research on how various countries can reduce disaster risks through climate change modalities and how policy implementation across sectors can be improved (Mugambiwa & Tirivangasi, 2017; Abramskiehn et  al., 2017); hence, the methodology for the research is based on addressing these knowledge gaps by focusing on how climate finance modalities can augment disaster risk management in different contexts. This chapter focuses on determining the aspects that can enhance disaster risk management and the implementation of NDCs in SSA since the developing countries are projected to bear approximately four-fifths of the costs caused by a 2 °C increase in average global temperatures (Campillo et al., 2017). The chapter also highlights the climate change and sustainable water management issues in Malawi, which is a Least Developed Country (LDC) in Southern Africa that is considered to be amongst the world’s dozen countries that are most vulnerable to the adverse effects of climate change and amongst those with the least resources to adapt (Olson et al., 2017; GoM, 2015a). Arguably, improving the understanding of the disaster risk management and climate change policy landscape in Malawi has the potential to improve the knowledge and understanding of climate change and disaster risk management issues in some of the most vulnerable countries. In order to achieve the aim of this chapter, an exploratory assessment using secondary data consisting of various academic literature, case studies, policy briefs and project reports focusing on the nexus of climate change, disaster risk management, sustainable water management and climate finance was undertaken (Ostad-Ali-­ Askari & Eslamian, 2019). Hydrological and climate forecasts will always have some uncertainties due to limitations of the climate/hydrological models used, carbon cycles, input data errors and structure of the climate models (Gan et al., 2016). Additionally, SSA’s climate change vulnerability is influenced by factors such as high poverty levels, access to water, poor infrastructure and low social resiliency (Filho et al., 2019; Hallegatte et al., 2016); hence, there are substantial variations in socio-economic conditions and hydrological patterns (i.e. precipitation patterns, evapotranspiration rates, groundwater recharge rates, etc.) (Al-Gamal et al., 2009) between and within countries, and this requires the need for a spatially explicit localisation to determine the vulnerability of populations. Consequently, rather than attempting to formulate a conceptual framework depicting the relationship between climate finance flows, climate change vulnerability and hydrological disasters, the chapter focuses on theorising that understanding and addressing the climate change maladaptations can improve the implementation of policies and improve the effectiveness of climate finance in reducing the climate change vulnerabilities and hydrological disasters. This approach is therefore anticipated to support the conceptualisations that explain how policy coherence across the various sectors leads to improved outcomes at lesser cost (Nhamo et al., 2018; England et al., 2018). The methodological approach adopted in this chapter is therefore similar to the studies such as England et  al. (2018), Schroeder et  al. (2018) and Guha (2020)

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where document analyses were undertaken to posit narratives on the research issue rather than developing a model to examine the research issues.

3 Climate Change and Water Management: The SSA and Malawi Dynamics Some studies point out that Africa’s continued rapid population growth coupled with environmental degradation and predicted climate change can potentially create a global water crisis and food insecurity (Lal, 2013; Burns et  al., 2010; Cooper et al., 2008). This follows that the projected trends in world population growth and dynamics will place substantially greater multi-sectoral demands on water, leading to greater competition between sectors for an increasingly limited supply of abstracted water, and the higher water demand will curtail the ability of irrigated agriculture to respond to the expanding food requirements of tomorrow’s Africa (Cooper et al., 2008). Since the impacts of population growth and climate change on water availability and food security will vary from one country to another and from time to time, to avert the future disasters, there will be a need for more water balance and water management country assessments to be undertaken particularly in developing countries and the countries with a high vulnerability to climate change such as Malawi. Malawi is located in Southern Africa between latitudes 9.5–17°S and longitudes 32–36°E. The country has a total area of 118,484 km2, of which 94,080 km2 is land and 24,404 km2 is occupied by lakes and rivers (Ngongondo et al., 2015). Malawi experiences a mild tropical climate with an austral summer rainy season between November and April and a dry season between May and October. Rainfall depends on the position of the Inter-tropical Convergence Zone (ITCZ) and varies in its timing and intensity from year to year. Countrywide rainfall varies from 725 mm in the low lying rift valley to 2500 mm in the highlands. Temperature is also controlled by the varying topography and ranges from 22 to 27 °C in the summer months. In the dry season (winter months) between May and August, day temperatures drop to around 18  °C, whereas night-time temperatures drop to 5  °C (Ngongondo et al., 2015). As a consequence of climate change, Malawi is projected to likely become significantly warmer, with an increase of between 1.5 °C and over 3.5 °C by 2050, and precipitation will likely decrease during the rainy season by around 150  mm by 2050 (Olson et al., 2017; Nhamo et al., 2016). There are about 65,300 megalitres of water available per day in Malawi, or approximately 1.7  megalitres/person/year making the country water vulnerable (GoM, 2012). Malawi is considered to be water stressed with less than 1700 m3 of freshwater per capita, and the estimates for future water are less than 1000 m3 per capita by 2020, which places the country into the water-scarce category (Nhamo et al., 2016). However, some studies have shown that the rainfed Water Productivity (WP) values for Malawi (i.e. WP is a measure of

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the ability of agricultural systems to convert water into food) were between 0.29 and 0.4 kg/m3, which were slightly lower compared to other global studies that found the WP values ranging from 0.35 to 1.1 kg/m3, suggesting there is still room for WP improvement in Malawi (Nhamo et al., 2016). With the aforementioned factors in mind, it can be argued that the policies aiming to reduce the country’s water demand and improve WP can potentially avert the future water stress related disasters in the country.

4 Towards Hydrological Resilience and Sustainable Water Management in SSA 4.1 Climate Change and Water Sector Maladaptations: Physical Factors Climate change and the growing population in SSA and Malawi call for a greater emphasis by policymakers to apply a combination of technical, economic and institutional measures capable of developing the water resources in a sustainable way that may avert conflicts amongst users and mitigate stress on freshwater environments (Kumambala, 2010). Water resource availability at any temporal and spatial scales is governed by the complex interactions between the climate and hydrological processes, and global warming-induced climate change is bound to further complicate this already complex interaction (Ngongondo et  al., 2015). Additionally, non-climatic aspects such as changing land use, population density, urban growth, land degradation and pollution affect water resources quality and water availability (Kusangaya et  al., 2014; Al-Gamal et  al., 2009). Consequently, reducing water-­ stress-­related disaster risks in most SSA communities will call for a greater understanding of how water demand from non-climatic aspects can be reduced and managed. From an institutional and socio-economic perspective, unsustainable climate change adaptation/maladaptation and unsustainable water management practices can occur when what seem to be successful climate change adaptation strategies may in fact undermine the social, economic and environmental objectives associated with sustainable development and/or where a strategy or policy makes sense from one perspective, or for one group, may at the same time reduce the livelihood viability or resource access of other groups (Eriksen et  al., 2011). In the case of Africa, where only over 5% of its available cultivated land is under irrigation, representing the lowest percentage of any continent (Mashnik et al., 2017), increasing the deployment and utilisation of irrigation is considered as an effective strategy for reducing climate change vulnerability, poverty and food insecurity (Joshua et al., 2016; GoM, 2016a; Daccache et al., 2015). However, whilst irrigation can potentially reduce climate change vulnerability by improving access to water for agriculture during dry months, there are also instances where irrigation can be a

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maladaptation by inducing water stress through the excessive abstraction of water and reducing the availability of water for human consumption. For example, in the case of Malawi, the Government of Malawi has a political ambition or target to develop approximately one million hectares of agricultural land for irrigation (GoM, 2011, 2012). However, some studies have indicated that the total potential for irrigation in Malawi lies between about 162,000 and 485,000  hectares (GoM, 2012). Moreover, demand for water for irrigation is expected to, on average, increase by 19% a year through 2035, from a daily demand of 2632  megalitres in 2010 to 15,364  megalitres per day in 2035, thereby totalling 23% of the expected water resources available in 2035, on an annual average basis. On the other hand, Malawi’s NDCs (GoM, 2015a) has plans to increase land under irrigation through the Greenbelt Initiative from 20,000 to 40,000 hectares and increase irrigation (by an unspecified amount) at smallholder level. However, there is some evidence to suggest that smallholder irrigation will further reduce the water available for large-­ scale irrigation systems, hydropower and municipal use (USAID, 2013), and that demand for water for all uses in Malawi is expected to increase five-fold by 2035; hence, if by 2035 irrigation is expanded to 485,000 hectares, the result would be a water deficit because after the demand for water for human use is met, there would not be enough water to irrigate 485,000 hectares (GoM, 2012). From this data and predicament, it might be argued that some policies are unattainable when further assessments are undertaken and that political goals/ambitions are not always in synch with technological and physical realities. So, whilst increasing land for irrigation might seem like an effective climate change adaptation strategy by improving farmers’ access to water, in actual fact, this could be a maladaptation as it might induce vulnerabilities in other sectors and communities and cause water access and availability problems for water utilities in the future. Accordingly, since increasing irrigation may be a maladaptation in some contexts, there are two issues that warrant further exploration by policymakers if the aim of climate change policies and development policies are to simultaneously reduce climate change vulnerability and water stress. First, the Malawi scenario provided suggests that in some cases there are misalignments between the political goals/ambitions and technological realities. Policymakers should therefore ensure that the policies that are adopted are driven by the capacities of available technologies and scientific data rather than the political aspirations only. Second, if reference is made to the study by Chirambo (2018) and FAO (2010), it might be hypothesised that investments in irrigation should be complemented by improving the efficiencies across agriculture value chains since a lot of wastage in water, inputs and produce occurs in SSA’s agriculture sector. This is particularly important since the agriculture sector is responsible for up to 70% of water withdrawals in some SSA countries (Nhamo et  al., 2018); hence, with switches to crops with less water demands, use of drip irrigation, improving water harvesting and so forth, the rates of water abstraction could be reduced, and this can ultimately lead to the reduced levels of vulnerability and water stress in communities.

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4.2 Climate Change and Water Sector Maladaptations: Institutional Factors Another issue that might be considered as a maladaptation in the water and irrigation sector is the promotion of irrigation for agriculture without due consideration to existing regulatory constraints and institutional frameworks. Some studies in Malawi have highlighted that due to the persistent declining yields from rainfed production in part because of perennial rainfall failure, some Malawian communities have resorted to using irrigation as a climate change adaptation strategy (Joshua et  al., 2016). However, the shift from a dependence on rainfed agriculture to irrigation farming has in turn triggered water conflicts in some communities over the control of the resource as existing water legislation fails to adequately provide for rules governing sharing of water resources between the various stakeholders (Joshua et  al., 2016). Malawi’s Water Resources Bill, which was assented to in 2013, has not been operationalised; hence, the country still lacks a water regulatory authority, which could improve the water management practices and the sustainability of water supply services since the current mandate for water and sanitation sectors are currently contested by different ministries and entities (World Bank, 2015b). Furthermore, although Malawi is striving to create a system for Integrated Water Resources Management (IWRM), shortfalls are evident as the approaches that have been adopted to promote IWRM are being applied in a context that lacks the solid institutional capacity needed to deal with the country’s growing and significant water scarcity challenges, and these approaches do not yet capture or regulate small-­scale users nor consider the likely shortages due to the impacts of climate change (USAID, 2013). IWRM is a process which promotes the coordinated development and management of water, land and related resources in order to maximise the economic and social welfare in an equitable manner without compromising the sustainability of vital ecosystems and the environment (GWP, 2018). Therefore, promoting irrigation and building irrigation infrastructure without due consideration to establishing an accompanying enforceable regulatory framework to regulate the accessibility of water resources and regulate water demand through permits, restrictions and allocations to various users can arguably be seen to be unsustainable or be a maladaptation since this limits the extent to which water may be equitably accessed and utilised between the various stakeholders and user groups, and this is also contrary to the IWRM principles which call for a balance in economic and social benefits amongst different water resource users.

4.3 Climate Change and Water Sector Maladaptations: The Solutions Maladaptations – whether created through physical oversights or through institutional oversights – need to be minimised to ensure the sustainable management of water sources and courses and to reduce the occurrences of disasters for people

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living near water courses. In a bid to understand the causes of climate change vulnerability and the causes of hydrological disasters, Marigi (2017) emphasised that weather-related natural hazards are not always harmful; however, once the natural hazards interact with people, infrastructure, livelihood systems and governance systems, damages and disasters may happen. With this in mind, it might be argued that policies aiming to reduce the climate change and hydrological maladaptations and vulnerabilities in the context of Africa should not only have a focus the understanding the utility/uses of the various water sources/hydrological systems but also the financial capacities and capabilities of the institutions tasked with planning and managing hydrological resources. Using Malawi as an example, in general terms: Malawi’s water resources are used for a number of purposes, including human use (potable water supply and sanitation), agriculture, mining and electricity generation using hydropower schemes. In 2010, human use and irrigation together made up the majority of Malawi’s water demand for the consumptive use, totalling 21% and 77%, respectively (GoM, 2012; Nhamo et al., 2016). However, there are two main threats to water sustainability in Malawi. Firstly, unsustainable agricultural water use has been the cause for soil degradation, groundwater depletion, water pollution and water-related ecosystems degradation (Dile et al., 2013). Secondly, water degradation due to industrial and agricultural pollution contributes heavily to water scarcity (Kumambala, 2010). With these two issues in mind, it can be argued that improving water use, efficiency and consumption in the agricultural sector and improving agricultural practices may arguably enhance sustainable water management in Malawi (and other SSA countries that have high water usage through irrigation and agriculture). Accordingly, some of the options that policymakers and communities could have to improve the utilisation of water in rural communities and to ameliorate the impacts of floods and droughts on the agriculture sector include (i) the enhancement of infrastructural safety (building of flexible flood defence structures), (ii) building water storage dams and (iii) promoting rainwater harvesting (NASAC, 2015). However, in keeping with the observations of Marigi (2017) and Satterthwaite et al. (2018), addressing the physical deficits for reducing vulnerability in communities is insufficient to manage disasters, hence, the need to improve the understanding of the institutional factors influencing disasters and vulnerability in a community or country. In the case of Malawi, it can be argued that the country’s disaster risk management framework is attempting to simultaneously enhance the physical and institutional attributes for reducing vulnerability through various projects. For example, GoM (2015b) and World Bank (2016) showed that the flood and drought resilience and recovery projects in the country have various components that emphasise the simultaneous enhancement of physical and institutional strategies such as rehabilitating damaged infrastructure (e.g. buildings and irrigation schemes), improving water resources management (e.g. riverbank protection and installation of flood protection bunds), initiating labour intensive public works programmes to improve the incomes for vulnerable populations and strengthening institutions tasked with policy development and disaster preparedness and post-disaster recovery. More details on these approaches can be sourced from the Malawi Floods Emergency Recovery Project

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(MFERP) (GoM, 2015b) and Malawi Drought Recovery and Resilience Project (MDRRP) (World Bank, 2016). Since both the MDRRP and the MFERP were primarily financed through grants from multilateral lenders, it is evident that the disaster risk management sector in Malawi and other similar SSA countries could greatly benefit from the availability of more climate funds related to disaster risk management to complement the existing projects in this sector that are implemented through local and international financing. Additionally, Saunders (2019) considered the low levels of usage of climate finance modalities in some countries to be attributed to the low institutional capacity of most SSA countries to develop international climate finance projects and low institutional capacity to manage substantial funds. However, since existing disaster risk management projects are also focusing on building local institutional capacities, it might be argued that such institutional capacity activities will not only help with enabling countries to develop better disaster risk management policies and networks but could also help with enabling such countries to attract more climate finance in the long-run. On another note, the agriculture sector influences water access and availability through the direct abstraction of water and influences water pollution and environmental degradation through input use and agricultural practices. Addressing these concerns, therefore, calls for encouraging rural communities to utilise various strategies that have an emphasis on simultaneously improving agricultural productivity, maintaining water flow and quality and sustaining ecosystems. Such strategies include Ecosystem Based Adaptation (EBA), Climate Smart Agriculture (CSA) practices and Conservation agriculture (CA). EBA refers to the implementation of agricultural management practices that use or take advantage of biodiversity, ecosystem services or ecological processes (either at the plot, farm or landscape level) to help increase the ability of crops or livestock to adapt to climate variability (e.g. the use of mulching or local species as cover crops to help conserve soil structure, the use of fertiliser trees, etc.) (Vignola et  al., 2015). EBA approaches can also reduce disaster risks through nature-based systems for regulation of microclimates and flood prevention, which can avoid the maladaptations that happen when communities invest in engineering solutions using flawed climate change projections and scenarios (Midgley et al., 2012). CSA encompasses practices that help to sustainably increase agricultural productivity, adapt and build the resilience of agricultural and food security systems and reduce the greenhouse gas emissions from agriculture (Maguza-Tembo et  al., 2017). CA encompasses agronomic practices that promote minimal soil disturbance, year-round ground cover and crop rotations in order to sustainably improve water use efficiency, reduce soil erosion and boost crop production (TerAvest et al., 2015). Some of the aspects that have constrained the wide-scale deployment of EBA, CSA and CA approaches despite their good credentials on enhancing resilience and reducing disaster risks include (i) poor monitoring of programmes affecting the ability of management actions to be appropriately adjusted in response to changing conditions, (ii) a lack of or irrelevant knowledge/information on climate change, (iii) limited extension services in rural areas and (iv) the knowledge gaps about the costs and benefits of implementing agriculture sector environmentally friendly climate change mitigation and

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adaptation strategies (Spires et al., 2014; Colls et al., 2009; Maguza-Tembo et al., 2017). Arguably, the current scenarios are pointing out that there is an underinvestment in agricultural extension services, and this is limiting the diffusion and impacts of EBA, CSA and CA in the climate change vulnerability and disaster management fora. Accordingly, it could be sensible to start promoting the use of climate finance modalities to increase the investments in agricultural extension services that can enhance the development and implementation of EBA, CSA and CA activities. From the analysis provided above, there are strong indications that the use of approaches such as EBA are important in the SSA context since they can mitigate the impacts of floods and disasters to communities whilst also exploring the opportunities for reducing the vulnerability of ecosystems, biodiversity and communities to climate change. In North Africa, some research pointed out that the various North African countries have similar water and hydrology-related climate change exposures and vulnerabilities; hence, it was suggested that more efforts should go into increasing regional cooperation between countries focusing on sharing good practice to mitigate the impacts of climate change (Schilling et al., 2020). This observation seems to also align with the studies by Faiyetole and Adesina (2017) who suggested that in Africa’s context, regional climate change initiatives are more effective than national initiatives by up to a factor of 8. These considerations therefore provide two salient points to guide policymakers. First, it suggests that there is a need for policymakers in SSA to put more weight on establishing the modalities for viewing and exploring how different countries can be managing climate vulnerabilities collectively as regional blocks, since this can improve the effectiveness of disaster risk management activities. Second, it suggests that there is a need to explore how the various climate finance modalities are amenable to the implementation of regional programmes more particularly if there will be a need for different countries to mobilise local resources for climate change programmes rather than international climate finance.

5 Reducing Economic Vulnerabilities and Hydrological Stress: The Role of Non-farm Enterprises An assessment by Al-Gamal et al. (2009) showed that climate change is likely to impact groundwater resources, either directly, for example, via changing precipitation patterns, or indirectly, for example, through the interaction of changing precipitation patterns via changing land-use practices and water demand. Kusangaya et al. (2014) concluded that given the already large spatial and temporal variability of climatic factors in regions such as Africa, climate change impacts on water resources are likely to be more pronounced in the near future than previously foreseen. With these two considerations in mind, it might be posited that reducing communities’ dependence on water for agricultural livelihoods could mitigate disasters and economic vulnerabilities. This section therefore provides a narration of how transitions

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to non-farm enterprises can improve disaster resilience and the implementation of SDG 1.5 (build the resilience of the those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and environmental shocks and disasters) and SDG 1.b (create sound policy frameworks, based on propoor and gender-sensitive development strategies, to support accelerated investment in poverty eradication actions). The current ambitions as presented in NDCs submitted to the UNFCCC falls far short of reaching any of the goals in the Paris Agreement and the global goal to limit temperature increase to 2 °C (Röser et al., 2016; Day et al., 2016). It has therefore been pointed out that between now and 2030, climate change policies and stringent global emissions reductions can do little to alter the amount of global warming that will take place, and as such a plausible option, therefore, is to reduce the vulnerability and poverty through the targeted adaptation investments and improved socio-­ economic conditions (i.e. increase rural incomes, lower poverty and inequality, etc.) (Hallegatte et al., 2016; Biesbroek et al., 2010). In the case of Malawi, it has been suggested that Malawi’s climate change-related costs are equivalent to losing at least 5% of the country’s Gross Domestic Product (GDP) each year (GoM, 2016b). At continental level, a failure for countries and communities to adapt to climate change is projected to force more than 86 million people in SSA to move within their countries’ borders by 2050 (Rigaud et al., 2018), hence perpetuating the potential for more social conflicts and competition for resources such as water and land. This can further increase the social and economic costs attributed to climate change damages and adaptation interventions. With such a diverse range of socio-economic costs related to initiating climate change adaptation programmes and/or rectifying the damages due to the failures to adapt to climate change, it can be argued that new policies and innovations focusing on improving investments into sectors and infrastructure that can enhance climate change adaptation require to be closely integrated with broader policies for inclusive development and poverty alleviation. Globally, in addition to ensuring food security, the agriculture sector also provides livelihoods for almost two-thirds of the world’s extremely poor, or some 750 million people (FAO, 2016), and agriculture is the economic and social mainstay of some 500 million smallholder farmers in developing countries, making the sector to be the largest source of incomes, jobs and food security (World Bank, 2017). Unfortunately, climate change has the potential to decrease the output and productivity of the agriculture sector. For example, Africa’s 2015–2016 drought led to drought-induced declines in maize estimated to have reduced GDP in the SADC region by 0.1 percentage point and increased poverty by 1.4 million people (World Bank, 2017). Similarly, on a national scale, climate change and variability are considered to have increased the frequency of floods and droughts in Malawi (World Bank, 2016; GoM, 2015b). Floods and droughts in Malawi are therefore expected to constrain development and prosperity in the country since some studies have indicated that up to US$12.5 million (1% of Malawi’s GDP) and US$9 million (0.7% of Malawi’s GDP) is the annual cost of addressing droughts and floods, respectively (GoM, 2016b), and in the last 36  years, over 24 million Malawians have been adversely affected by eight major droughts in the country (World Bank,

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2016). These scenarios presented arguably illustrate that the hydrological and climatic perturbations will constrain socio-economic development in Malawi and other countries with a heavy reliance on agriculture. Various local development plans and disaster risk management strategies and policies for countries such as Malawi have been criticised for having an emphasis on providing relief after climatic shocks strike rather than fostering adaptation and ex-ante support (WEF, 2015); hence, this approach can increase the vulnerability of communities to the economic shocks in the light of the increasing threats of water stress and occurrences of floods and droughts. This lack of pro-active approaches in the disaster risk management strategies can also be criticised as it limits the potential to integrate the local development plans with disaster risk management policies to improve the people’s livelihoods, more particularly in creating non-farm enterprises. In this regard, when an analysis of SSA rural household spending and incomes are undertaken, it can be seen that non-farm enterprises are a complement to agricultural enterprises; hence, increasing the role or income from non-farm enterprises in households can in some cases help households to transition from a dependence of high water intensity agriculture systems to businesses and entrepreneurial activities with less dependence on water and agriculture and as such increase household incomes and resilience to disasters and climate change vulnerability. This follows that whilst it might be expected that farming communities would borrow money to buy inputs for their farming activities, in actual fact, some research has pointed out that farming communities usually borrow money or use credit to buy stock and inputs for their non-farm business start-ups and non-farm enterprises. Interestingly, this suggests that farmers prefer to use loans and credit to finance the set up/expansion of their non-farm enterprises and then use the generated cash from these non-farm enterprises to finance external input purchases of seeds, fertiliser and so forth for their farms (Adjognon et al., 2017; Christiaensen, 2017). What is also important to consider is that 44% of households in rural Africa participate in the non-farm economy (Nagler & Naudé, 2017) and that rural households in Africa currently derive about two-thirds of their income from on-farm agriculture but are on a trajectory to have an average of one-third (on average) of their income earnings from on-farm agriculture as the case is in other developing countries (Christiaensen, 2017). Arguably, when consideration is made to these factors, one can hypothesise that on one hand, the importance of non-farm enterprises to the incomes of rural communities and rural households will gradually increase and on the other hand, the increased dependence on non-farm enterprises in Africa as the case is in other developing regions might reduce the water demand and hydrological stresses of some localities due to a reduction in water demand from agriculture. The development of climate change programmes and socio-economic development policies and strategies that focus on supporting the development of non-farm enterprises in rural Africa could therefore be considered as viable strategies that can improve hydrological resilience and mitigate disasters. This follows that non-farm enterprises can foster climate change adaptation and improve disaster risk management by enabling governments to create jobs and enabling households to increase incomes, build assets and acquire technologies for water saving without having to increase their

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investments and demands on land and water sources. As a reference point, a study by Allam and Jones (2018) showed that improvements in waste management and recycling in Benin could help create more than 3200 permanent jobs in the economy, hence, showing that many African countries have various under-exploited non-farm enterprises and industries that can create new non-agriculture-based jobs and incomes. In this case, climate finance programmes should therefore also consider supporting entrepreneurship and enhancing the capacities of rural households to successfully establish and scale-up non-farm enterprises as a means for reducing climate change vulnerability.

6 Discussion Climate change is not happening in a vacuum but rather in societies that have varying levels of vulnerability to climate change and disasters due to factors such as differences in the rates of social-economic development, industrial growth, fiscal space and demographic transitions. At a global level, unmitigated climate change could exacerbate the losses from climate-related disasters and ultimately lower average global incomes by 23% by the year 2100 (Haworth et al., 2016). Similarly, many African countries are already water scarce, and it is projected that in Southern Africa food, security and water availability might become compromised as annual rainfall is expected to decrease by 20% by 2080 due to climate change (Nhamo et al., 2018). The attainment of the SDGs in many African countries is therefore closely hinged to how climate finance and other financing mechanisms are utilised to augment disaster risk management, hydrological resilience and climate change resilience. A lot of discourse on the climate change and water nexus in Africa is arguably focused on the impacts of climate change on the availability of water for agricultural industries (Nhemachena et al., 2020; Nhamo et al., 2016; Dile et al., 2013; Shiferawa et al., 2014). This could be attributed to the importance of Africa’s agriculture sector to job creation and socio-economic development since the agriculture sector supports up to 60% of rural populations in different African countries. Climate change-­ induced hydrological changes are projected to lead to agricultural productivity reductions of between 15% and 50% (Nhemachena et  al., 2020); hence, climate change has significant ramifications on the incomes of people and industries that depend on agriculture. Notwithstanding the aforementioned considerations, many developing countries are also under pressure to ensure the availability and sustainable management of water and sanitation in order to attain the SDG 6 (sustainable management of water). In order for this goal to be met, policies and strategies aiming to promote the sustainable management of water and sanitation need to pay due consideration to (i) promoting the need to conserve and sustainably use oceans, seas and freshwater resources, (ii) protecting biodiversity and ecosystems, (iii) tackling water scarcity and water pollution and (iv) strengthening cooperation on desertification, land degradation and drought (UN, 2015). Paradoxically, whilst climate change

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vulnerabilities, water stresses and hydrological stresses are increasing, the resources available for enhancing hydrological resilience through financing of water sector investments and sustainable water resources management through ODA are arguably decreasing (i.e. ODA funding commitments to the water sector have dropped by more than 25% between 2012 and 2016 (UN, 2018)). Added to this, the global financing system for development is undergoing reforms in that the global development finance landscape is changing from a model centred on ODA and the coverage of remaining financing needs through external debt to a framework with greater emphasis on the mobilisation of domestic resources (Nnadozie et  al., 2017). Similarly, at national level, in some countries, only about 3.5% of government spending goes to climate change, disaster and water issues, despite these being priority areas in the national policies (England et  al., 2018). These issues arguably mean that the financial and technical resources available for the programmes to reduce the vulnerabilities to hydrological extremes and mitigating the disasters could be decreasing, and as such, leaving the SSA governments with less funding for water sector infrastructure investments, capacity building, hydrological monitoring and prediction and policy reforms. Whilst developing countries can initiate fiscal reforms in order to enhance their potential to implement programmes for SDG 6, climate change and disaster risk management through internally generated resources and domestic taxes (Nnadozie et al., 2017; Begashaw & Shah, 2017), the current data suggest that government efforts to increase domestic revenues and improve tax collection have not been very encouraging in many developing countries. For example, the rate of taxation (ratio of tax revenue to GDP) in LDCs declined from the peak of 11.1% in 2012 to 8.8% in 2016, and for SSA countries, there was a decline from 14.9% in 2006 to 10.7% in 2016 (UN, 2018). The low tax collections could increase the likelihood that developing country governments might not have the potential to mobilise adequate resources to attain the SDG 6 goals, enhance hydrological resilience and improve disaster risk management. However, on a positive note, it can be seen that some climate change outcomes as implemented through climate finance and SDG 13 could have a lot of relevance to the achievement of some SDG 6 outcomes. For example, the programmes for strengthening resilience to climate-related hazards and natural disasters (SDG 13.1) could have synergies with the programmes for implementing IWRM (SDG 6.5), especially where nature and ecosystems are used to mitigate hazards rather than some engineered solutions. This therefore means that the SDG 6 experts and project implementers can reduce SDG 6 finance gaps as caused by reductions in ODA through the policies and strategies that align the SDG 6 objectives with SDG 13 programmes so that SDG 6 programmes may be implemented through climate finance. In attempting to understand how the SSA countries prioritise the various climate change-related sectors and programmes, there is a need to determine how NDCs depict the current and future vulnerabilities for countries. NDCs play a vital part in facilitating the successful transitions of countries from the positions of climate change vulnerability to positions of successful climate change adaptation as they provide an analysis of the various vulnerabilities in different sectors in a country

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and the proposed strategies and projects aimed at addressing these vulnerabilities. To date, most NDC policy debates have focused on the failure of the NDCs framework to reach the Paris Agreement’s target of limiting global temperature increase to 2 °C (Röser et al., 2016; Jiang & Hanaoka, 2017; Zhang & Pan, 2016), and as such, the inadequacies of some NDCs in addressing climate change-induced hydrological vulnerabilities and water sector vulnerabilities may not have yet been thoroughly debated. In this regard, the Global Water Partnership (GWP, 2018) undertook an analysis of water-specific commitments in the NDCs of 80 countries in order to ascertain the alignments between NDCs, SDG 6 implementation and national development planning processes. The Global Water Partnership (GWP, 2018) subsequently discovered that despite SDG 6.5 calling for the international and national policymakers to implement IWRM at all levels, including through transboundary cooperation as appropriate, from the NDCs analysed, only a quarter of the countries planning for water-related adaptation explicitly referred to taking an integrated approach across sectors and levels, and a large majority (over 80%) of water-stressed countries in the sample did not prioritise IWRM. Additionally, it was also discovered that in terms of NDCs water-related priorities, for most countries, actions promoting investments in governance and institutional aspects in the water sectors were ranked above actions promoting investments in infrastructure. These issues therefore highlight that the prioritisation of IWRM could be weak in the NDCs of many water-stressed countries and that climate change policies could have weak links to IWRM as a strategy for enhancing resilience to disasters and climate change. When reference is made to Smucker et  al. (2020), England et  al. (2018), Nhamo et  al. (2018) and Nyandiko (2020), it was discovered that even though climate change adaptation, disaster risk reduction and land restoration have various linkages, the disaster risk reduction and climate change adaptation institutions operate asymmetrically or in silos; hence, the convergence of these different agenda may be achieved through informal working platforms for intersectoral collaboration between state and non-state actors rather than through formal mechanisms of policy integration established in law. This therefore suggests that addressing the low prioritisation of IWRM as a strategy for enhancing resilience to disasters and climate change can still be pursued through networks, platforms and “informal policies,” thereby increasing the potential for climate finance to still contribute towards SDG 6 financing despite the shortfalls in NDCs.

7 Conclusions Climate change has the potential to adversely affect most, if not all, of the societies in Africa; hence, there is an urgent need for policymakers in Africa to ensure that climate change impacts, such as recurring climate extremes like droughts and flooding, do not lead to disasters and economic vulnerabilities in communities. On the other hand, the implementation of SDG 6 can lead to sustainable economic growth in Africa by ensuring the availability and sustainable management of water for

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various uses so that the adverse impacts of water scarcity and droughts on households and communities are mitigated. However, there are some threats that hydrological resilience, access to water for households and industries and disaster risk management might be compromised because (i) some countries have incoherent policies across sectors and these cause climate change maladaptations, (ii) some fiscal reforms in SSA countries have been unable to significantly improve the mobilisation of domestic taxes for financing socio-economic development programmes and (iii) water sector investments in SSA could be declining due to reduced ODA allocations for the water sector. However, with the UNFCCC and Paris Agreement both advancing for increased climate finance disbursement to support climate change adaptation and resilience in developing countries, there are renewed prospects that climate finance can be used to augment disaster risk management, SDG 6 activities and hydrological resilience programmes simultaneously. What is now needed in the disaster risk management framework is for SSA countries to address their challenges in implementing programmes that cut across different sectoral policies since this challenge increases the threats of climate change vulnerability and disasters in many communities and countries. This chapter therefore provides some narratives and analyses of the issues that magnify climate change vulnerability and disasters and the policies and approaches that can enable climate finance to improve the implementation of water sector programmes for disaster risk management and hydrological resilience. Many developing countries have shown their commitment to enhance climate change mitigation, climate change adaptation and disaster risk management as evidenced from the various NDCs that the developing countries submitted to the UNFCCC. However, since some research has shown that most NDCs are not well aligned to the SDG 6 aspirations as they lack water-specific commitments and integrated approaches for water-related adaptation, there are threats that the linkages and synergies between SDG 13 and SDG 6 could be under-exploited, and this could inadvertently increase the cost of implementing policies and programmes since the policy conflicts increase the technical and financial costs for implementing programmes. With the above considerations in mind, climate finance projects should not only focus on addressing the immediate and direct climate change related activities but emphasis should also be made to utilising climate finance to increase the institutional and technical coherence between SDG 6 and NDC activities. Climate change has various implications for the socio-economic development and disaster risk frameworks of different countries. This therefore means that the SSA policies and approaches for supporting hydrological resilience, disaster mitigation and climate change adaptation have to address both the immediate-term and long-term climate change vulnerability and disaster risk management issues. With these issues in mind, the following considerations may be prioritised: 1. Some SSA countries could be susceptible to climate change vulnerability, disasters and maladaptations due to over ambitious political agenda that exacerbate policy conflicts since some political agendas are not in synch with technological and physical realities. Addressing this challenge will call for climate finance

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modalities to finance processes that can enable frequent and systematic policy reviews/updates across development sectors so that political aspirations and national policies are continuously aligned. 2. In some instances, regional cooperation on disaster risk management enhances disaster resilience, and regional climate change initiatives are more effective than national initiatives. This therefore suggests that the impact of climate finance on disaster risk management processes might be amplified when climate finance is used to initiate regional disaster risk management programmes. 3. The SSA disaster management processes need to be reformed to have more focus on providing ex ante support rather that providing relief. This therefore means that climate finance modalities could have a greater influence on supporting disaster risk management processes and the implementation of SDG 1.5 and SDG 1.b by promoting entrepreneurship and the development of non-farm enterprises, since these actions can reduce the dependence of peoples’ incomes on high water dependency activities/agriculture.

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Part II

Extreme Hydro-Meteorological Events: Flood, Drought, Precipitation and Temperature

Chapter 7

Assessing Risks and Resilience to Hydro-­Meteorological Disasters Never Mujere

Abstract  Hydro-meteorological disasters negatively impact ecosystems and livelihoods in many ways. These disasters are commonly associated with hydrological droughts and floods. Nevertheless, farmers always learn and adopt strategies to reduce effects of impending disasters in their localities. Effective coping strategies require sound understanding of the drivers of these hydrological disasters. This paper gives an overview of the current state of scientific knowledge on disaster management framework, hydrological droughts and flooding. It models hydro-­ meteorological disasters and discusses the strategies employed by farmers at Nyanyadzi smallholder irrigation scheme in Zimbabwe to mitigate disasters. Crop yield and river flow data were obtained from irrigation scheme files. The research findings highlight the temporal variations of hydrological droughts and how drought management strategies have been ineffective as coping mechanisms. The importance adopting of community-driven integrated disaster management approach coupled with a better understanding of management options is crucial for improving decision making in disaster events. Keywords  Adaptive capacity · Disaster · Hazard · Modelling · Risk · Vulnerability · Hydrological drought · Floods · Nyanyadzi · Zimbabwe

1 Introduction Hydro-meteorological extremes such as droughts and floods are common phenomena and frequently occur in various places across the world. They are transformed or exacerbated by human action or inaction. Flooding and droughts cause loss of harvests, enormous displacements, disruptions of access to critical services, damage N. Mujere (*) Department of Geography, Geospatial Science and Earth Observation, University of Zimbabwe, Harare, Zimbabwe © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_7

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to property and life and loss in industrial production due to damage to factories or a resulting shortfall in supply of raw materials (Caloiero, 2018). Flooding causes long-term damage to health, with immediate impacts such as drowning, physical trauma, infections and chemical hazards, and also affects well-being, livelihoods and social cohesion. It has direct and indirect knock-on effect on other critical infrastructure such as railways and wastewater services (Kundzewicz & Kaczmarek, 2000). Storms and droughts kill tens of thousands of people worldwide and display millions every year. More than 3000 people died in China’s catastrophic Yangtze River flood, millions were displaced, and the financial burden was estimated to be US$30 billion (Annan, 1999). Significant devastating effects of disasters on ecosystems and society call for implementing multi-sectoral and interdisciplinary solutions across a broad range of professions, private and public agencies. To address the complex challenges, improvements in disaster risk assessment and loss estimation methodologies have been identified in the Hyogo Framework for Action (2005–2015) and the Sendai Framework of Disaster Risk Reduction (2015–2030). The Hyogo Framework for Action aimed at addressing disaster risk factors by involving action across multiple sectors as part of resilience building. It has been an important instrument for raising public and institutional awareness, generating political commitment, and focusing and catalysing actions by a wide range of stakeholders at all levels. The Sendai Framework for Disaster Risk Reduction 2015–2030 was adopted at the third United Nations conference on disaster reduction held from 14 to 18 March 2015 in Sendai, Japan. The goal of the Framework is to prevent new and reduce existing disaster risk through the implementation of integrated and inclusive social, cultural, economic, political, legal, health, educational, environmental, technological and institutional measures that prevent and reduce hazard exposure and vulnerability to disaster, and increase preparedness for response and recovery, and thus, strengthen resilience.

1.1 Disaster Management Framework Disaster management seeks to reduce the vulnerability of societies to the effects of hazards and also to address the man-made causes. However, there are many uncertainties in knowing when and where disasters are likely to occur both in space, in the immediate term and in long timescales (Caloiero, 2018). Nevertheless, there are many things that we can do to prepare for disasters and manage the risk. These include strengthening components of disaster prevention, preparedness, response, rehabilitation, reconstruction, mitigation and recovery (Fig. 7.1). Advances in early warning of disasters is important for prevention, to facilitate relief operations and to allow people to move out of harm’s way (UNSDR, 2009). Improvements in wide-area satellite surveillance technologies are revolutionising the collection of early-warning data relevant to disaster prevention. The internet is facilitating the real-time dissemination of satellite-derived and other warning data. There is a clear financial incentive for taking prevention more seriously. In the 1960s, natural disasters caused some US$52 billion in damage; in the early 1990s,

7  Assessing Risks and Resilience to Hydro-Meteorological Disasters

Preparedness Action to increase capacity of a community for prompt and efficient response.

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Disaster Impact

Mitigation Action to prevent property damage and minimize economic impacts. Prevention Action to mitigate the severity of impact.

Response Effectiveness depends on training and experience of emergency response teams.

Recovery Action to assist communities/nation to return to pre-disaster level of functioning.

Redevelopment Action to redistribute economic losses (there should be a long-term link between disasterrelated activities and national activities.

Fig. 7.1  Critical activities in disaster management cycle

the cost reached US$479 billion (Annan, 1999). Effective prevention strategies save billions of dollars and thousands of lives annually. Funds currently spent on intervention and relief could be devoted to enhancing equitable and sustainable development instead, which would further reduce the risks of disasters. However, building a culture of prevention is not easy. Whilst the costs of prevention have to be paid in the present, its benefits lie in the distant future. Moreover, the benefits are not tangible, they are the disasters that do not happen. It is not surprising that preventive policies receive support that is more often rhetorical than substantive. The recovery phase occurs after the disaster has passed. It includes relief measures, reconstruction and event analysis. Often, this phase is aligned with the aim to achieve a similar economic standard to that before the event. If society has learned from the event, then any recovery is followed by a disaster risk-reduction phase, which includes preventive measures (e.g. creating natural retention in catchments, changing land use, rethinking urban design, planning and architectural norms and implementing structural flood defences) and precautionary measures (e.g. supporting insurance).

1.2 Disaster Risk Assessment Disaster risk is the expected losses (e.g. lives, health status, livelihoods, assets, persons injured, damage to property and disruption of economic activity), which occur in a particular community or a society over some specified future time period

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(UNSDR, 2009). This definition reflects that a disaster is the realisations of risk that occur when a hazard occurs in a vulnerable or susceptible society, environment and economy (UNSDR, 2009). Vulnerability describes factors or constraints, for example, economic, social, physical or geographic, which reduce the ability to prepare for and cope with the impact of hazards. For example, below-normal streamflows (hazard) in an irrigation scheme (vulnerable area) cause loss of crop yield (disaster). This means that hazards alone do not cause disasters, unless they are exposed to elements at risk. Figure 7.2 shows that disaster risk (risk related to particular hazards) results from the interaction between hazards and vulnerability conditions. Disaster risk (R) is the probability of loss which is estimated as the product of hazard (H) and vulnerability (V). Vulnerability is calculated as the sum of sensitivity (S) and exposure (E) of elements at risk less adaptive capacity (A). Sensitivity is the likelihood to experience harm or susceptibility of people or property to the effects of the hazard. Thus, horticultural crops are more affected and respond faster to droughts than cereals. Exposure is the duration to which systems or other elements present in hazard zones are subject to potential losses. Growing crops in greenhouses reduce their exposure to frost attack. Adaptive capacity (A) is the ability to reduce, moderate, cope and adapt to disaster risk. In disaster-prone areas, structural and non-structural interventions to limit the impact of disaster include risk zoning or mapping, raising awareness, early warning systems, evacuation of settlements and disaster relief (Sarma, 1999; Kundzewicz & Kaczmarek, 2000).

Floods, torrential rains, storms, etc.

People, property, etc.

Hazard

Exposure

Disaster Risk

Resistance

Vulnerability Fig. 7.2  Components of the disaster risk

against

hazards

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Hazard mapping as a non-structural strategy is carried out by experts to establish, for defined geographical areas, the extent to which a hazard pose a threat to people, property, infrastructure and economic activities . Data over extensive areas collected during fieldwork or from remotely sensing platforms are analysed and displayed in a Geographic Information System (Sarma, 1999).

1.3 Hydrological Droughts Hydrological droughts occur when water supplied is less than water demanded for crop production due to negative anomalies in surface and subsurface water systems (Caloiero, 2018). This is due to a significant reduction in water availability below the expected amount for a specified period in a particular area. Such lack of water in the hydrological system manifests itself in abnormally low river flows and abnormally low levels in lakes, reservoirs and groundwater (Van Loon, 2015). The droughts can, however, cover extensive areas and can last for months to years, with devastating impacts on the socio-economic and ecological systems. The classification of hydrological droughts by Van Loon (2015) is based on their causative factors and propagation processes. Hydrological droughts are thus classified into classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-­ season drought, cold snow season drought, warm snow season drought, snowmelt drought, glacier melt drought and composite drought. A drought in this wet season decreases storage and can influence dry conditions. During the dry season, potential evapotranspiration is generally higher than precipitation, which potentially gives evapotranspiration a larger role in drought development. This type of hydrological drought is termed wet-to-dry-season drought and was found to occur predominantly in Mediterranean, savannah and monsoonal climates. Table  7.1 summarises the underlying processes for each hydrological drought type, related to precipitation (P control), temperature (T control), or a combination (P/T) of both. River flow droughts are periods during which flows are below specified threshold levels (Madsen & Rosbjerg, 1995; Bonaccorso et al., 2003). By setting up a partial duration series consisting of drought events that do not exceed a specified threshold, Qr, independent drought sequences are thus created. Each drought flow below Qr defines a drought event E. Consecutive drought occurrences were pooled together to make one drought event (Tallaksen et al., 1997). Independence in drought events is due to relatively long average lapse of time between consecutive events. Threshold levels are commonly defined by quintiles such as the mean or median flows (Zaidman et al., 2001), specific reservoir yields (Loáiciga, 2005), percentages of the mean flow and the flow duration curve (Zelenhasic, 2002) and irrigation crop water requirements (CWRs). Knowledge of the characteristics of river flow drought processes assist water managers to make decisions about mitigation measures, properly manage water resources and provide information for the design of supply infrastructure such as dams (Woo & Tarhule, 1994).

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Table 7.1  Types of hydrological droughts based on propagation processes including temperature (T) and precipitation (P) controls on development and recovery Type of hydrological drought Classical rainfall deficit drought Rain-to-snow-­ season drought Wet-to-dry-­ season drought Cold snow season drought

Warm snow season drought Snowmelt drought Glacier melt drought Composite drought

Governing process(es) Rainfall deficit in any season

Development P control

Recovery P control

Rainfall deficit in rain season, drought continues into snow season Rainfall deficit in wet season, drought continues into dry season Low temperature in snow season leading to early beginning of snow season (Sub-type A), delayed snow melt (Sub-type B) and no recharge (Sub-type C). High temperature in snow season leading to (i) Early snow melt (Sub-type A) in combination with rainfall deficit (Sub-type B) Lack of snowmelt in spring due to low P or high T in winter Lack of glacier melt in summer due to low T in summer Combination of a number of drought events over various seasons

P control

T control

P control

P and T control T control

T control

T control P and T control P and/or T control T control P and/or T control

P control P control P control P or T control P control

Source: Modified from Van Loon (2015: 366)

1.4 Probability Distribution of Drought Events River flow droughts like floods are stochastic processes related to random phenomena. An appropriate way to investigate the statistical distribution of river flow droughts is by means of probability theory (Tallaksen et al., 1997). Owing to their uncertainty nature, theoretical distributions are applied to find out whether droughts can be described by such distributions. Modelling of hazard characteristics by probability distributions provides information helpful in water resources planning and management (Abaurrea & Cebrian, 2002). River flow droughts occurring in an interval (0, t) are stochastic processes, hence, a non-linear function of time. They are characterised by independent and identically distributed random variables (Tallaksen et al., 1997). An appropriate way to investigate the statistical distribution of river flow droughts is by means of probability theory. The description of drought characteristics by probability distributions provides information helpful in water resources planning and management (Abaurrea & Cebrian, 2002). Such information includes the number of droughts N, inter-­ drought recurrence time or frequency F, drought duration, D and drought severity H, which can be analysed by fitting statistical models such as geometric, Poisson and exponential to empirical data. Table 7.2 shows the statistical models for analysing probability distributions of drought events

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Table 7.2  Probability distribution of hydrologic droughts Drought statistic Number of river flow droughts, N

Explanation The probability P that n river flow droughts occur in a given period (0, t) is a Poisson process (Madsen & Rosbjerg, 1995). P  Nt  n  

 t  n!

n

e

 7.1

 t 

where λt is the mean or expected number of river flow droughts, e is the exponential function, t is the time period and n = 1, 2, 3…. Drought duration, D

The duration of river flow droughts is modelled using the exponential probability law (Madsen & Rosbjerg, 1995; Zelenhasic, 2002). D  u   1  e  u

Drought severity, H

 7.2 

where λ is the reciprocal of the mean of G. Drought severity is the sum of water deficits during the drought periods. It follows the exponential probability distribution (Zelenhasic, 2002). H  x   1  e  x

 7.3

where λ is the reciprocal of the mean deficit and x is flow in m3 Drought frequency, The frequency F of drought occurrence or return period.is the average F elapsed time between occurrences of drought events. It is based on the probability that a given event will be equalled or exceeded in any given period (Loáiciga, 2005). The expected frequencies are given as: F = mP  (7.4) where m is the total number of observed runs and P is the theoretical probability given by geometric distribution:   1 PR  r   1  p1  1  p2   p1r 1  p2r 1    p1  p2  

 7.5

where r represents the length of drought return period, p1 defines the probability of river flow drought and p2 is the probability of non-river flow drought. Example: Return period of 10 years means a disaster in a year has a 10% chance of occurring.

The probabilistic nature of low river flows implies uncertainty in forecasting irrigation water supply. Although several theoretical distributions may be fitted to the duration, deficit and time of occurrence of droughts, in this study, the Poisson distribution was selected because river flow droughts are independent and identically distributed random variables (Tallaksen et al., 1997; Woo & Tarhule, 1994).

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Fig. 7.3  Location of Nyanyadzi River system in Chimanimani district, Zimbabwe

Making the distinction between hydrological drought types is important for statistical analysis, attribution of change and prediction of hydrological drought development and recovery. A clear understanding the different processes underlying hydrological drought development is critical for devising preventive strategies that work.

2 Study Area Nyanyadzi irrigation scheme (Fig. 7.3) is a state-owned run-off river scheme located in Manicaland province in eastern Zimbabwe. It is administered and managed by the Department of Agricultural Rural Extension services (AGRITEX). The scheme occupies an area of 414 ha and was opened in 1934 (Mujere & Eslamian, 2014). It was established as a drought relief project in the semi-arid region Chimanimani district to provide food in an area of recurring droughts where peasants were only able to produce a meaningful harvest once in 5 years, reduce government cost in providing famine relief, and reduce the peasants’ method of shifting cultivation and consequential destruction of natural resources by setting them permanently on good soil where proper agricultural practices would occur and encourage peasant movement from subsistence to a cash economy to practise proper agricultural practices (UNDP, 2019).

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Nyanyadzi irrigation scheme has design efficiency of 70% below the field gate (Pearce & Armstrong, 1990). This means that 30% of water transferred from the field gate does not reach the crop root zone due to conveyance, distribution, field application and percolation losses. Seepage losses along the diversion unlined canal from the river account for 25% of the irrigation water supply (Pearce & Armstrong, 1990). The scheme lies at an altitude of 530 m in a down-faulted valley of the Save and Odzi Rivers. Soils are of alluvial origin comprising deep, well-draining sand loams and sand clays of high fertility underlain by coarse river sand. Considerable N–S and E–W faulting has resulted in a complexity of geological horizons outcropping in the area. Rocks comprise basement complex granites, limestones, quartzites of the Umkondo system and pre-Karoo dolerites. Temperatures are generally high with maximum daily temperatures for July and January being 25 °C and 31 °C, respectively. The mean monthly temperature range is about 10 °C. Highest and lowest mean monthly temperatures were experienced in October (25 °C) and July (15 °C), respectively (Fig. 7.4). The scheme receives less than 400 mm of rainfall annually. Hence, all rainfall is effective for crop production as recommended by the Meteorological Services Department (1983). The rainfall is unreliable and comprises erratic and isolated rainstorms. The rain season occurs between October and March, but the onset of the rains may be delayed until late December and terminate at the beginning of February. In such a dry region of the country, irrigation water is crucial to satisfy crop water demand. Figure 7.5 shows the mean monthly rainfall distribution at Nyanyadzi irrigation scheme. The total annual evaporation can rise to about 1900 mm whilst a daily maximum of 11 mm between September and February is often experienced. Annual evapotranspiration rates exceed rainfall even during the rainy season. The area’s mean annual evapotranspiration is about 123 mm while the aridity index (mean annual evaporation divided by mean annual precipitation) is 3.0 (Fig. 7.6). Nyanyadzi River flow pattern is seasonal in nature, with lowest flows occurring during the dry months, from April to November whilst high flows are experienced

Temperature, °C

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Fig. 7.6  Mean monthly evapotranspiration

from December to March. River flows occur at the peak of the rainfall season especially in January or February. They are dependent on the inter-tropical convergence low-pressure system and tropical cyclones from the Indian Ocean (Tumbare, 2000). Figure  7.7 shows the inter-monthly variability of Nyanyadzi river flow over the 33-year period from 1969 to 2003. Mean monthly flow is 3.54  ×  106 m3. With February having the highest mean monthly flow value of 11.23 × 106 m3 whilst in September, the lowest, 0.82 × 106 m3 were recorded. The average monthly coefficient of variation (CV) was 102%. February show highest variability (143%) whilst the lowest (66%) was experienced in November. Flows decrease from April to September since winter seasons are dry. Nyanyadzi irrigation scheme has been facing problems of seasonal water shortage since its establishment in the 1930s. This is due to changing regime of river flow and heavy siltation in the river channel, weir, main canal and night storage dam causing a decrease in storage capacity (Bolding, 2004). Besides causing crop yield reduction, low irrigation water supply often results in clashes between irrigators and other competing upstream water users (Mujere & Eslamian, 2014). Scarcity of water is more pronounced in Block C (65 ha), which depends solely on Nyanyadzi

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Fig. 7.7  Mean monthly river flows

River for its water supply. Farmers in blocks A (137 ha), B (147 ha) and D (69 ha) receive supplementary water from Odzi River via a night storage dam. Water from Odzi River constitutes about 60% of the 3 blocks’ water requirements. Figure 7.8 shows the layout of Nyanyadzi irrigation scheme. This study focuses on Block C of the irrigation scheme. It intends to identify and characterise in an objective way hydrological drought events in terms of their duration, frequency, severity and magnitude. This is achieved using the threshold concept, in which a drought event occurs when the hydrological variable under investigation remains below a fixed threshold or reference level (Madsen & Rosbjerg, 1995).

2.1 Data Collection and Analysis 2.1.1 River Flow and Crop Yield Data Monthly river flow data at station E119 across Nyanyadzi River were collected from the Zimbabwe National Water Authority (ZINWA). River flow measurements for gauging station E119 (Nyanyadzi River downstream of the proposed Nyanyadzi Dam) discontinued in February 2000 when the station was drowned by Cyclone Eline floods. E119 flow data were extended to September 2003 by regressing with E120 data. Thus, data spanned from October 1969 to September 2003. Data were used in estimating irrigation water supply. Crop yield data were collected from irrigation scheme files. The irrigation scheme extension officers collect information on cropped areas and crop production for each farmer every farming season.

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Fig. 7.8  Nyanyadzi irrigation scheme layout and water supply infrastructure

2.1.2 Bean Crop Water Requirements Crop water requirements (CWRs) for beans, planted on the 1st of April and harvested on the 30th of June, with a growing season of 120 days were estimated using the CROPWAT model version 5.1 model using meteorological and hydrological data for Nyanyadzi irrigation scheme (FAO, 1991). Estimation of CWR was done by taking into account the effect of climate (given as reference crop evapotranspiration, ETo) and crop characteristics (given by crop coefficients, Kc). ETo was estimated using the Penman-Monteith equation, and standard Kc values produced by FAO were used were used in estimating CWRs (FAO, 1991) as:

CWR = ETK (7.6)

2.1.3 Threshold River Flow The threshold river flow Qr that satisfies crop water requirements when seepage losses are taken into account was estimated from 80% of the seasonal bean crop water requirements (CWR). A figure of 80% of CWRs denotes the water stress level

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below, which significant yield reduction occurs. The cut-off or threshold level Qr distinguishes drought flows (when river flows, Q equal to or are below Qr) from non-drought flows (Q>Qr). Each flow below Qr defines a drought event. Once such a threshold was determined, it allowed for simultaneous definition of the main river flow droughts characteristics in terms of the number, duration and magnitude. 2.1.4 Irrigation Water Supply and Seepage Losses The relationships between Nyanyadzi River flows, Q and irrigation water supply IWS to Block C was established using measurements done by and Pearce and Armstrong (1990). Thus: IWS  0.04Q  7.5 (7.7) Seepage losses were estimated as a fixed proportion of 30% of IWS from the scheme’s design efficiency of 70%. Seepage losses along the unlined diversion canal were estimated to be 25% of IWS before 1996 as observed by and Pearce and Armstrong (1990). The diversion canal was lined in 1996; hence, seepage losses were assumed to be negligible since then. Thus, seepage losses L were estimated from:

L = cIWS (7.8)

Where the loss constants are c = 0.55 and 0.3 for the 1969 to 1995 and 1996 to 2003 periods, respectively. The drought magnitude or deficit volume S was obtained by subtracting net IWS from the threshold level flow Qr as (Abaurrea & Cebrian, 2002):

S  Qr  NetIWS (7.9)

Where:

NetIWS  IWS  L (7.10)

2.1.5 Estimation of River Flow Drought Event Statistics In this study, irrigation of beans, planted on the first of April and harvested at the end of June, with a growing season of 120 days is considered in analysing droughts. The duration of river flow droughts D was estimated as the number of consecutive bean crop seasons when flows Qt, were less than threshold Qr followed and preceded by at least one season interval where (Qt > Qr).

