CLIMRISK-RIVER: Accounting for local river flood risk in estimating the economic cost of climate change. (October 2020)

• Record Type: Journal Article
• Authors: Ignjacevic, Predrag; Botzen, W.J. Wouter; Estrada, Francisco; Kuik, Onno; Ward, Philip; Tiggeloven, Timothy
• Is Part Of: Environmental modelling & software. Volume 132(2020)
• Publication Date: 2020-10
• Subjects: Integrated assessment modelling -- Climate change -- River flood risk -- River flood adaptation; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104784
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: This study aims to improve the estimates of the economic impacts of climate change by developing a river flood risk model CLIMRISK-RIVER and introducing it into an existing climate-economy integrated assessment model (IAM). It operates on a local scale and can project climate change-related river flood damage for various socioeconomic, climate and flood adaptation scenarios. Whereas other IAMs have relied on temperature as a climate change proxy, we show that precipitation is a key variable in projecting river flood damage. The way adaptation is accounted for in our flood damage functions has a large influence on the results, highlighting the relevance of modelling local level adaptation in IAMs. Results presented at different spatial scales demonstrate the relevance of river flood damage functions for estimating the economic impacts of climate change and allows for exploration of the spatial distribution of impacts through local estimates. Highlights: Reduced form river flood damage functions predict the output of more complicated models well. Precipitation, previously unaccounted for in climate-economy IAMs, is a key variable in projecting river flood damage. River flood adaptation has a large influence on climate-related flood damage and needs tobe modelled explicitly in IAMs. Local damage estimates show substantial spatial heterogeneity, making them essential in climate impact assessment