Measuring community disaster resilience for sustainable climate change adaptation: Lessons from time-series findings in rural Cambodia.

Donor-funded climate and disaster resilience programmes and projects aim to help build the capacities and resilience of communities. Measuring resilience is critical, therefore, in providing feedback, evidence, and accountability. This paper presents recent two-year time-series findings from an ongoing multi-partner academic and practical collaboration pertaining to a climate change adaption project with rural communities in Cambodia. To measure community resilience, the study used the Flood Resilience Measurement for Communities, which measures, using mixed methods, disaster resilience capacities across five key dimensions of resilience: human, social, physical, natural, and financial capitals. The study analysed and reported changes in these areas of resilience in the selected villages, generating insights into the strengths and weaknesses of flood resilience capacities in the region. This paper provides valuable guidance as to where investment can be most effective in different communities, confirming the usefulness of the tool in measuring resilience and assessing the effectiveness of the project concerned.

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

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.

An overdue alignment of risk and resilience? A conceptual contribution to community resilience.

A systematic review of literature on community resilience measurement published between 2005 and 2014 revealed that the profound lack of clarity on risk and resilience is one of the main reasons why confusion about terms such as adaptive capacity, resilience, and vulnerability persists, despite the effort spared to operationalise these concepts. Resilience is measured in isolation in some cases, where a shock is perceived to arise external to the system of interest. Problematically, this contradicts the way in which the climate change and disaster communities perceive risk as manifesting itself endogenously as a function of exposure, hazard, and vulnerability. The common conceptualisation of resilience as predominantly positive is problematic as well when, in reality, many undesirable properties of a system are resilient. Consequently, this paper presents an integrative framework that highlights the interactions between risk drivers and coping, adaptive, and transformative capacities, providing an improved conceptual basis for resilience measurement.

Business recovery from disasters: Lessons from natural hazards and the COVID-19 pandemic.

This paper compares economic recovery in the COVID-19 pandemic with other types of disasters, at the scale of businesses. As countries around the world struggle to emerge from the pandemic, studies of business impact and recovery have proliferated; however, pandemic research is often undertaken without the benefit of insights from long-standing research on past large-scale disruptive events, such as floods, storms, and earthquakes. This paper builds synergies between established knowledge on business recovery in disasters and emerging insights from the COVID-19 pandemic. It first proposes a disaster event taxonomy that allows the pandemic to be compared with natural hazard events from the perspective of economic disruption. The paper then identifies five key lessons on business recovery from disasters and compares them to empirical findings from the COVID-19 pandemic. For synthesis, a conceptual framework on business recovery is developed to support policy-makers to anticipate business recovery needs in economically disruptive events, including disasters. Findings from the pandemic largely resonate with those from disasters. Recovery tends to be more difficult for small businesses, those vulnerable to supply chain problems, those facing disrupted markets, and locally-oriented businesses in heavily impacted neighborhoods. Disaster assistance that is fast and less restrictive provides more effective support for business recovery. Some differences emerge, however: substantial business disruption in the pandemic derived from changes in demand due to regulatory measures as well as consumer behaviour; businesses in high-income neighborhoods and central business districts were especially affected; and traditional forms of financial assistance may need to be reconsidered.

Differences in the dynamics of community disaster resilience across the globe.

The consideration of disaster resilience as a multidimensional concept provides a viable and promising way forward for reducing risk and minimizing impacts today and in the future. What is missing is the understanding of the actual dynamics of resilience over time based on empirical evidence. This empirical understanding requires a consistent measure of resilience. To that end, a Technical Resilience Grading Standard for community flood resilience, was applied in a longitudinal study from 2016 to 2018 in 68 communities across the globe. We analyse the dynamics of disaster resilience using an advanced boosted regression tree modelling framework. The main outcome of our analysis is twofold: first, we found empirical evidence that the dynamics of resilience build on a typology of communities and that different community clusters experience different dynamics; and second, the dynamics of resilience follows transitional behaviour rather than a linear or continuous process. These are empirical insights that can provide ways forward, theoretically as well as practically, in the understanding of resilience as well as in regard to effective policy guidance to enhance disaster resilience.

If Numbers Can Speak, Who Listens? Creating Engagement and Learning for Effective Uptake of DRR Investment in Developing Countries.

INTRODUCTION: With a renewed emphasis on evidence-based risk sensitive investment promoted under the Sendai Framework for Disaster Risk Reduction 2015-2030, technical demands for analytical tools such as probabilistic cost-benefit analysis (CBA) will likely increase in the foreseeable future. This begs a number of pragmatic questions such as whether or not sophisticated quantitative appraisal tools are effective in raising policy awareness and what alternatives are available. METHOD: This article briefly reviews current practices of analytical tools such as probabilistic cost-benefit analysis and identifies issues associated with its applications in small scale community based DRR interventions. RESULTS: The article illustrate that while best scientific knowledge should inform policy and practice in principle, it should not create an unrealistic expectation that the state-of-the art methods must be used in all cases, especially for small scale DRR interventions in developing countries, where data and resource limitations and uncertainty are high, and complex interaction and feedback may exist between DRR investment, community response and longer-term development outcome.  DISCUSSION: Alternative and more participatory approaches for DRR appraisals are suggested which includes participatory serious games that are increasingly being used to raise awareness and identify pragmatic strategies for change that are needed to bring about successful uptake of DRR investment and implementation of DRR mainstreaming.

Revisiting the 'disaster and development' debate - Toward a broader understanding of macroeconomic risk and resilience.

Debate regarding the relationship between socioeconomic development and natural disasters remains at the fore of global discussions, as the potential risk from climate extremes and uncertainty pose an increasing threat to developmental prospects. This study reviews statistical investigations of disaster and development linkages, across topics of macroeconomic growth, public governance and others to identify key challenges to the current approach to macro-level statistical investigation. Both theoretically and qualitatively, disaster is known to affect development through a number of channels: haphazard development, weak institutions, lack of social safety nets and short-termism of our decision-making practices are some of the factors that drive natural disaster risk. Developmental potentials, including the prospects for sustainable and equitable growth, are in turn threatened by such accumulation of disaster risks. However, quantitative evidence regarding these complex causality chains remains contested due to several reasons. A number of theoretical and methodological limitations have been identified, including the use of GDP as a proxy measurement of welfare, issues with natural disaster damage reporting and the adoption of ad hoc model specifications and variables, which render interpretation and cross-comparison of statistical analysis difficult. Additionally, while greater attention is paid to economic and institutional parameters such as GDP, remittance, corruption and public expenditure as opposed to hard-to-quantify yet critical factors such as environmental conditions and social vulnerabilities. These are gaps in our approach that hamper our comprehensive understanding of the disaster-development nexus. Important areas for further research are identified, including recognizing and addressing the data constraints, incorporating sustainability and equity concerns through alternatives to GDP, and finding novel approaches to examining the complex and dynamic relationships between risk, vulnerability, resilience, adaptive capacity and development.