Modeling of Rainfall - Runoff Kashkan River Catchment Based on Statistical Models

Surface runoff form rainfall to that part is called the gradient along the surface of the earth now and into the flow of surface or subsurface of the basin is out. Hydrological models that can be structural according to operating features of the basin affect the desired interaction phenomenon and it's with a reasonable approximation to show. River Basin of Kashkan under basin Karkheh basin is important. For modeling "Rainfall, runoff," statistical data from 14 storms during the period 1389-1360, the following is a watershed moment Poldukhtar that the water has been used. Then, based on five characteristics as the independent variable and seven Haytvgraph 14 storm hydrograph characteristics as dependent variables, a multivariate regression to assess Account different models for Rainfall runoff modeling has been. And the results showed that among a variety of methods, a multivariate regression, linear methods, explained, and power have the most decisive for modeling Rainfall - runoff are. Then, based on multiple regression to provide a regression model Rainfall - runoff discussed.. the multivariate regression modeling has been at tempted models for evaluating models Rainfall - Runoff using A number of criteria and indicators in clouding, correlation coefficient, standard error, the relative error of estimation and verification, the mean absolute percentage error, Relative mean squared, error squares Square of the mean square error, the average absolute error is used. R^2 Obtained show that 0.796 percent of maximum intensity of storm runoff in the basin Kashkan related to three factors (MIS), the amount of excess Rainfall (ASP) and duration of excess Rainfall (DSP) is.