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J4  2009, Vol. 43 Issue (6): 1107-1111    DOI: 10.3785/j.issn.1008-973X.2009.06.024
    
Impact analysis for rainfall depthsimulation of different durations through several Copulas
XU Yue-ping, TONG Yang-bin, FU Qiang, ZHU Rong
(School of Architecture and Civil Engineering, Zhejiang University, Hangzhou 310027, China)
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Abstract  

To reduce uncertainty in hydrological frequency analysis, four different Copulas were used to model the bivariate distribution functions for rainfall depths of various durations with generalized extreme-value distribution and generalized logistic distribution as marginals. The simulation  showed that the Farlie-Gumbel-Morgenstern and Gaussian Copulas can model the dependence between variables reasonably, while Gumbel and Clayton Copulas did less well. The conditional probabilities of rainfall depth combinations for different durations can be obtained. The  Copula method to calculate design rainstorm for different return periods is  reasonable and provides a new alternative to traditional frequency analysis.



Published: 01 June 2009
CLC:  TV122.5  
Cite this article:

HU Ru-Ping, TONG Yang-Bin, FU Jiang, et al. Impact analysis for rainfall depthsimulation of different durations through several Copulas. J4, 2009, 43(6): 1107-1111.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2009.06.024     OR     http://www.zjujournals.com/eng/Y2009/V43/I6/1107


几种Copulas模拟不同历时降雨量的影响分析

为减小水文频率分析中的不确定性,采用4种不同的Copulas联结函数来模拟不同历时降雨量的相关关系,并得出边际分布分别为广义极限和广义逻辑斯特的两元联合分布.模拟结果表明,Farlie-Gumbel-Morgenstern和Gaussian Copulas能较好地模拟变量之间的相关关系,而Gumbel和Clayton Copulas则相对较差.通过计算Copula的条件分布可以得到不同历时降雨量组合的概率.根据Copula联结函数来推求不同重现期的设计暴雨,可以同时考虑不同历时降雨量的相关性,该方法科学合理,为水文频率分析方法提供了新的思路.

[1] YUE S. A bivariate gamma distribution for use in multivariate flood frequency analysis [J]. Hydrological Process, 2001, 15(6): 10331045.
[2] YUE S, RASMUSSEN P. Bivariate frequency analysis: discussion of some useful concepts in hydrological application [J]. Hydrological Process, 2002, 16(14): 28812898.
[3] 熊立华, 郭生练. 两变量极值分布在洪水频率分析中的应用研究[J]. 长江科学院院报, 2004, 21(2): 3537.
XIONG Li-hua, GUO Sheng-lian. Application study of a bivariate extremal distribution in flood frequency analysis [J]. Journal of Yangtze River Scientific Research Institute, 2004, 21(2): 3537.
[4] 肖义,郭生练,熊立华,等. 一种新的洪水过程随机模拟方法研究[J]. 四川大学学报:工程科学版, 2007, 39(2):5560.
XIAO Yi, GUO Sheng-lian, XIONG Lihua. A new random simulation method for constructing synthetic flood hydrographs [J]. Journal of Sichuan University:Engineering Science Edition, 2007, 39(2):5560.
[5] 许月萍, 李佳, 曹飞凤,等. Copula在水文极限事件分析中的应用[J]. 浙江大学学报:工学版,2008, 42(7):11191122.
XU Yue-ping, LI Jia, CAO Fei-feng,et al. Applications of Copula in hydrological extreme analysis\[J\]. Journal of Zhejiang University :Engineering Science, 2008, 42(7):11191122.
[6] NELSEN R B. An introduction to copulas lecture notes in statistic [M]. Berlin Heidelberg: Springer,1999.
[7] CAPRAP, FOUGRES A L, GENEST C. Bivariate distributions with given extreme value attractor [J]. Journal of Multivariate Analysis, 2000, 72(1): 3049.
[8] GENEST C, FAVRE A C. Everything you always wanted to know about copula modeling but were afraid to ask [J]. Journal of Hydrologic Engineering, 2007, 12(4): 347368.
[9] RENARD B, LANG M. Use of a Gaussian copula for multivariate extreme value analysis: some case studies in hydrology [J]. Advances in Water Resources, 2007, 30(4): 897912.
[10] ZHANG L, SINGH V P. Bivariate flood frequency analysis using the copula method [J]. Journal of Hydrologic Engineering, 2006, 11 (2): 150164.
[11] GENEST C, BOIES J C. Detecting dependence with Kendall Plots [J]. American Statistical Association, 2003, 57(4):110.
[12] HOSKING J R M, WALLIS J R. Regional frequency analysis—an approach based on L-moments [M]. Cambridge: Cambridge University Press, 1997.

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