Standardized disaster and climate resilience grading: A global scale empirical analysis of community flood resilience

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/91744 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/91744 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/91744 archive 353 disk0/00/01/67/58 2020-10-01 07:02:37 2025-03-26 05:00:18 2020-10-01 07:02:37 article show Hochrainer-Stigler S. 7958 0000-0002-9929-8171 Laurien F 2139 0000-0001-7329-5864 Velev S. 2238 Keating A. 2024 Mechler R. 7793 0000-0003-2239-1578 Standardized disaster and climate resilience grading: A global scale empirical analysis of community flood resilience pub prog_risk Resilience; Floods; Expert grading; Technical grading standards; Standardized resilience grading; Flood resilience measurement tool Suitable and standardized indicators to track progress in disaster and climate resilience are increasingly considered a key requirement for successfully informing efforts towards effective disaster risk reduction and climate adaptation. Standardized measures of resilience which can be used across different geographical and socioeconomic contexts are however sparse. We present and analyze a standardized community resilience measurement framework for flooding. The corresponding measurement tool is modelled based on and adapted from a so-called ‘technical risk grading’ approach as used in the insurance sector. The grading approach of indicators is based on a two-step process: (i) raw data is collected, and (ii) experts grade the indicators, called sources of resilience, based on this data. We test this approach using approximately 1.25 million datapoints collected across more than 118 communities in nine countries. The quantitative analysis is complemented by content analysis to validate the results from a qualitative perspective. We find that some indicators can more easily be graded by looking at raw data alone, while others require a stronger application of expert judgement. We summarize the reasons for this through six key messages. One major finding is that resilience grades related to subjective characteristics such as ability, feel, and trust are far more dependent on expert judgment than on the actual raw data collected. Additionally, the need for expert judgement further increases if graders must extrapolate the whole community picture from limited raw data. Our findings regarding the role of data and grade specifications can inform ways forward for better, more efficient and increasingly robust standardized assessment of resilience. This should help to build global standardized and comparable, yet locally contextualized, baseline estimates of the many facets of resilience in order to track progress over time on disaster and climate resilience and inform the implementation of the Paris Agreement, Sendai Framework, and the Sustainable Development Goals. 2020-12-15 published Elsevier 10.1016/j.jenvman.2020.111332 126 2898 3131 147 204 public Journal of Environmental Management 276 e111332 TRUE 1095-8630 FALSE no info:eu-repo/semantics/article