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水力发电学报 ›› 2019, Vol. 38 ›› Issue (3): 75-82.doi: 10.11660/slfdxb.20190308

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基于Copula函数的大坝洪水漫顶风险率计算

  

  • 出版日期:2019-03-25 发布日期:2019-03-25

Estimation of dam overtopping risk rate based on Copula functions

  • Online:2019-03-25 Published:2019-03-25

摘要: 洪水漫顶风险率分析计算对于大坝风险管理具有重要意义。本文基于Copula函数计算大坝洪水漫顶风险率,并分析不同Copula函数及峰量相关性对漫顶风险率的影响。清江流域隔河岩水库实例表明:最优的Gumbel-Hougaard Copula函数能较好地描述洪峰、洪量的上尾相关性,计算的洪水漫顶风险率为3.79×10-5,而Frank和Clayton Copula函数得到的风险率明显偏低。随着洪峰、洪量相关系数的增加,洪水漫顶风险率也增加。假设峰量相互独立的情况下洪水漫顶风险率被低估,而完全相关的情况下则被高估。基于Copula函数的两变量统计方法能够有效捕捉洪峰、洪量的实际相关关系,得到的风险率更加合理,为大坝洪水漫顶风险率分析提供科学依据。

关键词: 大坝洪水漫顶, 风险分析, Copula函数, 蒙特卡罗模拟, 隔河岩水库

Abstract: Flood overtopping risk rate is a key factor in reservoir operation and dam safety management. This paper estimates this factor based on Copula functions and analyzes its dependency on the selection of these functions and the correlation between flood peak and volume. We apply the Gumbel-Hougaard Copula function to an analysis of the Geheyan reservoir in the Qing River basin, and demonstrate that its optimal form can better describe the upper tail dependence between flood peak and flood volume, while the Frank and Clayton Copula functions underestimate the risk rate significantly. For this reservoir, the estimated flood overtopping risk rate is 3.79×10-5, but it increases as the correlation between flood peak and volume increases. In the cases of full correlation it is overestimated while underestimated in the independence cases. Our bivariate statistical approach based on Copula functions, through effectively capturing the dependence between flood peak and volume, improves the estimation of overtopping risk rate and would be useful for overtopping risk analysis.

Key words: dam flood overtopping, risk analysis, Copula function, Monte Carlo simulation, Geheyan reservoir

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