Accurate prediction of water infiltration rate is very important for programming the soil and water conservation practices in catchments .In this study, the efficiency of infiltration rate models was investigated in three land uses consist of dry-farming, irrigated farming and pasture lands in Tahamchai catchment (20 locations with three replications) in north west of Zanjan province, Iran. The efficiency of models was assessed using the measured data based on the determination coefficient (R2), root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). Results indicated that there is obvious variation in water infiltration rate in different land uses, so that the highest value was in dry-farming lands (16.6 cm h-1) and the lowest value was in pastures (5.4 cm h-1). Among the proposed models, the Kostiakove’s equation showed the highest R2 (0.99), the lowest error (RMSE= 0.01 cm h-1) and the highest NSE (0.99) in pasture. Philip’s equation appeared to be more efficient in the rainfed-farming and irrigated farming lands with R2=0.99, RMSE ranging from 0.14 to 0.22 and NSE=0.99. Although, the Green-Ampt’s equation was fitted relatively well to the measured data (R2= 0.94), its error index (RMSE= 2.32 cm h-1) was relatively high, indicating the least efficiency among the models. The GA model showed higher estimation error for higher infiltration rate values which occur mostly at initial times of water infiltration process. Therefore, regarding the higher correlations of the Kostiakove’s and Philip’s equations with the measured data, these two models are recommended for predicting water infiltration rate in different land uses of Tahamchai catchment.
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