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Assessment of typhoon storm surge disaster scale based on expansion model
- Journal of Oceanology and Limnology Vol. 41, Issue 2, Pages: 518-531(2023)
- Affiliations：
1.College of Engineering, Ocean University of China, Qingdao 266100, China
2.Dornsife College, University of Southern California, Los Angeles CA90089, USA
3.Statistics and Applied Probability, University of California Santa Barbara, Santa Barbara CA93106, USA
4.Department of Mathematics, Harvard University, Cambridge MA02138, USA
5.State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
- Author bio：
yuzongbing1989@163.com
- Funds：
DOI：
CLC：Received：30 January 2022，
Published：01 March 2023
- Accepted：
Scan QR Code
LIU Guilin,NONG Xiuxiu,KOU Yi,et al.Assessment of typhoon storm surge disaster scale based on expansion model[J].Journal of Oceanology and Limnology,2023,41(02):518-531.
摘要
Abstract
The South China Sea suffers strongly from the typhoon storm surge disasters in China
and its northern coastal areas are facing severe risks. Therefore
it is necessary and urgent to establish an assessment system for rating typhoon storm surge disaster. We constructed an effective and reliable rating assessment system for typhoon storm surge disaster based on the theories of over-threshold
distribution function family
and composite extreme value. The over-threshold sample was used as the basis of data analysis
the composite extreme value expansion model was used to derive the design water increment
and then the disaster level was delineated based on the return period level. The results of the extreme value model comparison show that the Weibull-Pareto distribution is more suitable than the classical extreme value distribution for fitting the over-threshold samples. The results of the return period projection are relatively stable based on different analysis samples. Taking the 10 typhoon storm surges as examples
they caused landfall in the Guangdong area in the past 10 years. The results of the assessment ranking indicate that the risk levels based on the return period levels obtained from different distributions are generally consistent. When classifying low-risk areas
the classification criteria of the State Oceanic Administration
China (SOA
2012) are more conservative. In the high-risk areas
the results of the assessment ranking based on return period are more consistent with those of the SOA.
关键词
Keywords
references
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