Sensitivity analysis and impact quantification of the main factors affecting peak discharge in the SCS curve number method: An analysis of Iranian watersheds

Abstract

The SCS curve number method is the most commonly used method for the estimation of peak discharge in a watershed. This method is used in numerous complex models such as SWAT, HEC-HMS, EPIC, and AGNPS, but has never been analyzed using the sensitivity analysis, to the best of the authors’ knowledge. The present study deals with the effects of the time of concentration time, watershed area, amount of rainfall at different return periods and the α-coefficient on the nature of the SCS curve number method in the estimation of peak discharge and its reaction to change in the input parameters (coefficient of estimation for getting the time of effective rainfall, which is usually equal to 0.133). Results indicate the effective role of CN on the input to the peak discharge model. The sensitivity of the model, during the estimation of peak discharge, increases following the increase in the return period. The sensitivity analysis of SCS curve number method was performed via the MATLAB program. Due to the increased application of MATLAB program for general basin conditions, it can be applicable in special watersheds to find out the parameter(s) having a significant impact on peak discharge.