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3 Results 3.1 River Flow Droughts at Nyanyadzi Irrigation Scheme The seasonal bean crop water requirements (CWRs) of 80 × 103 m3 was estimated from CROPWAT model. Threshold flow value Qr of 64 × 103 m3 was estimated from 80% of CWRs after seepage losses were taken into account. Five consecutive drought events were experienced from 1991 to 1996. Two droughts events were experienced during the period 1970–1971 and 1983–1984. Whereas farmers experienced a drought event lasting for one season in 1973 and 1987. Figure 7.9 shows that 11 droughts were experienced during the 33 bean cropping seasons from 1969 to 2003. The mean deficit volume for the 11 droughts is 48 × 106 m3. The maximum deficit volume of 68 × 106 m3 occurred in 1992 when the nation experiences a drought of living memory, whereas least deficit volume is 15 × 106 m3 experienced in 1984 (Fig. 7.10). No bean crop was harvested from the fields in 1973, 1992, 1994 and 1995 (Fig. 7.11) as a result of poor water supply. Highest yields of 1.56 t/ha were obtained in 1974 when water supply was adequate. During seasons of zero crop yields, the amount of water received (rainfall and irrigation water supply) in Block C was too low to sustain crop productivity. The block received 39 mm in 1973, 5 mm in 1992, 24 mm in 1994 and 11 mm in 1995. These figures are too low compared to the seasonal bean crop water requirements of 309 mm. Nevertheless, in some seasons which experienced droughts, farmers harvested more crop than when water supply was adequate and vice versa (Figs.  7.10 and

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Fig. 7.10  Drought magnitude during bean cropping seasons 1.8 1.6 1.4 Yields, tha

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0 Cropping Seasons

Fig. 7.11  Bean crop yields

7.11). Improved water use efficiency in the fields could account high yields during periods of water shortage and vice versa. Also, this lower yields during seasons of water supply adequate can be attributed to water wastage and leakages along the distribution systems.

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3.2 Coping with Hydrological Droughts Farmers at Nyanyadzi irrigation scheme have learnt to live with hydro-­meteorological disasters to such an extent that they recognise that river flow droughts continue to happen as it is a natural phenomenon. They are always employing adaptation strategies during periods of water shortage. Actions to adjust, recover, manage, prevent or reduce the adverse effects of hydrological droughts are taken before, during, or after the hazards. Over time, they have learnt to live with river flow droughts. Farmers and the responsible authorities embark on upstream destruction of illegal gardens to improve downstream water supply. Upstream raids were conducted during winter seasons in 1968, 1984, 1987, 1988, 1991, 1994 and 1995. However, upstream raids are said to have little success because illegal irrigators reconstruct their furrows soon after the raiders leave (Bolding, 2004). Limiting the irrigated acreage areas is done to have equitable distribution of scarce water. Commonly, the plot sizes are cut to one acre (i.e. one-acre rule) for each farmer. Interviews with farmers and scheme management show that cutting the sizes of irrigated acreages had been met with strong resistance from farmers. Farmers’ livelihoods depend on the scheme; hence by reducing their small plots, they harvest insufficient food. After the rainy season, canals are blocked with silt, and debris significantly reduces irrigation water supply. Farmers have over the years tried to build silt traps to reduce siltation along diversion canals. Observations show that due to a lack of expertise and funds, the traps constructed are not strong enough and don’t last long. Also, it takes 2–3 months to clear all canals of silt. As it takes a long time to completely clean the canals, it means crops would dry out, and the entire yield would be lost before water is received in the farms. Thus, the irrigation scheme remained in a perpetual cycle where it would fill up with sand after each rainy season:

4 Conclusion Hydrological droughts remain one of the major threats to food security in irrigated agriculture. Understanding causes of hydrological droughts is the first step to reduce their threats. Special attention is given to the critical properties of disasters, namely hazard, vulnerability, adaptive capacity, risk preparedness, response and recovery. Adaptive mechanisms need to be incorporated into local, national, regional and global policies towards good environmental planning. Best practices and models that work to reduce vulnerability to disaster risk need to be simple, cheap and easily affordable. As with models, their relevance in disaster risk reduction is critical in spatial decision making. This study characterises river flow droughts in Block C of Nyanyadzi irrigation scheme in Zimbabwe. A river flow drought in this case was defined as a period when water supplied was less than water demanded in the irrigation block. The research

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observed that the irrigation block scheme is highly vulnerable to hydrological droughts because of its location in a semi-arid environment and sole reliance of on river flows. Bean crops are sensitive to droughts as no crop is harvested at times of poor water supply. Adaptation mechanisms employed by farmers are rather short term. Thus, long-lasting sustainable solutions need to be developed to adapt and mitigate effects of droughts in the scheme.

References Abaurrea, J., & Cebrian, A.  C. (2002). Drought analysis based on a cluster Poisson model: Distribution of the most severe drought. Climate Research, 22(4), 227–235. Annan, K. (1999). Preventing war and disaster: A growing challenge. UN Department of Public Information. Bolding, A. (2004). In hot water: A study on socio-technical intervention models and practices of water use in the smallholder agriculture, Nyanyadzi catchment, Zimbabwe. Wageningen University. Bonaccorso, B., Cancelliere, A., & Rossi, G. (2003). An analytical formulation of return period of drought severity. Stochastic Environmental Research and Risk Assessment, 17, 157–174. Caloiero, T. (2018). Hydrological hazard: Analysis and prevention. Geosciences, 8, 389–394. FAO. (1991). CROPWAT version 5.7, Irrigation and management tool. FAO. Kundzewicz, Z.  W., & Kaczmarek, Z. (2000). Coping with hydrological extremes. Water International, 25(1), 66–75. Loáiciga, H.  A. (2005). On the probability of droughts: The compound renewal model. Water Resources Research, 41(1), 9–19. Madsen, H., & Rosbjerg, D. (1995). On the modelling of extreme droughts. In Proceedings of a symposium on: Modelling and management of sustainable basin-scale water resource systems (Vol. 231, pp. 377–385). IAHS Publication. Meteorological Services Department. (1983). Climate handbook of Zimbabwe. MSD. Mujere, N., & Eslamian, S. (2014). Climate change impacts on hydrology and water resources. In S. Eslamian (Ed.), Handbook of engineering hydrology: Modelling, climate change, and variability (pp. 118–132). Taylor and Francis Group. Pearce, G. R., & Armstrong, A. S. B. (1990). Smallholder irrigation design: Nyanyadzi, Zimbabwe. Summary report of case studies on field level water use and distribution. Report ODI 98, HR. Sarma, P. (1999). Flood risk zone mapping of Dikrong sub basin in Assam. Brahmaputra Board. Tallaksen, L. M., Madsen, H., & Clausen, B. (1997). On the definition and modelling of streamflow drought, duration and deficit volume. Hydrological Sciences Journal, 42(1), 15–33. Tumbare, M. J. (2000). Mitigating floods in Southern Africa. In Proceedings of the 1st WARSFA/ WaterNet Symposium: Sustainable use of water resources, Maputo, 1–2 November, 2000. UNDP. (2019). Let it flow: Adapting the Nyanyadzi irrigation scheme to climate change. UNDP. UNSDR. (2009). Global Assessment report on disaster risk reduction and poverty in a changing climate. UNDP. Van Loon, A. F. (2015). Hydrological drought explained. WIREs Water, 2, 359–392. Woo, M., & Tarhule, A. (1994). Streamflow droughts of Northern Nigeria. Hydrological Sciences Journal, 39(1), 19–34. Zaidman, M. D., Rees, H. G., & Young, A. R. (2001). Spatio-temporal development of streamflow droughts in Northwest Europe. Hydrology and Earth System Sciences, 5(4), 733–751. Zelenhasic, E. (2002). On the extreme streamflow drought analysis. Water Resources Management, 16, 105–132.

Chapter 8

Flood Resilient Plan for Urban Area: A Case Study Anant Patel, Neha Keriwala, Darshan Mehta, Mohamedmaroof Shaikh, and Saeid Eslamian

Abstract  Extreme rainfall and sea-level rise due to climate change may have disastrous consequences. In order to take action on the city’s issues with climate change, a new approach called flood resilient urban design was created. Floods caused by global warming and urban growth prompt cities to have various disaster response and preparation strategies included in their master planning efforts. In order to decrease risk, susceptibility and general disaster preparation, it is essential to include the improvement of flood resilience in development planning. Natural disasters cause damage in many sectors such as water management, energy, ecosystems and health. An efficient water management system keeps cities safe from floods and droughts. For flood damage reduction, several regulation methods and public-private collaboration are being used for people’s safety. This chapter proposes a novel A. Patel (*) Civil Engineering Department, School of Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Department of Civil Engineering, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, Gujarat, India e-mail: [email protected] N. Keriwala Civil Engineering Department, School of Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India D. Mehta Civil Engineering Department, Dr. S. & S. S. Ghandhy Government Engineering College, Surat, Gujarat, India Department of Civil Engineering, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, Gujarat, India M. Shaikh Department of Civil Engineering, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, Gujarat, India S. Eslamian Department of Water Science and Engineering, College of Agriculture, Center of Excellence in Risk Management and Natural Hazards, Isfahan University of Technology, Isfahan, Iran © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_8

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flood management plan and land use planning techniques in response to urban flooding. The most significant hydraulic construction constructed on rivers is a dam. It is also a well-known truth that dam collapse causes catastrophe in the downstream river reach, resulting in the loss of human life, property and economic resources. As a result, it is critical to conduct research and develop a flood mitigation strategy for the metropolitan city downstream of each dam and determine the region that would be flooded in the worst-case scenario of a dam collapse. This chapter focuses on research being conducted for Ahmedabad, situated in the lower basin of the Sabarmati River, India. This research will aid in the development of an emergency action plan for the evacuation of the general population and minimising property damage. Keywords  Flood management · Flood resilient plan · Flood modelling · Sabarmati river · Dam

1 Introduction Natural disasters often result in many deaths and are a substantial financial burden on societies because of urban design shortfalls and other shortcomings. As a worldwide danger, flooding often happens in various locations; some places are being more destroyed than others. Riverine floods, storm runoff floods, cyclonic floods and meteorological floods constitute urban floods (Admiraal & Cornaro, 2020). The flash floods were allowed to happen repeatedly, causing large-scale flooding each time a monsoon hits. A rise in various disasters, including heavy rain, flooding, and intense storms, has resulted from recent decades because climate change continues to affect the planet (Afriyanie et al., 2020). Consequently, everyone—from global and local governments to companies and citizens—are more aware of the need to implement comprehensive and interdisciplinary policies grounded in Disaster Risk Reduction (DRR) strategies to deal with the unpredictable impacts of global warming. Rapid growth and climatic change have enhanced the probability and degree of floods (Bardhan, 2017). Without good transportation, cities fail to operate smoothly. Transportation is more critical since it connects many important buildings such as hospitals, financial institutions, schools, and public services. This boosts its importance in disaster circumstances. Transportation networks are vulnerable to many kinds of accidents, including terrorism and floods, earthquakes, and landslides (Chang et al., 2021). Any disruption to the network has the possibility of a rapidly negative impact on many systems and services that are dependent on other network-­­ linked elements. To better prepare against threats, authorities should prioritise developing the resilience of transportation networks (Chuang et  al., 2020). Even while many of these hazards are rare and impossible to predict, some of them do follow a pattern, and proper planning may help to reduce their impact (Ciullo et al.,

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2017). The US transportation industry faces rising sea levels, more severe precipitation, and stronger hurricanes, which are considered among the five critical climate change problems faced by the United States (Cristiano et al., 2020). Flooding affects millions of people around the world and represents a significant risk. The annual total damage from floods, according to the OECD (2016) has exceeded $40 billion (Patel & Shah, 2020). The number of people exposed to flooding is projected to rise from about 700 million to 1.9 billion by 2050 because of rising sea levels, growing populations, and increased susceptibility to disasters (Patel & Patel, 2021). Flooding may occur if cities are situated on the ocean or floodplains (Forero-Ortiz et  al., 2020; Golz et al., 2015; González et al., 2021). There are a lot of problems being caused by climate change right now. To find solutions to disasters like floods, several industries have turned to natural science and medical research. The creation of strategies to prevent flooding and drought catastrophes includes managing water systems, building social infrastructure, and focusing on sustainable growth (Goodchild et al., 2018; Gupta, 2007). In order to reduce flood damage, regulation and private sector partnerships are being used. Through research based on water management and land use design in response to unusual weather, this study is looking to offer innovative waterfront management methods that improve coastal communities and provide amenities and public spaces. It’s essential to find and deal with minor disasters so communities can be ready for more significant disasters (Hammond et al., 2018; Haruna et al., 2018). Based on statistical data analyses, it was found that the government is the most crucial entity to serve as a stakeholder for recovery; also, the households suffer economically without enough assistance from communities and/or NGOs (Hewawasam & Matsui, 2020; Hofmann, 2021). A significant increase in building assets at risk to flood has been predicted because of economic and urban development in a sizable combination. Flood risk evaluations, on the whole, have evolved to include hazard, exposure, and vulnerability parameters (Khirfan & El-Shayeb, 2020; Kim & Marcouiller, 2018). To determine whether land use or population distribution will better show risk, one may look at the many kinds of asset exposure, which reflect the resources that will be lost. Four building damage classes were given depth-damage curves (Kim & Newman, 2020). Even though there are several methods for assessing exposure levels based on building materials, urban areas are frequently simplified in flood risk assessments, and they’re shown as only one land-­­ use type. Because differences in the built environment have a significant effect on potential flood damage, this generalisation limits flood risk assessment (Lee et al., 2018; Lourenço et al., 2020). Also, understanding that human habitation is diverse allows us to envision many urban futures. Human settlement’s functional and physical variety can’t be appropriately represented by using a single urban land-use class to account for built-up land. Urban growth produces several settlement types (Mehta et  al. 2013a, b). Low population density and lack of multi-story apartment complexes may occur in a vast suburban setting, while dense, multi-story apartment buildings occur in cities. This chapter examines the potential risk to the Sabarmati River caused by different urban development pathways.

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Natural disasters, such as flash floods, storm surge, and tidal flooding, are an obvious consequence of human interference in the water cycle, a discovery that has had a major impact on planning and research, and the realisation that traditional drainage systems aren’t adequate for sustainability goals under new social and environmental conditions (Mehtab & Kumara, 2021; Patel et al., 2018). New standards and architectural principles have been adopted since the 1990s to reduce the effect of runoff and floods on cities (Mehta et al., 2021; Mugume & Butler, 2017). Cities face severe risks due to flooding, which have substantial repercussions on society, the economy, and the environment. A few indicators are predicting an increase in these problems. The increase in urban populations will result in more people being vulnerable to floods. In addition, by 2050, there will be about 3.3 billion people in cities (Mehta & Yadav, 2020a, b; Nhamo et al., 2021). The urban expansion will put pressure on available land, which will likely rise over 1.5 million km2 in the next two decades (Mehta et al. 2013a, b; Patel et al., 2020). More flooding occurs because it decreases infiltration and allows the hydrological response to occur more quickly, decreasing the natural storage areas (Mehta & Yadav, 2020a, b). Another essential thing to remember is that economic development helps enhance the value of exposed assets. Additionally, severe rainfall is predicted to increase in many areas of the globe (Palazzo, 2019). Others concentrate on resilience, while others focus on robustness in flood risk. There is a belief that what makes cities resilient in the face of flooding goes beyond the traditional definition. When looking at it from our perspective, we consider “urban flood resilience” to be the ability of an urban system to resist, absorb, accommodate, adapt to, transform, and recover from flooding. Flood-vulnerable areas have been extensively studied. The Sabarmati basin, situated in a dry part of Rajasthan and in northern Gujarat, receives very little rainfall during the monsoon season. Few studies have been done in the Sabarmati Basin since it doesn’t often flood (Pandya et al., 2017; Patel, 2018). Heavy monsoon rain resulted in significant flooding in the Sabarmati basin in Gujarat, which suffered from significant floods during the 2006 monsoon (Patel et al., 2020). A 2006 flood ravaged the city of Ahmedabad since it was at the base of the Sabarmati River. Thus, the riverfront was totally submerged, and some low-lying neighbourhoods were also flooded. Several techniques have been used to model streamflow and floods, including empirical methods, data-driven models (Patel, 2020), system dynamics models (Raška et al., 2019), remote sensing techniques (Restemeyer et al., 2019). 2D models perform better than 1D models on flat topography with huge flood extents if adequate data is provided. In this context, this article provides a practical methodological framework for improving the efficacy of decision support systems by adapting different structural and non-structural mitigation measures techniques to meet decision-maker requirements. Ahmedabad lies in the lower Sabarmati River basin, and this chapter will cover the flood resilience plan for the Ahmedabad city as a case study. Ahmedabad is an important city in India and formerly the capital of Gujarat. It is one of the country’s largest urban areas. Ahmedabad, the location of the Sabarmati River in western India, lies on the banks of the Sabarmati River. Much rain fell in Gujarat in the 2006

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monsoon season. Surat and areas in southern and central Gujarat, including Ahmedabad, were trapped by the floods. Because of the flood that started because of a heavy rainstorm, about 250 people died, and many homes were destroyed. The Ahmedabad district saw widespread flooding due to the discharge of 2.75  lakh cusecs of water from the Dharoi Dam due to extreme rainfall in the area’s catchment zone.

2 Study Area 2.1 Ahmedabad City The Ahmedabad district is taken as a case study in this chapter, which is in the state of Gujarat (Fig.  8.1). Ahmedabad is the most extensive urban, highly populated industrialised city in Gujarat, Western India. The River Sabarmati divides Ahmedabad into two physically different regions: Eastern and Western. Ahmedabad district is made up of 11 talukas surrounding the city of Ahmedabad, including Ahmedabad City, Barwala, Bavla, Daskroi, Detroj-Rampura, Dhandhuka, Dholka, Mandal, Ranpur, Sanand, and Viramgam. According to the 2011 census, Ahmedabad Location Map of Study Area

Fig. 8.1  The study area of Ahmedabad district

23°0′0″N 21°0′0″N 71°0′0″E

73°0′0″E

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district ranks eighth out of 640 districts in terms of population, with a total population of 7,045,314. The municipal territory is governed by the Ahmedabad Municipal Corporation (AMC), which spans an area of 466 square kilometres. Ahmedabad district has a total size of 7170 squarekilometres. Ahmedabad’s urban and peri-urban zones are distinguished by various microenvironments, including rural areas in the west, highly populated urban conglomerates in the west and central regions, and industrial districts in the central and eastern regions. Ahmedabad district is situated in Gujarat State, in western India. It is bounded to the north by Mehsana and Gandhinagar districts; to the east by Kheda and Anand districts; to the south by The Gulf of Khambhat, Botad, and Bhavnagar districts; and to the west by Surendranagar district. Ahmedabad is the district’s main city.

2.2 Sabarmati River Ahmedabad lies in the northern section of Gujarat and the western part of India, on the banks of the river Sabarmati. It is situated at 23.03°N 72.58°E and has an area of 205 km2. The elevation is 53 m on average. The Sabarmati divides the city into eastern and western halves linked by five bridges, two of which were built after independence. Although the river is perennial, it dries up in the summer, leaving just a tiny trickle of water running. Summer, monsoon, and winter are the three major seasons. Except for the monsoon, the climate is extremely dry. During March to June, the weather is very hot, with typical summer temperatures ranging from 43 °C to 23 °C. From November to February, the average maximum temperature is 36 °C, and the lowest temperature is 15 °C. During that time, the weather is parched. Cold northerly winds cause a moderate chill in January. From mid-June to mid-September, the southwest monsoon winds provide a humid environment to Ahmedabad. The annual rainfall totals 932 mm. The highest recorded temperature is 50 °C, while the lowest is 5 °C. Sabarmati is a significant river in Gujarat that is used for drinking and other household uses. It also transports industrial and sewage wastes from neighbouring companies and municipal corporation regions, making it prone to degradation. As a result, regular monitoring is required to restore and maintain the quality and quantity of the Sabarmati river. Figure 8.2 shows the Sabarmati River basin with various gauging station locations in it.

3 Methodology A flood resilient plan for any urban city is given below in Fig. 8.3. There are two main methods to make the city resilient against floods. Usually, combinations of both the methods are helpful which will have high resiliency during flood situations.

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Fig. 8.2  Sabarmati river basin

Structural plan and non-structural plan both are most important for any urban city. The structural plan covers the construction of various hydraulic structures on the river and near the urban city. It also covers the urban stormwater management plan and groundwater recharge using the rainwater harvesting technique. In the s­ tructural plan, river training works are most important for these which drain more silt which causes sedimentation and erosion. Also, flood wall construction is the solution for the urban city. On the other hand, non-structural plan has a lot of options available, which covers flood modelling, flood inundation, flood mapping, flood forecasting, and flood warning system installation. By using the new GIS technology and satellite datasets and computer software, flood monitoring using water level sensor networks is trending now in the whole world for accurate flood forecasting and warning

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Hydrological Data 1. Dam& Reservoir construction 2. Ground Water Rescharge well 3. Urban Storm water Management using Rain water Harvesting 4. River training works 5. Flood Wall and Groyanes

Meteorological Data Satellites based image data sets Administrative, Population and Urban Development Zone data

1. Flood Modelling and Flood inundation mapping 2. Flood forecasting and warning system 3. Flood monitoring using Wireless sensor network system 4. Live flood streaming using App 5. Training and awarness program for flood management

Combination of Structural & Non Structural Method for Flood Mitigation

Flood Resilient City

Fig. 8.3  Flood resilient plan for any urban city

well in advance to the city government and people. Awareness and training programmes related to floods are also crucial for the awareness of people.

4 Proposed Plan for Flood-Resilient Urban City According to several studies, planning may be effective in flood-resilient cities because it uses flood risk reduction methods in developing plans, and integration can offer a way of resistance to flooding impact and building up adaptation to flooding risk by never entirely avoiding flood. Disaster mitigation formerly relied heavily on development planning (Restemeyer et al., 2015). It is possible to take a “hard” strategy like building a levee or a flood dam to fight floods. These initiatives would make flood defences stronger and reduce the chance of floods (Shaikh et al., 2018). Similarly, better planning will encourage land use management and development control, which will reduce risk. The increase in flood protection measures will not decrease flood risks but rather help resist floods. He also believes that protective structural measures included in the resilience concept weaken resilience by eliminating resistant characteristics. Advocates of change may be motivated by the fact

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that first disasters are unmitigable, because they are naturally occurring (Sagathia et al., 2020). Second, we have long been causing environmental problems through human activities like development, which are long, time-consuming, and expensive to remedy (Siekmann & Siekmann, 2015). The problem may be best solved with the whole reform of the existing system. Socio-ecological resilience has transformability because it allows for drastic and systemic adjustments to be made so that a new, more stable, and resilient system may be built to address future disaster risks better. It may involve such actions as relocating very toxic zones or rebuilding every facet of the development planning system, including changes to existing development laws and standards and reforms in planning governance (Norizan et al., 2021). To alter things, transformation planning involves a large amount of effort, collaboration with all parties, and investment in resources. If existing conditions were awful, the public would want significant changes to revitalise the area. Because of this, metrics of transformability are unique because this study relies on measurements suitable for being deployed as project plans for regional areas. Table 8.1 shows the characteristics of flood risk reduction methods that must be included in flood-resilient planning based on findings in the literature. Wamsler (2014) discovered that disaster risks might be reduced by adopting a strategy of minimising vulnerability and maximising resistance. The researchers led by Restemeyer et al. (2015) focused on flood interventions that focus on the qualities of robustness, adaptability, and transformability. Robustness and adaptability have different approaches to solving the vulnerability problem: Robustness tends to advocate for technical and structural solutions, whereas adaptability favours using non-structural methods. This study is transformable and emphasises the need for social transformation while also enhancing governance in urban planning.

4.1 Non-structural Mitigation Plan 4.1.1 Flood Modelling and Flood Inundation Mapping Flood plain mapping will be more straightforward because of the benefits of hydrological modelling, which include a greater understanding of the relationship between land and water resource management and how engineers may design new structures. In addition to helping the city analyse flood-prone areas and flood insurance, this technique may be used. In water resources and many other sectors, Remote Sensing and GIS serve as indispensable sources of information, essential to collecting, storing, retrieving, and deciding on data by location, carrying out spatial analysis, and presenting (Singh et al., 2021). Figure 8.4 shows the flood modelling using the HEC HMS model used by many researchers for flood modelling for any river. Hydrologic Engineering Center-River Analysis System (HEC-RAS) software can do visualisation operations, rainfall-runoff simulations, and mapping operations by combining interfaces (Patel, 2020; Shaikh et  al., 2021). To understand the

Criteria/measures dimension

Flood wall Green areas as flood retention Drainage system improvement Flood-prone infrastructure for housing Separate treatment of rainwater Public spaces for emergency Disaster insurance Citywide emergency rescue and evacuation route system Risk reduction measures for infrastructure, housing, transportation, and utilities Envision 'safe and secure environment as local plan goal Regulate development based on risks level Construction of flood embankment and water retention ponds Flood protection measures for property and buildings Protections of natural slopes, water bodies, and mangrove forests Land allocation for public uses during emergency Risk ranking measures in zoning plan Enhancing accessibility for daily activities

Dimension

Hazard reduction and avoidance Vulnerability reduction Preparedness for response Preparedness for recovery Sensitivity to hazard Exposure minimization

Adaptive capacity improvement Robustness – reduces flood probability Adaptability – reduces consequence of flooding Transformability – foster societal change Adaptation – living with floods by retrofitting the existing urban area

Dimension

Table 8.1  Summary of various flood mitigation measures Improving infrastructure and utilities network for resistance Provision of law and regulation for disaster preparedness and mitigation Incorporation of indigenous knowledge of coping capacity Technical measures, for example, dikes, dams, and barriers Spatial measures, for example, river widening Land use control di flood prone area Flood-proofing existing building and infrastructure in flood-prone area Warning and evacuation schemes Flood insurance Risk communication and awareness among private and public stakeholders and Provide more open spaces Redesign building to retrofit flood-proofing Building adaptive temporary infrastructure in floodplain areas

Criteria/measures dimension Non-­­ structural measures Structural Measures

Floodplain management through land use planning and development control. Flood mapping -–flood hazards map and flood risk map Land use planning and zoning Flood proofing – making building watertight/ impermeable to floodwaters Wet flood proofing – allows water to enter the structure with little or no damage Dry flood proofing –prevents floodwater from entering the facility up to a specified level Flood forecasting and warning system Flood response through flood evacuation plan Water level regulating structures, for example, barrages, tidal gates, flood gates Dam River channelisation and improvement works, for example, widening and deepening River diversion and flood bypass, for example, SMART Tunnel (Stormwater Management and Road Tunnel) Retention and detention ponds Bunds, for example, embankment, flood wall, flood banks Revetment system Bridges and crossings

Dimension Criteria/measures dimension

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HEC-HMS Basin Model (Loss, Transform and Base flow) Meteorological Model (Precipitation, Evapotranspiration) Control Specification (Event period) Time Series data (Precipitation Gauge)

Runoff Hydrograph

Validation with observed Gauge data

Fig. 8.4  Flood modelling using HEC-HMS model

movement of water above the surface and below the surface and their interactions with environment and man made structures carried out using the simulations of physical systems and small-scale models is known as hydrological modelling. When it comes to the possibility of flooding, flood risk assessments are conducted to discover the likely source, total quantity, and potential mitigation and protection tactics. We may utilise hydraulic models of various dimensions to simulate different flood types. We will better understand flood risk, enabling us to develop flood-­ management solutions. Figure 8.5 shows the flood mapping and simulation methods flow chart using the HEC RAS software, which is used for the flood simulation and flood zone mapping. HEC-RAS is software that models water hydraulics through natural rivers and other channels. Before the 2016 update to Version 5.0, the program was one-­ dimensional, meaning that there is no direct modelling of the hydraulic effect of cross-section shape changes, bends, and other two- and three-dimensional aspects of flow. The release of Version 5.0 introduced two-dimensional modelling of flow and sediment transfer modelling capabilities. The program was developed by the United States Army Corps of Engineers in order to manage the rivers, harbours, and other public works under their jurisdiction; it has found wide acceptance by many others since its public release in 1995. The HEC in Davis, California, developed the RAS to aid hydraulic engineers in channel flow analysis and floodplain determination. It includes numerous data entry capabilities, hydraulic analysis components, data storage and management, and graphing and reporting capabilities. Figure 8.6 shows the flood inundation mapping using the HEC-RAS software for the Sabarmati river. In this modell, the main focus area is Ahmedabad city, which is shown in Fig. 8.6.

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Rainfall Soil Landuse/ Landcover

Data Procurement & archived data collection (Satellite data, IMD, CWC, SWDC, Census) Hydrological Models - SUH - SCS - HECHMS

Stream network; Watersheds; Slope; Flow direction; Stream length; Stream centroid length River Cross Section River Profiles

Flood forecast Field Validation: Establishment of HydroMeteorological Network (Rain gauge/Stream Gauge) Auto level survey Highest flood level data collection

DEM (SRTM)

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Flow Velocity

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Flood Vulnerability Demographic data Population data Flood Risk Zonation

Fig. 8.5  Flood simulation and flood risk zonation using HEC-RAS model

Fig. 8.6  Flood inundation mapping for Ahmedabad city using HEC-RAS

RAS Mapper is a tool inside the HEC-RAS programme that is used to prepare basin terrain using GIS technology. Once the basin’s terrain layer is created in RAS Mapper, it is immediately linked with the HEC-RAS geometry tool. A 2D flow area is a tool in a geometric data editor that allows you to create a 2D flow area polygon to depict the river basin’s border (Wang et al., 2018). Within the 2D flow region, a computational mesh or computational grid is formed. Each cell in this grid has three properties: cell centre, cell faces, and cell points.

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In order to create spatially accurate flood extent estimates for Ahmedabad city, inundation models simulate water flow throughout the floodplain. A floodplain inundation map with the depth of water at each pixel is produced using the supplied hydrologic boundary conditions (expressed either as discharge or as level of water). Finite-element solutions to the St. Venant (or Shallow Water) equations are the most common way to implement these models. Academics and practitioners alike rely on these types of models virtually exclusively. However, expanding their scope and influence is fraught with difficulties. An in-depth look at the issues and ways to overcome them using finite-element methods is provided herein. An accurate elevation map of the appropriate floodplain is needed to run these models (around 1 m resolution, depending on the characteristics of the basin). However, they do not need knowledge of riverbed bathymetry. As a result of this research, we now have a greater understanding of how the various strategies work and how they compare to one another. Water temperature modelling, sediment transport/mobile bed calculations, and generic water quality modelling are all possible using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) software (nutrient fate and transport). HEC-RAS is intended to conduct hydraulic calculations for a complete network of natural and built channels in one dimension (1D), two dimensions (2D), or a combination of 1D and 2D. The main hydraulic capabilities of HEC-RAS are summarised here. Simulation of an Unsteady Flow. When used in conjunction with the HEC-RAS modelling system, this component may simulate unsteady flow in one dimension and in two dimensions, or it can represent a combination of unsteady flow in one dimension and two dimensions. It was included within the HEC-RAS Unsteady Flow Engine to make it easier to mix 1D and 2D hydrodynamic modelling. In HEC-RAS lingo, a project is a collection of data files pertaining to a certain river system. Any or all of the analyses provided in the HEC-RAS package may be carried out by the model as part of the project. Plans, geometric data, steady and unsteady flow data, quasi-steady and semi-steady flows, and sediment and water quality information are all included in a project’s information files. Hydraulic designs are also included in the project’s information files. The model may wish to come up with a number of distinct strategies over the course of a project. Each strategy is based on a unique collection of geometric and flow facts (and possibly sediment data, water quality data, and hydraulic design information). The model may quickly come up with fresh ideas after the foundational data has been put into the HEC-RAS. The results of the simulations may be compared in tabular and graphical form once they have been completed for all of the different designs. Many researchers have used HEC-RAS software for different regions and achieved good outcomes. Masood and Takeuchi (2012) performed 1D hydrodynamic modelling for mid-eastern Dhaka, Bangladesh. The modelling showed that the maximum depth is 7.55 m, and the affected area is more than 50%. Timbadiya et al. (2014) studied the 1D hydrodynamic model for two flood events in the lower Tapi River (India) and suggested that the predicted flood level was computationally acceptable. Patel et al. (2018) carried out a 1D hydraulic model for 11 km of the lower part of the Ambica River (India) with 359 surveyed cross-sections to estimate

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the level of the flood. The results of their study found inundations of both the right and left banks. Tunas and Maadji (2018) assessed flood control structure performance using HEC-RAS 1D hydrodynamic model on Palu River, Indonesia. They identified critical cross section and water-carrying capacity of river for 25-year return period. Tarekegn et al. (2010) assessed DEM for 2D hydraulic modelling in the data-scarce region of Lake Tana Basin, Ethiopia. Their research shows that effects of high water levels have been observed up to a distance of 13-km upstream from the lake with RMSE = 0.20 m. Quirogaa et al. (2016) used 2D hydraulic simulation for flood analysis in the Bolivian Amazonia, Brazil. Their simulation shows good performance when comparing the flood recorded by satellite images. Patel et al. (2017) assessed the flood inundation mapping of Surat City by 2D hydraulic modelling. Their results show that 75–77% of the area was flooded in 2006 with R2 = 0.937. 4.1.2 Flood Warning and Forecasting System To help get ahead of possible flooding and avoid further danger, flood preparedness strategies have been proposed, including methods to make accurate predictions of floods and reduce the level of risk (Wang et al., 2019). It is difficult to completely control floods because of unpredictable things like flood magnitude, timing, and location. The traditional approach to flood control relies primarily on structural solutions, such as dams and levees, which aim to manipulate the course of the flood to reduce the maximum heights and ranges. Structural solutions (such as dams and embankments) improve over flooding but are not enough to eliminate it. Flood specialists have encouraged local governments to change their policy of building flood control systems towards preventing floods (Wilson, 2020). Structural approaches tend to be expensive and irreversible, whereas non-structural strategies are inexpensive and are easier to reverse. Non-structural methods are seen as being just as important for developing flood risk control solutions. Advances in technology and natural catastrophe predictions are intrinsically connected to this paradigm shift. The Integrated Flood Management Concept has replaced traditional, fragmented, and localised thinking about flood plain resources, shifting management strategy to using those resources more effectively. Flooding is a common natural hazard with significant potential for catastrophe, responsible for one-third of all-natural eventrelated losses. Even without climate change aid, citizens have increasingly feared that flooding has become more widespread, constant, and severe in recent years. In hydrology, predicting floods is among the most complex and time-consuming processes. It’s also one of the most critical hydrological problems due to its crucial part in avoiding monetary and human suffering. In many areas of the world, flood forecasting is the only plausible option available for flood control. There has been improvement in weather forecasting dependability in recent years thanks to the inclusion of hydrological modelling and advancements in data collection via satellites, together with understanding and methods for managing uncertainty and communicating results (Wu & Chiang, 2018).

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For example, IoT and computational models such as artificial neural networks (ANNs) have allowed the execution of new strategies, permitting the development of new apparatus and programming that enables the development of continual water-level information that is necessary for flood watching and estimation. In addition to discovering early notifications of potential flooding, IoT sensors are being used in tropical countries like Indonesia to provide information on impending flooding, including helpful warnings for people in areas at risk. IoT devices are being used in urban settings in applications such as smart trash companies, which use remote sensors. An audit of the documents is anticipated to provide a complete and thorough understanding of the level and progress of the assessment by using IoT sensors for detecting flooding in both coastal locations and inland lakes, for example. The method suggested in this chapter may be one of the most acceptable options for Ahmedabad city’s flood forecasting system. This method may be improved further by including an Artificial Intelligence (AI) system for the warning system. Wireless water level measurement sensors must be installed. For efficient and fast data transfer, a wireless network should be utilised for data transmission and collecting. The data obtained by the data monitoring room is analysed and forecasts the likelihood of a flood occurring. The method used here is based only on the identification of low-lying regions and the installation of sensors. This model may be coupled with other flood forecasting models to predict the flood, such as real-time flood forecasting. It is well known that a greater number of natural disasters come in the form of flooding. This also means a large amount of harm is done to the infrastructure. The most worrying fact is that the lives of everyday people are also deeply affected. Through combining monitoring of water resources with IoT, we can better plan for potential problems and what to do about them as shown in Figs. 8.7 and 8.8. By adding an early flood warning system to the mix, we will be able to avoid wasting time and money while also keeping people safe. A network is created to retrieve

Fig. 8.7  Advanced water level monitoring method using AI and IoT

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Aerospace images

Preliminary processing of the images

On-line hydrological data

Calculation and forecasting of the water discharge

Digital terrain model

Crowdsourcing

Automatic modelling of the water spread using the hydrological models

Post-processing of the results and their saving in the database; flood map vectorization

Updating and correction of the model

Rendering and distribution of the modelling results

Filtering and processing of the messages.

Providing the results of modelling to the external software via standard protocols WMS, WCS

Publishing of the Personal notification of the interested persons short-term forecast at the public geoportal and organizations using the mobile devices

Fig. 8.8  Live flood warning system: using GIS GPS & AI

data via services such as GSM, or any other accessible network, and then processed into a central computer. In order to use data gained and to carry out proper actions, an SMS application has been provided to the PC worker. The two framework’s restriction for activating the GSM module was to send a text message to the PC operator. This will examine how a water level monitoring system works and will investigate weather patterns such as rainfall and runoff. It will analyse the river system, looking at the recent flood-affected regions and will examine river sections and build a water level sensor. The Use of Computer-Assisted Learning Systems (ANNs) In order to simulate the biological neural network, ANNs use interconnected neuron units as the basis for their mathematical modelling systems. When it comes to machine learning, neural networks (ANNs) are the most often used because of their versatility and efficiency in simulating complicated flood processes. Multilayer Perceptron (MLP) A BPNN is often used to train the overwhelming majority of flood prediction ANN models. The MLP, a more complex version of ANNs, has lately acquired favour in place of the more frequently used BPNNs. Networks with linked nodes in numerous layers may be trained using MLP, which is one of the most used FFNNs. The MLP is characterised by its simplicity, nonlinear activation, and large number of layers. The model was frequently utilised in flood prediction and other sophisticated

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hydrogeological models because of these qualities. In a comparison of flood modelling ANN classes, MLP models were shown to be more effective and more generalisable. To be fair, however, optimising the MLP is more of a challenge. Adaptive Neuro-Fuzzy Inference System (ANFIS) Natural language is used in the fuzzy logic of Zadeh, which is a qualitative modelling method with a soft computing technology. Expert knowledge may be integrated into a fuzzy inference system using fuzzy logic, which is a simplified mathematical paradigm (FIS). A less sophisticated approximation function in a FIS replicates human learning more closely, opening the door to nonlinear modelling of severe hydrological phenomena. Wavelet Neural Networks (WNN) WT (Wavelet transform) is a mathematical technique for evaluating time-series data and extracting information from it. In fact, WT improves modelling performance dramatically. The dependable decomposition of an original time series by means of a wavelet transform helps to enhance the quality of the data. Discrete WT (DWT) improves flood forecast lead times by decomposing the original data into bands and so improving prediction accuracy. When developing a model, better-quality data may be extracted using DWT’s decomposition of the basic dataset into distinct resolution levels. Flood time series prediction makes extensive use of DWTs, thanks to their many advantageous properties. Rainfall–runoff, daily streamflow, and reservoir inflow are only a few examples of how DWTs were used in flood simulation. In addition, wavelet-based neural networks (WNNs), which mix WT and FFNNs, and wavelet-based regression models (which integrate WT and MLR) were employed in time series flood forecasts using hybrid DWT models, for example. According to reference, a study on the use of WNNs in flood prediction found that they might significantly improve model accuracy. WNNs, on the other hand, have lately been popular in flood modelling because of their ability to enhance time-series data for applications such as daily flow, rainfall–runoff, water level, and flash floods. Decision Tree (DT) With its vast use in flood simulation, the DT ML approach is a key player in predictive modelling. DT makes use of a decision tree, which has branches that lead to many possible outcomes at the leaves’ respective goal values. Final variables in a classification tree (CT) have a fixed set of values where the leaves represent class labels and branches indicate conjunctions of feature labels. The term “regression tree” refers to an ensemble of trees used in a DT when the target variable has continuous values. There are several parallels and distinctions between regression and classification trees. Since DTs are rapid algorithms, ensembles using them to simulate and predict floods have become highly popular. CART, a common DT used in ML, has been effectively used to flood modelling, although its usefulness to flood prediction has yet to be completely examined. Another widely used DT approach for flood prediction is the random forests (RF) method (see below). Numerous trees are included in RF. A separate set of values is connected with each individual tree’s response predictor values. The top classes are selected by an ensemble of these

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trees. RF was presented in reference as a viable option to SVM in flood prediction modelling because of its greater performance. When it came to floods, Bui and colleagues looked at the performance of ANN, SVM, and RF, with RF coming out on top. The M5 decision-tree method is another important DT. In order to reduce the final variable’s variance, M5 builds a DT by dividing the decision space into single characteristics. Additional flood prediction DT techniques include reduced-error pruning trees (REPTs), Nave Bayes trees (NBTs), chi-squared automatic interaction detectors (CHAIDs), logistic model trees (LMTs), alternating decision trees (ADTs), and exhaustive CHAIDs (E-CHAIDs). Recent Developments in the World in Terms of AI and Machine-Learning Technology Improving Water Levels Forecasting: A dedicated deep neural network architecture designed exclusively for water level forecasting, which enables us to use some exciting recent breakthroughs in ML-based hydrology in a real-world operational scenario to improve flood predictions. It has two distinct characteristics that set it apart from other hydrologic models. When it comes to generalisability, the rainfall-­­ runoff model excels at this. As a result, the model’s performance may be fine-tuned for each location while generalising effectively to various locations. To begin with, a network of smaller neural networks, each representing a different point along the river, is trained in HydroNets to account for the network topology of the river network being represented. Upstream models may now send information encoded in embeddings down to downstream models using neural networks, allowing each model to know all it needs without having to drastically extend its parameter set. Although the morphological inundation models do not encompass the majority of the population, precise forecasts are still required. Using publicly accessible data, such as stream gauge readings, public satellite imagery, and low resolution elevation maps, we developed an end-to-end ML-based method to reach this audience and boost the effect of our flood prediction models. We train the model to immediately infer the inundation map from the data it receives in real time. 4.1.3 Flood Awareness It is essential to be prepared in the event of a flood, which no one can predict in advance. This is why, in the event of a flood, every family should have a plan in place. Public awareness and education are essential for minimising natural disaster-­­ related fatalities, injuries, and property loss. People need to be aware of the natural dangers that they are likely to be faced in their areas. They should know what to do in the case of a storm, earthquake, flood, fire, or other possible occurrence and what to do in the event of a storm, earthquake, flood, fire, or other potential occurrence. Natural disaster education and awareness should be made a national priority. Household survival plans should contain basic information on what hazardous events are most likely to occur in particular areas, what emergency equipment and supplies should be on hand, what measures should be taken to minimise damage,

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and what escape and evacuation arrangements should be undertaken. Community-­ based planning and education should be encouraged. Schools, government institutions, community and religious organisations, business and neighbourhood organisations, hospitals and medical organisations, and the news media should all be engaged. Disaster Preparedness and Rehabilitation: Disaster Awareness Raising and Training in Uttar Pradesh facilitates flood awareness and training to help people cope with floods and improve their quality of life. The programme, which had previously been implemented in 35 schools and 20 villages, was later expanded to include teacher training in all 234 schools in Uttar Pradesh’s flood-ravaged Bahraich District. The Himalayan Center for Environmental Education (CEE) organised and conducted a number of programmes and seminars to educate and raise awareness among students, teachers, villagers, and school department officials on the significance of developing adaptability to changing circumstances. The activities were carried out via a number of different programmes, as detailed below. Flood Mobile Applications 1. Flood: American Red Cross: The American Red Cross is a great resource for flooding alerts. It keeps track of all possible floods throughout the United States and sends out notifications when things become bad in your area. You’ll get a map of the impacted region and advice on what to do next when you search up an alert. You can check when an area was put on flood watch and when warnings were issued in the past, so you can understand how fast the situation is developing. There is also basic advice on what to do just before a flood to keep you and your family safe. 2. A Weather Station in Your Pocket: NOAA Weather Radar Live is mainly a weather tracking programme, but it also includes everything you’ll need to monitor the danger of floods and other severe weather occurrences. There is an interactive map that is updated as required with severe weather warnings. The current and “feels like” temperatures and the likelihood of precipitation and humidity are all given. You can easily set up the software to monitor a large number of locations across the globe, with precise information on each one available at any moment. Most importantly, you’ll get a push notification whenever an alert is issued, which may include floods, snow, storms, tornadoes, and other severe weather situations. 3. Simple River Monitoring: Flood watch: Simple River Monitoring tracks all rivers throughout the nation using real-time data from the US Geological Survey, providing you the most up-to-date and accurate stream gauge data available. Favourite rivers may be saved and accessed quickly. In each situation, an arrow shows whether the water is rising or evaporating. The graphs also indicate how the water levels have changed over the past 24 h and historical data dating back 7 days and beyond. Flood watch isn’t very appealing, but it gives a fast picture of how the water levels are increasing around you, notifying you if they’re unusually high so you know when to be worried.

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4. Colorful Displays: NOAA Weather Center: NOAA Weather Center is a vibrant yet comprehensive app that provides weather updates. It’s not designed for floods, but it’s more than capable of providing you with information on possible flash flood warnings. The application begins with a map view that shows where you are in respect to weather patterns. 5. For Varied Information: For a wide range of information, check out the Weather Channel’s forecast and radar maps. The Weather Channel Forecast and Radar Maps are known for their accuracy. Its updates are regular, with weather changes being reported every 15 min or so. That’s precisely what you need while coping with extreme weather. In addition to comprehensive maps that show you precisely what’s going on and what’s coming, the app offers alerts for severe weather events such as flash floods, other storms, and accidents. You may keep a close watch on particular issues to determine what formal advice is available for dealing with them. Wind speed data and rain predictions offer you an idea of what to expect.

4.2 Structural Mitigation Plan 4.2.1 Dam, Reservoir/Hydraulic Structure Construction and Operation (Dharoi Dam) Dam is a civil structure, which is built mainly for storing or retaining water by constructing a wall on the river, stream, or an estuary. There are different types of materials used in the construction of the dam. But in India, gravity dams or concrete dams are common in nature. Dharoi Dam is a gravity-type dam, which is constructed on the Sabarmati River near Dharoi, Kheralu Taluk, Mehsana District, Gujarat. Dharoi Dam was constructed in 1978 to serve purposes like power generation, flood control, and irrigation. This dam covers the catchment area of about 5475 km2. The reservoir capacity of this dam is about 907.88 Mm3. Height of this dam is about 45.87 m and length is about 1207 m. This dam consists of 12 radial spillway gates with ogee-type spillway. Basically the construction of this dam started in 1971 and it was completed in 1978. In the Dharoi Dam construction project, about 28 villages are completely submerged, and 19 villages are partially submerged. In this dam a total of 349.49 hectare forestland, 2727.55 hectare barren land, and 7489.59 hectare agricultural land is submerged in the upstream side of the dam. The area of the full reservoir is about 107 km2 among them gross storage capacity is about 907.88 Mm3 and effective storage capacity is about 131.99 Mm3. Maximum discharge of spillway is about 21,662 cumecs. For providing water for the domestic and irrigation purpose canal network is established in which the length of the left bank canal is about 29.50 km, and length of the right bank canal is about 43.50 km. Granite and Callogenesis type of rock are present at the dam site. The estimated cost of this project is about 9600 lacs rupees as per the government estimation team. Due to the

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present scenario of the climate and the decreasing nature of rainfall and also changes in the land use land cover pattern, the reservoir level is reduced or the reservoir storage capacity is reduced, and also, the water quality in the command area of the dam is degraded, so to avoid these things, the management of the dam is required. The operation management is carried out in the different ways such as the recharge of the nearby ground as well as surface water bodies, sedimentation reduction, development of the watershed of the river and also the improvement in the management practices of the main and distributary canal systems. This management practices help in the enhancement of the storage capacity and better quality in the downstream areas. Also, the gate and spillway maintenance are very important criteria to improve the capacity and better enhancement of the dam water. 4.2.2 Flood Walls A floodwall is a freestanding, permanent, engineering barrier intended to keep floods from encroaching. Floodwalls are made of masonry or reinforced concrete. Floodwalls protect buildings from hydrostatic and hydrodynamic stresses and ­create a barrier against flooding. It has the potential to divert flood-borne debris and ice away from the structure. Floodwalls are often positioned some distance away from the structure to minimise the need for structural changes. Floodwalls may defend the low side of the site, or they may encircle the site and must connect onto high land, depending on the geography of the site. Floodwalls surround the entrances that allow access to the property. Types of floodwalls that are commonly found are gravity, cantilever, buttress, and counterfort. Gravity Floodwalls The gravity floodwall is a construction that relies on its weight for structural integrity. Rather than the weight of the retained materials (water or soil) on top of the wall foundations, structural stability is achieved by effectively placing the bulk of the wall at its base. The gravity floodwall resists overturning because of the dead weight of the building material, which is either concrete or masonry. It is simply too heavy to be flipped by a lateral flood force. In comparison to the other types of floodwalls mentioned in this context, gravity floodwalls are simple to build. The major drawback of gravity floodwalls is that they need a large quantity of materials in comparison to other floodwall kinds. Cantilever Floodwalls Cantilever floodwalls are the most popular kind of floodwall because they are inexpensive to design and build. Cantilever motion is employed to keep the bulk behind the wall. Concrete or concrete blocks with steel reinforcing bars inserted in the concrete core of the wall are used to build cantilever floodwalls. The weight of the earth on the heel section of the foundation contributes to stability, as does the weight of the wall itself, which is balanced by lateral pressures and overturning moments.

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Buttress and Counterfort Floodwalls The sole difference between buttress and counterfort floodwalls is that the transverse support wall is on opposing sides. The transverse support wall in a counterfort wall is on the toe side, while the transverse support wall in a buttressed floodwall is on the heel side. Counterfort floodwalls are more common than buttressed floodwalls because their transverse support walls are concealed under the retained material, which may be water or soil, while buttress floodwalls take up space that might otherwise be used. Reduction in Erosion and Flood in Sabarmati River Flood prevention, bank protection, and river training have all been developed as a result of thorough hydrological and hydraulic research. The waterway’s optimum width of 263  m has been chosen and executed. Both sides of the river have diaphragm walls constructed into the riverbed to a depth of more than 10 m, as well as retaining walls that protect low-lying regions from floods and prevent riverbank erosion. The Sabarmati has been channelised to maintain a consistent width while maintaining the river’s flood-carrying capability. The project can now withstand flood levels of 4.75 million cubic metres without spilling into the city. 4.2.3 River Training Works The majority of Indian rivers run over alluvial plains, causing them to meander in breadth and discharge to fluctuate greatly during flood season compared to low flow season. As a result, various sediment loads are carried by rivers at different times. Rivers alter their cross section. Therefore, change their courses as a result of this non-uniform fluctuation in discharge and sediment load. River training is essential for flood reduction and bank protection from erosion caused by flash floods, therefore, guaranteeing safe flood passage. The structural measures made to enhance the river and its banks are referred to as river training works. The primary goals of river training are to (i) remove large floods safely and quickly, (ii) to effectively convey the silt downstream, (iii) to avoid bank erosion and maintain the river’s path. (iv) to prepare the rivers flow path to prevent damage to lands, crops, and other property due to floods or erosion, and (v) to rectify bank and flow conditions that are out of control. River training works may be categorised based on the following: (a) their alignments in relation to flow: (i) transversal protection oriented perpendicular to the water channel, such as spurs, check dams, and bars, (ii) transversal protection positioned perpendicular to the water course, such as culverts and (iii) longitudinal protection structures, such as levees or embankments, rock riprap to protect banks from erosion, diaphragm walls, flood barriers, and so on, built parallel to the river channel; (b) depending on action: (i) direct protection to the potion that needs protection, such as riprap and (ii) indirect protection, which alters flow conditions to protect spurs, for example.

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A Case Study of Sabarmati River Sabarmati is a river in western India that originates in the Aravalli highlands of Rajasthan and flows for 371 km through Rajasthan and Gujarat before reaching the Gulf of Cambay. Gujarat is the state through which it flows the most. The river is broad and shallow, with a high width–depth ratio, and it is extremely meandering in alluvial zones, changing its path on a regular basis. In the lower reaches of this river, severe bank erosion has been recorded. Gandhinagar and Ahmedabad are two major cities in Gujarat that are situated on the river’s banks. Many flood occurrences occurred in the Sabarmati River, affecting Ahmedabad. The river, which runs through the heart of Ahmedabad, has been under tremendous strain as a result of the city’s rapid urban and industrial development. The river’s erosive character necessitated the development of bank protection work along the stretch of river that runs through Ahmedabad. In 1997, AMC came up with the concept of riverfront development and established the Sabarmati Riverfront Development Corporation Limited (SRFDCL). The project’s primary goal was to reduce erosion and flooding in order to protect the city and to retain and replenish river water. People who live near the bank will benefit socially. By selling property (reclaimed along the bank owing to the building of diaphragm walls) for commercial development, sustainable development may be achieved. The river was channelised to maintain a constant width of 275 m, and riverbed land was recovered to provide 11.25  km of public waterfront on both sides. The construction proceeded in the following manner. To prevent scouring, a working platform was built first, followed by a diaphragm wall with anchor slab, that is, a

High flood level (HFL) Retaining wall Water level

Anchor slab / Lower promenade level

Earthfill / Embankments

Existing storm water outlet

Riverbed level Scour level 10–14m Diaphragm wall

Fig. 8.9  Retaining wall and embankment fill

Riverbed land / Public

Private

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lower promenade up to a depth of 10–14 m below the riverbed. Finally, a retaining wall was built up to the height of the HFL, and an earth fill embankment was built behind it as shown in Fig. 8.9. As a result, the danger of erosion was removed, and the risk of flooding in low-lying areas was substantially decreased. 4.2.4 Ground Water Recharge Well From the last two to three decades, the ground water level has depleted every year to a certain extent. There are many reasons behind that but the main reason is the overuse of the ground water and also the global warming as well as greenhouse effect. To improve the ground water level and for fullfilment of the water demand, the ground water recharge techniques are used. Groundwater recharge is the process of adding the water in the ground surface or in the unsaturated zone of the aquifer through various techniques or various methods. This recharge phenomenon is also called the artificial ground water recharge in which recharge well is a very common and important method of ground water recharge. Recharge wells are also called the Injection wells. Basically this recharge well technique is a subsurface method of recharging the groundwater to directly discharge water into the deep water bearing zones. Recharge well is one type of caisson, which is caused by the aquifer material. If the covering material is of the unconsolidated type, then the screen is placed in the well in the zone of the injection. Injection well or recharge well is suitable only in the area where there is a thick impervious layer between the surface of the soil and the aquifer that is replenished. Recharge wells are also helpful in the area where the availability of the land is less so large infiltration surface required. Compared to all other methods of artificial recharging techniques this method provides higher discharge, construction, and easy maintenance. Recharge well is also suitable in the hilly area, up dip outcrops or erosional exposure of the confined aquifer stream bottom. Recharge well creates the downward movement so it gives the influx of groundwater to an aquifer. In recharge well the shape of the water table is the concave type within the radius of influence. Recharge wells help channel this run-off more effectively and more quickly into the aquifer. In the long run, these recharge wells effectively provide water in the dry years or in drought condition. In the village areas the recharge wells are easily dug and easily constructed to recharge the groundwater. The only one disadvantage of this recharge well is the skilled person required in the construction of this type of well. There are some important points which are considered while we construct the recharge well. The recharge well should be far away from any soak or the toilet pit and any building foundation. If the recharge well is constructed near the bore well it gives the better result in discharge and increase in the ground water table of that area. Concrete slab is constructed above the well mouth so that accidents are avoided.

