Published on May 9, 2014
Analytical tools to identify priority actions for climate- resilient communities: A case study SVRK Prabhakar et. al. and Kenta Usui IGES 13 May 2014 Presented at the World Bank Central Asia Climate Knowledge Forum, Almaty Kazakhstan
This presentation is based on the work published in: Prabhakar, S.V.R.K (Ed.). 2014. Adaptation decision making frameworks and tools: Multi-criteria decision making tools for prioritizing adaptation actions at community level Hayama, Japan: Institute for Global Environmental Strategies. http://pub.iges.or.jp/modules/enviroli b/view.php?docid=4969 This work is funded by the "Environment Research and Technology Development Fund" of the Ministry of the Environment, Japan 2
Community decides • Appropriate decision-making at the community level is critical for adaptation – Adaptation is highly context-specific and no one-size-fits- all. – Adaptation require engagement of local community • But how do communities decide? – Community members have varying understanding on climate change and adaptation measures – What criteria underlies their decisions? – What factors influence their decisions? 3
Analysing decision-makings • A decision-making process on adaptation has been analyzed through Analytical Hierarchy Process (AHP) – Bangladesh, India and Nepal – Drought-prone and flood-prone communities – Male and female group 4
5 Drought-prone Flood-prone Bangladesh Chapainawabganj district Rajbari district India Kanpur Dehat district Udham Singh Nagar district Nepal Birganj district Bardiya district
Methodology: AHP • Analytical Hierarchy Process (AHP) – AHP allows users to employ multiple criteria to assess and compare various alternatives – Each criteria is weighed (each criteria has different importance) – The weight of each criteria is determined by pairwise ranking process(comparing two criteria to see which one is more important) 6
7 Salad CurryFried chickenSushi Price Taste Healthy Choose dinner for tonight GoalCriteriaAlternatives 0.10 0.65 0.25 0.250.050.4 0.35 AHP application: An example e.g. How to choose from a restaurant menu? 5 Price Taste 9 7 3 1 3 5 7 9
Case 1: Nepal – drought -male 8 Escape drought Cost effectiveness Harvesting surface water Pump for groundwater Alternative Crops Pest Control Drought resistance varieties Increase in crop yield Availability of water Bring effect on policy Replicable Easy to see the benefit Less investment Reduce drought sensitivity and improve adaptive capacity GoalCriteriaIndicatorsPractices 0.39 0.38 0.06 0.06 0.12 0.65 0.18 0.09 0.03 0.05 0.78 0.11 0.11
Case 1: Nepal – drought -male 9 0 0.1 0.2 0.3 0.4 0.5 Pump for groundwater Harvesting surface water Pest control Alternative crops Drought resistant varieties Aggregated score of adaptation practices and their composition Availability of Water Increase in Crop Yield Escape drought Cost effectiveness Less investment
Case 2: Bangladesh – flood-female 10 Improved communication Balanced nutrition Embankment Modern ag. knowledge Income diversification Increase in income Increase in yield Cost effectiveness Communicabil ity Relates to alternative income Homestead elevation Reduce flood sensitivity and improve adaptive capacity GoalCriteriaIndicatorsPractices 0.12 0.77 0.10 0.14 0.14 0.27 0.10 0.34 0.04 0.78 0.18
Case 2: Bangladesh – flood-female 0 0.2 0.4 0.6 0.8 1 Modern agriculture knolwedge Embankment Income diversification Increase in yield Increase in income Improved communication Balanced nutrition Homestead elevation 11
– Considerable variation from community to community – In drought-prone areas, boring wells were generally preferred over surface water. Water- saving activities such as change in cropping pattern and organic farming were also preferred. – In flood-prone areas, saving assets/lives through embankment, as well as access to alternative employment also preferred. – Limited but visible difference identified between male and female groups 12 Key findings
• AHP can reveal the decision-making process, identify priority actions, and also suggest adaptation indicators. • However, pairwise ranking process can be time consuming and difficult to be understood. • AHP more understood in relatively well- educated community. • Clear incentives (e.g. possibility of project funding) desirable to engage community members 13 Role of AHP to identify priority actions
14 iges.or.jp Contact for details on this study: email@example.com
Criteria Hazard India Drought Male Easy to understand (0.5), easy to observe (0.5) Female Easy to understand (0.5), easy to observe (0.5) Flood Male Prior experience (0.9) Female N/A Bangla desh Drought Male Cost effectiveness (0.76) Female Relates to production (0.5), Relates to economic well- being (0.31), cost effectiveness (0.30) Flood Male Communicability (0.76) Female Communicability (0.78) Nepal Drought Male Bring effect on policy (0.78) Female Easy to see benefits (0.71) Flood Male Easy to see impacts (0.79) Female Easy to see effect (0.76) 15
Indicators Country Hazard Gender Indicators India Drought Male Reduction in soil erosion (0.36), Water availability (0.33) Female Water availability (0.75) Flood Male Reduction in erosion (0.60) Female N/A Banglad esh Drought Male Availability of irrigation water (0.56), Female Irrigation water availability (0.36), increase in income (0.19) Flood Male Improved communication (0.4), increase in yield (0.38) Female Homestead elevation (0.34), improved communication (0.27) Nepal Drought Male Availability of water (0.65) Female Availability of water (0.52) Flood Male Land saved (0.37), property saved (0.24) Female Human lives saved (0.44) 16
Practices Country Hazard Gender Practices India Drought Male Land levelling(1.0), Bore well (0.83) Female Water availability (1.0), Land levelling (0.47) Flood Male River embankment (1.0), Female N/A Banglad esh Drought Male Groundwater (1.0) Female Groundwater (1.0) Flood Male Embankment (1.0) Female Embankment (1.0) Nepal Drought Male Pump for groundwater (1.0), Harvesting surface water (0.98) Female Pump for groundwater (1.0), Harvesting surface water (0.94), Green manures (0.84) Flood Male Early warning (1.0), Embankment (0.67) Female Evacuation of livestock (1.0), Evacuation of assets (0.82) 17
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