Climate Risk Assessment for Ecosystem-based Adaptation A guidebook for planners and practitioners Published by: in cooperation with: As a federally owned enterprise, GIZ supports the German Government in achieving its objectives in the field of international cooperation for sustainable development. Published by: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH Registered offices Bonn and Eschborn Global Project “Mainstreaming EbA — Strengthening Ecosystem-based Adaptation in Planning and Decision Making Processes“ Address Friedrich-Ebert-Allee 36 + 40 53113 Bonn, Germany T +49 228 4460-1535 F +49 228 446080-1535 E arno.sckeyde@giz.de I www.giz.de; www.adaptationcommunity.net This project is part of the International Climate Initiative (IKI). The Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) supports this initiative on the basis of a decision adopted by the German Bundestag. Authors: Michael Hagenlocher1), Stefan Schneiderbauer2), Zita Sebesvari1), Mathias Bertram3), Kathrin Renner2), Fabrice Renaud4), Helen Wiley1), Marc Zebisch2). 1 ) United Nations University, Institute for Environment and Human Security (UNU-EHS), Bonn, Germany 2 ) Eurac Research, Institute for Earth Observation, Bolzano/Bozen, Italy 3 ) Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), Bonn, Germany 4 ) University of Glasgow, School of Interdisciplinary Studies, Dumfries Campus, Dumfries, United Kingdom Suggested citation: GIZ, EURAC & UNU-EHS (2018): Climate Risk Assessment for Ecosystem-based Adaptation – A guidebook for planners and practitioners. Bonn: GIZ. Design and editing: Additiv. Visuelle Kommunikation, Berlin, Germany Photo credits: Cover - GIZ/Harald Franzen, p. 17, 25, 29, 30, 31, 37, 49, 50, 51, 53, 56, 68, 69, 76, 78, 81, 88 - GIZ p. 43, 45, 59, 61, 63 - @MINAM, Peru, 2017 URL links: This publication contains links to external websites. Responsibility for the content of the listed external sites always lies with their respective publishers. When the links to these sites were first posted, GIZ checked the third-party content to establish whether it could give rise to civil or criminal liability. However, the constant review of the links to external sites can- not reasonably be expected without concrete indication of a violation of rights. If GIZ itself becomes aware or is notified by a third party that an external site it has provided a link to gives rise to civil or criminal liability, it will remove the link to this site immediately. GIZ expressly dissociates itself from such content. On behalf of Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) Berlin and Bonn GIZ is responsible for the content of this publication. Bonn 2018 Climate Risk Assessment for Ecosystem-based Adaptation A guidebook for planners and practitioners Contents Acknowledgements 9 Quick tour guide 9 I. Introduction 11 Context of this Guidebook Target group 12 Instructions for using the Guidebook 14 Introduction to the application example 15 II. Conceptual framework 18 The IPCC AR5 risk concept in the context of social-ecological systems (SES) Social-ecological systems (SES) 18 Risk 18 Hazard 20 Exposure 20 Vulnerability 21 Impacts 21 Reducing risk through adaptation 22 III. Guidelines 23 Module 1: Preparing the risk assessment 25 Module 2: Developing impact chains 32 Module 3: Identifying and selecting indicators for risk components 43 Module 4: From data acquisition to risk assessment 49 Module 5: Normalisation of indicator data 53 Module 6: Weighting and aggregating indicators 59 Module 7: Aggregating risk components to risk 63 Module 8: Presenting and interpreting the outcomes of the risk assessment 66 Module 9: Identifiying adaptation options 74 IV. How to use the risk assessment for monitoring and evaluation 82 V. Concluding remarks 84 Literature 85 VI. The EbA Guidebook Annex 89 Qualification criteria and quality standards for EbA – the FEBA example 89 Additional sources where EbA measures are presented 91 Application example 2: Adaptation to salinity intrusion in low elevation coastal zones 95 List of boxes List of tables Box 1: ...............................................13 Table 1: ...............................................24 Concepts and definitions related to Overview of the nine modules of this Guidebook Ecosystem-based Adaptation Table 2: ...............................................39 Box 2: ...............................................35 Ecosystem-based and conventional adaptation Additional interlinkages between factors of the options impact chains Table 3: ..............................................48 Factors and indicators for each risk component Table 4: ...............................................52 Original data for the different indicators Table 5: ...............................................54 Example of indicators and their scales of measurement Table 6: ...............................................55 Class scheme for variables with ordinal scale Table 7: ...............................................57 Direction, min-max values and defined thresholds for each indicator Table 8: ...............................................58 Normalised data for the different indicators Table 9: ..............................................61 Aggregated indicators (hazard, exposure, vulnerability) Table 10: .............................................64 Risk classes Table 11: .............................................65 Risk scores List of tables_Annex List of figures Table_Anx 1: .....................................89 Figure 1: ...............................................15 FEBA EbA qualification criteria EbA Mainstreaming cycle Table_Anx 2: .....................................94 Figure 2: ...............................................17 Sources of online databases containing EbA Land use types in the river basin measures Figure 3: ...............................................19 Table_Anx 3: ...................................103 Illustration of the core concepts of the Ecosystem-based and conventional adaptation IPCC WGII AR5. options Figure 4: ...............................................22 Table_Anx 4: ...................................107 Adaptation can reduce the risk by reducing the Indicators for each risk component vulnerability and sometimes the exposure Table_Anx 5: ...................................109 Figure 5: ...............................................33 Raw data for the different indicators – Structure and key elements of an impact chain attributes for each district Figure 6: ...............................................37 Table_Anx 6: ...................................110 Impact chain with intermediate impacts and Direction, min-max values and defined hazard factors identified thresholds for each indicator Figure 7: ...............................................38 Table_Anx 7: ...................................111 Impact chain with vulnerability factors added, in- Normalised data for the different indicators – cluding ecological and social sensitivity and capacity attributes for each district Figure 8: ...............................................40 Table_Anx 8: ...................................112 Impact chain with exposure added Aggregated indicators (hazard, exposure, vulnerability) and risk scores Figure 9: ...............................................41 Entry points for adaptation practitioners working on natural resource conservation and management Figure 10: .............................................42 Ecosystem-based and conventional adaptation options Figure 11: ...............................................46 Figure 22: ...............................................72 Impact chain with hazard indicators added Comparing exposure indicator values of District 3 and District 5 visualised in a bar chart Figure 12: ...............................................47 Impact chain with indicators Figure 23: ...............................................73 Vulnerability indicator values for District 3 Figure 13: ...............................................51 and District 4 shown as a spider diagram Visualisation of original data following data acquisition Figure 24: ...............................................75 Figure 14: ...............................................60 Different spatial relationships between Aggregating single factors to risk components ecosystem service provision areas (P) and ecosystem service benefiting areas (B) Figure 15: ...............................................62 within social-ecological systems (SES) Maps of the six districts and their aggregated hazard, exposure and vulnerability values Figure 25: ...............................................76 Suggested EbA measures to tackle flood risk Figure 16: ...............................................64 in District 4 Scheme for aggregating the risk components Figure 26 ...............................................79 Figure 17: ...............................................65 Co-benefits and potential unintended Aggregated risk index consequences of EbA measures Figure 18: ...............................................69 Figure 27: ...............................................83 Cause and effect relationships describe the M&E of adaptation through repeated risk situation and helped identify potential EbA assessment adaption measures Figure 19: ...............................................70 Map showing the overall risk value and the contributions of each risk component per district Figure 20: ...............................................71 Aggregated risk components and overall risk for all six districts of the river basin shown as a bar chart Figure 21: ...............................................71 Aggregated risk components visualised for all six districts of the river basin as radar chart Figure_Anx 10: .....................................114 List of figures_Annex Aggregated risk components to a composite risk index Figure_Anx 1: .......................................90 Figure_Anx 11: .....................................115 Example assessement framework of EbA quality Suggested EbA measures to tackle salinity standards for Element A ‘helping people to adapt’ intrusion risk and qualification criteria 1 Figure_Anx 12: .....................................116 Figure_Anx 2: .......................................95 Co-benefits and potential unintended Land use along the coastline consequences of EbA measures Figure_Anx 3: .......................................99 Impact chain with intermediate impacts and hazard factors identified Figure_Anx 4: .....................................100 Impact chain with vulnerability factors added, including ecological and social sensitivity and capacity Figure_Anx 5: .....................................101 Impact chain with exposure added Figure_Anx 6: .....................................102 Entry points for adaptation practitioners and planners working on natural resource conservation and management Figure_Anx 7: .....................................104 Visualisation of potential adaptation measures (incl. EbA measures) in the impact chain Figure_Anx 8: .....................................106 Impact chain with indicators Figure_Anx 9: .....................................113 Visualisation of aggregated hazard, exposure and vulnerability component Abbreviations AR4 IPCC Fourth Assessment Report AR5 IPCC Fifth Assessment Report BMU Federal Ministry for the Environment, Nature Conservation and Nuclear Safety BMZ Federal Ministry for Economic Cooperation and Development CBA Cost-benefit analysis CBD Convention on Biological Diversity CCA Climate Change Adaptation CEA Cost-effectiveness analysis DRR Disaster Risk Reduction EbA Ecosystem-based Adaptation Eco-DRR Ecosystem-based disaster risk reduction ESS Ecosystem Services FEBA Friends of Ecosystem-based Adaptation GEF Global Environment Facility GI Green Infrastructure GIS Geographical Information Systems GCF Green Climate Fund IKI International Climate Initiative IPCC Intergovernmental Panel on Climate Change IUCN International Union for Conservation of Nature M&E Monitoring & Evaluation MCA Multi-criteria analysis NAP National Adaptation Plan NBS Nature-based solution PEDRR Partnership for Environment and Disaster Risk Reduction RBC River basin Committee SES Social-ecological system SUL_NBS Sustainable Use of Land and Nature-based Solutions UNCCD UN Convention to Combat Desertification UNISDR UN International Strategy for Disaster Risk Reduction UNFCCC UN Framework Convention on Climate Change WGII Working Group II Climate Change, Mexico), Fernando Camacho Acknowledgements (Commission of Natural Protected Areas, Mexico), Erin Gleeson (The Mountain Institute, USA), Gi- This publication was commissioned by the acomo Fedele (Conservation International, USA), Global Project ‘Mainstreaming EbA – Strengthen- Lili Ilieva (Practical Action, Peru) and Paul Schu- ing Ecosystem-based Adaptation in Planning and macher (GIZ, Central Asia). Decision Making Processes’ on behalf of the Fed- Valuable feedback on the text was provided eral Ministry for Environment, Nature Conserva- by: Alexandra Köngeter (GIZ, Germany), Andrea tion and Nuclear Safety (BMU) under its Interna- Bender (GIZ, Germany), Margarita Victoria Ces- tional Climate Initiative (IKI). pedes Aguero (GIZ, Peru) and Dolores Nuevas Valuable input for this publication was pro- (GIZ, Philippines). vided by two workshops. Contributions dur- The authors would like to thank Janna ing the workshop in Bonn, Germany (24–25 July Frischen for her support in drafting the second 2017), were provided by: Susanne Schwan (GIZ, application example in the annex. Germany), Maylin Meincke (GIZ, Germany), Ro- land Treitler and Jaruwan Ngamsing (GIZ, Thai- land), Luise Richter (GIZ, Vietnam) and Camilo De la Garza Guevara (GIZ, Mexico). Additional contributions were provided dur- ing the 2nd EbA Community of Practice work- Quick tour guide shop in Bangkok, Thailand (21–24 August 2017), Building on and extending the Vulnerability by: Martin Becher (GIZ, Brazil), Mariana Egler Sourcebook (GIZ 2014) and its Risk Supple- (Ministry of Environment, Brazil), Poom Pinthep ment (GIZ and EURAC 2017), this Guidebook and Ratiporn Srisomsap (GIZ, Thailand), Sari- provides guidance on how to systematically ya Srichuae (Department of Public Works and consider ecosystem-based solutions in the Town & Country Planning, Thailand), Nitiphan context of climate risk assessments. Trongkarndee (Department of Water Resources, Thailand), Ravindra Singh (GIZ, India), Albert It demonstrates how to identify potential ad- Magalang (Environmental Management Bureau aptation measures, perform related (spatial) – Department of Environment and Natural Re- planning, and utilise the risk assessment for sources, Philippines), Elizabeth Bandojo (Hous- monitoring and evaluation (M&E) after ac- ing and Land Use Regulatory Board, Philippines), tions have been implemented. Thora Amend and Kathleen Schepp (AMBERO Consult), Vladimir Lekarkin (Committee of En- It presents one consistent and coherent ap- vironmental Protection, Tajikistan), Nguyen Sy proach to address Ecosystem-based Adapta- Linh (Institute of Strategy and Policy on Natural tion (EbA) – other approaches also exist with Resources and Environment, Vietnam), Margarita different underlying concepts, which are fea- Caso Chávez (National Institute of Ecology and sible and used in practice. 9 It introduces key concepts and methodologi- ments to repeated assessments in the imple- cal steps relevant for climate risk assessments mentation or the M&E phases. in the context of EbA and related concepts, It is complemented by an Annex, which pro- illustrating its methodology with a concrete vides: application example. 1. information on qualification criteria and It is designed to provide answers to the follow- quality standards for EbA, ing key questions: 2. additional sources and references where How can climate risk assessments in the con- possible EbA measures are presented, and text of EbA and related concepts be conduct- 3. a second application example where key ed? What are key steps and requirements (e.g. steps of the risk assessment and the identi- in terms of resources, data, and software)? fication of EbA measures are illustrated for a How can climate risk assessments support coastal area. the identification of EbA measures as part of an overall adaptation strategy, their (spa- tial) planning, and their monitoring and evaluation (M&E)? It can be read and used as a stand-alone docu- ment. For additional details on key steps in The following icons will help you navigate the risk assessment procedure, references are through the Guidebook: made to the Vulnerability Sourcebook and its Risk Supplement. ? GUIDING QUESTIONS: It is particularly helpful in cases that require Refers to more detailed information in the a consistent, standardised approach to gather Vulnerability Sourcebook or its Risk Supplement. information on climate related risk and to use this information for adaptation planning. It can be applied at different spatial scales, ranging from local to landscape or even na- tional levels, covering different social, eco- nomic, political and ecological settings and their connections within social-ecological A P P L I C AT I O N E X A M P L E : Preparing the risk assessment systems (SES). It can be applied at different stages of adap- tation planning, from initial baseline assess- 10 I I. I N T R O on health and well-being, additional sources of income, water purification, carbon storage, pol- lination, and recreation services) while contribut- ing to the conservation of biodiversity (CBD 2009). Introduction In recent years, EbA measures have increasingly been promoted and piloted to help people adapt to climate change and reduce climate-related dis- Context aster risk. The current investments in EbA – e.g. of this Guidebook by the International Climate Initiative (IKI) of the German Federal Government, the Global Envi- ronment Facility (GEF) or the Green Climate Fund Introduction into (GCF) – and the increasing recognition of the ap- the thematic scope proach as a cost-effective ‘low-regret’ solution in target group the context of National Adaptation Plan (NAP) structure of the Guidebook processes represents a significant opportunity to a concrete application example promote the uptake of EbA and to mainstream it into general adaptation, disaster risk reduction, Ecosystem-based Adaptation (EbA) is ‘the use and development planning globally. of biodiversity and ecosystem services as part of Climate vulnerability and risk assessments an overall adaptation strategy to help people to are now widely used as a structured way to iden- adapt to the adverse effects of climate change’ tify potential measures as well as most appropri- (CBD 2009). The approach was recognised as being ate locations for the implementation of adapta- cost-effective and generating social, economic, tion and disaster risk reduction (DRR) planning at health and cultural co-benefits, (such as impacts local, national and regional levels. To provide guidelines for standardised assess- ments, the Vulnerability Sourcebook (GIZ 2014) was commissioned by GIZ and developed jointly by adelphi and EURAC Research. Its guidance is based on the concept of climate change vulner- ability as described in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC 2007). The recently devel- oped Risk Supplement to the Vulnerability Source- book (GIZ and EURAC 2017) adapted the climate risk concept as introduced in the Fifth Assess- ment Report (AR5) by the IPCC Working Group II (IPCC 2014a). This risk concept, which is also applied here and adjusted to the EbA context, al- 11 I I N T R O lows for the joint consideration of adaptation and In response to this demand, this Climate DRR measures, making this Guidebook suitable Risk Assessment for Ecosystem-based Adaptation for many more potential users. Guidebook provides a standardised approach to Climate risk assessments in general, and in climate risk assessments in the context of EbA- particular the modular ‘Sourcebook approach’ (GIZ planning by following the well-established, mod- 2014; GIZ and EURAC 2017) to standardised vul- ular Sourcebook (GIZ 2014) methodology and us- nerability and risk assessments, are powerful tools ing an illustrative application example. for identifying effective DRR and climate change adaptation (CCA) strategies. Ideally, they provide relevant information on the climate-related risks Target group of societies, economies and ecosystems, along the dimensions of hazard, exposure and vulnerability. This Guidebook targets both governmental In the context of EbA planning, however, the con- and non-governmental organisations mandated nections and interdependencies between humans, with or engaged in the planning of adaptation, livelihoods, ecosystems and their services need to DRR and development measures. It aims to sup- be taken into consideration, focusing on social- port these processes by providing a standardised ecological systems (SES) as the main unit of analysis, methodology for assessing climate risks in the i.e. complex, integrated systems in which humans context of EbA and to showcase potential co-ben- are part of nature (Berkes and Folke 1998; Ostrom efits of EbA based on direct and indirect linkages 2009). Thus, adaptation planning in the context of to other sectors. EbA represents a departure from the ‘conventional’ The Guidebook is of particular interest to adaptation planning (e.g. in the form of hard engi- technical experts and planners working at local, neered solutions, such as dykes, sea walls, etc.) by sub-national or national levels. It offers an effec- means of 1) a more targeted and systematic incor- tive tool that can: poration of biodiversity and ecosystem services (ESS) into risk assessments, 2) a thorough identifi- provide a sound assessment of climate risk(s) cation of both ecosystem-based and conventional in the context of social-ecological systems adaptation options in a spatially explicit manner, (SES); 3) unveiling both potential co-benefits and unin- tended negative outcomes of ecosystem-based op- improve adaptation and development plan- tions, and 4) identifying feedback loops. During the ning by explicitly considering ecosystem- scoping process for this Guidebook, it has become based and conventional options in the form of apparent that there is a strong demand for guid- integrated ‘adaptation packages’; ance on how to assess climate risk(s) of SES, so as inform the selection and spatial planning of to enable and monitor adaptation planning, con- adaptation measures; sidering both ecosystem-based and conventional adaptation options and providing entry points for support the monitoring and evaluation (M&E) DRR considerations. of adaptation. 