Holistic characterization of flash flood vulnerability: Construction and validation of an integrated multidimensional vulnerability index

Abstract

• Integrated and multidimensional approaches are key to identifying vulnerability underlying causes. • Validation of vulnerability indices can be tackled through sensitivity and uncertainty analysis. • Integrated and multidimensional vulnerability analysis is key to tackling integrated flood risk management. Over the last twenty years, numerous strategies and policies (e.g., 2030 Agenda for Sustainable Development) have emerged to promote flood risk reduction that is compatible with the conservation or restoration of river ecosystems, with the ultimate goal of achieving sustainable development. In this context, vulnerability analysis is considered a key aspect in flood risk reduction, and the most widespread methodology for its characterization is the construction of indices. However, such indices have been obtained so far through a fragmented approach, either because they do not consider all vulnerability dimensions (i.e., social, economic, ecosystem, physical, institutional and cultural) or components (i.e., exposure, sensitivity and resilience). Moreover, indices developed on a regional scale focusing on areas prone to flash floods are rarely validated, as the necessary information is often not available and flash floods do not occur simultaneously in all urban areas of a given region. This paper addresses the above two knowledge gaps and describes the construction at regional level of a flash flood Integrated Multidimensional Vulnerability Index (IMVI). Vulnerability here is characterized holistically, integrating in the index all the dimensions and components involved. Subsequently, an uncertainty and sensitivity analysis was performed to validate the IMVI. Lastly, vulnerability regional spatial patterns were identified through a Latent Class Cluster Analysis. The methodology implemented here allows one to identify vulnerability sources and their underlying causes, helping to improve flood risk management. Moreover, validation outputs enable to determine index uncertainty sources, thereby encouraging decision-makers to design more cost-effective vulnerability reduction strategies.