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4.2.5 Stormwater Management In the present scenario due to global warming and due to the greenhouse effect the rainfall pattern is being uneven and uncertain. Due to that condition some areas are affected by flood and some areas are affected by the drought condition. To avoid these things stormwater management is essential to prevent the erosion of the agricultural land and flooding of the inhabited urban or the rural areas. Basically the main aim or the main purpose of the storm water management is the process to manage the surface runoff in the effective manner with the help of better management practices as well as the different field techniques. In urban areas where runoff is not infiltrated due to the impervious strata the storm water management is followed by the draining of the surface runoff water. Basically the storm water management in urban areas is done by the modern approaches to rebuild the natural water cycle, that is, to store the runoff water by constructing the retention basins for a certain time period. The cost of stormwater management depends on the planning, implementation, and operation, and maintenance required expert knowledge in the water resources field. Due to the impermeable surfaces in the urban areas, flooding occurs very often due to the man-made effects. In urban areas, the runoff velocity is very high. In urban areas the storm surface runoff is added with the storm water drainage system so the peak flow increases the peak flow and overland flow volume and decreases the ground water flow and evapotranspiration. Urban storm or the surface runoff of the urban area contains the large amount of the colloids and the higher concentration of the metals and the different toxic components. So to avoid these things the drainage system should be well maintained and managed for the storm water should be well maintained. Stormwater management includes a better drainage system, which is very helpful and very effective. Stormwater management increases the water supply and water consumption efficiency. Storm water management improves the economic efficiency of the services to sustain operations and investments for water, wastewater, and storm water quality. In urban areas detention ponds, retention ponds as well as rainwater harvesting are very popular and effective techniques which are used in the storm water management in urban areas. Also, different types of infiltration devices and different pervious materials are used for the effective and efficient storm water management techniques.

5 Conclusions Many big cities situated on the shore, such as Mumbai, Bangkok, Dhaka, and Jakarta, are very vulnerable to floods. For instance, new buildings, installation of infrastructure, and rebuilding of drainage networks in metropolitan environments have all affected how water flows. These areas also get heavy rain during the monsoons. It is likely to be hard to execute structural mitigating measures because of resource and space limitations. Flood-proofing and other non-structural methods like better flood warning systems have been discovered to be more beneficial in

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flood damage reduction. In recent decades, the significant danger of climate-related catastrophe and rising development demands have made it difficult for planning officials to come up with strategies for sustainable growth. There has been a spike in interest in how to create resilience so as to minimise the harm done by natural disasters by strengthening the community’s resistance and its capacity to adapt. Although it cannot be completely prevented, catastrophe risk comes from unavoidable natural risks. This chapter seeks to learn how flood-risk mitigation strategies are included into state plans. Even yet, the information in this chapter of the qualitative content analysis describes the DRR measures’ comprehensiveness and an overview of research studies on the subject. It said that the findings and conclusions are relevant only to the degree that each community plan has some strategy built in. Research has found that the hazard avoidance, vulnerability reduction, and disaster preparation aspects have been covered in different ways by different flood protection strategies. Building resilience to disasters via DRR interventions should emphasise interventions on building preparation rather than on decreasing vulnerability, since adaptive measures are of greater importance to resilience than efforts to reduce risk. Structural defence measures are perhaps a standard strategy for planners who have consistently followed the established methods for dealing with flood problems. To minimise flood risks, adaptation, and preparedness actions should be implemented. In order to prepare for climate change-related hazards, local jurisdictions must do comprehensive environmental and vulnerability assessments of their various regions and have excellent communication with their residents in order to share and acquire the knowledge that may improve local resilience. Effective DRR actions against global climate problems rely on working with other governmental and non-­ governmental sectors. Therefore, this chapter suggests an improved integration of various measures to make citizens and communities more resilient. That should be done by getting more inclusive participation among civil societies and stakeholders to build up long-term safety, liveability, and resilience in local development projects. Although the understandability of DRR and flood resilience ideas among planners is unclear, there is certainty of their inclusion in municipal plans to include strategies. In order to better understand why local flood resilience plans are being integrated with DRR plans, it is critical to dissect these motivations. In order to understand how DRR and flood resilience develop in local flood risk management and development planning, the authorities must provide more detailed information.

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Patel, P., & Patel, A. (2021). Low cost model for desalination of water using solar energy to overcome water scarcity in India. Materials Today: Proceedings. https://doi.org/10.1016/j. matpr.2021.02.804 Patel, A., & Shah, A. (2020). Sustainable solution for lake water purification in rural and urban areas. Materials Today: Proceedings, 32, 740–745. https://doi.org/10.1016/j.matpr.2020.03.473 Patel, D. P., Ramirez, J. A., Srivastava, P. K., Bray, M., & Han, D. (2017). Assessment of flood inundation mapping of Surat city by coupled 1D/2D hydrodynamic modeling: A case application of the new HEC-RAS 5. Natural Hazards, 89(1), 93–130. Patel, S. B., Mehta, D. J., & Yadav, S. M. (2018). One dimensional hydrodynamic flood modelling for Ambica River, South Gujarat. Journal of Emerging Technologies and Innovative Research, 5(4), 595–601. Patel, P., Bablani, S., & Patel, A. (2020). Impact assessment of urbanization and industrialization using Water Quality Index on Sabaramati River, Ahmedabad. In International conference on innovative Advancement in Engineering and Technology (IAET) (pp.  1–7). SSRN Elsevier. https://doi.org/10.2139/ssrn.3553800 Quirogaa, V. M., Kurea, S., Udoa, K., & Manoa, A. (2016). Application of 2D numerical simulation for the analysis of the February 2014 Bolivian Amazonia flood: Application of the new HEC-RAS Version 5. Ribagua, 3(1), 25–33. Raška, P., Stehlíková, M., Rybová, K., & Aubrechtová, T. (2019). Managing flood risk in shrinking cities: Dilemmas for urban development from the Central European perspective. Water International, 44(5), 520–538. https://doi.org/10.1080/02508060.2019.1640955 Restemeyer, B., Woltjer, J., & van den Brink, M. (2015). A strategy-based framework for assessing the flood resilience of cities – A Hamburg case study. Planning Theory and Practice, 16(1), 45–62. https://doi.org/10.1080/14649357.2014.1000950 Restemeyer, B., Van Den Brink, M., & Woltjer, J. (2019). Decentralized implementation of flood resilience Measures–A blessing or a curse? Lessons from the Thames estuary 2100 plan and the Royal Docks Regeneration. Planning Practice and Research, 34(1), 62–83. https://doi. org/10.1080/02697459.2018.1546918 Sagathia, J., Kotecha, N., Patel, H., & Patel, A. (2020, February 21). Impact assessment of urban flood in Surat City using HEC-HMS and GIS.  In International conference on innovative advancement in engineering and technology (IAET). SSRN Elsevier. https://doi.org/10.2139/ ssrn.3558360 Shaikh, M., Yadav, V. G., & Yadav, S. M. (2018, April). Simulation of rainfall-runoff event using Hec-HMS model for Rel Sub-Basin, Gujarat, India. International Journal of Emerging Technologies and Innovative Research, 5(4), 402–407. Shaikh, M., Yadav, S. M., & Manekar, V. (2021, April). Hydraulic modelling of extreme flood event of semi-arid river basin. In EGU general assembly conference abstracts (p. EGU21-10218). Siekmann, T., & Siekmann, M. (2015). Resilient urban drainage  – Options of an optimized area-­management. Urban Water Journal, 12(1), 44–51. https://doi.org/10.108 0/1573062X.2013.851711 Singh, P., Amekudzi-Kennedy, A., Woodall, B., & Joshi, S. (2021). Lessons from case studies of flood resilience: Institutions and built systems. Transportation Research Interdisciplinary Perspectives, 9(February), 100297. https://doi.org/10.1016/j.trip.2021.100297 Tarekegn, T.  H., Haile, A.  T., Rientjes, T., Reggiani, P., & Alkema, D. (2010). Assessment of an ASTER-generated DEM for 2D hydrodynamic flood modeling. International Journal of Applied Earth Observation and Geoinformation, 12(6), 457–465. Timbadiya, P. V., Patel, P. L., & Porey, P. D. (2014). One-dimensional hydrodynamic modelling of flooding and stage hydrographs in the lower Tapi River in India. Current Science, 106(5), 708–716. Tunas, I.  G., & Maadji, R. (2018). The use of GIS and hydrodynamic model for performance evaluation of flood control structure. International Journal on Advanced Science, Engineering and Information Technology, 6(8), 2413–2420.

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Chapter 9

Flood and Drought Risk Assessment, Climate Change, and Resilience Omar-Darío Cardona, Gabriel Bernal, and María Alejandra Escovar

Abstract  Work on disaster risk is a challenge due to hazard complexity and interaction between socio-ecological systems. However, potential uses of disaster risk assessment include land-use planning, infrastructure development prioritization, and insurance measures, which can be developed in local, subnational, or national scales by public or private initiatives to build resilience and face the uncertain impacts of climate change. This chapter presents the advantages of using probabilistic risk assessments to assess the potential losses of floods and droughts for crop production and the built environment. Two case studies show that probabilistic flood and drought risk assessments are robust and flexible tools to estimate risk and compare the impacts of hazard control and vulnerability reduction initiatives to ensure risk reduction and resilience. Keywords  Probabilistic risk assessment · Stochastic drought modeling · Stochastic flood modeling

O.-D. Cardona (*) Instituto de Estudios Ambientales, Universidad Nacional de Colombia Sede Manizales, Manizales, Colombia INGENIAR Risk Intelligence, Bogotá, Colombia e-mail: [email protected] G. Bernal INGENIAR Risk Intelligence, Bogotá, Colombia Departamento de Ingeniería Civil y Agrícola, Universidad Nacional de Colombia Sede Bogotá, Bogotá, Colombia M. A. Escovar INGENIAR Risk Intelligence, Bogotá, Colombia © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_9

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1 Introduction Disasters are serious disruptions of the functioning of society due to the occurrence of hazardous events that cause losses and impacts on the exposed elements (i.e., humans, crops, and built environment) according to their vulnerability (UNISDR, 2015). Moreover, disaster risk expresses the probability of loss as a function of the probability of occurrence of a hazardous event and its interaction between exposure and vulnerability conditions of each social system. Therefore, disaster risk management encloses the processes for designing, implementing, and assessing measures to improve the understanding of disaster risk, encourage disaster risk reduction and transfer, and promote disaster preparedness, response, and recovery practices (IPCC, 2012). The objective of disaster risk management is to reduce the potential losses that a disaster can generate in a certain community with actions that can also increase the development and resilience of those communities (Eslamian et al., 2019). Disaster risk management measures can include infrastructure building or retrofitting; land-use and urban growth planning; development of financial protection instruments to transfer risk, design, and enforcement of construction codes; early warning systems implementation; and emergency preparedness plans. All of these actions are imperative, as each one of them responds to different risk levels; however, the first step for efficient risk management is risk identification, quantification, and understanding. Therefore, risk knowledge is a fundamental component of sustainability and development transformation to build resilience. The objective of this chapter is to describe the fully probabilistic disaster risk assessment methodology, implemented in the CAPRA Next Generation platform, used to estimate the potential losses of disasters that have not happened yet. It seeks to meet the Sustainable Development Goal 1.5: Building resilience and reducing vulnerability to climate-related extreme events and disasters. Also, this chapter describes how climate change projections – and their uncertainty – can be included in disaster risk assessment. The complete methodology is described using two case studies, developed by INGENIAR Risk Intelligence, in which flood and drought hazard interacts with the conditions that make people, places, and economic systems exposed and vulnerable in different scales and social contexts. The results of the disaster risk assessment included in this chapter were useful to develop and implement risk mitigation and transfer measures based on robust metrics. Although event forecasting and early warning are important components of risk understanding, they fall beyond the scope of this chapter. The risk assessment methodology is presented in detail in the first section of the chapter. The second section presents the case study of La Mojana region in Colombia where flood risk was assessed, followed by the case study of the drought risk profile for Uruguay. These case studies are useful to argue why identifying risk requires robust methodologies to provide institutions, communities, and government with proper guidelines to define risk reduction policies and prevent cascading effects such as forced displacement, famine, or food and water insecurity.

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2 Methodology Disaster risk reduction initiatives aim to develop and implement measures to reduce and prevent potential losses derived from the impacts of extreme events on exposed and vulnerable communities. There are three main points to highlight. First, as the purpose of the assessment is to prepare for extreme events – that may exceed the reaction capacity of stakeholders – it is possible to argue with high confidence that the event with the worst consequences has not happened yet. Second, it is important to pass from hazard itself to an evaluation of risk in terms of potential losses and the impacts of intervention alternatives. Finally, the exposure and vulnerability conditions are dynamic and case-dependent. Therefore, it is important to have flexible methodologies to estimate risk that bring robust results, which can be applied at different scales and compared when intervention prioritization is needed. Disaster losses are uncertain because of the random nature of the hazardous events (not fully predictable in time and magnitude), their complex interactions with the socio-environmental systems, and their susceptibility to suffering damage. As mentioned by Eiser et al. (2012), it is only because decisions should be made under uncertain conditions that the concept of risk is of any interest. Moreover, uncertainty is the result of incomplete knowledge and the intrinsic nature of perils. For example, potential flood aspects are unknown, such as when the next event will happen; where, for how long, to which extent; its magnitude (water depth in each location); how crops, buildings, and infrastructure will respond to water accumulation; and how damage is derived to economic and human losses. Therefore, the risk assessment must have a robust science background that consciously manages the uncertainties related to hazard, exposure, and vulnerability and provide tools to make decisions with sufficient information. Uncertainty in disaster risk can be handled using probability theory coupled with physical models that simulate the behavior of the natural system assessed. Probabilistic risk assessment estimates the potential losses – loss of life, loss of ecosystem services, or financial loss due to damaged property – that can occur if a hazardous event happens on exposed and vulnerable communities. The methodology is based on the research done by Cardona (1989) and Ordaz (2000) for seismic disaster risk and is fully implemented in the CAPRA software (Bernal, 2018; Cardona et al., 2012). As disaster risk is a function of hazard, exposure, and vulnerability (UNISDR, 2015), each of these three components, and their uncertainties are analyzed. Details on flood and drought hazard assessments, exposed database generation, and vulnerability concepts are described in Cardona et al. (2012).

2.1 Probabilistic Risk Assessment A probabilistic risk analysis is basically intended to determine the probability distribution of loss that exposed assets may suffer over a given period of time as a consequence of the occurrence of natural hazards, rationally integrating the

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uncertainties that exist in different parts of the process. The basic question to answer with a probabilistic risk assessment is: given that there is a set of assets exposed to the effects of one or more natural hazards, how often will losses occur that exceed a certain value? Then, risk is defined as a mathematical expectation of loss (Rougier, 2011) and is estimated as a random variable. Disaster risk estimation can be performed in three main stages: hazard assessment, exposure and vulnerability definition, and loss estimation. • Hazard modeling determines the domain – in space and time – of the collection of possible hazard events that can occur in the study area, defines the characteristics of each event – in terms of the intensity of each hazard – and assigns a probability to each hazard outcome. • Exposure characterizes the collection of exposed elements that can be damaged after the occurrence of hazard events. Vulnerability models translate the hazard intensity into a scalar quantity of loss. • Risk estimation defines the probability function that represents the loss for each particular combination of hazard, exposure, and vulnerability conditions. 2.1.1 Loss Exceedance Curve The procedure for probabilistic calculation is an estimation of losses that will affect a group of exposed assets during each of the scenarios, which collectively describe the hazard, and then probabilistically integrating the results obtained using the frequency of occurrence of each scenario as a weighting factor. The main aspects to be estimated are the loss domain (as the universe of all the possible losses) and the probability density function that better describes the loss, which is defined within the loss domain. For the case of natural hazards, the loss probability distribution should indicate that small losses are more frequent than the occurrence of large losses, that is, extensive risk (small disasters and everyday risk) is more common than catastrophic risk. The mentioned distribution function is usually represented by the loss exceedance curve (LEC) shown in Fig. 9.1, which establishes the number of times in a year in which a loss value will be surpassed. This amount is known as the annual exceedance rate, which is a unique and specific value for each amount of loss and incorporates the contribution of all possible hazard scenarios. In the loss curve shown in Fig. 9.1, the exceedance rate is shown in the left vertical axis, and the return period is shown in the right vertical axis. The return period is the expected value of time between events. Thus, it is the average time period for which, considering a sufficiently long-time window, a given loss will be equalized or exceeded. The return period of the loss is the inverse of its exceedance rate. The LEC provides an exhaustive quantification of risk, in terms of probability, regardless of the type of hazard assessed. It will never be possible to know the exact magnitude of a future disaster – in terms of the loss and outcomes that will cause – but it is possible with the LEC to know the probability that any loss amount will be exceeded within any time frame and use this information to support the decision– making process for risk reduction.

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2.1.2 Risk Metrics The loss exceedance curve has all the relevant risk information needed to define the occurrence process of events that may cause losses to exposed elements. This curve is complemented with punctual risk metrics that express risk as individual figures, which is useful to communicate risk assessment results (Cardona et al., 2012). The main risk metrics used in probabilistic assessments are the average annual loss (AAL) and the probable maximum loss (PML). • AAL is the annual expected loss value or the equivalent to an annual payment that would be needed to compensate the accumulated losses in a long enough timeframe. It is the area under the LEC. For the calculation of the AAL, the occurrence process of damaging scenarios is supposed to be stationary. In a simple insurance system, the AAL is equivalent to the annual premium. The average annual loss is a useful risk metric, as it encloses in a unique value the impacts of the occurrence of the hazardous scenarios over vulnerable exposed assets. Given that the AAL determines the expected value of loss and not its uncertainty, it is a robust risk indicator. • PML is a value associated with a loss that does not occur very often, and it is therefore, usually related to long return periods, or what is the same, to low exceedance rates. PML is a curve that relates losses with their corresponding return periods. Return periods, which are the inverse of the exceedance rates, are calculated from the total probability theorem, which means that for any loss level, its return period is calculated as the inverse of the sum over all the scenarios, of the probability of exceeding said loss level multiplied by the frequency

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of the scenario’s occurrence. There are no standards to select fixed return periods for analysis, which answers to the fact that it depends on the risk aversion of who is doing the assessment. Therefore, LEC, AAL, or PML are useful risk metrics that can be used to compare the risk impacts between hazards or different actions of the same hazard. As shown in the following section, risk metrics can be a useful tool to compare the impacts of the construction of flood control infrastructure or compare the effects of drought hazard in different productive sectors at the national scale. 2.1.3 Retrospective Versus Prospective Risk Assessment Following a probabilistic approach, risk assessment follows two main principles: (1) there is a collection of events, including the null event, that contains all the events of interest, and (2) two events cannot happen simultaneously. Therefore, the appropriate mathematical framework that allows the calculation of the probability of occurrence of any loss event – defined in a completely arbitrary way – requires the definition of a set of mutually exclusive and collectively exhaustive events. As each loss event is the result of a hazard event, then hazard models must provide a set of events that are also mutually exclusive and collectively exhaustive. Risk can be evaluated from a retrospective approach through evaluating a catalog of past disasters or from a prospective approach using probability theory to estimate future disasters and their losses. A retrospective analysis of disasters highlights changes and trends of recorded events. However, there is not sufficient recorded data of previous events from which to extrapolate to predict or estimate losses that may occur as disaster catalogs are incomplete. Also, restraining past events can limit the scope of action, especially considering low-term memory related to catastrophic events, no records on long-term climate variability, or the fact that conditions underlying risk can accumulate over time. Otherwise, a prospective approach uses a set of stochastic events generated from physical-based models and enables a vision to the future, to analyze potential events that have not happened yet and avoid the construction of new risk. The prospective approach, in terms of probabilistic assessment methodologies, is preferred because it includes uncertainties in hazard (frequency or intensity of events, climate change), vulnerability (probable damage related to event intensity), and risk (probable losses after the materialization of events). However, retrospective and prospective methods can be coupled in a hybrid approach (Velásquez et al., 2014) to include the losses of previous events, which better represent extensive risk (low-severity and high-frequency events), and the losses of events that have not happened yet, which better describe intensive risk (high-severity, mid- to low-frequency events). The three approaches mentioned are presented in Fig.  9.2, which presents the hazard intensity exceedance rate curve. This hazard exceedance curve is equivalent to the LEC, but exceedance rates are related to a hazard intensity measure and not losses. The graph shows the exceedance curves for the case of droughts, and the intensity measure is the drought

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indicator (as an absolute value). Each of the curves is the result of computing the exceedance rate for each index value (domain values from 0 to 3) for all the events of each climate scenario (historic weather, simulated series based on current weather, and series including climate change). The historic curve, also known as the empirical curve, is calculated from the index series from the historical drought events derived from daily precipitation and rainfall data from 1981 to 2010. As the curve represents the mean value of the exceedance rate, the historic curve has a confidence interval (shown in a grey shadow) that represents the variability of the exceedance rate. This confidence rate is wider as the hazard index increases, showing that greater variability is expected from higher magnitude events. The simulated exceedance curve (in blue) is the result of the analysis of a drought index series derived from 1000 stochastic precipitation and temperature series. As the number of events is higher (1000 stochastic years vs. 30  years of records) the variability is neglectable. Note that with the simulated scenario, the complete domain of the hazard intensity is covered, as the historic curve only reached the drought index of 1.7, and the simulated curve reached values higher than 2.7. Then, retrospective and prospective risk assessment can be complemented if sufficient information is available. The graph also shows the hazard exceedance curve for four climate change scenarios – related to the Representative Concentration Pathways (RCP) that define the expected greenhouse gas concentration in the atmosphere. The hazard exceedance curves for climate change move upwards, compared to the historic and simulated curves. This shows that for the same value of drought index the exceedance rate is also higher, that is, hazard events of that magnitude are more frequent. Then, hazard exceedance curves and loss exceedance curves, which are build following the same

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methodology, are useful to compare different hazard scenarios and their risk outcomes.

3 Results and Discussion This section presents the application of the fully probabilistic risk assessment methodology in two case studies developed by INGENIAR Risk Intelligence making use of the next-generation platform CAPRA Robot (Bernal, 2018). The first one shows the importance of using probabilistic methodologies for flood risk assessment. In addition, it shows how the results of these evaluations can be used to examine the relevance  – in economic, environmental, and social terms  – of flood control and adaptation to fluvial geographies measures. The second case shows the results for a national probabilistic drought risk assessment. This case shows the advantage of using a robust methodology to compare the risk results for different sectors – agricultural and livestock – and for different climate scenarios – considering the current climate and including the projections of change of precipitation and temperature of the global circulation models.

3.1 Probabilistic Flood Risk Assessment, Climate Change, and Resilience: The Case of La Mojana, Colombia La Mojana, located in the northwest of Colombia, is an alluvial delta of more than one million hectares where the Magdalena River, the Cauca River, and the San Jorge River converge. It is an extremely flat land with multiple water channels and permanent and temporary wetlands. It is a subregion of Depresión Momposina, which main environmental functions are to store floodwater, maintain surface water during dry periods, and accumulate sediments, which are key functions to the ecological balance of the region (Aguilera, 2004). More than 400,000 people live in the area, distributed in 11 municipalities of four departments. These underdeveloped communities depend on livestock production, subsistence crops, and traditional fishing and are highly vulnerable to drought and flood events. The rainy season in 2010–2011, aggravated by the impacts of La Niña, caused wide and severe damage throughout the region destroying homes and commercial buildings, flooding crops and grassland affecting the agriculture sector, and, in general, affecting lives and livelihoods of thousands on the region. This study (Cardona et  al., 2017), financed by the Colombian government through the Adaptation Fund, aimed to complete the flood risk assessment for La Mojana, following a fully probabilistic approach. The outcomes of the assessment were useful for the Adaptation Fund to develop the action plan for disaster risk management and adaptation to climate change in the area, prioritize housing

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improvement projects after the 2010–2011 flood event, and obtain funding for the US$117 million project “Scaling up climate-resilient management practices for the vulnerable communities of La Mojana” partially funded by the Green Climate Fund (PNUD, 2019). 3.1.1 Flood Risk Assessment in La Mojana The objective of this project was to create a comprehensive probabilistic risk model for the 11 municipalities in the Mojana Region in Colombia. The uncertainties associated with the occurrence of floods and the potential damage to exposed elements were included in the risk assessment, as the risk was estimated as the probability of occurrence of different amounts of economic losses. Although this region is prone to floods, historic records had not sufficient information to derive the conditions that caused extreme events in the past. The hazard assessment team had access to 38 years of incomplete data on precipitation and flow data, from which only five extreme flood events were successfully derived. Therefore, it was imperative to generate stochastic flood events in the area to assess the potential impacts of floods that have not happened yet or similar events that were not properly recorded. More than 150 stochastic events were generated following the hydrology and hydraulic response of the entire basin, including the complex system of river streams and swamps that make this region prone to floods. Moreover, these flood scenarios included the possibility of failure of the existing flood defenses in the region considering their fragility functions and failure probability. Hazard assessment provided the region with flood footprints for multiple return periods shown in Fig.  9.3, and also, it was an opportunity for Colombian researchers to develop state-of-the-art hydrology and hydraulic models for a region that was not studied in detail. Regarding the exposure, the risk assessment model considered the entire portfolio of exposed elements including housing, hospitals, schools, government buildings, lifelines, roads, and crops. The process to build the exposure database included the analysis of Landsat imagery for urban centers and rural dispersed settlements. With the support of local authorities and NGOs, data on building type, number of stories, elevation from the ground, and occupation were gathered. The construction of the exposure database also required close work with education, health, and infrastructure authorities, both on the local and the national scale. The final outcome of the exposure assessment provided the local and national authorities with updated information on the inhabitants of the region and their condition. In terms of vulnerability, based on the existing information on exposed elements and local materials and practices, models of vulnerability to floods of different types of constructions and crops were developed. The replacement cost of the buildings included in the exposure database was estimated at US$3000 million (more than 10 billion COP). For the current conditions, the annual average loss was estimated at US$50 million (more than 166,000 million COP), which is equivalent to 16‰ of the exposed value  – this is an

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Fig. 9.3  Integrated hazard maps for 10, 50, 100, and 500-year return periods (left to right) for the current conditions in La Mojana

annualized value of the potential losses in the future. The probable maximum losses, for 100-year return period, were estimated at US$175 million (590,000 million COP) or 5.6% of the exposed value and for 500-year return period were more than US$230 million (788,000 million COP) or 7.5% of the exposed value. These risk results show that La Mojana is a high-risk region under the current conditions of hazard (normal weather) and vulnerability. 3.1.2 Assessment of Interventions of the Flood Control Infrastructure With the purpose to reduce the current risk conditions in La Mojana and reduce the vulnerability of its inhabitants, the first set of interventions alternatives was developed focusing on flood defense infrastructure. The risk assessment model was used to assess the impact of different settings for the flood defense, which included (1) the reinforcement of the existing flood wall defense, (2) the reinforcement of the existing flood wall defense and the construction of a larger wall through all the riverbank, (3) the reinforcement of the existing flood defense wall and the construction of bypass structures to ensure water flow to wetlands in the dry season, (4) build a new flood defense wall, parallel to the existing one, with bypass structures. Figure 9.4 shows the flood footprint for 10-, 50-, 100-, and 500-year return periods for the multiple interventions related to flood defenses in the area. The shades of blue show the water depth in each location, where darker blue represents a deeper flood. The maps show how building defenses can increase the hazard in a nonlinear way; therefore, there is high uncertainty of the impacts of defenses in the area. Risk results for each intervention are shown in Table 9.1. With these results, it is clear that the alternative of reinforcing the existing flood defense makes that the expected annual losses increase from 16‰, in the current state, to 39.7‰ under the assumption of the application of the intervention. On the contrary, the results of the alternative of reinforcement of existing wall and the construction of a new long one, do show a reduction in the expected annual losses to 13.7‰. However, this must be

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Fig. 9.4  Integrated Hazard maps for 10, 50, 100, and 500-year return periods (by column, left to right) for multiple scenarios of flood defense wall interventions

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Table 9.1  Flood risk assessment results for La Mojana

Exposed value [million US$] AAL Normal weather PML 100-year 250-year 500-year 1000-year

No intervention 3000

Reinforce existing wall

Reinforce and build larger wall

Reinforce existing wall

Build new parallel wall

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carefully considered because impacts do not change in a linear manner, and the effects in certain municipalities can be harmful and do not compensate for the overall reduction. As for the results of the alternative of the reinforcement of the existing wall and construction of bypasses, the expected annual loss is 16.8‰ under the assumption of the application of the intervention. Finally, with the construction of a parallel wall, also with bypass, the expected AAL is 17‰. The last two alternatives of intervention showed no significant reduction of risk compared to the current state. Following these results, the reinforcement of the existing defense wall and the construction of new ones were not recommended for the region. Therefore, less hard interventions were analyzed to find alternatives to reduce vulnerability and risk in the region. 3.1.3 Assessment of Multiple Alternatives to Building Resilience and Adapt to a Changing Future in Amphibious Territories As mentioned by Berman (2010), flood control infrastructure shows that it is important to abandon the compulsive control of water and, on contrary, generate living conditions that are flexible to accept climatic influences in areas where there is a strong dynamic relationship between land and water. As shown in the previous section, flood control systems can be responsible for unintentionally amplifying risks, both social and environmental. To reduce the vulnerability of the local communities, interventions like stilt housing, schools, and hospitals were evaluated. Considering limited resources to support families that suffered losses in the 2010–2011 event, the risk assessment model was used to identify the areas that needed to be prioritized. For example, the next map shows the optimal stilt height for the integrated hazard of 475-year return period. The map shows the areas where the government had to prioritize the interventions to reduce potential losses and is useful to design future stages of intervention as resources become available (Fig. 9.5). The combination of location (11 municipalities), hazard scenarios, and intervention alternatives generated millions of possible scenarios that could be implemented.

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Fig. 9.5  Optimal stilt height for housing for 475–year return period in La Mojana

Using genetic algorithms as an optimization process, the potential intervention scenarios were compared to come up with the most adequate one(s) in terms of the Cost–Benefit ratio  – the cost of implementations vs. the reduction on potential losses. The 10-top options were compared with each other, in terms of the physical risk, their environmental impact, and the total risk. The latter was calculated in an integrated manner using a holistic risk estimation technique (Cardona et al., 2007), which allows incorporating underlying aspects of the social, environmental, and institutional order recognized as the root causes of vulnerability and risk in La Mojana. Therefore, it was possible to present a set of structural intervention recommendations and projects to include in the Action Plan for the region to be complemented with nonstructural measures to intervene in the risk root causes.

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3.2 Probabilistic Drought Risk Assessment, Climate Change, and Resilience: Results from the Agriculture Sector in Uruguay In Uruguay, disasters are almost exclusively associated with hydrometeorological phenomena. Extreme floods have caused massive internal displacements in the past, given the vast expanses of flooded land after the overflow of rivers or the flooding caused by heavy rainfall on a very flat topography. Besides, the dry seasons, in many cases intensified by the La Niña, have generated important droughts in Uruguay, affecting in an important way the agricultural and livestock sector, the latter being of great importance in the Uruguayan economy. With this in mind, for the first time in the country, a drought risk profile was developed for Uruguay to assess the impacts of extreme water stress conditions on agriculture and livestock production (Cardona et al., 2018). The crops included in the analysis were selected in terms of food security (rice, wheat) and the role in the national economy (beef and lamb meat, soybeans, and grapes for wine production). Drought risk assessment was performed for rainfed crops and grassland, under hazard events derived from stochastic weather series that represent the normal weather (mean 1981–2010) and climate change scenarios considering the four Representative Concentration Pathways (RCPs). The identification of drought risk in Uruguay was made following the probabilistic assessment methodology that aims to estimate the probability distribution of the loss that can occur in a set of exposed elements, after the occurrence of a natural phenomenon. Probabilistic models make it possible to estimate the potential future levels of loss, considering extremes droughts in the region and the uncertainty in its estimation, and the inherent vulnerability of the exposed crops, grasslands, and herds and their uncertainty. The main results for the drought risk assessment are presented as follows. 3.2.1 Probabilistic Hazard Assessment and Integrated Hazard Maps Agricultural droughts occur when the water content of the soil does not satisfy the water demand of crops, in addition to an increase of soil’s evaporation and crop transpiration. Thus, scenarios considered for the hazard definition consist of events of continuous and simultaneous conditions of deficit of precipitation and high temperature that can affect plant development. Only 25 drought events were identified from historic weather records between 1981 and 2010. To obtain a larger number of drought events, the hazard component for the probabilistic risk assessment of meteorological droughts was defined as a set of stochastic scenarios, collectively exhaustive and mutually exclusive. These scenarios describe the spatial distribution, the frequency of occurrence, and the randomness of the intensity of droughts in the region of interest. A total of 750 drought scenarios were derived from 1000-year stochastic simulation of normal weather conditions  – rainfall and temperature

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series  – after which the identification of droughts was performed using the Reconnaissance Drought Index (RDI) (Tsakiris et al., 2007). Droughts events were considered for an RDI threshold of −1, which denotes moderate to severe events (Banimahd & Khalili, 2013). Drought hazard assessment can consider the impacts of climate change in terms of increase of the mean air temperature or changes in precipitation, either projections for dryer or wetter future conditions. The methodology applied in this hazard assessment considers the Global Circulation Models that are part of the Coupled Model Intercomparison Project (CMIP5) that promotes a set of coordinated climate model experiments and provided scientific data for the AR5 (IPCC, 2014) (Intergovernmental Panel on Climate Change). The flexibility of the proposed model allows the evaluation of different climate change scenarios on drought risk assessments, including the evaluation of the Representative Concentration Pathways (RCP) or greenhouse gas concentration trajectories. Consequently, the results of drought risk assessments can be compared to establish to what extent a projection on rising temperatures and decreasing rainfall can increase the severity and frequency of droughts. The hazard assessment including climate change selected the CCSM4 (Community Climate System Model) (NCAR & UCAR, 2016) as the global circulation model that better fits the national conditions in the calibration period (1981–2010). Then, the normal weather stochastic series was adjusted with the long-term projections of changes in temperature and precipitation for each RCP of the CCSM4 model. Following the methodology, the RDI index was computed for each climate scenario, and droughts events were identified following the same index threshold. The results of the total number of events identified and the mean duration of those events are shown in Fig. 9.6. Results show how with climate change (scenarios RCP2.6, RCP4.5 RCP6, RCP8.5) there is a higher number of droughts events identified with higher concentrations of greenhouse gases in the atmosphere (or higher RCP), going from 750 events in the current weather simulation to 892 events in the simulation with modifications of RCP 8.5, the strongest business as usual scenario. In terms of duration, the box and whisker diagram – for the current weather and each of the series perturbed according to the predictions by RCP  – show that simulated droughts maintain a constant

Fig. 9.6  Total number of drought events identified in each climate scenario and their mean duration

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dispersion between scenarios (size of the box that represents the 25th percentiles – lower limit – and 75th – upper limit), with an ascending average (green line) that indicates that with higher RCP the longer the droughts. The boxplot graph shows how for the current weather normal, the mean duration of drought events is 3 months, while for the extreme scenario RCP8.5 – which is the business as usual scenario – the mean duration of drought events increases to 4 months. In all cases, external points are located outside the boxes, which represent extreme values with durations greater than 12 months, which represent rare low-frequency and high-­ magnitude events. Once the complete set of drought scenarios were obtained, they could be integrated using the appropriate arithmetic, in order to obtain uniform hazard maps. These maps allow us to compare hazard intensities with different return periods and establish, which locations are in general under the highest or lowest danger. Integrated hazard maps for 10-, 20-, 50-, 100-, and 200-year return periods are presented in Fig. 9.7 for severity, Fig. 9.8 for duration, and Fig. 9.9 for drought intensity, which is the ratio between the severity and duration. It is important to highlight the fact that these uniform hazard maps are not single events that can occur at one point in time; instead, they collect the contributions from all possible individual drought events that may occur in the territory in an infinite timeline. This provides a broader view of the drought hazard in a territory, expanding the scope of analysis and implications this hazard has in both spatial and temporal dimensions. When integrating the effects of climate change into the estimation of the drought hazard in Uruguay, it can be said that a higher number of drought events is expected with a higher concentration of greenhouse gas in the atmosphere, that is, droughts (of different intensity, severity, and duration) may occur more frequently. Also, an increase in the mean duration of events is expected, when comparing to the current normal weather. Related to the spatial distribution of droughts, it is important to mention that there is not a linear relation between a climate scenario and the drought intensity parameter, although the maps presented in the latter figures show a consistent area, in the south-west region of the country, where drought is more severe and last more time. 3.2.2 Assessment Impacts of Drought, Considering Current Conditions and Climate Change, in Crop and Livestock Production The results for the drought risk assessment for agriculture and livestock production in Uruguay are presented as follows. The expected Annual Average Loss AAL (the annual value that must be paid to compensate, in the long term, all future losses) and the Probable Maximum Loss PML (relates the losses to its corresponding return period) are estimated for the country and presented in Table 9.2. The probabilistic drought risk assessment model considered the yearly production of crops and livestock products equivalent to 6.1% of Uruguay’s GDP (relative to the 2017 GDP). Results show that under current weather conditions, potential losses of crops are US$9.3 million (equivalent to 0.6% of its exposed value),

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Fig. 9.7  Integrated drought severity maps for 10-, 25-, 50-, 100-, and 200-year return periods for current normal weather and climate change scenarios RCP4.5 and RCP8.5 in Uruguay

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Fig. 9.8  Integrated drought duration maps for 10-, 25-, 50-, 100-, and 200-year return periods for current normal weather and climate change scenarios RCP4.5 and RCP8.5 in Uruguay

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Fig. 9.9  Integrated drought intensity maps for 10-, 25-, 50-, 100-, and 200-year return periods for current normal weather and climate change scenarios RCP4.5 and RCP8.5 in Uruguay

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Table 9.2  Drought risk assessment results for crops, livestock, and total sector in Uruguay for the current weather scenario Results Exposed value AAL

PML/exposed value [%]

USD millions USD millions % Return period years 20 50 100 200

Crops $1,540 $9.3 0.6 Crops % 4.9% 5.6% 5.7% 6.0%

Livestock $1925 $50.6 2.6 Livestock % 22.8% 28.2% 40% 54.8%

Total $3465 $60.0 1.7 Total % 12.4% 15.5% 23.3% 24.5%

Fig. 9.10  Probable maximum loss curve for crops, livestock, and total sector in Uruguay

potential losses for livestock are US$50.6 million equivalent to 2.6% of its exposed value), and the total potential losses are US$60 million (equivalent to 1.7% of the crops and livestock exposed value). These results confirm that livestock production is the sector more vulnerable to droughts, especially because under water stress conditions it is difficult to provide animals sufficient food (dry grass or forage) because of the reduction of their yield. Also, these risk results also show how under current weather there are risk conditions in the country that need to be managed, and alternatives to mitigate the hazard, transform living conditions or transfer risk should be considered in the short term. The PML values for 20-, 50-, 100-, and 200-year return periods for the current weather risk scenario were obtained from the curve presented in Fig. 9.10, which relates the loss values with a complete series of years of return period. This graph

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Fig. 9.11  Probable maximum loss curve for the total crop and livestock production in Uruguay for the current weather and climate change scenarios

shows separately the probable maximum losses for each sector assessed and the total value after aggregation. Figure 9.11 shows the PML curve for the aggregation of crop and livestock production, for the current weather and the climate change scenarios. The curves show how the bigger changes are expected for events with return periods over 100 years, which are low-frequency and high-magnitude events. Under current weather conditions, the PML for 100 years is US$806 million, while for the RCP8.5 (business as usual scenario) PML for 100 years return period is US$860 million, approximately a 7% increase if projections of the CCSM4 model are close to reality. Risk metrics can also be presented in maps to allow the spatial comparison of risk between scenarios and to prioritize interventions in the territory. Figure 9.12 shows the maps of the average annual loss (%), relative to the exposed value, of each of the departments in the country. These maps are the result of aggregating the AAL metrics of each cropland and grassland (defined in the exposure model) to political boundaries to inform the national government of the risk conditions each department face. It is important to notice that, although the hazard intensities shown in the integrated maps (see Figs. 9.7, 9.8, and 9.9) are higher in the southwest region of the country, risk results are higher in the East region. This shows how risk is not limited to hazard intensity, as the departments in the west are less vulnerable to droughts than the departments on the east, despite the hazard exposure in each case.

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Fig. 9.12  Ratio of the annual average loss and the expected value for each department in Uruguay, for the expected loss in crops and livestock production (%)

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4 Conclusions This work presents a fully probabilistic risk assessment methodology that can be applied in multiple scales and assess multiple hazards, in a robust way that produces risk metrics that can be comparable to provide decision-makers with information for implementing intervention alternatives to build resilience. The proposed methodology was applied in a flood risk assessment in La Mojana, a low–income highly vulnerable region in Colombia. Flood risk assessment was performed to the built environment in a fragile ecosystem in which communities face human development challenges, including risk. The case study showed that the construction of hard infrastructure for flood control is not always a risk reduction alternative but can create new risks for the local communities and their livelihoods. Also, the flood risk assessment provides the national government with information to prioritize the delivery of aid and technical support as the areas where houses at higher risk were fully identified. The study also justified the access to additional funding from international agencies to build resilience in the region. Also, the probabilistic risk assessment was used to estimate the drought risk profile for Uruguay, where crop and livestock productions are imperative sectors for the national economy. Drought risk assessment was performed on a stock of crops and livestock products selected considering food security (subsistence farming) and their role in the national economy (national and international trade). The drought risk profile results concluded that the areas of the country exposed to the higher hazard intensities are not necessarily the most vulnerable. Therefore, it is important to estimate not only hazard but also risk, making informed decisions and building resilience. The case study included the estimation of the risk conditions under the current weather and under the potential impacts of increasing temperatures and decreasing rainfall associated with climate change. It was shown that the effect of climate change is non–linear, still uncertain, and adds a layer of complexity to current vulnerabilities and risks. The drought risk profile at a national scale was useful for the agriculture planning authorities to develop further instruments to support producers. Also, the methodology and results of the study encourage the development of a national disaster risk atlas that included the risk assessment for floods, droughts, strong winds, and forest fires for the built environment, crops, and ecosystem services. A fully probabilistic risk assessment is a useful tool to identify and understand risk, embrace the uncertainty of the natural and social systems, and uncertain future climate or development conditions. These robust methodologies provide institutions, communities, and governments with proper guidelines to build resilience at multiple scales.

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References Aguilera, M. (2004). La Mojana: riqueza natural y potencial económico. Documentos de Trabajo Sobre Economía Regional, 48. Banimahd, S. A., & Khalili, D. (2013). Factors influencing Markov chains predictability characteristics, utilizing SPI, RDI, EDI and SPEI drought indices in different climatic zones. Water Resources Management, 27(11), 3911–3928. https://doi.org/10.1007/s11269-­013-­0387-­z Berman, I. (2010). Amphibious territories. Achitectural Design, 80(3), 66–73. Bernal, G. A. (2018). CAPRA GRM. Cardona, O. D. (1989). Enfoque metodológico para la evaluación de la amenaza, la vulnerabilidad y el riesgo sísmico. Revista de Ingeniería Sísmica, 37, 31–63. Cardona, O.  D., Carreño, M., & Barbat, A. (2007). Urban seismic risk evaluation: A holistic approach. Natural Hazards, 40, 137–172. https://doi.org/10.1007/s11069-­006-­0008-­8 Cardona, O. D., Ordaz, M., Reinoso, E., Yamin, L., & Barbat, A. (2012). CAPRA – Comprehensive approach to probabilistic risk assessment: international initiative for risk management effectiveness. In 15th world conference on earthquake engineering. Cardona, O. D., Bernal, G. A., Zuloaga, D., Escovar, M. A., & Olaya, J. C. (2017). Modelación probabilista de inundaciones en La Mojana. Cardona, O. D., Bernal, G., Escovar, M. A., Villegas, C., & González, D. (2018). Perfil de riesgo por sequía e inundación de Uruguay – Estimación del valor expuesto y modelación de la vulnerabilidad. Consorcio INGENIAR – CIMNE. Eiser, J. R., Bostrom, A., Burton, I., Johnston, D. M., Mcclure, J., Paton, D., et al. (2012). Risk interpretation and action: A conceptual framework for responses to natural hazards. International Journal of Disaster Risk Reduction, 1, 5–16. https://doi.org/10.1016/j.ijdrr.2012.05.002 Eslamian, S., Reyhani, M. N., & Syme, G. (2019). building socio-hydrological resilience: From theory to practice. Journal of Hydrology, 575, 930–932. IPCC. (2012). Managing the risks of extreme events and disasters to advance climate change adaptation: A special report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press. IPCC. (2014). Climate change 2014: Synthesis report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Core Writing Team, R. K. Pachauri, & L. A. Meyer, Eds.). IPCC. NCAR, & UCAR. (2016). CCSM4.0 public release. Retrieved from http://www.cesm.ucar.edu/ models/ccsm4.0/ Ordaz, M. (2000). Metodología para la Evaluación del Riesgo Sísmico Enfocada a la Gerencia de Seguros por Terremoto. Universidad Nacional Autónoma de México. PNUD. (2019). USD117 Million will be invested in environmental project Mojana: Climate and life. Retrieved from http://www.co.undp.org/content/colombia/es/home/presscenter/pressreleases/2019/02/MojanaClimateAndLife.html Rougier, J. C. (2011). Quantifying hazard losses. Risk and Uncertainty Assessment for Natural Hazards, 9781107006195(2003), 19–39. https://doi.org/10.1017/CBO9781139047562.003 Tsakiris, G., Pangalou, D., & Vangelis, H. (2007). Regional drought assessment based on the Reconnaissance Drought Index (RDI). Water Resources Management, 21(5), 821–833. https:// doi.org/10.1007/s11269-­006-­9105-­4 UNISDR. (2015, August). Proposed updated terminology on disaster risk reduction: A technical review (pp. 1–31). Velásquez, C., Cardona, O. D., Mora, M. G., Yamin, L., Carreño, M., & Barbat, A. (2014). Hybrid loss exceedance curve (HLEC) for disaster risk assessment. Natural Hazards, 72, 455–479.

Chapter 10

Flood Risk Predictions in African Urban Settlements: A Review of Alexandra Township, South Africa C. C. Olanrewaju and M. Chitakira

Abstract Accurate and effective management of floods is necessary to reduce losses from floods. This is achieved by a good knowledge of the drivers of flood risks, which include climate change, societal risk perceptions, urbanization, and associated land-use changes. Sustainable management of floods requires techniques and models that can produce accurate and timely predictions. While vulnerability can increase flood risks, a proper knowledge of the vulnerable population and various coping strategies will help in disaster risk reduction and management. This chapter reviews the relationship between major factors influencing flood risks in Alexandra, a township in the City of Johannesburg in South Africa. It also reviews the preference of Artificial Neural Network (ANN) for flood predictions against other models in the identification of the most important variables responsible for floods in the selected study area. The ultimate goal is to prevent loss of life and effectively reduce the cost of flood management. An extensive literature search of published articles available from online databases (Scopus, PubMed and web of science), published theses, and newspaper articles was conducted in this review. This review revealed inadequate risk planning and inefficient coping strategies within the community. As such, help does not reach the affected people on time, resulting in loss of lives. The review also showed a lack of clear strategies in place to reduce the vulnerability of poor community members and that poverty plays a major role in intensifying vulnerability. An argument emerging from the review is that the ANN is a potentially effective flood prediction tool, which enables efficient preparation and mitigation of flood hazard. The review is hoped to provide flood disaster managers and other stakeholders with insights into effective management of flood risks in the study area and other places with related conditions. Keywords  Flood risks · Societal vulnerability · Artificial Neural Network · Flood management · Alexandra Township · City of Johannesburg

C. C. Olanrewaju · M. Chitakira (*) Department of Environmental Sciences, School of Ecological and Human Sustainability, University of South Africa, Pretoria, South Africa e-mail: [email protected] © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_10

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1 Introduction Natural disasters such as tropical cyclones, droughts, and floods are experienced regularly around the world (Chau et al., 2013). The consequences of environmental change make floods to remain the most continuous and obliterating of all cataclysmic events around the globe (Ni et al., 2014). The severity of a flood is a critical determinant of loss of life, coupled with the after effects of diseases and starvation (Alexander, 2006). According to Alderman et al. (2012), floods will intensify the weight of disease, morbidity, and mortality globally and increase economic and social disruptions, thus, placing continuing stress on health services. The flood disaster that occurred in China in 1931 is said to be the most deadly flood disaster of the twentieth century, which resulted in the death of over a million people (NASA, 2015). The 2000–2010 decade recorded 53,000 deaths due to floods globally (EM-DAT, 2011, Alderman et al., 2012). A flood is said to have occurred when water overflows mostly onto land, which ordinarily is not submerged (Mandel et al., 2005). It is a result of excess water flowing on land that used to be dry (Djimesah et al., 2018). Water causing disastrous flooding originates from different sources, which include prolonged and intense rainfall, downstream blocking of river channels by avalanches and landslides, snow melt, river blockages or upstream failure of dams, tides that are abnormally high, tidal waves, and storm surges (Mandel et al., 2005). Floods are further exacerbated where human-made barriers such as network of canals and roads exist. These barriers obstruct the natural and free flow of water. Li et al. (2013) noted that developed and developing countries have become defenseless to flooding calamities. Flood disasters were frequently experienced throughout the recent decades in South Africa. The flood that occurred over most of Southern Africa from December 1999 to March 2000 was described as the most severe humanitarian disaster in the sub-­ continent (Alexander, 2002). According to Alexander (2002), thousands of people in the two northern province of South Africa had difficulty accessing potable water resulting in loss of lives in thousands and infrastructure destruction. The city of Johannesburg and other municipalities in South Africa were declared disaster areas as a result of the floods that occurred across the country in 2010/2011 that caused many deaths and loss of property (RSA, 2011). The flood disaster that hit Johannesburg in 2016 was very devastating with infrastructural damages and displacement of residents especially in the informal settlements of Alexandra township (Sibanda, 2016). Movement of individuals from rural to urban areas has caused increasing vulnerability to floods. The United Nations estimates that by 2050, about three billion people will be living in informal settlements (Ademiluyi, 2010). By 2030, African cities will have over 300 million migrants from rural to urban cities (Masilela, 2012). Most cities in sub-Saharan Africa have a substantial percentage of their populace living in informal settlements (Nchito, 2007). It has been postulated that by year 2020, there would be an influx of additional 20 million people from rural to urban areas in South Africa, resulting in proportional increase in occupation of areas

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that are flood prone (Alexander, 2006). Household surveys carried out by Statistics South Africa in 2011 showed that 1789 million households in South Africa (12.1%) lived in informal settlements, with Gauteng province having the highest number (South-Africa-Year-Book, 2012/13). By the year 2018, the number of informal settlements had risen to 13.1%, with Gauteng province recording the highest of 19.8% (StatsSA, 2019). The low-income sector is the one most affected by population increase as it is forced to construct illegal and substandard dwellings, making it highly vulnerable to the effects of floods. Floods can be grouped into different types and occur in different scales (Jain et al., 2018). Floods can also be described according to speed of occurrence, geography of affected area, or cause. According to the Victoria State Emergency Service (SES), floods can be caused by more than just rain, which can happen at any time and at anywhere (USGS, undated). There are two basic kinds of floods, which include flash floods and riverine floods. Flash floods are common in urban settlements due to limited infiltration and rapid drainage. Water cannot be soaked into paved surfaces and thus is redirected into storm drains and city sewage systems causing overwhelming and subsequent flooding (Means, 2018). According to Means (2018), flash floods are the most lethal because of their sudden onset. They can form within 6 or less hours of precipitation (SES, undated). Due to heavy precipitation, rapid onset, and a short response time, flash floods can have high societal impacts (Jain et al., 2018). It is noted that rainfall is a major factor but not the only contributor to flooding in urban areas (Douglas et al., 2008). Major causes of floods include natural (such as extreme rainfall and low-lying topography) and anthropogenic activities (such as deforestation and urbanization). Such factors increase the recurrence and severity of floods (Kasiviswanathan et al., 2017; Nguyen et al., 2021). Flooding disasters in urban areas are exacerbated by blocked drains, poor waste management, expanded density of settlements, occupation of areas prone to floods, and impervious surfaces, for example, streets, asphalts, solid surfaces, and so on (Douglas et al., 2008). Some of the worst flood disasters recorded in urban areas are due to heavy and sudden precipitation events that generate flash floods that are not easily and accurately predicted and subsequently warned against (Dyson, 2009). As noted by Fatti and Vogel (2011), a lack of understanding of climate forecast hampers the building of resilience against flood disasters. Floods are a natural hazard that cannot be completely eliminated, but its effects can be reduced by taking appropriate measures. Flood risk is defined as the degree of the total adverse effect of flooding, which incorporates certain concepts such as difficulty and danger of evacuating people and possessions, loss of production, damage to public property, threat to life, potential damage to infrastructure, and social interruptions (Rani et al., 2018). When flood risk is high, the level of vulnerability and hazard will also be high. Flood risk can be reduced by decreasing the level of vulnerability and reducing exposure (Dang et al., 2010). Flood predictions with subsequent management plays a significant role in timely and effective decisions for disaster mitigation and prevention.

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Flooding in the Alexandra Township is often due to heavy down-pours coupled with unplanned residential development associated with rapid growth of urbanization,  which makes the drainage system unable to cope with excessive water. In response to devastating floods around the world, several researchers have recently attempted to develop smarter and stronger flood protection tools such as satellite imaging, remote sensing technology, fiber optics and electronic sensors enabled and stored on bridges, and dykes for nonstop monitoring (DeCastro et  al., 2013, Krzhizhanovskaya et al., 2011). Regardless of the endeavors by governments and private sector organizations  to increase alerts and raise communities’  awareness, flash floods continue to be one of nature’s most dreadful killers because of the absence of a lead-time (DeCastro et al., 2013). Flood forecasting for large rivers has witnessed successes, unlike the case of urban floods because of the complexity of the  factors involved  and high population densities in urban areas (Chang et  al., 2014). Flash floods are characterized by water flowing quickly over the land inundating homes, destroying properties and drowning people. Relocation of residents have been suggested by several researchers to be the best way to solve the problem (Owusu-Asante & Ndiritu, 2009). However, this is not a simple task to accomplish as residents have deep traditional, psychological, and cultural attachments to their areas such as graveyards of their relatives. Social aspects of poverty and poor perceptions of flood risks add to the complexity of the matter (Dalezios & Eslamian, 2016). This chapter anchors on the review of flood risk predictions in Alexandra, a township in the Gauteng province of South Africa. The chapter reviews the state of research relating to practices and people’s perceptions of risk and the level of risk they assign to climate change and floods, highlighting the different connections researchers have made concerning these phenomena. Also reviewed are the causes and consequences of urban floods and the relationship between climate change and urban floods, delving into the vulnerability to floods and the different coping strategies utilized by people affected by floods. The chapter also reviews the different flood management concepts employed in general and in the study area in particular. Flood prediction models used in the forecast of floods are reviewed, identifying the various gaps created by each model and their subsequent upgrade and highlighting the preference of ANN in flood predictions. This review is an initial stage in the development of a framework for flood risk predictions to enhance flood risk management in the Alexandra township. Multiple sources of information are utilized in this review. Peer-reviewed and published research articles on floods risk prediction and management from scientific research databases are used. Published theses and online reports, flood reporting sites, and newspaper articles are also consulted to obtain as much literature on flood predictions in the focus area as possible. Databases on discipline and alignment to the scope of the review are selected. This review covers events of the period from 1997 to 2021. The review period is selected to study the flood pattern and vulnerability of the community members and the coping strategies developed. Such information is intended to contribute to the development of an integrated framework

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Table 10.1  Sources of documents for the current review

1 2 3 4 5 6 7 8 9

Databases ScienceDirect Scopus PubMed Web of Science Google Scholar IEEE Xplore (Institute of Electrical and Electronics Engineers SciELO DOAJ (Director of Open Access Journal) SpringerLink/Springer

10 EM-DAT (International Disaster Database) 11 Other sources (Newspaper online, reliefweb, ebook, world Bank, United Nations, NASA, WHO, MPDI, etc.)