12 BOX 1 I Concepts and definitions related to I Ecosystem-based Adaptation N T R This box provides an overview of the most relevant concepts which could benefit from this Guidebook and introduces O the most relevant frameworks, policies and networks associated with these concepts. Ecosystem-based Adaptation (EbA) EbA is the use of biodiversity and ecosystem services as part of an overall adaptation strategy to help people to adapt to the adverse effects of climate change. It aims to maintain and increase the resilience and reduce the vulnerability of ecosystems and people in the face of the adverse effects of climate change (CBD 2009). Ecosystem-based disaster risk reduction (Eco-DRR) Eco-DRR is the sustainable management, conservation, and restoration of ecosystems to reduce disaster risk, with the aim of achieving sustainable and resilient development (Estrella and Saalismaa 2013). Green infrastructure (GI) GI is a strategically planned network of high quality natural and semi-natural areas with other environmental features, which is designed and managed to deliver a wide range of ecosystem services and protect biodiversity in both rural and urban settings. It aims to enhance nature’s ability to deliver multiple valuable ecosystem goods and services, such as clean air or water (EC 2013). Nature-based solutions (NBS) NBS is an umbrella concept for various ecosystem-related approaches. It covers actions to protect, sustainably manage, and restore natural or modified ecosystems that address societal challenges effectively and adaptively, simultaneously providing human well-being and biodiversity benefits. NBS aim to achieve society’s development goals and safeguard human well-being in ways that reflect cultural and societal values and enhance the resilience of ecosystems, their ca- pacity for renewal and the provision of services (Cohen-Shacham et al. 2016). Relevant frameworks, policies, and networks Concept Frameworks & policies Networks EbA UN Framework Convention on Climate Change (UNFCCC), Convention on Friends of EbA (FEBA), EbA Biological Diversity (CBD), UN Convention to Combat Desertification (UNCCD) Community of Practice Eco- Sendai Framework for Disaster Risk Reduction 2015-2030, UN Interna- Partnership for Environment and DRR tional Strategy for Disaster Risk Reduction (UNISDR) Disaster Risk Reduction (PEDRR) GI Sendai Framework for Disaster Risk Reduction 2015-2030, European Natura 2000 network Commission Green Infrastructure Strategy NBS International Union for Conservation of Nature (IUCN), EU Research NbS-4-Resilience, Partnership and Innovation policy agenda on Nature-Based Solutions and Re-Na- on Sustainable Use of Land and turing Cities – Horizon 2020 Nature-based Solutions (SUL-NBS) 13 I I N T R O The Guidebook is written for users with a basic The EbA Guidebook comprises four chapters: understanding of the concepts ‘vulnerability’ and ‘risk’. It not only targets planners and coordinators After the Introduction (Chapter I), Chapter II of risk assessments, but also conservation experts introduces the conceptual risk framework used who are concerned with risk reduction and adapta- in this Guidebook. It clarifies how (and in which tion. Conservation experts – including focal points sense) the terms ‘risk’, ‘hazard’, ‘exposure’, ‘vulner- of the Convention on Biological Diversity (CBD) – ability’, ‘impact’ and ‘adaptation’ are used. The will find guidance on how to engage with the wider framework is based on a state-of-the-art under- adaptation and DRR community in order to better standing of social-ecological risk assessments and achieve joint objectives of sustainable long-term suggests innovative, transparent and reproduc- adaptation and conservation. The Guidebook ac- ible ways to identify, monitor and evaluate EbA knowledges the specific conditions prevailing in measures. The conceptual framework and the many developing countries and emerging econo- definitions provided are particularly targeted at mies, such as limited data availability. readers seeking a more profound understanding Although this Guidebook focuses on EbA of the concepts behind vulnerability and risk as- planning, it acknowledges related concepts such sessments or adaptation planning. as Ecosystem-based disaster risk reduction (Eco- Building on the conceptual framework, DRR), Nature-based Solutions (NBS) and Green Chapter III provides detailed practical instruc- Infrastructure (GI). They could clearly profit from tions for the implementation of risk assessments, the methodology outlined here for the identifica- following the well-established, modular Source- tion and (spatial) planning of appropriate inter- book methodology (GIZ 2014) and using an ap- ventions. Box 1 provides definitions of related plication example to illustrate its implementa- concepts. This may help users find opportunities tion. The nine modules provide simple and clear to use the Guidebook for the planning and imple- step-by-step instructions on the major stages to mentation of Eco-DRR, NBS or GI measures. conducting a risk assessment (Module 1-7), visu- alising and communicating outcomes (Module 8), and identifying EbA measures (Module 9). Some of the more technical modules (mainly Modules 4-7) are very similar to those outlined in Instructions for using the Guidebook the Vulnerability Sourcebook (and are presented in a more condensed form), while the others have This Guidebook is designed as a stand-alone been substantially adjusted to accommodate for document. However, the Vulnerability Sourcebook the special aspects of risk assessments and the (GIZ 2014) and its recent Risk Supplement (GIZ and identification and spatial prioritisation of meas- EURAC 2017) provide additional in-depth direc- ures within the EbA context. tions related to some assessment steps described Each module in Chapter III starts with a brief in Chapter III. Further reference to these docu- overview of key steps and guiding questions. ments is provided where particularly useful. These general explanations are followed by the 14 I I N T R O Figure 1: EbA Mainstreaming cycle (Source: Adapted from GIZ 2016) Module 1 Apply a climate change System of interest & ecosystems lense (social-ecological system) Challenges Environmental & socio-economic parameters Adaptation goals Monitoring & evaluation Assess of adaptation climate risks Chapter IV Modules 2-8 Climate signals Mainstreaming cycle Hazards & intermediate impacts Exposure Vulnerability Risk(s) Implementation Identify adaptation options Module 9 Identify adaptation options Identify co-benefits Prioritise and select adaptation options description of the individual steps, based on a concrete application example, focusing on flood Introducing the application example risk in a river basin. The same application exam- ple is used throughout the nine modules, allow- ing for an integrated understanding of all stages. The application example complements the Finally, Chapter IV provides a short overview on generic step-by-step instructions of the Guide- how to use climate-risk assessments to support the book by illustrating these steps and associated monitoring and evaluation (M&E) of EbA measures. guiding questions using a semi-fictitious case. 15 I I N T R O A P P L I C AT I O N E X A M P L E : ised by scattered, informal settlements, natural Climate change adaptation vegetation cover and agricultural land. It also fea- within river basin management tures two small wetlands. The main urban centre in the basin is located along the administrative boundary between Districts 3 and 4, where the The application example presents a case study elevation is only 8 m above sea level. With a pop- which is typical for many EbA practitioners. It in- ulation of 46,000, both districts combined host volves a river basin with a high risk of loss of lives around 70 percent of the population in the river and of damages to property due to river flooding. basin. Districts 5 and 6 border the coastline and are used primarily for agricultural production and aquaculture. Except for District 1, most of the Description of the river basin including social- river basin has been highly modified through the ecological features: construction of canals, dykes and control meas- ures such as dams. The basin is characterised by a tropical rain- forest climate with temperatures ranging from an average low of 22 °C to an average high of 34 °C. Adaptation challenges: Between May and September, the rainfall amounts to 100 to 150 mm/month, from October to January In the river basin, inadequate coordination the precipitation varies between 250 and 750 mm/ between different sectors and a lack of formal month. The basin comprises an area of approxi- rules for urban planning have increased inunda- mately 550 km² (55,000 ha) with a population of tion and damage levels during flooding events. Be- approximately 100,000 people, concentrated in an cause there is little to no control over the location urban centre that relies economically on the agri- of new settlements, recent developments resulted cultural outputs from the basin. The river basin is in the loss of retention areas, as stream flows were situated in six administrative districts (see Figure 2). modified, while no compensatory measures were The upper catchment of the river basin (Dis- taken to offset losses in ecosystem functions, such trict 1) is located in a forested mountainous area as water storage and regulation. Wetlands and with an elevation of about 1,750 m above sea level floodplains have been converted into agricultural at the highest point and a steep slope gradient of land without leaving buffer strips, and river modi- 1,700 m elevation change within 15 km. In the fications have further increased flow velocity and past, landslides have frequently occurred in the peak flows during flooding events, often relocat- upper river basin, so any change in land use poses ing problems downstream. In addition to land use a potential threat. District 2 is mainly character- changes, flooding in the basin is likely to be exac- 16 I I N T R O erbated because of climate change, with projected Local water management authorities have flooding events increasing in both frequency and determined that it is necessary to perform a risk intensity. Thus, the local population could face assessment in order to identify adaptation meas- large economic losses; crop failure and decline in ures (incl. EbA solutions), which could be put in production not only affects the agricultural sector, place to effectively counter present and future but also business sectors within the urban centre. flood risks in the basin. Figure 2: Land use types in the river basin (Source: authors) Cropland (rainfed) Shrubs Wetlands Cropland (irrigated) Sparse vegetation Rivers Mosaic cropland/natural vegetation Tree cover (flooded, saline water) Districts Mosaic natural vegetation/cropland Settlements River basin Forest Water bodies 17 II II. F R A M E W O R K Social-ecological systems (SES) Conceptual Definition SES: complex ‘systems of people and nature, emphasising that humans must be seen framework as a part of, not apart from, nature’. (Berkes and Folke 1998) By considering a complex systems of people and nature, it pays particular attention to the de- The IPCC AR5 risk concept pendency of people (socio-economic-cultural con- in the context of social-ecological text) on ESS1 such as food and water supply (pro- systems (SES) visioning services), extreme event buffering and climate regulation (regulating services) which are of central importance in the context of risk reduc- This chapter defines relevant key terms covering: tion and adaptation. It considers both human-in- Social-ecological systems (SES) duced and biophysical drivers of risk and helps to Risk pursue adaptation strategies that make use of the Hazard multiple benefits provided by ecosystems. Exposure The risk of climate-related impacts within a Vulnerability social-ecological system results from the interac- Impacts tion of climate-related hazards (including hazard- Adaptation ous events and trends) with the vulnerability and exposure of human and natural systems. (Source: The latest IPCC assessment report (AR5), pub- IPCC 2014a, p. 1046) lished in 2014, has introduced the concept of cli- mate risk which replaced the AR4 concept of cli- mate (change) vulnerability. It was adopted from Risk the concepts and practices of carrying out risk Definition Risk: ’The potential for consequenc- assessments in the DRR community. The climate es where something of value is at stake and where risk concept allows to include all aspects of an the outcome is uncertain (...). Risk results from the SES – from climate-related hazards to social- and interaction of vulnerability, exposure, and hazard ecosystem-related vulnerability and exposure (...).’ (IPCC 2014a, p. 40) factors – which contribute to risks. A climate risk is the potential for specific, cli- mate-related consequences (climate impacts) that 1 http://www.aboutvalues.net/ecosystem_services/ 18 II F R A M E W O R K Figure 3: Illustration of the core concepts of the IPCC WGII AR5. The risk of climate-related impacts within a social-ecological system results from the inter- action of climate-related hazards (including hazardous events and trends) with the vulner- ability and exposure of human and natural systems (Source: IPCC 2014a, p. 1046) Social-ecological system (SES) Impacts CLIMATE SOCIOECONOMIC Vulnerability PROCESS Socio- Natural economic RISK pathways variability Hazards Emergent Adaptation Anthropo- and mitiga- Key genic climate tion actions change Governance Exposure EMISSIONS and land-use change may affect assets, people, ecosystems, culture, etc. clarify who or what may be affected. Examples Typically, an SES will be exposed to more than one for risks include: risk of water scarcity for small- climate risk. When starting a climate risk assess- holder farmers (water scarcity as a potential con- ment, it is thus necessary to specify the risk(s) the sequence of climate impacts, smallholder farmers study focuses on, to identify the types of hazards are at risk); risk of food insecurity for rural popu- and climate impacts that create the risk(s) and to lation; risk of species extinction for biodiversity; 19 II F R A M E W O R risk of damage to transport infrastructure due to of life, injury, or other health impacts, as well as K erosion and landslides, etc. damage and loss to property, infrastructure, liveli- Risk is something where the ‘outcome is un- hoods, service provision, ecosystems, and environ- certain’. In a risk assessment, this uncertainty can mental resources. In the [IPCC] report, the term be addressed in different ways. In disaster risk as- hazard usually refers to climate-related physical sessments, one common approach is a probabil- events or trends or their physical impacts.’ (IPCC istic assessment, where risk is represented as the 2014a, p. 39) probability of hazardous events or trends to occur, A hazard may be an event (e.g. a heavy rain multiplied by the impacts of these events or trends event), but it can also be a direct physical impact. (IPCC 2014a). In the context of climate change risk, A hazard is not necessarily an extreme weather such a probabilistic approach is often not feasible. event (e.g. tropical storm, flooding), but can also be Most hazards and consequences cannot be de- a slow onset trend (e.g. less water from snow melt, scribed as standard events, which is one require- increase in average temperature, sea-level rise, ment for a probabilistic approach. Furthermore, salinity intrusion, etc.). If possible, the probability the consequences of climate change can per-se not of a specific hazardous event or trend should be be assessed with a probabilistic approach, since the estimated. This can be done by defining hazards future of socio-economic pathways, greenhouse as critical events or critical physical impacts (e.g. gas emission pathways and thus climate impacts is ‘heavy rain events’ instead of ‘rain’ or ‘heat days’ uncertain. Instead, scenario approaches are applied instead of ‘temperature’). Later in the assessment, (e.g. different climate consequences for differ- this will be further specified by setting thresholds ent greenhouse gas emission scenarios; different and identifying frequencies (e.g. ‘number of days vulnerability scenarios based on socio-economic with more than 50 mm rainfall’). pathways). Therefore, we propose to understand climate risk as a function of hazard, exposure and vulnerability, as proposed by the IPCC in its AR5 Exposure report (IPCC 2014a), but to make the likelihood and uncertainty explicit wherever possible, par- Definition Exposure: ‘The presence of people, ticularly in the selection of hazard indicators. livelihoods, species or ecosystems, environmental functions, services, and resources, infrastructure, For a more in-depth discussion see Chapter II or economic, social, or cultural assets in places of the Risk Supplement, p. 11-21. and settings that could be adversely affected.’ (IPCC 2014a, p. 39) ‘Exposure’ refers to relevant elements of the Hazard SES system (e.g. people, livelihoods, assets, but also species, ecosystems, etc.) that could be ad- Definition Hazard: ‘The potential occurrence versely affected by hazards. The degree of expo- of a natural or human-induced physical event sure can be expressed by absolute numbers, den- or trend or physical impact that may cause loss sities, proportions, etc. (e.g. ‘population density 20 III F R A M E W O R in an area affected by drought’; ‘percentage of tions, organizations, and systems, using available K wetlands in a district affected by pollution’, etc.). skills, values, beliefs, resources, and opportunities, A change in exposure over time (e.g. ‘change of to address, manage, and overcome adverse condi- number of people living in drought-prone ar- tions in the short to medium term’, IPCC 2014b, eas’) can significantly increase or decrease risk. p. 1762; e.g. early warning systems in place), and the adaptive capacity (‘The ability of systems, in- stitutions, humans and other organisms to adjust Vulnerability to potential damage, to take advantage of oppor- tunities, or to respond to consequences’; IPCC Definition Vulnerability: ‘The propensity or 2014b, p. 1758; e.g. knowledge to introduce new predisposition to be adversely affected. Vulner- farming methods). A lack of capacity can signifi- ability encompasses a variety of concepts and cantly increase the vulnerability of a system at elements including sensitivity or susceptibility stake and therefore its level of risk. to harm and lack of capacity to cope and adapt.’ (IPCC 2014a, p. 39) Vulnerability addresses those attributes of Impacts the exposed SES-elements that may increase (or decrease) the potential consequences of a specific Definition Impacts: ‘Effects on natural and climate hazard. It comprises two relevant ele- human systems. In [the IPCC] report, the term im- ments: sensitivity and capacity. pacts is used primarily to refer to the effects on Sensitivity is determined by those factors natural and human systems of extreme weather that directly affect the consequences of a hazard. and climate events and of climate change. Im- Sensitivity may include ecological or physical at- pacts generally refer to effects on lives, livelihoods, tributes of a system (e.g. type of soil on agriculture health, ecosystems, economies, societies, cultures, fields, water retention capacity for flood control, services, and infrastructure due to the interaction building material of houses) as well as social, eco- of climate changes or hazardous climate events nomic and cultural attributes (e.g. age structure, occurring within a specific time period and the income structure). In the context of EbA, it is rec- vulnerability of an exposed society or system. The ommended to consider how (intact or deteriorat- impacts of climate change on geophysical systems, ed) ESS affect sensitivity. including floods, droughts, and sea level rise, are a Capacity in the context of climate risk assess- subset of impacts called physical impacts.’ (IPCC ments refers to the ability of societies and com- 2014a, p. 39) munities to prepare for and respond to current ‘Impact’ is the most general term to describe and future climate impacts. It does not cover the consequences, ranging from direct physical im- capacity of ecosystems to respond to impacts but pacts of a hazard to indirect consequences for the rather the social capacity to manage ecosystems. society (so-called social impacts). Impacts are ba- Capacity comprises two major components: the sic building blocks of the cause-effect chains (im- coping capacity (‘The ability of people, institu- pact chains). 21 II F R A M E W O R K Figure 4: Adaptation can reduce the risk by reducing the vulnerability and sometimes the exposure (Source: GIZ and EURAC 2017) Social-ecological system (SES) Adaptation Climate Signal decreases Hazard decreases increases Direct physical impacts Sensitivity Exposure Vulnerability Capacity (Coping, Adaptive) Risk relocating farmers to an area that is not drought- prone. However, these measures are oftentimes Reducing risk through adaptation politically sensitive and not always viable. It is therefore recommended to focus on adaptation Definition Adaptation: ‘The process of ad- measures targeting the sensitivity and/or capacity justment to actual or expected climate and its analysed within the impact chain. In the context effects. In human systems, adaptation seeks to of EbA, measures that could decrease sensitivity – moderate or avoid harm or exploit beneficial op- for instance by restoring ecosystem services– are portunities.’ (IPCC 2014a, p.40) of particular interest. Generally, adaptation measures can reduce the risk by reducing vulnerability and, in certain cases, also exposure (see Figure 4). Vulnerability can be reduced either by decreasing sensitivity or by increasing capacity. For instance, if a flood For more information on identifying and risk needs to be tackled, the restoration of wet- planning EbA options see Module 9. lands may be able to reduce sensitivity, while more knowledge on flood resistant buildings may For more detailed information on the differ- increase capacity. In principal, adaptation meas- ences in the concepts, see Chapter II of the Risk ures may also focus on reducing exposure, e.g. by Supplement (p. 11-21). 22 IIII III. Guidelines This chapter provides detailed instructions on how to conduct a risk assessment within the context of EbA. The chapter is structured along nine sequential modules describing key steps and guiding questions to be considered for risk assess- ments and how such assessments can support the identification and spatial prioritisation of adapta- tion measures including both ecosystem-based and conventional options. EbA is a landscape approach – i.e. a frame- work to integrate policy and practice for multiple land uses within a given area –, where decisions (policies, planning, and implementation) need to be based on spatial information. The generic instructions and the illustrative application ex- ample imply a strong spatial perspective and sug- gest the use of Geographical Information Systems (GIS) to support the risk assessments. Table 1 provides an overview of the content of the nine modules and their key means of im- plementation. 23 III Table 1: Overview of the nine modules of this Guidebook G U I Module What you will learn in this module Key means of D implementation E L 1 You will assess the initial situation of the analysis, define objec- Desktop-based; I Preparing tives and decide on the topic and scope of the climate risk correspondence and N the risk assessment, especially with regard to EbA. You will also plan the interviews with experts and E assessment implementation of the risk assessment. relevant actors S 2 You will get acquainted to and develop impact chains. You will learn Desktop-based and Developing how these chains form a central element of the overall risk assess- workshops with experts for the impact chains ment approach and how they provide entry points for the identifica- thematic area(s) at stake; tion of EbA options. You will define the underlying factors for the other relevant actors three risk components hazard, exposure and vulnerability. 3 You will identify and select indicators in order to quantify the factors Desktop-based and Identifying and that determine the risk. You will learn what makes a good indicator workshops with experts for selecting indica- and how to phrase it with reference to a critical state. the thematic area(s) at stake tors for risk components 4 You will learn how to acquire, review and prepare the data you need. Desktop-based; data Data acquisition acquisition through data and management transfer, data analysis, expert interviews, questionnaires, etc. 5 You will normalise the different indicator datasets into unit-less Desktop-based; experts Normalisation values with a common scale from 0 (optimal) to 1 (critical). You will for the thematic area(s) at of indicator data learn about setting thresholds of a normalisation range for quantita- stake (particularly for the tive indicators and how to apply a five-class evaluation scheme for threshold definition) categorical values. 6 You will learn how to weigh indicators if some of them are con- Desktop-based Weighting and sidered to have a greater or smaller influence on a vulnerability aggregating component than others. You will also aggregate individual indicators indicators to the three risk components. 7 You will aggregate the risk components ‘hazard’, ‘vulnerability’ and Desktop-based Aggregating risk ‘exposure’ to a single composite ‘risk indicator’. components to risk 8 You will learn how you can present and interpret the results of the Desktop-based for the Presenting and risk assessment. preparation, dissemination interpreting the events for the presentation outcomes of the risk assessment 9 You will firstly see how impact chains and risk assessments can Desktop-based; workshop Identifying EbA support the identification and spatial planning of EbA options. with key actors for strategy options The module subsequently explains the concept of ‘EbA co-benefits’ development and planning and describes how you can specify them. 24 m1 III Module 1 m1 Preparing the risk assessment This module outlines four essential steps and useful guiding questions for preparing a climate risk assessment in the context of EbA. It shows you how to assess the initial situation of your analysis, how to define objectives, decide on the topic and scope of the assessment (especially with regard to EbA), and make key decisions that will influence the entire risk assessment. It is impor- tant to include relevant actors already at this stage of the process. This ensures transparency and provides substantiation for any decisions and open questions. 25 m1 III G U I D E Step 1 Step 2 L Understand the context of a climate Identify objectives and I risk assessment for adaptation expected outcomes N E S Each risk assessment takes place in a unique The decision to conduct a climate risk as- setting. Taking time to explore this context helps sessment is usually driven by a particular need you define the objectives and scope of the assess- or information gap. This step helps you define ment and to plan resources accordingly. the objectives of the assessment and the in- tended outcomes and outputs. Knowing what ? GUIDING QUESTIONS: to expect also makes it easier to manage the expectations of participating institutions and At what stage of adaptation planning is your stakeholders. assessment taking place? And what are the development and adaptation priorities (if al- ? GUIDING QUESTIONS: ready defined)? The risk assessment usually occurs in the con- Which processes will the climate risk assess- text of broader processes such as the preparation ment support or feed into? for a National Adaptation Plan (NAP) with clear In order to define the objective of the risk as- development and adaptation goals and priorities. sessment, ongoing adaptation processes and the Identifying and understanding such processes information requirements of relevant stakehold- helps to articulate the objective and to highlight ers need to be taken into account. potential synergies between the assessment and other processes. What do you and key stakeholders wish to learn from the assessment? Which institutions and resources can and Typical examples for objectives include the should be involved in your risk assessment? identification of risk hotspots in a certain area, or Choosing the relevant partner institutions the identification of relevant measures that help and stakeholders is decisive for the participa- to reduce the climate risk. tive process, as it creates co-ownership and has Who is the target audience for the risk assess- an impact on the success of the assessment. Lo- ment results? cal institutions from different levels (community, It is crucial to clearly define the target audi- regional, national), experts and stakeholders from ence such as: local communities, ministries and different sectors add valuable knowledge to the national agencies tasked with adaptation plan- assessment process, and their participation will ning, decision makers at different administrative enhance acceptance of the result. levels. What outputs do you expect? Possible desired outputs may be a map of risk 26 III m1 hotspots, a set of (ecosystem-based) adaptation tion? Which events and impacts were observed in measures, their co-benefits and drawbacks, or a the past? Which known risks and impacts may be narrative analysis of a climate risk and its deter- relevant for the future? mining factors. What major non-climatic drivers influence these risks? Step 3 For a full assessment, you also need to consid- er how non-climatic drivers (such as unsustain- Determine the scope of able land use or changes in income situation of the assessment local communities) influence the risks. Once you have identified the objectives and What ecosystems and relevant ecosystem ser- the context, you need to define the scope of the vices affect these risks? risk assessment. Knowing the scope is the basis Try to find out which ecosystems play a key for developing impact chains, the key compo- role in reducing the risks and how they are man- nent of this risk assessment, described in the next aged. What key ecosystem services (e.g. water module. regulation, flood prevention, erosion control) do they provide that could reduce risks? ? GUIDING QUESTIONS: What is the geographical scope of your as- What exactly is your risk assessment about? sessment and what spatial detail are you You should determine the thematic focus of aiming for? the assessment (e.g. a certain sector or application Decide whether the assessment will focus field, such as river basin management, agricultur- on a specific community, a district/province, al production, water provision, etc.) and the over- or on a clearly definable ecosystem (e.g. a river all relation between climate, ESS and risk in the delta or protected natural area), on a single spa- area under consideration. Are you considering tial unit (e.g. one district) or several areas that particular social groups? Does your assessment need to be compared (e.g. two or more districts). focus on just one subject or on combined sub- Is there a specific spatial scale that needs to be jects (e.g. risk to agricultural production affecting considered? crops and livestock)? And which elements at risk (e.g. farmers, agricultural land, infrastructure, etc.) What is the time period of the assessment? should you consider? A climate risk assessment can refer to differ- ent time (reference) periods. It is advisable to start What climate related risks do you intend to with the current climate risks related to impacts assess? from current climate variability, climate extremes Are you, for instance, addressing the risk re- and recent changes of climate conditions. Addi- lated to hazardous events such as flooding, or the tional future climate risks (related to impacts due risk related to trends such as increasing precipita- to future climate variability and future climate 27 m1 III G U I D E extremes, e.g. for the year 2050) can subsequently be helpful to include milestones in the imple- 2 L be elaborated. mentation plan and to ensure proper monitoring. I N What are the right methods for your climate What resources are required? E risk assessment? As these assessments usually call for large S Risk assessments can incorporate various dif- amounts of data, it is imperative to plan sufficient ferent methods, using quantitative models (e.g. time for data acquisition, preparation and pro- climate or hydrological models), participatory ap- cessing. The more data-driven the assessment, the proaches or a combination of the two. more technical capacities and skills are required. Step 4 Prepare an implementation plan Based on the understanding gained through Steps 1 to 3 of this module, you can develop a concrete work plan for implementing the risk assessment. In doing so, you need to involve the participating institutions and stakeholders and carefully consider the resources available. ? GUIDING QUESTIONS: Which people and institutions are involved? Take sufficient time to identify key actors and institutions relevant for conducting the risk as- sessment. This will avoid implementation delays at a later stage of planning. For practical guidelines how to develop a con- crete work plan for implementing the risk assess- Tasks and responsibilities: Who has what? ment see Vulnerability Sourcebook, p. 40–53. A It is crucial that all key stakeholders involved template assessment implementation plan is in- have a clear and thorough understanding of the cluded in Annex 1 of the Vulnerability Sourcebook. objectives and their roles. This will encourage co- operation and reduce overlaps in responsibilities. What is the time plan of the risk assessment? 