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A Flood Risk Framework Capturing the Seasonality of and Dependence Between Rainfall and Sea Levels—An Application to Ho Chi Minh City, Vietnam

A. Couasnon Orcid Logo, P. Scussolini Orcid Logo, T. V. T. Tran Orcid Logo, D. Eilander Orcid Logo, S. Muis Orcid Logo, Han Wang, J. Keesom, J. Dullaart Orcid Logo, Yunqing Xuan Orcid Logo, H. Q. Nguyen Orcid Logo, H. C. Winsemius Orcid Logo, P. J. Ward Orcid Logo

Water Resources Research, Volume: 58, Issue: 2

Swansea University Authors: Han Wang, Yunqing Xuan Orcid Logo

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DOI (Published version): 10.1029/2021wr030002

Abstract

State-of-the-art flood hazard maps in coastal cities are often obtained from simulating coastal or pluvial events separately. This method does not account for the seasonality of flood drivers and their mutual dependence. In this article, we include the impact of these two factors in a computationall...

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Published in: Water Resources Research
ISSN: 0043-1397 1944-7973
Published: American Geophysical Union (AGU) 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa59167
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Abstract: State-of-the-art flood hazard maps in coastal cities are often obtained from simulating coastal or pluvial events separately. This method does not account for the seasonality of flood drivers and their mutual dependence. In this article, we include the impact of these two factors in a computationally efficient probabilistic framework for flood risk calculation, using Ho Chi Minh City (HCMC) as a case study. HCMC can be flooded sub-annually by high tide, rainfall and storm surge events or a combination thereof during the monsoon or tropical cyclones. Using long gauge observations, we stochastically model 10,000 years of rainfall and sea level events based on their monthly distributions, dependence structure and co-occurrence rate. The impact from each stochastic event is then obtained from a damage function built from selected rainfall and sea level combinations, leading to an expected annual damage (EAD) of $1.02B (95th annual damage percentile of $2.15B). We find no dependence for most months and large differences in expected damage across months ($36M-166M) driven by the seasonality of rainfall and sea levels. Excluding monthly variability leads to a serious underestimation of the EAD by 72% to 83%. This is because high-probability flood events, which can happen multiple times during the year and are properly captured by our framework, contribute the most to the EAD. This application illustrates the potential of our framework and advocates for the inclusion of flood drivers’ dynamics in coastal risk assessments.
Keywords: compound flood; flood risk; skew surge; seasonality; ho chi minh city; dependence
College: College of Engineering
Funders: Dutch Research Council (NWO) (VIDI; grant no. 016.161.324; and grant no. ALWOP.164); Vietnam National University –Ho Chi Minh City under grant C2018-48-01
Issue: 2