Link www.sciencedirect.com www.scopus.com www.pubmed.ncbi.nim. nlm.gov www.webofknowledge.com www.scholar.google.com www.ieeexplore.ieee.org www.scoelo.org.za www.doaj.org www.link.springer.com/ www.springer.com www.emdat.be

No. of articles 36 12 2 21 24 5 5 4 14 1 18

for the management of flood risk in the study area. Table 10.1 shows the databases and sources of information used in this review.

2 Bio-physical Characteristics of Alexandra Township Alexandra was established in 1912 as a native township for blacks in South Africa, located 13  km northeast of Johannesburg city center (Vogel, 1996). The Jukskei River is the longest of the three rivers draining the northern and the north-eastern suburbs of Witwatersrand with its source from the Bezuidenhout valley east of Johannesburg. It flows through Alexandra separating the township into two sub-­ catchments, namely the east and west bank having striking differences (Mgquba & Vogel, 2004). The east bank (east of the Juskei River) houses about 5% of the total inhabitants of Alexandra. It is further divided into the east bank, which was redeveloped in 1980 for the middle to high income earners, and the far east bank, which was  initially developed in 1999 as Athlete’s village containing 1700 formal houses and now known as “Tsusumani village” (UN-Habitat, 2009). The west bank, also known as “Old Alex” (west of the Juskei River), is densely populated, comprising of informal settlements many of which have been located below flood line and home to  some of the poorest people in the city  (UN-Habitat, 2009; Mgquba & Vogel, 2004) (Fig. 10.1). Alexandra extends over 800 hectares of land. This area was originally meant to accommodate a total of 70,000 people. It increasingly became overpopulated with an increase in population from 30,000 in the mid-1920s to an estimated 350,000 by

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Fig. 10.1  Map of Alexandra. (Murray, 2009)

2009 (UN-Habitat, 2009, Murray, 2009, Wilson, 2002). There has been an influx of migrants from neighboring countries as a result of wars and depleted economies and young black South Africans from rural areas in search of employment (Murray, 2009). According to Murray (2009), an estimated 350,000 residents were congested in 4000 formal houses and 34,000 informal self-built houses known as shacks, mostly situated on unfavourable topography on  the west bank. These shacks are located on tiny plots of land with no unauthorization prior to building.  The land is unserviced and lacks basic social amenities as well as proper physical infrastructures (Fig. 10.2). The unplanned population rise has caused an overloading of the infrastructure resulting in low piped water pressure, frequently clogged and overflowing sewers, and narrowing of the river channel due to illegal dumping of refuse into the Jukskei River. This has increased the risk of flooding in the event of heavy rainfall (Magubane, 2019) (Fig. 10.3). Extreme torrential rains constantly put the area under

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Fig. 10.2  Picture of shacks in Alexander township (SABC, 2021)

Fig. 10.3  View of Stjwetla shacks in Alexandra, on the banks of the Juskei River. (Photo credit: Thembisani Dube in Sehoai, 2020)

the threat of flooding (Mgquba & Vogel, 2004). Alexandra township has been recorded as having yearly flood disasters from 1994 to 2000 (Mgquba & Vogel, 2004). The flood disaster that affected Alexandra in the year 2000 is reported to be the worst of its kind in living memory, with huge social and financial impacts (Van-­ Bladeren & Van-de-Spuy, 2000). Alexandra has been found to be one of the poorest and most impoverished residential areas in the country, which implies high vulnerability of the area to flood disasters (Morgan, 2019).

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3 Explaining the Concept of Risk An understanding of risk and the degree of vulnerability are very crucial in working out risk reduction measures (Rana & Yayant, 2016). Risk due to floods is the likelihood of a flood event occurring and the degree of harm caused (Fuchs et al., 2005). The harm relates to the expense (in fiscal esteem) of objects affected by the flood and the vulnerability against process magnitude (Zischg et al., 2018). According to Zischg et al. (2018), the knowledge of hazardous process and the impact they cause is required to manage flood risks. Analysis of flood risks is frequently being carried out from a dynamic viewpoint as opposed to from a static point of view because the single factors of the risk formular and the resulting risk are evolving over time (Merz et al., 2010, Muzzorana et al., 2012). This has led to numerous studies on the changes of natural risks over the decades (Achleitner et al., 2016). In a study carried out by Zischg et  al. (2018), rather than concentrating on the future increment of flood risks alone, the researchers investigated the elements of the change itself on flood plains. The study revealed that while flood risk is developing extensively, it is not really expanding. The study confirmed that over two centuries, there was a relevant decrease in flood risks in the area. Technical means of controlling extreme floods have become limited in the past years (Pahl-Wostl, 2007). In Europe, technical flood protection structures are unable to cope with the increasing flood risk such that it is necessary for alternative or supplementary means to be considered (Jupner, 2018). This has led to a paradigm shift in flood management. This shift is likely to move strategies of flood resistance or flood protection towards flood resilience or flood risk management, respectively (Hartmann & Spit, 2015). This strategic shift will mean managing a flood risk by minimizing the damages instead of just defending against floods (Klijn & Koppenjan, 2012). This can be achieved by incorporating measures as a result of collaboration with local government in developing and implementing risk management measures (Johann & Leismann, 2017). According to a study by Jupner (2018), awareness and acceptance of stakeholders (affected population) is very important for efficient reduction of flood damage. There are, however, challenges in getting the stakeholders and encouraging their involvement in the process of flood risk management (Roos et al., 2017). Getting stakeholders involved internalizes the concept of risk. According to Roos et al. (2017), several communities that are aware of risk do not consider it as their responsibility or something that can be managed. Their research found that internalization of flood risk is a prerequisite for all those involved to perceive flood risk as individual responsibilities that can be prepared for and subsequently managed. Roos et al. (2017) showed that the challenge of stakeholder involvement revolves around how flood risks are construed socially. Further, when external danger is perceived, it leads to stakeholders taking no action, but the reverse is the case when internal risks is perceived. For example, floods are seen as innovative difficulties that are effortlessly fathomed by engineering solutions (Hartmann, 2011); thus, floods are manageable and perceived as risk and not danger (Renn, 2008). Risks are conditions

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that are manageable within a subsystem, while dangers are external conditions that cannot be managed by the system (Luhmann, 1993, Aven & Renn, 2010). Luhmann (1993) affirms that risks are ascribed to choices that are made, while dangers are externally credited in this manner disguising hazards and accepting they are sensible. Studies show that if an individual can perceive flood risk and is aware of the severity of the problems faced, it would lead to greater attitude change (Masud et al., 2018). According to Nyakundi et al. (2010), people perceived flood risk only to the magnitude they had experienced previously. This is to say that the memory of past risk influences how individuals perceive and react to future flood events. Risk perceptions and behavior are influenced by human differences such as age, class, ethnicity, gender, and subculture (Wisner & Luce, 1995). Research carried out to examine the attitude, awareness, perception, and response of residents to floods in the Mdloti flood plain near Durban, South Africa, indicated that almost 50% of the respondents lived in flood prone areas and were unaware of the consequences of flood hazards. It was found that about 77% of the respondents perceived flooding to be an act of nature and 35% blamed flood disasters to be due to negligence on the part of the government and local authorities (De-Villiers & Maharaj, 1994). Another study carried out in Ekurhuleni Municipality in Johannesburg South Africa show that residents’ perceptions of risk is influenced by history of distrust between residents and local government (Fatti & Patel, 2013). According to Wisner and Luce (1995), the inability to perceive flood risk and the need for flood evacuation plan by the residents of flood prone areas of Alexandra Township is tied to the fear of loss of belongings. The residents, especially those residing in shacks, fear that their belongings may be looted.

4 How Climate Change Relates to Flood Risk Without the knowledge of climate change and other contributing factors causing floods, it becomes extremely difficult to get a good hydrological prediction model. This is because climate change impacts greatly on hydrological responses. Climate change has had a global effect on water cycle, socioeconomic systems, and the atmosphere with a likelihood of its impact increasing in the twenty-first century (IPCC, 2013). Some studies have attributed the increase in temperature to climate change due to rapid urbanization, deforestation, and rising concentration of greenhouse gases (Banasik et  al., 2014). Other studies have attributed increasing frequency of flood events to climate change impacts (Gizaw & Gan, 2016, Jiang et al., 2017). Gizaw and Gan (2016) in their study of southern Alberta region in Canada demonstrated the changes that are expected and the force and recurrence of extraordinary precipitation occasion. Southern Alberta has been known to experience major floods, which are estimated to be of 100-year or higher return periods occurring a few times lately (Gizaw & Gan, 2016). This confirms the report by Barrow and Yu (2005) that climate change impact has a possibility of leading to higher maximum, mean, and minimum temperatures in the future. Climate change can lead

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to change in average and extreme conditions. Extreme weather events will increase in recurrence because of climate change (IPCC, 2014). The impacts of climate change on flooding vary within a watershed and between watersheds by geographical characteristics such as land use/land cover, soil, slope, and precipitation-related features (Praskievicz & Chang, 2009). Studies show that the effect of climate change on flooding is greater in unplanned than planned urban development (Ahmed et al., 2018). In a study carried out in the North east of the United States of America, climate change is anticipated to have more intense and successive rainfalls and increased temperatures (Cheng et al., 2017). Research has shown that Africa is one of the most vulnerable regions affected by climate change (Epule et al., 2017). In a research on six major cities in Africa (Lagos, Mombasa, Der-es-Salaam, Accra, Douala and Addis Ababa), it was observed that climate change and adaptation effort is not as hopeless as presumed and has promising prospects (Filho et al., 2018). The geographical location of South Africa is a region most vulnerable to climate change, as such, achievements of sustainable development is threatened due to the growing social and economic costs of climate change (IPCC, 2012)

5 Urban Flooding Dynamics To be able to evaluate the best way to cope with flood disaster within the urban settlement, urban flooding itself needs proper understanding. Urban flooding is a contributing factor to economic, social, and governance challenges in many areas worldwide. In Africa, these challenges have great impacts on public health, poverty alleviation, and sustainable development especially in rapidly expanding megacities (Davis, 2015). Studies carried out in recent years have attributed the increase in flood risk to urbanization (Zhang et al., 2008, Fernandez & Lutz, 2010). These studies reveal that the expansion in urban settlements and construction of artificial surfaces such as asphalts, sidewalks, roads, or driveways lead to increased flow of water due to excess storm water over the surface of the earth as a result of minimal water loss through soil infiltration (Mahmoud & Gan, 2018). Urban flooding is aggravated by overpopulated cities as a result of migration due to search of a better life and civil wars (Davis, 2015). Research by Davis (2015) showed that megacities in Africa are at a risk of geological disasters, thereby posing huge waste management problems, poor air quality, water use problems and climate change. Research also showed that flooding in Africa is due to inadequate drainage as a result of blocked channels leading to overland flow and poor waste collection (UN-Habitat, 2010). Africa is the fastest urbanizing region in the world, and African cities exhibit similar qualities such as informal settlements along flood plains, poor infrastructure, lack of adequate services, and poverty (ActionAid, 2006). This is the case with Alexandra Township. Climate change and urban development are key factors contributing to increased flood damage (Poelmans et  al., 2011). However, research shows that flood risk

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could be significantly increased as a result of urban development and accelerating urbanization without the participation of climate change (Jha et  al., 2012). Investigations carried out to ascertain the relative impact of climate change and future urban expansion on floods found out that urban expansion into flood-plains was the major factor responsible for potential flood related damages (Poelmans et al., 2011). A study carried out by Beckers et al. (2013) showed that the influence of climate change is more in wet areas than dry ones. Urban development may increase the risk of future floods because of local changes in hydrological conditions and existing models for urban land-use changes only consider the expansion process without considering the distinctiveness of the existing urban areas (Mustafa et al., 2018). This review showed that overpopulation in Alexandra township has led to the construction of informal settlements using substandard building materials along the flood plain. This is a catalyst for excessive damage and loss of lives when floods occur.

6 Flood Vulnerability in Alexandra Township Inability to understand the vulnerable groups will make it difficult to assist the affected community. Vulnerability refers to a series of processes and conditions occurring from social, physical, economic, and environmental circumstances, which leads to susceptibility of communities, infrastructures, or environment to the impacts of hazards (Wilson, 2012). Vulnerability can be defined in broader terms to refer to the characteristics of an individual or group of people as regards their capacity to anticipate, cope with, resist, or recover from an impact of a natural hazard (Blaikie et al., 2004). In poor urban environments, vulnerability to floods is associated with socioeconomic and physical phenomena and numerous factors that increase or decrease the ability to cope and adapt to changes brought about by the flood (Salami et al., 2017). Several researchers identified various factors that exacerbate social vulnerabilities. These include livelihood circumstances, geographical location, and social protection (Rufat et al., 2015). Research shows that vulnerability to floods in Alexandra is largely as a result of various historical events and policies in South Africa which include an interplay of apartheid, capitalism, colonialism and the associated segregation laws (Mgquba & Vogel, 2004). According to Mayekiso (1996), these factors have played an important role in shaping the political, social, and economic setting that causes vulnerability in Alexandra Township. Some research attributed the vulnerability of Alexandra to the layout of rocks and silt that does not accommodate large quantities of water easily (Owusu-Asante, 2008). The Jukskei River, which flows through Alexandra, has also been found to increase vulnerability (Mgquba & Vogel, 2004). One survey attributed vulnerability of Alexandra Township to a large number of people, which causes overcrowding and its subsequent problems such as blockage and overflow of sewages and inadequate flood maintenance (Project-­ Spotlight, 2000).

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Various plans to rebuild or remodel Alexandra have been proposed such as the Urban Renewal Plan of 1986, which gave birth to east Alexandra and engineering schemes carried out in an attempt to improve infrastructure such as sanitation, road, and housing (Dirsuweit, 1998). However, according to Vogel (1996), this led to more influx of migrants putting more pressure on the built and physical environment. Mgquba and Vogel (2004) observed that construction of backyard shacks and numerous informal settlements in close proximity and on flood plains of the Jukskei River was because of accommodation shortages. Setjwetla informal settlement, which lies along the Juskei River, is highly prone to flood disaster especially during the rainy season making the residents vulnerable to diseases. According to an assessment carried out by Mgquba (2002) after the flood disaster of 2000 which was termed to be the most horrific, key determinants to vulnerability in Alexandra were seen to be the lack of access to resources (leading to physical and social poverty) and poor state of infrastructure. Another report by the CoJ (2008) pointed to the rapid change in land use and loss of open space and infilling of wetlands as responsible for the increase in surface runoff, which leads to the vulnerability of the residents to floods. It has been observed that residents of flood-prone areas, despite exposure to recurrent flood risks, tend to refuse to relocate because the present location is linked to their immediate economic survival (Nyakundi et al., 2010).

7 Coping Strategies in Place Different victims and households vulnerable to floods employ different ways of coping during flood disasters. Coping strategies help affected victims to sustain their livelihoods during the recovery and rehabilitation phases (Samaraweera, 2018). Samaraweera (2018) also affirms that coping strategies are also influenced by past experiences of the victims. In a study to explore geographical patterns and disaster management in Alexandra Township, it was observed that the practice of disaster management is relatively new in South Africa and as such, many local Governments do not have well-informed coping strategies to manage floods (Mere, 2011). The study also found out that the Alexandra community had created rescue groups that help in flood disasters. However, the rescue groups are inadequate and undeveloped. Governmental and non-governmental organizations made regular inputs by offering clothing and food to the affected flood victims. Notwithstanding, the community remains unsatisfied (Mere, 2011). Individual coping strategy is on a minimal level as the victims rely majorly on the community and government support to cope with flood disasters. Above studies have showed that relocation has not been a successful option, and the government has not been able to develop new strategies or measures to improve the coping strategies in the community.

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8 Resilience and Flood Management Approaches To be able to inform policies through the different phases of the disaster management cycle and to reduce the cost and time spent on flood disasters, a review of flood management is required. Over the decades, there has been considerable advancement in urban flood management concepts (Fletcher et al., 2015). Flood management is increasingly moving towards source control, which refers to the control of water where and when it falls (Bertilsson et al., 2019). Bertilsson et al. (2019) proposed integrating source control to flood management over watershed to reduce changes in urban water cycle. A group of researchers demonstrated the effectiveness of the integration of source control in flood management (Ahiablame et al., 2012). Research demonstrated adaptation as fundamental to resilience and sustainability concepts as evolving from fail-safe goals where infrastructures are designed to provide protection against flood risk when risk is adequately predicted to fail-to-safe systems as a result of uncertainties that urban infrastructures are currently facing (Kim et al., 2017). Fail-to-safe systems depart from the traditional calculations of flood risk in construction of flood infrastructures to construction of infrastructure that are able to withstand unpredicted risk (Kim, 2018). Research revealed that policy-­makers throughout the world are changing the way they deal with urban flooding, shifting their strategy of defense against inundation to the approach of flood risk management (Pender & Neelz, 2007). Combining structural and non-­ structural measures of prevention, mitigation, preparedness, response and recovery from flooding was shown to be effective  in reducing  flood damages and effectively managing flood risks (Bertilsson et al., 2019). According to Bertilsson et al. (2019), the related consequences of a flood event depend on the magnitude of the flood itself and the vulnerability of the affected system. Disaster risk communication is a very vital part of Disaster Risk Reduction (DRR) policy-making (Henriksen et al., 2018). Flood risk communication stimulates interest in several activities related to flooding, increases public knowledge about the behavior and attitude of people in crisis situation and emergency responses during flooding, and enhances decision-making process (Kellen et  al., 2012). According to Kellen et al. (2012), risk communication has gradually evolved from communication exclusively between experts to an inclusive participation of risk managers and the public. Traditional methods of sending reports and information (print, broadcast, and media) to municipalities by scientists and engineers have been replaced recently by modern techniques such as model simulations and web-based data information interactive tools (Marin-Ferrer et al., 2017). This has made problems of flood risk management easy to analyze and easier for stakeholders to understand. This enables stakeholders and local community to participate in acquiring more knowledge of risk reduction leading to better interaction between authorities and stakeholders (Henriksen et al., 2018). A study by Henriksen et al. (2018) proposed a structure to reformulate the great perspective of early warning and monitoring frameworks towards a participatory one. The study revealed that when risk communication and

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awareness are enhanced, there is potential for the public to participate in all phases of the DRR cycle. The study also showed that electronic access to hydrological information and boundless demonstration of results also supports integrated and adaptive learning and management of flood risk at a catchment scale. The integration of digital technologies and social media in the Nordic nations can boost electronic access to recorded information, real-time forecast, and climate forecast and predictions. This integration also provides a sound and unified stage for communication and participation of stakeholders in planning, decision-making, and the learning of hazard and risk. Such a web of learning can prompt increment in resilience in the society as well as flood risk assessment across communities. It enables proper analysis of risk areas, optimization of environmental change, adjustment at the catchment scale, and trade-offs in expenses (Henriksen et al., 2018). The extensive and potent use of social media in dissemination of information will aid mitigation and preparedness measures. After the flood disaster of 2000, the new South African disaster management Act 57 of 2002 stipulated some profiles of vulnerability to be taken to ensure effective and appropriate mitigation. Such mitigation includes vulnerability assessment of communities and households to disasters that may occur and increasing the capacity of communities and households to minimize the impact of future disasters (Mgquba, 2002). Key issues were however raised about the implementation of the Act and the capacity of current disaster management institution to undertake such an assessment (Mgquba, 2002). As a follow up, a group of researchers examined the response to flood that occurred between December 2010 and February 2011. This was done to determine the functionality and draw backs of disaster management system in South Africa, it was shown that the response was adequate at the national level, but district municipalities struggled due to shortage of skills and lack of disaster management structures (Zuma et al., 2012). Zuma et al. (2012) observed a weak transfer of information from the district level through to the national level in South Africa, which has a negative impact on flood risk management. In the South African context, managing flash floods should include an understanding of the floods and the physical environment by the society (Fatti & Vogel, 2011), Societal factors such as budget allocation, political agendas, and governance can promote or decrease adaptive measures to flood risks.

9 Models for Predicting Flood Risk Several authors have established theories and methods of flood risks analysis. Rana and Yayant (2016) tried to find the relationship between actual and perceived risk. Lazrus et  al. (2016) looked into how individuals see, comprehend, and envision reacting to flash flood risk and alerts. Some researchers have calculated flood risks using linear regression model (Pandy & Naguyen, 1999, Zhang & Hall, 2004). Regression models however have not been suitable due to abnormality of most of the data (Danso-Amoako et al., 2012), which violates the presumptions of linear

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regression (Meier et al., 2009). The intricate and in addition the non-direct nature of the dependent with the independent variables marks out the unsuitability of regression models. Assessing flood risk hazard is mainly to obtain accurate risk levels, but researchers have faced a lot of difficulties as a result of the nonlinear and multivariable relationship that exists between indices and risk levels (Wang et  al., 2015). The analytical hierarchy process (AHP) has been utilized to remedy the difficulties encountered with obtaining accurate risk levels (Stefanidis & Stathis, 2013; Yang et al., 2013; Fernandez & Lutz, 2010), but there are inconveniences and complexities in applying it practically (Wang et  al., 2015). Using the AHP requires more qualitative than quantitative data, thus making results less objective (Stefanidis & Stathis, 2013). Other methods utilized to assess risk levels of floods include set pair analysis (SPA) (Zou et al., 2013; Guo et al., 2014) and the fuzzy comprehensive evaluation (FCE) (Jiang et  al., 2009; Li, 2013; Lai et  al., 2015). These too have produced mixed results as they are influenced significantly by index weight making the computations complex (Feng & Luo, 2009; Zou et al., 2013). Artificial Neural Network (ANN) has been found to fill the gaps of the other models in that it solves nonlinear and improve computing (Wang et al., 2015). ANN is a factual and refined model in its forecast and classification procedure fit for deriving the patterns and standards of entangled information (Paliwal & Kumar, 2009) or data that is too complex and not easily identifiable by traditional statistics (Lingireddy & Brion, 2005). It is a mathematical model that stimulates biological neural networks (Danso-­ Amoako et al., 2012). Reports from ongoing investigations have shown that ANN offers a promising option for hydrological estimating (Elsafi, 2014) and is the most popular forecasting model among the intelligent methods (Muhamad & Din, 2016). A novel technique for predictions of dam break flow using a regular ANN model indicated that the ANN simulates the dam break stream issue attractively and outperformed the classical numerical results with its simplicity, quickness, and accuracy (Seyedashraf et  al., 2017). The ANN models are useful prediction of the relationship between runoff and rainfall parameters and have been used to handle problems that are complex as compared to other traditional models (Aichouri et al., 2015). They have been effectively utilized in river flow predictions (Raid et  al., 2004, Lallahem et al., 2005), forecast of water quality parameters (Maier & Dandy, 1996), prediction of evaporation (Sudheer et  al., 2002), and prediction of flood disasters. A study carried out in Northern Algeria to predict flow and rainfall series using the ANN methods was found to be more suitable in the prediction of river runoffs than classical regression model (Aichouri et al., 2015). Nkoana (2011) used ANN in the modeling of flood prediction and early warning in Msundusi area in South Africa. The study only focused on precipitation as its input to model the flood predicted. Some researchers have used ANN in combination with other models. It was confirmed that combining methods increases prediction power and precision in recognition compared to using a single machine learning model (Althuwaynee et  al., 2016). ANN back-propagation neural network in combination with Information Diffusion Method (IDM) for flood analysis is used in a disaster situation to map a

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multidimensional disaster space to a one-dimensional disaster space enabling resolution of the level of loss in flood disaster (Li et al., 2013). IDM is used to offset information deficiency by utilizing fuzzy mathematical set value method for samples, thus optimizing the utilization of fuzzy information of samples (Li et  al., 2013). ANN, Maximum Entropy (MaxEnt), and Support Vector Machine (SVM) are used for spatial prediction of landslide susceptibility (Chen et al., 2017). The study proved that the combination could be used in other natural hazards. Chen et al. (2017) used a flood-prone area with 11 landslide controlling factors and concluded that distance from rivers, distance from roads, and elevation were observed to be the best factors in landslide occurrence. Four unique sorts of information driven methodologies: ANN, Adoptive neuro-fuzzy inference systems (ANFIS), Wavelent neural networks (WNN), and hybrid ANFIS with multi-resolution analysis using wavelets (WNF) were found to be highly efficient in forecasting. However, its efficiency is seen to decrease with increasing lead time from 12 to 48 hours (Badrzadeh, 2015). The polynomial neural network technique or group method data handling (GMDH) was proposed for rare events predictions where it was found that GMDH with residual feedback improves forecasting model accuracy (Fong et al., 2012). It was also found that a feed-forward back propagation ANN model using a hyperbolic tangent sigmoid transfer function performed well and accomplished the most accurate rainfall forecasting (Rahman & Alias, 2011). Luo and Wu (2010) developed a rainfall-forecasting model using the projection pursuit regression (PPR) and ANN where the PPR technology is used to select input features for ANN. This technique is done to reduce the data because a large data with noise will increase the ANN model complexity, thereby easily leading to decrease in its forecasting ability (Lou & Wu, 2010). A novel hybrid of Radial Basis Function Neural Network (RBF-NN) model based on Wavelet Support Vector Regression (W-SVMR) developed for rainfall forecasting gave a better alternative for precipitation predictions than other models (Wang & Wu, 2012). Muhamed and Din (2016) in their research showed that data preprocessing is advantageous in producing accurate predictions. This is on the grounds that it enhances the performance of the ANN, which otherwise cannot capture accurately the different characteristics of data pattern and avoids the ambiguity with the quality of prediction results. Banihabab (2016) used ANN as an innovative Black Box Rainfall Runoff (BBRR) for flash flood forecasting. The research engaged the signal delay idea in developing Dynamic Artificial Neural Network (DANN). DANN, which used time delay units by recurrent connections was seen to be computationally stronger than feed-forward artificial neural network. This is due to longer estimated Flood Warning Lead-Time (FWLT) and Expected Lead-Time (ELT), which give time to prepare and mitigate against the negative consequences of the flood (Banihabib, 2016) and is also considered desirable for predictions (Assaad et al., 2005; Chang et al., 2012). Most environmental information is exceedingly mind-boggling making customary measurements usually incapable of comparing connections between variables (Danso-Amoako et  al., 2012). In flood risk assessment, the unpredictability and non-straight nature of the dependent with the free variables makes numerous

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forecast models inadmissible. As such, a model that can catch and learn both complex nondirect and straight relationships from modeling information is required (Danso-Amoako et al., 2012). This is especially so when the underlying physical relationship is not properly understood (Lingireddy & Brion, 2005). This makes the ANN very useful for flood predictions in urban settlements like Alexandra Township.

10 Conclusions This review has revealed that the unpredictability of urban floods poses a very high risk to lives and livelihoods especially in densely populated areas that are unplanned and lacking proper and basic infrastructure. Further, the review has highlighted the inability of the disaster management practitioners to develop sustainable strategies to effectively manage flood disasters in the study area. This study also showed that vulnerability to flood risk is largely connected to poverty and the ability to internalize the concept of risk and how these are socially construed. Historical events in Alexandra township were found to contribute to floods. It was shown that various flood prediction techniques are applied for management of flood risk. The review has highlighted the potential of ANN or its hybrid as a very efficient tool for flood predictions in urban areas as compared to other flood prediction models. The findings from this review are expected to inform preparedness measures or strategies aimed at preventing potential risks from turning into disasters for the individual and the society at large. It has shed light on various ways to mitigate flood risks to acceptable and reasonable dimensions by development of activities to cope with residual risks or adaptation to leftover risks. Promotion of a positive perception of flood risks by local communities can encourage their participation in flood mitigation measures. The study is also expected to inform policy-makers on the advantages of instituting advance planning and ready measures to respond to emergency situations and implement effective measures during or immediately after a flood incidence. The study will hopefully contribute to a better understanding of urban flood disasters, timely and accurate prediction of floods and management in the study area in particular, and other parts of the world where appropriate, using the ANN model.

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Chapter 11

Anthropological Study of a Typical Drought-Prone Village in India: Strategies for Sustainable Rural Habitat Iyer Vijayalaxmi Kasinath and Subham Das

Abstract  Drought-prone villages face the problems of agricultural productivity, lack of alternative livelihood options, predominance of wasteland, inadequate water supply, and absence of physical and sociocultural infrastructure. The study aims to develop a comprehensive policy framework to mitigate the socioeconomic and environmental issues against the vulnerability. The methodology comprises an anthropological study focusing on the dynamics of drought in economy, ecology, and culture of a typical agrarian village of Purulia District in West Bengal, India, from micro to macro level to understand the consequences of drought. The results indicate ecological vulnerability such as extreme climatic condition, generation of wasteland, rocky undulating soil, top soil erosion and human-made contingencies like deforestation, absence of water conservation, over utilization of existing water bodies resulting in water scarcity, ecological degradation, and absence of major agrarian activity. Absence of alternative agroforestry, non-farm livelihood practices, knowledge of drought mitigation, sustainable living practices, inadequate physical infrastructure, and pressing issues in housing with population growth results in degradation of socioeconomic profile, loss of natural resource, and poor living condition, which increases risk of habitat loss with regular drought occurrence. The study can be adapted and improvised according to rural neighborhoods with other significant livelihood practices along with their geographical, climatic vulnerability, livelihood contingencies, and sociocultural resonance. Most researches focus on the geophysical and meteorological characteristics while the anthropo-geographical aspects like local ecology, local patterns of livelihood, and local strategies of drought management are largely overlooked. This research considers all of these aspects and suggests a policy framework toward ensuring the security of food and livelihood in these disaster-prone neighborhoods. The framework can serve as a model to facilitate integrated measure for ecological and economic sustainability against the drought risk with diversified livelihood opportunities, environmental upgrade, augmentation of physical infrastructure, retrofitting strategies of housing for future

I. V. Kasinath (*) · S. Das School of Planning and Architecture, Vijayawada, India e-mail: [email protected] © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_11

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expansion, and optimization of sociocultural space, which will foster sustainable living, cohesive social well-being and resource optimization. Keywords  Anthropology · Drought prone · Habitat framework policy · Landscape & ecology · Rural Housing · Sustainable livelihood · Village upgrade

1 Introduction Drought is the consequence of the geological, topographical, hydrological, meteorological, and climatic factors of an area making it largely unavoidable. It is considered as a natural disaster. Drought not only affects the economic strata and causes the degradation of natural resources but also vividly influences their sociocultural practices. While the irregularity in the monsoon season is at times the cause for the recurrence of drought having an adverse effect on the physical environment, social causes like mismanagement and over exploitation of resources are also responsible for damaging the ecological base. Consequently, the economic imbalance leads to social and cultural disruption. A study report was published, which assessed the resilience of terrestrial ecosystem to drought at the district and state level from 2000 to 2014. The data is illustrated in Fig. 11.1, which shows that only 32% of the total area of India is covered by the resilient districts, and remaining 68% of area were non-resilient districts, with the severely non-resilient districts alone covering nearly 30% of the area. About 65% of the districts with less than 20% forest cover were non-resilient. The report also showed that 42% districts with temperate climate had higher tendency to be resilient than the ones with tropical (32%) and dry (38%) climate (Eslamian & Eslamian, 2017). In West Bengal, drought significantly affects almost 28 lakh people. Four districts in the western part of West Bengal that are severely affected by this hazard are Purulia, West Midnapore, Bankura, and Burdwan with the first two being the worst affected due to hydro-meteorological factors, socioeconomic and anthropogenic factors, and lack of government initiatives. Rural people of this district have developed several indigenous water-­conservation strategies and practices that help them to survive. It also helps to recharge groundwater and conserve water. Pitcher Watering System (Kalsi Sech Padhati), water-­ cooling methods along with natural purification methods (with Nolkhagra, Fitkari), Drip Watering System, Cultivation of Sugarcane using environmental moisture and dew, use of compost pits as water storage tank (Gobar Khal), Sacred Pond, Contour Bunding, usage of plants (Tuber, Palash, Panthapadap, creepy plants) to quench the thirsts like oral rehydration, digging a big hole in the middle of the pond (Happa), Aquifer system (Bhurbhuri), naturally created water storages beside the river, embankment on river, and many more indigenous customs are what they follow with respect to rainfall and social activities. Permaculture is an integrated approach that will diversify the biodiversity and drought land agriculture for future sustainability. The agro/social forestry is an

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N 35° N

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25° N

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Resilience

Resilient Slightly non-resilient Moderately non-resilient Severly non-resilient

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Fig. 11.1  Map showing the resilience of different districts in India (Source: Science chronicle, 23rd October, 2018)

important aspect of the tribal livelihood in the area though it’s not been practiced primarily. Over dependence on the forestry for livestock, fuel, and food still remains as a major concern for depletion of ecological balance. Integrated farming, engineered method of watershed, rainwater harvesting, vermicomposting, and ecological farming along with scientific dry land agricultural practice are largely overlooked, which can play an important role to deal with the drought for sustainable habitat management. Developing an effective strategy to deal with the recurrence of drought has been an integral part of the post-independence Indian planning strategy, although there is hardly any noteworthy achievement. Therefore, a policy framework is needed to be prepared to ensure the security of food and livelihood in these disaster-prone neighborhoods. A study by Mathur and Jayal (1993) found that over the years, drought relief has been contingent with political largesse and the declaration of a region as drought-affected has turned into a prerogative of politicians. Very often, the failures of formulation and implementation of public policy are camouflaged through reiterating the emphasis on “drought as a natural calamity.”

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A study by Mishra (2005) concluded that the problem that lies with the study of famine in the aftermath of a drought is the lopsided focus on the responses of the affected community alone and not that of the other sections of the society, who are not only unaffected but in a way are instrumental in creating the famine. A study by Vasavi (1995) found that the delineation of drought-prone areas lacks a holistic approach because it takes into account only the geophysical characteristics and meteorological factors, whereas anthropo-geographical aspects like local ecology, local patterns of livelihood, and local strategies of drought management are largely overlooked. A study by Jodha (1991) proposed that the rationale behind the coping strategies of the farmers of drought-prone areas should be taken into consideration by the policymakers and planners in order to make the government’s strategies for drought management more effective.

1.1 Sustainable Framework to Assess Rural Vulnerability Against Drought A complex and interrelated range of social, economic, political, and environmental developments are threatening dryland sustainability, both ecologically and economically, and posing challenges to the researchers, policymakers, and most importantly rural land users (Fraser et al., 2011). Anthropological study based on detailed ethnographic description is able to merge the social structure, cultural practices, technology, and environmental context to an overarching logic of survival and cultural persistence at an individual and societal level. Various approaches are used in order to assess vulnerability of an area to extreme natural hazards. While vulnerability assessments do often take into account livelihoods or required assets for a sustainable means of living, the number of frameworks that definitely analyze the livelihood vulnerability to natural hazards are limited (Carr, 2014). The concept of “social-ecological resilience” resonates well with the comprehensive perspective of vulnerability. Although resilience and vulnerability are conceptually related, they are not mirror versions of each other (Gallopin, 2006). Socioecological framework for a disaster-prone area that equip individuals to cope with stress and uncertainty is needed. Culture-specific cognitive processes induce residents to detect signs of environmental change and the models they use to predict future environmental states while they adapt between indigenous coping arrangements and those the state imposes on communities (Hall, 1976). The sustainable livelihoods framework, which consisted of natural, social, financial, physical, and human capitals, is the most relevant to understand vulnerability to drought (Chambers & Vonway, 1992). It comprises the key components that create livelihoods and the contextual factors that externally influence household asset base such as shocks, trends and seasonality (Donhoue & Biggs, 2015; Hahn et al., 2009). Therefore, the sustainable livelihoods framework incorporated the issues of extreme climate exposure and household adaptive capacity. Although this framework offers many useful insights of micro-­ level details of household’s livelihood and considers the wider context in which

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those livelihoods operate, it has a number of limitations. These include its inability to take into account the dynamism in capital assets over time, inadequate consideration of the higher levels of governance, and insufficient attention to the complex ecological consequences of livelihood adaptations (Small, 2007). The present study is projected with the integrated framework assessment to mitigate ecological, livelihood, and sociocultural vulnerability in rural fabric and to alleviate them toward a sustainable future as a meaningful response against drought.

1.2 Comparison of Prior Studies and the Current Study for the Relevance of the Research One of the major problems that develops due to recurring drought in a region and the failure of the government to provide adequate support mechanisms is the crisis of food among the local people because famine, apart from being physical in nature, is also a social phenomenon that involves the inability of a large number of people to establish their common food in the society (Dreze & Sen, 1999). Moreover, it is not the overall levels of food production but rather people’s command over that food, which shapes whether or not food crisis develops (Sen, 1981). When the food crisis emerges, it not only affects the existing livelihood of the people but also alters their economy. The poor are the most vulnerable during such a natural calamity. They cope up with the circumstance by minimizing the quantity and the frequency of food intake and developing the habit of taking previously restricted inferior foodstuffs (Dash and Behura, 2000). However, the continuous shortage of food compels them to lose their productive assets through distress sale, which adversely affects their capacity to resume the normal economic operation even after normalcy is restored (Nadkarni, 2000). Apart from affecting the economy of the people, drought also affects the local ecology and the cultural practices, since these are interrelated to each other. Therefore, the relationship between the social structures, the local economy, ecology, and cultural practices must be understood as a whole, since the pre-drought physical environment and post-drought social milieu are interlinked in a chain process, which converts the “meteorological drought” into “hydrological drought,” the “hydrological drought” into “agricultural drought,” the “agricultural drought” into “food drought” and the “food drought” into “economic drought” (Dubhashi, 1992).

1.3 Aim of the Study This study intends to examine the dynamics of drought on the lives of rural people from three different perspectives: economic, ecological, and socio-cultural practices and to provide a comprehensive framework in all three parameters for holistic upgrade of rural habitat. The underdeveloped economy of the drought-prone rural

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neighborhood is not primarily a techno economic problem, but is rather due to ecological vulnerability and socio-cultural problem and is the product of a low agricultural productivity, lack of alternative livelihood options, predominance of wastelands, inadequate water supply, and absence of physical and socio-cultural infrastructure in a complex setting.

2 Methodology of the Study An anthropological study is done layered with primary survey and documentation from secondary sources for the detail assessment of Dumdumi, a typical drought-­ prone village of Purulia District. The study is done from macro or neighborhood level to micro or plot level to understand the challenges and dynamics of drought on the ecological, physical, and lastly, sociocultural aspects of the rural fabric. In the macrolevel study, it comprises of present demographics, connectivity, and major agrarian livelihood calendar and physical characteristics of the whole neighborhood. The study is further elaborated with the seasonal calendar and poverty index of the whole neighborhood to assess the socioeconomic and sociocultural scenario of the rural habitat, which will indicate the impact of drought on the rural fabric, its people, and their interrelationship and a comparative cluster level assessment to understand the household characters and its relevance in housing, livelihood, and issues of sustainable living practices. Further, a sample cluster of the village is taken for the plot-wise assessment of the tangible and intangible transformation of the dwelling units on the basis of transition of housing spaces due to family growth and qualitative aspects to assess the pressing issues of housing and to develop a comprehensive policy-level framework of the agrarian rural neighborhood. Informed consent is obtained from the villagers during the unstructured interviews for collection of information.

2.1 Study Area The Dumdumi village under the Jabarrah panchayat in the Purulia district of West Bengal was taken as the study area. Purulia district has been severely hit by droughts very often and is ranked 16th and 15th in HDI and GDI index of West Bengal, respectively (Directorate of Census Operations, 2011) 2.1.1 Location and Size District Purulia, with its funnel-like shape, is located in the western-most part of the “Rarh” region of West Bengal. The other three parts of the district are bounded by the state of Jharkhand. The eastern part is bounded by the districts of Barddhaman, Bankura, and Paschim Medinipur.

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2.1.2 Physiography The topographical feature shows gradual descent from the uneven Chhota Nagpur plateau to the plain land of the state in the East. The district of Purulia is divided into three sub-micro regions on the basis of elevation and the nature of topography, namely Damodar- Darkeshwar Upland, Upper Kasai Basin, and BagmundiBundwan Upland. 2.1.3 Climate Purulia has an extreme climate with temperature reaching 7 °C during winter and scorching at 46.5 °C during summer. The southwest monsoon is the principal source of rainfall. Average annual rainfall is 1357 mm, based on last 50 years climatic data. The relative humidity is high during monsoon season, up to 75–85% but is lower during summer, up to 25–35%. It has been observed that medium type of drought occurs once in every 3  years, and severe type of drought occurs once in every 10  years in the district, though the annual rainfall has increased from 798 to 1558 mm in the past decade. 2.1.4 Water Levels and Scarcity The district is identified as drought prone as per official records of the department of irrigation, which also shows that Purulia possesses only 9972 tanks and 4312 wells. Purulia is one of the most backward districts of West Bengal and highly dependent on rural economy. Water scarcity is a regular phenomenon of Purulia. Water development is linked closely with poverty reduction, especially in low-­ income countries that are highly dependent on rural economy. On the other hand, the water table that indicates the water level in area shows that water levels rise up to 7 m bgl during July to October and reduces up to 100 m bgl during rest of the year. From Table  11.1, it can be seen that only 13.78% of the net groundwater reserve is being utilized among the blocks at present, with a huge potential that has been left untouched.

Table 11.1  Classification of ground water utilization in the district Ground water utilization classes Name of the blocks Very low (below 300 Arsha, Bandwan, Manbazar-II, Neturia, Raghunathpur-II, Santuri ham) Low (300–599 ham) Baghmundi, Balarampur, Barabazar, Hura, Jhalda-II, Manbazar-I, Para, Puncha, Raghunathpur-I Low (300–599 ham) Purulia-I and II Source: Roy (2014a, b), Hahn et al. (2009)

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A study by Haldar and Saha (2015) found that water scarcity is a regular threat for the people of Purulia district, which in turn has huge negative impacts on the development of Purulia. The major factors of surface and ground water were investigated and shown in Fig. 11.2. The primary causes of water scarcity in Purulia were also analyzed through the casual chain analysis that can be seen in Figs. 11.3, 11.4, and 11.5, which will help in further planning of water resource management of the district.

Types & Composition of soil

Geological Factors

Permeability & Porosity of soil Structure - of land Surface Depression

Topographical Factors

Vegetative Cover Slope & Gradient Physiological Division Precipitation Temperature

Availability & Potentiality of Groundwater Hydro meteorological Factors

Evapotranspiration Surface Runoff

Soil moisture Sunshine Hours Urbanization Deforestation Grazing Anthropogenic & Socio Economic Factors

Primitive techniques Poverty Population Growth

Fig. 11.2  Major factors of availability and potentiality of surface and ground water. (Source: Haldar & Saha, 2015)

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Wood for Fuel De vegetation/ Deforestation from Lumbering

Loss of Water

Green House Gases

Fodder Demands

Human Influence Declining Precipitation

Climate Change Natural Variability

Fig. 11.3  Water scarcity due to decrease in precipitation – casual chain analysis. (Source: Haldar & Saha, 2015)

Lack of EIA process Energy Demand Inadequate Inter Sectoral Coordination

Increased Evaporation

Deforestation/ De Vegetation from Lumbering

Inadequate Legal/Regulatory Basis

Water Requirements

Insufficient Regional Agreements

Inadequate Technology

Fig. 11.4  Water scarcity due to increase in evaporation – casual chain analysis. (Source: Haldar & Saha, 2015)

Insufficient Knowledge/ Understanding

Increased Grazing

Inadequate Enforcement/ Monitoring

Inadequate Legal/Regulatory

Poverty Lack of Budget Inadequate Institutions

Inadequate Intersectional Coordination

National Regional

Fig. 11.5  Water scarcity due to increased grazing  – casual chain analysis. (Source: Haldar & Saha, 2015)

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2.1.5 Forest Resource The natural forests of the district are primarily of damped and deciduous nature and restricted to northwest part of the district covering Ayodhya hills and Panchet hills of northeast. The tropical dry deciduous forest, which occupies 12% of the total district area, is mostly composed of Sal trees (Shorea robusta). Sal is a sacred tree of tribals, and under its shade their deities are worshipped. Matkam, Mohul, or Mahua (Madhuca indica) are other very important trees. Its hard reddish-brown timber is used for many purposes. It has been observed that the district has a rich assemblage of timber, fiber, and oil yielding and especially medicinal plants. Deforestation has adverse consequences, as minerals and deep humus, previously protected by the vegetation, are rapidly leached exposing poor sand or lateritic clay. The developed forests face great hindrances in growing up again in a changed microclimate and on nutrient exhausted soils. Only stunted trees survive on these depleted soils. Such edaphic influences are most prominent in the dry, gravelly, and rocky surface outcrops, capable of supporting only scrub, grass, ephemeral herbs, and xerophytic plants as they are better adapted to the dry season, unreliable precipitations, and depleted soils. 2.1.6 Economic Status Agriculture is the principal source of livelihood, almost 70% of the working population gets engaged in agriculture either as cultivators or as agricultural laborers, though the per-capita income is considerably low. Most rural households practice subsistence farming under adverse and risky environmental conditions, As a consequence, migration from rural areas to urban areas increase. The natural resource base can be characterized as poorly suited to agriculture due to climatic, water resource, and soil conditions. The Tussar silk weaving industry was also established during the early part of the twentieth century in Raghunathpur and some other places. The Purulia district also has a potential for silk production as the geo-­ climatic condition of the district is favorable for growth and development of Sericulture Industry.

3 Results and Discussion For detailed assessment, a sample village of Purulia district has been chosen for the study, as a typical village of drought occurrence. Figure 11.6 shows the connectivity of Dumdumi village, located in Hura Block under the constituency of Jabarrah Panchayat. It is a small village with 193 household with an average 5 persons per family. It can be seen from Table 11.2 that there are 27% of indigenous Santhal population, who are categorized as Scheduled Tribe, whose livelihoods only revolve around the declining forestry, and almost 80% of the

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Fig. 11.6  Connectivity and location map of the village

total working population are marginal agrarian labor, which indicates the vulnerability of livelihood due to the occurrence of drought every year. The access to the nearest private bus transport is at a distance of 5 km, and the access to train and public road facilities is at a distance of 7–8 km, which renders the place inaccessible during emergencies. Proximity of local markets at Hura (daily), Maguria, and Ladhurka (only Monday) is at a distance of more than 15 km, which restrict the market growth of their agrarian livelihood due to their inaccessibility to local transportation. Table 11.3 shows that presently, involvement of families in silkworm production is increasing in Hura and Kashipur Block, but no trace of this practice was found in the village itself. This broadens the scope of forestry-based livelihood at household level, which can be beneficial for rural folklore. It also has the potential to be a major off season livelihood practice for a yearlong sustainable economy engaging the women folk and it will be an effective measure of providing ecological benefits in the drought prone area. The sowing or agrarian calendar indicates the Khariff (rain fed) along with Rabi season (Post rain), which accounts only for 40% of the year. This causes an unemployment and food risk during the remaining 60% of the year, which results in the locals depending on the agro and horticulture for their food security instead of

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Table 11.2  The present demographics of the Dumdumi Village Description Population Children (0–6) Scheduled caste Scheduled tribe Literacy Total worker Main worker Marginal worker

Total no. 1030 141 19 278 71.09% 514 119 395

Male 500 67 10 130 84.06% 281 119 162

Female 530 74 9 148 58.77% 233 nil 233

Table 11.3  Involvement of farmer facilities in cocoon production in different block level units Block name Hura Kashipur

No. of units in blocks 10 20

No. of families involved 65 145

No. of people associated 325 (Male-140, female-174) 726 (Male-327, female-344)

Table 11.4  Major agrarian livelihood of the village (Sowing calendar) Agro products Rice Maize Pulse

Khariff (rain fed) July–August, July–Nov, Nov–Jan July, Oct–Dec Nil

Mustard Potato

Nil Nil

Khariff (irrigated) Nil Nil Nil Nil Nil

Rabi (Rain fed) Nil Nil 3rd Oct–Nov, Feb–Mar Oct–Nov, Feb–Mar Nov (2nd –4th), Feb–Mar

Rabi (irrigated) Nil Nil Nil Nil Nil

market distribution. From Tables 11.4 and 11.5 it can be seen that forestry-based livelihood practice such as Lac and Sericulture is completely absent in the area. These practices not only induce women engagement but also have tremendous market potential due to the geoclimatic advantages of Purulia. From Table 11.6 it is evident that due to the ecological contingencies like undulated topography, rocky character of the soil, and the unplanned catchment ponds, the rainwater gets wasted. Figure 11.6 shows that the general slope is toward the Eastern side and more toward the South-East, South-West side of the village. Slope is less than 10 m per km, which varies from 751 to 722 ft (Fig. 11.7). Rainfall is moderate in monsoon as it can be seen in Fig. 11.8. The higher summer temperature tends to dry up the moisture resulting in evaporation and higher surface air temperature as seen in Fig. 11.9. The top soil develops cracks during the summer. The rare vegetation cover, topography, and soil characteristics are major reasons behind the low ground water table, which is a primary concern for agrarian livelihood due regular drought occurrence and occasional heat waves.

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Table 11.5  Cultivation of Agrarian and horticulture crops in the village Typology Agro products Lac culture (not practiced) Sericulture (not practiced) Organic farming

Major agrarian products are seen to be cultivated Aman paddy, boro paddy, wheat, maskalai, mustard, potatoes Lacca cultivation Silkworm cultivation regarding WADI project

Sesame, mung bean, maize, pigeon pea, roselle, peanut, millet, fallow mustard, wheat, potato Horticulture products (mainly Khariff season) Typology Major products are seen to be cultivated Fruit Mango, guava, jackfruit, banana, and so forth Plantation crop Coconut Flower Gladula, rose, tuberose, marigold, palash Spices Red chili, ginger, garlic, onion. Vegetable Brinjal, cucurbit, tomato, cabbage, cauliflower, ladies finger, okra, and so forth Medicinal crop Nil Table 11.6  Physical aspects of the village Soil and topography Agro-ecological sub region Agro-climatic zone Agro-climatic zone-

Rocky, undulated Eastern plateau, sub-tropical climate (hot-arid summer and moderate winter) Lower Gangetic plain (source: Planning Commission) Red, laterite soil zone (WB-5)

Fig. 11.7  The topographical gradient is graded in the map

The seasonal calendar is a reflection of the socioeconomic and sociocultural scenario of the rural habitat, which indicates the impact of drought on the rural fabric, its people, and their interrelationship. From Tables 11.7 and 11.8 it can be assessed that ecological contingency, nonavailability of water, mono-cropping, and primitive techniques result in very low or no productivity. This can further lead to unemployment and food scarcity, which are

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500 400 300 200 100

0

Jan

Feb

Mar

Apr

May

June

July

Aug

Sep

Oct

Nov

Dec

Fig. 11.8  Comparative Rainfall Index of Purulia with West Bengal. (Source: Meteorological Department, Govt. of India) 40 35 30 25 20 15 10 5 0

Jan

Feb

Mar

Apr

May

June

July

Aug

Sep

Oct

Nov

Dec

Fig. 11.9  Comparative temperature index of Purulia with West Bengal. (Source: Meteorological Department, Govt. of India)

the two primary concerns of an agrarian livelihood. Also, horticulture, agro allied, agroforestry sectors are either completely ignored or unknown to the agrarian population and non-farming practices are almost obsolete. Apart from rare small business, many people are unemployed, which increases the crisis of livelihood and the likelihood of forced migration in future. Though having a rich cultural index, drought has impacted the lives of the residents of the Purulia village, which is correlated with economy and infrastructure. The major festivals are celebrated on the occurrence of first cultivation of paddy, which is sometimes absent due to the drought, resulting in the loss of traditional practices and cultural disintegration. Therefore, it becomes necessary to revive and reestablish their cultural integrity. With the increase in population, the dependency on natural resources will increase. Thus, it is important to adapt the integrated framework for future risk mitigation. The following table is a comparative assessment of different clusters present in the village fabric marked in Fig. 11.10. From Table 11.9 it can be seen that major sustainable living practices are missing, which should be incorporated into the lifestyle as a cluster and plot level

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Table 11.7  Seasonal calendar Parameters Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec Agriculture (Khariff) Paddy (Aman) ✗ ✓ ✓ ✓ ✓ ✗ ✗ ✗ ✓ ✓ ✓ ✓ Maize ✗ ✗ ✗ ✗ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Pulse ✗ ✗ ✗ ✗ ✓ ✓ ✓ ✓ ✗ ✗ ✗ ✓ Oil-seed ✗ ✗ ✗ ✗ ✗ ✓ ✓ ✓ ✓ ✗ ✗ ✓ Animal husbandry Livestock ✗ ✗ ✓ ✓ ✓ ✗ ✗ ✗ ✓ ✓ ✓ ✓ Poultry farming ✓ ✗ ✗ ✓ ✓ ✓ ✓ ✗ ✓ ✓ ✓ ✓ Duck farming ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Pisciculture ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✓ ✓ (rainfed) Horticulture Vegetables ✗ ✗ ✓ ✓ ✓ ✗ ✗ ✗ ✓ ✓ ✓ ✓ Fruit ✗ ✓ ✓ ✗ ✗ ✓ ✓ ✓ ✓ ✗ ✗ ✓ Spices ✗ ✗ ✗ ✗ ✗ ✓ ✓ ✓ ✓ ✓ ✗ ✓ Flower ✗ ✓ ✓ ✓ ✓ ✓ ✓ ✗ ✓ ✓ ✓ ✓ Medicinal plants ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ Agroforestry Agro food ✗ ✗ ✗ ✗ ✗ ✓ ✓ ✓ ✓ ✓ ✗ ✓ Fungi-culture ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✓ ✓ ✓ ✓ ✓ Food fuel ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Craftsmanship ✗ ✗ ✗ ✗ ✓ ✓ ✓ ✗ ✗ ✗ ✗ ✗ Cottage industry ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ Sericulture ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ Lac culture ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✓ ✓ ✗ Non-farm activities Blacksmith ✓ ✓ ✓ ✗ ✓ ✓ ✓ ✗ ✗ ✗ ✗ ✗ Local business ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Daily wage ✗ ✗ ✗ ✓ ✓ ✗ ✗ ✗ ✓ ✓ ✓ ✓ labor Cultural index ✗ ✓ ✓ ✓ ✗ ✗ ✗ ✓ ✗ ✓ ✓ ✓ Festivals 2nd Jan: Makar Sankranti, Tushu parab; 15th Jan: Bhassing, Pooja-o parab; (indigenous 19-20th Jan: Akhan Jatra; Mid-March-May: Choli Parab, Charak Puja, cultural index) Chaitra Sankranti, Baha (spring fest), Bheja Bandha; 15-16th Aug: Manasa Puja, Karam Parab; ; Sep: Bhadu Festival; Nov: Badhna Parab, 15th Nov-15th Dec-Jathel Utsav

intervention by taking principles from other progressive habitat. Backyard farming with water conservation may be an effective measure mitigating food risk. Apart from agrarian, other livelihood option should be adopted during the drought occurrence. From Figs. 11.11, 11.12, 11.13, 11.14, and 11.15 it can be assessed that housing is the most important aspect for the habitat, which will grow. Based on the

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Table 11.8  Poverty status Index Component Improved/ increased Not improved Remains same Issues and assessments

Component Improved/ increased Not improved Remains same Issues and assessments

Occupation ✗

Income Housing ✗ ✗

Literacy ✗

✗

✓

✗

✓

✓

✗

✓

✗

Emphasis should be on year-round integrated agriculture, non-farm activities, agroforestry toward effective economic sustainability. Dependency on forestry ✓

Consideration of IAQ, physical infrastructure, future extension Family size ✗

Community-based learning system for womenfolk, elderly

✗

✓

✗

✗

✗

✓

Integrated livelihood strategy to mitigate drought risk against ecological contingency to have a sustainable economic well-being

Informal education, healthcare, housing plugin

Economic well-being

Clothing ✗

survey, it can be seen that a proper framework is needed for future expansion and retrofitting of the dwelling units with improved techniques, materials, indoor air quality along with plugging of livelihood, and household space to mitigate the pressing issues in accordance to family growth, separation, and spatial requirements (Fig. 11.16). Table 11.10 is a plot-wise comparative assessment of tangible and intangible transformation of Mudi Para (taken as a sample cluster), which is illustrated in Figs. 11.17 and 11.18. From Table  11.10 it can be assessed that climate has not been considered for spatial quality in dwelling unit. Mutual shading and utilization of spaces is a great finding in this organic settlement. However, absence of window has diminished the day lighting and indoor environmental quality as seen in Fig.  11.16, though this proved appropriate in cooling down temperature resulting in indoor thermal comfort, but improved fenestration techniques, opening size, and location with cost effective local materials can serve the purpose. Due to family growth and separation of household, encroachment in the courtyard is predominant. Due to structural inability and need for vertical expansion, the courtyard is very small. Maintenance and durability are compromised with the low-income profile. Absence of rain-water harvesting and solid-waste management system was evident. Solid-waste management is necessary, which produces manure from the daily waste, and the generated renewable energy will ensure future sustainability.

