A vulnerability-adjusted approach to 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. They also use arbitrary return period thresholds, which can disguise potentially catastrophic hazards. To address these limitations, 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). This human welfare-centred approach radically alters how we perceive the geography of risk and could be used as a complement to traditional population or asset-centred approaches. We present global results for both unadjusted and vulnerability-adjusted risk at the subnational (Admin 2) level; country case studies illustrate how accounting for vulnerability changes the perceived subnational geography of risk. Globally, adjusting for vulnerability significantly reduces the total number of people estimated to be at ‘high risk’ from  over 575 million to about 117 million. However, this latter estimate is likely an underestimate given the relatively coarse resolution of the economic data available, which disguises variation in vulnerability between communities within large cities and urban regions. Given the increasing concentration of the global human population in cities, there is an urgent need to improve the resolution of vulnerability mapping within large human settlements to inform mitigation measures.