中山大学学报自然科学版 ›› 2011, Vol. 50 ›› Issue (2): 110-115.

• 研究论文 • 上一篇    下一篇

广东西江北江洪水联合概率分布研究

陈子燊 1,刘曾美1,2,路剑飞1   

  1. (1 中山大学水资源与环境系,广东 广州510275;2 华南理工大学水利水电工程系,广东 广州510640)
  • 收稿日期:2010-09-17 修回日期:1900-01-01 出版日期:2011-03-25 发布日期:2011-03-25

Flood Joint Probability Distribution of theXijiang River and Beijiang River in Guangdong Province

CHEN Zhishen1 , LIU Zengmei1,2 ,LU Jianfei1   

  1. (1.Department of Water Resource and Environment,Sun Yatsen University,Guangzhou 510275,China;〖JP〗2 Department of Water Conservancy and Hydropower Engineering,South China University of Technology,Guangzhou 510640,China)
  • Received:2010-09-17 Revised:1900-01-01 Online:2011-03-25 Published:2011-03-25

摘要: 基于Copula函数分析了由思贤滘连通的广东西江水文站马口和北江水文站三水构成的两个样本的洪水联合概率分布特征,获得如下结论:经过优选的马口、三水洪水边缘分布可分别由P-III型和GEV表示;拟合优度检验指标表明二者的最优连接函数均为Archimedean copula类的Gumbel-Hougaard Copula;重现期介于10~500 a之间的马口、三水洪水边缘分布与联合分布的洪水设计值相对差值大约介于0.6%~1.5%之间;基于条件概率计算的两站相同设计频率洪水的遭遇概率都大于88%。

关键词: 西江北江洪水, 边缘概率分布, 联合概率分布, Copula函数, 拟合优度检验, 条件概率分布

Abstract: The characteristics of joint probability distribution of flood were analyzed between the Makou Station(MS) in Xijiang River and the Sanshui Station(SS) in Beijiang River which are connected by the Sixianjiao Channal based on Copula function Some conclusions were abtained as following: (1) Optimized marginal distributions of flood of Makou and Sanshui can be represended by the Pearson pattern Ⅲand GEV (generalized extreme value) distribution, respectively; (2) GumbelHougaard Copula was the optimal copula selected by the results of goodnessoffit test; (3) The relative differences of the special frequency design values between the marginal distribution of Makou and Sanshui floods and the joint distribution were from 0.6% to 1.5% for the return periods between 10 years and 500 years; (4) The probabilities of Makou and Sanshui meeting floods with each other were higher than 89% for the same design frequencies of two stations based on the conditional probability.

Key words: Xijiang River and Beijiang River floods, marginal probability distributions, joint probability distributions, Copula functions, goodness of fit test, conditional probability distributions

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