Among all natural disasters, floods have historically been the primary cause of human and economic losses around the world. Improving flood risk management requires a multi-scale characterization of the hazard and associated losses—the flood loss footprint. But this is typically not available in a precise and timely manner, yet. To overcome this challenge, we propose a novel and multidisciplinary approach which relies on a computationally efficient hydrological model that simulates streamflow for scales ranging from small creeks to large rivers. We adopt a normalized index, the flood peak ratio (FPR), to characterize flood magnitude across multiple spatial scales. The simulated FPR is then shown to be a key statistical driver for associated economic flood losses represented by the number of insurance claims. Importantly, because it is based on a simulation procedure that utilizes generally readily available physically-based data, our flood simulation approach has the potential to be broadly utilized, even for ungauged and poorly gauged basins, thus providing the necessary information for public and private sector actors to effectively reduce flood losses and save lives.
Wharton Risk Management and Decision Processes Center, University of Pennsylvania, 3730 Walnut Street, Philadelphia, PA 19104, USA;Willis Research Network, 51 Lime Street, London, EC3M 7DQ, UK;Willis Research Network, 51 Lime Street, London, EC3M 7DQ, UK;Department of Civil and Environmental Engineering, Princeton University, E413 Engineering Quad, Princeton, NJ 08544, USA;Wharton Risk Management and Decision Processes Center, University of Pennsylvania, 3730 Walnut Street, Philadelphia, PA 19104, USA;Willis Research Network, 51 Lime Street, London, EC3M 7DQ, UK;Department of Civil and Environmental Engineering, Princeton University, E413 Engineering Quad, Princeton, NJ 08544, USA
Recommended Citation:
Jeffrey Czajkowski,Luciana K Cunha,Erwann Michel-Kerjan,et al. Toward economic flood loss characterization via hazard simulation[J]. Environmental Research Letters,2016-01-01,11(8)