Compounding effects of urbanization, climate change and sea-level rise on monetary projections of flood damage

Abstract

Climate change and urbanization play critical roles in compounding future flood risk due to their adverse impacts on the rainfall regime and sea level rise. Although past studies have predicted the spatiotemporal variations in flood risk, these have appreciable limitations, viz. (i) flood risk is predicted mainly by accounting for one driver at a time (either ocean flooding or fluvial flooding); and (ii) monetization of flood damage due to future flooding had not been investigated. However, multiple drivers could lead to flooding in coastal areas. This study presents an innovative approach for investigating the cumulative effects of urbanization, changes to the rainfall regime, and sea level rise on consequential flood damage in a coastal urban area. A comprehensive flood damage and hazard prediction model was developed by integrating 1D-2D aspects of MIKE FLOOD and GIS technology to assess the flood scenarios for 2040, 2070, and 2100 by investigating three predictor variables: urbanization, rainfall regime, and sea level rise. The factorial design approach was used to construct a total of 27 future flood scenarios. Time horizons of 30 years provided for effectively capturing climate change and its influence on the hydrologic regime. The Generalized Linear Model (GLM) was applied to create a statistical model based on future scenarios for each time horizon. Results confirmed that changes to the rainfall regime significantly influence the average annual damage (AAD) caused by flooding for all time horizons. At the same time, the significance of the effects of urbanization and sea level rise was found to vary. The model predicts that by 2040, urbanization would exacerbate AAD, with a significant contribution from sea level rise. In contrast, sea level rise would provide a marginally greater and more significant contribution to AAD compared to urbanization in 2040 and 2070. Compared to the base year 2017, AAD was 78%, 197%, and 351% higher in 2040, 2070, and 2100, respectively. The proposed flood damage prediction model developed can guide modelers and decision-makers in assessing the compounding flood damage for future flood management in any geographic location.