2 Ideally next to future climate-related hazards also future Realistic time planning is key, especially vulnerability and exposure pathways should be considered. However, due to data constraints, this is in most cases not fea- when dealing with unexpected challenges. It can sible. 28 III m1 A P P L I C AT I O N E X A M P L E : Management, the national Ministry of Environ- River basin management – ment, and – on the local level – river basin work- preparing the risk assessment ing groups and committees, communities and private sector representatives. Their involvement from the start and throughout the assessment was not only important to gather all available Step 1 local knowledge, but also essential for the own- Understanding the context ership of the process and the acceptance of the of a climate risk assessment measures. During the implementation process, for adaptation expert knowledge on potential measures, their feasibility and risk factors were gathered. At what stage of adaptation planning is the assessment taking place? Are there already risk or impact assessments? In the river basin, there is a growing aware- Step 2 ness of the necessity to implement adaptation Identifying objectives and measures. An adaptation strategy at national level expected outcomes was in preparation, future concrete actions need- ed to be based on a more sophisticated risk assess- What do you and key stakeholders wish to ment. This was the first climate risk assessment in learn from the assessment? the river basin. The team agreed that it was most important to determine the risk of river flooding for peo- What are the development and adaptation ple’s lives, damage to property and critical infra- priorities (if already defined)? structures, and (how) it can be reduced through It was determined, that as a result of climate adaptation, including EbA measures. And that change, floodings will increase in frequency and the assessment should also specify which poten- in intensity in the river basin. Therefore, the lo- tial co-benefits and trade-offs EbA options might cal population is expected to face large economic have. losses due to crop failure and a decline in produc- tion. Ecosystem services such as water provision Which processes will the risk assessment sup- and regulation present unused potential for sus- port or feed into? tainable adaptation measures. A key priority is It was evident that the outcome of the risk flood risk reduction through the implementation assessment (with its focus on EbA) would inform of EbA measures in the river basin. the Regional and National Adaptation Plan. Which institutions and resources can and Who is the target audience for the risk assess- should be involved in the risk assessment? ment results? Key actors to be included in this risk assess- The results of the risk assessment would pri- ment were the Regional Department of Water marily be presented to the local community, i.e. 29 III G U I D E all residents and especially landowners, leaders What major non-climatic drivers influence L and farmers, regional governments and the rel- these risks? I evant administrations and departments. During the assessment process, the team N found that the number of people living in the E What outputs are expected? river basin is increasing. The major sectors ag- S It was expected that by the end of the assess- riculture, industry and mining, but also oth- ment process, there would be a map of flood risk ers, depend on water from the river and have hotspots and related ecosystem services, a list of modified the natural river flow by converting indicators and datasets, a narrative analysis of the the natural vegetation, which had an important risk and its determining factors. Also, the assess- risk buffering function, into cropland and other ment should help identify adaptation measures land use types. The river runs through settle- (incl. EbA) and locations where they can be im- ment areas, and houses are built in close prox- plemented most efficiently. imity to the shore. Deforestation and wetland degradation are becoming more widespread. In parts of the basin, more than half of the popula- Step 3 tion depends on income from agriculture. The Determining the scope of area is economically deprived. There is a lack of the assessment spatial planning and only some flood resistant housing. What exactly is the risk assessment about? The assessment aimed to determine the risk What ecosystems and relevant ecosystem ser- of damage to property and loss of lives due to vices affect these risks? flooding, considering the effect(s) of EbA meas- The western mountainous area up-stream is ures, their co-benefits and drawbacks for the six dominated by a large forest that plays an impor- districts in the river basin, considering all social tant role for water regulation and erosion preven- groups. tion. The eastern lowlands are characterised by What climate related risks should be assessed? natural coastal forest and cropland. Several wet- The assessment focused on the risk of flood- lands are located in the central part of the river ing caused by too much precipitation. basin. Their water retention capacity significantly reduces flood risks. In several places buffer zones What events and impacts occurred in the past? are found along the river that prevent soil erosion River flooding due to too much precipitation and siltation of rivers. had occurred both in the wet and in the dry season. What is the geographical scope of your as- Which known risks may be relevant for the sessment and what spatial detail are you future? aiming for? Precipitation increase during October and The assessment covered one river basin con- November (rainy season becomes wetter). sisting of six administrative districts. 30 III m1 What is the time period of the assessment? munity. The local government would participate The assessment referred to current climate in all meetings, provide technical expertise and risks related to impacts from current climate var- information about ongoing adaptation planning iability. processes. What is the time plan of the risk assessment? Step 4 The risk assessment was to be completed in Preparing an 18 months. implementation plan Which people and institutions are involved? It was decided that institutions such as the lo- cal office of an international development agen- cy, the local university, the local government, and local non-governmental organisations dealing with ESS would be involved throughout the as- sessment process. In the preparation phase, meet- ings with all partner institutions and stakeholders were scheduled to introduce them to the climate risk assessment, the objectives, methodology and envisaged outcomes. Together with relevant part- ners, local water management authorities deter- mined which institution needed to be involved in which step in the process and would be responsi- ble for what task. Tasks and responsibilities: Who does what? Discussions with all partners involved in the assessment led to the following allocation of tasks: The international development agency was responsible for the methodological approach, guidance to the team, planning, organising and coordination. The local university would gather data (qualitative and quantitative) and take on data management and mapping. The local non- governmental organisation would provide local knowledge, take part in action groups and passes the information on to other people in the com- 31 m2 III G U Module 2 I Developing impact D E chains L I This module gives an introduction into the Impact chains: definition and key N development of impact chains. They form a cen- elements E tral element in the overall risk assessment ap- S proach and provide entry points for the identifi- An impact chain, or cause-effect chain, is an cation of EbA options. First, the concept and the analytical tool that helps you better understand, key elements of impact chains are described, then systemise and prioritise the factors that drive risk the key steps in the development of such chains in the system of concern. The structure of the will be introduced, and finally you will see how impact chain concurs with the key components impact chains can inform the identification of of the conceptual framework presented in chap- EbA measures. ter II. Impact chains – as proposed in the Vulner- A climate risk project that aims to identify ad- ability Sourcebook, its Risk Supplement and in this aptation measures on a more qualitative level may Guidebook – always have a similar structure (see already conclude with the development of impact Figure 5): a climate signal (e.g. a heavy rain event) chains. However, an assessment with the objec- may lead to a direct physical impact, causing a tive of comparing climate risk in different regions sequence of intermediate impacts (e.g. erosion or of enabling future monitoring and evaluation upstream, contributing to flooding downstream), (M&E) needs to quantify risks and their compo- which – due to the vulnerability of exposed ele- nents and thus to continue with Module 3. ments of the social-ecological system (SES) – fi- nally lead to a risk (or multiple risks). Impact chains are composed of risk com- ponents (hazard, exposure, vulnerability; see coloured containers in Figure 5) and underly- ing factors for each of them (white boxes). The hazard component includes factors related to the climate signal. The vulnerability component comprises factors related to the sensitivity of the SES and the social capacity. The exposure compo- nent is comprised by one or more exposure fac- tors. In contrast to these three components, in- termediate impacts are not a risk component by themselves, but merely an auxiliary tool to fully grasp the cause-effect chain leading to the risk. By definition, they are a function of both hazard and vulnerability factors. This means that all im- pacts identified which do not only depend on the climate signal, but also on one or several vulner- 32 III Figure 5: Structure and key elements of an impact chain (Source: GIZ and EURAC 2017) m2 Social-ecological system (SES) Hazard Risk component Climate signal Climate signal Exposure Impact Vulnerability of SES of SES Sensitivity Intermediate impacts Sensitivity Impact Exposure Capacity Exposure Impact Capacity Risk(s) Factor ability factors need to be placed here. As opposed this section: (1) identify potential climate impacts to a climate signal, an intermediate impact can be and risks, (2) determine hazard(s) and interme- influenced by measures. diate impacts, (3) determine the vulnerability of the social-ecological system, and (4) determine exposed elements of the social-ecological system. A sound understanding of the system of concern Impact chain development: key steps and the incorporation of expert/local knowledge and basic principles through a participatory process (e.g. workshops, focus group discussions, etc.) form the basis for The development of impact chains comprises the development of impact chains. Building such four sequential steps that are briefly described in impact chains is an iterative process. New rele- 33 m2 III G U I D E vant aspects can emerge during the development more than one risk (e.g. risk of loss of life and risk L process. of damage to critical infrastructure due to tropi- I There are a number of basic principles to con- cal storms), you might want to develop different N sider when you brainstorm on the various factors impact chains for each risk. These could be com- E to generate an impact chain: bined in a later stage of the risk assessment (see S Module 7). To avoid double counting, a factor should be allocated to one risk component only. Step 2 Factors allocated to one component should (as Determine hazard(s) and much as possible) be independent of factors of intermediate impacts other components. ? GUIDING QUESTIONS: Factors representing potentially hazardous events can either be allocated to the hazard Which climate-related hazards pose a risk component (preferably when these events are to your system of concern? external triggers, which can hardly be influ- Which intermediate impacts link the enced by adaptation within the system) or hazard(s) and the risk(s)? classified as intermediate impacts (preferably First, identify the relevant climate signal(s) when they are influenced by the vulnerability (e.g. too much precipitation) which lead(s) to the and can be reduced by adaptation) potential impacts and risks identified in Step 1. The climate signal leads to a sequence of interme- For further details on basic principles see Vul- diate impacts (which can be partly influenced by nerability Sourcebook, p. 58–59. the vulnerability of the social-ecological system), such as too high water levels or increased flow ve- locity and flooding. Step 1 For all hazards and intermediate impact fac- Identify potential climate tors, we recommend a wording that implies a impacts and risks critical state, e.g. ‘too much precipitation’ rather than ‘precipitation’. With hazard factors and in- ? GUIDING QUESTIONS: termediate impacts identified, you now have a good basis for determining relevant vulnerabil- Which major climate impacts and risks affect ity factors. your system of concern? The development of an impact chain always starts with the identification of potential climate impacts and risks (e.g. risk of loss of life due to a specific hazard). If the risk assessment covers 34 III Step 3 lematic since, at a later stage, the factors of both Determine the vulnerability of sub-components will be aggregated into the m2 component vulnerability of the social-ecolog- the social-ecological system ical system. ? GUIDING QUESTIONS: Please consider the state of relevant ecosys- tems, their services (particularly regulating ser- What are the main societal and ecological vices) and how they might contribute to increased drivers of vulnerability of the social-ecologi- climate risk(s) and/or help to mitigate risk(s). cal system? Which aspects contribute to ecological and Step 4 societal susceptibility, and which factors de- Determine exposed elements termine the social capacities to cope with haz- ards or to adapt to changing conditions in the of the social-ecological system system? ? GUIDING QUESTIONS: Factors allocated to the vulnerability com- ponent should represent two aspects, sensitivi- Which elements of the social-ecological sys- ty and capacity, where capacity includes factors tem are present in places that could be ad- associated with the (lack of) short-term cop- versely affected by hazards? ing as well as long-term adaptive capacity (see ‘Exposure’ refers to the presence of relevant definitions of coping and adaptive capacity in elements of the social-ecological system (e.g. chapter II). people, livelihoods, assets, but also species, eco- An unambiguous allocation of the individ- systems, etc.) in places that could be adversely ual factors to either of the two sub-components affected by hazards. The scoping process in Mod- is often not possible. This, however, is unprob- ule 1 already provided initial ideas about the ex- BOX 2 Additional interlinkages between factors of the impact chains Please note that these four steps lead to the creation of separate boxes showing a limited number of relationships that are not further specified. In reality, any system comprises many more connections and cross-linkages of differ- ent forms, intensities and significance. You can draw these interlinkages in the impact chains and thus create a paper model that helps to understand the complexity of reality. However, these additional connections, which do not directly lead from a factor to another, cannot be operationalised within the scope of this risk assessment. 35 m2 III G U I D E posed elements, which now need to be further A P P L I C AT I O N E X A M P L E : L specified. For instance, the more people live in Developing impact chains I flood-prone areas, the higher the related risk. In N most cases, the exposure component will consist E of considerably less factors than hazard or vul- S nerability. Step 1 For further details on the four key steps see Risk Identification of potential Supplement, p. 27–37, and Vulnerability Source- climate impacts and risks book, p. 56-66. The scoping phase (Module 1, Step 3) revealed that the main risk in the basin is the ‘risk of dam- How can impact chains inform the age of property and loss of live due to flooding’. identification of EbA measures? Impact chains not only provide an under- Step 2 standing of the key components and underlying Determining hazards and factors contributing to potential climate impacts intermediate impacts and risks, but also support the brainstorming on potential adaptation options or ‘packages’ – in- Figure 6 shows the draft impact chain with cluding EbA. The vulnerability factors can serve as intermediate impacts and hazard factors for the starting points for such a brainstorming exercise, river basin. Here ‘too much precipitation’ has and are of particular interest with regard to EbA been identified as the key hazard (note: the defi- factors related to the ecological dimension of the nition of thresholds determining ‘too much pre- social-ecological system (i.e. the ecosystems and cipitation’ will be introduced in Module 3). These their services). If the impact chain, for example, readily measurable factors led to more complex shows a sequence of causes and effects, leading factors such as too high water level and increased from deforestation to reduced erosion prevention flow velocity and in turn to increased erosion, (loss of a regulating service) and increased flood- causing sediment deposition in downstream ar- ing in downstream areas, then it is evident that eas and increased flooding. afforestation or reforestation programmes can be suitable EbA measures for tackling the flooding problem. Step 3 Determining the vulnerability of the social-ecological system Figure 7 shows the impact chain comple- mented by relevant vulnerability factors. Linking 36 III Figure 6: Impact chain with intermediate impacts and hazard factors identified m2 Hazard Intermediate Impacts Too much precipitation Too high Increased flow in wet season water level velocity Too much precipitation Erosion in dry season Sediment deposition Siltation of river bed Degradation of aquatic ecosystem Exposure Flooding Vulnerability Risk Risk of damage of property and loss of lives due to flooding vulnerability factors with the related intermedi- ‘lack of water and wetland management capacity’ ate impacts helped to understand cause-effect re- rather than ‘water and wetland management ca- lationships, e.g. the intermediate impact ‘erosion’ pacity’. in the catchment is not only a result of too high The impact chain indicates the distinction be- water levels and increased flow velocity, but also tween social and ecological sensitivity factors as well directly related to ‘deforestation’ and the deterio- as capacity factors and highlights the role of eco- ration of the ESS ‘erosion protection’. system services. For example, the high dependency Note that vulnerability factors in the impact on agricultural income in the river basin leads to chain were phrased expressing a critical state, deforestation which in turn leads to reduced ero- e.g. ‘wetland degradation’ instead of ‘wetland’, or sion protection and consequently to erosion. 37 m2 III 38 G N U D E E S L I I Hazard Wetland Vulnerability degradation Figure 7: Impact chain with vulnerability factors added, including ecological and social sensitivity and capacity Too much precipitation in wet season Reduced Unsuitable use Lack of water and wetland Intermediate of flood plains management capacity natural Impacts retention Too much precipitation Too high Increased flow capacity in dry season water level velocity Agricultural land too close to river Eco- Strong dependency system Missing buffer on agricultural income Erosion services strips Sediment deposition Reduced erosion protec- Lack of protected Siltation of tion Deforestation forest areas river bed Degradation of aquatic ecosystem River ecosystem Built infrastructure disconnected blocking river flow Flooding Lack of financial Exposure resources of people Absence of flood Lack of urban resistant housing planning Risk Risk of damage of property and loss of lives due to flooding Risk Exposure Climate Intermediate Sensitivity Sensitivity Capacity Signal Impact Ecological Socio-economic III Step 4 Figure 9 shows the impact chain with those fac- Determining exposed elements tors highlighted that can serve as potential entry m2 of the social-ecological system points for adaptation practitioners working on natural resource conservation and management. The brainstorming exercise with relevant For example, the impact chain shows that, ac- stakeholders revealed that, in the past, the ele- cording to the consulted experts, the unsustain- ments frequently affected by floodings in the able use of floodplains in the river basin has led river basin were to wetland degradation (ecosystem) and in con- sequence to reduced natural retention capacity people, (regulating service). Additional factors contrib- uting to the ecological dimension of vulnerabil- property and buildings, and ity in the river basin are: degradation of forest critical infrastructure, more specifically ecosystems resulting in reduced erosion control power plants. (regulating service); lack of protected areas; dis- connected river ecosystems. Figure 8 shows the impact chain, which now Based on such a visualisation, the following includes exposed elements. EbA options were identified (see Table 2 and Figure As indicated in the general introduction of 10): (1) wetland restoration, (2) retention ponds, (3) Module 2, the impact chain can also serve as a ba- riparian zone restoration, (4) afforestation / refor- sis for the identification of adaptation measures. estation, and (5) buffer strips along rivers. Table 2: Ecosystem-based (green dots) and conventional (blue dots) adaptation options; cf. Figures 8-10 Ecosystem-based Adaptation options Conventional adaptation options 1 Wetland restoration Capacity building 2 Retention ponds Livelihood diversification 3 Riparian zone restoration Communication & awareness campaigns 4 Afforestation/reforestation 5 Buffer strips 39 m2 III 40 G N U D E E S L I I Hazard Wetland Vulnerability degradation Too much precipitation in wet season Reduced Unsuitable use Lack of water and wetland Intermediate of flood plains management capacity natural Impacts retention Too much precipitation Too high Increased flow capacity in dry season water level velocity Agricultural land too close to river Eco- Strong dependency Figure 8: Impact chain with exposure added system Missing buffer on agricultural income Erosion services strips Sediment deposition Reduced erosion protec- Lack of protected Siltation of tion Deforestation forest areas river bed Degradation of aquatic Exposure ecosystem River ecosystem Built infrastructure disconnected blocking river flow People living in flood prone areas Flooding Lack of financial resources of people Property and buildings in flood prone areas Absence of flood Lack of urban resistant housing planning Critical infrastructure in flood prone areas Risk Risk of damage of property and loss of lives due to flooding Risk Exposure Climate Intermediate Sensitivity Sensitivity Capacity Signal Impact Ecological Socio-economic Figure 9: Entry points for adaptation practitioners working on natural resource conservation and management (green and orange boxes) Hazard Wetland Vulnerability degradation Too much precipitation in wet season Reduced Unsuitable use Lack of water and wetland Intermediate of flood plains management capacity natural Impacts retention Too much precipitation Too high Increased flow capacity in dry season water level velocity Agricultural land too close to river Eco- Strong dependency system Missing buffer on agricultural income Erosion services strips Sediment deposition Reduced erosion protec- Lack of protected Siltation of tion Deforestation forest areas river bed Degradation of aquatic Exposure ecosystem River ecosystem Built infrastructure disconnected blocking river flow People living in flood prone areas Flooding Lack of financial resources of people Property and buildings in flood prone areas Absence of flood Lack of urban resistant housing planning Critical infrastructure in flood prone areas Risk Risk of damage of property and loss of lives due to flooding Risk Exposure Climate Intermediate Sensitivity Sensitivity Capacity Signal Impact Ecological Socio-economic III 41 m2 m2 III 42 G N U D E E S L I I Hazard Wetland Vulnerability degradation Figure 10: Ecosystem-based (green dots) and conventional (blue dots) adaptation options – see also Table 2 Too much precipitation 1 in wet season Reduced Unsuitable use Lack of water and wetland Intermediate of flood plains management capacity natural Impacts retention 3 1 3 Too much precipitation Too high Increased flow capacity in dry season water level velocity Agricultural land 2 too close to river Eco- 2 Strong dependency system Missing buffer on agricultural income Erosion services strips Sediment 3 5 3 deposition Reduced erosion protec- Lack of protected Siltation of tion Deforestation forest areas river bed 2 4 Degradation of aquatic Exposure ecosystem River ecosystem Built infrastructure disconnected blocking river flow People living in flood prone areas Flooding 3 Lack of financial resources of people Property and buildings in Absence of flood Lack of urban flood prone areas resistant housing planning 1 Critical infrastructure in Ecosystem-based adaptation options Conventional adaptation option flood prone areas Risk Risk of damage of property and loss of lives due to flooding Risk Exposure Climate Intermediate Sensitivity Sensitivity Capacity Signal Impact Ecological Socio-economic m3 III Module 3 Identifying and selecting indicators for risk components This module explains how to select indicators to quantify the factors determining the risk. The m3 guiding question here is: How to assess the vari- ous factors that lead to the risk? Good indicators for risk components are valid and relevant (they represent well the is- sue you would like to address), practical and affordable (they are accessible with reasonable efforts and resources), clear in their direction (an increase in value is unambiguously positive or negative with re- lation to the factor and risk component), phrased with reference to a critical state (rel- evant according to the AR5 risk approach). 