Flood risk is increasing worldwide and there is a growing need to better understand the co-benefits of investments in disaster resilience. Utilizing a multinational community flood resilience dataset, this paper takes a systems approach to understanding community-level flood resilience. Using a cluster analysis and bivariate correlation methods, we develop a typology of community flood resilience capacity based on community characteristics and five capitals (human, financial, natural, physical, and social). Our results reinforce the importance of context-specific policymaking and give recommendations of four distinct clusters to investigate the relationship between flood resilience and prevailing development conditions. We especially find that communities with higher interactions between their capital capacities tend to have higher flood resilience levels. Additionally, there are indications that stronger interactions between community capacities can help to induce multiple co-benefits when investing in disaster resilience. Our results also have important policy implications on the individual community level. For example, based on our results, we suggest that communities with lower flood resilience capacities and interactions can best build resilience on leveraging their relatively higher human capital capacities to strengthen the financial and social capitals. Negative effects might happen for urban communities when co-benefits of natural and physical capital are not fully integrated. The highest flood resilience capacity is found in communities with a well-balanced household income distribution which is likely a contributing factor to the importance of financial capital for this cluster. Our results emphasize the importance of an integrative approach to management when implementing systematic flood disaster resilience metrics and development measures.

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.

Given the increased attention put on strengthening disaster resilience, there is a growing need to invest in its measurement and the overall accountability of resilience strengthening initiatives. There is a major gap in evidence about what actually makes communities more resilient when an event occurs, because there are no empirically validated measures of disaster resilience. Similarly, an effort to identify operational indicators has gained some traction only more recently. The Flood Resilience Measurement for Communities (FRMC) framework and associated, fully operational, integrated tool takes a systems-thinking, holistic approach to serve the dual goals of generating data on the determinants of community flood resilience, and providing decision-support for on-the-ground investment. The FRMC framework measures “sources of resilience” before a flood happens and looks at the post-flood impacts afterwards. It is built around the notion of five types of capital (the 5Cs: human, social, physical, natural, and financial) and the 4Rs of a resilient system (robustness, redundancy, resourcefulness, and rapidity). The sources of resilience are graded based on Zurich’s Risk Engineering Technical Grading Standard. Results are displayed according to the 5Cs and 4Rs, the disaster risk management (DRM) cycle, themes and context level, to give the approach further flexibility and accessibility. The Zurich Flood Resilience Alliance (ZFRA) has identified the measurement of resilience as a valuable ingredient in building community flood resilience. In the first application phase (2013-2018), we measured flood resilience in 118 communities across nine countries, building on responses at household and community levels. Continuing this endeavor in the second phase (2018 – 2023) will allow us to enrich the understanding of community flood resilience and to extend this unique data set. We find that at the community level, the FRMC enables users to track community progress on resilience over time in a standardized way. It thus provides vital information for the decision-making process in terms of prioritizing the resilience-building measures most needed by the community. At community and higher decision-making levels, measuring resilience also provides a basis for improving the design of innovative investment programs to strengthen disaster resilience. By exploring data across multiple communities (facing different flood types and with very different socioeconomic and political contexts), we can generate evidence with respect to which characteristics contribute most to community disaster resilience before an event strikes. This contributes to meeting the challenge of demonstrating that the work we do has the desired impact – that it actually builds resilience. Our findings suggest that stronger interactions between community functions induce co-benefits for community development.

Communities around the world in natural hazard-prone regions are increasingly aware of the benefits of using spatio-temporal data to better understand their predicament. With the advent of new service technologies, such as web mapping, free and open satellite data and the proliferation of mobile technologies, the possibilities for both understanding and improving community resilience are on the rise. Resilience service technologies aim to provide risk-informed products in easy-to-use manner for enabling stakeholders to implement efficient and practical resilience activities in their communities.This paper presents a service-oriented approach aiming to harnessing risks and resilience data in hazard-prone regions for raise awareness regarding early warning systems, safety conditions of minorities in community groups and plan for long-term resilience strategies. With our resilience dashboard platform, we utilize information of various risk and resilience services to identify and visualize susceptible hotspots for decision-makers. Our resilience dashboard also brings about the coordination between different web services to retrieve the features and impose the thresholds. We co-developed with local humanitarian and development teams the resilience dashboard which is designed to put geo-spatial flood resilience data into the hands of decision-makers. We identified three use cases which consider an added value of resilience service technologies by focusing on early warning systems, targeting minority groups and long-term resilience planning in Nicaragua, Nepal and Bangladesh. We will demonstrate the context-specific needs of resilience services technologies, how to target user needs and how it could potentially be scaled up and applied to similar regions around the world.

Severe flooding in Western Germany, Belgium and the Netherlands in July 2021, particularly along the rivers Erft, Ahr and Meuse rivers has led to more than 240 causalities and an estimated damage of 29,2 billion EUR in Germany alone. The high human and economic costs of the event brought systemic problems in the flood risk management system to light and raised questions about the limits of disaster risk management and climate change adaptation. Using a forensic disaster analysis approach, the Post Event Review Capability (PERC), we systematically analyse the strengths and weaknesses of the flood risk management systems in the affected regions, the emergency response and recovery to draw lessons for future disaster risk management and climate change adaptation strategies. For that, PERC synthesizes existing information about the event from the hydro-meteorological characteristics of the physical impact and combines it with qualitative interviews with first responders, flood risk managers and other directly affected stakeholders. We will present key findings from the PERC study on the 2021 floods including the main drivers behind the high casualties and potential shortcomings in the emergency response and recovery as well as recommendations and opportunities for improvement.