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Fig. 11.10  Land use map of the village showing natural and built morphology

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Table 11.9  Cluster level analysis of the village Mudi Para (Tribal) 20

Mahato Para (SC,ST) 12

Pathar Para (tribal) 09

Sardar Para Ansari Majhi Para (tribal) Para 23 11 04

51

27

14

62

28

11

262

144

57

380

170

75

Dense, linear, roadside High Seen

Medium, sporadic

Sparse, sporadic

Dense, linear

Medium, linear

Medium, sporadic

User density Built-up addition Future Not encroachment possible Livelihood practices Agriculture ✗ Livestock ✓ Poultry farming ✗ Agrarian ✓ marginal, non-worker Daily wage ✓ labor Agro-forestry ✗ Others practices Small business

High Seen

High Seen

High Seen

High Not seen

High Seen

Not possible

Not possible

Not possible

Not possible

Possible

✓ ✓ ✓ ✓

✗

✗

✗

✓

✓ ✓ ✓ ✓

✓ ✓ ✓

✓ ✓ ✓

✓

✓

✗

✓

✓

✓ Small household practices

✓ Fungi culture, blacksmith agro-food

✗ Small household practices

✓ Duck-­ farm, fishery

Economic Very poor status Sustainable living practices Rain water ✗ harvesting Waste ✗ management Vegetable In few garden cases

Poor

Very poor

✗ Duck-­ farm, fishery, Agro-food Poor

Very poor

Very poor

✗

✗

✗

✗

✗

✗

✗

✗

✗

✗

Rare

Rare

Yes

In few cases Yes

Description Total no. of dwelling units Total no. of household Total population Cluster density

✓ ✗

Predominance of wasteland is a concern, which covers almost 60% of total village (Fig. 11.19). Having degraded barren lands for no purpose with lack of vegetation cover, topography, soil characteristics, permeability, rainfall, and land cover management results in erosion of top soil cover (Fig. 11.20).

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Cluster wise Population projection Ansari para Sardar para Majhi Para Pathar para Mahato para Mudipara 0

100

200 2031

300 400 2021 2011

500

600

Fig. 11.11  Approximate population projection of different cluster (considering decadal growth rate 20.8% as a constant for population projection)

Fig. 11.12  Small courtyard due to liner encroachment

So reclamation of the wasteland along with soil conservation and landscape strategy is required to improve the drought land ecology and livelihood concerns of the villagers. Over utilization of water bodies and absence of rain water harvesting along with all the ecological contingency result in water scarcity and drought. Absence of scientific approach for new watershed and water conservation leads to pressing livelihood issues. The landscape existence along the built fabric and roadside is less, and backyard farming is abandoned as can be seen in Fig. 11.19. Due to water scarcity, native forestry is very sporadic, which creates a huge imbalance to the habitat. With population growth and economic degradation the over dependency on the forestry leads to a vulnerable ecosystem.

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Fig. 11.13  Courtyard living is a center of rural lifestyle

Fig. 11.14  Livestock space are integral to the housing

4 Framework Policy for Sustainable Rural Habitat and Conclusion Habitat is a concept that comprises physio-biotic and sociocultural component, which integrate the people (species) and place (nature). To strengthen the balance of a typical drought-prone rural neighborhood, a sustainable habitat policy should be a framework to:

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Fig. 11.15  Existence of roadside vegetation is rare

Fig. 11.16  Pictures showing high-density living space, courtyard after expansion, and visibility in dark indoor spaces

(i) Integrate and strengthen the rural landscape into livelihood to mitigate drought and environmental issues and to upgrade the whole neighborhood for a sustainable future. (ii) Include measured habitat interventions with livelihood opportunities. Investment in rural infrastructure is essential to trigger socioeconomic upgrade. Habitat planning in the village needs to include concerns of livelihood creation, physical infrastructure, working capital, and market linkages. Rural infrastructure development that supports economic activity such as work center must be planned and made available. Climatic variations, including droughts affect all aspects of human life, including health, homes, livelihoods, and cultures. Threats of this magnitude affect the stability and a sense of cultural identity, well-being, and security. Drought, being a result of climate, affects the livelihood of the people, which impacts issues of housing and

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Table 11.10  Plot-wise housing transformation analysis and livelihood assessment of Mudi Para Description Plot 1 (type- I)

Plot-2 (type- I)

Total population Avg. family size No. of household Kitchen

7 to 12

Granary Livestock Livelihood practices Outdoor living Ground coverage Toilet Ventilation quality Daylight provision RWH SWM Structural condition Description

Plot 5 (type- I)

Plot 6 Plot 7 Plot 8 (type- III) (type-­III) (type- II)

4 to 9

Plot 3 Plot 4 (type- III) (typeIII) 3 to 5 5 to 8

4 to 6

5 to 7

2 to 3

6 to 9

3.5 to 4

2 to 4.5

1.5 to 2.5 2.5 to 4

2 to 3

2.5–3.5

2 to 3

3 to 4.5

2 to 3

2 to 3

2 to 3

2 to 3

2 to 3

2 to 3

2 to 3

2 to 3

Separated (2–3) Common Separated Nil

Separated (1–2) Separated Separated Dhekishal

Separated (1–2) Common Separated Nil

Common Separated (1–2) Common Separated Common Common Nil Nil

Separated (1–2) Common Common Nil

Common Separated (1–2) Common Separated Nil Common Nil Poultry

Less space Less space Less space 29% to 41% to 35% to 45% 42% 48% Nil to 1 1 Nil to 1 Poor Poor Poor

Less space 38% to 50% Nil to 1 Poor

Less space Less space Less space 26% to 45% to Same 62% 67% Nil to 1 Nil to 1 Nil Poor Poor Moderate

Poor

Poor

Poor

Poor

Nil Nil Nil Nil Nil Nil Moderate Moderate Poor

Nil Nil Poor

Nil Nil Nil Nil Nil Nil Nil Nil Moderate Moderate Moderate Poor

Poor

Plot 9 Plot 10 Plot 11 Plot 12 (type- II) (type- III) (type- II) (typeIII) 4–7 4 to 7 7 to 9 5 to 7

Total population Avg. family 2–3.5 size No. of 2 to 3 household

Poor

Less space 58% to 71% Nil to 1 Poor

Moderate Poor

Plot 13 (type- I)

Plot 14 Plot 15 (type- II) (type- III)

16 to 22

3 to 5

3 to 4

2 to 3.5

3.5 to 4.5 2.5 to 3.5 8 to 5.5

1.5 to 2.5 3 to 2

2 to 3

2 to 3

2 to 3

2 to 3

2 to 4

1 to 3

ethno-cultural practices. Archaeologists credit increased productivity that came with agriculture as the foundation of civilization, allowing humans to live in larger settlements, and develop social hierarchies (Sahlin, 2006). The pressure due to drought is felt by all the villagers, so gradually the ethno-cultural practices get diluted with time. Hence, the environmental issue is the strongest link to economic, social, and cultural degradation. So environmental adversity should be focused primarily in the sustainable framework to mitigate the issues and to provide a holistic and integrated solution for the habitat in order to strengthen and revive the livelihood, housing, and other sociocultural factors.

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Fig. 11.17  Previous Scenario of Mudi para (taken as a sample cluster for assessment)

Fig. 11.18  Present scenario of Mudi para (taken as a sample cluster for assessment)

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Fig. 11.19  Degraded landscape morphology of the rural fabric

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Fig. 11.20  Classification of wasteland

Fig. 11.21  Illustration of the Geddesian Triad theory

4.1 Theoretical Underpinning Theory of Triad (work–place–folk) by Sir Patrick Geddes comprises three components of a habitat, which is illustrated in Fig. 11.21. “The environment acts, through function, upon the organism and conversely the organism acts through the function upon the environment”. Based on the theory of human settlements by C.A. Doxiadis, the five elements of human settlement (man, shell, society, nature, and network) are interlinked at neighborhood and family level and are to be considered for framework policy of rural habitat (Fig. 11.22).

4.2 Sustainable Framework Policy for Drought-Prone Rural Habitat 4.2.1 Wasteland Reclamation It is done by the removal of hard cover of “Latosol,” and the “tanr” can be reclaimed. This becomes more workable and suitable for plantation as seen in Fig. 11.23.

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Fig. 11.22  Illustration of Doxiadis theory of Ekistics and it’s inter relationship

Fig. 11.23  Reclamation of wasteland

4.2.2 Soil Conservation Lack of vegetation cover, slope, soil characteristics, permeability, rainfall, and land cover management results in erosion. So plantation of grass and shrubs, afforestation, and gully binding must be carried out to control soil erosion as seen in Fig. 11.24.

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Fig. 11.24  Measures to protect the top soil erosion

Fig. 11.25  Adaptive measures and engineering methods for water conservation

4.2.3 Water Conservation Engineering methods of location, slope, grading, and contouring are required for macro, mini watershed, construction of large percolation tanks/wells, and reservoir in cluster at neighborhood level. Integrated farming, as seen in Fig. 11.25 must be practiced. This will result in water conservation and allow more seepage of ground water. Integrated farming may reduce ground water resources, and the surface storage may be utilized for immediate and small irrigation purposes during the normal times. 4.2.4 Afforestation in Degraded Forest Land Massive afforestation program should be undertaken with native, indigenous trees such as Sal (Shorea robusta), Mahua (Madhuca longifolis), Palash (Butea ­monosperma), Arjun (Terminalia arjuna), Kusum (Schleichera oleosa), and so forth.

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4.2.5 Preservation and Plantation of Indigenous Plants of Wasteland The following trees must be used extensively for afforestation: 1. Medicinal value 2. Planation value 3. Host plant for Lac insect 4. Host plant for silkworm 5. Fiber producing Plant 6. Social/Agroforestry plant 7. Timber-yielding tree 8. Fuel wood producing 9. Soil binder plant

Neem, Dhatura, Mocha Plant Date Palm, Amla, and so forth Palash Arjun, Sal, Akashmoni Sisal, Sabai Grass Arjun, Akashmoni Babul, Neem, Banyan Dhakti Bush etc. Lantana

4.2.6 Principles of Permaculture The principles illustrated in Fig. 11.26 can be a miracle for this rural framework as it stands on care for Earth and care for people, which direct toward local ecological and socioeconomical sustainability. 4.2.7 Social Forestry Practicing social forestry can be beneficial in drought-prone livelihood and ecology as demonstrated through Fig. 11.27. 4.2.8 Sustainable Strategies Sustainable measures for dryland agriculture with agroforestry should be incorporated as illustrated in Fig. 11.28. Other strategies include the practice of vermicomposting and solid-waste management along with clean and renewable energy generation at cluster and neighborhood levels, reinforcing a “habitat” paradigm over a focus on “housing” to include

Fig. 11.26  Casual chain analysis of permaculture practices and its role for habitat sustainability

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Fig. 11.27  Social forestry and its role for ecological and livelihood sustainability

Fig. 11.28  Adaptive measures for sustainable agriculture focusing on agroorestry. (Source: fao.org)

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water and sanitation facilities, framework for future growth with alternative building material, improved techniques for thermal comfort, and satisfactory indoor environment quality while protecting the courtyard as major activity space from encroachment and incorporation of livelihood spaces if absent. 4.2.9 Livelihood Strategies Livelihood strategies should be adopted all yearlong to integrate sustainable economy as illustrated from Figs. 11.29, 11.30, and 11.31.

Agriculture

Aquacultur

Integrated agro cum Pisciculture

Duck

Integrated duck cum fish farming

Fig. 11.29  Integrated farming practice

Agro forestry based livelihood practices

p Sericulture practice (Moriculture-Cultivation from seeds, Root-grafting, Stem –grafting, f leaf picking, branch cutting, top shoot harvesting, silkworm rearing, silk reeling and market distribution)

Fungi g culture p practice (Cultivation, production, processing of mushroom, packaging and market distribution)

Shellac Production (Stic lac cultivation, production of shellac products and market distribution)

Horticulture (Cultivation of fruits, exotic vegetables, ethno botanic species, from commercial harvest to market distribution)

Fig. 11.30  Sustainable agroforestry-based practices with its market-based framework 3. Agro g based livelihood practices p

Crafts and artefacts based practices (Cultivation, processing of raw materials, production of crafts from bamboo and Sabai grass and market distribution)

Agro food production (Household industry) (Processing of puffed rice, pickle, masalas and ketchup, packaging and market distribution)

Livestock, poultry farming (Processing of dairy products, poultry products, packaging and distribution)

Fig. 11.31  Agro-based micro cottages industry with its market-based framework

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Integrated work-cum-community center along with a cooperative society and microfinance facility is required to serve the economic activities also informal education, skill development, and sociocultural practices at the neighborhood level.

5 Conclusions The agriculture sector is most vulnerable to the impending environmental threats and impacts of climate change. Agrarian families whose livelihoods depend on natural resources frequently cope with the vagaries of weather and historically have to adapt to the climatic risks. From this study, it can be concluded that drought has vividly influenced the economy, ecology, and sociocultural practices of the village. The interrelationship between the natural and anthropogenic factors is primarily responsible for it. It is also expected that some arid and semi-arid regions encounter reduced rainfall amounts and consequently experience more prolonged and severe droughts. Reducing the livelihood vulnerability of farm families and enhancing the resilience need a comprehensive assessment of livelihood vulnerability in the face of climate variability (e.g., drought) and change. An improved ability to predict and characterize exposure is necessary, but not sufficient, to develop realistic estimates of drought impacts. A systematic way of addressing sensitivity of specific socioecological systems that match exposure estimates in space and timescales is also required. While the current extensive drought scenario has caused negative impacts on the village, findings revealed that residents’ livelihood vulnerability is not the same in different drought-affected areas. The consequences of moderate and medium-duration drought and also moderate/ severe and long-term droughts were potentially dramatic and made farm families more vulnerable. So to mitigate the risk of drought and its impact on the lives of villagers, the habitat policy will be an integrated framework based on the primary survey and secondary research focusing on sustainable livelihood practices and ecological upgrade of the rural fabric. From the principles of permaculture, the corresponding seven layers may be used as a tool for sustainable ecosystem that directly benefits humans by creating a vibrant, healthy, and productive community through reconnecting them to the nature in regenerative ways. Agro and social forestry-based livelihood practices will increase women engagement and will prove to be an alternative source of income while enhancing the biodiversity and drought land ecosystem and ensuring natural resource optimization. Technical assistance should be provided to people through various training and capacity building programs for coping with the drought situation based on their cultural mechanisms. In the social forestry program, plantation of drought resistant, fruit-bearing, and indigenous plants based on the need of the local people will help the program. So decision-making in this regard should take place with the consultation of the local people along with the scientific examination of the soil.

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This research framework is based on an agrarian village of Purulia, West Bengal, India. It can be optimized as a model framework for a sustainable and resilient habitat program in drought-prone rural areas, which can be improvised according to varied livelihood with specific context to geographical, climatic vulnerability, and cultural resonance. With this approach, the ecological balance will be restored resulting in a resilient future. Acknowledgments  The authors thank Dr. Souvanic Roy of Indian Institute of Engineering Science Technology, Shibpur, for his constant support.

References Behura, N. K. (2000). Crisis management: Lessons from the past: A case study of drought situation. Man in India, 80(1&2), 75–88. Carr, E. D. (2014). From description to explanation: using the livelihoods as intimate government (LIG) approach. Applied Geography, 52, 110–122. Chambers, R., & Vonway, G. (1992). Sustainable rural livelihoods: Practical concepts for the 21st century. Institute of Development Studies. Directorate of Census Operations. (2011). District census handbook-Purulia: Village and town directory, Part XII-A. Ministry of Home Affairs. Donohue, C., & Biggs, E. (2015). Monitoring socio-environmental change for sustainable development: Developing a multidimensional livelihoods index (MLI). Applied Geography, 62, 391–403. Dreze, J., & Sen, A. (1999). Hunger and public action. Oxford University Press. Dubhashi, P. R. (1992). Drought and development. Economic and Political Weekly, 27(13), A27A36. Eslamian, S., & Eslamian, F. (2017). Handbook of drought and water scarcity, Vol. 3: Management of drought and water scarcity. Taylor and Francis, CRC Group, 645p. Fraser, E., Dougill, A., Hubacek, K., Quinn, C., Sendzimir, J., & Termansen, M. (2011). Assessing vulnerability to climate change in dry land livelihood systems: Conceptual challenges and interdisciplinary solutions. Ecology and Society, 16(3), 3. Resilience Alliance Inc. Gallopin, C. (2006). Linkages between vulnerability, resilience, and adaptive capacity. Global Environmental Change, 16, 293–303. Hahn, M.  B., Riederer, A.  M., & Foster, S.  O. (2009). The livelihood vulnerability index: A pragmatic approach to assessing risks from climate variability and changes- A case study in Mozambique. Global Environmental Change, 19, 74–88. Haldar, S., & Saha, P. (2015). Identifying the causes of water scarcity in Purulia, West Bengal, India – A geographical perspective. IOSR Journal of Environmental Science, Toxicology and Food Technology, 9(8, Ver. I), 41–51. Hall, A. (1976). Drought and irrigation in north-east Brazil. University of Glasgow. Jodha, N.  S. (1991). Drought management: Farmers’ strategies and their policy implications. Economic and Political Weekly, 26(39), A98–A104. Mathur, J. S., & Jayal, N. (1993). Drought policy and politics: The need for a long-term perspective. Sage. Mishra, A. (2005). Local perceptions of famine: Study of a village in Orissa. Economic and Political Weekly, 40(6), 572–578. Nadkarni, M. V. (2000). Poverty, environment, development: A many patterned nexus. Economic and Political Weekly, 25(14), 1184–1190. Roy, A. (2014a). Availability, scarcity and potentiality of ground water resources of Purulia District, West Bengal: An appraisal. International Journal of Scientific Footprints, 2(1), 78–93.

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Roy, A. (2014b). Deforestation in social context: A case study of Purulia district in West Bengal, India. Journal of Arts Science & Commerce, 5(1), 114–120. Sahlin, M. (2006). The original affluent society. In J. Solway (Ed.), The politics of egalitarianism: Theory and practice (pp. 79–98). Berghahn Books. Sen, A. (1981). Poverty and famines: An essay on entitlement and deprivation. Oxford Clarendon Press. Small, L.  A. (2007). The sustainable rural livelihoods approach: A critical review. Canadian Journal of Development Studies, 28, 27–38. Vasavi, A.  R. (1995). Bureaucratization of drought condition: A critique of policies. Lokayan Bulletin, 12(3).

Chapter 12

Risk Management of Extreme Precipitation in Mexico: Building Resilience Evelia Rivera-Arriaga, Rodolfo Silva, Cesia J. Cruz-Ramírez, Isaac Azuz-­ Adeath, Beatriz E. Vega-Serratos, and Gregorio Posada Vanegas

Abstract  The climate system tends to respond to changes in a gradual way until it crosses some threshold; thereafter, any change defined as abrupt is one where the response is much greater than the change in the perturbing force. Improving resilience to the extreme events caused by climate change has become an important issue, and links between factors such as demographics, climate change effects, water and food availability and supply, governability and violence, risk and vulnerability, economic and ecological crises, and health and sanitation have gained importance in the global context. Coastal governance involves economic, social, environmental, institutional, cultural, traditional, and political entities, and it can be viewed as a combination of shared government, in which society also assumes the legitimacy of the process and the recognition of the decisions made. The difference of considering governance for climate change-related effects beyond thinking about governance for anything else is the resilience for long-term, uncertain futures. According to the IPCC (2014), resilience is the ability of a system to anticipate, absorb, and adapt to climate-related shocks and stresses and to respond in ways that preserve, restore, or improve its essential functions, structures, and identity. This chapter is focused on improving the resilience of the 11,600  km of the Mexican coastline to abrupt climate changes. This study identifies the areas most at risk, based on an evaluation of the hazards they face and their degree of vulnerability. The elevations, geology, geomorphology and displacement of the coastline, significant wave heights, tidal range, the level of natural protection, hazards induced from extreme waves and storm surge, and rainfall were included in the risk analysis. Socioeconomic characteristics, such as total population, population density, GDP E. Rivera-Arriaga (*) · B. E. Vega-Serratos · G. P. Vanegas Institute EPOMEX, University of Campeche, Campeche, Mexico e-mail: [email protected] R. Silva · C. J. Cruz-Ramírez Instituto de Ingeniería, National University of Mexico UNAM, Mexico City, Mexico I. Azuz-Adeath Centro de Enseñanza Técnica y Superior University, CETYS University, Mexicali, Mexico © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_12

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per capita, economic participation rate, human development index, marginalization index, poverty, economic units (tourism), total gross production, gross value added (tourism), protected areas, and productive sectors were used to evaluate social vulnerability. Keyword  Resilience · Extreme rain · Governance · Risk management · Vulnerability index

1 Introduction Abrupt climate change is defined by the Intergovernmental Panel on Climate Change as, “The nonlinearity of the climate system may lead to abrupt climate change, sometimes called rapid climate change, abrupt events, or even surprises. The term abrupt often refers to time scales faster than the typical time scale of the responsible forcing. However, not all abrupt climate changes need be externally forced. Some changes may be truly unexpected, resulting from a strong, rapidly changing forcing of a nonlinear system” (IPCC, 2012). A mechanism that might lead to abrupt climate change would have the following characteristics: a trigger or, alternatively, a chaotic perturbation, causing the crossing of a threshold (something that initiates the event); an amplifier and globalizer to intensify and spread the influence of small or local changes; and a source of persistence, allowing the altered climate state to last for periods as long as centuries or even millennia (NRC, 2002). The climate system tends to respond to changes in a gradual way until it crosses some threshold: thereafter, any change that is defined as abrupt is one where the change in the response is much larger than the change in the forcing. The changes at the threshold are therefore abrupt relative to the changes that occur before or after the threshold and can lead to a transition to a new state. The spatial scales for these changes can range from global to local. In this definition, the magnitude of the forcing and response are important. In addition to the magnitude, the timescale being considered is also important. Because of the subjective nature of the definitions of threshold and abrupt, there have been efforts to develop quantitative measures to identify these points in a time series of a given variable (Karl et al., 2000; Lanzante, 1996; Seidel & Lanzante, 2004; Tomé & Miranda, 2004). The most common way to identify thresholds and abrupt changes is by linearly de-trending the input time series and looking for large deviations from the trend line (IPCC-AR4, 2007); however, other techniques need to be used according with the data temporal extent, periodicity of measurement, and practical interest. To emphasize the importance of these factors, the use of proxy records in paleoclimate studies can be analyzed. The end of Pleistocene associated with the last glaciation opens the Holocene period with a sudden increase (in a geological time scale) of the global temperatures; some events have been defined as abrupt climate

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changes in this scale, such as the Older and Younger Dryas (14.5–11.5 thousand years before the present), or The Little Ice Age (1300–1850 of the current age). Various theories have been proposed to explain the mechanism that triggered such large-scale events from changes in the thermohaline circulation pattern due to flood of freshwater, the impact of a comet, or as an integral part of the deglacial process that produce the last termination at global scale (Stocker, 1999; Qiang et al., 2004; Dahl et al., 2005; Broecker et al., 2010). Nevertheless, if we look at the time series in this timescale, other potential abrupt climate changes could be identified (Fig. 12.1), and the concept of scale of analysis appear as a critical issue in the definition of abrupt climate change for practical purposes in the context of human lifetime. Looking for practical and operative definitions, a series of recent proposals are: abrupt climate change, extreme weather/climate events, irreversibility, tipping point, compound events and cascading impacts have been established by Collins et al. (2019). Regarding “abrupt climate change” the authors mentioned use the definition: A large-scale change in the climate system that takes place over a few decades or less, persists (or is anticipated to persist) for at least a few decades, and causes substantial disruptions in human and natural systems. This definition is that adopted in this chapter. Building resilience to abrupt climate changes has become a global and national security issue. The linkages among demographic dynamics, climate change effects, water and food availability and supply, governability and violence, risk and vulnerability, economic and ecological crisis, health, and sanitation between other factors have begun to gain importance in the global context (Eslamian et al., 2019; Galgano, 2019; Kaufmann et al., 2010). This chapter is focused on the capabilities of Mexico to build resilience to abrupt climate changes. Mexico is subject to the atmospheric and oceanic influences and processes of the Pacific Ocean and the Gulf of California in the west and the Gulf of Mexico and the Caribbean Sea in the east. The country has an area of 1.9 million square kilometers (msk) and a maritime area of 3.2 msk. The 11,588  km of coastal zone is shared between 17 coastal states. One-hundred sixty municipalities have direct access to the sea, with a total population of 58 million, registered in 2020. The geographical location of Mexico makes it especially vulnerable to tropical systems originating in the Atlantic and the Pacific oceans; its latitudinal extension produces gradients of climatic variables and biodiversity in a north-south direction; large peninsulas on each coast border two extensive, semi-closed seas with characteristic dynamic processes (e.g., wind and tide circulation, thermohaline circulation, and upwelling). The El Lazo current in the east and the California Current in the west dominate the dynamics and productivity of the Mexican oceans. Various regions of the country are affected by global oscillations or modes of climate variability, acting in several time and space scales in the atmosphere-ocean-land system, such as the El Niño-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the North Atlantic Oscillation (NAO), or the Atlantic Multidecadal Oscillation (AMO).

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Fig. 12.1  Greenland surface air temperature proxy records. In part (a), the measured values of the last 11,550  years, with two linear trends superimposed, excluding the period −6000 to −10,000 years, which is the period with the highest absolute interdecadal differences greater than 0.1 °C, marked in part (b) with a square. Several major events are located in A: the late glacial maximum, the old dryas and the younger dryas. (Data source: Kobashi et al., 2017 from National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce. https:// www.ncdc.noaa.gov/paleo-­search/study/22057)

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To identify abrupt climate changes, long-term data availability with a wide spatial cover is vital, as well as the use of appropriate statistical methods to deal with extreme events, or episodic phenomena that cross thresholds difficult to establish in physical terms, due to the nonlinear and chaotic character of the climate system. There are several methodologies to analyze abrupt climate change (IPCC, 2012; Mudelsee, 2010; Vu et al., 2019). However, to extend the time series length, several investigations use climate model projections to substitute for the lack of long-term data. In the following paragraph, some examples are presented that try to identify abrupt climate changes, based on measured data of the climatic variables most extensively documented in Mexico, in this case, maximum and minimum surface atmospheric temperature and accumulated rain. Using annual values of the mean minimum temperature recorded in the coastal states of each Mexican coast, an abrupt change in the temperature’s linear trend slope can be observed during the year 2000 (Fig. 12.2). For each coast, significant differences (α  =  0.05) in the slope were observed for the period 1980–2000 and 2000–2019. This analysis was done without any previous treatment in the time series. Another method regularly used to identify abrupt climate change is the residual analysis of the linearly detrended time series of climate variables. Using the annual value of spatial averages (by coastal state) maximum surface atmospheric temperatures, and after the linear detrending process, the residual could give valuable information about abrupt changes. In the upper panel of Fig. 12.3, the maximum residuals in absolute terms for each coast correspond to the year 2010; looking at the original data (bottom panel), a clear change in the slope of the signal is seen. Again, there is a significant difference in the slopes for the periods 1980–2010 and 2010–2019 for both coasts. In this case,

Fig. 12.2  Minimum surface atmospheric temperature for the west coast (squares) and east coast (circles), with linear trends for the periods 1980–2000 and 2000–2019 superimposed in the corresponding section of the time series

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Fig. 12.3  Recorded data of the maximum surface atmospheric temperature (bottom part) for the west coast (light line) and the east coast (bold line). In the upper part of the figure the residuals (original data – linear trend for the full record) are presented. The highest absolute value in residuals occur during the year 2010 for both coasts (circle), followed by an apparent change in the behavior (slope) of both series

for the year 2010 a potential abrupt climate change could be identified for the maximum surface atmospheric temperature in both coasts. Looking at the recorded yearly accumulated rain time series for the west coast (Fig.  12.4), there is significant difference between the mean accumulated rain between the period 1980–1997 and 1998–2019, as well as in the slope of the corresponding regression line s1 = −4.4 and s2 = 8.3, respectively. In this sense, the years 1997–1998 could be considered a temporal point of abrupt change in the rain behavior for the full west coast. Some extreme values observed in Fig. 12.4, like the 1990 or 2010 peaks can be explained by the local or regional effect of tropical systems occurrence. In fact, for 1990, the neighboring states of Sonora, Sinaloa, Nayarit, and Jalisco have simultaneous significant residuals, as do the states of Nayarit, Guerrero, Oaxaca, and Chiapas in 2010, possibly associated with tropical system activities. However, this local/regional, time focalize effects, cannot explain the differences of 1980–1997 and 1998–2019 rains. The mechanism and forcing behind these changes are difficult to explain, and the extension of the time series limits the possibilities of generalization. However, with the existing measured data, some of the cases shown suggest abrupt climatic change points in time for the Mexican coasts.

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Fig. 12.4  Yearly accumulated rain for the Mexican west coast (1980–2019); the time series was split in two, with different mean values and linear trend slopes (both values with significant differences at α = 0.05)

The following sections present: (a) an analysis of the governance frameworks for climate change-related effects, which prioritizes the long-term resilience under uncertainty conditions; (b) the assessment of a vulnerability index developed for the Mexican coastal zone, based on environmental, demographic, and geomorphologic conditions; (c) a case study based on 40 years of daily precipitation records for the 17 Mexican coastal states, to identify medium and long-term changes in rainfall patterns, and (d) general conclusions about the abilities and needs of the Mexican coasts to enhance resilience to abrupt climate change effects.

2 Governance to Abrupt Climate Change Effects Coastal governance involves economic, social, environmental, institutional, cultural, traditional, and political entities, and it can be viewed as a combination of shared government in which society also assumes the legitimacy of the process and the recognition of the decisions made (Rivera-Arriaga & Vidal, 2020). According to the Special Report on Oceans and Cryosphere in a Changing Climate (Collins et al., 2019), decision-making is constrained by formal and informal institutional processes, such as rules and rights. Formal or informal political institutions generate rules for government operations and are crucial for framing how people and organizations may respond to climate-related events (Fraser & Kirbyshire, 2017). These

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events can be abrupt, extreme, intense, acute, chronic, extensive, or cyclical. Local and national governance can grant the capacity for prompt response in the case of abrupt climate change effects, and these responses can in turn impact the economy, livelihoods, and well-being (Fraser & Kirbyshire, 2017). Climate change events and responses imply people’s choices and decisions for achieving sustainability and climate-resilient development paths (IPCC, 2018; Moloney et al., 2017; Morchain, 2018). Decision-making to face impacts on vulnerable coastal populations caused by abrupt changes and extreme events, should take into consideration societal participation and local knowledge (Tozier de la Poterie & Baudoin, 2015). Contextualized decision-making diminishes vulnerability and risk, enhancing resilience (Mal et al., 2018). Governance for resilience, applied to the governance of climate abrupt-related impacts, also underlines how risks are addressed in the already complex interactions of socioeconomic and socioecological systems, which require a different approach (Fraser & Kirbyshire, 2017). The difference of considering governance for climate change-related effects, and thinking about governance for anything else, is the resilience for long-term, uncertain futures. This applies to how risks originate in the dynamic and complex interactions of socioeconomic systems and requires a novel approach to conventional risk management (Fraser & Kirbyshire, 2017). Across the fields of disaster risk resilience and climate change adaptation, the implementation of resilience thinking to policy has produced a debate about the forms of governance that properly address risk reduction and resilience building. This translates into the collaboration of many actors, who represent the multi-jurisdictional and multi-sectoral realm of resilience challenges. There are new and more adaptive forms of governance that can take into consideration the uncertainty, extremeness, and abruptness of climate changes related to top-down governance (Boyd & Juhola, 2015; Lebel et al., 2006), which are difficult to apply to local dynamics and context with rapid events of change (Chaffin et al., 2014). According to the IPCC (2014), resilience is defined as the ability of a system to anticipate, absorb, and adapt to climate-related shocks and stresses and to respond in ways that preserve, restore, or improve its essential functions, structures, and identity. The elements of governance that support resilience are based on how resilience is understood and therefore what governance for resilience is willing to achieve (Fraser & Kirbyshire, 2017). Governance for climate change adaptation and resilience comprise several practical and theoretical ideas. Table 12.1 summarizes these approaches. Any of these governance models can be applied in abrupt or extreme events related to climate change (Table 12.1). While decentralization, polycentric, multi-­ stakeholder, and multi-level governance are more related to the interventions of government institution, transformative, adaptive, and community-based governance are more related to strengthening the process and promoting learning. There are some common characteristics, which address resilience across these governance models for climate resilience, such as the involvement of diverse actors for decision-­ making and the participation of beneficiary groups and communities (Fraser & Kirbyshire, 2017).

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Table 12.1  Governance approaches to resilience building Governance approaches Decentralized governance

Multi-­ stakeholder governance

Multi-level governance

Polycentric governance

Participatory governance

Community-­ based governance

Adaptive governance

Characteristics It refers to the transfer of political power and fiscal and/or administrative functions from central government to lower or local levels. Political decentralization gives citizens more power in decision-making, while administrative decentralization refers to the redistribution of authority, responsibility, and financial resources to local levels. The involvement of diverse stakeholders across sectors, scales, and levels of government in decision-making is core for governance for resilience. This multi-stakeholder’s governance gathering (includes both state and non-state actors) results in a governance structure that brings together different partners across scales and/or sectors in dialogue, decision-making, and implementation of solutions in a coordinated and integrated manner (Djalante et al., 2011). It describes structures involving multiple stakeholders (state authorities) at different scales of government, from the global to the local (Leck & Simon, 2013). It specifically involves cross-level interaction and cooperation. It is considered a beneficial form of governance for resilience since it allows decisions to be taken at the most appropriate level to reflect diversity, it provides space for innovation, and it is more adaptive to changing preferences (Hooghe & Marks, 2003). It includes more opportunities to improve policy and increased interaction between parties, which helps build trust needed for cooperation (Cole, 2015). Polycentric governance considers a system where multiple stakeholders across multiple levels and sectors organize to form many coexisting centers of decision-making that are formally independent of each other (Biggs et al., 2015; Ostrom, 2010). It is a people-centered approach to governance that includes citizens, or representatives of a particular group of citizens, in decision-making which affects them, enabling decisions to consider the specifics of a given context (Collins, 2009). Through participatory processes, people collaborate in determining the objectives and processes by which resilience policy will be delivered in their local area (Forsyth, 2013). It focuses on building resilience through a bottom-up approach that considers the most vulnerable and lowest-income groups in society, in recognition of the fact that they are disproportionately affected by disaster and climate change. It focuses on empowering communities to participate in the governance of their own risk reduction. It comprehends a structured, iterative process of continual innovation, testing, learning, and adjustment (Allen et al., 2011, Chaffin et al., 2014). It aims for facilitating robust, flexible decision-making facing uncertainty and complexity, and it has proven to be useful for addressing disagreement among stakeholders as to how resource, or a problem, should be managed (Allen & Gunderson, 2011; Allen et al., 2011). (continued)

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Table 12.1 (continued) Governance approaches Transformative governance

Characteristics Transformative governance is an approach to environmental governance that has the capacity to respond, manage, and trigger regime shifts in coupled social-ecological systems (SESs) at multiple scales. The goal of transformative governance is to actively shift degraded SESs to alternative, more desirable, or more functional regimes by altering the structures and processes that define the system. Like adaptive governance, transformative governance involves a broad set of governance components but requires additional capacity to foster new social-ecological regimes including increased risk tolerance, significant systemic investment, and restructured economies and power relations. Transformative governance has the potential to actively respond to regime shifts triggered by climate change (Chaffin et al., 2016)

Source: Modified from Fraser and Kirbyshire (2017)

Governance facilitates ad hoc responses to extreme and abrupt events, while addressing local needs, promoting the integration of multiple processes and interests and fostering an attitude of appropriation, trust, and understanding (Adger et al., 2005; Carabine et al., 2016; Lebel et al., 2006). This promotes a dynamic and adaptive governance that conveys continual experimentation, innovation, and learning, which responds to new information and evolves more effectively toward a complex changing context (Cole, 2015). Governance seeks autonomy and self-regulation, as well as accountability and promotes communication, knowledge exchange, integration, collaboration, and shared decision-making across institutions and scales (vertical and horizontal), as outlined in Table 12.2. Around the world, abrupt climate changes and isolation from densely populated regions modulate people’s choices, and making the right decisions to manage such events, given uncertainty, is challenging (Collins et al., 2019). New models should be constructed that integrate uncertainty under abrupt scenarios and financial evaluation with different uncertainties and socio-ecological impact such as “Robust Decision Making,” “Decision Scaling,” “Assess Risk of Policy,” “Info-gap,” “Dynamic Adaptation Policy Pathways,” “Dynamic Adaptive Pathways Planning,” “Multi-Criteria Decision Analysis,” “Real Options Analysis,” and “Context-First” (Weaver et al., 2013). However, according to Collins et al. (2019), these frameworks have not been applied to abrupt or extreme changes. Governance and politics matter to resilience. At national and regional levels, weak governance is a major issue for achievable resilience and adaptation planning. The poor ability of local government to respond to abrupt events conveys major deficits in service and infrastructure provision, which increase vulnerability and risk (Satterhwaite, 2011). In Mexico, institutional political organization and the legal framework have resulted in a tendency to top-down, centralized approaches to risk management, which jeopardize the ability to respond to climate change and to visualize appropriate solutions in the local context. Ignoring traditional knowledge through top-down disaster risk reduction policies debilitates the resilience of vulnerable groups to climate impacts (Marino, 2012).

X

X

X

X

X

X

X

X

X

X

X

X

Flexibility, experimentation, innovation, and learning

Source: Modified from Fraser and Kirbyshire (2017)

Decentralised governance Multi-stakeholder governance Multi-level governance Polycentric governance Participatory governance Community-based governance Adaptive governance Transformative governance

Diversity and participation

X

X

X

X

Autonomy and self-regulation X

Table 12.2  Characteristics of governance for improving resilience to climate risks

X

X

X

X

X

X

X

X

X

Communication and Accountability knowledge sharing X

X

X

X

X

X

X

Collaboration, integration, and shared decision-making

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Lebel et al. (2006) stated how knowledge and information are critical for climate change preparedness, as well as the availability and distribution of institutional capacities for protecting against risks, financial and human resources are distributed by and who for. And whether this represents the interests of politically powerful groups in state and society (Fraser & Kirbyshire, 2017). This can result in partial solutions, or even solutions that could increase the risks assumed by the more vulnerable groups (Marino & Ribot, 2012). In the state of Campeche, one of the most vulnerable coastal states of Mexico, the city of Campeche suffers from flooding due to extreme rains, which affects people in over seven sectors of the city. A rain drainage system was begun, but it has not been finished (Rivera et al., 2020). The lag time between forecast, warning and event is related to temporal scales, before and after prevention and post-event response (Field et al., 2012; IPCC, 2012). To prepare for abrupt events in different spatial coastal dimensions, it is necessary to include coordination management and adaptation at local, regional, and sometimes international scales (Devine-Wright, 2013; Barnett et  al., 2014; Llyth et  al., 2016; Barange et al., 2018).

3 Coastal Zones of Mexico: A Vulnerability Index Various methodologies (Cruz et al., 2016, 2019; Escudero et al., 2012; Silva et al., 2014) were reviewed to assess the vulnerability of the population of coastal cities. Silva et al. (2014) carried out a study for the sustainable management of the Mexican coasts, presenting characterization and classification of the main coastal environments of the country. This study identifies the areas that are most at risk, based on an evaluation of the hazards they face and the degree of vulnerability of each area. The average elevation of the territory, geology, geomorphology, displacement of the coastline, significant wave height, tidal range, level of natural protection, hazards from extreme waves, and storm surge were factors that were included in the risk analysis. Socioeconomic characteristics, such as total population, population density, GDP per capita, economic participation rate, human development index, marginalization index, poverty, economic units (tourism sector), total gross production, gross value added (tourism), protected areas, and productive sectors, were used to evaluate the social vulnerability. In the present work, the vulnerability of coastal populations in Mexico was evaluated and related to the local environmental, morphological, and demographic variables, using the same methodology as that presented by Cruz et  al. (2019). The vulnerability of each coastal population, was described in an index of population vulnerability (IPV) given as follows:



IPV  12 ICE  11ID  10 IDP  9 ITI  8IMV  7IAD 6 IDC  5ITC  4 IPA  3IM  2 IV  IAC

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In this equation, ICE describes the vulnerability related to elevation, with 0, 0.2, 0.5, and 0.9 being assigned for the height above the sea level ≥ than 10 m, 4 m – 10 m, 1 m – 4 m, and ≤ 1 m, respectively. ID describes the vulnerability due to proximity of the coastline, with 0, 0.5, 0.7, and 0.9 for distances ≥4 km, 1 km – 4 km, 500 m – 1 km, and ≤ 500 m, respectively. IDP describes the vulnerability related to population density, given as 0.9 for concentrated densities and 0.2 for dispersed populations. ITI describes the vulnerability due to the type of infrastructure: urban (0.1) and rural (1.0). IMV describes the vulnerability due to the construction materials used for dwellings (0.2 for concrete and 0.9 for wood and others). IAD describes the vulnerability related to the height of the dune with 0, 0.5, and 0.9 for heights ≥5 m, 2 m – 5 m, and ≤ 0.9, respectively. IDC describes dune vegetation with 0.2, 0.5, and 1.0 for dune with vegetation, dune without vegetation, and no dune, respectively. ITC describes the vulnerability due to the type of coast, given as 0.2 for cliff or rocky and 0.7 for sand or gravel. IPA describes the vulnerability due to artificial protection, 0.5 with protection and 1.0 without protection. IM describes the vulnerability due to the presence of mangroves: 0.2 with mangrove and 0.9 without mangrove. IV describes the vulnerability due to the presence of vegetation: 0.2 with vegetation and 0.9 without vegetation, and IAC describes the vulnerability related to the presence of coral reefs: 0.2 with reefs and 0.9 without reefs. Using this methodology, the highest value of vulnerability is 71.1, and the lowest is 9.9. Settlements were considered to have, a low vulnerability with an IPV ≤ 30; moderate 30 > IPV ≤ 51 and high IPV > 51. The geographic information system devised by Cruz et al. (2019) was based on information concerning land use (INEGI, 2017), rivers, mangrove, and coastal population (CONABIO, 2010), ports (SCT, 2013), Pacific coral reefs (SOMAC, 2015), Atlantic coral reefs (Reefbase, 2018), coastal dunes (Martínez et  al., 2014), the exchange rate of erosion and accretion (m/year) (Valderrama et  al., 2019) and regionalization of the Mexican coastline (de la Lanza Espino et al., 2013). Digitized aerial and satellite photos complemented this information and morphological information from Fernandez et al. (2018). To illustrate how the analysis was performed, the results for Bahía de Todos los Santos, Ensenada, in Baja California, and its main demographic characteristics, are presented in Fig.  12.5 and Table  12.3. The demographic features used are taken from the latest dataset published by INEGI at locality level (2010), while the population density was evaluated using the urbanized area of each locality (Fig. 12.5, left panel, in gray). Of the 32 Mexican states, 17 have a coastline. According to the 2010 census, the population of Mexico was 112,336,538, with the coastal states having 46.2% of the national population. Considering a strip, of 10  km width from the coastline, the coastal population is 5.7% of the national total (91.16% urban and 8.84% rural) distributed in 1108 settlements (11.1% urban and 88.90% rural). Figure 12.6 shows the location of the coastal states and the coastal settlements. Considering the area of these 1108 settlements, the average density is 4000 inhabitants per km2 in urban areas and 1011 inhabitants per km2 in rural areas.

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Fig. 12.5  Bahía de Todos los Santos (a) settlements and land use and (b) type of coast Table 12.3  Main demographic features of the settlements in Bahía de Todos los Santos, Baja California Locality Ensenada Coronel Esteban Cantú El Sauzal De Rodriguez Colonia Costa Azul Cuatro Milpas La Joya San Miguel Nueva Ciudad de los Niños Parcela Numero Sesenta y Siete II Sección Ejido Esteban Cantú El Salitral

masl 16 12 34 4 40 10 101 37

Pop 279,765 468 8832 121 186 148 129 108

Distance to the coastline 500 m to 4 km 500 m to 4 km 0 m to 500 500 m to 4 km 500 m to 4 km 0 m to 500 0 m to 500 500 m to 4 km

Area Infrastructure (km2) Urban 69.24 Rural 0.35 Urban 6.07 Rural 0.82 Rural 0.56 Rural 0.52 Rural 1.02 Rural 0.01

Density (pop/km2) 4040 1338 1454 147 331 283 126 7638

5

142

500 m to 4 km

Rural

0.16 890

3

217

500 m to 4 km

Rural

0.11 1943

5

439

500 m to 4 km

Rural

0.12 3614

A coastal population is more vulnerable to the effects of climate events when there is an absence of protective ecosystem services (e.g., seagrasses, dunes, coral reefs) and if they are closer to the coastline and at lower altitudes. In Fig. 12.7 the main characteristics of each of the coastal states are shown. Figure 12.7a presents the relationship between the population of each coastal state and that of Mexico as a whole. Figure 12.7b takes only the population of each state that lives less than 10 km from the coast, to show the relationship between the coastal populations and the total coastal population of Mexico. In Fig.  12.7c the relationship is shown between the coastal populations (0). This means that the radiation probability is the following: (1) the incoming shortwave reflection increases during the day; (2) the outgoing longwave radiation at night is reduced; (3) the incoming nighttime longwave radiation increases; and (4) soil heat flux changes. Thus, SVF was then found to be a significant index as its influence on energy balance on urban climate, human biometeorology, and UHI phenomena (Lai et al., 2017; Lin et al., 2017; Matzarakis et al., 2007; Matzarakis & Mayer, 2008). Figure 13.1 explains the heat storage within urban geometry.

Fig. 13.1  Urban surface energy budget

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Fig. 13.2  Building density of eight cities in 2009 and 2019

Figure 13.2 provides an overview of building density in the eight study cities in Indonesia. It explains that Jakarta and Bandung just left 11% of open space area both in 2009 and 2019. Makassar in 2009 left 17% of open space, but 10 years later just left 16% of open space. In 2009, Medan and Denpasar have similar building density with 22% of open space area, but 10  years later, it left 20% from the total area. It is estimated that Banjarmasin had 43% of open space in 2009 but by 10 years later it had grown to 70%, leaving only 30% of open space. This is the most rapid change of LULC compared with any cities in Indonesia within 10 years. Pontianak seems to be the only city which promotes an open space, from 28% in 2009, which later in 10 years became 32% of the open space area. Padang contributed an urban open space of as much as 56% in 2009 and remained the same in, the next year, 2019. In the term of urban heat island, LULC and building density play an important role in microclimate, which is influenced by anthropogenic, sensible, latent, and storage heat, which then contribute to net heat flux store. Those urban energy budget also impact the human being for their urban biometeorology, especially for the area of urban canopy layer. The energy budget in the form of shortwave and longwave radiation fluxes is then measured into a mean radiant temperature (Tmrt). The higher the density of the building, the higher the impact on the net heat flux store.

2.2 Urban Tropical Climate Resilience Regions of Indonesia with low latitudes are located near the equator, in a hot-humid climate influenced by the amount of insolation. This incoming solar radiation is the greatest potential to conduct heat, which is the most significant aspect for outdoor conditions. However, this area does not have extreme climate because of the diurnal

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temperature lag, whether day or night, monthly or yearly. In tropical countries, the adaptability of people for acceptable (neutral) temperature range is considered high. In a study in Taiwan through an experiment of 300 people, it is known that the neutral perception of PET in a hot-humid climate is 26 °C–30 °C (Lin et al., 2010). Meanwhile, in the PET range of 30 °C–34 °C, people tend to feel slightly warm. People starts to feel warm when the PET hits 34 °C–38 °C and will feel hot in the PET range of 38 °C–42 °C. When the PET hits more than 42 °C, people in tropical climate will start to feel very hot. The PET value at a certain geographic location is significantly determined by climatological aspects, including air temperature, wind velocity, relative humidity, and most importantly the mean radian temperature (Tmrt). Tmrt is defined as the “uniform temperature” of an imaginary enclosure at which the radiant heat transfer from the human body equals the radiative heat transfer of the actual nonuniform cover (ASHRAE, 2001). During sunny weather in summer, this Tmrt is the most important meteorological input as a meteorological parameter on energy balance in the human body (Herrmann & Matzarakis, 2012). The Tmrt value is derived from all relevant luminous flux radiation which can be calculated based on shortwave and longwave radiation fluxes. Globe temperature (Tg) then becomes an important part as a representation of the weighted average of the radiation and ambient temperature (ambient temperature). Therefore, based on ASHRAE (2001), Tmrt can be calculated by knowing the values ​​of Tg and Ta as well as v with the equation:



  1.1  108  va0.6 4 MRT   GT  273    GT  Ta  0.4  D  

1/ 4

 273

where Tmrt = mean radiant temperature (°C). Tg = globe temperature (°C). v = wind speed (m/s), Ta = air temperature (°C). D = diameter of globe. ε = Emisivitas tubuh manusia. Menurut hukum Krichhoff, ε sama dengan koefisien absorpsi untuk radiasi gelombang panjang (nilai standar = 0.97). Long duration of solar radiation in low latitude offers a higher diurnal temperature in tropical climate, which then contributes to higher Tmrt. It will naturally be difficult to offer the preferable PET in neutral range. Increased shading and ventilation in urban areas can help to change the microclimate to reduce Tmrt. In dense urban areas such as Jakarta, Bandung, Makassar, Medan, and Denpasar which have land use cover of >80%, it will be difficult to promote urban ventilation and vegetation for green open areas. The lack of unbuilt areas will be prioritized for infrastructure facilities (such as transportation) rather than being used as green open space.

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3 Human Biometeorology in the Tropical Climate As mentioned in the previous chapter, long duration of solar radiation is the main challenge of human biometeorology in the tropical climate. Solar radiation due to geographical location and heat flux store contributes to high Tmrt, which later impacts on PET. The human biometeorology in the following eight cities uses PET index that is generated from RayMan Pro. The following personal data are typical characteristics of an Indonesian citizen: female, 35 years old, 65 kg weight, clo 0.7, met 80. Meanwhile, the extreme PET is calculated according to the peak Ta (air temperature) data for every month and year. In the following table, PET will be explained in the eight study cities.