43 m3 III G U I D E To quantify hazard factors, it is particularly to consider both coping and adaptive capacities. L advised to to use numbers representing intensi- For exposure, useful indicators are typically num- I ties (for example ‘water level > 1 m of average’) or bers, densities or proportions (e.g. ‘percentage of N frequencies (for example ‘heat days per year’) to population living in a floodplain’). E describe the potential occurrence of a hazardous S event. The hazard factor ‘too much precipitation’, for instance, could be phrased as ‘number of days Step 3 with more than 100 mm of precipitation’, thus re- Check if your indicators are ferring to a critical state. specific enough Keep in mind that intermediate impacts are not risk components by themselves, but only In this step, you should check again that each represent an auxiliary tool to understand the indicator is a suitable description of the factor, cause-and-effect relationship leading to the risk. that it is explicitly phrased, and that it has a clear For this reason, they will not be included in the direction with regard to the risk considered. aggregation to the overall risk (see Module 7) and thus do not have to be represented by indicators. Step 4 Create a list of provisional Step 1 indicators for each risk factor Selecting indicators for hazards At this point, you will have identified at least one indicator per factor in the impact chain. Now In this step, you select indicators describing compile all indicators in a table. It should contain climate drivers or hazards such as temperature the relevant information about each indicator: extremes or severe precipitation events leading the reasons for selecting it, the spatial as well as to intermediate impacts. temporal coverage, unit of measurement, inter- vals for updates, and potential data sources re- quired. Step 2 Selecting indicators for vulnerability and exposure In order to determine indicators describing vulnerability you need to select indicators for the level of sensitivity and of capacity. For each indi- cator you specify the direction: does a high value represent a high risk or a low risk? When selecting For details see Vulnerability Sourcebook, p. indicators for the capacity component, you need 74–84, and Risk Supplement, p. 42–46. 44 III A P P L I C AT I O N E X A M P L E : ing, it is clear in its direction (a higher percentage Identifying and selecting of elevated buildings decreases the vulnerability), indicators for risk the data needed came from an accessible source and was available at an appropriate temporal and spatial resolution. Figure 12 illustrates indicators m3 selected for six sensitivity, four capacity and three Step 1 exposure factors. Selecting indicators for hazards Step 3 Two factors describing the hazard were se- Checking if the indicators are lected. Both are climate drivers, both have to do specific enough with precipitation and both can be represented by indicators available from observations: From For each selected indicator one needs to check consultations with local experts, it was known again if it is sufficiently explicit, if it was phrased that precipitation of more than 100 mm in the towards the risk approach by making sure it had a wet season and more than 120 mm in the dry sea- clear ‘direction’ and if spatial and temporal cover- son over a certain number of days increases the age and resolution were appropriate for the risk risk of river flooding (critical state). Figure 11 il- assessment. The team was confident that ‘per- lustrates indicators for two hazard factors. centage of elevated buildings’ represents a suit- able sensitivity indicator for the factor ‘absence of flood resistant housing’ for the following reasons: it is directly related to the risk (a lower percentage Step 2 of elevated buildings increases the risk) and the Selecting indicators for vulner- data available for this indicator was at household ability and exposure level and from the last census conducted two years ago, thus spatial resolution was high and the During workshops and consultations with lo- data represented the current situation well. cal experts from the Regional Water Department, the Ministry of Environment and local leaders, a set of indicators was identified, describing the Step 4 vulnerability factors defined in Module 2. Creating a list of provisional For the vulnerability factor ‘absence of flood indicators for each factor resistant housing’, for example, it was decided to use ‘percentage of elevated buildings’ as an indica- For each component, the indicators identified tor. This indicator is valid as it represents the fac- were listed in a table which displays the unit of tor that ought to be assessed, it is reliable also for measurement as well as their direction in relation monitoring in the future, it has a precise mean- to the risk (Table 3). 45 m3 III 46 G N U D E E S L I I Hazard Wetland Vulnerability degradation Too much precipitation in wet season No. of days with Reduced Unsuitable use Lack of water and wetland precipitation > Intermediate of flood plains management capacity – 100mm Impacts natural retention Too high Increased flow capacity Too much precipitation in dry season water level velocity Agricultural land too close to river No. of days with Eco- Figure 11: Impact chain with hazard indicators added precipitation > – 120mm system Missing buffer Strong dependency Erosion services strips on agricultural income Sediment deposition Reduced erosion protec- Lack of protected Siltation of tion Deforestation forest areas river bed Exposure Degradation of aquatic People living in flood ecosystem prone areas River ecosystem Built infrastructure disconnected blocking river flow Flooding Property and buildings in Lack of financial flood prone areas resources of people Absence of flood Lack of urban resistant housing planning Critical infrastructure in flood prone areas Risk Risk of damage of property and loss of lives due to flooding Risk Exposure Climate Intermedi- Sensitivity Sensitivity Capacity Indicator Signal ate Impact Ecological Socio-economic Hazard Wetland Vulnerability degradation Too much precipitation % of area covered in wet season by wetlands No. of days with precipitation > Intermediate – 100mm Impacts Reduced Unsuitable use Lack of water and wetland natural of flood plains management capacity Too much precipitation Too high Increased flow retention Quality of in dry season water level velocity capacity Agricultural land operational RBCs too close to river No. of days with precipitation > – 120mm Eco- Missing buffer Strong dependency system strips on agricultural income Erosion Figure 12: Impact chain with indicators services % of labour force % of river line aligned Sediment by buffer strips in primary sector deposition Reduced erosion protec- Lack of protected Siltation of tion Deforestation forest areas river bed % of area covered % of forest area Exposure Degradation by natural forest protected of aquatic People living in flood ecosystem River ecosystem Built infrastructure prone areas disconnected blocking river flow No. of people per km 2 Flooding No. of dams and weirs in flood prone areas per km river length Property and buildings in Lack of financial flood prone areas resources of people No. of buldings per km2 % of population with Absence of flood Lack of urban in flood prone areas income below resistant housing planning national poverty line % of elevated % of municipalities with par- Critical infrastructure in buildings ticipation in planning process flood prone areas No. of critical infrastruc- Risk of damage of property and ture in flood prone areas Risk Climate Intermedi- Sensitivity Sensitivity loss of lives due to flooding Risk Exposure Capacity Indicator Signal ate Impact Ecological Socio-economic III 47 m3 m3 III Table 3: Factors and indicators for each risk component (hazard, exposure and vulnerability) with the indication of the direction that contributes to an increase of risk (+ = greater indicator values; - = smaller indicators values) Component Factor Indicator Direction G U Hazard Too much precipitation in wet season Number of days with precipitation + ≥ 100mm I D Too much precipitation in dry season Number of days with precipitation + E ≥ 120mm L I Exposure People living in flood-prone areas Number of people per km² in + N flood-prone area E S Property & buildings in flood-prone Number of buildings per km² + areas in flood-prone areas Critical infrastructure in flood-prone Number of critical infrastructure + areas in flood-prone areas Vulnerability Wetland degradation Percentage of area covered by wetlands – Missing buffer strips Percentage of river line aligned by buffer – strips Deforestation Percentage of area covered by natural – forest Lack of protected forest areas Percentage of forest area protected - River ecosystems disconnected Number of dams and weirs per km river + length Absence of flood resistant housing Percentage of elevated buildings – Lack of water and wetland management Quality of operational River basin – capacity committees (RBCs) Strong dependency on agricultural Percentage of labour force in primary + income sector Lack of urban planning Percentage of municipalities with – participation in planning process Lack of financial resources of people Percentage of population with income + below national poverty line 48 m4 III Module 4 Data acquisition and management This Module shows how to acquire, review and prepare the data you need. It includes guid- ance on data collection, database construction and linking relevant data to the chosen indicators to allow risk analysis and modelling. ? GUIDING QUESTIONS: m4 What kind of data do you need? Who can provide that data? Do the data have the quality you need (format, temporal and spatial coverage)? How are you going to structure and store the data? How are you documenting your data with metadata and/or fact sheets? For detailed guidance on data acquisition see Vulnerability Sourcebook, p. 88–103. 49 m4 III G U I D E A P P L I C AT I O N E X A M P L E : formation System (GIS), combining spatial data L Data acquisition and (representing areas affected by flooding) and data I on gridded (i.e. pixel-based) population obtained management N from global data repositories with data on the E location of buildings and critical infrastructures S obtained from the local government. What kind of data is needed? Who can provide that data? As the risk assessment within the context of A data search and enquiry at the various in- EbA aims for spatial-explicit outputs, georefer- stitutions identified the following data sources: enced data – either pixel based or referenced to National Survey Office, Meteorological Office, administrative areas – was needed. The best qual- Regional Statistical Office, Ministry for Environ- ity information available to describe an indicator ment, Regional Spatial Planning Department, Na- ought to be sourced. This information may be tional Office for Disaster Management, Regional quantitative or qualitative. University. At the Regional Spatial Planning De- Baseline geographic, recent climate, envi- partment, the experts were asked to rate the qual- ronmental, socio-economic and spatial planning ity of River Basin Committees. data was required, including land cover (globally available as gridded data), river network, munic- Do the data have the quality that is needed ipality boundaries and the extent of the flood- (format, temporal and spatial coverage)? prone area. Regarding climate data, precipitation Regarding the spatial scale, data should be as measured in mm from weather stations over the detailed as possible. Most of the data was refer- last 30 years (minimum ten years) was needed. enced to the districts; more detailed, sub-district Environmental data on forest, river and wetland information was available on land cover/use (ras- management, socio-economic data on the num- ter information with 30m resolution). The infor- ber of people, buildings, critical infrastructures, mation gathered had to cover all of the river basin on the ratio of people employed in the various and should not be older than two years. Spatially economic sectors, the number of people living referenced, reasonably scaled data covering the below the poverty line and spatial data on dam six districts of the basin could be obtained for all locations, elevated buildings and municipalities indicators. participating in the planning process – all the- ses datasets had to be obtained. In addition, in- How to structure and store the data? formation describing the quality of River Basin A data naming convention was defined and Committees (RBCs) had to be based on expert a logical folder structure created. Initially during judgements, and thus suitable experts had to be data collection, all datasets were stored in a folder found. structure organised by source. Subsequently, once Exposure of people, of critical infrastructure the data was being used, a folder structure organ- and of buildings to flooding was determined by ised by topic was created, and all data and meta- means of spatial analysis in a Geographic In- data that ought to be used actively was copied in 50 III there. Thus a copy of the original data in its origi- factsheets (one-page descriptions with a standard- nal state remained, which may be of interest as a ised structure) were created for all datasets used in reference at a later stage. the assessment. Figure 13 shows a map of the land cover in- How to document the data? formation for the river basin. From this dataset, Data and metadata was stored and managed the percentage of area covered by forest per dis- using GIS. The metadata was stored together trict could be extracted. Table 4 shows the attrib- with original data. For documentation purposes, utes for each indicator and district. m4 Figure 13: Visualisation of original data following data acquisition (forest cover extracted from land cover dataset) Cropland (rainfed) Shrubs Wetlands Cropland (irrigated) Sparse vegetation Rivers Mosaic cropland/natural vegetation Tree cover (flooded, saline water) Districts Mosaic natural vegetation/cropland Settlements River basin Forest Water bodies 51 m4 III Table 4: Original data for the different indicators – attributes for each district Component Factor Indicator District 1 2 3 4 5 6 G Hazard Too much precipi- Number of days with 2 3 4 4 5 4 U tation in wet season precipitation ≥ 100mm I D Too much precipi- Number of days with 2 3 4 4 5 4 E tation in wet season precipitation ≥ 100mm L I Exposure People living in Number of people per 30 210 2760 2530 1300 1170 N flood-prone areas km² in flood-prone area E Property & buildings Number of buildings 12 68 970 1100 450 280 S in flood-prone areas per km² in flood-prone areas areas Critical infrastructure Number of critical 0 1 3 2 1 0 in flood-prone areas infrastructure in flood-prone area Vulnerability Wetland degradation Percentage of area 0 9 0 0 0 0 covered by wetlands Missing buffer strips Percentage of river line 3 12 5 0 0 3 aligned by buffer strips Deforestation Percentage area cov- 73 7 0 0 0 4 ered by natural forest Lack of protected Percentage of forest 50 0 0 0 0 0 forest areas area protected River ecosystems Number of dams and 0.01 0.05 0.05 0.1 0.1 0.1 disconnected weirs per km river length Absence of flood Percentage of elevated 0 0 13 3 23 20 resistant housing buildings in the flood zone Lack of water and Quality of operational 4 5 2 1 3 4 wetland manage- RBCs ment capacity Strong dependency Percentage of house- 60 42 23 34 67 53 on agricultural income holds depending on agriculture for income Lack of urban Percentage of munici- 50 25 100 100 75 50 planning palities with participa- tion in planning process Lack of financial Percentage of popula- 27 17 6 12 32 18 resources of people tion with income below national poverty line 52 m5 III Module 5 Normalisation of indicator data This module explains how to transfer (nor- malise) the different indicator datasets into unit- less values with a common scale from 0 (optimal, no improvement necessary or possible) to 1 (criti- cal, system no longer functions). Normalisation converts numbers into a meaning by evaluating the criticality of an indicator value with respect to the risk. Assigning indicator values to numbers ranging from 0 to 1 requires setting thresholds. For some indicators these thresholds are obvious. For example, in the case of ‘percentage of area m5 covered by natural forest’, the value ‘0 %’ is criti- cal and represents the upper threshold of the nor- malisation range: during the process of normali- sation it will be transformed to the value ‘1’. The value ‘100 %’ is optimal and represents the lower threshold of the normalisation range: it will be transformed to the value ‘0’. In other cases, the allocation of thresholds is less evident. For instance, in a drought-prone area a region with an annual precipitation of 600 mm/year may be ‘0’ (optimal), while a region with precipitation of 200 mm may be ‘1’ (critical). Pre- cipitation values between 200 mm and 600 mm will be allocated to respective values between 0 and 1. Values exceeding this range will be either allocated to 0 (in this example all values > 600 mm will receive the number 0) or to 1 (all values < 200 mm) (see also Step 2). For this normative step, it is highly recommended to involve experts to agree on a suitable evaluation scheme. 53 m5 III G U I D E Step 1 define the range of indicator values that represent L Determine the scale this range of criticality levels (see introduction of I Module 5 above). In our application example of of measurement N the river basin, the value ‘2 days with precipita- E tion ≥ 100 mm in the wet season’ was allocated S In order to normalise the data, you first have the meaning ‘optimal rainfall conditions’, while to determine the scale of measurement for each ‘10 days with precipitation ≥ 100’ as ‘critically high’. indicator (see Table 5). Thus, the thresholds for this indicator are 2 and 10. Make sure that the meaning for an in- crease or decrease in value represents the respec- tive change in criticality with respect to the risk. Step 2 For instance, a higher value of the vulnerability Normalise your indicator indicator ‘percentage of area covered by wetlands’ values indicates a lower vulnerability and vice versa, so that in the normalisation process, smaller num- Indicator values can be normalised using two bers of this indicator must be allocated to higher different approaches, depending on the scale of values in the range between 0 and 1. Therefore, the measurement. In the case of metric values, you direction of the indicator’s value range is negative. need to check the ‘direction’ of the value range The stretch of indicator values between the and define thresholds. minimum and maximum threshold follows The values of indicators measured using a Equation 1. Indicator values smaller than xTmin metric scale are allocated to numbers between will be allocated to the value xTmin and indicator 0 and 1, with ‘0’ representing an optimal and ‘1’ values exceeding xTmax will be allocated to the representing a critical state. Identified thresholds value xTmax. Table 5: Example of indicators and their scales of measurement Indicator options Measurement unit Scale of measurement Amount of precipitation mm metric Land cover land use None (descriptive classes) ordinal Forest cover Percentage metric 54 III The formalised rules are: follows a rating scale by defining classes with a meaning applicable to the risk assessment from For xi <– xTmin g xTmin class value 1 = optimal to class value 5 = critical For xi >– xTmax g xTmax (see Table 6). Experts in the respective field should For xi >– xTmin AND xi <– xTmax allocate the various characteristics for each indi- cator (such as ‘forest’ or ‘built-up’ in the case of xi – xTmin land cover) to the different classes. Indicators for xnorm = which no measured or observed data is available xTmax – xTmin (for example ‘quality of operational River Basin Equation 1: Allocation of a normalised value to Committees’) may obtain their values based on an indicator value with ‘xnorm’ for the normal- expert opinion, also using five classes and a de- ised value, xi for the indicator value, xTmin for scription of each class according to Table 6. the lower threshold and xTmax for the upper In preparation for the aggregation of all in- m5 threshold of the normalisation range dicator values, the five-class scheme, too, needs to be transformed into the 0 to 1 range, which is Indicators specified by categorical values and used for the metric variables (see Table 6). an ordinal scale (e.g. land cover, soil type, govern- ment efficiency) are normalised applying a five- For details on how to normalise indicators see class evaluation scheme. This evaluation scheme Vulnerability Sourcebook, p. 106–119. Table 6: Class scheme for variables with ordinal scale Categorical class values within Class value within Description the range of 1 to 5 range of 0 to 1 1 0.1 Optimal (no improvement necessary or possible) 2 0.3 Rather positive 3 0.5 Neutral 4 0.7 Rather negative 5 0.9 Critical (could lead to severe consequences) 55 III G U I D E A P P L I C AT I O N E X A M P L E : L Normalisation of indicator data I N E S Step 1 Determining the scale of measurement It was found that the majority of indicators were measured in metric values. One indicator – ‘quality of operational River Basin Committees (RBCs)’ – had an ordinal scale of measurement. Step 2 Normalising the indicator values First, the direction of the indicators with a metric scale were determined, and subsequently (by applying thresholds representing optimal and critical states for each indicator) the values were transformed into a standardised score between 0 and 1. Table 7 shows the direction, the minimum and maximum value of the data and the defined threshold representing an optimal state (Thresh- old [min]) and a critical state (Threshold [max]) for each indicator. The results of the calculation for these normalisation steps are shown in Table 8. 