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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/nhess-2020-1
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-1
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 27 Jan 2020

Submitted as: research article | 27 Jan 2020

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This preprint is currently under review for the journal NHESS.

Global flood hazard map and exposed GDP comparison: a China case study

Jerom P. M. Aerts1, Steffi Uhlemann-Elmer2, Dirk Eilander3,4, and Philip J. Ward3 Jerom P. M. Aerts et al.
  • 1Water Resources Section, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, The Netherlands
  • 2Aspen Insurance Ltd, Zurich, Switzerland
  • 3Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
  • 4Deltares, Delft, The Netherlands

Abstract. Floods are among the most frequent and damaging natural hazard events in the world. In 2016, economic losses from flooding amounted to $56 bn globally, of which $20 bn occurred in China (Munich Re, 2017). National or regional scale mapping of flood hazard is at present providing an inconsistent and incomplete picture of floods. Over the past decade global flood hazard models have been developed and continuously improved. There is now a significant demand for testing of the 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 8 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, we include industry models, pluvial flooding, and flood protection standards in the analysis. We find substantial variability between the flood hazard maps in modelled inundated area and exposed GDP across multiple return periods (ranging from 5 to 1500 years) and in expected annual exposed GDP. For example, for the 100 year return period undefended (assuming no flood protection) hazard maps the percentage of total affected GDP of China ranges between 4.4 % and 10.5 % for fluvial floods. For the majority of the GFMs we see only a small increase in inundated area or exposed GDP for high return period undefended hazard maps compared to low return periods, highlighting major limitations in the models’ resolution and their output. The inclusion of industry models which currently model flooding at higher spatial resolution, and which additionally include pluvial flooding, strongly improves the comparison and provides important new benchmarks. Pluvial flooding can increase the expected annual exposed GDP by as much as 1.3 % points. Our study strongly highlights the importance of flood defenses for a realistic risk assessment in countries like China that are characterized by high concentrations of exposure. Even an incomplete (1.74 % of area of China) but locally detailed layer of structural defenses in high exposure areas reduces the expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.

Jerom P. M. Aerts et al.

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Short summary
We compare and analyze flood hazard maps from 8 global flood models 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, we include industry models, pluvial flooding, and flood protection standards in the analysis. We find substantial variability between the flood hazard maps in modeled inundated area and exposed GDP across multiple return periods and in expected annual exposed GDP.
We compare and analyze flood hazard maps from 8 global flood models that represent the current...
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