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Flood risk analysis based on nested copula structure in Armand Basin, Iran

Amini Sasan, Bidaki Rafat Zare, Mirabbasi Rasoul, Shafaei Maryam

Acta Geophysica

2022

Vol. 70, no 3

1385--1399

Merging different food characteristics in a distribution function is provided by copula structures. In this study, the nested copula structure was used to construct a triradiate distribution of food duration (D), peak (P), and volume (V). The required data were obtained by screening the food events recorded at Armand Gauging Station, Iran. The characteristics of selected 63 food events (1993–2018) were extracted and the best marginal distribution function of each was determined by Kolmogorov–Smirnov test. Then the fitness of six different copula functions (Frank, Clayton, Joe, Gumbel–Hougaard, Gaussian and Student’s t were examined for creating the joint distribution function. The best fitted marginal distribution is Johnson SB, for food duration, and Lognormal (3p), for food peak and food volume. The best-fitted function for creating bivariate and trivariate distributions of food characteristics in Armand Basin is Frank copula. In the next phase, the bivariate and trivariate joint return periods (at two states of AND, OR), Kendall return period and conditional return periods were calculated. The results revealed that the conditional return period of one food variable given two other food variables is greater than the corresponding values for the conditional return period of two food variables given the third food variable.