Joint probability distribution and risk identification of extreme precipitation based on R-Vine Copula function

被引：0
|
作者：
Zeng W. [1 ,2 ]
Xu M. [3 ]
Song S. [1 ,2 ]
Wu H. [1 ,2 ]
机构：
[1] College of Water Resources and Architectural Engineering, Northwest A and F University, Yangling
[2] Key Laboratory for Agricultural Soil and Water Engineering in Arid Area of Ministry of Education, Northwest A and F University, Yangling
[3] College of Economics and Management, Northwest A and F University, Yangling
来源：
Water Resources Protection | 2022年 / 38卷 / 06期
关键词：
Extreme precipitation factor; Henan Province; Joint probability distribution; R-Vine Copula function; Risk identification;
D O I：
10.3880/j.issn.1004-6933.2022.06.013
中图分类号：
学科分类号：
摘要：
On the basis of optimization of edge distribution function, a joint probability distribution model of extreme precipitation based on R-Vine Copula function is constructed with conditional Copula function and Vine graph structure. The model is verified and compared with the measured data of four meteorological stations in Henan Province. The risk of extreme precipitation is identified with extreme precipitation factors. The results show that this model is able to discriminate the tail characteristics among variables, with statistical characteristics, such as Kendall and Spearman correlation coefficients of the original sequences, maintained. The overall accuracy of this joint probability distribution model of extreme precipitation is better than that based on C-Vine Copula function. The probability distributions of annual precipitation and precipitation intensity, maximum 1d precipitation and maximum 5d precipitation in Henan Province are closely related. The influence of each index on the joint probability density shows spatial heterogeneity. © 2022, Editorial Board of Water Resources Protection. All rights reserved.
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页码：96 / 103
页数：7
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