Development of Analytical-Probabilistic Models for Estimating Urban Storm Water Runoff

The aim of this research is to evaluate some methods of developing analytical-probabilistic models in runoff volume estimation and it is shown that analytical models can be obtained with varying degrees of complexity based on different rainfall-runoff conversions. In this research, calibration and validation of analytical models were evaluated following a hybrid method. The efficiency of different types of rainfall-runoff transformations was measured in the western part of Kerman. The results of the analytical model for the observed and simulated runoff were compared with the storm management model (SWMM).According to outputs if for a runoff coefficient a value is considered in the range of 0.6-0.7, the first-order analytic-probabilistic model yields close results to the simulation ones that are obtained from the storm management model with less relative difference.In order to evaluate the reliability of the analytical model performance, with considering constant value for runoff coefficient, pf permeable zone, area of the impervious zone of the basin. Was gradually increases the results indicate that with the gradual increase of the permeability of the basin, the effect of the permeable area runoff coefficient on the annual runoff volume. Is less sensitive Using this model, a good accommodation between observational and computational data. Was obtained Analytical-probabilistic models due to less computations than continuous simulation models can be used as a continuous simulation model for analyzing urban runoff systems.