جستجوی مقالات مرتبط با کلیدواژه « تحلیل فراوانی چند متغیره » در نشریات گروه « آب و خاک »

Rainfall as an input factor for flood modeling and design of hydraulic structures has great importance. Rainfall frequency analysis is a major task for water resources planners and hydrologists. Considering this fact that hydrological phenomena including rainfall are multivariate (intensity-depth-duration) terms, joint modeling of several random variables would be required. Considering the importance of two rainfall characteristics including intensity and depth in flood management and design of hydraulic structures, in this research, copula function was used for the analysis of dependency structure of these two variables. For this purpose, 40 years recorded rainfall data in Minoodasht hydrometry station located on Chehelchay River in Gorganrood watershed was used. In order to determine the allowable risk of structure failure against rainfall, its univariate return period was compared with estimated joint return period through selected copula. In this study, Frank copula led to the best results in bivariate modeling of rainfall intensity and depth, according to goodness of fit tests. Associated return period was estimated by Frank copula to improve allowable structural risk estimation in comparison to univariate return period. For example, an incident with the intensity of rainfall equal to 45.43 mm/h and its depth of 168.61 mm for 100 years’ univariate return period is 53 years in "or" case and 954 years in "and" case for bivariate joint return period. Comparison of bivariate analysis with univariate analysis indicates the difference the outcome of these tow methods. As due to the lack of consideration of all effective features in the phenomenon, the univariate analysis of hydrological events would not be a comprehensive analysis, therefore, the multivariate analysis of hydrological events is recommended.

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.