56 III Table 7: Direction, min-max values and defined thresholds for each indicator Indicator Direction Min Max Threshold (min) (max) Number of days with precipitation ≥ 100mm + 2 5 2 10 Number of days with precipitation ≥ 120mm + 1 4 0 8 Number of people per km² in flood-prone area + 30 2760 0 3000 Number of buildings per km² in flood-prone areas + 12 1100 0 1500 Number of critical infrastructure in flood-prone area + 0 3 0 2 Percentage of area covered by wetlands - 0 9 0 10 m5 Percentage of river line aligned by buffer strips - 0 12 0 50 Percentage of area covered by natural forest - 0 73 0 100 Percentage of forest area protected - 0 50 0 75 Number of dams and weirs per km river length + 0.01 0.1 0 0.1 Percentage of elevated buildings in the flood zone - 0 23 0 100 Quality of operational River Basin Committees (RBCs) - 1 5 1 5 Percentage of households depending on agriculture for income + 23 67 25 75 Percentage of municipalities with participation in planning - 25 100 0 100 process Percentage of population with income below national poverty line + 6 32 0 30 57 m5 III Table 8: Normalised data for the different indicators Component Indicator District 1 2 3 4 5 6 G U Hazard Number of days with precipitation ≥ 100mm 0.00 0.13 0.25 0.25 0.38 0.25 I D E Number of days with precipitation ≥ 120mm 0.13 0.25 0.38 0.50 0.50 0.25 L I Exposure Number of people per km² in flood-prone area 0.01 0.07 0.92 0.84 0.43 0.39 N E S Number of buildings per km² in flood-prone 0.01 0.05 0.65 0.73 0.30 0.19 areas Number of critical infrastructure in flood-prone 0.00 0.50 1.00 1.00 0.50 0.00 area Vulnerability Percentage of area covered by wetlands 1.00 0.10 1.00 1.00 1.00 1.00 Percentage of river line aligned by buffer strips 0.94 0.76 0.86 1.00 1.00 0.94 Percentage of area covered by natural forest 0.27 0.93 1.00 1.00 1.00 0.96 Percentage of forest area protected 0.33 1.00 1.00 1.00 1.00 1.00 Number of dams and weirs per km river 0.10 0.20 0.10 1.00 1.00 1.00 length Percentage of elevated buildings 1.00 0.99 0.83 0.97 0.77 0.80 Quality of operational River Basin Committees 0.70 0.90 0.30 0.10 0.50 0.70 (RBCs) Percentage of households depending on agricul- 0.70 0.24 0.00 0.18 0.24 0.56 ture for income Percentage of municipalities with participation 0.50 0.75 0.00 0.00 0.25 0.50 in planning process Percentage of population with income below 0.90 0.57 0.13 0.40 1.00 0.60 national poverty line 58 m6 III Module 6 Weighting and aggregating indicators This module demonstrates how to weigh in- dicators if some of them are considered to have a greater or smaller influence on a risk compo- nent than others. The module also explains how to aggregate individual indicators of the three risk components. Step 1 Weighting indicators Weighting indicators helps you describe the risk components hazard, vulnerability and expo- sure. The different weights assigned to indicators m6 can be derived from existing literature, stakehold- er information or expert opinion. There are dif- ferent procedures for assigning weights: from so- phisticated statistical procedures (such as principal component analysis) to participatory methods. Step 2 Aggregating indicators Aggregation allows you to combine the nor- malised indicators into a composite indicator rep- resenting a single risk component (see Figure 14). 59 m6 III Figure 14: Aggregating single factors to risk components (in practice the number of indicators may derivate from the count of indicators shown in this conceptual visualisation) H1 H2 H3 H4 G U I D E L E1 E2 E3 E4 S1 S2 C1 C2 I N Weighted arithmetic E aggregation S Weighted arithmetic Weighted arithmetic aggregation aggregation Hazard Exposure Vulnerability Risk There are various aggregation methods (see Vulnerability Sourcebook, Expert box 16, p. 129). This Guidebook follows the Sourcebook ap- (I1 * w1 + I2 * w2 + ... In * wn ) proach, which recommends ‘weighted arith- CI = n ∑w metic aggregation’: Individual indicators are 1 multiplied by their weights, summed and subse- quently divided by the sum of their weights to Equation 2: Aggregating single indicators to a calculate the composite indicator of a risk com- risk component ponent (Equation 2). If there is no difference in weight, indicators are simply summed and di- For detailed guidance on weighting and ag- vided by the number of indicators. All indicators gregating indicators see Vulnerability Sourcebook, must be aligned in the same way towards the risk p. 122–131, and the Vulnerability Sourcebook (see Module 5). Template: Indicator Aggregation. 60 III A P P L I C AT I O N E X A M P L E : Weighting and aggregating indicators Step 1 Weighting indicators For the purpose of keeping the example sim- ple, it was decided to apply equal weights for all indicators. Step 2 m6 Aggregating of indicators The normalised indicator values were aggre- gated to composite indicators for each compo- nent. The results for the districts of the river basin are listed in Table 9 and visualised cartographi- cally in the maps in Figure 15. Table 9: Aggregated indicators (hazard, exposure, vulnerability) Risk component District 1 District 2 District 3 District 4 District 5 District 6 Hazard 0.06 0.19 0.31 0.38 0.44 0.25 Exposure 0.01 0.21 0.86 0.86 0.41 0.19 Vulnerability 0.57 0.65 0.49 0.66 0.89 0.84 61 m6 III Figure 15: Maps of the six districts and their aggregated hazard, exposure and vulnerability values Hazard Rivers Districts River basin G 0.06 - 0.20 U (very low) I D 0.21 - 0.40 E (low) L I 0.41 - 0.60 (medium) N E S Exposure Rivers Districts River basin 0.01 - 0.20 (very low) 0.21 - 0.40 (low) 0.41 - 0.60 (medium) 0.61 - 0.80 (high) 0.81 - 0.90 (very high) Vulnerability Rivers Districts River basin 0.49 - 0.60 (medium) 0.61 - 0.80 (high) 0.81 - 0.96 (very high) 62 m7 III Module 7 Aggregating risk components to risk This module explains how to aggregate the three risk components hazard, vulnerability and exposure into a single composite risk indicator. There are various possible ways to do so. Here a one-step approach using the weighted arithme- tic mean is proposed, which is consistent with the IPCC AR5 risk concept. The advantage of this ap- proach lies in its simplicity. Its main disadvantage is that a positive value of one component may conceal the fact that the value of another com- ponent is critical. This may lead to an undesired concealment of critical issues within a system. When applying this approach, weighting factors can easily be introduced (Equation 3), but are not considered in our application example. (Hazard * wH ) + (Vulnerability * wY ) + (Exposure * wE ) Risk = wH + wV + wE m7 Equation 3: Aggregation of risk components The results of this aggregation can be assigned to risk classes as proposed in Table 10. 63 m7 III G U I D E It is possible to combine several sub-risks into Table 10: Risk classes L an overall risk. This may be useful depending on I the context and the aim of your assessment. For N an aggregation of sub-risks to an aggregated risk, E Metric risk Risk class Description class value value within we recommend to use the same formula (weight- S within range the range ed arithmetic mean) as proposed in the Vulner- of 0 to 1 of 1 to 5 ability Sourcebook for the aggregation of sub-vul- nerabilities (p. 140–141). An alternative approach 0 – 0.2 1 Very low for aggregation with the help of an evaluation > 0.2 – 0.4 2 Low matrix is provided in the Risk Supplement, p. 54. > 0.4 – 0.6 3 Medium > 0.6 – 0.8 4 High For further details on the aggregation of the > 0.8 – 1 5 Very high various components of a specific concept see Risk Supplement, p. 52–54, and Vulnerability Source- book, p. 134–141. Figure 16: Scheme for aggregating the risk components SOCIO-ECOLOGICAL SYSTEM (SES) Hazard Weighted arithmetic Exposure Vulnerability aggre gation Risk 64 III A P P L I C AT I O N E X A M P L E : The values of the three risk components were Aggregating risk components aggregated by applying the arithmetic aggrega- to risk tion method. Table 11 shows the results of this calculation. These risk values are visualised carto- graphically in Figure 17. Table 11: Risk scores District 1 District 2 District 3 District 4 District 5 District 6 Risk 0.21 0.35 0.55 0.63 0.58 0.43 Figure 17: Aggregated risk index m7 0.21 - 0.40 (low) Rivers 0.41 - 0.60 (medium) Districts 0.61 - 0.63 (high) River basin 65 m8 III G U Module 8 I Presenting and D E interpreting the Step 1 L I outcomes of the risk Plan your climate risk assessment report N assessment E S This module shows you how to present and ? GUIDING QUESTIONS: interpret the results of the risk assessment. You visualise what you have learned from the assess- What were the objectives of your assessment? ment, considering the objectives set out initially. What methods did you use? You need to present the findings in a way that is appropriate for your target audiences. Visualis- How did you collect the required information? ing both the aggregated results and the individual What calculations did you carry out? underlying datasets allows you to recognise the How should the report be phrased to respond key drivers of risk. to your audience’s needs? Your findings should be described in an as- What are the lessons learned? sessment report. The descriptive text is accom- panied with figures visualising the outcomes. The When you start writing the report, you should assessment report should provide a clear descrip- first recapitulate the objectives on the basis of tion of the objectives of the risk assessment, of the which you carried out the risk assessment: give a methods applied and the key findings. You should clear, extensive description of the methodology write the report in a readily accessible way, giving you applied, including the individual steps and your audience an overview of the assessment and assessment methods (for example the number of providing them with all the background informa- expert workshops you carried out), the indicators tion they need to interpret and comprehend the you selected, how the information was acquired results according to their information needs. and of the detailed calculations you carried out. Subsequently you need to consider which content, style and language is appropriate for your target audience(s) and which graphical pres- entations are most suitable to help visualise the results. If the findings are targeted at external decision makers, it is essential to consider their objectives and which information (e.g. in terms of extent and level of detail) they need. The vo- cabulary and the way you explain the concept(s) should be accommodated to the skills and exper- tise of the target group, e.g. you should only use those technical terms that are appropriate (un- derstandable) to the readers. 66 III Lessons learned are valuable and should be overall risk, to recapitulate the challenges and included in the assessment report. By describing opportunities you encountered throughout the unanticipated findings and the challenges you assessment and to describe the ‘lessons learned’. encountered, you not only support others facing Here, you should also discuss uncertainties in similar obstacles, but also help the audience un- your assessment transparently, as knowing about derstand the results. knowledge gaps on climate change and its im- pacts will foster the audience’s understanding of your findings. Step 2 Describe your assessment Step 3 When structuring the assessment, keep the Illustrate your findings four core sections in mind: context and objectives Illustrations attract the reader’s attention and methodology and implementation make texts more comprehensible. Maps, diagrams findings and graphs are valuable and compelling tools for conclusions and lessons learned. illustrating assessment findings. It is crucial to choose the right type of illustration. The beginning of your report should clearly Maps are an excellent way to visualise geo- state the context, objectives and underlying as- graphic information and facilitate comparisons sumptions. This includes in particular the points of regions. A cartographic visualisation of assess- addressed in Module 1. A detailed report will also ment results allows your readers to immediately describe the resources and timeframe of the as- detect the variation of climate risks across re- m8 sessment to help the reader review assessment gions. Maps are especially valuable in participa- inputs and outputs accordingly. tive processes and very well suited to involving Next, outline the methods used in the assess- local stakeholders in the risk assessment. ment, thus providing a summary of what was Various types of diagrams and graphs – such done in Modules 2 to 7. This is key to the audi- as radar, pie, bar or line charts – can be used to il- ence’s interpretation of the findings. If the as- lustrate the findings of the risk assessment graph- sessment is used for monitoring and evaluation ically. (M&E), it should include a more extensive de- scription with indicator and data factsheets. The subsequent main part of the report pre- sents the results of the assessment. This is the place to describe how your findings should be For further details on presenting the outcomes interpreted, to present the values for individual of the assessment see Vulnerability Sourcebook, p. indicators, aggregated risk components and the 144–154. 67 III G U I D E A P P L I C AT I O N E X A M P L E : farmers, regional government, the relevant ad- L Presenting and interpreting the ministrations and departments. The report was I outcomes of the risk assessment thus written in a way that suited the information N needs of regional decision-makers and those who E were responsible for implementing the measures S at the district and local level. Step 1 Plan your climate risk assessment report Step 2 Describing the results of The writing of the assessment report started the assessment by first re-visiting the objectives and planned outcomes as defined in the initial phases of the During a series of workshops, an impact chain assessment – ‘What is the risk of river flooding (as shown in Figure 18) was developed by identify- for people’s lives, damage to property and criti- ing factors that lead to the risk of damage of prop- cal infrastructures, and (how) can it be reduced erty and loss of lives due to flooding. Based on a through adaptation, including EbA measures. good understanding of the situation in the river Which potential co-benefits and trade-offs may basin and the construction of a simplified (reduced EbA options have?’ (see Module 1, Step 2) – and amount of factors, links and feedback loops for the the envisaged outcome of the assessment: ‘a map purpose of this Guidebook) overview of cause and of flood risk hotspots and related ecosystem ser- effect relationships, the following five EbA options vices, a list of indicators and datasets, a narrative were determined: wetland restoration (1), reten- analysis of the risk and its determining factors.’ tion ponds (2), riparian zone restoration (3), affor- Regarding methods, it was decided to use an estation/reforestation (4) and buffer strips (5). approach based on impact chains, EbA and com- By identifying indicators, collecting and pre- posite, spatially explicit indicators. The required paring the corresponding datasets, each factor information came from a variety of sources and could be quantified. The indicator values were included quantitative as well as qualitative infor- normalised on a scale between 0 and 1, so that mation. Indicators were aggregated with equal they could be aggregated (by means of arithmetic weights, applying an arithmetic aggregation aggregation) to the three risk components (haz- method – first to the risk components hazard, ard, vulnerability and exposure), which, in a final vulnerability and exposure, subsequently to an step (also by means of arithmetic aggregation) overall risk. Thus, the outcomes consisted of nu- were aggregated to an overall risk value. meric values with a spatial reference on a district The visualisation of the overall risk value and level. its components shows that Districts 3, 5 and 6 The target audience for this climate risk as- have an intermediate risk, while District 4 – most- sessment was the local community, i.e. all resi- ly due to high exposure and high vulnerability – dents and especially landowners, leaders and has the highest risk of damage due to flooding 68 Hazard Wetland Vulnerability degradation Figure 18: Cause and effect relationships describe the situation and helped identify potential adaption measures Too much precipitation 1 in wet season Reduced Unsuitable use Lack of water and wetland Intermediate of flood plains management capacity natural Impacts retention 3 1 3 Too much precipitation Too high Increased flow capacity in dry season water level velocity Agricultural land 2 too close to river Eco- 2 Strong dependency system Missing buffer on agricultural income Erosion services strips Sediment 3 5 3 deposition Reduced erosion protec- Lack of protected Siltation of tion Deforestation forest areas river bed 2 4 Degradation of aquatic Exposure ecosystem River ecosystem Built infrastructure disconnected blocking river flow People living in flood prone areas Flooding 3 Lack of financial resources of people Property and buildings in Absence of flood Lack of urban flood prone areas resistant housing planning 1 Critical infrastructure in Ecosystem-based adaptation options Conventional adaptation option flood prone areas Risk Risk of damage of property and loss of lives due to flooding Risk Exposure Climate Intermediate Sensitivity Sensitivity Capacity Signal Impact Ecological Socio-economic III 69 m8 m8 III G U I D E (see Figure 19): There are by far more people liv- Step 3 L ing in District 3 and 4 than in any other district. Illustrating the findings I Moreover, District 4 has the highest density of N buildings in flood-prone areas. The results indi- Figure 20 shows the values of the risk compo- E cate that the districts downstream, due to a larger nents as a complex bar chart. We can easily notice S human presence in flood-prone areas, are more how the six districts compare. District 4 shows the at risk than the area upstream in the mountains. overall highest risk, and its largest contributing Lessons learned: The fact that, from the start, component is exposure. District 3 is equally ex- all relevant stakeholders from different adminis- posed, yet it has a lower overall risk than District 4. trative levels and different sectors as well as local Figure 20 clarifies that this is mainly due to the experts were involved, not only provided valuable lower vulnerability of District 3, which can mostly inputs and datasets for the assessment, but also en- be attributed to more buffer strips along the river, sured co-ownership and acceptance of the results. the fact that more than five times as many build- Figure 19: Map showing the overall risk value and the contributions of each risk component per district Risk components Hazard 0.21 - 0.40 (low) Rivers Circle size Exposure 0.41 - 0.60 (medium) Districts relative to the risk value Vulnerability 0.61 - 0.63 (high) River basin 70 III Figure 20: Aggregated risk components and overall risk for all six districts of the river basin shown as a bar chart 1.00 0.86 0.63 0.84 0.81 0.80 0.64 0.64 0.67 0.63 0.60 0.56 0.52 0.56 0.44 0.41 0.42 0.40 0.38 0.39 0.31 0.64 0.21 0.25 0.19 0.19 0.20 0.01 0.01 0.00 District 1 District 2 District 3 District 4 District 5 District 6 Hazard Exposure Vulnerability Risk ings in the flood zone are elevated and that the people living below the national poverty line and poverty rate is two third below the rate in District the highest proportion of households depending 4. District 5 has a similarly high overall risk as on income from agriculture, District 5 has the District 3 and 4, but this is due to a very high vul- highest vulnerability. Figure 21 shows the same nerability: as a result of the highest proportion of information presented as a spider diagram. Figure 21: Aggregated risk components visualised for all six districts of the river basin as radar chart m8 District 1 1.00 Hazard 0.80 Exposure District 6 0.60 District 2 Vulnerability 0.40 0.20 0.00 District 5 District 3 District 4 71 m8 III G U I D E In order to understand the underlying rea- that need to be graphically presented, a bar chart L sons for the aggregated values of the risk com- is a more suitable means of representation: Fig- I ponent, it is required to look at the individual ure 22 e.g. allows to make a statement about the N indicator values. They can be found in the respec- factors contributing to the exposure in District 3 E tive table, but often a diagram makes it easier to and District 5. District 3 has a much higher Expo- S grasp them. For the visualisation of many indica- sure than District 5 as more people, more build- tor values, e.g. for the vulnerability component, ings and more critical infrastructures are located it is recommended to use a spider diagram. The within the flood-prone area. individual normalised values of the vulnerability indicators of the two districts with the highest aggregated risk values, i.e. Districts 3 and 4, are shown in Figure 23. With one glance on this chart you can see that the higher vulnerability of Dis- trict 4 is mainly due to the number of dams and weirs along the river and – to a lower extent – to the quality of RBCs and the number of elevated buildings. If there are only few indicator values Figure 22: Comparing exposure indicator values of District 3 and District 5 visualised in a bar chart 1.00 Exposure in Districts 3 and 5 1.00 0.92 0.65 0.50 0.50 0.43 0.30 0.00 No. of people per km2 No. of buildings per km2 No. of critical infrastructure in flood prone area in flood prone area in flood prone area District 3 District 5 72 III Figure 23: Vulnerability indicator values for District 3 and District 4 shown as a spider diagram. Note that for District 3 the two indicators ‘percentage of households depending on agriculture for income’ and ‘percentage of municipali- ties with participation in planning process’ are displayed as one dot, since they both have the value 0. District 3 % of area covered by wetlands 1.00 % of population with income 0.90 % of river line aligned by below national poverty line 0.80 buffer strips 0.70 0.60 0.50 0.40 % of municipalities with 0.30 % of area covered by natural forest participation in planning process 0.20 0.10 0.00 % of households depeding % of forest area protected on agriculture for income Quality of operational River Basin No. of dams and weirs per km river Commitees (RBCs) length % of elevated buildings District 4 % of area covered by wetlands 1.00 % of population with income 0.90 % of river line aligned by below national poverty line 0.80 buffer strips m8 0.70 0.60 0.50 0.40 % of municipalities with 0.30 % of area covered by natural forest participation in planning process 0.20 0.10 0.00 % of households depeding % of forest area protected on agriculture for income Quality of operational River Basin No. of dams and weirs per km river Commitees (RBCs) length % of elevated buildings 73 m9 III G U Module 9 I Identifying adaptation D E options L Using impact chains and risk assess- I This module elaborates how climate risk as- ment to identify adaptation options N sessments can support the identification of ad- E aptation options – including EbA – as part of an As indicated in Module 2, impact chains can S overall adaptation strategy. First, it discusses how provide entry points and first guidance for the impact chains and risk assessments can support identification of adaptation options, including the identification and spatial planning of EbA conventional hard/‘grey’ (e.g. engineering-based), options. Then it explains the concept of ‘EbA co- soft (e.g. training, insurance, etc.), ecosystem- benefits’ and describes how these can be specified based/‘green’ and hybrid (combined grey and during the assessment process. Finally, it provides green) solutions. If the assessment aims to identi- information on required next steps towards im- fy where to implement EbA measures, then spatial plementing EbA measures based on a further pri- information is needed on risk hotspots (i.e. areas oritisation and selection process. of particularly high exposure, vulnerability and/ Responding to the need to link risk assess- or risk), on the status of key ecosystems and on ments more directly with adaptation planning, how their services contribute to the ecological di- this module, which is described neither in the mension of vulnerability. Vulnerability Sourcebook nor its Risk Supplement, Depending on the scope of the assessment, has been added to the Guidebook. the conditions in the area and the social ecologi- cal system under consideration, there are two main ways in which vulnerability and risk maps can support the planning and spatial prioritisa- tion of EbA measures: 1. service provision area = service benefit area ESS are produced in the same area where the benefit is realised (e.g. soil formation benefit- ting farmers). Measures are implemented in areas of par- ticularly high exposure, vulnerability and risk (e.g. focusing on restoration of degraded eco- systems and their services or even creation of new ecosystems). 2. service provision area ≠ service benefit area ESS are produced beyond the area where ben- efits manifest themselves (e.g. water regula- tion, flood prevention). 