3.1 Jakarta PET Index in the Peak Temperature Date 14/8/2009 18/10/2010 16/10/2011 13/9/2012 9/10/2013 10/10/2014 4/10/2015 9/10/2016 17/9/2017 15/11/2018 9/11/2019

Time 12:00 13:00 12:00 14:00 13:00 12:00 12:00 16:00 13:00 12:00 13:00

Rh (%) 58.0 59.0 46.0 51.0 46.0 42.0 41.0 64.0 48.0 45.0 50.0

V (m/s) 2.7 3.1 4.1 2.1 2.1 2.1 4.1 2.1 1.5 3.6 4.1

Ta max 36.0 36.0 35.2 36.0 37.2 36.6 37.3 37.0 36.0 36.8 38.9

TMRT 63.9 59.4 56.8 64.4 58.3 60.7 59.2 54.8 64.5 58.1 60.1

PET 48.1 45.4 42.7 48.3 41.3 47.2 46.1 45.2 49.2 45.4 48.6

Perception Very hot Very hot Very hot Very hot Hot Very hot Very hot Very hot Very hot Very hot Very hot

3.2 Bandung PET Index in the Peak Temperature Date 19.10.2009 03.06.2010 19.10.2011 18.01.2012 11.03.2013 03.11.2014 27.10.2015 04.06.2016 17.09.2017 16.11.2018 24.10.2019

Time 14:00:00 14:00:00 14:00:00 14:00:00 14:00:00 14:00:00 14:00:00 14:00:00 14:00:00 14:00:00 14:00:00

Rh (%) 61 48 27 38 50 28 27 47 36 39 19

V (m/s) 3.1 5.1 7.7 7.7 5.1 7.2 2.6 0.85 6.7 4.1 3.6

Ta max 32.6 30.6 31.2 30.2 31.7 32.4 34.0 31.8 31.8 32.3 33.6

TMRT 56.4 56.8 52.2 51.3 55.9 52.7 57.2 61.7 56.6 53.8 49.9

PET 40.3 35.9 33.3 31.7 37.1 35.6 42.2 45.5 36.3 37.7 37.3

Perception Hot Warm Slightly warm Slightly warm Warm Warm Very hot Very hot Warm Warm Warm

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3.3 Medan PET Index in the Peak Temperature Date 6/5/2009 8/24/2010 5/9/2011 6/12/2012 6/20/2013 7/6/2014 6/27/2015 4/22/2016 4/2/2017 7/14/2018 8/20/2019

Time 15:00 15:00 14:00 13:00 15:00 16:00 14:00 12:00 16:00 13:00 13:00

Rh (%) 47 41 41 32 34 62 44 53 73 63 64

V (m/s) 4.1 1.95 3.6 5.1 7.72 4.1 6.2 4.1 5.1 3.6 5.1

Ta max 36.0 36.0 36.0 37.0 36.1 35.6 36.0 37.0 36.0 35.6 37.2

TMRT 60.4 62.5 62.2 64.0 59.6 53.4 62.6 62.6 54.2 53.6 55.2

PET 45.1 47.5 46 46.9 43.4 42.2 44.9 47.2 42.6 42.5 44.5

Perception Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot

PET 40.1 41.7 41.1 47.5 43.4 39.7 45.0 42.1 41.5 41.2 40.0

Perception Hot Hot Hot Very hot Very hot Hot Very hot Very hot Hot Hot Hot

3.4 Padang PET Index in the Peak Temperature Date 22/12/2009 11/3/2010 11/2/2011 2/1/2012 5/3/2013 15/3/2014 5/4/2015 25/1/2016 2/6/2017 4/2/2018 13/2/2019

Time 12:00 15:00 12:00 15:00 15:00 15:00 12:00 15:00 11:00 15:00 13:00

Rh (%) 62.0 41.0 43.0 40.0 41.0 65.0 65.0 40.0 58.0 56.0 74.0

V (m/s) 4.1 5.7 2.6 1.5 2.6 5.1 1.0 5.1 3.1 4.1 4.1

Ta max 33.5 35.0 33.0 36.8 34.2 33.0 32 35.2 32.1 34 33

TMRT 55.2 57.0 56.7 59.8 59.2 57.3 60.4 56.6 61.1 56.7 56.2

3.5 Pontianak PET Index in the Peak Temperature Date 25/4/2009 18/5/2010 30/9/2011 9/9/2012 2/5/2013 1/8/2014 12/7/2015

Time 16:00 14:00 14:00 14:00 10:00 14:00 14:00

Rh (%) 49.0 56.0 47.0 47.0 57.0 56.0 49.0

V (m/s) 2.6 2.1 1.5 2.1 2.6 3.6 2.6

Ta max 36.7 35.0 35.0 35.2 36.0 35.4 35.8

TMRT 54.9 62.9 63.4 64.0 63.1 63.2 64.1

PET 44.6 46.7 47.7 47.3 47.3 45.8 47.4

Perception Very hot Very hot Very hot Very hot Very hot Very hot Very hot

13  Increasing Temperature Risk and Community Resilience: Urban Aspects Date 4/7/2016 8/6/2017 20/8/2018 11/8/2019

Time 15:00 15:00 13:00 14:00

Rh (%) 47.0 50.0 47.0 44.0

V (m/s) 0.6 2.1 2.6 3.1

Ta max 35.2 35.0 35.3 35.7

TMRT 62.5 60.3 63.8 63.8

PET 49.5 45.5 46.8 46.7

311 Perception Very hot Very hot Very hot Very hot

3.6 Banjarmasin PET Index in the Peak Temperature Date 07/19/2009 5/19/2010 8/16/2011 10/13/2012 10/17/2013 10/21/2014 10/23/2015 8/25/2016 9/26/2017 10/4/2018 10/23/2019

Time 12:00 15:00 13:00 14:00 14:00 15:00 15:00 13:00 15:00 15:00 15:00

Rh (%) 46 59 47 49 37 33 31 42 47 34 27

V (m/s) 3.1 1.5 3.1 4.1 6.2 3.1 3.1 2.1 1.5 3.1 2.6

Ta max 37.6 35.0 36.2 37.1 37.0 38.0 39.0 36.0 36.0 37.2 38.5

TMRT 65.5 60.6 64.2 60.5 59.1 60.4 61.1 64.7 62.3 61.0 61.0

PET 49.6 46.5 47.5 46.5 45.0 47.8 49.1 48.4 48.1 47.1 48.7

Perception Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot

3.7 Makassar PET Index in the Peak Temperature Date 10/18/2009 6/4/2010 8/28/2011 10/13/2012 9/25/2013 10/19/2014 10/18/2015 6/3/2016 9/9/2017 9/16/2018 10/20/2019

Time 12:00 14:00 13:00 14:00 12:00 12:00 13:00 11:00 14:00 15:00 15:00

Rh (%) 35 60 34 60 39 31 19 61 29 27 15

V (m/s) 5.1 2.1 5.1 4.6 3.1 5.1 5.1 2.6 6.7 5.7 5.1

Ta max 37.0 34.8 36.0 38.0 36.0 38.0 38.0 37.0 36.8 36.0 39.0

TMRT 55.2 62.9 62.0 60.8 58.9 56.0 57.6 65.1 62.0 59.7 59.4

PET 43.9 46.5 44.9 47.6 44.9 45.4 45.7 49.2 45.4 43.7 47.6

Perception Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot Very hot

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3.8 Denpasar PET Index in the Peak Temperature Date 14.11.2009 26.3.2010 17.2.2011 19.12.2012 6.10.2013 02.11.2014 02.12.2015 07.01.2016 31.10.2017 04.04.2018 7.12.2019

Time 13:00 13:00 13:00 13:00 13:00 14:00 15:00 12:00 14:00 14:00 14:00

Rh (%) 64 62 66 63 55 55 59 59 53 61 59

V (m/s) 4.1 4.6 3.6 3.6 3.1 3.6 3.1 2.6 2.1 2.1 6.2

Ta max 33.0 33.0 33.0 33.0 33.0 33.0 34.0 34.0 32.3 32.1 34.4

TMRT 53.8 57.7 56.0 54.7 57.4 56.7 57.2 56.0 58.0 60.7 55.6

PET 39 40.1 40.2 39.7 41.1 40.4 42.2 42.2 41.7 42.8 40.4

Perception Warm Hot Hot Hot Hot Hot Very hot Very hot Hot Very hot Hot

Very hot Hot Warm Slightly Warm Neutral

Fig. 13.3  Temperature fluctuation of the eight cities of Indonesia

The PET index in the peak temperature for eight metropolitan cities above shows that the highest PET value occurred mostly in the afternoon (after 12:00 am). The authors presented the summary of temperature fluctuation in the eight metropolitan cities of Indonesia from 2009 to 2019 in the following (Fig. 13.3): Figure 13.3 explains that none of the eight big cities in Indonesia offers the quality of urban space to human biometeorology. Bandung city, with a high altitude (+667 masl) and a maximum daily temperature of 28 °C, is not able to offer PET in the preferable neutral range. Denpasar and Padang in 10 years offer a “hot” perception toward their urban environment with PET range. 38 °C–42 °C. Meanwhile, human biometeorology perceived a “very hot” perception for Jakarta, Medan, Pontianak, Banjarmasin, and Makassar.

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4 Conclusions and Recommendations Vulnerability, resilience, and adaptation initiative suggest various things to specific humans and had been conceptualized in lots of specific methods relying on disciplinary traditions. This chapter adopts a case examination technique to discover interactions among vulnerability of increasing temperature of some cities of Indonesia and community resilience options in these urban cities. From the earliest to the contemporary period, urban environment was many times neglected, although they used to alternate water and perspective natural resources, discharge solid and liquid wastes, partly filled up or completely eliminated for land development, or simply sometimes regulated within a concrete channel to provide rapid discharge for floodwaters. Environmental concerns or aspects of aesthetics were not considered. This aims to apprehend why people reply to excessive temperatures in the manner that they do and permit a clean expertise of what underpins their selections and recognition on what is wanted for model movements that minimize impacts. This article has included and mentioned the effects of blended popular and unique vulnerability and community resilience to excessive temperatures. The technique taken in supplying a blended evaluation is novel and a contribution to expertise within side the experience that it lets in an included dialogue of the roots and drivers of vulnerability and resilience for expertise model to warmness and bloodless. The ranges of vulnerability and resilience deliver vital bases for the following: focused on at-chance older people (excessive vulnerability and low resilience), growing vulnerability discount movements (excessive vulnerability and excessive resilience), resilience constructing movements (low vulnerability and low resilience), and expertise “fulfillment cases” (low vulnerability and excessive resilience) and examine from them for growing suitable coverage measures. Generally, deliberate resilience model alternatives had been carried out via way of means of low vulnerability and excessive resilience individuals, while self-sustaining model alternatives had been extra not unusual place inside different individuals. Assets are on the middle for expertise vulnerability, resilience, and model; they’re the fundamental reasons of human vulnerability, and they affect the resilience of people through their hyperlinks to all three dimensions of resilience (comprehensibility, manageability, and meaningfulness) and decide the techniques and behaviors to be had to people for responding to excessive temperatures in particular (model), and different threats, shocks, and stresses in popular. The findings of this examination align with the United Nations 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs). The trend of increasing average daily temperatures in metropolitan cities is also recorded from year to year. This study provides a link between the urban environment’s spatial and microclimate that affected the human perception of living space and quality of life. The combination of urban morphology and human biometeorological conditions will provide an understanding of meteorological vulnerability and physiological aspects in the city inhabitant, such as thermal stress. Detailed resilience in spatial planning, buildings, and the environments are the targeted results of this study.

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References ASHRAE. (2001). Fundamentals Handbook 2001 (SI ed.). American Society of Heating, Refrigerating, and Air-Conditioning Engineers. Gagge, A. P., Stolwijk, J. A., & Nishi, Y. (1971). Effective temperature scale based on a simple model of human physiological regulatory response. ASHRAE Transactions, 77(pt 1) paper 2192, 247–263. Gagge, A., Berglund, P., & Fobelets, A. (1986). A standard predictive index of human response to the thermal environment. ASHRAE Transactions, 92, 23. Herrmann, J., & Matzarakis, A. (2012). Mean radiant temperature in idealised urban canyons – examples from Freiburg, Germany. International Journal of Biometeorology, 56(1), 199–203. https://doi.org/10.1007/s00484-­010-­0394-­1 Hondula, D. M., Balling, R. C., Andrade, R., Scott Krayenhoff, E., Middel, A., Urban, A., et al. (2017). Biometeorology for cities. International Journal of Biometeorology, 61, 59–69. https:// doi.org/10.1007/s00484-­017-­1412-­3 Höppe, P. (1984). Die Energiebilanz des Menschen. (Dissertation-unpublished) Wiss Mitt Meteorol Inst Univ München. Höppe, P. (1993). Heat balance modelling. Experientia. https://doi.org/10.1007/BF01923542 Höppe, P. (1997). Aspects of human biometeorology in past, present and future. International Journal of Biometeorology, 40(1). https://doi.org/10.1007/BF02439406 Höppe, P. (1999). The physiological equivalent temperature – A universal index for the biometeorological assessment of the thermal environment. International Journal of Biometeorology, 43(2). https://doi.org/10.1007/s004840050118 Lai, A., Maing, M., & Ng, E. (2017). Observational studies of mean radiant temperature across different outdoor spaces under shaded conditions in densely built environment. Building and Environment. https://doi.org/10.1016/j.buildenv.2016.12.034 Lee, H., & Mayer, H. (2013). Urban human-biometeorology supports urban planning to handle the challenge by increasing severe heat. Plea, 2013(September). Lin, T.  P. (2009). Thermal perception, adaptation and attendance in a public square in hot and humid regions. Building and Environment. https://doi.org/10.1016/j.buildenv.2009.02.004 Lin, T.-P., Matzarakis, A., & Hwang, R.-L. (2010). Shading effect on long-term outdoor thermal comfort. Building and Environment, 45, 213–221. Retrieved from http://download.xuebalib. com/xuebalib.com.25622.pdf Lin, T.-P., Chen, Y.-C., & Matzarakis, A. (2017). Urban thermal stress climatic mapping: Combination of long-term climate data and thermal stress risk evaluation. Sustainable Cities and Society, 34, 13–21. Matzarakis, A., & Mayer, H. (2008). Dependence of urban climate on urban morphology. In 5th Japanese-German Meeting on Urban Climatology (pp. 277–282). Retrieved from http://www. meteo.uni-­freiburg.de/forschung/publikationen/berichte/report18.pdf#page=277 Matzarakis, A., Rutz, F., & Mayer, H. (2007). Modelling radiation fluxes in simple and complex environments—Application of the RayMan model. International Journal of Biometeorology, 51, 12. https://doi.org/10.1007/s00484-­006-­0061-­8 Mayer, H., & Höppe, P. (1987). Thermal comfort of man in different urban environments. Theoretical and Applied Climatology, 38, 7. Muthers, S., Matzarakis, A., & Koch, E. (2010). Climate change and mortality in Vienna  – A human biometeorological analysis based on regional climate modeling. International Journal of Environmental Research and Public Health, 7(7). https://doi.org/10.3390/ijerph7072965 Nastos, P.  T., & Matzarakis, A. (2006). Weather impacts on respiratory infections in Athens, Greece. International Journal of Biometeorology. https://doi.org/10.1007/s00484-­006-­0031-­1 Omonijo, A.  G. (2017). Assessing seasonal variations in urban thermal comfort and potential health risks using physiologically equivalent temperature: A case of Ibadan, Nigeria. Urban Climate, 21. https://doi.org/10.1016/j.uclim.2017.05.006

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Paramita, B., & Matzarakis, A. (2019). Urban morphology aspects on microclimate in a hot and humid climate. Geographica Pannonica, 23(4). https://doi.org/10.5937/gp23-­24260 Paramita, B., Fukuda, H., Perdana Khidmat, R., & Matzarakis, A. (2018). Building configuration of low-cost apartments in Bandung—Its contribution to the microclimate and outdoor thermal comfort. Buildings. https://doi.org/10.3390/buildings8090123 Paramita, B., Kusuma, H. E., & Matzarakis, A. (2022). Urban performance based on biometeorology index in high-density, hot, and humid cities. Sustainable Cities and Society, 80. https://doi. org/10.1016/j.scs.2022.103767

Part III

Climate Changes, Agro-Forestry Resilience and Water-Food Security

Chapter 14

Climate Change Adaptation in Megacities : A Critical Review on the Brazilian Political Context L. D. Barreto Torres and G. F. Asmus

Abstract  Climate change adaptation and resilience building in megacities has been a rapidly growing concern worldwide, especially in the face of current and future environmental threats. Cities are important actors in the adaptation process as they respond to climate change with varied technological and social approaches  apart from the fact that most social, political, and technological changes take place in cities, along with a series of urban and environmental issues (resources depletion and distress, high consumption rate, overpopulation and waste generation). In this regard, developing countries are especially vulnerable, as they usually hold high inequality rates - where the poorest bear the highest costs in terms of material and human losses - and lack resources to invest on adaptation measures to make their cities more resilient. This review discusses the main challenges posed by climate change adaptation in the Brazilian context, more specifically in the megacity of São Paulo,  shedding light on the role of social and political  segregation in delaying actions directed at climate change adaptation and resilience building. Keywords  Resilient cities · Sustainable development · Urban environmental issues · Brazil

1 What Does Climate Change Adaptation Mean? The concept of adaptation – as well as its relevance – has varied throughout time, as discussions and paradigms around climate change advanced. Although the word adaptation has appeared  publically since the release of the first IPCC’s report (1990) - including the United Nations Framework Convention on Climate Change L. D. Barreto Torres (*) · G. F. Asmus Center of Engineering, Modelling and Applied Social Sciences, Federal University of ABC, Santo André, Brazil e-mail: [email protected] © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_14

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(UNFCCC, 1992)- concerns about the definition of the concept and its operationalization arose much later on. In the first IPCC report (1990), adaptation is mentioned as a strategy to be considered within a complementary package of actions to minimize the costs of climate change (IPCC, 1990, p. 16). A list of desirable actions for adaptation were summarized, such as to develop policies and capacitation programs for emergencies and disasters; to access areas under risk of sea level elevation and to develop wide-­ ranging management plans, reducing the vulnerability of populations, ecosystems and coastal developments as part of the management plans in coastal zones; and to improve the efficiency of natural resources’ use, to research on measures of desertification control, and to enhance crops adaptability to saline regimes (IPCC, 1990 – Policymakers Summary, p. xxvii). In UNFCCC (1992), adaptation is mentioned in a more generic way. For instance, in the section “Compromises,” it is stated that countries need to formulate policies and take adequate measures to adapt to climate change (UNFCCC, 1992, p. 09) and that cooperation is needed in the preparation to adapt to climate change  impacts (UNFCCC, 1992, p.  11). In spite of the scarce mentioning of the term  throughout the 1990's, the document represents a mark for attributing to developed countries the responsibility in aiding developing countries with the costs of adaptation to the adverse climate effects (UNFCCC, 1992, p. 14). In the Working Group II report of IPCC’s Second Assessmen, the word adaptation appeared in the tittle of the publication: “Impacts, Adaptations, and Mitigation of Climate Change: Scientific-Technical Analyses,” emphasizing the theme. Adaptation is present, more specifically, in sections dedicated to industry, energy, transportation, agriculture, and human settlements. In “Human Settlements,” the topic “adaptation options” (IPCC, 1995, p. 416–421), is subdivided into the sections “migration,” “energy,” “atmospheric pollution,” “sanitation and waste management,” “infrastructure,” “water supply,” and “health.” The text reiterates that the topic is still under development and that further research is needed to comprehend the current situation of human settlements on a regional scale, to only then enable the analysis of adaptative options. As regards the Working Group II report of IPCC’s Third Assessment, the space dedicated to adaptation was broadened. A sole  chapter arose dedicated entirely to adaptation: “Chapter 18 – Adaptation to Climate Change in the Context of Sustainable Development and Equity.” However, the concept still hadn’t been worked out. It is understood that adaptation capacity depends on the system’s vulnerability or on the people who expose themselves to the impacts of climate change. According to Obermaier and Rosa (2013), knowing what makes a system or people vulnerable is indispensable to understand under which circumstances they can adapt and how those adaptation processes are constructed. Thus, the concept attributed to adaptation in IPCC (2007) is as follows: Measures and initiatives to reduce the vulnerability of natural and human systems against the current or expected effects of climate change. Many types of adaptation exist, e.g. anticipatory and reactive, private and public, autonomous and planned. Some examples are the

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coastal dams, the replacement of sensitive plants with other resistant to thermal shock, etc. (IPCC, 2007, Synthesis report, p. 76)

Since the Fifth Assessment Rreport (2014), it is noticeable that adaptation has been having a more central role in the discussions regarding climate change. Besides four chapters dedicated entirely to adaptation, the theme is presented intrinsically in various other chapters, such as in the ones entitled “Human health: impacts, adaptation and co-benefits" (Chap. 11) and “Climate-resilient pathways: adaptation, mitigation and sustainable development”  (Chap. 20), as well as inside each of the regional chapters: “Africa” (Chap. 22), “Central and South America” (Chap. 27), and so on (IPCC, 2014). Still according to IPCC's Fifth Assessment (2014), adaptation to climate change is the process of adjustment to current or future climate and its effects. In human systems, adaptation aims at mitigating, avoiding damages or exploring beneficial opportunities  (Noble et  al., 2015).  In the Sixth Assessment Report, adaptation is clearly transectional in the Working Group II contribution. Planned adaptation, adaptation solutions, adaptation success and adaptation limits are considered at every chapter of the document. Entires sub-topics are dedicated to adaptation, as “Climate change adaptation for terrestrial and freshwater ecossystems” inside chapter “Terrestrial and Freshwater Ecosystems and Their Services” or “Planned Adaptation and Governance to Achieve the Sustainable Development Goals” inside chapter “Oceans and Coastal Ecosystems and Their Services” (IPCC, 2022). Yet, cross-chapters and Frequently Asked Questions boxes concernig adaptation can be found through all chapters.In this last IPCC report, it’s highlighted that implementing adaptation and mitigation actions together with the sustainable development goals helps to exploit synergies, reduce trade-offs and makes all three more effective (IPCC 2022, p.136). In the Conference of Parts, in Paris (COP-15, 2015), for instance, one of the biggest debates concerned the financing of adaptation in developing countries, following the premise that all countries share common responsibility, although differentiated in the resolution of the climatic problem (UNFCCC, 1992). The final text of COP-15, regarding climate finance, determines that developed countries should pledge 100 billion dollars per year in measures against climate change and for adaptation and mitigation in developing countries. Although the emphasis on adaptation has grown gradually, there still isn’t much progress in the implementation of the historic Paris Agreement (2015). According to Lesnikowski et al. (2015), who evaluated the national communications submitted from 2008 to 2012 by the parties to the Convention, the detection of concrete adaptation initiatives were still very limited at the time. Among all the actions reported, 75% were considered “groundwork,” that is, they were still on a research or planning level toward implementation. The authors pointed out that most adaptations until then were within the categories of “infrastructure,” “technology,” and “innovation.” The adaptation actions addressed were also grouped according to the “category of vulnerability”, that is, vulnerabilities provoking adaption  responses. The categories that received more attention were “Water Safety and Security” and “Food Safety and Security” (Fig. 14.1).

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Adaptation Groundwork

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Ai rq ua la De ce se li m rt C t y tri en ific ol ci ty t / at d /t co ion el e D nf Er com E ro lict os m co ug Fo io un no ht n ic m od / l a ic Fr s an tio es afe ds n s hw ty l at an F ide er d lo s ec se od Fr o cu s oz sy ri en ste ty gr ms ou In f e H nd M c e ar tio in us alth e d H e i ea M cos sea t en ys se ta te lh m e s R alt ai h Te Se n rre a Ru fall le n W T str v e of at ra ial er d e S l ris f i c t sa io o to e fe na sys rm ty l l te s an ife m d sty s se le W cur s ild ity In fir de e te Ot s rm he in r at e

200 180 160 140 120 100 80 60 40 20 0

Fig. 14.1  Number of countries reporting adaptation actions per category of vulnerability. The amount of countries exceeds the number of member nations (117) because the activities in groundwork level and adaptation activities are accounted for separately. (Source: Lesnikowski et al., 2015)

2 Climate Change Adaptation and Resilience Building In the adaptation discourse, resilience has been defined as the capacity to “persist, adapt and recover in the face of climate stresses and shocks”  (Berbés-Blázquez, Mitchell, Burch, & Wandel (2017). Working with the concept of resilience is important when speaking of adaptation toward sustainability, because it addresses many aspects of sustainable development, such as annihilating hunger and poverty and delivering good health, well-being, and sanitation. The authors stress that bringing resilience into the core of global climate change adaptation strategies means working toward shifting our approach from “predict-and-prevent” to “resilience-­ building,” given that the former prepares us for specific events whereas the latter can cover a broader range of probable impacts related to climate variables. According to Berbés-Blázquez et al. (2017), in order to achieve climate-resilient development, it is necessary to develop better integration between resilience and climate change adaptation strategies. For that matter, it is important to understand the evolution of both these concepts throughout the past decades. In the past 20 years, a wide range of studies have addressed the concept of resilience.1 The first document on the matter was published in 1968, and the number of studies in this direction shot up after the year 2005. Only in 2017, 2884 studies were  The Elsevier’s database Scopus returned 23,593 results on June 24, 2019, for the search criteria “resilience OR resilient AND environmental OR environment OR climate” in the title, abstract, or keywords of articles and reviews, from 1960 to the present. 1

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published addressing environmental resilience. However, the definition still appears to be imprecise and divergent, which poses an obstacle in achieving climate change adaptation from a resilience standpoint (Berbés-Blázquez et al., 2017). Besides the countless efforts to integrate resilience and climate change adaptation, it appears that part of the scientific community regards resilience as a topic mostly related to natural sciences and less invested in human needs and well-being, suggesting that it depoliticizes the narrative, dismissing or giving less attention to aspects like background social vulnerability and socioeconomic issues (Berbés-­ Blázquez et al., 2017). Henrique K. P. & Tschakert (2019) illustrate well such conflict by  shedding light on the project entitled Parque Várzeas Tietê PVT (Tietê Lowlands Park), in São Paulo city, which aims to restore the river’s floodplain vegetation in order to enhance its buffering effect and prevent floods. However, the project doesn’t take into account the fate of approximately 7500 low-income families living in the region, bringing to question the ostracism of informal urban settlements (Paiva Henrique & Tchakert, 2019). This example shows how the idea of climate adaptation is not extended to all in the same magnitude, tending to benefit one parcel of the population in detriment of others. On the other hand, some authors share the opinion that inclusive and socially adequate adaptation strategies are possible, so long they adopt an interdisciplinary approach under varying levels of governance, involving multiple stakeholders (government, civil society, academy, private sector) (Berbés-Blázquez et  al., 2017). These authors endorse the potential and applicability of resilience thinking for climate change adaptation, affirming that “resilience is well suited to deal with issues of uncertainty and complexity.” However, the way resilience is translated into actions depends on each context (Berbés-Blázquez et al., 2017).

3 Climate Change Adaptation in Megacities Urban settlements will likely continue to grow, overloading the existing infrastructure, which is already insufficient to cope with extreme climatic events (Paiva Henrique & Tschakert, 2019). As predicted by the last IPCC’s Assessment Report, it is expected that climate change impacts will exacerbate the current social inequalities, given that the least favored parcel of society  – usually occupying areas of environmental risk – will dispose of fewer means and resources to dodge this situation (Henrique K.  P. & Tschakert, 2019).  Ever since the release of the Fourth Assessment Report (AR4) of the Intergovernmental Panel of Climate Change (IPCC, 2007), many uncertainties arose, such as how much the global temperature would actually vary, how the changes in precipitation would take place, and how those changes would affect everyday life (Ribeiro, 2008). The report predicted impacts such as the increase in frequency, intensity, and duration of heat islands on urban areas, deterioration of air quality, and the escalation of risk events associated with intense precipitation in urban areas (floods, landslides, and similar). These predictions fomented a number of political, social, and economic discussions,

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including the reduction of greenhouse gas emissions and the conception of alternatives to prepare society for the inevitable environmental impacts for the years to come, even if we lacked scientific assertiveness at the time to consistently support such precaution (Ribeiro, 2008). This concern reflected on the number of studies (articles and reviews) addressing climate change adaptation published after the release of the AR4, which skyrocketed in the last decade, as shown in Fig. 14.2. Following this trend, the Fifth Assessment Report (2013) thoroughly explored concerns and strategies regarding climate change adaptation measures, based on vast scientific, technical, and socioeconomic research. The second part of the report (launched in 2014) addressed climate change impacts, adaptation, and vulnerability, shedding some light on the relation between socioenvironmental risks in urban areas and the magnitude of climate change events while highlighting adaptations that cannot be overlooked in order to reduce the vulnerability of less privileged groups (Bazrkar et al., 2015). The participation of urban centers (especially megacities) in promoting climate adaptation is crucial, given that more than half of the world’s population live in urban areas and that most economic activities that generate greenhouse gases are hosted within the urban perimeter (IPCC, 2014). Di Giulio et al. (2015) point out that megacities are important actors in the implementation of climate change adaptation measures, since climate change is intrinsically related to the urban context, given that cities are more susceptible to suffering the impacts of climate change phenomena, which could aggravate urban problems such as floods, landslides, and heat islands. The authors stress the relevance of local

Fig. 14.2  Number of documents addressing climate change adaptation by year. Search criteria: “climate change adaptation” OR (“adaptation policies” AND “climate change”; articles and reviews; article title, abstract, and keywords; all types of access; from all years to the present. (Source: Scopus database, 2019)

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governance in mitigating local environmental impacts by ensuring the implementation of adaptive measures. Given that most environmental transformation processes nowadays occur within the urban perimeter, megacities have a key role in promoting a broader debate about adaptation to climate change (Di Giulio et al., 2015). The authors discuss the existing challenges and opportunities in the city of São Paulo, which holds a population of more than 12 million people and is the largest metropole in South America, bearing the second largest gross domestic product (GDP) per capita of its micro-region (IBGE, 2018). The city is taken as a representative example of other megacities in the Southern Hemisphere, all of which deal with issues like disordered expansion, precarious settlements, lack of adequate sanitation structures, environmental degradation, and exacerbated social inequalities. In an attempt to mitigate the risks posed by climate change in present and future scenarios, São Paulo has featured a set of important initiatives, such as the following: composing the Cities Climate Leadership Group (C40) – which reunites the world’s greatest cities committed to climate change mitigation and adaptation strategies; the creation of a Municipal Policy on Climate Change in 2009  – the first legislation regarding climatic strategies of a local government in Latin America, according to São Paulo’s municipality (2012); and the incorporation of adaptation measures in urban planning policies, water management, and public health (Di Giulio et al., 2015, 2018).

4 Adaptation Policies in Brazil: The Case of São Paulo In the Brazilian context, the state of São Paulo is recognized for its pioneering role in translating environmental concerns into legislation and public policies applied to its territory, quickly responding to federal initiatives, or even inspiring the creation of environmental policies adopted at the federal level (Sánchez, 2008).  Actions toward climate change adaptation depend on the political priority given to this matter. Cities in the global north that have largely incorporated climate adaptation in their agendas, such as New  York and Rotterdam, have excelled in this purpose, whereas cities in the south have mostly failed to do so (Di Giulio et  al., 2018). Although São Paulo has struggled with land management alongside urban planning and climate-related disasters, the city has great potential to implement climate change adaptation measures, especially given that it has led research on climate change for years, transcending academy and taking this discussion to the political level while bearing institutional and financial competence to enforce climate adaptation measures (Di Giulio et al., 2018). According to Di Giulio et al. (2018), actions related to climate change adaptation are often integrated – urban planning, water management, and health promotion – and can be motivated by a set of factors, such as the possibility of addressing local issues, improving urban quality of life, and developing a cooperative connection with other municipalities regarding the use of common resources. Nevertheless, the

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authors stress that too much attention has been given to the mitigation of climate-­ related risks in the past years rather than adaptation measures. The megacity of São Paulo has a series of environmental planning instruments to achieve urban sustainability, ensuring infrastructure expansion, access to services, slum reduction and urbanization, job opportunities, and environmental resource preservation and care (Ramires & Mello-Théry, 2018). Among these environmental planning instruments, we can cite the municipal ecological-­economic zoning, the river basin plan, the municipal environmental plan, the 21 local agenda, and the integrated solid waste management plan. Also, São Paulo has a Director Strategic Plan for the development and expansion of the city up to 2030 (Law no. 16.050, 2014), aiming “to order the full development of the city’s social functions and the socially just and ecologically balanced, diversified use of its territory to ensure the well-being and quality of life of its inhabitants.” Although many of these plans aren’t specifically addressed to climate change, some of their actions can be connected to climate change mitigation or adaptation. Di Giulio et al. (2018) noticed that many actions from Sao Paulo’s Director Strategic Plan are aligned to mitigation strategies, such as the following: Promoting the construction of buildings which contribute to the reduction of GHG emissions; Reducing waste generation through selective waste collection, recycling and composting; Prioritizing public and non-motorized transport as well as a bus fleet fueled by clean energy sources; Exploring the interface between mobility and land use by increasing population density along exclusive access routes for buses; Supporting compact cities; Encouraging denser land occupation in regions where there are more jobs; Establishing new economic development centers in residential areas; Creating a system of protected areas, green areas and open spaces to the protection of Atlantic Rainforests, Providing incentives for public places that will become Special Environmental Protection Zones and Creating rural areas in the city within a sustainable development plan. (Di Giulio et al., 2018, p. 240)

As soon as climate change started to be specifically addressed in the Brazilian federal legislation, São Paulo started the planning for its territory. One year after the release of the National Plan on Climate Change (Decree no 6.263, 2008), São Paulo instituted its Municipal Policy on Climate Change (Law no 14.933, 2009). Beyond the presentation of clear GHG reduction targets associated with mitigation strategies, the document also addresses adaptation in energy, waste management, health, civil works, land use, and transportation sectors. One of the most prominent initiatives was the statement that all bus systems should use non-fossil fuel up to 2018. By that time, Brazil still hadn’t released its Intended Determined Contribution to ONU – which happened in 2016 – nor the National Adaptation Plan, also released in 2016. The Municipal Policy on Climate Change also instituted the Municipal Committee on Climate Change and Ecoeconomics, which, in turn, elaborated the City Action Plan for Mitigation and Adaptation to Climate Change (São Paulo’s City Hall, 2011). The plan covers transportation, energy planning, construction, land use, solid waste, and health sectors. Examples of actions are the creation of linear parks, green fleet deployment, energy-efficient buildings, population densification programs, capture of greenhouse gases in landfills, among others. The plan

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was released at the C40 São Paulo Summit, highlighting the prominence and commitment of the megacity in addressing climate change. However, there were no clear targets or terms involving each action proposed to the megacity. Terms were descripted as “continued term,” “medium term,” or “short term.” Other programs and policies also contribute to climate mitigation and adaptation in the megacity such as the Sustainable Procurement Program (2005), the 100 green parks program to expand green areas (2008), the Vehicular Pollution Control Plan (2007), taxi fleet with cleaner fuel and motor technologies (2012), and installed solar heating systems in new buildings of a certain scale since 2007 (Di Giulio et al., 2018). The Vehicular Pollution Control Plan, the use of biodiesel in the public bus fleet, and the expansion of bicycle paths were considered successful climate initiatives (Di Giulio et al., 2018; Ramires & Mello-Théry, 2018). However, such iniciatives proved to be vulnerable to governmental interests, being retrieved or cancelled together with the Meir and political team changes.

5 Impasses to Climate Change Adaptation: Far-right Populism and its Anti-Environmental Agenda In recent years, the Brazilian environmental protection agenda has been framed by the government and its supporters as a political deadlock in the economic development of the country, especially regarding the protection of native forests and indigenous territories, with the justification that resource  conservation will impair agricultural advancement  – the flagship of economic activity in Brazil (Araújo & Campos, 2022). Although there is a consensus among scientists that climate is changing in a global scale and that it poses serious threats to humankind and other species, many groups and individuals sustain the narrative that this claim is delusive, with these groups mostly sharing some common grounds such as gender, political views, and social hierarchy (Jylhä et al., 2016). Jylhä et al (2016) refer to this skepticism wave as the “conservative white male effect,” in which white males with a more political conservative view tend to deny climate change effects more often and consistently than other people. Such effect can be better understood when considering that these individuals are inclined to neglect any belief that could threaten their life status and social dominance, given that the lifestyle of wealthy classes is one of the primary causes of environmental distress and that the risks associated with climate change are unevenly distributed, impacting more harshly the most vulnerable populations (Jylhä et al., 2016). Looking at Brazil, most conservative white voters, especially males, were from areas dominated by agrobusiness (Araújo and Campos, 2022).  Even though climate change denial has gained momentum in some countries in the current decade, including in Brazil, in general, Latin Americans seem to be the ones who hold the strongest belief that global warming is indeed a result of human

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activities (Dayrell & Urry, 2015). In the Brazilian scenario, until the late 1990s, the country remained fairly conservative regarding cutting down on carbon emissions. After this decade, however, the number of Brazilians concerned with the environment rose considerably, and skepticism toward climate change was almost nonexistent, with 94% of Brazilians having stated that global warming was a serious threat (Dayrell & Urry, 2015). For the other integrants of the BRICs block, this percentage was much inferior – China, 33% and Russia, 47% – according to Dayrell and Urry (2015). Between 2008 and 2010, Brazil’s figures of concern about climate change continued to be the highest among the 47 countries analyzed (Dayrell & Urry, 2015). Nevertheless, ¼ of the people interviewed in Dayrell and Urry’s review (2015) stated that climate change was mostly a problem to be address by future generations. Dayrell and Urry (2015) investigated the increasing concern around climate change among Brazilians during the first decade of the twentieth century. Fossil-­ fuel-­based greenhouse gas emissions (GGE) in Brazil are low compared to global standards – 1,3% of the global emissions, which are mostly related to agricultural activities, land use, and deforestation practices (IEA, 2013 apud Dayrell & Urry, 2015). The authors argue that most of Brazil’s GGE resulted from deforestation in 2005, but this scenario changed throughout the following years, so much that, in 2010, GGE due to deforestation dropped by one-third as a result of the enforcement of strict environmental regulations. Alongside those measures, around the same time, Brazil pioneered a series of low-carbon initiatives, such as extensive biofuel production and the implementation of clean transportation systems (Dayrell & Urry, 2015). According to the authors, the public opinion in Brazil has been influenced over the years by scientific and corporate events and NGO initiatives, in such a way that in the mid-2000, the Brazilian government felt compelled to take action toward climate change adaptation, longing to address such increasing concern – not only in Brazil, but worldwide. Until recently, Brazil had done well in addressing these matters, especially considering that the country has had keen environmentalists in key government positions, such as Marina Silva and Carlos Minc as Environment Ministers (2003–2008 and 2008–2010, respectively) and Carlos Nobre leading the Brazilian Panel on Climate Change (Dayrell, 2015). In the 2014 elections, the major parties running for the presidency had environmental issues and sustainable development in their agendas. In such scenario, deforestation in the Amazon dropped between 2004 and 2012 but had a notorious increase between 2015 and 2016, accompanied by a severe economic and political crisis that extends until the current days (Pereira et al., 2019), which has reflected harshly on the environment, most notably on the Amazon rainforest. As widely known, the Amazon has a decisive role in halting global warming and climate change through its capacity to serve as a carbon sink. Recent events in Brazilian policy (last 5 years) have demonstrated that this role may be compromised in the near future. Between 1996 and 2005, Brazil deforested an average of 19,500 km2/year, releasing 0.7 to 1.4 billion tons of CO2 equivalent per year into the atmosphere (Pereira

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et al., 2019). In 2012, however, deforestation was reduced to the lowest historical level as a result of the Plan of Action for the Prevention and Control of Deforestation in the Legal Amazon, launched in 2004, which set targets to reduce and control deforestation until 2020 (Pereira et  al., 2019). The figures of degradation in the Amazon started to go up again between 2014 and 2016 – an average of 25%, corresponding to 6000 km2 in 2015 and 8000 in 2016. In 2016, the Brazilian congress approved a Constitutional Amendment Proposal (PEC 41) that froze public expenditures for 20  years (El País, 2016), impairing investments in crucial areas for sustainable development, such as health, education, and environmental conservation and surveillance. According to Pereira et al. (2019), this measure affects the effective functioning of organizations that monitor the Amazon, such as the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA) and the Chico Mendes Institute for Conservation and Biodiversity (ICMBio), which can contribute to an even higher spike in deforestation rates. Since then, the social and environmental prospects for Brazil and the world have been unsettling. The Brazilian president Jair Bolsonaro, who took office in January 2019, has adopted a series of environmental-harming measures, such as loosening environmental regulation – e.g., the licensing process and the enforcement of penalties for environmental crimes, cancelling climate events and nominating anti-­ environmentalist politicians for important government positions regarding the environment and climate change, inciting the occupation and unsustainable exploration of the Amazon, and compromising indigenous peoples’ living by refusing to recognize their territorial rights. One prominent example of the lack of commitment of the Brazilian government with climate issues was the cancellation of the Climate Conference (COP-25), previously expected to take place in Brazil in December 2019. The event was cancelled by the Brazilian government upon the justification that the country lacked the necessary resources to support the event. Since the first United Nations Conference on Environment and Development, held in Rio de Janeiro in 1992 (Eco-92), Brazil has directed important efforts toward environmental conservation. However, the latest trends in the country’s climatic policies indicate that this protagonism is threatened, accompanying a fast-pacing change in Brazil’s current political and environmental scenario, which, in turn, threatens environmental balance and climate regulation worldwide.

6 Conclusion Climate change denial holds back climate change adaptation and resilience building measures, and mainly permeates groups aligned with far-right ideologies, correlating  positively with three major social  factors: conservative political views, being male, and social dominance orientation – a scale of preference for in-group dominance over other social groups (group-based hierarchies), according to Pratto et al.

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(1994). This contributes to the perpetuation of group inequalities, making it difficult to reduce social vulnerabilities, and thus impairing effective actions toward sustainable climate change adaptation actions. This conclusion is in accordance with the dominant social structure seen in unequal countries likeBrazil, demonstrating that social-cultural context plays a major role in moderating environmental perception. Regarding the achievement of the Sustainable Development Goals through climate change adaptation, those are still not very well consolidated. The biggest challenges in this respect relate to lack of adequate governance – notably in megacities, which concentrate a set of environmental and social hardships; persistent socioenvironmental vulnerability of less privileged groups – especially in developing countries, fueling climate change skepticism worldwide and diluting individual cooperation toward adaptative actions. While we agree that urban governance is essential to guide the adaptative responses to climate change, as posed by Di Giulio et al. (2015) when presenting the case of São Paulo, we also believe that it is indispensable to consider the role of individual decision-making in creating and implementing adaptation policies, taking into account the subjective dimension of sustainable development, especially in the face of the current pessimistic scenario – which is evolving rapidly and differs from the scenario of 10 years ago, when most adaptative policies began to be evaluated and designed. In this sense, it is important to consider that along with political initiatives, individuals can also take on an active role in promoting social and environmental change and should therefore be seen not only as a result of multiple determinants but also as a social actor (Maciel & Alves, 2015). In accordance with this perspective, Bradley and Reser (2017) sustain that it is important to understand the psychological process of coming to terms with the threats posed by climate change, which could be key in improving understanding and cooperation when attempting to implement adaptative policies in various governance levels.

References Araújo, B. & Campos, F. (2022). Authoritarian Populism and the Environment in Brazil: Framings of Jair Bolsonaro’s anti-environmental discourse in national and international editorials, https:// doi.org/10.14195/2183-­5462_40_7 Bazrkar, M. H., Zamani, N., Eslamian, S., Eslamian, A., & Dehghan, Z. (2015). In W. Leal Filho (Ed.), Urbanization and climate change, handbook of climate change adaptation (pp. 619–655). Springer. Berbés-Blázquez, M., Mitchell, C. L., Burch, S. L., & Wandel, J. (2017). Understanding climate change and resilience: Assessing strengths and opportunities for adaptation in the Global South. Climatic Change, 141(2), 227–241. https://doi.org/10.1007/s10584-­017-­1897-­0 Bradley, G. L., & Reser, J. P. (2017). Adaptation processes in the context of climate change: A social and environmental psychology perspective. Journal of Bioeconomics, 19(1), 29–51. https://doi.org/10.1007/s10818-­016-­9231-­x Brazilian Institute of Geography and Statistics. (2018). Available in: https://cidades.ibge.gov.br/ brasil/sp/panorama. Accessed 29 Aug.

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Chalabi, Z., & Kovats, S. (2014). Tools for developing adaptation policy to protect human health. Mitigation and Adaptation Strategies for Global Change, 19(3), 309–330. https://doi. org/10.1007/s11027-­014-­9544-­9 Dayrell, C., & Urry, J. (2015). Mediating climate politics: The surprising case of Brazil. European Journal of Social Theory, 18(3), 257–273. https://doi.org/10.1177/1368431015579962 Decree no. 6.263, of 21 November 2007. (2008). National Plan on climate change – NPCC. Federal Government. Inter-ministerial Committee on Climate Change. Retrieved on 19 September, 2019, from: https://www.mma.gov.br/estruturas/smcq_climaticas/_arquivos/plano_nacional_ mudanca_clima.pdf Di Giulio, G. M., Vasconcellos, M. d. P., & Ribeiro, W. C. (2015). Climate change, risks and adaptation in the megacity of São Paulo: A perspective from human sciences. Encontro Nacional Da Associação Nacional de Pós Graduação e Pesquisa Em Ambiente e Sociedade, 1–20. Retrieved from https://bdpi.usp.br/single.php?_id=002885860&locale=en_US Di Giulio, G. M., Bedran-Martins, A. M. B., Vasconcellos, M. d. P., Ribeiro, W. C., & Lemos, M. C. (2018). Mainstreaming climate adaptation in the megacity of São Paulo, Brazil. Cities, 72(January 2017), 237–244. https://doi.org/10.1016/j.cities.2017.09.001 El País. (2016). Entenda o que é a PEC 241 (ou 55) e como ela pode afetar sua vida (understand what is the PEC 241 (or 55) and how it can affect your life). Available in: https://brasil.elpais. com/brasil/2016/10/10/politica/1476125574_221053.html. Accessed 2 Sept. Henrique, K.  P. & Tschakert, P. (2019). Contested grounds: Adaptation to flooding and the politics of (in)visibility in São Paulo’s eastern periphery, Elsevier, https://doi.org/10.1016/j. geoforum.2019.04.026 Intergovernmental Panel on Climate Change (IPCC) (2022). Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, https://doi.org/10.1017/9781009325844 Jylhä, K. M., Cantal, C., Akrami, N., & Milfont, T. L. (2016). Denial of anthropogenic climate change: Social dominance orientation helps explain the conservative male effect in Brazil and Sweden. Personality and Individual Differences, 98, 184–187. https://doi.org/10.1016/j. paid.2016.04.020 Law no. 14.933, of 05 June 2009. (2009). Municipal policy on climate change. Municipal Official Gazette. Law no. 16.050, of 01 August 2014. (2014). Urban development policy and Director Strategic plan for Sao Paulo municipality. Municipal Official Gazette n. 59. Lesnikowski, A. C., Ford, J. D., Berrang-Ford, L., Barrera, M., & Heymann, J. (2015). How are we adapting to climate change? A global assessment. Mitigation and Adaptation Strategies for Global Change, 20(2), 277–293. https://doi.org/10.1007/s11027-­013-­9491-­x Maciel, T. M. d. F. B., & Alves, M. B. (2015). A importância da psicologia social comunitária para o desenvolvimento sustentável The importance of community psychology in sustainable development La importancia de la psicología comunitaria para el desarrollo sostenible. Pesquisas e Práticas Psicossociais, 10(2), 272–282. Noble, I.  R., Huq, S., Anokhin, Y.  A., Carmin, J.  A., Goudou, D., Lansigan, F.  P., et  al. (2015). Adaptation needs and options (pp.  833–868). Climate Change 2014 Impacts, Adaptation and Vulnerability: Part A: Global and Sectoral Aspects. https://doi.org/10.1017/ CBO9781107415379.019 Obermaier, M., & Rosa, L.  P. (2013). Mudança climática e adaptação no Brasil: uma análise crítica. Estudos Avancados, 27(78), 153–176. Pereira, E.  J. de A.  L., Ferreira, P.  J. S., Ribeiro, L.  C. de S., Carvalho, T.  S., & Pereira, H.  B. de B. (2019). Policy in Brazil (2016–2019) threaten conservation of the Amazon rainforest. Environmental Science and Policy, 100(May), 8–12. https://doi.org/10.1016/j. envsci.2019.06.001 Pratto, F., Sidanius, J., Stallworth, L. M., & Malle, B. F. (1994). Social dominance orientation: A personality variable predicting social and political attitudes. Journal of Personality and Social Psychology, 67(4), 741–763. https://doi.org/10.1037/0022-­3514.67.4.741

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Prefeitura do Município de São Paulo (São Paulo’s City Hall). (2011). Diretrizes para o Plano de Ação da cidade de São Paulo para mitigação e adaptação às mudanças climáticas. São Paulo Ramires, J. Z. S., & Mello-Théry, N. A. (2018). São Paulo: Advances and setbacks, after almost a decade of climate change policy. Revue franco-brésilienne de géographie, 38, 10p. Ribeiro, W. C. (2008). Impactos das mudanças climáticas em cidades no Brasil. Revista. Parcerias Estratégicas, 27, 298–322. Sanchez, L. E. (2008). Avaliação de Impacto Ambiental: conceitos e métodos. São Paulo. United Nations. (1992). United Nations Framework Convention on Climate Change. 62220.

Chapter 15

Climate Change, Food Security, and Resilience: Hydrologic Excess and Deficit Measurement Omar-Darío Cardona, Gabriel Bernal, and María Alejandra Escovar

Abstract  Hydrologic extremes, in terms of floods and droughts, can become catastrophic events for vulnerable underdeveloped communities. Disaster risk management is a useful tool to understand risk drivers and bring relevant information to develop mechanisms to reduce vulnerabilities and potential damages, building resilience in the long term. This chapter presents an innovative probabilistic risk assessment methodology to quantify risk under conditions of water excess and deficit. The results of the drought risk profile for three countries in Central America show how the outcomes of the risk assessment methodology provide robust results to quantify risk in terms of potential losses of crop production and are used to analyze the linkages between risk assessment, food security, and resilience building. Keywords  Probabilistic risk assessment · Crops vulnerability · Agricultural drought · Stochastic drought modelling · Stochastic flood modelling

1 Introduction Hydrological extremes – droughts and floods – are natural hazards that can lead to losses in the agriculture sector, from agroindustry to subsistence agriculture and livestock production. In the context of climate variability and climate change, there is no confidence on how exactly climate change will impact  – directly or O.-D. Cardona (*) Instituto de Estudios Ambientales, Universidad Nacional de Colombia, Manizales, Colombia e-mail: [email protected] G. Bernal Departamento de Ingeniería Civil y Agrícola, Universidad Nacional de Colombia, Bogotá, Colombia M. A. Escovar INGENIAR Risk Intelligence, Bogotá, Colombia © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_15

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indirectly – agriculture and food systems or how their vulnerabilities can transform (Meybeck et al., 2012). Moreover, current weather conditions can be potential hazards to vulnerable socioeconomic systems and frequently are translated into disasters in terms of floods or droughts with their corresponding losses. Disaster risk is the result of the interaction between hazards and the conditions that make exposed elements  – people or assets  – vulnerable. As mentioned by Wilhite (1993) for the case of droughts, disaster impacts depend not only on the magnitude of the natural event but also on the societal vulnerability at the moment the event occurs. Understanding the key drivers that lead to crop losses enables an informed prioritization of disaster risk reduction and adaptation strategies to better protect farming systems and the population that depends on them (Lesk et al., 2016). Following these considerations, this chapter analyzes the concepts of climate change, food security, and resilience under the disaster risk lens, which brings relevant information to develop mechanisms to reduce vulnerabilities and potential damages. The objective of this document is to present an innovative probabilistic model to quantify risk underwater excess and deficit conditions developed by INGENIAR Risk Intelligence. It is a valuable approach to facing the main challenges of the agriculture sector: food security and climate change adaptation (Meybeck et  al., 2012). The proposed methodology follows a robust science background that consciously embraces the complexity and uncertainty of natural systems along with human vulnerabilities. The outcomes of this research provide robust results to quantify risk in terms of potential losses and support decision-making processes. This methodology focuses on the first step for efficient risk management: risk identification, quantification, and understanding. Risk knowledge is a fundamental component of sustainability and development transformation and is a path to building resilience. Event forecasting and early warning are out of the scope of this methodology, although they are important risk management tools, especially in terms of preparedness. In the first section of the document, the risk assessment methodology is presented in three main components: hazard, exposure, and vulnerability. In the second section of the study, the results of the drought risk assessment for El Salvador, Guatemala, and Honduras are presented. This case study provides the elements to analyze and discuss the linkages between risk assessment, food security, and resilience building.

2 Methodology Probabilistic risk assessment, for hazards such as floods and droughts, produces important information to develop mechanisms to reduce vulnerabilities and potential damages (Cardona, 1989; Ordaz, 2000). Risk assessment is divided into three main components: hazard, exposure, and vulnerability. According to the definition by UNDRR (2015), the hazard is associated with the potential damaging physical

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events (with a relevant intensity) that may cause disruptions in economic and social systems; exposure is the collection of exposed assets and people to hazards; and vulnerability are the physical, social, economic, and environmental conditions which reflect the susceptibility or predisposition of a community to be affected by the hazardous events. Interactions between hazard, exposure, and vulnerability that translate into risk can be evaluated from a retrospective approach – considering past events – or from a prospective approach, using probability theory to estimate potential events and damages. Risk assessments restricted to past events limit the scope of action, as there is insufficient recorded data and short-term memory related to catastrophic events to estimate potential losses from future hazard occurrences. On the other side, a prospective approach with a probabilistic framework analyzes the potential events that may happen but have not happened yet and includes uncertainties in hazard (frequency or intensity of events, climate change), vulnerability (probable damage related to event intensity), and risk (probable losses after the materialization of events). The main outputs of the prospective risk assessment are integrated hazard maps and loss estimation, typically reported in terms of economic losses but can also be reported in social or environmental metrics. The probabilistic risk assessment outcomes are useful for interdisciplinary collaboration and can be the source of data for water and land-use planning, development of financial protection mechanisms, and research on applications for human development, poverty reduction, and climate change adaptation initiatives (Gaaloul et al., 2021). The following section presents details, for each risk component, of the proposed methodology for hydrologic extremes events: floods and drought. Firstly, the hazard is defined as a set of stochastic scenarios that describe the spatial distribution, frequency of occurrence, and randomness of the intensity of the hazard in the region of interest. Later, the database of exposed elements is generated for the built environment (i.e., infrastructure, houses) or the agriculture sector (i.e., cropland, livestock) with data on location, characteristic elements, and valuation. Then, for each exposed element in the database, vulnerability is defined as a function that relates hazard intensity and damage for the case of the built environment or as the crop yield response to water for the case of the agriculture sector. Finally, risk is estimated in terms of potential economic or production losses derived from multiple hazard scenarios that have not happened yet.

2.1 Probabilistic Assessment of Meteorological Hazards: Floods and Droughts Within the methodology, hazard is defined as a set of events that fully represents the potential hazardous phenomenon. The collection of hazard scenarios is generated in a stochastic manner, which fully represent all the ways how the hazard can manifest itself in the analyzed territory. Each scenario contains a defined occurrence

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Fig. 15.1  Drought and flood risk assessment methodology

frequency and the spatial distribution of the parameters that define the probability distribution of intensities of the hazard. The measure of intensity corresponds to the physical variable that represents the severity of the phenomenon. In the case of floods, the intensity measurements commonly used are flood depth and flow velocity. For droughts, severity and duration are used to characterize events. Hazard assessment is particular for each case study. The scale and resolution, of both inputs and outputs, depend on the quality of available data and the purpose of the assessment. A visualization of the methodology is shown in Fig. 15.1. After gathering the appropriate information, hazard assessment for floods and droughts starts with the characterization of the local weather conditions. Then, with a weather generator, a set of stochastic precipitation and temperature time series are generated for multiple years, which represent the potential weather conditions that can happen in the future but are not a forecast. For the case of droughts, simultaneous conditions of low precipitation and high temperature are identified from the stochastic time series as presented in Bernal et al. (2017). On the other hand, in the case of floods, heavy rainfall events that last one or more days are identified. In both cases, climate change can be incorporated to compare how hazard changes under uncertain future climate. 2.1.1 Stochastic Generation of Rainfall Events The main input for the stochastic generation of rainfall events is historical climate data of the region of interest, which consists of daily precipitation and daily maximum, minimum, and mean temperature. Daily summary reports are collected from gauge stations distributed in the region or global datasets processed from the reanalysis of satellite records. Precipitation and temperature records are obtained for the longest recording period and the largest number of stations available in the study

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area. Afterward, a quality check of the input data is performed to remove inconsistent values and complete missing records. Then, for each day of the year, the algorithm finds the probability distribution that better fits historical records. Stochastic time series are generated using random numbers and the probability distribution parameters fitted for each day. Thus, random series of climate data are produced for each of the stations in the study area. Temporal and spatial correlation is considered to avoid abrupt changes in both precipitation and temperature values. Temporal autocorrelation indicates the correlation of a variable with its own future and past values (Wilks, 2006); spatial correlation represents the occurrence of similar conditions at multiple stations in the study area. Statistical analysis of rainfall series can be a challenge because of the nature of the variable. Considering the temporal variability of rain in many areas of the world, special consideration must be taken for no-rain days within the series. Values equal to zero can mislead the probability distribution fitting process. Then, the definition of the probability density function is divided into two parts: (i) the probability when precipitation is zero (P0) and (ii) the probability when precipitation is greater than zero (1-P0). The probability of a no-rain day is defined as the following: P= 0

n # drydays = N # total days in records

(15.1)

By following this procedure, the resulting precipitation series maintain the historic ratio of no-rain/rain days, according to the precipitation regime of the area. If the probability density function does not include this variation, dry days are not obtained in the simulated random series (Fig. 15.2). To illustrate the methodology, the results for one station in Guatemala (Cardona et al., 2018) are shown as follows. A total of 1000-year simulations of stochastic rainfall and temperature series were generated after selecting the best-fitted distribution for each day of the year. The software Drought Pro (Bernal et al., 2018) was used to fit the probability distributions and simulate precipitation and temperature series. It is worth noting that these 1000 years of simulations do not correspond to a

Fig. 15.2  Probability density function and cumulative density function considering no-rain days. P0 is the probability of no-rain days

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forecast; they are random values that have been correlated to fit and represent the climate of the study area and provide more information – compared to limited historical records – about possible drought or heavy rainfall events. These simulated series are the main input for the evaluation of probabilistic drought or flood risk, from which a greater number of stochastic events can be obtained to model hazards. The proposed methodology results in synthetic series with a good fit to historical data, which indicates that the random series adequately preserves the average climate characteristics of the area. Figure  15.3 presents a comparison between the historical and the simulated time series of precipitation and temperature in the station. The graphs show the average values of daily and monthly values for precipitation and mean temperature. For the case of precipitation, mean daily values are less than 10 mm per day and monthly values go up to 180 mm per month. The graphs show consistency between the historic and simulated data, where the root-mean-square error (RMSE) for daily values is 0.5 mm and for monthly values is 6.9 mm. When daily values are aggregated to monthly totals, the simulated data follows the same precipitation regime as the historical data. September and October are the wettest months, while February is the driest. For the mean temperature, daily values vary between 16 °C and 24 °C, and monthly means are between 18 °C and 23 °C. The uniformity between historic and simulated data is characterized by low RMSE values, which are 0.5 °C for daily data and 0.6 °C for monthly data.

