Comparison of estimates of global flood models for flood hazard and exposed gross domestic product

A China case study

Journal Article (2020)
Author(s)

Jerom Aerts (TU Delft - Water Resources)

Steffi Uhlemann-Elmer (Aspen Insurance Ltd)

Dirk Eilander (Deltares, Vrije Universiteit Amsterdam)

Philip J. Ward (Vrije Universiteit Amsterdam)

Research Group
Water Resources
Copyright
© 2020 J.P.M. Aerts, Steffi Uhlemann-Elmer, Dirk Eilander, Philip J. Ward
DOI related publication
https://doi.org/10.5194/nhess-20-3245-2020
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 J.P.M. Aerts, Steffi Uhlemann-Elmer, Dirk Eilander, Philip J. Ward
Research Group
Water Resources
Issue number
12
Volume number
20
Pages (from-to)
3245-3260
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Abstract

Over the past decade global flood hazard models have been developed and continuously improved. There is now a significant demand for testing global hazard maps generated by these models in order to understand their applicability for international risk reduction strategies and for reinsurance portfolio risk assessments using catastrophe models. We expand on existing methods for comparing global hazard maps and analyse eight global flood models (GFMs) that represent the current state of the global flood modelling community. We apply our comparison to China as a case study and, for the first time, include industry models, pluvial flooding, and flood protection standards in the analysis. In doing so, we provide new insights into how these components change the results of this comparison. We find substantial variability, up to a factor of 4, between the flood hazard maps in the modelled inundated area and exposed gross domestic product (GDP) across multiple return periods (ranging from 5 to 1500 years) and in expected annual exposed GDP. The inclusion of industry models, which currently model flooding at a higher spatial resolution and which additionally include pluvial flooding, strongly improves the comparison and provides important new benchmarks. We find that the addition of pluvial flooding can increase the expected annual exposed GDP by as much as 1.3 percentage points. Our findings strongly highlight the importance of flood defences for a realistic risk assessment in countries like China that are characterized by high concentrations of exposure. Even an incomplete (1.74 % of the area of China) but locally detailed layer of structural defences in high-exposure areas reduces the expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8%.