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为解决传统极值分布的尾部趋于零的速度快而导致的对海洋观测极值数据的尾部拟合不足的问题，本文基于组合模型的思想构建了一系列用于推算海洋环境设计参数的极值拓展模型。该系列模型利用积分变限函数融合了对数据尖峰拟合较好的经典极值分布和对数据厚尾拟合良好的Pareto分布的特征，可以同时拟合数据的“尖峰”和“厚尾”。利用该系列模型对广东汕尾1990—2012年间的增水数据进行分析，通过与传统极值模型的拟合效果进行对比，得到拟合数据的最佳模型为Gumbel-Pareto极值拓展模型。应用最佳拟合模型推算汕尾不同重现期下的增水值，为广东汕尾的海洋工程建设与安全分析提供参考。
Abstract：In order to solve the problem that the tail of the traditional extreme value distribution tends to zero quickly, which leads to the insufficient tail fitting of Marine observation extreme value data, this paper constructs a series of extreme value extension models for calculating the design parameters of Marine environment based on the idea of combinative model. This series of models use integral variable limit function to integrate the characteristics of classical extreme value distributions which fit the peak of data well and Pareto distribution which fits the thick tail of data well, which can fit the “peak” and “thick tail” of data simultaneously. This series of models was used to analyze the surge data from 1990 to 2012 in Shanwei of Guangdong Province. By comparing the fitting effect with the traditional extreme value model, the best model of fitting data is Gumbel-Pareto extreme value extension model. The optimal fitting model is used to calculate the surge value of Shanwei in different recurrence periods, which provides reference for the construction and safety analysis of ocean engineering.
[1] Chen B Y,Kou Y,Wang Y F,et al.Analysis of storm surge characteristics based on stochastic process[J].Aims Mathematics,2021,6(2):1177-1190.
[2] Liu G L,Chen B Y,Wang L P,et al.Wave height statistical characteristic analysis[J].Journal of Oceanology and Limnology,2019,37(2):448-460.
[3] Wang L P,Huang G L,Chen Z S,et al.Risk analysis and assessment of overtopping concerning sea dikes in the case of storm surge[J].China Ocean Engineering,2014,28(4):479-487.
[4] 刘妙品，姚琴.汕尾市海洋经济发展规划评估与展望[J].合作经济与科技，2022(11):16-18.Liu M P,Yao Q.Evaluation and prospect of marine economy development planning of Shanwei City[J].Cooperative Economy and Technology,2022(11):16-18.
[5] 殷玉齐，侯一筠，冯兴如，等.汕尾市引发灾害性海浪的热带气旋特征研究[J].海洋与湖沼，2021,52(1):66-74.Yin Y Q,Hou Y J,Feng X R,et al.Study on the characteristics of tropical cyclones causing catastrophic waves in Shanwei City[J].Oceans and Lakes,2021,52(1):66-74.
[6] 董胜，陶山山，赵玉良.海岸与海洋工程多种海洋环境动力要素联合设防标准研究[J].海岸工程，2022,41(4):412-427.Dong S,Tao S S,Zhao Y L.Research on joint fortification standard of various marine environmental dynamic elements in coastal and ocean engineering[J].Coastal Engineering,2022,41(4):412-427.
[7] Gumbel E J.Statistics ofextremes[J].Empire Survey Review,2011,15(114):187-190.
[8] Pavia E G,O′Brien J J.Weibull statistics of wind speed over the ocean[J].Journal of Applied Meteorology,2010,25(10):1324-1332.
[9] Liu G L,Cui K,Jiang S,et al.A new empirical distribution for the design wave heights under the impact of typhoons[J].Applied Ocean Research,2021,111:102679.
[10] Liu G L,Li X,Wang J H,et al.Research on the statistical characteristics of typhoon frequency[J].Ocean Engineering,2020,209:107489.
[11] Wang L P,Xu X,Liu G L,et al.A new method to estimate wave height of specified return period[J].Chinese Journal of Oceanology and Limnology,2017,35(5):1002-1009.
[12] Chen B Y,Kou Y,Zhao D,et al.Maximum entropy distribution function and uncertainty evaluation criteria[J].China Ocean Engineering,2021,35(2):238-249.
[13] 史道济.实用极值统计方法[M].天津：天津科学技术出版社，2006.Shi D J.Practical Statistical Method of Extreme Value[M].Tianjin:Tianjin Science and Technology Press,2006.
[14] Wang L P,Chen B Y,Zhang J F,et al.A new model for calculating the design wave height in typhoon-affected sea areas[J].Natural Hazards,2013,67(2):129-143.
[15] Liu G L,Gao Z K,Chen B Y,et al.Extreme values of storm surge elevation in Hangzhou Bay[J].Ships and Offshore Structures,2020,15(4):431-442.
[16] Feng J,Jiang W.Extreme water level analysis at three stations on the coast of the Northwestern Pacific Ocean[J].Ocean Dynamics,2015,65(11):1383-1397.
[17] Kim T,Hwang K,Kwon H.Stochastic analysis of typhoon-induced storm surge in the coastal area of the Korean Peninsula:Inference from a Nonstationary,Bayesian,Poisson,Generalized Pareto Distribution[J].Journal of Coastal Research,2018(85):896-900.
[18] Chen B Y,Liu G L,Wang L P,et al.Determination of water level design for an estuarine city[J].Journal of Oceanology and Limnology,2019,37(4):1186-1196.
[19] Ross E,Sam S,Randell D,et al.Estimating surge in extreme North Sea storms[J].Ocean Engineering,2018,154:430-444.
[20] Ross E,Randell D,Ewans K,et al.Efficient estimation of return value distributions from Non-Stationary marginal extreme value models using Bayesian inference[J].Ocean Engineering,2017,142:315-328.
[21] Mazas F,Hamm L.A multi-distribution approach to POT methods for determining extreme wave heights[J].Coastal Engineering,2011,58(5):385-394.
[22] 马志迁.广义Pareto分布的参数估计及在水文领域的应用[D].石家庄：河北科技大学，2018.Ma Z Q.Parameter Estimation of Generalized Pareto Distribution and Its Application in Hydrology[D].Shijiazhuang:Hebei University of Science and Technology,2018.
[23] Alzaatreh A,Lee C,Famoye F.A new method for generating families of continuous distributions[J].Metron,2013,71(1):63-79.
[24] Kim Yoonji,Kim Geunbae,Jung Unseob,et al.Blind interleaver parameter estimation using Kolmogorov-Smirnovtest[J].The Journal of Korean Institute of Communications and Information Sciences,2020,45(3):584-592.
[25] Marek Szyd?owski,Adam Krawiec,Aleksandra Kurek,et al.AIC,BIC,Bayesian evidence against the interacting dark energy model[J].The European Physical Journal C,2015,75:5.
基本信息:
DOI：10.16441/j.cnki.hdxb.20230031
中图分类号:P75;P731
引用信息:
[1]刘桂林,田雨航,宋时春,等.基于极值拓展模型的广东汕尾增水推算[J],2023,53(10):38-44.DOI:10.16441/j.cnki.hdxb.20230031.
基金信息:
国家自然科学基金项目(52071306)资助~~
2023-02-01
2023
2023-02-02
2023
1