74 III Measures are implemented in areas of low or 2017). For example, afforestation/reforestation medium vulnerability and risk as target re- upstream in a catchment not only reduces erosion gions, which provide key ecosystem services levels locally and provides a buffer for floods, but to areas with high exposure, vulnerability and by doing so also protects downstream areas. risk (e.g. focusing on the conservation and Further, the Guidebook emphasises the need sustainable management of existing natural for integrated ‘adaptation packages’, comprising ecosystems and their services). conventional infrastructure-based, ecosystem- based, hybrid, and political solutions to ensure Assessing specific key components and un- the sustainability and effectiveness of adapta- derlying drivers of risks can further support the tion measures. For example, strategic reforesta- planning of adaptation measures by pointing tion as an ecosystem-based solution can enhance out which drivers are particularly contributing the ecosystem service ‘flood regulation’ and thus to high levels of vulnerability and risk and hence reduce the flood risk significantly. However, if should be targeted by appropriate measures. Thus, trees are planted in a region where (informal) it is important to acknowledge that the drivers of livelihoods depend on cutting wood (e.g. for fire risk can vary spatially in a study area, requiring wood, etc.), the success of the measure may be place-based approaches to risk reduction and ad- threatened by potential deforestation. This is aptation planning. why integrated adaptation packages in the form Regardless of which approach is chosen (i.e. of combined reforestation and livelihood diver- option 1, option 2, or a combination of both), pri- sification programmes can significantly enhance ority should be given to measures that have effects the sustainability and adaptation benefits of the at both the local and the landscape level (FEBA measure. Figure 24: Different spatial relationships between ecosystem service provision areas (P) and ecosystem service benefiting areas (B) within social-ecological systems (SES) (Source: adapted from Fisher et al, 2009) m9 P P=B P B B SES SES SES 75 III G U I D E A P P L I C AT I O N E X A M P L E : tribute to the overall risk scores) supports the plan- L Identifying ning of potential EbA measures in the spatially ex- I adaptation options plicit social-ecological system (as identified during N the development of impact chains; see Module 2). E The exposure, vulnerability and risk maps S The information generated during the risk as- presented in Module 7 and the risk profiles de- sessment in the river basin (i.e. exposure, vulner- veloped in Module 8 show that risk is highest ability and risk, particularly risk maps and profiles in District 4 (0.63 in a scale from 0 to 1), largely which reveal how the underlying indicators con- driven by high exposure of people, infrastructure Figure 25: Suggested EbA measures to tackle flood risk in District 4, based on the findings described above Implementation of buffer strips along rivers Reforestation Wetland restoration Cropland (rainfed) Shrubs Wetlands Cropland (irrigated) Sparse vegetation Rivers Mosaic cropland/natural vegetation Tree cover (flooded, saline water) Districts Mosaic natural vegetation/cropland Settlements River basin Forest Water bodies 76 III and buildings to flooding (0.86), but also by high vulnerability of its social-ecological system (0.66). Identifying co-benefits and The risk profile shows that multiple factors feedback loops contribute to the district’s high vulnerability, including the lack of wetlands and buffer strips. Compared to conventional ‘grey’ engineering Flood risk in District 4, which is located in the solutions (e.g. dams, dykes, etc.), ecosystem-based downstream part of the river basin, is further ‘green’ solutions can generate additional social, aggravated by deforestation and the lack of wet- economic or cultural/recreational co-benefits lands and retention areas in upstream areas, such that go beyond adaptation benefits (CBD 2009). as District 2 and District 3. Depending on the type of EbA measure, potential It was decided that these measures should be co-benefits include, but are not limited to, posi- complemented by additional soft, hard or hybrid tive effects on health and well-being (e.g. clean as well as political and social measures, e.g. edu- air, increased food provision and nutrition, etc.), cation campaigns and livelihood diversification additional livelihood opportunities and sources programmes, as identified during the develop- of income (e.g. mangrove forests serving as nurs- ment of the impact chain. ery grounds for fish and shrimp, eco-tourism, etc.) and environmental benefits (e.g. water purification, carbon sequestration, climate regulation), while at the same time contributing to the conserva- tion of biodiversity. Further, EbA measures are of- ten cost-effective adaptation solutions. Mangrove restoration, for example, has proven to be more cost-effective than maintaining conventional hard structures such as dykes (UNEP, UNDP & IUCN 2012). Consequently, EbA options are considered to be so-called ‘low-regret’ solutions. However, trade-offs and unintended conse- quences may also arise, for example when an EbA m9 measure protects one group of people at the ex- pense of another, favours one ecosystem service over another (UNFCCC 2017), or increases existing health threats (e.g. serving as breeding ground for vector-borne diseases). Assessing and monitoring the (co-)benefits of EbA is, therefore, not sufficient. Instead, potential trade-offs, synergies, and unin- tended consequences should be considered during the identification, evaluation, design and imple- mentation of EbA measures (CBD 2016; UNFCCC, 77 m9 III G U I D E SBSTA 2017). Thus, impact chains can be a valu- A P P L I C AT I O N E X A M P L E : L able tool to identify such measures in a structured, Identifying I participatory manner following a sequence of key N adaptation options steps: E S For the previously identified EbA measure Step 1 ‘wetland restoration’ (see Figure 26), the following Identify potential co-benefits direct benefits, co-benefits and unintended con- sequences were identified: ? GUIDING QUESTIONS: 1. Direct adaptation benefits or effects include What would be potential co-benefits of a spe- increased ground water storage, increased cific EbA measure? water regulation during the dry season, and For each EbA measure identified and visual- better water quality. ised in the impact chain (Module 2), you should brainstorm on possible social, economic and eco- 2. A number of co-benefits were identified, affect- logical co-benefits that could affect the different ing both factors within the risk components risk components (intermediate impacts, exposure, (e.g. wetland restoration leading to increased vulnerability). The factors identified for these biodiversity, which in turn can result in more components can serve as a starting point for such eco-tourism and additional income for people a brainstorming exercise. living in the river basin), but also ‘outside’ of the risk components (e.g. wetland restoration leading to increased carbon sequestration and hence to mitigation of climate change Step 2 which in turn can have a long-term effect on Identify potential unintended precipitation patterns in the basin). consequences or drawbacks 3. It was determined that, due to the tropical cli- ? GUIDING QUESTIONS: mate in the region, increase of vector-borne diseases (e.g. dengue, malaria) and loss of Which unintended consequences (trade-offs) agricultural land are potential (unintended) might a specific EbA measure have? consequences that could adversely affect hu- Repeat the exercise described for Step 1, this man health and well-being in the river basin. time for potential unintended consequences or drawbacks of each identified EbA option. 78 Risk Figure 26: Co-benefits and potential unintended consequences of EbA measures (example: wetland restoration) Increased carbon Good health & well- sequestration/climate change mitigaton Wetland being (SDG 3) Better reforestation air quality Zero hunger Hazard Vulnerability (SDG 2) Increased ground Wetland Too much precipitation water storage degradation in wet season Intermediate Reduced Unsuitable use Lack of water and wetland natural management capacity Impacts retention of flood plains Too much precipitation Too high Increased flow capacity water level velocity Loss of agricultural land in dry season Increased water avg. during dry season Agricultural land too close to river Strong dependency Erosion Ecosystem on agricultural income Increase services Climate & Sediment in vector borne Missing buffer strips Increased livelihoods Society & Reduced from fishing Environment deposition diseases erosion protec- Economy New water plants to Siltation of tion Deforestation harvest river bed Increased biodiversity Lack of protected Degradation Better forest areas of aquatic water ecosystem quality Exposure River ecosystem Built infrastructure Flooding disconnected blocking river flow People living in flood prone areas Pollination, Increased Additional pest control tourism income More fish Property and buildings in Lack of financial flood prone areas resources of people More birds Absence of flood Lack of urban resistant housing planning Critical infrastructure in flood prone areas Risk Risk of damage of property and loss of lives due to flooding EbA Direct Co- Drawback measure benefits benefits III 79 m9 m9 III G U I D E ments and funding for projects, but they can also L Next steps towards the implementa- help to promote the use of EbA measures at a I larger scale. tion of EbA measures N There are various approaches to assess the E Consider what additional steps are required adaptation options, including cost-benefit analy- S in order to effectively plan and implement EbA sis (CBA), cost-effectiveness analysis (CEA), and options. Depending on the spatial resolution of multi-criteria analysis (MCA). They can be com- the risk assessment (e.g. district level in the ap- bined, so as to consider environmental, social and plication example), further in-depth and spa- economic costs and benefits in order to make the tially explicit analysis may be useful to identify best recommendations. where measures should be implemented in order CBAs should follow best practices to establish to unfold the maximal direct adaptation benefit. priorities in implementing EbA measures. They For example, hydrological models taking into ac- should quantify benefits of ecosystem services as count climate data (precipitation, evaporation, well as costs associated with management. How- etc.), existing flood control measures, topography, ever, planners need to take into account the in- soil conditions, land use and river geometry can herent challenges involved in assigning econom- be useful tools to simulate the effects of potential ic values to system components that cannot be adaptation measures (incl. EbA) on flood hazards translated into monetary terms (e.g. cultural ser- and hence support their planning and prioritisa- vices – spiritual and aesthetic). Incorporating rap- tion. id ecosystem services appraisals into assessments Assessing the (economic, environmental, and is one way to assess not only current ecosystem social) costs, benefits and impacts of adaptation services and co-benefits, but also how these might measures is crucial for the planning stage of the change in the future. adaptation process. Additionally, it helps you de- Ultimately, assessing costs and benefits of cide on where and when to implement measures EbA options allows planners to make informed and how to efficiently prioritise and allocate lim- decisions about what measures will best meet the ited financial and technological resources. Once needs of stakeholders. However, to support and sites are selected, you can engage with stakehold- encourage the further implementation of EbA ers to ensure that the proposed EbA options are measures and their upscaling, further informa- acceptable to community members. tion on the costs, benefits and economic incen- When evaluating EbA options, take into ac- tives is needed. count how they contribute to the project adap- While various valuation methods are avail- tation goals and define measurable criteria for able, there are still multiple challenges for im- assessing this contribution, such as efficiency, plementing and upscaling EbA measures. One effectiveness, equity, urgency, flexibility, robust- challenge is the need for additional evidence that ness, practicality, legitimacy, and coherence with EbA approaches can reduce biophysical risks as other strategic objectives. Economic assessments effectively as grey infrastructure and deliver- of EbA options may be necessary to secure invest- ing other ecosystem service co-benefits. Another 80 III challenge is that many valuation methods for as- sessing the costs and benefits of adaptive infra- structure projects or ecosystem services have not yet been widely applied in EbA contexts. Further, ecosystem services and other direct and indirect benefits offered by EbA measures tend to be un- derestimated, which prejudices the adaptation decision-making process. GIZ has developed a Sourcebook on valuing the benefits, costs and impacts of EbA measures (GIZ 2018). It aims to assist in building awareness, knowledge and capacity about why, how and in which contexts EbA valuation can be used to in- form, guide and influence adaptation decision- making. The sourcebook combines information on valuation theory and methods with real- world examples, showing step-by-step how to commission, design and implement EbA valua- tion studies. m9 81 IV IV. M & E In addition to the question of whether and how risk assessments can inform the identifica- tion, planning and prioritisation of EbA options, How to use the discussion around monitoring and evaluation (M&E) of adaptation in general (and of EbA in par- the risk assess- ticular) has gained attention over the past years. Performing M&E is particularly important in ment for climate change adaptation, as decisions for adap- tation measures are typically taken under uncer- monitoring tainty. M&E can support required adjustments in the adaptation strategy. It also helps to identify and evaluation future needs and trigger points for adaptive man- agement, i.e. changing strategies or methods to manage future uncertainties. Within an EbA con- text, M&E allows managers to understand which progress has been made and which obstacles still have to be overcome. There are a number of con- siderations for effective M&E of implemented EbA measures. It should incorporate appropri- ate methods to check whether management ap- proaches are effective, taking into account the amount of time particular EbA measures need before they are established and before they can provide their intended benefits and co-benefits. M&E does not only involve tracking indicators that measure adaptation outcomes, but also en- gaging with stakeholders to incorporate feedback. Overall, it should be regarded as a tool that helps you understand which EbA measures can most effectively improve future implementation. Indicator-based risk assessments, as sug- gested in this Guidebook, can contribute to an overall M&E framework by using climate risk as- sessments as one of multiple tools to support the M&E of adaptation – including EbA. Initial risk assessments provide baselines for understanding changes in risk levels before the implementation of adaptation measures. Post-implementation 82 IV M & E risk assessments inform about the overall change overall changes in the social-ecological system of risk in an area. which are independent from the measure im- As risk scores are highly aggregated, M&E plemented). must consider changes in the risk component Despite these limitations, repeated risk as- (exposure and vulnerability) and their individu- sessments can inform about overall progress in al factors. This is crucial in order to understand the climate risk reduction of a region, even if it changes in the underlying factors and whether may not be unequivocally attributable to a certain and to which degree they are affected by the im- EbA measure. plementation of adaptation measures. However, By using an adaptive management approach, M&E based on risk assessments has a clear limi- risk assessments can facilitate adjustments or fur- tation: attributing positive or negative trends or ther implementation needs. Subsequently, EbA outcomes to particular, previously implement- measures can be modified as needed and resourc- ed measures is difficult, as a large number of es reallocated to measures that produce the most factors can influence the outcome (for example positive results. Figure 27: M&E of adaptation through repeated risk assessment (Source: UNU, EURAC) Baseline risk Implement Repeated risk Repeated risk Repeated risk assessment EbA measure assessment assessment assessment Identify risk hotspots & Compare & Compare & Compare & adaptation options identify changes identify changes identify changes t0 t+1 t+2 t+n present future future future 83 V V. C O N C L U S I spatial information, can be identified and speci- O N fied within the risk assessment process and used as starting points for further adaptation planning. Concluding For a successful implementation and uptake of climate risk assessments – as for any risk assess- remarks ments following the Vulnerability Sourcebook- approach – the participation of a wide range of actors is pivotal. This approach has already been applied in more than 20 different contexts, and it This Guidebook relies at its center on an ex- was possible to derive the following conclusions: ample, outlining how to apply climate risk assess- ments in the context of Ecosystem-based Adapta- Participation of different stakeholder groups in tion (EbA) as part of an overall adaptation strategy. climate risk assessments The Guidebook addresses typical elements of EbA helps to better understand the social-ecologi- which – in the context of climate change adap- cal system and its interaction by making use tation – intends to make use of the relationships of both local and scientific knowledge and between society, economy and ecosystems, con- combining a diversity of sector experience; stituting a social-ecological system (SES). strengthens knowledge and awareness among Of particularly noteworthy importance are the different actors involved; the spatial characteristics of any risk assessment aiming to support EbA. Unlike many other risk supports ownership by relevant stakeholders, reduction or adaptation measures, EbA needs from government to affected communities. to be based on a spatially explicit ‘landscape ap- Impact chains (cause-effect relationship) proach’. Therefore, the question ‘where’ is even more indispensable than in other cases when go- help decision makers to better understand the ing through the various analysis steps. relation between climate risks and sustain- Through the application example the Guide- able development; book demonstrates how EbA options make use of support transparency and credibility of cli- mate risk assessment results; increase political support for identified adap- tation actions. This publication presents one possible meth- od for implementing a climate risk assessment focusing on EbA. It intends to provide general systematic guidance; the specific details need to be adapted to the circumstances in the region un- der consideration. 84 V C O N C L U S I – good practice examples and lessons learned in O Literature Europe. Bundesamt fur Naturschutz (BfN) – Fed- N eral Agency for Nature Conservation. Adhikari, B.R., Suwal, M.K. 2013: Hydrogeo- Dourojeanni et al. 2016: Vulnerability Assess- logical Study in Bangsing Deurali VDC, Syangja: ments for Ecosystem-based Adaptation: Lessons An Ecosystem-based Adaptation in Mountain from the Nor Yauyos Cochas Landscape Reserve Ecosystem in Nepal. IUCN. in Peru. In: Salzmann N., Huggel C., Nussbaumer S., Ziervogel G. (eds) Climate Change Adaptation Baig et al. 2016: Cost and Benefits of Ecosys- Strategies – An Upstream-downstream Perspec- tem Based Adaptation: The Case of the Philip- tive. Springer. pines. Gland, Switzerland: IUCN. Emerton, L.; Huxham, M.; Bournazel, J.; Ku- Berkes, F. and Folke, C. 1998: Linking Social mara, M.P. 2016: Valuing Ecosystems as an Eco- and Ecological Systems: Management Practices nomic Part of Climate-Compatible Development and Social Mechanisms for Building Resilience. Infrastructure in Coastal Zones of Kenya & Sri Cambridge Univ. Press. Lanka. In: Renaud et al. (eds.), Ecosystem-Based Disaster Risk Reduction and Adaptation in Prac- Bourne et al. (2012): Climate Change Vulnera- tice. Springer, pp. 23-43. bility Assessment for the Namakwa District Munic- ipality. Conservation International, South Africa. Estrella, M. and Saalismaa, N. 2013: Ecosys- tem-based disaster risk reduction (Eco-DRR): An CBD 2009: Connecting Biodiversity and Cli- overview. In: Renaud, F.G.; Sudmeier-Rieux, K.; mate Change Mitigation and Adaptation: Report Estrella, M.; Nehren, U. (eds.) 2016: Ecosystem- of the Second Ad Hoc Technical Expert Group on Based Disaster Risk Reduction and Adaptation in Biodiversity and Climate Change. CBD Technical Practice. Springer, pp. 26-54 Series No. 41. Etzold, J. 2015: Ecosystem-based Adaptation CBD 2016: Synthesis Report on Experiences in Central Asia: Vulnerability of High Mountain with Ecosystem-Based Approaches to Climate Ecosystems to Climate Change in Tajikistan’s Change Adaptation and Disaster Risk Reduction. Bartang Valley – Ecological, Social and Economic CBD Technical Series No. 85. Aspects – with references to the project region in available online* Kyrgyzstan. GIZ. Cohen-Shacham, E.; Walters, G.; Janzen, C. and Maginnis, S. (eds.) 2016: Nature-based Solu- tions to address global societal challenges. IUCN. Doswald, N. and Otsi, M. 2011: Ecosystem- based approaches to adaptation and mitigation * You can find a link in the online version of this document. 85 V C O N C L U S I European Commission 2013: Building a GIZ and EURAC 2017: Risk Supplement to O N Green Infrastructure for Europe. European Union. the Vulnerability Sourcebook. Guidance on how available online* to apply the Vulnerability Sourcebook 2017: Risk Supplement to the Vulnerability Sourcebook. FEBA 2017: Making Ecosystem-based Ad- Guidance on how to apply the Vulnerability Sour- aptation Effective: A Framework for Defining cebook’s approach with the new IPCC AR5 con- Qualification Criteria and Quality Standards cept of climate risk. GIZ. (FEBA technical paper developed for UNFCCC- available online* SBSTA 46). Bertram, M., Barrow, E., Blackwood, K., Rizvi, A.R., Reid, H., and von Scheliha-Dawid, GIZ 2018: Valuing the Benefits, Costs and Im- S. (authors). GIZ, IIED and IUCN. pacts of Ecosystem-based Adaptation Measures: A available online* sourcebook of methods for decision-making. GIZ. available online* Fisher, B., Turner, R. and Mauling, P. 2009: De- fining and classifying ecosystem services for deci- IPCC 2007: Assessment of adaptation prac- sion making. Ecological Economics 68: 643-653. tices, options, constraints and capacity. Climate available online* Change 2007: Impacts, Adaptation and Vulner- ability. Contribution of Working Group II to the Franco, C. and Brander, L. 2017: Application Fourth Assessment Report of the Intergovern- of Cost-Benefit Analysis to Ecosystem based Ad- mental Panel on Climate Change. Cambridge aptation (EbA) solutions for climate change: Final University Press. results. The Nature Conservancy. available online* IPCC 2014a: Climate Change 2014: Impacts, GIZ 2014: The Vulnerability Sourcebook. Adaptation, and Vulnerability. Part A: Global and Concept and guidelines for standardised vulner- Sectoral Aspects. Contribution of Working Group ability assessments. GIZ. II to the Fifth Assessment Report of the Intergov- available online* ernmental Panel on Climate Change. Cambridge University Press. GIZ 2015: Pre-selection and Preparation of available online* Ecosystem-based Measures in the Pilot Areas Huai Sai Bat and Tha Di for discussion and final IPCC 2014b: Climate Change 2014: Impacts, decision-making in collaboration with local wa- Adaptation, and Vulnerability. Part B: Regional ter committees. GIZ. Aspects. Cambridge University Press. available online* GIZ 2016: How to mainstream Ecosystem- based Adaptation? What are tools for integrating Jiménez Hernández, A. 2016: Ecosystem- EbA into decision making and planning? GIZ. based Adaptation Handbook. IUCN. available online* available online* 86 V C O N C L U S I Mataki et al. 2013: Choiseul Province climate UNFCCC/SBSTA 2017: Adaptation planning, O change vulnerability and adaptation assessment implementation and evaluation addressing eco- N report: securing the future of Lauru now. SPC/ systems and areas such as water resources. UNF- GIZ/SPREP. CCC/Subsidiary Body for Scientific and Techno- logical Advice. Mant et al. 2014: Opportunities for using cli- available online* mate change mitigation and adaptation measures to make progress towards the CBD Aichi Biodi- Vicarelli M.; Kamal, R. and Fernandez, M. versity Targets: Guangxi Province, China. UNEP- 2016: Cost Benefit Analysis for Ecosystem-Based WCMC. Disaster Risk Reduction Interventions: A Review of Best Practices and Existing Studies. In: Renaud Ostrom, E. 2009: A General Framework for et al. (eds.), Ecosystem-Based Disaster Risk Reduc- Analyzing Sustainability of Social-Ecological Sys- tion and Adaptation in Practice. Springer. tems. Science, 325 (5939): 419-422. Schumacher, P.; Garstecki, T.; Mislimshoeva, B.; Morrison, J.; Ibele, B.; Lesk, C.; Dzhumabaeva, S.; Bulbulshoev, U. and Martin, S. 2018: Using the Open Standards-based framework for planning and implementing Ecosystem Based Adaptation projects in the high mountainous regions of Cen- tral Asia. Springer. Travers A.; Elrick, C.; Kay, R.; Vestergaard, O. 2012: Ecosystem-based Adaptation Guidance: Moving from Policy to Practice. UNEP working document. available online* UNEP, UNDP and IUCN 2012: Making the Case for Ecosystem-based Adaptation: Build- ing Resilience to Climate Change. UNEP/UNDP/ IUCN. available online* UNFCCC 2011: Assessing the costs and ben- efits of adaptation options – an overview of ap- proaches. UNFCCC. available online* * You can find a link in the online version of this document. 