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Potential impacts of storm surge-induced flooding based on refined exposure estimation: a case study in Zhoushan island, China

Authors :
Bairu Chen
Junyu He
Zhiguo He
Li Li
Qian Chen
Feixiang Li
Dongdong Chu
Zeng Cao
Xuchao Yang
Source :
Geomatics, Natural Hazards & Risk, Vol 14, Iss 1 (2023)
Publication Year :
2023
Publisher :
Taylor & Francis Group, 2023.

Abstract

AbstractStorm surge-induced flooding (SSIF) is a major hazard for coastal areas under intensified typhoons. Therefore, it is essential to assess the potential impacts of SSIF (SSPIA). This study proposes a multidisciplinary framework for refined SSPIA using an ocean model and a refined exposure estimation method. First, a finite-volume coastal ocean model (FVCOM) and a typhoon model were developed and validated. Then, five scenarios of varying intensity were defined and combined with FVCOM to identify inundation scenarios. Subsequently, machine learning was used to obtain the fine-scale gridded population and gross domestic product (GDP) maps based on the census and geospatial data. Finally, we assessed the magnitude of the affected population and GDP based on the inundation scenarios and refined exposure datasets. We selected Zhoushan Island as a study area to implement this framework. Our assessment results show that the lowest scenario (955 hPa) affected 2587 people and 323.745 million CNY of GDP, while the highest scenario (915 hPa) affected 259,516 people and 20,178.898 million CNY of GDP. Therefore, it is imperative to implement effective mitigation and adaptation measures to address the threat of SSIF. This framework will apply to all flood-prone areas for a refined assessment of the potential impacts of SSIF.

Details

Language :
English
ISSN :
19475705 and 19475713
Volume :
14
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Geomatics, Natural Hazards & Risk
Publication Type :
Academic Journal
Accession number :
edsdoj.7c0a109e36574f8e8700f360114ea038
Document Type :
article
Full Text :
https://doi.org/10.1080/19475705.2023.2232080