Integrating social vulnerability into global flood risk mapping

Abstract

Global flood risk maps combine data from hydrodynamic models with gridded population or GDP data to estimate the amount of people or wealth likely to be exposed to future flood events. These estimates rarely incorporate measures of social vulnerability, which is a key source of variation in outcomes for exposed populations. To address this lacuna, we integrate annual average exceedance probability estimates from a high-resolution (~90m) flood model with gridded population and economic data to create a global vulnerability-adjusted risk index for flooding (VARI Flood). Designed for decision makers, this approach radically alters how we perceive the geography of risk by identifying ‘hotspots’ characterised by high population density and high levels of social vulnerability. VARI Flood could be used as a complement to traditional population or asset-centred approaches. Our results also highlight the urgent need to improve social vulnerability mapping within cities and rapidly urbanizing regions.