Evaluation of Rainfall-Runoff-Retention Model (3RM) in Kassilian and Darjazin Watersheds

Document Type : Research Paper

Authors

1 M.Sc. Graduated, Department of Water Engineering, Faculty of Agriculture, University of Shahrekord, Shahrekord, Iran.

2 Professor, Department of Water Engineering, Faculty of Agriculture, University of Shahrekord, Shahrekord, Iran.

Abstract

Hydrological models make it possible to simulate the rainfall-runoff process, the amount of runoff from rainfall in areas without statistics or with incomplete statistics. One of the most practical and globally accepted rainfall- runoff model provided by American Soil Conversation Service, (SCS) known as SCS-CN where CN refer to Curve Numbers based on soil hydrological conditions. In this research, Rainfall-Runoff-Retention Model (3RM) was used introduced the new concept for rainfall Interceptions as Antecedent Effective Retention (IER) instead of the Antecedent Moisture Content (AMC) and calculating it by water balance method. SCS-CN model with this new revision were applied in Darjazin (semi-arid climate) and Kassilian (very humid climate) catchments in Iran. The results of the study showed that Darjazin watershed with 29.38 persent rock cover (D) and 3.27 persent hydrologic soil group (A) with a holding potential of 20.66 mm and Kassilian watershed with forest cover 77 persent and rock mass cover 0.0 persent has a lot of retention potential (51.11 mm). The value of α (ratio of initial retention to potential retention) was obtained between 0.05 and 0.13 in different basins. Also, the results of model fitting on rainfall-runoff data showed that the evaluation indices including coefficient of determination R2, RMSE, NRMSE and NSE for predicting runoff in Darjazin catchment (0.998, 0.439, 0.029, and 0.998) respectively, while the same indicators for the Kassilian watershed are (0.867, 0.264, 1.009 and 0.859) respectively. The results show that the model has an acceptable ability to predict runoff and actual retention in all two watersheds.

Keywords

Main Subjects


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