Fig. 15.3  Mean daily (left) and mean monthly (right) data for historic (1981–2010) and simulated series for precipitation (top) and mean temperature (bottom)

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Fig. 15.4  Yearly precipitation boxplot for historical and simulated data. The graph shows the outliers obtained in the simulated series (points above 1500 mm/year), which represent events that have not been recorded before

One of the advantages of the methodology is that the simulated series include outliers of precipitation and temperature which have not happened yet but might occur with a low probability in the future. These climate outliers can configure drought or heavy rainfall scenarios not recorded before. Figure 15.4 shows the boxplot of data from historical and simulated precipitation data for yearly totals. The box height is the interquartile range (or the difference between the third and first quartile), the band inside the box is the second quartile or median, and whiskers above and below the box represent the minimum and maximum values. Points above the maximum value are outliers, which are three times the interquartile range or move above the third quartile. Thus, according to the boxplot results, simulated data maintains the median (around 900 mm/year), but minimum and maximum precipitation data have a wider range, including outliers that in one of the 1000-year simulation represent an increase of more than 50% in rain compared to the highest yearly precipitation recorded between 1981 and 2010. 2.1.2 Heavy Rainfall and Flood Events As mentioned before, this methodology has been applied in previous studies including a probabilistic assessment of flood hazard for the Rio Yaguaron basin in Uruguay (Cardona et al., 2017). To illustrate the methodology, results from this case study are presented. To assess heavy rainfall hazard in the Rio Yaguaron basin, a total of 1000 simulations were run to generate an equivalent of 1000 years of stochastic precipitation values. These simulations cannot be considered a precipitation forecast but a series of data that statistically represent the historic precipitation regime of the area. Figure  15.5 shows the adjustment of the mean daily precipitation values for the historic record in the period 1981 to 2010, and the stochastically generated series, for the same location. The graph shows how the methodology results in a simulated

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Fig. 15.5  Daily precipitation average for the historic series (1981–2010) and the simulated series (1000 simulations) (Cardona et al., 2017)

series with a proper fit to the mean historic records, which implies that the random series keeps the climate normal mean but also includes scenarios that have not happened yet. A heavy rainfall event is defined by the following criteria: • The minimum number of stations that records rainfall within the study area. This number depends on the location and density of stations within the basin. The rainfall isolines are defined from the events identified in the stations that record precipitation for each event. • The minimum threshold for precipitation value to consider the event as heavy rainfall and not a moderate event. This value must be exceeded in at least the minimum number of stations to define a scenario (e.g., records higher than 20 mm in 24 h). • The average threshold that considers a minimum value for the mean rainfall in the number of stations that exceed the minimum threshold. This criterion is used to ensure that rainfall of considerable intensity occurs in a large area and is not limited to punctual heavy rains. To illustrate the outcomes of the methodology, Fig. 15.6 shows different heavy rain events obtained for the Rio Yaguaron basin in Uruguay. The values in the maps represent the total daily rainfall for a heavy rain scenario. These events correspond to rainfall records identified in more than 90% of the stations (minimum number of stations was 45 of 48 stations), 100 mm/day minimum threshold for rainfall in a station, and 100 mm/h average rainfall for the stations that recorded rain. These are extreme precipitation conditions for the area. One of the advantages of using the stochastic generation of precipitation series, in multiple stations within the study area, is that the spatial distribution of rain is derived directly from the simulated data. There is no need to establish geometric patterns of representative events to define the storm’s centermost probable location.

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Fig. 15.6  Spatial distribution of heavy rain scenarios for Rio Yaguaron basin (Cardona et  al., 2017). All the generated scenarios are unique and mutually exclusive

The spatial interpolation in this study consists of applying the Kriging geostatistical method (Li & Heap, 2008), adjusting the variogram of the input data to a Gaussian type. As shown in the previous maps, the occurrence of heavy rains in the basin changes considerably in intensity and spatial distribution. There are not two equal heavy rains in the full set of events. To complete the model, the temporal distribution of rain is calculated from the Huff curves (Rao & Kao, 2006). 2.1.3 Water Deficit and Drought Events Droughts, different from other natural hazards, accumulate slowly over an extended period; in many cases, it takes years until the termination of the event, with nontangible impacts which spread over large geographical areas (Wilhite, 1993). Wilhite and Glantz (1985) defined drought in four categories: meteorological, hydrological, agricultural, and socioeconomic. The first three approaches define drought as a physical phenomenon, while the socioeconomic drought is defined in terms of the supply and demand of water in the social system (Mishra & Singh, 2010). Meteorological droughts assess local below-the-average rainfall conditions that last for an extended period. Agricultural drought links the effects of the meteorological drought with the impacts on agriculture of precipitation shortages, higher

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evapotranspiration rates, and soil water deficits, among others. Hydrological droughts are defined on watershed or river basin scales and assess the effects of precipitation shortage on surface and subsurface water supply. It is difficult to identify when drought starts and ends, as impacts may be difficult to recognize before damage is caused. Thus, indicators and indices are used to describe droughts (World Meteorological Organization (WMO) & Global Water Partnership (GWP), 2016). Indicators are variables that describe local conditions such as precipitation and temperature. Drought indices are mathematical values that quantify drought severity using the mentioned indicators. The probabilistic hazard assessment methodology – described in this chapter – uses indices reported in the literature that considers precipitation and temperature as the main drought indicators, mainly the Standardize Precipitation Index (SPI) (Mckee et  al., 1993), the Standardize Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano et al., 2010), and the Reconnaissance Drought Index (RDI) (Tsakiris et al., 2007). These indices represent meteorological droughts, as no soil moisture indicators are included to represent agriculture droughts. Within the proposed methodology, soil characteristics are included in the crop vulnerability module. Drought indices are computed for the precipitation and temperature stochastic time series, generated in the previous step of the hazard assessment, for each station considered in the area of interest. From these results, regional drought events can be identified within the stochastic data of simultaneous conditions of lack of precipitation and high temperature in multiple stations. The objective is to identify drought conditions that impact a certain extension of the territory. Local, national, or regional drought events can be identified from the stochastically generated data, following the resolution of data and scope of the assessment. The extension of drought is defined as a fraction of stations under drought conditions from the total. For example, a regional drought, in spatial terms, is an event in which the number of stations with indices below the threshold (i.e., −1) is higher than a certain fraction (i.e., 50%). All regional droughts are considered as individual drought scenarios that have a frequency of occurrence of one in n years of simulation. A visual representation of the identification of regional droughts is shown in Fig. 15.7, where each station has an index time series and scenarios are the result of simultaneous drought conditions in all the stations. From the indices’ results, each drought event can be represented according to its severity, duration, and intensity (Mishra & Singh, 2010). With a set of drought scenarios, spatially distributed drought scenarios for the duration, severity, and intensity for the complete study area are generated with spatial interpolation techniques. For each case, the criteria to define a regional drought – index value threshold and the number of stations with simultaneous drought reports – are selected according to the scope of the use of the results. Index values closer to zero identifies mild drought events that can be also seasonal dry periods, while index values closer to −1.5 identify severe drought events, which are less frequent and more intense (Banimahd & Khalili, 2013). A regional drought event, one of a large number of stations with simultaneous drought reports, is less likely to occur than events considering a small group of stations, which have a local impact. For each one of the resulting regional drought events, spatial interpolation is

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Fig. 15.7  The identification of regional droughts is done by identifying periods of time in which the drought index threshold is exceeded simultaneously in several stations located within the study area (Bernal et al., 2017)

performed using Kriging methods to compute severity, duration, and intensity values obtained for each station. Following a probabilistic hazard approach (Cardona et  al., 2012), integrated hazard maps can be generated from a large number of regional drought events, which are a great tool to communicate risk. It is important to consider certain aspects of the use of indices and drought modelling. Firstly, the selection of the index to use, as well as the definition of the threshold to define when a drought occurs, depends on the criteria of the modeler. There is not a single index that properly defines droughts around the world, and thresholds are closely related to the application of the hazard assessment and risk tolerance of the model users. So, as drought modelling is complex, the results of a hazard assessment are the product of the modeler inputs. In this case, the methodology seeks extreme events that are not related to normal seasonal variation of precipitation and temperature regimes. The final goal is to select uncommon events that may have important impacts on agriculture. 2.1.4 Effects of Climate Change on Hazards The Intergovernmental Panel on Climate Change in the Assessment Report AR5 concluded that climate systems like the atmosphere and ocean have warmed, snow and ice amounts have diminished, and sea level has risen (IPCC, 2014, p. 2). Then, the imperative question to ask is as follows: can climate change affect the occurrence of future droughts or floods? Changes in the frequency, magnitude, spatial extent, and duration of hydrologic extreme events  – droughts and floods  – are expected under climate change projections. From a risk knowledge approach, this question must be answered based on the results of robust models that consider uncertainty and should not be limited to the expected outcome based on suspicion.

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Great advances in climate modelling have happened recently such as complex numerical models that represent the response of the global climate system to increasing greenhouse gas concentration. These general circulation models (IPCC, 2013) include multiple variables within models that seek to represent complex biochemical and physical processes; however, they are not necessarily fully understood or represented, which might result in uncertain outcomes. The proposed methodology analyzes the general circulation models (GCMs) to establish the potential changes in temperature and precipitation. AR5 includes more than 60 GCMs from 26 research centers worldwide. Figure 15.8 shows the multiple projections on change in precipitation and temperature in a certain location within Guatemala for the GCMs included in AR5. Temperature changes vary from 0 °C to 1.8 °C for the mean projections of 2011–2040 and between 0 °C to 5.5 °C for the mean projections of 2071–2099. On the other hand, the GCMs do not agree on changes in precipitation, as some models project dryer weather, with a reduction of up to a 60% in precipitation levels, while other models project more rainfall with a 60% increase for the mean values of the 2071–2099 period. The dispersion of the projected changes in temperature and precipitation shows the high uncertainty related to climate change modelling. These changes are expected, but we are not certain how these changes will manifest in the future. Therefore, multiple approaches to include climate change can be adopted. The proposed hazard model can include the effects, projected by climate models, of future changes in temperature (cooler or warmer areas) and changes in precipitation (increase or decrease of frequency and intensity of rain). Given the dispersion of global circulation models, the model that best fits the baseline climate (1981–2010) should be selected. The proposed methodology identifies the model whose calibration results in history best fit the climate records in the area. The aim is to select the model that best replicates past conditions to reduce the uncertainty of projections for the future. To carry out this validation process, the temperature and precipitation values ​​corresponding to the base period (given by each of the GCM) are compared with the values ​​of the climate database. The GCM that minimizes the differences between the historical records and the predictions in the greatest extent of the

Fig. 15.8  Projected changes in temperature (left) and precipitation (right) daily means for AR5 GCM in Guatemala

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territory is selected. Then, the stochastic climate series are adjusted to include the future projections on temperature and precipitation from the most adequate GCM model. The objective of the proposed model is to get results of drought risk assessments that can be compared and establish how rising temperatures and decreasing rainfall can increase the severity and frequency of hydrological extremes. The hazard assessment includes the evaluation of the four Representative Concentration Pathways (RCP) or greenhouse gas concentration trajectories. To illustrate the effects of climate change on hazard intensity, the following figures show the integrated drought maps for Guatemala, El Salvador, and Honduras. These maps are the result of the integration, using the appropriate arithmetic, of the complete set of drought scenarios generated for the study area, for the normal weather (1981–2010), and climate change scenarios for multiple RCPs. These maps allow us to compare hazard intensities with different return periods and weather scenarios and establish which locations are in general under the highest or lowest danger. Figure 15.9 presents the integrated maps for drought severity; Fig. 15.10 presents the integrated maps for drought duration, and Fig. 15.11 presents the maps for intensity (ratio between severity and duration) for 20- and 50-year return periods for the current weather and climate change scenarios. The integrated hazard maps show, in a consistent but nonlinear way, that the areas close to the dry corridor are more prone to droughts. Severity Duration Intensity The previous uniform hazard maps are the addition from all potential individual drought events that may occur in an infinite timeline, not unique events that can occur at one point in time. They do not represent a single event that may occur, but instead, they show the effects of all possible events that may occur in the future. These maps give a broader view of the drought hazard and show the implications this hazard has in both spatial and temporal dimensions. With these maps, stakeholders can measure and communicate hazards that, can be an input for decision-­ making, like the definition of land use regulations or irrigation systems considering the drought knowledge.

2.2 Crop and Livestock Exposure and Vulnerability 2.2.1 Exposed Elements Database for the Agriculture Sector Exposed elements are geographically referenced assets that are susceptible to being affected by the occurrence of a hazardous phenomenon. For the risk assessment for the agriculture sector, the exposed elements are crops located in the area where the

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Fig. 15.9  Integrated hazard maps for drought severity for 20- and 50-year return periods. Maps a and b show the current weather conditions, and maps c to h show the conditions under climate change scenarios

drought or flood hazard was estimated. For each exposed element or cultivated land unit in the region under analysis, it is necessary to know the characteristics of the crop that is typically grown in that location. That information includes the type of crop, its seasonality, and the area sown (Fig. 15.12). Additionally, information on

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Fig. 15.10  Integrated hazard maps for drought duration for 20- and 50-year return periods. Maps a and b show the current weather conditions, and maps c to h show the conditions under climate change scenarios

typical yields (product weight produced per unit area) is also required. This information must be obtained from official sources. Crop-specific parameters that are needed to complete the exposed elements database and that are inputs for the vulnerability module of the drought risk assessment include the crop calendar, yield, and economic valuation.

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Fig. 15.11  Integrated hazard maps for drought intensity for 20- and 50-year return periods. Maps a and b show the current weather conditions, and maps c to h show the conditions under climate change scenarios

Another necessary variable for drought risk assessment is the capacity of the soil to retain water, which depends to a great extent on its texture. The size of the soil particles, or texture, is defined according to the content of sand, silt, and clay. This is how sandy soils have little capacity to retain water due to their structure of coarse

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Fig. 15.12  Data requirements for the exposure module for drought risk assessment. Each land unit must be fully characterized in the exposed element database

particles, while soils with fine particles retain water in micropores and have a greater field capacity. 2.2.2 Crops’ Response to Water The vulnerability concept encloses the conditions determined by physical, social, economic, and environmental factors or processes which enhance the susceptibility of an exposed element to the impact of hazards (UNISDR, 2015, Chapter 31; Cardona 2004, 2011). For the agriculture sector risk assessment, crop vulnerability is the yield loss suffered by the crop during an extended period of water shortage or excess (FAO’s Irrigation and Drainage Paper No. 66 Crop yield response to water by Steduto et al., 2012b). Then vulnerability models are different for each crop and are independent of the occurrence and frequency of the hazard (Quijano et al., 2015). The crop yield response to water, which in this proposed methodology follows the FAO’s approach, assesses parameters that model the interaction of the crop with soil and air systems in two stages: (1) optimal conditions, yield formation with no limits in nutrition and water resources for the plant; and (2) limited conditions, yield formation under water stress. The crop biomass is calculated based on the amount of water transpired, and the crop yield is computed as the fraction of biomass that goes into the harvestable parts of the crop. The model is divided into the following components: (i) climate (temperature, precipitation, evaporative demand, and carbon dioxide concentration), (ii) crops (development, growth, and yield processes), (iii) soil (water and salt balance), and (iv) management (agricultural practices). For a detailed explanation of each component, see FAO’s Manual (Steduto et al., 2012a). The model is appropriate and interesting for drought risk assessment because of the following: • The model relates a reduction in biomass to the reduction in yield, and therefore, higher economic losses are associated with drought hazard.

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• The model complements the hazard assessment by including the effect of soil moisture anomalies and crops’ physiological response to water deficits. • The model can provide results at a daily timescale, which better represents the dynamics of crop response to water in different growth stages. This feature is convenient as weather parameters used to calculate drought hazard are also assessed on a daily timescale. • The model fully incorporates climate change. It includes the concentration of carbon dioxide concentrations in the atmosphere and its changes in time. Also, biomass production can be estimated for precipitation and temperature conditions under climate change scenarios. • FAO has established standard crop parameters, as well as their calibration and validation methods. • It is possible to include modifiers related to agriculture practices (i.e., irrigation or fertilization), according to data availability. In general, the crop-water model estimates the impacts of lack of water – in the case of droughts – or lack of soil aeration, in the case of floods, in canopy growth, stomatal conductance, canopy senescence, root deepening, and harvest index. The model follows the crop growth stages (vegetative, flowering, yield formation, and ripening) as deepening of roots, growing foliage, and accumulating biomass (including distinct phenological stages for herbaceous or forage crops) and relates to the total amount of water transpired. The model parameters are the following: phenology, rooting depth, canopy cover, soil evaporation, biomass production, and harvestable yield. Figure 15.13 shows how the five processes can be affected by water

Fig. 15.13  Schematic representation of the crop response to water stress, considering green canopy and root growth and biomass and yield formation (Fig. 1.2a in Raes et al., 2011, Chapter 1)

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stress conditions, calculated in a daily time step. See AquaCrop Reference Manual (Raes et al., 2011; Steduto et al., 2012a) for more details. The main outputs of the vulnerability module are the potential yield and actual yield, calculated for each crop in each cultivated land unit, under the climate conditions of each stochastic hazard scenario.

2.3 Probabilistic Risk Assessment The quantification of the probable losses due to hazards is the main output of the probabilistic risk assessment. Probable losses are computed from the potential damages that the agriculture sector or the built environment can suffer during the occurrence of events that collectively describe the hazard. The fully probabilistic approach identifies geographic areas at risk incorporating the uncertainty of the natural phenomena and exposure and vulnerability of the system. Economic losses are modelled as random variables, which define their probability distribution. The analytical framework for probabilistic risk assessment has been used in seismic risk assessment (Cardona, 1989; Cardona et  al., 2012; Ordaz, 2000) and other hazards like droughts (Bernal et al., 2017; Quijano et al., 2015). Disaster risk assessment includes (i) the uncertainty associated with the probability of occurrence of the hazardous event, (ii) the spatial variability of the intensity of each hazard scenario, and (iii) the loss for each exposed element given its vulnerability. The loss exceedance curve, shown in Fig.  15.14, has all the relevant risk 0.001

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information needed to define the occurrence process of events that may cause losses to exposed elements, including the frequency and the mean return period at which a loss exceeds a specific value. Additional risk metrics used in this work are the Average Annual Loss (AAL) and the Probable Maximum Loss (PML). These metrics are individual figures used to communicate risk assessment results or as an input in the decision-making process (Cardona et al., 2012). The AAL is the equivalent to an annual payment that would be needed to compensate the accumulated losses in a long enough timeframe, and the PML is the set of loss values for each long return periods that are presented as a curve. As mentioned before, the hazard is represented as a set of events, which are mutually exclusive and collectively describe all the possible intensities of the phenomena in the area. For each hazard event, a loss probability distribution is determined for each of the assets included in the exposure database. Later, with the proper arithmetic, as losses are random variables, the sum of the probable losses is computed for all the events and all the exposed elements, considering the correlation that exists among them. When estimating the exceedance rate of catastrophic events, in which large losses are expected, the number of events plays an important role in the uncertainty of the results. With few events, for example, considering only events recorded in history, the variance is greater than when considering a large number of events obtained from stochastic generation. Therefore, for the risk assessment result to be statistically sufficient, many simulated hazardous events must be used to reduce uncertainty. In general terms, the quantification of the impact of an event can make a distinction between damage and loss (FAO, 2017). Damage is the total or partial destruction of physical assets or infrastructure and is expressed in terms of a replacement cost. Loss refers to the changes in economic flows occurring because of a disaster, such as the decline of income because a productive activity is interrupted. For the drought or flood risk assessment for the agriculture sector, the probable loss is related to the reduction in production income (loss of profits) of crops due to the reduction in yield of each cultivated land. Contrarily, for flood risk assessment for the built environment, the probable loss is computed from the relationship between relative damage of the exposed element and the depth of water (hazard intensity). The relation damage vs. intensity is defined by the vulnerability function for each type of asset. 2.3.1 Effects of Climate Change on Risk Climate change adds an important layer of uncertainty to previously existing risks (Meybeck et al., 2012), and it is expected to impact sectors such as agriculture and livestock production. There are huge uncertainties in the way climate change will, directly and indirectly, impact agricultural and food systems and their vulnerabilities. Some expected impacts on the cropland include reduction in yields, increases in water demand, changes in the length of the growing period, and land degradation

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including a reduction in soil quality. However, a slight increase in air temperature is associated with an increase in potential yield. Since the generation of biomass, which is the same as the growth of the plants, is directly proportional to the transpiration, as the temperature increases, larger volumes of biomass are expected. With this, there are higher harvest values at the end of the crop growth period. Also, it has been shown how a slight increase in the concentration of CO2 in the atmosphere can favor the growth of plants, a criterion that is included in the FAO AquaCrop model (Raes et al., 2011). The previous remarks, which seem contradictory, must be evaluated with a robust approach when considering climate change’s uncertainty in the probabilistic risk assessment. With analysis that moves away from expectations and prejudices about what is expected to occur under climate change, it is possible to reach conclusions that are useful for decision-making and long-term planning. From a wider perspective, hydrological extremes can interrupt market access, trade, and food supply to urban centers, reduce producers’ income, and erode the livelihoods of the most vulnerable farmers. Moreover, climate change impacts can also affect land use and agriculture practices. The real effect of climate change on food production is not limited to the outcome of the physical risk assessment that models the crop’s response to water stress because climate change also impacts the relationships between the components of the system (Meybeck et  al., 2012). Therefore, a complete analysis should include multiple system domains – biophysical, economic, social, and institutional – that operate at multiple scales. All these issues make risk assessment a complex challenge, and methodologies like the one presented in this document are valuable contributions to interdisciplinary work which aims to reduce losses and build resilience. 2.3.2 Flood and Drought Risk Assessment Limitations It is important to mention that the methodology for hydrologic extremes risk assessment for the agriculture sector must make assumptions and define limits for its interpretation. Firstly, this methodology does not aim to forecast the occurrence of hazardous events; then, the set of events generated are potential scenarios that may happen but not necessarily will. Also, since the production of the agricultural sector is subjected to year-to-year variations resulting from multiple circumstances that are not related to the weather phenomena – market variations, changes in demand, and diseases outbreaks – the use of expected production implies that none of the non-disaster-related factors would have significantly affected the production in the absence of a disaster. Also, the methodology does not consider loss or damage to human life or impacts on the availability of water for drinking water supply, power generation, or groundwater dynamics.

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3 Results and Discussion The probabilistic risk assessment methodology for droughts was published by Bernal et  al. (2017) and implemented in the open-source software Drought Pro (Bernal et al., 2018). It has been used to estimate drought risk assessment for the agriculture sector in Central America, Uruguay, Niger, and Kazakhstan. The following sections present the results of the drought risk profile for El Salvador, Guatemala, and Honduras, relating the probable losses in the agriculture sector to food insecurity in terms of reduction in the production of cereals.

3.1 Droughts Risk Assessment in Central America: Impacts on Food Production 3.1.1 Dry Corridor in Central America Due to its geographical location, high climate variability, exposure to extreme hazards, and challenges in the human development of its inhabitants, Central America is a region prone to disaster risks. Vulnerable rural communities in Central America currently suffer from extreme droughts that exacerbate their precarious food and nutrition security (FAO Food and Agriculture Organization of the United Nations, 2018). The most affected area by climate-related hazards is known as the Dry Corridor. It is an ecoregion of dry tropical forests in Central America, covering the lowlands of the Pacific coastal area, and most of the central pre-mountain region of El Salvador, Guatemala, Honduras, Nicaragua, Guanacaste in Costa Rica, and Panama’s Arco Seco area (FAO Food and Agriculture Organization of the United Nations, 2015). The occurrence of droughts, excessive rains, and severe flooding is frequent in the area, which directly affects the agriculture production and livelihoods of vulnerable rural communities. Inhabitants of the Dry Corridor have suffered from extreme drought events recently, where it is estimated that more than one million families rely on subsistence farming (FAO Food and Agriculture Organization of the United Nations, 2015). Cereal production, mainly maize and beans, is the most affected by drought. For example, according to FAO (2018) in the drought event reported in 2018 – associated with El Niño phenomena– the governments of El Salvador, Guatemala, and Honduras reported losses of 281,000 hectares of these crops. For the subsistence farmers, these losses lead to a reduction of food to eat or sell, and an increase in the cost of staple foods for the entire population. Such recent extreme drought events show how food insecurity exists in the Dry Corridor, and climate change can be an extra challenge to secure enough food production. With this in mind, the drought risk profile was developed for El Salvador, Guatemala, and Honduras to assess the impacts of extreme water stress conditions on agriculture production. The crops included in the analysis were selected in terms

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of food security (maize, beans, and rice) and their role in the national economy (coffee, sugar cane, oil palm). Drought risk assessment was done for rainfed crops under hazard events derived from stochastic weather series that represent the normal weather (mean 1981–2010) and climate change scenarios considering the four RCPs. The main results for the drought risk assessment are presented as follows: 3.1.2 Drought Risk Assessment for the Agriculture Sector in El Salvador, Guatemala, and Honduras The risk results for the drought risk assessment for the three mentioned countries are presented herein. The Average Annual Loss – annual value that must be paid to compensate, in the long term, all future losses – and the Probable Maximum Loss for a 100-year return period are estimated for each country and presented in Table 15.1. The values reported are relative to the national GDP, to inform governments of the potential impacts of drought events on their economy. The risk assessment model assessed the yearly production of crops equivalent to 3.9% of El Salvador’s GDP, 7.4% of Guatemala’s GDP, and 10.8% of Honduras’ GDP. The Average Annual Loss (relative to the 2017 GDP) is presented for the normal weather and the climate change scenarios. Results show that even under current conditions, potential losses of droughts have an impact of up to 0.6% of the national GDP for current weather and more than 1% for RCP8.5 in the case of Honduras. It is also interesting to notice that under the RCP2.6 scenario, which defines the actions to keep global mean temperature increase below 2 °C by 2100, the expected losses (AAL and PML) for the three countries are lower than under the current normal weather. In general terms, Honduras is the country with the highest risk in all the scenarios considered, current weather conditions, and projected changes with climate change. Figure 15.15 shows the maps of the average annual loss, relative to Table 15.1  Drought risk assessment results for the agriculture sector Exposed value [million USD] National GDP 2017 [million USD] Ratio EV/GDP Agriculture GDP/national GDP Agriculture GDP [million USD] AAL/GDP 2017 [%] Normal weather RCP 2.6 RCP 4.5 RCP 8.5 PML100/GDP 2017 [%] Normal weather RCP 2.6 RCP 4.5 RCP 8.5

El Salvador 980 24,805 3.9% 11.9% 2952 0.15% 0.13% 0.15% 0.21% 6.06% 5.91% 6.28% 8.73%

Guatemala 5574 75,620 7.4% 10.1% 7638 0.26% 0.21% 0.27% 0.45% 12.40% 11.17% 14.61% 21.49%

Honduras 2477 22,979 10.8% 13.9% 3194 0.61% 0.47% 0.70% 1.07% 28.11% 26.84% 33.13% 41.46%

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Fig. 15.15  Average annual loss (relative to its exposed value) per department for El Salvador, Guatemala, and Honduras (The maps show the results for the current weather (top, left), RCP2.6 (top, right), RCP4.5 (bottom, left), and RCP8.5 (bottom, right). Green indicates lower risk; red is higher risk)

the exposed value, of each of the departments in the three countries. These maps allow the spatial comparison of risk between scenarios and are a tool to prioritize interventions in the territory. One interesting result of the drought risk assessment is the estimation of the potential reduction in crop production. That is, for the staple crops, rice, maize, and beans, the fraction of yearly reduction in production is quantified for each weather scenario considered – current and including climate change projections. The results are shown in Table 15.2. For example, under the conditions of the current weather (1981–2010), the potential loss in production in an average year is 2.8% for El Salvador, 7.8% for Guatemala, and 3.2% for Honduras. In the extreme scenario of RCP8.5 – the business-as-usual scenario of climate change – the potential losses increase for the three countries and in the case of El Salvador is almost three times higher than under the current weather conditions. Table 15.2 shows that the potential losses do not follow a linear behavior, and the risk conditions in the three

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15  Climate Change, Food Security, and Resilience: Hydrologic Excess and Deficit… Table 15.2  Average Annual Production Loss relative to potential production [%] Rice Beans Current RCP RCP RCP Current RCP RCP RCP weather 2.6 4.5 8.5 weather 2.6 4.5 8.5 0.9 0.6 1.0 3.1 2.4 2.3 2.4 3.5

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countries are diverse. For El Salvador and Guatemala, the highest expected losses are for maize production, while Honduras results show higher expected losses for rice and beans. These potential reductions in food production, especially staple crops grown by subsistence farmers, are a clear indication of the lack of food security suffered in the region. Moreover, it is important to notice that even under current weather conditions, expected losses in crop production are high and might increase if no climate change mitigation is achieved in the short term.

4 Conclusions A probabilistic risk assessment methodology to evaluate the potential impacts of hydrological extremes  – floods and droughts  – in the agriculture sector was presented. Following a case study in Central America, drought risk was assessed under normal weather conditions and climate change scenarios. It was shown that climate change may have an important effect on agriculture, as crop production can decrease with a direct impact on fragile food security in the area. The proposed methodologies address the uncertainty embedded in hazard, exposure, and vulnerability of cropland. Addressing uncertainty is a condition to build resilience. The identification and understanding of risk –under current conditions and climate change projections– is the first step to develop tools and initiatives to adapt and transform socioeconomic systems to reduce vulnerability. This drought and flood risk assessment model is a contribution to understanding climate-related risk within a multidisciplinary working group that aims to address serious human development issues: food security and disaster risk reduction. It is necessary to expand the research on understanding and quantifying drought and flood risk to build resilience. For example, in the case study presented in this chapter, food security was addressed from the production pillar; however, models should be further developed to also consider conditions of access and utilization, as access does not necessarily imply sufficient, safe, and nutritional food.

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Chapter 16

Climate Change and Agroforestry Resilience Strategy in West Africa’s Cocoa Supply Chain Dynamics S. A. Igbatayo

Abstract  The emergence of climate variability and change in West Africa pose considerable threat to the region’s largely vulnerable ecosystems, and the people’s prime source of livelihoods, where more than 70% of the population relies on agriculture for their well-being. The Intergovernmental Panel on Climate Change acknowledged a sustained decline in annual rainfall over the region since the end of the 1960s, with a reduction of 20–40% in the periods 1931–1960 and 1968–1990. The “cocoa belt” stretches from Sierra Leone, Guinea, Liberia, Cote d’Ivoire, Ghana, and Nigeria to Southern Cameroon, accounting for 70% of the world’s annual cocoa production, estimated at 4.5 million tonnes in 2016. A potent strategy against climate change is the adoption of agroforestry, defined as the intentional integration of trees and shrubs into crop and animal farming systems aimed at creating environmental, economic and social benefits. The extensive adoption of agroforestry in West Africa’s cocoa belt has become a resilient adaptation mechanism against the impact of climate change. However, rising atmospheric temperatures and incessant droughts are creating deep uncertainty across the region. Therefore, the major objective of this chapter is to shed light on the threats posed by climate change on cocoa production trends in West Africa. The study employs empirical data to analyse the effects of climate change on both agroforestry resilience and cocoa production dynamics in West Africa. The result reveals an emergent decline in productivity, attributable to ageing and diseased trees, as well as biodiversity loss, compounded by climate change. Keywords  West Africa · Agroforestry · Climate change · Resilience · Cocoa · Sustainability

S. A. Igbatayo (*) Department of Economics, Afe Babalola University, Ado-Ekiti, Nigeria © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_16

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1 Introduction Agroforestry has emerged as a tool in contemporary agricultural practice, which integrates trees and shrubs with cropping systems and/or livestock for land management aimed at increasing agricultural productivity, while conserving natural resources. Agroforestry is accompanied by various benefits: food, shelter, energy, medicines, as well as cash income, which is critical for transforming livelihoods. West Africa is endowed with considerable forest resources across the region’s tropical agro-ecological zones. The region’s tropical rainforests traverse 11 countries along the coastal region, contributing to the peoples’ socio-economic well-being. However, the region has lost a considerable proportion of its primary forest cover over the past several decades, fuelled by human activities, including fuel wood consumption, rapid urbanization, demographic explosion, overgrazing, mining, agricultural extensification, among other things (Igbatayo, 2018). The negative trend has been exacerbated by the emergent global climate change, which has triggered a rise in atmospheric temperatures and irregular precipitation. These conditions have been blamed for incessant droughts and a significant reduction in annual rainfall, with serious inter-seasonal and decadal variability (Climate Path, 2018). The increasing loss of forest cover has impacted cocoa productivity in West Africa, which accounts for more than 70% of the world’s annual production. This development poses a threat to the sustainability of the region’s cocoa production and the global consumption of chocolate. In order to stem the tide, stakeholders in the global cocoa-chocolate industry have initiated concerted efforts aimed at fostering resilience on West Africa’s cocoa value chain. A major component of the initiative embraces agroforestry as a cornerstone to rehabilitate cocoa farms in the region (CIAT, 2011; USDA, 2011; AFTA, 2018). The effects of climate change on West Africa’s cocoa producing regions hold grave consequences for the global cocoa value chains. While cocoa is grown as the world’s global tropical zone, chocolate, the major end product of cocoa, is mostly consumed in developed market economies and is largely located in the Northern Hemisphere. Indications are that the global demand for cocoa is rising in recent times, against the backdrop of unsteady supply in West Africa, which accounts for more than 70% of the global market. The emergent global climate change is undermining the biodiversity of cocoa growing regions through a combination of rising atmospheric temperature and declining precipitation. Indeed, several areas of cocoa growing regions in West Africa, especially in the last few decades, have experienced declining annual rainfall, with more than 30% in both seasonal and decadal variability (IPCC, 2007). In several cocoa producing countries in the region, declining annual rainfall has triggered incessant droughts, undermining the fertility of soils and vegetative cover in cocoa plantations. This development has impacted negatively on cocoa productivity, as well as farmers’ income. Compounding the trend is the fact that a considerable proportion of cocoa plantations in West Africa is old and in dire need of rehabilitation. However, due to the unattractive nature of cocoa production, there is an emergent challenge of sustainability, as the youth find cocoa

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supply chain unattractive, while the elderly continue to saddle themselves with the increasing rigours of the job. This development is expected to fuel lower production trends in the future and accompanied by a spike in the price of chocolate. The threat posed by dwindling cocoa supply chain in West Africa has prompted the intervention of cocoa-chocolate players in the global marketplace, with action plans to revive cocoa plantations in the region and foster best practices to mitigate poverty and inequality along the cocoa global value chain. Climate change and variability is fuelling poverty, particularly among resource-­ poor farmers in West Africa. Over 70% of the region’s population derives its livelihoods from farming. Climate change impact on the region’s agroforestry resources is depriving farmers of income, fuelled by declining productivity, particularly cocoa farmers. Already, the region is deeply impoverished, with about 50% of its population living in extreme deprivation, or less than the equivalent of US$1.25.00/person/ day, the poverty benchmark for low-income countries. Indeed, most countries in West Africa are ranked alongside the least developed countries, and the region is home to some of the most impoverished people in the world (United Nations, 2019). This development poses considerable challenges for region’s policymakers and global partners.

2 Objectives and Methodology The major objective of this chapter is to highlight the state of forestry resources in West Africa. Specific objectives are to: • • • • •

Elaborate the benefits of agroforestry in land management Evaluate the state of forestry in the region Examine climate risk and vulnerability Discuss the effects of deforestation on cocoa production Spotlight resilient measures aimed at fostering sustainable cocoa production

The study employs both quantitative and qualitative data to analyse the effects of climate variability on the state of agroforestry resources in West Africa, as well as its cocoa growing regions. The study also relies on empirical data generated by publications from such international development agencies as the World Bank, the United Nations and its agencies, as well as various journals and other periodicals. This is complemented by interviews with stakeholders around the region. The geographical focus of the study is the West African coastal region, acknowledged as the ‘cocoa belt’ stretching from Sierra Leone, Guinea, Liberia, Cote d’Ivoire, Ghana and Nigeria to Southern Cameroon, accounting for 70% of the world’s annual cocoa production, estimated at 4.5 million tonnes in 2016.

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3 Agroforestry: A Conceptual Framework The Food and Organisation of the United Nations (FAO, 2015) defines agroforestry as a collective name for land use systems and novel technologies, where woody perennials (trees, shrubs, palms, bamboo, etc) are deliberately employed on the land management units, as agriculture crops and/or animals, in some form of unique arrangement or temporal sequence. On the other hand, the Association for Temperate Agroforestry (AFTA, 2018) defines agroforestry as an intensive land management system that optimizes the benefits associated with the biological interactions created when trees and/or shrubs are intentionally combined with crops and/or livestock. In yet another definition, the US Department of Agriculture (USDA, 2018) defines the concept of agroforestry as a unique land management approach that deliberately blends agriculture and forestry to enhance profitability, productivity and environmental sustainability. It is however clear from the aforementioned definitions of agroforestry that the concept is a reflection of novel nomenclature for a set of old practices. In addition, the concept has emerged with a considerable level of acceptability in the international land-use framework in contemporary times (Nair, 1993). It is further acknowledged from these definitions that agroforestry usually involves two or more species of plants (or plants and animals), at least one of which is a woody perennial; it is an integrated system with two or more outputs, comprising a cycle spanning more than 1 year and featuring a more complex, ecologically (structurally and functionally) and economically, than a mono cropping system. Indeed, agroforestry has emerged as a dynamic, ecologically based, natural resources management framework, with the integration of trees on farms as well as in agricultural landscapes. This is also accompanied by diversification and sustainable production for increased social, economic and environmental benefits for land users at all levels. Agroforestry practices are laden with a wide range of products and services, with trees providing food, shelter, energy, medicine, cash income, as well as raw materials for craft, fodder, forage and other resources to meet social obligations (Wafuke, 2012) Agroforestry system can be classified into three major categories (FAO, 2015): • Agrisilvicultural systems refers to a mixture of crops and trees, including alley cropping or home gardens. • Silvopastoral systems embrace forestry and grazing of livestock on pastures, rangeland or on farm. • Agrosilvopastoral systems comprise home gardens, with animals as well as scattered trees on croplands employed for grazing after harvest. In order to understand the framework of agroforestry, it is important to examine its components: land, trees and non-trees. It is acknowledged that agroforestry system is a framework by which land is managed for the benefit of the land owner, environment and long-term welfare of society. Agroforestry is particularly useful for managing delicate land holdings, such as ill-side farming, where farming may lead to rapid loss of soil, or other environments in need for preservation of

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biodiversity (Morote et al., 2020). In order to create a sustainable agroforestry system, it is important to understand the role played by multipurpose trees or perennial shrubs. The most important of these trees are legumes, noted for their ability to fix nitrogen and make it available to other plants. The roles of trees on the small farms include the following (Martin & Sherman, 1992): sources of fruit, nuts, edible leaves and other food; providing construction materials, posts, lumbers, branches for use as wattle (a fabrication of poles interwoven with slender branches, etc) and thatching; sources of non-edible materials, including sap, resins, tannins, insecticides, medicinal compounds, fuel, beautification and shade; providing soil conservation, especially on hillsides; and improving soil fertility. In order to maximize the benefits associated with agroforestry systems, considerable knowledge of their properties is critical. These include desirable information on various species, particularly on their benefits; adaptability to local conditions (climate, soil and stresses); the size and form of the canopy and root system; as well as suitability for various agroforestry practices. Some of the most common uses of trees in agroforestry system are the following: individual trees planted in home gardens, around houses, paths and public places; dispersed trees in cropland and pastures; rows of trees with crops in between (alley cropping); strips of vegetation along contours or waterways; living fences and borderlines boundaries; windbreaks; improved fallows; terraces on hills and small earthworks; erosion control on hillsides, gullies and channels; and woodlots for the production of fuel and timber. Concerning the use of non-trees in agroforestry systems, any crop plant can be adapted, based upon nutrition requirements, self-sufficiency and soil protection. Selection of crops for agroforestry system requires considerable knowledge of the crops, production uses as well as family needs, opportunities for barter and markets. Also, farm animals can be used in agroforestry systems, with the choice of livestock based on the value associated with the animal, especially as it may concern income, labour as well as non-food products, including crop residues and manure. Agroforestry systems have emerged as useful tools for farmers, ranches, woodland owners, communities and other stakeholders intending to employ sustainable strategies that leverage agricultural land management practices with the protection of natural resources. They provide a framework with an admixture of trees and crops to enhance long-term production of food and related products, while conserving the soil and water, diversifying and expanding local economies, providing wildlife habitat and ensuring a more pleasurable and healthy place to work and live (USDA, 2018). Figure 16.1 illustrates the interface between agriculture and forestry in the emergence of agroforestry. It reveals the interrelationships between forestry and agriculture, as well as the unique challenges that constitute driving forces for the emergence of agroforestry as a land management framework. It also features special conditions and constraints peculiar to the phenomenon. The framework embraces tree planting for the reclamation of degraded land, integrated systems with ‘non-forest’ trees, as well as woody perennials on farms, among other things.

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Fig. 16.1  The interface between forestry and agriculture and the emergence of agroforestry systems in tropical agro-ecological systems of developing countries. (Source: Martin & Sherman, 1992)

4 An Overview of Forest Endowment in West Africa The tropical rainforest in West Africa covers an area measuring 250,000 square kilometres or 19% of Africa’s total. The ecological zone stretches from the eastern border of Sierra Leone through the coastal areas of Ghana and the Republic of Benin. It also stretches from southern Nigeria and ends at the border of Cameroon, along the Sanaga River. Specifically, the tropical rainforest encompasses the following countries in its woods across West Africa: Benin, Cote d’Ivoire, Ghana, Gambia, Guinea-Bissau, Sao Tome and Principe, Sierra Leone and Togo (Nix, 2017). A considerable proportion of West Africa’s tropical rainforest is the Guinean forests, stretching across 12 countries and three Islands in West Africa (Khaligian, 2012). The Guinean forests feature one of the most diversified ecological zones in the world, making up a tropical rainforest biome across West Africa. The area’s vegetation can be categorized into moist forests along the coast; freshwater swamp forest; and semi-deciduous forest, located inland along the Cameroon highlands. The Guinean forest hotspot is an abode to an estimated 9000 vascular plant species, about 20% of which are believed to be endemic. The forests are also home to more than 25% of Africa’s mammals, including more than 20 species of primates

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Fig. 16.2  Locations of the Guinean forests in West Africa. (Source: Microsphere, 2018)

(Microsphere, 2018). Figure 16.2 reveals the distribution of the Guinean forests in West Africa. It shows the stretches of the Guinean forests along the coast in several West African countries. West Africa’s once vibrant and extensive rainforests have been undermined by decades of unmitigated anthropogenic forces, unleashed by various interests. Recent data reveal that less than 1.5% of West Africa has primary forest cover, while more than 5400 square miles or 1.4 million hectares, equivalent to 26% of primary forest cover, have disappeared across the region and leaving an estimated residue, ranging between 11,600 and 15,400 square miles, or 3 and four million hectares of such forest (Butler, 2006). This is in sharp contrast to about a hundred years ago, when West Africa featured some 193,000 squares miles or 50 million hectares of coastal rainforests. However, a combination of human activity, ranging from logging, road construction, mining to such subsistence activity as collection of fuel wood and shifting cultivation, has decimated primary forest resources of the region. Indeed, indications are that deforestation of primary forest has increased by more than 20% since the late 1990s, with dire consequences for biological diversity (Igbatayo, 2018). The decimation of the Guinean forests is particularly critical. Originally, the upper Guinean forest comprised dense vegetation, covering an estimated 680,000 square kilometres. By 1975, only a remnant or relic patches of dense forest remained, with a loss of 84% of the original forest cover. The historical, dense forest ecosystem has been undermined by a series forest fragments, separated by agricultural communities and degraded lands. Also, between 1975 and 2013, further damage had been inflicted through removal of forest and wood products, plantations and other uses; resulting in the loss of 28% or 62,000 square kilometres of the forest. Of the primary forest remaining in the upper Guinean forest, Guinea contains 6%; Sierra Leone, 4%; Liberia, 49%; Cote d’Ivoire, 21%; Ghana, 18%; and Togo, 2%.

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Loss of 90%

Loss of 88%

400,000

Loss of 84%

Area (sq km)

500,000

Loss of 68%

600,000

Loss of 47%

700,000 Original extent of the Upper Guinean forest

300,000 200,000 100,000 0 Original 1900 (Mittermeier et al., 1999)

1920 (Unwin, 1920)

1975

2000 2013

Fig. 16.3  Deforestation of the Upper Guinean forest, 1900–2013. (Source: USGS, 2015)

Indeed, by 2013, the Guinean forest countries were left with only about 70,000 square kilometres of dense forest cover and 32,000 square kilometres allocated as national parks, classified forest, nature reserve and wildlife sanctuaries (USGS, 2015). Figure  16.3 shows the evolution of forest degradation in upper Guinean countries from 1900 to 2013. It reveals the gradual degradation of primary forest cover from the end of the nineteenth century to 2013.

5 Deforestation and Socio-Ecological Consequences in West Africa Deforestation has risen as a disturbing phenomenon undermining development prospects in West Africa, especially in contemporary times. The region has lost about 90% of its primary forest cover since the end of the nineteenth century, with grave consequences to the environment. Various studies reveal that the socio-­ economic impacts of deforestation are multidimensional. For example, Garcia-­ Carreras and Parker (2011), in a study on the effects of deforestation on rainfall in West African forests, show that the phenomenon reduces precipitation over neighbouring trees about 50%, attributed to increased surface temperature of farmlands, which affects the formation of rain clouds. The study also suggests that rainfall reduces further as a consequence of deforestation. The development also poses an existential threat on the remaining forests due to the trees’ increasing sensitivity to drought. The study’s revelation holds serious consequences for the region’s rain-fed agriculture, as farmers in the region, which constitute more than 70% of the

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population, are resource-poor and lack access to irrigation facilities to drive agriculture productivity. However, comprehending the regional or global impact of deforestation on climate change and agriculture often requires modelling to drive policies that mitigate the phenomenon. Lawrence and Vandecar (2015), in a study featuring the General Circulation Model, reveal that a complete deforestation of the tropics could result in global warming equivalent to that attributed to burning of fossil fuel since 1850, accompanied by significant warming and considerable drying in the tropics. However, the study also shows that in a regional context meso-scale models that capture topography and vegetation-based discontinuities and small clearing may enhance rainfall. Although, at the smaller scale, a critical deforestation threshold exists, beyond which rainfall declines, the study further reveals. This poses considerable challenges to the future of agriculture productivity in the tropics, given increasing risks associated with deforestation-induced increase in average atmospheric temperatures, as well as heat extremes and a decline in average rainfall, or precipitation frequency. The lack of consistency in rainfall patterns in parts of West Africa, associated with climate change, holds grave consequences for farmers’ productivity and income levels in a region already undermined by endemic poverty. West Africa’ forests are endowed with some of the greatest concentrations of plants and animal species in the world, with considerable diversity in fauna and flora. The region is also acknowledged as a biodiversity hotspot. However, the increasingly fragile ecosystems that make this possible are now threatened by deforestation, fuelled by anthropogenic forces. Cote d’Ivoire is a prime example of the region’s loss of biological diversity. The nation is endowed with the highest levels of biological diversity in West Africa, with over 1200 animal species, comprising 232 mammals, 702 bird, 125 reptiles, 38 amphibians and 111 fishes. This is complemented by 4700 plant species (Butler, 2006). Most of the biodiversity hotspot is located in the rugged interior region as well as in coastal areas. However, a combination of anthropogenic forces, including deforestation, mining, urbanization, agriculture intensification and conflict has decimated the nation’s stock of natural resources. By 2005, the nation had lost most of its primary forest cover. Indications are that the nation’s forested area had declined precipitously, falling from around 16 million hectares to ten million. Loss of biodiversity is widespread across West Africa. In Nigeria, the region’s largest economy, with the highest population, estimated at more than 190 million people, continues to suffer considerable biodiversity loss, largely attributable to deforestation. Reports reveal that the nation lost about half of its primary forest cover between 1990 and 2010, from 17,234 to 9041 hectares). This development has fuelled one of the most severe desertification rates in the world, with the loss of 55.7% of the nation’s primary forest cover between 1995 and 2005. The annual rate of deforestation in Nigeria is estimated at 3.5% or loses ranging between 350,000 hectares and 400,000 hectares. It is noteworthy that a considerable proportion of West Africa lies at the heart of the tropical climate, accompanied by some of the world’s most endowed biodiversity hotspots. However, widespread deforestation, partly driven by global warming

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and anthropogenic activities, has undermined biodiversity, leading to the destruction of natural habitats for both plants and animals. This development has also posed existential threats to plants and animal species. Indeed, widespread deforestation is fuelling extinction of some plants and animal species in the region. For example, deforestation is affecting the migratory patterns of birds and animal species, with grave consequences for the food chain. Such wildlife species, including elephants, buffalos, tigers, lions and other exotic animals, are deemed to be threatened with extinction. The trend has assumed alarming dimensions over the past few decades, galvanizing researchers, policymakers and development partners to mitigate the trend and reverse the damages unleashed on agro-ecological systems in particular and biodiversity in general.

6 Promoting Resilience to Mitigate Deforestation The loss of tropical forests in West Africa has assumed a worrisome dimension, against the backup of only 10% of primary forest cover left across the region since the end of the nineteenth century. Even more critical is the fact that 30% of the forests, which provide vital economic and ecosystem benefits, have been lost over the past 25 years. However, several global initiatives have emerged to address the challenge (USAID, 2018): • The 1992 Convention on Biological Diversity (CBD). • The 1981 Convention for cooperation in the protection and management of marine and coastal environment of the West African region. • The Cartagena Protocol on Biosafety to the Convention on Biological Diversity. • The United Nations Convention on Climate Change. • The Convention on International Trade in Endangered Species of Wild Fauna and Flora. • The International Tropical Timber Agreement (ITTA). • The United Nations has also initiated other measures to spur biodiversity, tackle desertification, conserve migratory species and boost water management. In order to foster resilience and boost ecosystems across West Africa, various partnerships have been forged at local, national and regional levels. For example, USAID (2018), leveraging its West Africa Biodiversity and Climate Change (WA BICC) initiative, has forged partnerships at the regional level to boost conservation and climate-resilient, low-carbon growth emission throughout West Africa. In order to achieve this objective, WA BICC is supporting ongoing efforts at national and regional levels to coordinate and integrate climate policy and socio-economic approaches, develop and refine climate and disaster related indicators as well as improve techniques for data collection, analysis and communication. West Africa’s coastal regions are particularly vulnerable to rising sea levels, attributed to global warming. Coastal erosion or sea advance is fuelling degradation of vital coastal wetlands, including mangrove forests, which cover about 15,000

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square kilometres in West Africa. According to the USAID (2018) report, a sea level rise of 0.5 m will result in a loss of between 806 and 2149 square kilometres. Indeed, the loss of coastal wetlands is likely to have negative consequences for the economy, particularly the reduction of fisheries and other animal resources, decline of fish populations and wetland vegetation of the countries concerned. Also associated with rising sea levels are the threats posed by salinization of coastal wetlands, which often fuels mangrove die-offs, increased salinity in groundwater aquifer and surface water, which also undermines subsistence farming in coastal wetlands. In order to address these challenges, the USAID has established a 5-year West Africa Biodiversity and Climate Change (WA BICC) programme in collaboration with West Africa and international partners to foster coastal ecosystem resilience to climate change in West Africa. The initiative aims at promoting best practices and policies that drive national adaptation plans to respond to and mitigate climate change at the local level. Primary activities associated with the initiative are to: • • • • • •

Develop regional policy instruments for coastal resilience. Support the National Adaptation planning strategies. Generate and employ climate and geospatial information. Address climate effects on coastal system. Implement intensive site-based coastal Adaptation strategies. Support regional communities of practice and information and knowledge management system (IKMS). • Implement coastal management public sensitization and behavioural change communication. As part of its delivery mechanism, WA BBIC is working with ECOWAS, the Abidjan Convention as well as the Mano River Union (MRU) countries and other stakeholders as part of the initial phase of the programme. In concerted efforts aimed at confronting the threats posed by deforestation across West Africa, the International Union of Forest Research Organization (IUFRO), in partnership with four west African counties  – Cameroon, Ghana, Liberia and Nigerian  – and supported by the International Tropical Timber Organisation (ITTO), through the Reducing Deforestation and Degradation and Enhancing Environmental Services from forests (REDDES), established a project to elaborate and disseminate forest-related scientific information in the region. The goal of the initiative was to support efforts aimed at reducing deforestation and forest degradation by spurring socio-economic sustainability and community well-­ being, especially in forest-dependent parts of West and Central Africa (IUFRO, 2015). Specially, the objectives of the project are as follows: 1 . Assessment of REDDES pilot areas 2. Sharing and dissemination of REDDES scientific information to policymakers and forest stakeholders 3. Broadening and deepening the research and networking capacity of African forest scientists

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In order to tackle the challenge and the threats posed by deforestation, IUFRO engaged various forest stakeholders in the four countries concerned, mobilizing support from government officials, local communities, NGOs and private sector payers. The project identified common challenges as well as solutions to be developed among the pilot sites. In Cameroon, the REDDES strategies identified and agreed upon by all stakeholders targeting the establishment of a participatory forest management system. This also embraced development of a participatory forest management plan for the regulation of wood and non-timber forest products (NTFP), as well as the protection of rare species. In addition, a framework was established for a joint forest planning and implementation with communities, which would also serve to foster transparency as a measure aimed at tackling corruption. On the other hand, the stakeholders’ consultation in Ghana culminated in the proposal of a six-point REDDES strategy, with specific implementation activities to reverse deforestation and enhance tree cover, as well as reducing carbon foot print at the district level. Elements of the strategies include the promotion of community-­ based fire prevention and management, establishing plantations of indigenous tree species, including Teminilia superba and Entandrophrama spp., among others. They also included introduction and promotion of sustainable agroforestry and on-­ farm practice, as well as the creation of awareness on environmental degradation, including building of capacities of public institutions, local communities, media and other stakeholders on the linkages between sustainable forest management, environmental services and livelihoods. Under similar circumstances, strategies crafted through consultation in Nigeria focused on raising awareness among forest-dependent communities on environmental degradation and the negative effects on human well-being. The consultation also comprises allocation of land for forestry, aimed at spurring participation of farmers, provision of farm inputs, supporting and facilitating communal forestry, as well as making available to them tree seedlings, while empowering local communities and traditional institutions to sustain forests. Finally, the project’s consultative strategies with stakeholders in Liberia focused on priority actions aimed at fostering socio-economic development needs of forest-­ dependent communities. The strategies included the imperative to establish sustainable forest management framework in the Yorma Forest Reserve to provide an equitable access to benefit local communities; allocation of adequate land to local forest fringe communities in order to practice sustainable agroforestry, as well as growing more cash crop; establishment of community woodlots in support of the production of firewood and charcoal; and creating a payment scheme for local communities to keep and sustain the forest in their areas (Foli & Kleine, 2014). Deforestation in recent times is also assuming more disturbing dimensions in West Africa’s plantation farms. In the quest to sustain their livelihoods, farmers are engaging in deforestation practices to grow such cash crops as cocoa, coffee, rubber and palm produce, among others. The practices fuel large-scale deforestation, with the attendant consequences. However, stakeholders, including national governments, research, institutions and multinational companies are addressing the challenge posed by deforestation

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across the region. For example, stakeholders in the global chocolate and cocoa industry are engaging West African farmers to embrace agroforestry as a sustainable, ecologically driven, natural resource management framework that promotes integration of diverse food, fodder, timber and shades in agriculture landscape (Huffington Post, 2018). It is against this backdrop that the World Cocoa Foundation (WCF), in collaboration with global stakeholders, launched the Cocoa and Forest Initiative. Embraced by more than 20 global stakeholders, including the world’s leading chocolate and cocoa supply chain networks, the partnership is committed to working together to end deforestation and forest degradation in the cocoa supply chain, with an initial focus on Cote d’Ivoire and Ghana (Coffee & Cocoa International, 2017).

