4.7 Article

Quantitative risk assessment of typhoon storm surge for multi-risk sources

Journal

JOURNAL OF ENVIRONMENTAL MANAGEMENT
Volume 327, Issue -, Pages -

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2022.116860

Keywords

Multi-risk sources; Risk assessment; Typhoon storm surge; Copulas; Geographic information system; Depth-damage functions

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This paper proposes a rapid, accurate, and comprehensive quantitative risk assessment method for Typhoon storm surge (TSS) under multi-risk sources. By identifying the primary risk sources and constructing a dependence structure, the method calculates the probability of each superposition scenario and converts inundation into economic and population risks. Case study results demonstrate the feasibility and accuracy of the method. This study is of great significance for disaster control, sustainable development, and decision-making.
Typhoon storm surge (TSS) is a complex marine disaster affected by multi-risk sources. Quantitative risk assessment is an important prerequisite for identifying risk areas and designing risk reduction strategies. This paper aims to propose a rapid, accurate, and comprehensive quantitative risk assessment method for TSS under multi-risk sources, including disaster occurrence probability and severity. First, identify the primary risk sources according to the disaster-causing mechanism of TSS. Then, based on the official public data from 1989 to 2020, the dependence structure among multi-risk sources is constructed using Copulas to calculate the probability of each superposition scenario. Meanwhile, build visual scenario databases employing Geographical Information System (GIS) techniques. Subsequently, the extent and depth of inundation are translated into economic risk and population risk using GIS and depth-damage functions. Finally, taking the Mangkhut as a case study, the method's feasibility and accuracy are verified. The results show that the primary risk sources of TSS are storm tide, astronomical tide and coastal waves. The Gumbel Copula is optimal, with OLS (ordinary least squares) and D of 0.0186 and 0.1831, respectively. The probability assessment under different superposition scenarios in-dicates that the greatest threat of TSS in Guangzhou comes from the storm tide and the astronomical tide. As for the Mangkhut case study in Jiangmen City, the assesses occurrence probability is 0.0355%, the accuracy of economic risk assessment (except mariculture) is 95.28%, and the accuracy of population risk assessment is 98.60%. Residences and the disaster-bearing bodies in 0-3 m inundation depth are most severely affected by TSS disasters. Measures such as locating residential and important buildings away from the shoreline (at least 10 km) and ground (above 3 m), formulating disaster emergency plans, and developing the forecast and prevention of storm tides and astronomical tides will help ensure the safety of residents' life and property. This paper provides an efficient and accurate method, which is of great significance for disaster control, sustainable development, and decision-making.

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