An enhanced SMA based SCS-CN inspired model for watershed runoff prediction |
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| Authors: | S Verma S K Mishra A Singh P K Singh R K Verma |
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| Institution: | 1.Environmental Engineering and Management Group,National Institute of Industrial Engineering-Mumbai,Mumbai,India;2.Department of Water Resources Development and Management,Indian Institute of Technology,Roorkee,India;3.Water Resources Systems Division,National Institute of Hydrology,Roorkee,India;4.National Mission of Himalayan Studies,G. B. Pant National Institute of Himalayan Environment and Sustainable Development,Almora,India |
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| Abstract: | Incorporation of initial soil moisture (V 0) in the Soil Conservation Service Curve Number (SCS-CN) methodology helps to avoid the sudden jumps in Curve Number (CN) and, in turn, in computed runoff. It invoked the development of an enhanced (yet simple) Soil Moisture Accounting (SMA) procedure-based-SCS-CN inspired model, by incorporating initial moisture (V 0). Its performance is tested using a dataset of 152 small to large watersheds of USDA (total 38,169 storm events), and compared with original SCS-CN method, Mishra and Singh (Acta Geophys Polon 50(3):457–477, 2002), Michel et al. (Water Resour Res 41(2):W02011, 2005) and Singh et al. (Water Resour Manag 29(11): 4111–4127, 2015) model using four statistical indices (RMSE, R 2, PBIAS and NSE) and rank grading system (RGS). The proposed model scores highest (= 691 marks out of maximum 2280 marks) (Rank I) followed by Singh et al. (Water Resour Manag 29(11):4111–4127, 2015) model with 642 marks (Rank II), Michel et al. (Water Resour Res 41(2):W02011, 2005) model with 376 marks (Rank III) and Mishra and Singh model with 362 marks (= Rank IV). The original SCS-CN model, however, performs the poorest of all with 209 marks (Rank V). |
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