Flood Frequency Analysis Using Archimedean Copula Functions Based on Annual Maximum Series (Case Study:Arazkuseh Hydrometric Station in Golestan Province)

Document Type : Original Article


1 M.ScGraduated Studentof Water Resources Engineering,Gorgan University ofAgricultural Sciences and Natural Resources., Gorgan., Iran

2 Associate Prof., Dept. of Water Engineering, Gorgan University of Agricultural Sciences and Natural Resources., Gorgan., Iran

3 Assistant professor of Water Engineering Department, water and soil Engineering college, Gorgan Agriculture Science and Natural Resource University., Gorgan., Iran


Univariate frequency analysis of hydrological events has some shortcomings caused by the lack of taking into account all characteristics of such events. Therefore, bivariate frequency analysis  of hydrologic events such as flood can be useful in hydraulic design of structures and water resources management. The peak discharge and volume of flood are two important parameters in design of structures, thus, Archimedean copula functions were used for analysis of dependence structure between peak discharges and flood volumes. The time series of discharge for Arazkusehhydrometric station for a period of 40 years was constructed based on annual maximum (AM) discharge in daily scale. This station area is 1678.1 km2.The results showed that Gumbel extreme value copula was the best choice for fitting to data. Beased on design requirements, one can choose joint return period in "and", "or" and "conditional". For example, considering univariate frequency analysis results the return period of peak discharge equal to 50 years, while for a same value of peak discharge and volume in "and", "or" condition, the joint return periods are 72 and 38 respectively.  The return period of "or" case was less than univariateand the highest value was belong to "and" case. This shows that planning or design based on "or" case is more confident, because results to larger values of peak discharge and volume quantile for the same value or univariate return period. 


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Volume 8, Issue 2 - Serial Number 46
November and December 2014
Pages 353-365
  • Receive Date: 03 December 2013
  • Revise Date: 09 April 2014
  • Accept Date: 07 May 2014
  • First Publish Date: 22 May 2014