Analysis of storm surge characteristics based on stochastic process

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Abstract

Most of the offshore projects will be impacted by storm surge, especially in the sea area where typhoons are frequent, and storm surge disasters are inevitable. The establishment of a theoretical distribution model of the number of typhoon occurrences and random waves is of great theoretical and practical significance for the study of the number of storm surge impacts and damage to marine engineering as well as the safety evaluation of offshore engineering. Based on stochastic process theory, this paper discusses the effects of the number of typhoon occurrences and typhoon intensity on wave displacement and water level by constructing a compound Poisson process model of typhoon frequency and typhoon intensity. The limitations of using typhoon intensity and wave height as random variables in the marine environment are improved. The average cumulative damage, reliability, and average service life of marine works were analyzed by marine works reliability analysis and a compound Poisson process of the number of storm surge impacts on marine works and the damage caused to marine works by each impact. The results show that the statistical theoretical model and reliability analysis of the storm surge hazard factors based on the stochastic process covers the original extreme value statistical distribution model, and can determine the parameters in the model according to different thresholds in line with the objective facts, and then deduce the design return level, while the deduced return level still has a certain degree of reliability in the case of short or missing data. Therefore, the stochastic process-based model of the imputed level of design parameters for the marine environment provides a new option for marine engineering design and risk management.

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Chen, B., Kou, Y., Wang, Y., Zhao, D., Liu, S., Liu, G., … Han, X. (2021). Analysis of storm surge characteristics based on stochastic process. AIMS Mathematics, 6(2), 1177–1190. https://doi.org/10.3934/math.2021072

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