87 VI A N N E X 88 VI VI. A N N E X whether an envisaged approach qualifies as EbA. For this to be the case, all three elements of the CBD definition of EbA (CBD 2009) need to be ful- The EbA filled: A) it helps people adapt to climate change B) by an active use of biodiversity and ecosystem Guidebook services C) in the context of an overall adapta- tion strategy. In order to determine, practically, Annex whether a measure meets the requirements of EbA, the FEBA paper provides five qualification criteria covering all three elements of the EbA definition (see Table_Anx 1). The EbA Guidebook can be used as a tool to Qualification criteria and determine which qualification criteria are ful- quality standards for EbA – filled. For example, the reduction of vulnerabili- the FEBA example ties (criteria 1) could be evaluated using the EbA The climate risk assessments carried out fol- Table_Anx 1: FEBA EbA qualification criteria lowing this Guidebook result in a comprehensive (Source: FEBA 2017) picture of the risk under consideration. They pro- vide knowledge about cause and effect relation- ships, spatial risk hot spots, the underlying factors Elements of CBD Qualification Criteria: contributing to the risk, and subsequently they definition: enable the identification and spatial planning of A) EbA helps people to 1. reduces social and envi- suitable EbA options. The FEBA (Friends of Eco- adapt ronmental vulnerabilities, system-based Adaptation) assessment framework 2. generates societal summarised below can be used to improve the benefits in the context of quality of EbA measures, it can help correct your climate change adaptation, course during the implementation phase, and it can be used as a basis for reporting. B) EbA makes active 3. restores, maintains or use of biodiversity and improves ecosystem health, A technical paper published by FEBA provides ecosystem services guidance on criteria and quality standards for an effective EbA (FEBA 2017). We highly recommend C) EbA is part of an 4. is supported by policies overall adaptation at multiple levels, to consult the FEBA criteria when designing, im- strategy plementing and monitoring EbA measures also in 5. supports equitable the context of climate risk assessments. governance and enhances The FEBA criteria are based on practical expe- capacities. riences in various regions, ecosystems and levels of governance. The first important step is to check 89 VI A N N E X Guidebook approach by making use of repeated teria listed above. The assessment results in one risk assessments over time (see Chapter IV). Soci- of four categories – from very weak to very strong etal benefits in the context of climate change ad- EbA. The quality of an EbA initiative is measured aptation (criteria 2) can be assessed using the im- with indicators. pact chain methodology as discussed in Module 9. FEBA propose some example indicators for After having answered the question whether each of the quality standards and the four catego- the measure qualifies as EbA, the FEBA paper pro- ries (Figure_Anx 1). Indicators should be measur- poses a practical framework that allows users to able, be it in a quantitative or a qualitative way. assess the quality of the EbA initiative by draw- The assessment framework not only helps you ing on a set of quality standards, which are each determine whether a strategy is weak or strong in linked directly to one of the five qualification cri- terms of EbA quality, but also provides a baseline Figure_Anx 1: Example assessment framework of EbA quality standards for Element A ‘helping people to adapt’ and qualification criteria 1 (Source: FEBA 2017) Quali- Quality Continuum of EbA quality fication Stan- Example indicators Criteria dards Very strong Strong Weak Very weak 1.1 Use of Yes, short-, Very Extent of information about future climate medium- and limited or climate change used information long-term not at all Quality of climate data sources Reduces social and environmental vulnerabilities 1.2 Use of Yes Very Extent of relevance of local resources local and limited or consulted (individuals, communities, NGOs) traditional not at all Participation of affected natural resource knowledge users during planning process Quality of consultation process 1.3 Taking Yes, clearly Yes, but Extent to which information from VA is into account integrating only mar- being considered findings of findings of cli- ginally Consideration of climate risk reduction vulnerability mate change Extent to which ecosystem services are assessement vulnerability assessed by the VA assessements 1.4 Vulner- Land/sea- Local Number or percentage of population ability scape scale scale with reduced vulnerability reduction at or larger Effects from different scales of the appro- ecosystems are considered priate scale 90 VI A N N E X on how an EbA approach can be improved. Thus ing an EbA priority areas map to support spatial the framework can be applied during Module 9 of planning for measures and maximise potential this Guidebook when initially planning EbA op- benefits. EbA options presented include manag- tions. Additionally, it provides a tool that is use- ing and restoring wetlands and river corridors ful both during the implementation and during for biological diversity and the prevention of the monitoring and evaluation (M&E) of the EbA soil erosion, restoring wetlands and terrestrial measure. vegetation to secure groundwater recharge, and conserving water catchments for key ecosystem services delivery and to build climate change re- Additional sources where EbA meas- silience. ures are presented https://www.conservation.org/publications/ Documents/CI-CASCADE-Namakwa-Vulnera- This section provides an overview of addi- bility-Assessment.pdf tional online and literature sources where EbA measures are presented and discussed, organised Asia by continent. It should be noted that many of the reports listed here draw on older conceptual GIZ (2015). Pre-selection and Preparation of framings of vulnerability and risk under the IPCC Ecosystem-based Measures in the Pilot Areas Huai AR4 (IPCC 2007) or AR5 (IPCC 2014), rather than Sai Bat and Tha Di (Thailand) for discussion and the adapted AR5 risk concept in the context of final decision-making in collaboration with local social-ecological systems (SES) presented in this water committees. GIZ. Guidebook. The section provides only examples Final design and implementation of ecosys- without being exhaustive. See Table_Anx 2 for on- tem-based measures requires a careful preselec- line database sources. tion of potential measures and locations all of which are based on results of a vulnerability as- Literature sources sessment (VA). This report contains an overview about general EbA options suitable for imple- Africa mentation in the pilot areas from which potential locations associated with measures are derived. Bourne et al. (2012). Climate Change Vulnera- http://www.ecoswat-thailand.com/down- bility Assessment for the Namakwa District Munic- load/2015_05_25_ecoswat_eba_preselectionre- ipality. Conservation International, South Africa. port.pdf This vulnerability assessment addresses cli- mate change risks and impacts, identifies priori- Mant et al. (2014). Opportunities for using cli- ties areas for EbA and conservation actions, and mate change mitigation and adaptation measures makes recommendations for EbA actions. The to make progress towards the CBD Aichi Biodiversi- report includes two prioritisation tools, includ- ty Targets: Guangxi Province, China. UNEP-WCMC. 91 VI A N N E X This report examines opportunities for for- climate change in selected regions of Kyrgyzstan est-based climate change mitigation and adapta- and Tajikistan. Identified measures included tion in Guangxi Zhuang Autonomous Region in floodplain forests and brush land with patches southern China. It provides information on how of wet meadows, forests of steep tributary valleys, spatial analyses can contribute to identifying the and pastures and hay meadows. best areas to implement potential measures. For- Baig et al. (2016). Cost and Benefits of Ecosys- est management options include, for example, tem Based Adaptation: The Case of the Philippines. conservation of existing forests, establishing pro- IUCN. tected areas, and undertaking reforestation. This report aims to increase the knowledge https://www.uncclearn.org/sites/default/files/ base regarding the effectiveness of EbA in order inventory/12052015unepchi2.pdf to enhance information-based decisions. It as- serts that assessing the costs and benefits of EbA Adhikari, B.R. and Suwal, M.K. (2013). Hydro- options helps highlight the potential benefits of geological Study in Bangsing Deurali VDC, Syang- conservation, restoration, and sustainable man- ja: An Ecosystem-based Adaptation in Mountain agement. Examples from the Philippines include Ecosystem in Nepal. IUCN. mangrove ecosystem restoration, the creation This study attempts to understand the effects and management of marine sanctuaries, and cor- of hydrogeological factors on the recharge of the al reef and wetland management. springs of Bangsing Deurali VDC of Syangja dis- https://portals.iucn.org/library/sites/library/ trict in Nepal in order to develop feasible options files/documents/2016-009.pdf for rational use of water available and EbA op- tions for sustainable water supply of springs and watersheds. Measures such as retention ponds are Australia/Oceania explored. Mataki et al. (2013). Choiseul Province climate https://www.iucn.org/sites/dev/files/content/ change vulnerability and adaptation assessment re- documents/hydrogeological_study_in_bangsing_ port: securing the future of Lauru now. SPC/GIZ/SPREP. deurali_vdc_syangja.pdf The report stresses the importance of eco- system services for the adaptive capacity of the Etzold, J. (2015). Ecosystem-based Adapta- province at community levels. It details how wa- tion in Central Asia: Vulnerability of High Moun- ter catchment management is an important EbA tain Ecosystems to Climate Change in Tajikistan’s response to address watershed degradation that Bartang Valley – Ecological, Social and Economic has led to an increase in flooding events. Coast- Aspects – with references to the project region in al vegetation, such as mangrove ecosystems, are Kyrgyzstan. GIZ. presented as key measures in coastal protection This report is part of a project that aims to and disaster risk reduction. Additional EbA meas- identify and establish adaptation measures to ures addressed include management of tidal wet- 92 VI A N N E X land systems for coastal defense, management of areas: inland waters, coastal zone, agriculture and slope vegetation for landslide risk, and the estab- forestry, and cities with examples of EbA meas- lishment of diverse agricultural and agroforestry ures including river restoration, sand nourish- systems in agricultural land. ment, and dune restoration. https://www.weadapt.org/sites/weadapt.org/files/ https://www.bfn.de/fileadmin/MDB/documents/ legacy-new/placemarks/files/52d3d4b75546achoiseul- service/Skript_306.pdf vulnerability-assessment.pdf South America Franco et al. (2017). Application of Cost-Ben- efit Analysis to Ecosystem based Adaptation (EbA) Dourojeanni et al. (2016). Vulnerability Assess- solutions for climate change: final results. The Na- ments for Ecosystem-based Adaptation: Lessons from ture Conservancy. the Nor Yauyos Cochas Landscape Reserve in Peru. In: This report details how cost-benefit analysis Salzmann N., Huggel C., Nussbaumer S., Ziervogel G. can be applied to evaluate EbA options. Included (eds) Climate Change Adaptation Strategies – An Up- are some options identified during a project in stream-downstream Perspective. Springer. Micronesia and Melanesia to help communities This study compares three different vulner- and ecosystems adapt to climate change in low ability assessment approaches, which were car- lying atoll islands and high islands watersheds. ried out simultaneously in the same location in Possible EbA measures identified by communities Peru. All three sought to identify appropriate EbA included green buffer strips, shoreline revegeta- measures based on ecological and social vulnera- tion, coral reef conservation, sea grasses restora- bilities. Selected measures included community- tion, giant clam gardening, etc. based grassland management, domestic livestock husbandry, and conservation and management Europe of upper micro-watersheds, wetlands and water- courses. Doswald, N. and Otsi, M. (2011). Ecosystem- based approaches to adaptation and mitigation - good practice examples and lessons learned in Online database sources Europe. Bundesamt fur Naturschutz (BfN) - Federal Agency for Nature Conservation. Table_Anx 2 provides a selection of open sources This report explores good practice exam- where ecosystem-based adaptation and related ples of ecosystem-based approaches to climate examples from around the globe are presented. change mitigation and adaptation in Europe. The study compiled 101 case studies, including 49 EbA examples, with the majority coming from the United Kingdom, Germany, and the Netherlands. These case studies were divided into the following 93 VI Table_Anx 2: Sources of online databases containing EbA measures A N N Title/geographic Description/web link E range of measures X Database on ecosystem- This is an initiative under the Nairobi work programme to provide examples of ecosystem- based approaches to based approaches to adaptation, supplementing information to FCCC/SBSTA/2011/INF.8, Adaptation (UNFCCC) mandated by the SBSTA at its thirty-fourth session under the Nairobi work programme. Global http://www4.unfccc.int/sites/NWP/Pages/ecosystems-page.aspx Climate Change Adapta- The database provides web-based guidance on the integration of biodiversity within tion Database – adaptation planning. It gathers information tools and case studies from a number of relevant Integrating Biodiversity partners. It provides links to scientific studies and other resources on biodiversity-related into Climate Change Ad- climate change adaptation. These examples can assist managers and governments to find aptation Planning (CBD) adaptation options that will not have a negative impact on biodiversity. Global https://adaptation.cbd.int/options.shtml#sec1 WOCAT Global Database The Global Database on Sustainable Land Management (SLM) of WOCAT (the World on Sustainable Land Overview of Conservation Approaches and Technologies) provides free access to the Management (UNCCD) documentation of field-tested SLM practices – many of which are relevant for climate change adaptation. An SLM practice can be either an SLM Technology (a physical practice Global that controls land degradation and/or enhances productivity, consisting of one or several measures) or an SLM Approach (ways and means used to implement one or several SLM Technologies, including technical and material support, stakeholder engagement, and other). https://qcat.wocat.net/en/wocat/ PANORAMA – Solutions This is an interactive platform and database of specific, applied examples of successful NBS, for a healthy planet (GIZ, EbA and Eco-DRR processes or approaches structured according to regions, ecosystems, IUCN, UN Environment, specific thematic areas, governance and hazards addressed. It is useful for identifying different GRID Arendal, Rare) targets (Aichi, Sendai Framework, SDGs, NDC) and outlining challenges. Global http://panorama.solutions/en/portal/ecosystem-based-adaptation Natural Water NWRM cover a wide range of actions and land use types. Many different measures can act Retention Measures as NWRM by encouraging the retention of water within a catchment and, through that, catalogue (EU) enhancing the natural functioning of the catchment. The catalogue of measures is sorted by sector. It has been developed in the NWRM project, representing a comprehensive but Europe non prescriptive wide range of measures. http://nwrm.eu/measures-catalogue Adaptation Solutions The portal brings the story of climate change in the Hindu Kush Himalaya to life, mapping Portal (ICIMOD, climate change impacts through hazards (floods, droughts, heat, fire, landslides) for the whole Hi-AWARE, CAS) region. It exchanges local solutions from different river basins to increase adaptive capacity. Hindukush & Himalaya http://www.cas-platform.com/hi-aware/ Region Naturally resilient This database allows to explore over 50 solutions and case studies on nature-based solutions communities and included case studies of successful projects from across the US to help communities learn (US National Planning more and identify which nature-based solutions might work for them. The explorer allows to Association) filter by cost, region, hazards, and more. North America http://nrcsolutions.org/ 94 VI A N N Application E X example 2: Adaptation to salinity Description of the coastal area including social- intrusion in low elevation ecological features: coastal zones The region is characterised by a tropical, This annex provides a second application ex- monsoonal climate with temperatures ranging ample of how the Guidebook approach can be from an average low of 20 °C to an average high applied. The case study presents a coastal area, of 33 °C. During the rainy season from May to including a river delta, experiencing high risk for November, the area experiences monthly rainfall the loss of agricultural livelihoods due to salinity between 200 mm and 350 mm, whereas during intrusion. the dry season from December to April, monthly Figure_Anx 2: Land use along the coastline Districts Rivers Settlements Cropland (irrigated) Cropland (rainfed) Grassland Mosaic herbaceous cover Mosaic natural cover Shrubland (evergreen) Forest Mangroves 95 VI A N N E X average rainfall ranges from 10 mm to 100 mm. tion or degradation of soils and wetlands. The average annual humidity is 80% and the rain- The districts located by the sea (district 1, 2, 8, 9, fall 1,600 mm. The long coastline has a length of 10 and 18) are partly covered by mangrove forests 200 km and approximately 6.5 million people are along the coastline. Those forests are essential for living in the study area, which is sub-divided into shoreline protection and provide important eco- 18 administrative districts (Figure_Anx 2). system services for the region. Yet, mangroves are The coastal area is characterised by a river severely threatened due to the increasing demand delta with fertile soils, which is mainly covered for farmland and aquaculture. The conversion of by croplands. Approximately 60% of the GDP is wetlands and forests triggers erosion, threaten- generated from agricultural products and fishing. ing existing farmlands. The area is characterised Some districts face high poverty rates and rely by intensive agriculture, mainly consisting of ir- heavily on income from agriculture as they lack rigated croplands, with a few extents of natural other types of economic opportunities. vegetation, in particular natural forests, shrubs and herbaceous cover. The remaining mangrove Adaptation challenges: forests are protected, but have severely decreased in extent within the last decades. Wetlands along As a low-lying coastal region, the region is the river have been degraded, and the river bed particularly susceptible to salt-water intrusion and delta have been modified to generate addi- resulting from a combination of sea level rise and tional space for farmland, which has led to de- land subsidence due to groundwater extraction. creased retention capacity and higher flood levels In the dry season and during times of drought, a during the wet season. In general, the remaining deficit in rainfall in the basin results in low river ecosystems in the study area are poorly managed flows contributing to increased duration and and do not contribute to a reduction of risk. levels of salinity intrusion. Additionally, during Most farmers are not trained in land manage- drought periods demand for irrigation water in- ment, which leads to an increased risk of soil deg- creases, as less water is stored in fields. Due to in- radation. Climate change puts increasing pres- tensified agricultural production and infrastruc- sure on the agriculture-based production system ture development, land has been and continues in the study area. On a communal level, water to be converted to crop land – both upstream and management plans are available to deal with wa- in the coastal zones. Furthermore, groundwater ter scarcity. National support and water manage- is extracted in order to decrease salinity levels of ment plans, however, are lacking. Furthermore, needed water in the short term, which feedbacks the water regime downstream has changed due to into an overexploitation of natural resources in increased upstream development (including land the long term. Increased salinity intrusion is one use changes), increasing irrigation water extrac- of the drivers of land use changes, e.g. the conver- tion and hydropower development. Transbound- sion of rainfed or irrigated crop systems into sa- ary river basin agreements are in place. line aquaculture. This generates several potential environmental problems such as increased pollu- 96 VI A N N E X Module 1 What is the risk of loss of agricultural liveli- hoods due to salinity intrusion in the study Preparing the risk area, and (how) can it be reduced through ad- assessment aptation, including EbA measures? What are potential co-benefits and trade-offs Step 1 associated with EbA options? Understanding the context of a cli- mate risk assessment for adaptation Step 3 Determining the scope At a national level, adaptation to increasing of the assessment salinity intrusion is high up on the political agen- da, but requires a detailed baseline risk assess- The assessment aimed at analysing the risk ment to identify hotspots (in all its dimensions of of loss of agricultural livelihoods in a coastal hazard, exposure, and vulnerability) and evaluate zone due to salinity intrusion and at identifying social-ecological conditions. For this particular suitable adaptation (including EbA) measures. It region, this was the first climate risk assessment focused on two risk factors contributing to in- being conducted. It was expected that salinity in- creased duration and levels of salinity intrusion: trusion would continue to increase due to chang- the hazard of increasing rainfall deficits in the ba- es in precipitation, fluctuations in river flows and sin resulting in low river flows during dry season rising sea levels combined with land subsidence. and times of drought; and a higher sensitivity of This required the planning of adaptation meas- the population due to increasing demand for ir- ures to prevent crop failure and loss of livelihoods. rigation water during drought periods, when less The high dependency of local communities as water is stored in fields. well as national food security on rainfed and ir- The assessment covered all 18 districts in the rigated agriculture makes adaptation to changing study area and focused on current risks. salinity levels imperative. Amongst the key actors are the Department of Water Management and Step 4 Environment at the district level, the National Ministry of Agriculture, as well as representatives Preparing an from affected communities. implementation plan It was decided that local stakeholders ought to Step 2 be included in the assessment (in order to be able Identifying objectives and to draw on local knowledge and create ownership of the process), that an international develop- expected outcomes ment agency working with local experts would be The assessment aimed at providing answers coordinating the process, and that local universi- to the following key questions: ties would give input and help with data collec- 97 VI A N N E X tion (qualitative and quantitative). Participatory approaches were to be used to identify local per- Module 2 ceptions of climate risks and existing adaptation Developing impact practices to increased salinity intrusion. All stake- chains holders within the region were to be included with a special focus on farmers and landowners, and further measurements undertaken throughout the Step 1 year to determine the extent of salinity intrusion Identify potential climate impacts in both wet and dry season. The risk assessment and risks should be completed after 18 months, revealing Loss of agricultural livelihoods due to salinity potential risk hotspots and suitable sites for (eco- was identified as the main risk. system-based) adaptation measures. Step 2 Determine hazard(s) and intermediate impacts The key hazard – deficit in rainfall in the basin, leading to reduced water flows, sinking ground- water tables, reduced water storage in the field and increased irrigation needs – was added to the impact chain (Figure_Anx 3). It was concluded that contribution of relative sea level rise to this process is minor to date, but will likely exacerbate in the future. Step 3 Determine the vulnerability of the social-ecological system Relevant factors determining the vulner- ability of the social-ecological system (SES) were identified. As shown in Figure_Anx 4, the factors determining vulnerability affect the intermediate impacts and the overall risk of loss of agricultural livelihoods due to salinity. A loss of the ecosystem 98 VI A N N E X services ‘retention capacity’ and ‘groundwater Step 4 recharge capacity’, for example, leads to lowered Determine exposed elements ground water tables. The loss of these services is of the social-ecological system caused by a combination of social and ecological changes, such as land conversion and soil degra- Exposure of relevant elements of the social- dation driven by e.g. lack of knowledge of land ecological system to salinity intrusion was evalu- conservation or lack of land tenure. For example, ated, with the exposed elements at risk being stakeholders highlighted that agricultural inten- salinity sensitive agricultural land and farmers sification in the study area has led to a degrada- whose livelihoods are affected (Figure_Anx 5). tion of land and soil with impacts on natural groundwater recharge capacity. Figure_Anx 3: Impact chain with intermediate impacts and hazard factors identified Hazard Intermediate Impacts Deficit in Lowered ground rainfall water table Reduced water storage in field Relative sea level rise Increased irriga- tion needs Reduced low flows of surface water Increased duration and level of high salinity Exposure Vulnerability Risk Risk of loss of agricultural livelihoods due to salinity 99 100 N N A X E VI Vulnerability Figure_Anx 4: Impact chain with vulnerability factors added, including ecological and social sensitivity and capacity Population growth & socioeconomic Reduced transformation natural Land/soil too retention degraded capacity Hazard Intermediate Impacts Eco- Lacking knowledge Deficit in Lowered ground on land conservation rainfall water table system services Land not owned Agricultural Reduced water by farmers intensification storage in field Reduced Relative sea natural level rise Increased irriga- ground- tion needs water Land conversion recharge from natural Infrastructure capacity systems upstream development and in delta Altered natural Reduced low flows of river flow surface water Lacking Too strong depend- enforcement of Lack of national Increased duration and ency on agricultural regulations land use policy level of high salinity income Exposure Lack of early warning system Lack of water Lack of management in the transboundary river delta management Poverty Risk Risk of loss of agricultural livelihoods due to salinity Risk Climate Intermediate Sensitivity Sensitivity Capacity Signal Impact Ecological Socio-economic Vulnerability Population growth & socioeconomic Reduced transformation natural Land/soil too retention degraded capacity Hazard Intermediate Impacts Eco- Lacking knowledge Deficit in Lowered ground on land conservation water table system Figure_Anx 5: Impact chain with exposure added rainfall services Land not owned Agricultural Reduced water by farmers intensification storage in field Reduced Relative sea natural level rise Increased irriga- ground- tion needs Land conversion water recharge from natural Infrastructure capacity systems upstream development and in delta Altered natural Reduced low flows of river flow surface water Lacking Too strong depend- enforcement of Lack of national Increased duration and ency on agricultural regulations land use policy level of high salinity income Exposure Lack of early Exposed salinity sensitive warning system agricultural land Lack of water Lack of management in the transboundary river delta management Poverty Exposed farmers Risk Risk of loss of agricultural livelihoods due to salinity Risk Climate Intermedi- Exposure Sensitivity Sensitivity Capacity Signal ate Impact Ecological Socio-economic 101 VI N N A X E 102 N N A X E VI Vulnerability Figure_Anx 6: Entry points for adaptation practitioners and planners working on natural resource conservation Population growth & socioeconomic Reduced transformation natural Land/soil too retention degraded capacity Hazard Intermediate Impacts Eco- Lacking knowledge Deficit in Lowered ground on land conservation rainfall water table system services Land not owned Agricultural and management (green coloured boxes) Reduced