Compound flood impact of water level and rainfall during tropical cyclone periods in a coastal city: the case of Shanghai
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Compound flooding is generated when two or more flood drivers occur simultaneously or in close succession. Multiple drivers can amplify each other and lead to greater impacts than when they occur in isolation. A better understanding of the interdependence between flood drivers would facilitate a more accurate assessment of compound flood risk in coastal regions. This study employed the D-Flow Flexible Mesh model to simulate the historical peak coastal water level, consisting of the storm surge, astronomical tide, and relative sea level rise (RSLR), in Shanghai over the period 1961–2018. It then applies a copula-based methodology to calculate the joint probability of peak water level and rainfall during historical tropical cyclones (TCs) and to calculate the marginal contribution of each driver. The results indicate that the astronomical tide is the leading driver of peak water level, followed by the contribution of the storm surge. In the longer term, the RSLR has significantly amplified the peak water level. This study investigates the dependency of compound flood events in Shanghai on multiple drivers, which helps us to better understand compound floods and provides scientific references for flood risk management and for further studies. The framework developed in this study could be applied to other coastal cities that face the same constraint of unavailable water level records.
Date Issued
2022-07
Date Acceptance
2022-05-10
Citation
Natural Hazards and Earth System Sciences, 2022, 22 (7), pp.2347-2358
ISSN
1561-8633
Publisher
Copernicus Publications
Start Page
2347
End Page
2358
Journal / Book Title
Natural Hazards and Earth System Sciences
Volume
22
Issue
7
Copyright Statement
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
License URL
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000826518500001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
CHINA
CLIMATE-CHANGE
DEPENDENCE
EVENT
EXTREME RAINFALL
Geology
Geosciences, Multidisciplinary
LOSSES
Meteorology & Atmospheric Sciences
MODEL
Physical Sciences
RISE
RIVER DISCHARGE
Science & Technology
STORM-SURGE
Water Resources
Publication Status
Published
Date Publish Online
2022-07-18