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.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Supported by the National Natural Science Foundation of China (Nos. 52071306, 52101360), the Natural Science Foundation of Shandong Province (No. ZR2019MEE050), and the State Key Laboratory of Coastal and Offshore Engineering (No. LP2104)
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Liu, G., Nong, X., Kou, Y. et al. Assessment of typhoon storm surge disaster scale based on expansion model. J. Ocean. Limnol. 41, 518–531 (2023). https://doi.org/10.1007/s00343-022-2051-z
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DOI: https://doi.org/10.1007/s00343-022-2051-z