Evaluating Efficiency of Analytical Hierarchy Process for Estimating Runoff Coefficient in Amameh Watershed

One of the components of watershed water balance, which is very important in watershed management and water resources management, is runoff. Appropriate estimation of runoff value requires determining Runoff Coefficient (RC). This study was conducted to evaluate the effectiveness of multi-criteria decision-making methods in order to estimate the RC in Amameh watershed, Iran. To do this, at first, slope angle, vegetation (land use), hydrologic soil groups, maximum daily rainfall and area of the study area layers was entered into geographic information system (GIS). After performing the necessary processing on the layers, it were converted to raster formats based on the study area boundary. In the next step, the analytical hierarchy process (AHP) structure was established based on the research purpose. The weighted index values for each layer and their different classes were then determined based on the weighted index of the AHP by Expert Choice software. Based on these five criteria, three models were made. Therefore in model 1, slope angle, vegetation (land use) and  hydrologic soil groups; in model 2, maximum daily rainfall, area of the study area and hydrologic soil groups and in model 3,  soil infiltration and area of the study area were used. The estimated RCs were then estimated based on weight for each criteria in each model. The estimated RC with the observed RC, which have been measured using the Kamphorst rainfall simulator at 60 points in different land uses with an intensity of 60 mm hr-1 for 90 min, were compared. The obtained results showed that the second model with Nash-Sutcliffe Efficiency (NSE) coefficient of 0.59 and root mean squares error (RMSE) of 0.363 had a better efficiency than the other two models. In general, the results showed that the AHP method due to its simplicity, the application of qualitative and quantitative criteria simultaneously and the ability to assess compatibility in judgments can be used in the study of RC.