water by farmers intensification storage in field Reduced Relative sea natural level rise Increased irriga- ground- tion needs water Land conversion recharge from natural Infrastructure capacity systems upstream development and in delta Altered natural Reduced low flows of river flow surface water Lacking Too strong depend- enforcement of Lack of national Increased duration and ency on agricultural regulations land use policy level of high salinity income Exposure Lack of early Exposed salinity sensitive warning system agricultural land Lack of water Lack of management in the transboundary river delta management Poverty Exposed farmers Risk Risk of loss of agricultural livelihoods due to salinity Risk Climate Intermedi- Exposure Sensitivity Sensitivity Capacity Signal ate Impact Ecological Socio-economic VI A N N E X After the identification of hazard, exposure ic sensitivity and capacity, can be entry points for and vulnerability factors, entry points for (ecosys- the identification of adaptation measures. tem-based) adaptation measures or ‘adaptation Table_Anx 3 and Figure_Anx 7 present po- packages’ (see Module 9) were identified by the tential adaptation options, both EbA and con- participants. Figure_Anx 6 highlights elements ventional, which in turn comprise soft (e.g. rais- of the impact chain that could potentially be tar- ing awareness for sustainable land management geted by adaptation measures. Factors related to practices) and hard/engineering-based approach- ecological sensitivity, as well as to socio-econom- es (e.g. construction of a sea wall). Table_Anx 3: Ecosystem-based (green dots) and conventional (blue dots) adaptation options Ecosystem-based adaptation options Conventional adaptation options 1 Wetland restoration Construct reservoirs 2 Floodplain restoration & reconnection Construction of a sea wall 3 Protection/restoration of forests upstream Separate freshwater and brackish water zones with sluice gates 4 Protection/restoration of coastal vegetation Artificial groundwater recharge during the rainy (incl. mangroves) season 5 Reconnect lower estuary ecosystem incl. salt Change the crop to more saline tolerant crops incl. marches halophytes 6 Diversify agricultural system to maintain genetic Bring fresh river water to saline region: divert diversity of crops and increase robustness against water from upstream to downstream (large scale uncertain salinity conditions infrastructure measure for water diversion) 7 Improve soil quality incl. methods of soil conser- Establish irrigation procedures that help to vation, land preparation maintain high soil moisture and wash out the soil salinity periodically 103 104 N N A X E VI Vulnerability Population growth 1 & socioeconomic Reduced 1 7 transformation natural Land/soil too Figure_Anx 7: Visualisation of potential adaptation measures (incl. EbA measures) in the impact chain retention degraded capacity Intermediate Eco- Lacking knowledge Hazard system Impacts 4 2 on land conservation Deficit in Lowered ground services water table Land not owned Agricultural rainfall by farmers intensification 4 2 Reduced water Reduced storage in field natural 3 4 ground- water Land conversion Relative sea Increased irriga- recharge from natural Infrastructure level rise tion needs capacity systems upstream development and in delta 7 6 Altered natural Reduced low flows of river flow surface water Lacking Too strong depend- enforcement of Lack of national ency on agricultural regulations land use policy Increased duration and income level of high salinity Lack of early 3 2 5 Exposure warning system Lack of water Lack of 2 5 6 management in the transboundary river Exposed salinity sensitive Poverty delta management agricultural land Exposed Ecosystem-based adaptation options Conventional adaptation option farmers Risk Risk of loss of agricultural livelihoods due to salinity Risk Climate Intermedi- Exposure Sensitivity Sensitivity Capacity Signal ate Impact Ecological Socio-economic VI A N Module 3 application example it increases risk, as it reveals a strong dependency on agricultural income and N E Identifying and thus in turn potentially high losses due to salinity X selecting indicators for intrusion. Figure_Anx 8 shows the impact chain with indicators for the hazard, exposure and vul- risk components nerability components. Step 1 Step 3 Selecting indicators for hazards Checking if the indicators Following the Guidebook approach, one indi- are specific enough cator was identified for each factor in the impact As outlined in the Guidebook, it is important chain. The number of days with precipitation be- that every indicator has a clear direction with a low a critical relevant threshold is an important determined negative or positive contribution to factor partly determining the agricultural produc- risk and is precisely measurable. The ‘percent- tivity in the study area. Local experts and farmers age of mangroves deforested’ can be measured had to be consulted in order to define a locally rele- and monitored continuously with satellite data, vant threshold for rainfall per day. In the dry season, whereas the indicator ‘lack of transboundary river there are sometimes several weeks without rainfall. management’ is a process of policy negotiations Although the region is adapted to dry season con- and is valid for the whole region, equally contrib- ditions, a late onset of the rainy season or a too early uting to the vulnerability and risk of each district. start of the dry season leads to an increase of salin- Spatial resolution and precise data at local level ity levels. For salinity levels, the indicators ‘percent- remains a key challenge for the determination age of area with salinity > 4 g/l’ and the ‘number of of some indicators, e.g. the corruption index, as days with salinity > 4 g/l’ were identified. data is only available at national level. Here expert judgement can help to acquire information on corruption levels across the 18 districts. Step 2 Selecting indicators for vulnerability and exposure Step 4 Following the identification of hazard indi- Creating a list of provisional cators, indicators for vulnerability and exposure indicators for each factor factors were selected according to Module 2. It Next all indicators were listed in a table, in- was decided to use a variety of different indicators cluding the unit of measurement, as well as their targeting environmental and societal aspects, as direction in relation to risk (Table_Anx 4). well as indicators directly referring to agriculture and land use, according to the setting of the case study. Some indicators, for example ‘percent- age of the contribution of agriculture to national GDP’, might be perceived in another context as a positive development for the region, but in the 105 106 N N A X E VI Hazard Intermediate Vulnerability Cation exchange Impacts capacity (cmol/kg) Deficit in Lowered ground Population growth Organic carbon rainfall water table & socioeconomic content (g/kg) No. of days with pre- transformation Reduced Land/soil too cipitation below local Reduced water natural degraded relevant threshold storage in field retention % of farmers capacity trained in land Increased irriga- Lacking knowledge management tion needs on land conservation Relative sea Eco- level rise % of farmers without system an official land title Reduced low flows of services Land not owned Agricultural Figure_Anx 8: Impact chain with indicators surface water by farmers intensification Reduced natural % of natural % of mangroves Increased duration and ground- wetlands drained deforested level of high salinity water recharge Land conversion Infrastructure “% of area No. of days capacity from natural development with salinity with salinity systems upstream > 4 g/L > 4 g/L and in delta Altered natural river flow Ratification of land % of river length Corruption use policy (yes/no) unmodified % contribution index Lacking Exposure of agriculture enforcement Lack of national Too strong depen- to GDP of regulations land use policy dency on agricultural income Exposed salinity sensitive Availability and level of agricultural land transboundary river basin Lack of early agreements (yes/partly/no) % farmers who Lack of water Number of farmers per km2 warning system in area with high salinity have received EW management in Lack of messages before the delta transboundary river management Poverty % population below the Groundwater utili- Exposed zation m3/day national poverty line farmers Km2 of cropland in area Risk of loss of agricultural with high slinity Risk Climate Intermedi- Exposure Sensitivity Sensitivity livelihoods due to salinity Risk Capacity Indicator Signal ate Impact Ecological Socio-economic Table_Anx 4: Indicators for each risk component (hazard, exposure and vulnerability) with increasing tendency (+) VI and decreasing tendency (-) A N N Component Factor Indicator Direction E X Hazard Deficit in rainfall Number of days with precipitation below local + relevant threshold per year Exposure Exposed farmers Number of farmers per km² in area with + high salinity Exposed salinity sensitive Km² of cropland in area with high salinity + agricultural land Vulnerability Land/soil too degraded Organic carbon content (g/kg) - Cation exchange capacity (cmol/kg) - Land conversion from natural Percentage of natural wetlands drained + systems upstream and in delta Land conversion from natural Percentage of mangroves deforested + systems upstream and in delta Altered natural river flow Percentage of river length unmodified - Lacking knowledge of land Percentage of farmers trained in land - conservation management Land not owned by farmers Percentage of farmers without an official + land title Too strong dependency on Percentage of contribution of agriculture to GDP + agricultural income Lack of early warning systems Percentage of farmers who have received - early warning (EW) messages before Poverty Percentage of population below national + poverty line Lacking enforcement Corruption index - of regulation (1-5 with 1-very low, 5-very high) Lack of national land use Ratification of land use policy - policy (yes/no) Lack of transboundary river Availability and level (binding or voluntary) - basin agreements of transboundary river basin agreements (3-available and legally binding, 2-available but non-binding, 1-not available) Lack of water management Groundwater utilisation (m³/day) - in the delta 107 VI A N N E X Module 4 sure of farmers and agricultural land to salinity was determined by means of spatial analysis in a Data acquisition and Geographic Information System (GIS), combining management spatial data representing areas affected by salinity > 4g/l and data on land use/land cover and grid- ded (i.e. pixel-based) population data obtained The measurement and data collection might from global data repositories. differ significantly depending on the specific in- Table_Anx 5 shows the attribute values of dicator. As the risk assessment within the context each indicator per district. of EbA aims at a spatially explicit output, georef- erenced data was considered to be particularly useful. It can be pixel-based information or ref- erenced to administrative areas. For baseline in- formation about the region, geographic, environ- mental, climatic, socio-economic and spatial data was collected. Baseline geographic data for the application example includes administrative data about the districts, current land use, water bodies, information on soil properties and the extent and level of salinity. Socio-economic data marks an important component as well as including census data, poverty estimations or education levels. For the hazard component, precipitation data was ob- tained from local weather stations. Accordingly, data was acquired from mete- orological offices, regional statistics offices, min- istries and municipalities, regional research in- stitutes/universities or publically accessible data portals providing geographic data and satellite images. Collecting data on district level not older than two years is sometimes very challenging and cannot be achieved for all factors. For example, census data is not provided every year, but in in- tervals of five to ten years. Even though data might not be as spatially differentiated or not available for the requested time period, it can still reveal regional differences in the study area or historic changes of certain factors. In this example, expo- 108 Table_Anx 5 : Raw data for the different indicators (excl. intermediate impacts) – attributes for each district (D1-D18) Component Factor Indicator D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 D16 D17 D18 Hazard Deficit in rainfall Number of days with precipitation be- 24 22 24 19 18 19 22 16 23 24 23 17 18 20 19 21 21 22 low local relevant threshold per year Exposure Exposed farmers Number of farmers per km² in area 68,729 55,449 73,969 37,796 0 3,970 2,825 62,085 70,674 43,763 49,080 0 0 4,025 6,745 28,644 13,264 41,232 with high salinity Exposed salinity sensitive Km² of cropland in area with high 960 760 770 320 0 25 35 470 710 540 310 0 0 120 45 150 215 650 agricultural land salinity Vulne- Land/soil too degraded Organic carbon content (g/kg) 183 138 210 126 57 62 48 72 68 64 60 75 55 83 70 70 51 61 rability Cation exchange capacity (cmol/kg) 60 61 63 62 57 55 56 58 60 57 57 56 58 58 61 57 54 56 Land conversion from natural Percentage of natural wetlands 15 9 8 14 7 7 4 8 11 10 9 8 7 8 7 7 8 10 systems upstream and in delta drained Land conversion from natural Percentage of mangroves deforested 21 12 0 0 0 0 0 9 11 16 5 2 1 4 3 5 8 18 systems upstream and in delta Altered natural river flow Percentage of river length unmodified 89 87 98 96 97 98 97 97 90 66 71 75 78 55 76 79 61 92 Lacking knowledge of land Percentage of farmers trained in land 22 18 20 15 17 21 24 19 18 21 19 20 18 16 14 17 19 16 conservation management Land not owned by farmers Percentage of farmers without an 45 55 38 35 37 36 36 51 48 39 37 31 42 38 32 52 36 53 official land title Too strong dependency on Percentage of contribution of 52 55 66 44 63 48 47 59 62 61 46 56 54 58 65 63 59 66 agricultural income agriculture to GDP Lack of early warning systems Percentage of farmers who have 45 31 36 25 34 38 42 31 34 28 43 39 36 27 32 34 31 26 received EW messages before Poverty Percentage of population below the 20 15 15 10 10 10 15 20 20 20 20 23 10 10 10 15 15 20 national poverty line Lacking enforcement of regulation Corruption index (1-5 with 1-very 3 4 3 2 4 5 4 3 2 4 4 4 3 2 2 3 3 2 low, 5-very high) Lack of national land use policy Ratification of land use policy (yes/no) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Lack of transboundary river Availability and level of transboundary 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 basin agreements river basin agreements Lack of water management in Groundwater utilisation (m³/day) 135 63 135 63 50 50 95 63 95 95 95 50 11 11 142 142 142 142 the delta 109 VI N N A X E VI A N N E Module 5 Step 2 Normalising the indicator X Normalisation values of indicator data After clarifying the direction of each indica- tor, data was transformed into a standardised Step 1 score between 0 to 1 by applying thresholds rep- Determining the scale of resenting optimal and critical states for each in- measurement dicator. Table_Anx 6 shows for each indicator the direction, the minimum and maximum value of After data acquisition it was found that the the data and the defined threshold, as identified majority of the indicators can be measured in by the workshop participants. The results of the metric values. normalisation step are displayed in Table_Anx 7. Table_Anx 6: Direction, min-max values and defined thresholds for each indicator Indicator Direction Min Max Thresold Thresold (min) (max) Number of days with precipitation below + 16 24 7 28 local relevant threshold per year Km² of cropland in area with high salinity + 0 960 0 1000 Organic carbon content (g/kg) - 48 210 0 450 Cation exchange capacity (cmol(kg) - 54 63 0 240 Percentage of natural wetlands drained + 4 15 0 25 Percentage of mangroves deforested + 0 21 0 25 Percentage of river length unmodified - 55 98 0 100 Percentage of farmers trained in land management - 14 24 0 100 Percentage of farmers without an official land title + 31 55 0 100 Percentage of contribution of agriculture to GDP + 44 66 25 75 Percentage of municipalities with participation in planning process - 25 45 0 100 Percentage of population with income below the national poverty line + 10 23 0 30 Corruption index (1-5 with 1-very low, 5-very high) - 2 1 5 5 Ratification of land use policy (yes/no) - 0 0 0 1 Availability and level (binding or voluntary) of transboundary river basin agreements - 2 2 1 3 (3-available and legally binding, 2-available but non-binding, 1-not available) Groundwater utilisation (m³/day) - 11 142 0 140 110 Table_Anx 7: Normalised data for the different indicators (excl. intermediate impacts) – attributes for each district (D1-D18) Component Factor Indicator D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 D16 D17 D18 Hazard Deficit in rainfall Number of days with precipitation be- 0.81 0.71 0.81 0.57 0.52 0.57 0.71 0.43 0.76 0.81 0.76 0.48 0.54 0.62 0.57 0.67 0.67 0.71 low local relevant threshold per year Exposure Exposed farmers Number of farmers per km² in area 0.98 0.79 1.00 0.54 0.00 0.06 0.04 0.89 1.00 0.63 0.70 0.00 0.00 0.06 0.10 0.41 0.19 0.59 with high salinity Exposed salinity sensitive Km² of cropland in area with high 0.96 0.76 0.77 0.32 0.00 0.03 0.04 0.77 0.71 0.54 0.31 0.00 0.00 0.12 0.05 0.15 0.22 0.65 agricultural land salinity Vulne- Land/soil too degraded Organic carbon content (g/kg) 0.59 0.69 0.53 0.72 0.87 0.86 0.89 0.84 0.85 0.86 0.87 0.83 0.88 0.82 0.84 0.84 0.89 0.86 rability Cation exchange capacity (cmol/kg) 0.75 0.75 0.74 0.74 0.76 0.77 0.77 0.76 0.75 0.76 0.76 0.77 0.76 0.76 0.75 0.76 0.78 0.77 Land conversion from natural Percentage of natural wetlands 0.60 0.36 0.32 0.56 0.28 0.28 0.16 0.32 0.44 0.40 0.36 0.32 0.28 0.32 0.28 0.28 0.32 0.40 systems upstream and in delta drained Land conversion from natural Percentage of mangroves deforested 0.84 0.48 0.00 0.00 0.00 0.00 0.00 0.36 0.44 0.64 0.20 0.08 0.04 0.16 0.12 0.20 0.32 0.72 systems upstream and in delta Altered natural river flow Percentage of river length unmodified 0.11 0.13 0.02 0.04 0.03 0.02 0.03 0.03 0.10 0.34 0.29 0.25 0.22 0.45 0.24 0.21 0.39 0.08 Lacking knowledge of land Percentage of farmers trained in land 0.78 0.82 0.80 0.85 0.83 0.79 0.76 0.81 0.82 0.79 0.81 0.80 0.82 0.84 0.86 0.83 0.81 0.84 conservation management Land not owned by farmers Percentage of farmers without an 0.45 0.55 0.38 0.35 0.37 0.36 0.36 0.51 0.48 0.39 0.37 0.31 0.42 0.38 0.32 0.52 0.36 0.53 official land title Too strong dependency on Percentage of contribution of 0.54 0.60 0.82 0.38 0.76 0.46 0.44 0.68 0.74 0.72 0.42 0.62 0.58 0.66 0.80 0.76 0.68 0.82 agricultural income agriculture to GDP Lack of early warning systems Percentage of farmers who have 0.55 0.69 0.54 0.75 0.66 0.62 0.58 0.69 0.66 0.72 0.57 0.61 0.64 0.73 0.68 0.66 0.69 0.74 rseceived EW messages before Poverty Percentage of population below the 0.67 0.50 0.50 0.33 0.33 0.33 0.50 0.67 0.67 0.67 0.67 0.77 0.33 0.33 0.33 0.50 0.50 0.67 national poverty line Lacking enforcement of regulation Corruption index (1-5 with 1-very 0.50 0.25 0.50 0.75 0.25 0.00 0.25 0.50 0.75 0.25 0.25 0.25 0.50 0.75 0.75 0.50 0.50 0.75 low, 5-very high) Lack of national land use policy Ratification of land use policy (yes/no) 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Lack of transboundary river Availability and level of transboundary 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 basin agreements river basin agreements Lack of water management in Groundwater utilisation (m³/day) 0.04 0.55 0.04 0.55 0.64 0.64 0.32 0.55 0.32 0.32 0.32 0.64 0.92 0.92 0.00 0.00 0.00 0.00 the delta 111 VI N N A X E VI A N N E Module 6 lowing the approach described in the Guidebook. The results are shown in Table_Anx 8. The maps X Weighting and in Figure_Anx 9 represent these results for the 18 aggregating indicators districts in the study area. Step 1 Weighting indicators Module 7 For the sake of simplicity, it was decided to Aggregating risk apply equal weights for all indicators. components to risk Step 2 The values of the three risk components (haz- Aggregating of indicators ard, exposure, vulnerability) were aggregated into risk values by applying the arithmetic aggrega- Then the normalised indicator values were tion method. The results are shown in Table_Anx aggregated to composite indicators for each 8 as well. These risk values were also visualised in component (hazard, exposure, vulnerability) fol- a map (see Figure_Anx 10). Table_Anx 8: Aggregated indicators (hazard, exposure, vulnerability) and risk scores District Hazard Exposure Vulnerability Risk District 1 0.81 0.97 0.57 0.78 District 2 0.71 0.78 0.56 0.68 District 2 0.81 0.89 0.48 0.73 District 3 0.57 0.43 0.54 0.51 District 4 0.52 0.00 0.52 0.35 District 5 0.57 0.04 0.47 0.36 District 6 0.71 0.04 0.47 0.41 District 7 0.43 0.68 0.59 0.56 District 8 0.76 0.86 0.61 0.74 District 9 0.81 0.58 0.60 0.66 District 10 0.76 0.51 0.53 0.60 District 11 0.48 0.00 0.55 0.34 District 12 0.52 0.00 0.56 0.36 District 13 0.62 0.09 0.62 0.44 District 14 0.57 0.07 0.53 0.39 District 15 0.67 0.28 0.54 0.50 District 16 0.67 0.20 0.55 0.47 District 17 0.71 0.62 0.62 0.65 District 18 0.81 0.97 0.57 0.78 112 VI Figure_Anx 9: Visualisation of aggregated hazard, exposure and vulnerability component A N Hazard N E 0.43 - 0.60 (medium) X 0.61 - 0.80 (high) 0.81 - 0.82 (very high) Rivers Districts Exposure 0.00 - 0.20 (very low) 0.21 - 0.40 (low) 0.41 - 0.60 (medium) 0.61 - 0.80 (high) 0.81 - 0.97 (very high) Rivers Districts Vulnerability 0.47 - 0.50 (medium) 0.51 - 0.60 (medium) 0.61 - 0.62 (high) Rivers Districts 113 VI Figure_Anx 10: Aggregated risk components to a composite risk index A N N Risk E X 01 0.34 - 0.40 (low) 0.41 - 0.50 (medium) 02 0.51 - 0.60 (medium) 03 0.61 - 0.70 (high) 08 0.71 - 0.78 (high) 09 04 Rivers 10 07 Districts 18 17 11 06 05 16 14 12 15 13 Module 8 (Module 8) provides further examples of how the results could be visualised to support the Presenting and identification and spatial planning of adapta- interpreting the out- tion options. comes of the risk assessment Module 9 As displayed above, the outcome of the as- Identification of sessment is a map for each component (hazard, vulnerability, exposure; Figure_Anx 9), as well as adaptation (incl. EbA) a risk map (Figure_Anx 10). Not all districts face options the same risk of loss of agricultural livelihoods due to salinity. The risk assessment revealed Based on the impact chain a number of op- that districts with a coastline (districts 1, 2, 8, tions were identified (Table_Anx 3). Figure_Anx 11 9, 10 and 18), but also several interior districts specifies areas within the study area where sug- (districts 3, 7, 11 and 14), are severely affected by gested EbA measures should be implemented to salinity intrusion. However, this does not auto- effectively tackle the risk of salinity intrusion. matically result in high risk values, as the com- Figure_Anx 12 illustrates i) direct adapta- ponents exposure and vulnerability are equally tion benefits, ii) co-benefits, and iii) unintended weighted in the risk assessment. The Guidebook consequences (or potential trade-offs) for the 114 VI A N N E X EbA measure ‘Protection/restoration of coastal sources of food besides agriculture in coastal vegetation (incl. mangroves)’: regions), but also ‘outside’ of the risk compo- nents (e.g. mangrove forests increasing car- Direct adaptation benefits include shoreline bon sequestration will contribute to climate stabilisation and, thus, protection of agri- change mitigation). cultural land and increased ground water As outlined in the Guidebook, potential draw- storage. backs or trade-offs of adaptation measures There are a number of co-benefits affect- must be considered as well (e.g. the loss of ag- ing both factors within the risk components ricultural land due to forest restoration de- (e.g. mangrove forest restoration leads to creases the area of available farmland and increased biodiversity and, in turn, results might lead to further intensification of the in more breeding grounds for birds and fish, agricultural production, because remaining creating additional income and alternative space has to be used more efficiently). Figure_Anx 11: Suggested EbA measures to tackle salinity intrusion risk Districts Restoration of coastal Rivers vegetation Settlements Restoration of Cropland (irrigated) Restoration coastal of coastal vegetation Cropland (rainfed) vegetation Grassland Diversify Mosaic herbaceous cover agricultural system Mosaic natural cover Shrubland (evergreen) Forest Mangroves Floodplain restoration and reconnection 115 116 N N A X E VI Climate Risk Climate change Better Life on Land mitigation (SDG 13) (SDG 15) Good health & Figure_Anx 12: Co-benefits and potential unintended consequences of EbA measures well-being (SDG 3) Hazard Nutrient Vulnerability Population uptake growth & Increased carbon Water socio-eco- Land/soil too sequestration purification nomic trans- degraded Lacking knowledge formation on land conservation Reduced Better water and natural soil quality Climate & Environment retention Land not owned Loss of agri- Intermediate (example: restoration of coastal vegetation) capacity cultural land by farmers Impacts Society & Economy Lowered ground Increased ground Agricultural Deficit in water storage Restoration of water table intensification rainfall Ecosystem coastal vegetation Reduced water services storage in field Reduced Infrastructure Land conversion development natural Relative sea groundwa- from natural level rise Increased irriga- ter recharge systems upstream Better air tion needs capacity and in delta quality Water purification Reduced saltwater Altered natural Lacking Lack of national intrusion river flow enforcement land use policy of regulations Reduced low flows of surface water Reduced erosion Flood control Lack of trans- Lack of water management boundary river Increased duration and in the delta management Too strong de- Coastal level of high salinity protection pendency on agri- Exposure cultural income Wood and timber Exposed salinity sensi- Lack of early tive agricultural land warning system More fish Increased and birds biodiversity Poverty Additional Increased Cultural income tourism services Exposed farmers Risk Risk of loss of agricultural livelihoods due to salinity EbA Direct Co- Drawbacks measure benefits benefits