7 Climate Risk and Vulnerability in West Africa Climate change, a global phenomenon unleashed across the world, holds grave implications for humanity and ecosystems. The threats posed by climate change are acknowledged as the most critical challenges in contemporary times (Hulme, 2017). The United States Aeronautic and Space Administration (NASA, 2013) defines climate change as the transformation in the average weather pattern of a region over a long period of time. The transformation is usually associated with atmospheric temperature and precipitation. Climate change is attributed to both natural and anthropogenic forces. In case of the former, transformation occurs in the sun’s radiation, volcanoes or other changes that emerge in the climate system; in the latter, climate change is fuelled by transformation in the composition of the atmosphere or land use. It is however important to note that the contemporary change in the global climate system is likely triggered by anthropogenic forces, accompanied by rising atmospheric concentration of carbon dioxide, methane and nitrous oxide, which emerged around 1750, at the dawn of the industrial revolution (Climate Path, 2018). In West Africa, climate change and variability have assumed problematic dimensions in contemporary times, fuelling environmental degradation and loss of biodiversity. The Intergovernmental Panel on Climate Change (2007) observes a significant reduction in seasonal precipitation since the end of the 1960s across the region, with a drop ranging between 20% and 40% over the periods 1931–1960 and 1968–1990. The long-term decline in rainfall has been blamed for the southward shift of the Sahelian, Sudanese and Guinean agro-ecological zones during the latter half of the twentieth century. In a recent study, Hartley et al. (2016) reveal that average atmospheric temperatures are rising in the region, increasing by 1 °C since 1960, on average. However, average temperatures in the Sahel have risen higher: 1.5 °C to 2  °C, with the warmest months of the year – April, May and June – featuring even greater increases of up to 3  °C, attributable to warmer night temperatures. Another factor fuelling climate change is the variability in rainfall patterns, defined as the average deviation from the mean. In West Africa, rainfall variability is not just inter-­ seasonal but has emerged as a multi-decadal phenomenon, in line with the IPCC

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(2007) report. Indeed, annual rainfall variability can be severe, ranging from 40% to 80% and increasing with decreasing rainfall patterns. The phenomenon is even more severe in the Sahel. While average annual rainfall has recovered considerably in parts of the region, it is insufficient to match precipitation records in the earlier part of the twentieth century, leaving dry spells to continue. It is however important to note that the impact of global warming on rainfall in West Africa is particularly challenging, against the backdrop of different and often conflicting climate models, which feature significant variation on the future of rainfall in the region. While there is a high level of confidence in the increase of atmospheric temperature, estimated between 3 °C and 6 °C above twentieth-century levels, some models project a dryer future by 2100, others a welter future, and yet others projecting no significant change in total rainfall (USGS, 2015). It is however incontrovertible that West Africa has witnessed extreme weather events, particularly over the past 50 years, and the trend is likely to continue into the foreseeable future (Robinson & Brooks, 2010).

8 The Impact of Climate Change on Forest Resources in West Africa Climate variability and change continue to undermine natural resources around the world through global warming and increasing weather events. The phenomena are, therefore, expected to trigger widespread economic, environmental and social repercussions. Climate change impact on forests has acquired a worrisome dimension, given the role trees play in carbon sequestration. Forest vegetation and soil contain about half of the world’s terrestrial carbon. Trees absorb co2 through photosynthesis, store it as carbon and release it through respirations, decomposition and combustion (FAO, 2013a). The ‘carbon sink’ function of forests increases with its rate of growth and its permanence with which it retains carbon. However, climate change and increasing climate variability are creating both direct and indirect impacts on forests and forest-dependent communities. In West Africa, forests are acknowledged as valuable ecosystems. In addition to harbouring a vast array of plants and animal species, forests also provide food, herbal medicines, energy and tourism to various communities. However, warmer temperature, drought and decline in precipitation can lead to loss of vegetation and deterioration of landcover. Also, incessant droughts can dryout water sources critical to plant and animal species. On the other hand, increases in intense rainfall can fuel floods with potentials to undermine land, soil, watershed and ecosystems. The emergent climate change has subjected tropical forests in West Africa to become vulnerable to extreme weather events in recent years, accompanied by incessant drought, flash floods, erosion and saltwater intrusion in coastal areas (USAID, 2012). Nigeria, like other coastal countries in West Africa, has lost a considerate proportion of its forest resources over the past several decades. Some of the loses are

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attributed to climate change, which affect the nation’s mangrove ecosystem in the coastal areas through flooding and erosion, as well as saltwater intrusion, as sea levels continue to rise against the backup of global warming (Idowu et al., 2011). In the nation’s tropical forest ecosystem, reduction in precipitation has fuelled drought and triggered fires in the dry season, resulting in widespread deforestation. On the other hand, in the nation’s Sahelian ecosystem, prolonged drought over the past several decades has triggered a southward shift in desertification, with the decimation of trees left in the fragile environment. These developments have undermined the livelihoods of forest-dependent communities, forcing many into vicious circle of poverty (Beyioku, 2016). The impact of climate change on West African forests has grave implications for cocoa producing farms, which rely on trees to provide canopy for the optimum growth and productivity of cocoa trees. In a report titled ‘Predicting The Impact of Climate change on the Cocoa Growing Regions in Ghana and Cote d’Ivoire’, the International Center for Tropical Agriculture (CIAT) (2011) shows that an increase in atmosphere temperature of more than 2 °C by 2050 would significantly impact West Africa’s cocoa productivity areas. The report projects that suitability of areas for cocoa production will begin to decline by 2030, fuelled by climate change, as the trees will struggle to get adequate water during the growing season, leaving them more vulnerable to stress during the dry season. Areas that may be particularly affected include Moyen-Comoe, Sud-Comoe and Agneby in Cote d’Ivoire, as well as the Western and Brong Ahafo in Ghana, according to the report. The researchers noted that marginal cocoa growing areas are already stressed and that cocoa cultivation will need to shift to high attitudes, which are particularly limited in West Africa. Ironically, this development may lead to the clearing of more forests. The report also suggests measures to stem the tide, including planting more trees, diversifying the livelihoods of cocoa farmers and taking measures to minimize bushfires. It further urges governments and stakeholders to develop new climate-resilient cocoa trees as the cornerstone of policies that promote climate adaptation.

9 Cocoa Production in West Africa: Recent Trends and Developments West Africa accounts for more than 70% of the world’s annual cocoa output, which is produced in the region’s ‘cocoa belt’, stretching from Sierra Leone to Southern Cameroon. Cocoa production in the region is led by Cote d’Ivoire, with 37.1% of the global output, followed by Ghana, Nigeria and Cameroon, with 21.9%, 5.9, and 5.2%, respectively (Südwind et al., 2013). In West Africa, up to 90% of farmers in cocoa producing countries rely on the commodity for their primary income. While the cocoa tree is indigenous to South America, where it was discovered by Dutch traders in 1560, it was introduced into the African continent in 1871 in Ghana (SWAC/OECD, 2007). Cultivation of cocoa tree gradually spread from Ghana to

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Cote d’Ivoire, Nigeria, Cameroon and other West African Countries, which subsequently adopted the tree as cash crop, providing a reliable source of livelihood to millions of small-holder farmers across the region (Wessel & Quist-Wessel, 2015). Cocoa is cultivated on more than six million hectares of land in the West African tropical agro-ecological zone. The crop is popular amongst resource-poor, small-­ holder farmers because of the relatively inexpensive nature of inputs needed to maintain the trees. Since colonial times, West African producers have come to rely on cocoa as a major source of foreign exchange earnings and government revenue, which accounted for the region’s leading position on the global output of cocoa. Table 16.1 reveals West Africa’s cocoa production trends, compared with the global output, from 1984 to 2014. As illustrated in Table 16.1, the share of West Africa’s global cocoa output has increased steadily in recent times, rising from 52%, or 1011 tonnes in the 1984–1985 cropping season, to 71%, or 3098 tonnes in the 2013–14 season. This development is largely attributed to the significant rise of production in Cote d’Ivoire from 565 tonnes in the 1984–1985 cropping season to 1741 tonnes in the 2013–2014 season. In one of its latest reports on cocoa production, the International Cocoa Organization (ICCO, 2016) reveals regional cocoa production trends, including projections, covering 2014/15–2016/17 seasons, as shown in Table 16.2. Table 16.2 reveals the global production of cocoa beans from 2014/15–2016/17, including projections. The data are disaggregated into regional distribution, showing Africa’s domination, with 3074 tonnes or 72.3%; 2918 tonnes or 73.3; and 3565 tonnes or 75.8% of actual production, estimates and forecasts for 2014/15, 2015/16 and 2016/17 cropping seasons, respectively. As usual, Cote d’Ivoire remains the largest producer of cocoa beans over the period in view, with 796 tonnes or 42.2%; 1581 tonnes or 39.7%; and 2010 tonnes, or 42.7% of the actual production, estimates and forecasts for 2014/15, 2015/16 and 2016/17 cropping seasons, respectively. Table 16.1  West African and world Cocoa bean production trends, 1984–2014 (thousand tonnes) 1984–85 1989–90 1994–95 1999–20 2004–05 2009–10 2010–11 2012–13 2013–14 Cameroon 120 125 107 120 130 205 229 225 210 Cote 565 708 876 1300 1273 1242 1511 1449 1741 d’Ivoire Ghana 175 295 304 440 586 632 1025c 835 897 Nigeria 151 170 140 165 190 235 240 238 250 West 1011(5)b 1298(54) 1427(60) 2025(69) 2179(70) 2314(64) 3005(70) 2747(69) 3098(71) Africaa World 1944 2412 2368 2937 3289 3365 4312 3945 4365 Sources: 1984–2000. Cocoa Growers Bulletin 40(1988), 45(1992), 50(1996), 52(2000); 2014–2015. ICCO Quarterly Bulletin of Cocoa Statistics XXXI (2006), XXXIX(2013), (XL 2014) Note: aWest Africa: total production of Cameroon, Cote d’Ivoire, Ghana and Nigeria b Between brackets; percentage of world cocoa production c While no official data exist, it is projected that about 75,000–100,000 tonnes of cocoa beans may have been smuggled from Cote d’Ivoire to Ghana in the 2010–2011 season

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Table 16.2  Global production of cocoa beans, 2014/15–2016/17 (thousand tonnes)

Africa Cameroon Cote d’Ivoire Ghana Nigeria Others Americas Brazil Equador Others Asia & Oceania Indonesia Papua New Guinea Others World total

2014/15 3074 232 1796 740 195 111

72.3%

Estimates 2015/16 2918 73.3% 211 1581 778 200 148

Forecasts 2016/17 3565 75.8% 240 2010 950 225 140

777 230 261 286

18.3%

666 140 232 294

16.7%

757 180 270 307

16.1%

400 325 36 39

9.4%

397 320 36 41

10.0%

397 290 40 49

8.1%

4251

100.0%

3981

100.0%

4700

100%

Source: ICCO Quarterly Bulletin of Cocoa Statistics, Vol. XLIII, NO. 3 Cocoa Year 2016/17

The next section elaborates cocoa production trends in West Africa, with an overview of Cameroon, Cote d’Ivoire, Ghana and Nigeria, the dominant producers in the region, which are examined in turn.

10 An Overview of Cocoa Production in Cameroon Cameroon is a major producer of cocoa beans in the world, accounting for 232,000 tonnes or 5.4% of the global output in 2014 (ICCO, 2017). Cocoa was introduced into the coastal zone of Cameroon in 1892 from South America and has spread throughout the nation’s cocoa belt, representing about 37% of cultivated soil in the nation. The cocoa belt in Cameroon traverses the coastal zone, as well as the centre, south and eastern regions in the country (Republic of Cameroon, 2014). Cocoa beans supply is spread around the nation’s cocoa belt, with 50%, 35% and 15% originating from the southwest, centre and southeast of the country, respectively. Cocoa is a cash crop for about 75% of farmers in Cameroon. Cultivation of the tree is dominated by small-holder farmers, with 80% of the farms yielding 300 kg/Ha (Nkelle, 2010). However, the mean yield of productive cocoa in the southwest is considerably higher, placed at 446Kg/Ha. The cocoa season in Cameroon begins from August to July, with harvests peaking from October to January/February, while a light crop harvest runs from April/May to June/July. Cocoa has emerged as a major cash crop in Cameroon, accounting for more than 15% of annual export revenues. Cocoa production has increased significantly in the nation in recent times, rising from 120,619 tonnes in 2000 to 225,000 in 2013 and

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ranking the country as the fourth largest producer in the world, behind Cote d’Ivoire, Ghana and Indonesia (ICCO, 2014). As a result of rising prices, cocoa production has improved considerably, now accounting for 25% of non-oil exports. Also, cultivation of the tree has spread to 8 out of the nation’s 10 regions, covering an area estimated at 450,000 hectares. The cocoa economy in Cameroon features about 600,000 producers, comprising five million people, who derive their livelihoods, either directly or indirectly from the cocoa economy (ICCO, 2011). However, Cameroon faces a variety of challenges to sustain cocoa production and meet the national target of 300,000 tonnes/annual set for 2015. This is against the backdrop of declining productivity, fuelled by ageing plantations, as well as attacks on trees by diseases and pests. Indications are that as much as 30% of cocoa beans are lost to diseases and pests attacks annually in the country (Fule, 2013). The challenges are compounded by an ageing population of farmers. Other challenges associated with sustainability of cocoa production in Cameroon are as follows (Nfinn, 2005): • Poor knowledge of farmers on the application of fungicides and pesticides on cocoa tree, triggering resistance by pests to chemicals • Lack of inputs by resource-poor farmers • Dearth of warehouses to store dried cocoa • Poor farm-to-market roads • Lack of adequate drying facilities • Price volatility associated with the global markets

11 An Overview of Cocoa Production in Cote d’Ivoire Cote d’Ivoire is the world’s largest producer of cocoa beans, accounting for 42%, or 1796 tonnes in 2014. The country overtook Ghana as the world’s leading producer of cocoa in 1978, with the commodity becoming the nation’s major foreign exchange earner and accounting for 40% of its export earnings in recent times (Revolvry, 2017b). Cocoa production in Cote d’Ivoire is dominated by small-holder farmers, with plots measuring between 0.5 and 2.5 hectares. While cocoa is cultivated in the nation’s tropical agro-ecological zone, located primarily in the southwest until the mid-1900s; over the next 30 years, however, production is expected to spread to the centre and southwest regions of the nation. Cocoa production is largely driven by migrant labour in Cote d’Ivoire, with a large proportion of laborers originating from the north, as well as Mali, Niger and Burkina Faso (Kotecki, 2010). Cocoa production provides employment for one million farmers, while more than six million people rely on it, either directly or indirectly for their livelihoods (ICCO, 2011). Cote d’Ivoire remains the world’s leading cocoa producer since 1999, spurred by a variety of economic reform agenda. At the heart of the government liberalization agenda is the abandonment of price setting, allowing the private sector to handle both marketing and producer prices, which are largely driven by market forces. The

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reform agenda was anchored on three pillars: (i) the creation in January, 2012, of a central body, le conseil du café-cacao (CCC), with representatives of stakeholders responsible for management, development, regulation and price stabilization of cocoa; (ii) the creation of a new marketing framework, involving the forward sale of 70–80% of the coming year’s crop through twice-daily auctions; and (iii) the setting up of a reserve fund at the Central Bank of West African States (banquecentrale des Etats de l’Afrique de l’Ouest-BCEAO) to hedge the risk beyond the normal operations of the price guarantee scheme. The fund, which is projected to reach FCFA 70 billion or €106.7 million, is aimed at protecting against price fluctuations in the world’s cocoa markets (Agritrade, 2012). Prices were initially fixed at 725 CFA or US$1.41 per kilogram – a 9% increase on 2011–2012 average producers’ income. The price was also about 60% of the international market price. During the 2010/11 cropping season, farmers earned about 667 CFA or US$1.29 per kilogram, while the recommended price stood at 1000 CFA, or US$2.00/kilogram (IRIN, 2012). Favourable market prices over the past few years have galvanized cocoa production in Cote d’Ivoire to record levels. According to reports released by the Coffee and Cocoa Council, production increased during the 2016/17 cropping season by 28.5% to a record 2.15 million tonnes. Exports also increased by 23.3% to 1.9 million tonnes, raising producers’ income by 28.6% to 2.013 trillion CFA, the report reveal. While cocoa production continues to show positive prospects into the foreseeable future in Cote d’Ivoire, the development is also accompanied by some daunting challenges. A major issue is the prevalence of child labour on cocoa farms in Cote d’Ivoire. A report on the negative trend estimated 1.8 million children under 15 years were working in West Africa’s farms, with the majority engaged in Cote d’Ivoire (Agritrade, 2012). The report was also complemented by another, released by the US Department of Labor in 2013, revealing that the worst forms of child labour was prevalent on cocoa plantation in Cote d’Ivoire, with 39% of children aged 5–14 years engaged in agriculture, particularly on cocoa farms under conditions of forced labour (Tulane University, 2015).

12 An Overview of Cocoa Production in Ghana Cocoa was introduced to Ghana in 1895, from the Island of Fernando Po (now Bioko) in Equatorial Guinea, and the nation began to export the crop to Europe at the end of the nineteenth century. Ghana has embraced cocoa production as a cash crop, becoming the world’s largest producer and exporter between 1911 and 1976 (Divine Chocolate, 2011). Cocoa plays a vital role in Ghana’s economy, employing approximately 800,000 farm families distributed over six of the ten regions in the country. The crop generates about US$2 billion in annual foreign exchange earnings and accounts for about 10% of the country’s annual gross domestic product (COCOBOD, 2017). While Ghana has lost its leading position in cocoa production to Cote d’Ivoire, it remains, by far, the second largest producer of cocoa beans in the

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world, estimated at 740,000 tonnes or 17.4% of the global output in 2014 (ICCO, 2017). While the cocoa economy now enjoys limited government intervention in Ghana, the reverse was the case in the past. Indeed, the colonial administration in Ghana took over the administration of cocoa trade in the 1930s, in the wake of promising prospects of the commodity becoming a viable source of government revenue and foreign exchange earner. It set up a monopoly, Ghana Cocoa Board (COCOBOD), buying all cocoa produced in Ghana. This agency, first under the colonial government and then the Independent Ghanaian government, also aimed at protecting farmers from incessant price volatility. The government has intervened positively to sustain cocoa production, through a research institute, as well as provision of such critical inputs as fertilizers and agrochemicals and a quality control division which has preserved Ghana’s reputation for high-quality cocoa beans. However, cocoa production in Ghana is associated with a number of challenges. Price volatility in the world’s markets has been accompanied by instability of cocoa production in the nation. For example, in the late 1970s, cocoa prices declined by more than two-thirds, plunging the cocoa economy in Ghana into a crisis. The situation was compounded by the fact that farmers were being paid only 40% of the global market prices by COCOBOD, triggering abandonment of cocoa production by farmers. Production levels further declined with the droughts and bush fires in the early 1980s, causing a sharp decline in Ghana’s cocoa production from a third of the global output in 1972 to just 12% in 1983. This development prompted an intervention by the World Bank and the International Monetary Fund (IMF), with the Structural Adjustment Program (SAP), which brought a reform agenda that liberalized the cocoa economy, freeing the sector from government control and subjecting it to the vagaries of market forces (Laven & Boomsma, 2012). Another challenge associated with the cocoa economy in Ghana is the prevalence of child labour. Like Cote d’Ivoire, child labour in Ghana’s cocoa farms is an obnoxious practice that has assumed a worrisome dimension in recent times. This development has attracted the attention of the international community, spurring intervention to stem the tide (IDS/UG, 2008). The prevalence of child labour is, indeed, a symptom of endemic poverty, which has continued to undermine the development of Ghana’s cocoa economy. While the poverty headcount ratio has declined among cocoa producing households from 60.1% in the 1990s to 23.9% in 2005, it remains a worrisome issue in the country, attracting the attention of policymakers.

13 An Overview of Cocoa Production Trends in Nigeria Nigeria is acknowledged as the fourth largest cocoa producer in the world, behind Cote d’Ivoire, Ghana and Indonesia, and accounting for 5.9% of the global output in 2013 (Südwind et  al., 2013). The country is also the third largest exporter of cocoa beans, behind Cote d’Ivoire and Ghana. The crop remains a major non-oil

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export earner in Nigeria, a position dating back to colonial times. Indeed, Nigeria was the second largest producer of cocoa in 1970, when the nation relied on agriculture as the cornerstone of its economy. However, the emergence of crude oil in the early 1970s resulted in the marginalization of Nigeria’s agricultural economy, creating a sharp decline in cocoa production. By 2010, cocoa production in Nigeria only accounted for a paltry 0.3% of GDP, while production between 2000 and 2010 averaged 389,272 tonnes per annum (Revolvry, 2017a). Cocoa was introduced to Nigeria in the 1870s in Bonny and Calabar. The crop’s production shifted to Southwest Nigeria, which accounts for more than 70% of the nation’s annual output. The south-south and south-east geopolitical zones account for the balance. These regions are located in the nation’s tropical agro-ecological zones, which are most suitable for cocoa production. Prior to the advent of the petroleum industry in Nigeria, cocoa was the nation’s prime source of government revenue and foreign exchange earner, with production peaking in 1970, when it produced 308,000 tonnes. Thereafter, production continued to decline, dropping sharply in 1980 and 1981 to 155,000 tonnes and declining further to 110,000 tonnes by 1990 and 1991 cropping season (Adeyeye, 2011). Persistent decline in Nigeria’s cocoa production in the 1970s and 1980s alarmed policymakers, triggering a reform agenda for the cocoa economy and grounded in the Structural Adjustment Program (SAP), which was embraced in 1986. The reform agenda included the abolition of the Cocoa Marketing Board, which allowed farmers to sell directly to exporters at the prevailing global market prices. Also, farmers engaged in exports were allowed to keep the proceeds in foreign currency. This development provided the incentives to revive the cocoa economy in Nigeria, with annual output increasing from 2000 to 2006 significantly (FAO, 2013b). Cocoa production is dominated by resource-poor, small-holders, cultivating between 0.5 and 2 hectares of land. However, production is driven largely by family labour, which limits average production. Nigeria’s cocoa production is characterized by low yields, estimated at 500 kg (0.5 tonnes) per hectare. The nation features some of the lowest yields, compared with those from Ghana, Cameroon and Cote d’Ivoire, according to the FAO (2013b) report. Apart from low yields, dwindling cocoa production trends in Nigeria is attributable to ageing farmers and plantation, as well as damages caused by diseases and pests. Indeed, about 60% of cocoa farms are 40 years old, with declining productivity. The United States Department of Agriculture (USDA) (2014) identified some of the most critical factors limiting cocoa production in Nigeria: (i) dearth and low utilization of fertilizers, despite declining soil fertility; (ii) shortage and high cost of farm labour; (iii) the effect of climate change is becoming more severe, lengthening the dry season, undermining productivity and affecting the rate of new plantings; (iv) poor access roads to the major producing areas; and (v) inadequate subsidies for such critical inputs as fertilizers and seedlings, as these are often diverted by middlemen and politicians.

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14 Concluding Remarks Agroforestry is a relatively new practice, which integrates trees and shrubs with cropping systems and/or animal husbandry in order to boost agricultural productivity and conserve natural resources. The practice has gained international acclaim, particularly against the backdrop of the emergent global climate change. Agroforestry is increasingly embraced in West Africa, where the region’s primary forest cover has suffered severe loses during the past several decades. The region has lost 90% of its primary forest cover since the end of the nineteenth century, driven by such anthropogenic forces as fuel wood consumption, logging, demographic explosion, rapid urbanization, mining and agricultural extensification, amongst others. The trend has been compounded by climate change and variability, which have undermined the region’s fragile ecological systems, with the loss of biodiversity. The destruction of West Africa’s forest resources holds implications for the sustainability of cocoa, a major ingredient for the manufacture of chocolate. The region accounts for more than 70% of the world’s annual cocoa production. However, increasing deforestation, among other critical challenges, is posing a threat to the sustainability of future cocoa production. Consequently, stakeholders in the cocoa-­ chocolate industry have embarked on concerted efforts to revive cocoa plantations in the region by embracing agroforestry practices that render cocoa trees more resilient to climate change. The reforestation of cocoa farms is acknowledged as a robust climate adaptation strategy to bolster long-term sustainability of cocoa production in West Africa. It is noteworthy that the region’s socio-economic profile reveals a population deeply impoverished, with most nations listed alongside the least developed countries in the world. Most of the population also derives its livelihoods from rain-fed agriculture, which is increasingly threatened by the global climate change phenomenon (Beloku, 2016).

References Adeyeye, C. (2011). Cocoa production and price stability: An industrial relations perspective. Available at: www.ilo.org/public/english/iira/documents/congresses/regional/lagos2011. Accessed 7 Dec 2017. Agritrade. (2012, December). Special report: Cote D’Ivoire’s Cocoa sector reforms 2011–2012. Association for temperate Agroforestry (AFTA). (2018). What is Agro forestry? Available at: www.aftaweb.org/about/what-­is-­agroforetry.html. Accessed 25 July 2018. Beloku, J. (2016). Climate change in Nigeria: A brief review of causes, effects and solutions. Available at: https://fmicgov.ng/climate-­change.nigeria-­brief-­review-­causes-­effects-­solution. Accessed 27 May 2018. Butler, R. (2006). Global biological diversity in decline. Available at: https://news.mongabay. com/2006/03/globalbiological-diversity-in-decline/ Accessed 30 July 2018. Climate Path. (2018). The science of climate change: What we know and how we know it. Available at: https://developmenteducation.ie/resource/food.crises.in-­the-­sahel-­the-­crisis-­that-­refuses-­ to-­go-­away. Accessed 27 July 2018.

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Coffee and Cocoa International. (2017, June 15). Companies need governments to help stop deforestation. Available at: https://www.coffeeandcocoa.net/2017/06/15/companies.governments/. Accessed 27 July 2018. COCOBOD (2017). Sustainable cocoa production. Available at: https://www.idhsustainabletrade. com/uploaded/2017/06/COCOBOD_1RT-Cocoa-and-Forests-Initiative.pdf/. Accessed 30 July 2018. Divine Chocolate. (2011). Cocoa and Ghana. Available at: www.divinechocolatte.com/uk/about­us/research-­resources. Accessed 7 Dec 2017. Food and Agriculture Organization of the United Nations (FAO). (2013a). Climate change guidelines for forest managers (FAO forestry paper 172). FAO. Food and Agriculture Organization of the United Nations (FAO). (2013b, February). Analysis of incentives and disincentives for cocoa in Nigeria. Monitoring African food and agricultural policies. FAO. Food and Agriculture Organization of the United Nations (FAO). (2015). Definition of Agro forestry. Available at: www.FAD.org/forestry/agroforestry/80338/en/. Accessed 25 July 2018. Foli, E., & Kleine, M. (2014). IUFRO: Reducing Deforestation and Forest Degradation in Central and West Africa / Current Activities and Projects / Special Programme for Development of Capacities. Available at: http://www.iufro.org/science/special/spdc/actproj/reddes-main/ Accessed: 30 July, 2018. Fule, C. (2013). Historic Cocoa farming in Cameroon. Future for smallholders? Available at: https://www.siani.se/blog/historic-­cocoa-­farming-­cameroon-­future-­for-­smallholders? Accessed 4 Dec 2017. Garcia-Carreras, L., & Parker, D. (2011). How does local tropical deforestation affect Rainfall? Available at: https://personalpages.manchester.ac.uk/staff/luis.garcia-carreras/files/2011a_garcia-carreras.pdf/ Accessed: 30 July, 2018. Hartley, A., Rowell, D., Jaricot, S., Guichard, F., Macadam, I., Taylor, C., & D. Parker (2016). West Africa Regional Review: A century of climate change – 1950 to 2050. Future climate for Africa. Huffington Post. (2018). Cocoa farming: The key to reversing deforestation in West Africa. A feature article published on 18th January. Hulme, M. (2017). Climate change, concept of. In D. Richardson (Ed.), The international encyclopedia of geography: People, the earth, environment and technology. American Association of Geographers and Wiley. Idowu, A., Ayoola, S., Opele, A., & Ikenweiwe, N. (2011). Impact of climate change in Nigeria. Iranica Journal of Energy and Environment, 2(2), 145–152. Igbatayo, S. (2018). Fostering climate-resilient biodiversity framework in West Africa and implications for regional development. In W. Leal Filho (Ed.), Handbook on climate change resilience. Springer International Publishing AG. Institute of Development Studies (IDS)/University of Ghana (UG). (2008). Mapping sustainable production in Ghanaian Cocoa. Report to Cadbury. Integrated Regional Information Networks (IRIN). (2012). Cocoa farmers welcome state-imposed prices. Available at: www.irinnews.org/news/2012/12/11/07cocoa-­farmers-­welcome-­state-­ imposed-­prices. Accessed 6 Dec 2017. Intergovernmental Panel on Climate Change (IPCC). (2007). The regional impacts of climate change: African coastal zones (Fourth assessment report). Intergovernmental Panel on Climate Change (IPCC). International Centre for tropical Agriculture (CIAT). (2011, September). Predicting the impact of climate change on the Cocoa-growing Region in Ghana and Cote D’ivoire (Final report). International Centre for tropical Agriculture (CIAT). International Cocoa Organization (ICCO). (2011). Sanitary and Phytosanitary Standard (SPS): Cameroon. Available at: www.icco.org/sites/sps/index.html. Accessed 4 Dec 2017. International Cocoa Organization (ICCO). (2014). Cocoa year in Cameroon 2013/2014. Quarterly Bulletin of Cocoa Statistics, XL(1).

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International Cocoa Organization (ICCO). (2017). Quarterly Bulletin of Cocoa Statistics, Vol. XLIII, No. 3, Cocoa year 2016/17. International Union of Forest Research Organizations (IUFRO). (2015). Reducing deforestation and forest degradation in central and West Africa. Available at: https://www.iufro.org/science/ special/spdc/actpro/reddesmain/Accessed 30 July, 2018. Khaligian, A. (2012, January 13) The Guinean Forests of West Africa critically Endangered. Biodiversity hotspot Eco-tours. Issue No. 17. Kotecki, S. (2010). Cocoa and development in Cote D’Ivoire. A master of arts degree thesis: University of Florida. Laven, A., & Boomsma, M. (2012). Incentives for Sustainable Cocoa Production in Ghana. Moving from Maximizing Outputs to Optimizing Performance. Lawrence, D., & Vandecar, K. (2015). Effects of tropical deforestation on climate and agriculture. Available at: https://www.semanticscholar.org/paper/Effects-of-tropical-deforestation-onclimate-and-Lawrence-Vandecar/6031c89cab819e38fc25581df69fc24790f5d6ab/. Accessed 30 July 2018. Martin, F., & Sherman, S. (1992). Agro forestry principles. Echo technical note. (Revised and updated by Motis, T. (2007)). Microsphere (2018). Guinean forests of West Africa biodiversity hotspots. Available at: https:// www.microsfere.org/index.php/guinean-forests-of-west-africa-biodiversity-hotspot/. Accessed 30 July 2018. Morote, A.  F., Hernández, M., & Eslamian, S. (2020). Rainwater harvesting in urban areas of developed countries. The state of the art (1980–2017). International Journal of Hydrology Science and Technology, 10(5), 448–470. https://doi.org/10.1504/IJHST.2020.10029926 Nair, P. K. R. (1993). An introduction to agro forestry (In collaboration with International Centre for Research in Agroforestry). Available at: https://www.worldagroforesty.org.units/Library/ Books/PDFs/32-­An-­Introduction-­to-­agroforestry. Accessed: 25 July 2018. National Aeronautic and Space Administration (NASA). (2013). What are climate and climate change? Available at: https://www.nasa.goalaudience/forstudents/5-­8/features/nasa-­knows/ what-­is-­climate-­change58-­html. Accessed 27 July 2018. Nfinn, T. (2005). Cocoa production in Cameroon. In Proceedings of the 9th North American Agro forestry Conference. Nix, S. (2017). The African Rain Forest. Available at: https://www.thoughtco.com/african-­ rainforest-­1341794. Accessed 25 July 2018. Nkelle, N. (2010). The sustainability of Cameroon Cocoa economy. Available at: https://www.icco. org/sites/www.roundtablecocoa.org/documents/3%20mr.%20Ngo%Nkelle%20Victor%-­%20 Cameroon.pdf. Accessed 6 Dec 2017. Republic of Cameroon. (2014). The Cameroon Cocoa Story. The Department of Crop Science. (In association with Südwind, Supply Change and Global 2000). Revolvry. (2017a). Cocoa Production in Ivory Coast. Available at: https://www.revolvy.com/topic/ cocoaproductioninIvoryCoast. Accessed 6 Dec 2017. Revolvry. (2017b). Cocoa Production in Nigeria. Available at: https://www.revolvy.com/amin/ index.php?s=cocoaproductioninNigeria. Accessed 7 Dec 2017. Robinson, R., & Brooks, R. (2010). West Africa: The climate of change climate change impacts, awareness and preparedness across West Africa. Sahel and West Africa Club (SWAC)/Organization for Economic Cooperation and Development (OECD). (2007). Atlas on Regional Integration in West Africa economy series. Cocoa. Südwind, INKOTA, & Mondo and EAP. (2013). Make chocolate fair. An Enlightenment Campaign. The International Centre for Tropical Agriculture (CIAT) (2011). CIAT warns on climate change impact on cocoa production. Available at: https://sdg.iisd.org/news/ciat-warns-of-climatechange-impact-on-cocoa-production/. Accessed 25 July 2018. Tulane University. (2015). Survey research on child labour in west African cocoa growing areas. School of Public Health and Tropical Medicine.

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United Nations Conference on Trade and Development (UNCTAD). (2019). The least developed countries report, 2019. The Present and Future of External Development Finance-old dependence, new challenges. Available at: https://unctad.org/en/PublicationsLibrary/ldcr2019_ en.pdf/. Accessed 25 Sept 2020. United States Department of Agriculture (USDA). (2011). USDA Agro forestry strategic framework. Available at: https://www.usda.gov.sites/default/files/documents/factsheet-­final. Accessed 25 July 2018. United States Department of Agriculture (USDA). (2014, August). Nigeria hikes target on Cocoa production (USDA Foreign Agricultural Service). Global Agricultural Information Network. United States Geological Survey (USGS) (2015): Biodiversity and Protected Areas in West Africa. Available at: “https://eros.usgs.gov/westafrica/biodiversity-protected-areas”Biodiversity and Protected Areas in West Africa | West Africa/ Accessed: 30/10/2023. United Nations (2019). The least developed countries report 2019. Available at: https://unctad.org/ webflyer/leastdeveloped-countries-report-2019/. Accessed: 25 Juy, 2018. USDA (2018). Agro forestry Practices. Available at: https://www.fs.usda.gov/nac/practices/ Accessed: 25 July, 2018. USAID. (2012). Climate change adaptation in Western Africa. Available: https://www.climatelinks.org/sites/default/files/assets/document/west-­africa/. Accessed 27 July 2018. USAID (2018a). Wet Africa Biodiversity and Climate Change (WA BICC). Available at: https:// pdf.usaid.gov/pdf_docs/PA00TJX1.pdf/. Accessed 30 July 2018. Wafuke, S. (2012). Adoption of agroforestry technologies among small-scale farmers in Nzoia location, Lugari District, Kenya (A thesis submitted to the graduate school, in partial fulfillment of the requirements of master of science degree in environmental science). Egerton University. Wessel, M., & Quist-Wessel, F. (2015). Cocoa production in West Africa, a review and analysis of recent development. NJAS-Wageningen Journal of Life Sciences, 74–75(2015), 1–7.

Chapter 17

Spatial-Temporal Changes of Water Resources: Associated Impact as a Natural Hazard Yaser Sabzevari and Saeid Eslamian

Abstract  The passage of time and the increasing population and increase in the harvest of the water resources, in addition to the quantitative shortcomings, have created the quality problems. These issues are more significant in arid and semiarid regions, which are more dependent on these resources. Assessing the quantity and quality of water resources, in addition to determining their chemical status in general hydrogeological studies, determines their quality in drinking, agriculture, and industry. These assessments, in groundwater and surface water resources study projects including water reservoir surveys, remote water monitoring, water resources development projects, executive and management plans, watershed and aquifer management, dam and water structures projects, irrigation and drainage projects, biological and environmental surveys, and water supply and distribution projects have a special place. However, the study of the quality of water resources in different regions is essential for the proper management of water resources. Different methods are used to determine the trend of temporal changes. This shows that the study of these changes in each region is necessary due to the impact of quantitative and qualitative variables of water resources and their effectiveness in the occurrence of natural hazards such as environmental problems. Therefore, the purpose of this study is to investigate the temporal-spatial changes of water resources. The results of studies showed a great variability of the surface and groundwater resources with respect to the time and place, which has caused an imbalance in the temporal and spatial distribution of quantitative and qualitative variables of water resources in the different regions. Therefore, this could be hazardous and should be reconsidered in water resources management. Keywords  Quantitative · Qualitative · Groundwater · Surface water · Hazard

Y. Sabzevari · S. Eslamian (*) Department of Water Science and Engineering, College of Agriculture, Isfahan University of Technology, Isfahan, Iran e-mail: [email protected] © Springer Nature Switzerland AG 2023 S. Eslamian, F. Eslamian (eds.), Disaster Risk Reduction for Resilience, https://doi.org/10.1007/978-3-031-22112-5_17

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1 Introduction In general, water crisis can be considered as a natural hazard from both resource and the consumption perspectives. For example, the total renewable water resources of Iran are estimated at 130 billion cubic meters per year. Accordingly, per capita renewable water is estimated to be less than 1700 m3 per year per person, which is much less than the global amount (7000 cubic meters) and slightly higher than the average in the Middle East and North Africa (1300 cubic meters) (Madani, 2014). In 1989, Falkenmark et al. introduced a per capita water stress limit of 1700 cubic meters per year (Falkenmark et al., 1989). According to this index, the reduction of renewable water per capita to less than 1700 m3 per year per person puts the state of Iran’s water resources in a state of water stress. The UN Commission on Sustainable Development’s most recent and most reliable indicator is the reduction of water resources based on the result of the amount of water harvested per year and as a percentage of total annual water resources. According to this index, if the total annual consumption of water resources in each country exceeds 40% of the total annual renewable resources, the country will suffer from a severe water crisis, between 20% and 40% of moderate to the severe water crisis, between 10% and 20% of water crisis in a balanced way, and for the amounts less than 10%, the water crisis will be low (Mohamadjani & Yazdanian, 2014). Given that water consumption in Iran is more than 70% of all renewable water resources (Madani, 2014), so Iran is in a very severe water crisis based on this indicator. At the same time, given the phenomenon of climate change, it does not seem correct to consider these values as the stable values. This is because many researchers have emphasized that the areas located in mid-latitudes (15–40 degrees north) will face the significant increases in temperature and the significant reductions in precipitation in the future (Reidsma et al., 2009). However, there is a disagreement among researchers about the drought in Iran in the last decade, and some consider it to be due to the natural climatic processes, and some consider it to be the permanent climate change in Iran. Competition for water between the different uses of agriculture, industry, and drinking is also increasing. More food production for the world’s growing population takes place mainly in the new Faryab lands, which will increase the water abstraction for agricultural use (Schultz, 2017). Concerns about water quality have been widely felt in the last three decades of the twentieth century, with water quality now as important as quantity. Water pollution as a natural hazard not only affects water quality but also threatens the human health, economic development, and social welfare (Milovanovic, 2007). Understanding the quality of pollutants, determining and studying the temporal and spatial changes of pollutants, is one of the most important components of water resource management studies (Kruse & Eslamian, 2017; Rahbari et  al., 2006). Sources of water pollutants can be point sources such as agricultural drains, urban

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and industrial effluents, and extensive sources such as drainages of agriculture. Due to the importance of water and the effects that pollution can have on the human health and natural ecosystems, water quality monitoring is very important (Nouri et al., 2007). In addition to surface water, groundwater resources are the most important and valuable sources of water supply for the various uses and types of human activities (Prasad & Narayana, 2004). The passage of time and the increasing population and increase in the harvest of these resources, in addition to the quantitative shortcomings, have created quality problems (Zareian & Eslamian, 2021). These issues are more significant in arid and semiarid regions, which are more dependent on these resources (Gaaloul et  al., 2017). In these areas, due to the lack of water resources, access to appropriate quality resources is important (Latif et al., 2005; Shakerian et al., 2011; Zehtabian et al., 2010). Assessing the quantity and quality of water resources, in addition to determining their chemical status in general hydrogeological studies, determines their quality in drinking, agriculture, and industry. These assessments, in groundwater and surface water resources study projects, Water Reservoir Surveys, Remote Monitoring, Water Resources Development Projects, Executive and Management Plans, Watershed Management and Aquifer Management, Dam and Water Structures Projects, Irrigation and Drainage Projects, Biological Surveys Environment, and water supply and water distribution projects, have a special place (Zaghiyan et  al., 2021). On the other hand, the importance of water for health and development is such that the World Health Organization (WHO) has identified the most important shortcoming of the twentieth century as the lack of public access to safe and adequate water resources (Mahdinia et al., 2005). In general, water quality is a relative matter and represents the properties of water, which are defined through physical, chemical, and biological properties. The quantity and quality of water resources operate on a spatial and temporal scale and cannot be assumed to be constant over time and space (Mozafarizadeh, 2006). Therefore, in order to use the water resources and identify the potential for future uses, it is important to examine the changes in the qualitative and quantitative characteristics of these resources over time. In arid and semiarid regions, most of the water supply sources are provided by groundwater sources (Khosravi et al., 2016). Increasing the harvests from these resources and climate change have put more pressure on them (Edmunds et al., 2003; Kulkarni et al., 2015; Zehtabian et al., 2010). In addition to the quantitative issues, this issue has led to quality problems. On the other hand, describing water quality is difficult and costly due to the spatial variability of pollutants and the range of indicators to be measured (chemical, physical, and biological) (El Khanji & Eslamian, 2020). However, the study of the quality of water resources in the different regions is essential for the proper management of water resources (Zehtabian et  al., 2010). Different methods are used to determine the trend of temporal changes.

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1.1 Trend of Changes in Quantitative-Qualitative Variables of Water Resources Various methods are used to determine the trend of temporal change (Zareian and Eslamian, 2008;  Shrestha & Kazama, 2007). In general, these methods can be divided into three categories: graphic methods, parametric methods, and nonparametric methods. One of the most common nonparametric methods in analyzing the trend of time series is the Mann-Kendall test (Adeli et al., 2018; Behmanesh et al., 2016; Pasquini et  al., 2006). In addition, the test is recommended by the World Meteorological Organization to detect the trends in environmental data series. Many researchers in their research have studied the trend of qualitative changes in water resources, some of which are mentioned below. Anderson et al., (2010) in a study with the strong correlation between ecohydrology and ecological quality of rivers, have investigated Scotland’s water quality changes using the Mann-Kendall test. Water has implied the impact of climate change on the water quality of the Scottish River. Mei et al. (2014) evaluated the trend and the temporal and spatial variability of surface water quality between the rural and urban areas. The 11-year statistics have been declining from 2000 to 2010, and water quality indicators show the higher concentrations of pollutants in urban water than in the suburbs and villages due to the population density. Boyacioglu and Boyacioglu (2008) examined the trend of changes in chloride, nitrate, sodium, sulfate, and total solutes at seven stations in the Tahtali watershed of Turkey using the nonparametric Mann-Kendall tests and age gradient estimators. The results show a decrease in the concentration of most of these elements in river water. Kauffman and Belden (2010) analyzed the water quality of 30 American rivers between 1970 and 2005. Using the seasonal Mann-Kendall test, they concluded that water quality remained constant or improved in 69% of the stations. Deilam and Rouhani (2012) conducted a study on the trend of water quality changes in the Gorgan River using Mann-Kendall test. The results of this study showed the significant trends related to the annual water quality variables, especially in the eastern part of the basin. Zare Garazi et al. (2011) by examining the trend of long-term changes in water quality variables of Chehelchai river in Golestan province in Iran with Mann-­ Kendall test showed that the seven parameters have a significant upward trend. Soleimani Sardou et  al. (2012) in a study investigated the trend of the chemical variables in water quality of the Chamjangir River in Khorramabad, Iran. In their study, they used the nonparametric Mann-Kendall test and showed that despite the decreasing trend in the variability of acidity and flow rate, other parameters such as electrical conductivity, bicarbonate, chlorine, calcium, magnesium, and total solids, The solution had an upward and significant trend at the 99% confidence level, which confirms the decrease in water quality and increase in the soluble materials. Dinpazhoh (2016) examined the changes in water quality parameters of a number of rivers in East Azerbaijan in Iran province using the Mann-Kendall test. For this purpose, 10 stations were selected, and the trend of changes in 13 parameters of

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river water quality was analyzed. The trend slope of each component in the statistical period was calculated by the Sen’s slope estimator method. The results showed that in the stations, the trend of positive ion concentration and electrical conductivity is increasing.

1.2 Spatiotemporal Changes of Quantitative-Qualitative Variables of Water Resources Geostatistical methods can reduce the costs and increase the accuracy of estimates due to capabilities such as reducing the number of samples, co-application, and providing more accurate estimates of the location of variables. From a statistical point of view, each sample is related to its surrounding sample to a certain distance and the degree of correlation between the values of the closer samples is probably higher. In recent years, a lot of research has been done in the field of preparing the quality maps of groundwater resources, some of which are mentioned below: Yousefi et al. (2018) did a study for comparison and zoning of groundwater quality in Bojnourd plain in Iran during the dry and wet periods using the SPI, RAI, and PN indices and compared the quality of groundwater resources using the Piper and Wilcox diagrams. The results showed that during the drought period, more than 50% of the sample wells are in a very saline and unsuitable condition for agriculture. Torabipoodeh and Hamehzadeh (2018), in a study to investigate the chemical quality of water and the trend of changes in quality parameters in the Kashkan basin in Iran, extracted and analyzed the Schuler diagram for each station and used the Wilcox diagram to evaluate the water quality in agriculture. The results showed that water quality has decreased in the study area. Belkhiri et al. (2018) evaluated the quality of groundwater and its suitability for drinking and agricultural uses using self-organizing maps. The results showed that the whole sample was divided into three clusters that the electrical conductivity from cluster 1 to cluster 3 was increasing, and the type of water in clusters 2 and 3 was saturated. The ion ratio studies indicate the role of carbonate rock dissolution in increasing the hardness of groundwater, especially in cluster 1. Jeihouni et al. (2018) evaluated the long-term groundwater balance and water quality monitoring in the eastern plains of Lake Urmia in Iran. The results showed that the groundwater balance is negative during the study period. In addition, the quality of aquifers decreased during the study period, which was severe in the west and southwest of the study area. Dev and Bali (2019) evaluated the quality of groundwater and its suitability for drinking and agricultural use in the Congracas region of Himachal Pradesh, India. The results showed that most of the water quality variables are exceeded by the international and regional standards. Jafari et al. (2018) evaluated groundwater quality for drinking and agricultural purposes in Abhar, Iran. The results showed that according to the standard of the World Health Organization and the Iranian standard for drinking, reduced quality, and the main problem in the agricultural sector, the total water hardness was

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estimated. Abbasnia et al. (2018) studied the groundwater quality of Chabahar in Sistan and Baluchestan in Iran for irrigation purposes with the help of irrigation water quality index and its zoning with GIS. The results of 40 wells showed that 40% of the samples classified as water were very good and 60% of the samples were good water. Pawar and Panaskar (2014), in Mumbai, India, using groundwater quality index, studied the temporal and spatial changes in groundwater quality. Their results showed that 74% of the collected samples are in the category of non-potable water and are not suitable for drinking. , in their research, sampled ten different wells throughout Niatin Kora in India and parameters such as TDS, EC, PH, SO4, and CO2 for 4 months from March 2012 to June 2012 based on the method standards measured. The results showed that parameters such as PH, EC, and SO4 were within the range recommended by the WHO, but in some sites, the TDS was higher than the allowable limit.

1.3 Changes in Water Resource Quality Variables with Quality Indicators One of the simple and far from the mathematical and statistical complexities to describe the quality of water is the use of quality indicators (Khosravi et al., 2016). conducted a study in the coastal karst aquifer of Tripoli, Lebanon, along the eastern Mediterranean coast, and concluded that the GQI index can be used for effective planning for water quality management for sustainable resource utilization. Groundwater helps especially in summer when nutrition is limited. used groundwater quality index in their research and found that the main source of water pollution is from agricultural lands around the aquifers and reported that the parameters of ammonia, nitrate, and ammonia nitrogen have a stronger relationship with the water quality index. used the GQI index to identify water pollution sources in the Udaipur region of India and concluded that fluoride, sodium, EC, and TDS are significantly increasing. Judoi and Zare (2009) used the GQI index to study the groundwater quality of Feyzabad plain in Iran for drinking. They concluded that the GQI method is consistent with the other methods of assessing groundwater quality and can be used as a reliable indicator for spatial and even temporal changes in the groundwater quality. Dashti Barmaki et al. (2014) in the evaluation of groundwater quality index (GQI) in Lenjanat aquifer in Iran concluded that groundwater quality in the study area is moderate and relatively high. Khosravi et al. (2016) studied the temporal and spatial changes of groundwater quality in Yazd-Ardakan plain in Iran using the GQI index. The result of the study showed that the trend of the GQI index in the region is decreasing and land use has a great role in reducing the GQI index and consequently the groundwater quality of Yazd-Ardakan plain. Dabiri et al. (2016) evaluated the changes in groundwater quality of Sangan-Khaf plain in Iran using the GQI index. The results showed that the value of this index for the study plain varies between

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66.01% and 81.39%, which indicates the average to acceptable water quality of the region. This index has decreased in the direction of groundwater flow, which indicates the effect of lithogenic changes in the presence of calcareous layers and clay belts in the region. In the study of Nasrabadi and Maedeh (2014), which examined the quality index in groundwater in Tehran in Iran, it was observed that water quality in 2012 was lower than in 2011. Also, the value of the index in the eastern and southern parts of Tehran is higher than the other sampling sections, indicating the lower water quality of these areas.

1.4 Hazards Due to Quantitative and Qualitative Changes in Water Resources Increased groundwater abstraction and declining water levels over several consecutive years cause cracks and subsidence. Because due to the drop in groundwater level, water is drained from the pores of the soil, and the weight of the topsoil causes air to escape from the pores and the ground settles, which in some cases causes cracks, etc. Land subsidence is one of the geomorphic hazards, which has a slow motion and shows its destructive effects in the long run. Occurrence of this hazard can be a factor in creating and intensifying the vulnerability of the focus of human activities located in substrates with natural hazardous infrastructure. The salts in the water on the soil surface, in addition to salinization and soil hardening, caused the accumulation of salts around the plant roots, reduced growth, poisoning, and premature aging of the plant. Among these, attention to the total hardness, EC, TDS, pH, chlorine, and sodium parameters is very important. Since sodium chloride (Nacl) is the most abundant and soluble salt, and its presence in the soil causes osmotic stress, loss of ionic balance, limits the growth and reduced plant yield. Due to the decrease in quality and increase in the amount of groundwater quality parameters, a decrease in yield occurs for crops. Even salt-tolerant plants may have reduced yields due to declining groundwater quality due to improper abstraction from the aquifer, advancing saline water fronts, decreasing water levels, increasing solutes in the water, and the use of the poor irrigation. Increasing the concentration of certain parameters in water resources can also pose a risk to humans. High concentrations of soluble solids cause cardiovascular problems; liver, kidney, bone, and skeletal diseases; mucosal diseases; cancer; and thyroid disease. High concentrations of total hardness cause kidney, cardiovascular disease, esophageal and gastric cancers, hypertension, atherosclerosis, and kidney and bladder stones in the susceptible individuals. The residual chlorine in combination with the organic matter in the water forms a compound called trihalomethane, which has been shown to be carcinogenic. It can also cause miscarriage, eye disease, and neurological disorders. Excess sodium causes heart problems, gill light damage, and in some cases instant death in infants, high blood pressure, thinning and rupture of small artery walls, and damage to the brain and eyes. High

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concentrations of calcium and magnesium sulfates also cause diarrhea, especially in cocaine. The study of various researches in the field of temporal and spatial changes of water resources shows that the study of these changes in each region is necessary due to the impact of quantitative and qualitative variables of water resources and their effectiveness in the occurrence of natural hazards such as the environmental problems. Therefore, the aim of this study is to investigate the temporal-spatial changes of water resources particularly aquifers for controlling the groundwater pollution and drawdown hazard.

2 Methodology The different methods are used by various researcher to study the temporal-spatial changes of water resources. The following are methods that are more common in the subject under study.

2.1 Mann-Kendall Test So far, different methods have been proposed to study the trend of time series, which are generally divided into three categories: graphical methods, parametric methods, and nonparametric methods. Nonparametric tests are not sensitive to the pattern of data distribution and can be used if the data are not normal (Behmanesh & Azad Talatapeh, 2015). Their distribution is random, so using parametric methods such as Pearson’s method to determine the trend for this data is difficult and the result will not be very accurate, so the nonparametric Mann-Kendall test for this purpose has been used (Ansari et al., 2016). The Mann-Kendall test is used to check for the presence or absence of the trends over time for each time series. This test is based on nonparametric linear regression logic. The results of this test show whether there is a significant increase or decrease in the level of certainty in the variable time series trend or not (Pasquini et al., 2006). The nonparametric Mann-Kendall test is not sensitive to the normality of the data. The Mann-Kendall test was first developed by Mann (1945) and then developed by Kendall (1975). The use of this method was recommended by the World Meteorological Organization (Stasik et al., 2016). One of the strengths of the Mann-­ Kendall method is that it is suitable for the time series that do not follow a specific distribution. In this study, Excel software was used to determine the trend by Mann-­ Kendall test. This method is used to examine the trend of data. In this method, the S statistic for the gth month and the kth station is calculated as follows (Yue et al., 2002):

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n 1 n 1



Sgk    sgn  X jgk  X igk  ,   i  j  n i

j  i 1

(17.1)

where n is the number of series data and sgnθ is a function of the sign and θ is the difference between the two observations in each of the studied variables in the different years i and j, which is defined as follows: if 1  Sgn     0 if 1 if 



0 0 0

(17.2)

Mann and Kendall showed that when n ≤10 is 10, the S statistic is distributed almost normally and has a mean of 0 and the following standard deviation (Ansari et al., 2016):



 

gg k

 n  n  1  2 n  5    d  d  1  2 d  5    18

(17.3)

where d is the same number of data in the time series. In this method, Sgk is normalized as follows:

 Sgk  Sgk – sgn  Sgk 



(17.4)

Then the standardized test statistic or Z, which has a standard normal distribution with a mean of zero and a variance of 1, is obtained as follows: Z gk 

 Sgk

 

1/ 2

gg

(17.5)

Assumption zero (lack of trend at significance level ∝) is accepted as long as −Z1+a/2 ˂ Zgk ˂ Z1+a/2 otherwise rejected (Ansari et al., 2016).

2.2 Modified Mann-Kendall Test If the first-order autocorrelation coefficient of the data set is significant, the autocorrelation effect is removed from the data series by pre-bleaching. To deny, first, the new data series with respect to the slope of the trend line, β, is calculated as follows:

yI  X I – r1 X i1



(17.6)

Y. Sabzevari and S. Eslamian

396

where β is the slope of the trend line. Then, the new series is obtained as follows: yI  X I – r1 X i1



(17.7)

r1 is the first-order autocorrelation coefficient. By re-adding the trend sentence (β × i) to the recent data series, the following series is obtained: yi  yi –    i 



(17.8)



If the value of Z is greater than ±1.96, the data has a trend, and the null hypothesis is rejected; otherwise, it has no trend. Z: Is the standard normal distribution statistic and can take different values in a two-domain test depending on the confidence levels tested. The value of Z statistic for 95% and 99% confidence levels is considered equal to 1.96 and 2.58, respectively.

2.3 Investigating the Quality of Water Resources for Agricultural Purposes 2.3.1 Permeability Index (PI) The permeability index is a parameter used to evaluate the quality of irrigation water and is expressed by Eq. 17.9: PI 

Na   HCO3 Ca 2   Mg 2   Na 



100

(17.9)

All ions in this equation are in milliequivalents per liter. Doonen (1964) divided irrigation water according to the permeability index, according to which water can be classified as categories 1, 2, and 3 for the proper irrigation and category 3 with maximum (PI), 25% for unsuitable irrigation. Table 17.1 shows water classification based on permeability index (PI).

Table 17.1  Water rating based on PI PI >75 25–75