Quantitative risk assessment of storm surge using GIS techniques and open data: A case study of Daya Bay Zone, China

Si Wang; Lin Mu; Mengnan Qi; Zekun Yu; Zhenfeng Yao; Enjin Zhao

doi:10.1016/j.jenvman.2021.112514

Quantitative risk assessment of storm surge using GIS techniques and open data: A case study of Daya Bay Zone, China

J Environ Manage. 2021 Jul 1:289:112514. doi: 10.1016/j.jenvman.2021.112514. Epub 2021 Apr 8.

Authors

Si Wang¹, Lin Mu², Mengnan Qi³, Zekun Yu⁴, Zhenfeng Yao⁵, Enjin Zhao⁶

Affiliations

¹ Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, 511458, China; College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China; Hubei Key Laboratory of Marine Geological Resources/College of Marine Science and Technology, China University of Geosciences, Wuhan, 430074, China. Electronic address: ws_wuhan@cug.edu.cn.
² Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, 511458, China; College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China. Electronic address: moulin1977@hotmail.com.
³ South China Sea Marine Prediction Center, State Oceanic Administration, Guangzhou, 510310, China; Key Laboratory of Marine Environment Survey Technology and Application, Ministry of Natural Resource, Guangzhou, 510300, China. Electronic address: qmn2008j@126.com.
⁴ Hubei Key Laboratory of Marine Geological Resources/College of Marine Science and Technology, China University of Geosciences, Wuhan, 430074, China.
⁵ Department of Natural Resources of Huizhou Bureau, Huizhou, 516001, China.
⁶ Hubei Key Laboratory of Marine Geological Resources/College of Marine Science and Technology, China University of Geosciences, Wuhan, 430074, China. Electronic address: zhaoej@cug.edu.cn.

PMID: 33839613
DOI: 10.1016/j.jenvman.2021.112514

Abstract

Storm surge is a natural disaster, often causing economic damage and loss of human life in the coastal communities. In recent decades, with more people attracted to coastal areas, the potential economic losses resulted from storm surges are increasing. Therefore, it is important to make risk assessments to identify areas at risk and design risk reduction strategies. However, the quantitative risk assessment of storm surge for coastal cities in China is often difficult due to the lack of adequate data regarding the building footprint and vulnerability curves. This paper aims to provide a methodology for conducting the quantitative risk assessment of storm surge, estimating direct tangible damage, by using Geographical Information System (GIS) techniques and open data. The proposed methodology was applied to a coastal area with a high concentration of petroleum industries in the Daya Bay zone. At first, five individual typhoon scenarios with different return periods (1000, 100, 50, 20, and 10 years) were defined. Then, the Advanced Circulation model and the Simulating Waves Nearshore model were utilized to simulate storm surge. The model outputs were imported into GIS software, transformed into inundation area and inundation depth. Subsequently, the building footprint data were extracted by the use of GIS techniques, including spatial analysis and image analysis. The layer containing building footprints was superimposed on the inundation area layer to identify and quantify the exposed elements to storm surge hazard. Combining the exposed elements with their related depth-damage functions, the quantitative risk assessment translates the spatial extent and depth of storm surge into the estimation of economic losses. The quantitative risk assessment and zonation maps for sub-zones in the study area can help local decision-makers to prioritize the sub-zones that are more likely to be affected by storm surge, make risk mitigation strategies, and develop long-term urban plans.

Keywords: Building footprint; Depth–damage function; GIS; Hazard assessment; Risk zonation map; Storm surge modeling.

MeSH terms

Bays*
China
Cities
Geographic Information Systems*
Humans
Risk Assessment