Curve‐Number/Green–Ampt mixed procedure for streamflow predictions in ungauged basins: Parameter sensitivity analysis |
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| Authors: | S Grimaldi A Petroselli N Romano |
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| Institution: | 1. Department for Innovation in Biological, Agro‐food and Forest systems (DIBAF) ‐ University of Tuscia, , 01100 Viterbo, Italy;2. Honors Centre of Italian Universities (H2CU) ‐ The Sapienza University of Rome, , 00184 Roma, Italy;3. Department of Mechanical and Aerospace Engineering ‐ Polytechnic Institute of New York University, , Brooklyn, NY, 11201, USA;4. Department of Sciences and Technologies for Agriculture, Forestry, Nature, and Energy (DAFNE) ‐ University of Tuscia, , 01100 Viterbo, Italy;5. Department of Agriculture, Division of Agricultural, Forest and Biosystems Engineering ‐ University of Naples Federico II, , 80055 Portici, Italy |
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| Abstract: | A procedure combining the Soil Conservation Service‐Curve Number (SCS‐CN) method and the Green–Ampt (GA) infiltration equation was recently developed to overcome some of the drawbacks of the classic SCS‐CN approach when estimating the volume of surface runoff at a sub‐daily time resolution. The rationale of this mixed procedure, named Curve Number for Green–Ampt (CN4GA), is to use the GA infiltration model to distribute the total volume of the net hyetograph (rainfall excess) provided by the SCS‐CN method over time. The initial abstraction and the total volume of rainfall given by the SCS‐CN method are used to identify the ponding time and to quantify the hydraulic conductivity parameter of the GA equation. In this paper, a sensitivity analysis of the mixed CN4GA parameters is presented with the aim to identify conditions where the mixed procedure can be effectively used within the Prediction in Ungauged Basin perspective. The effects exerted by changes in selected input parameters on the outputs are evaluated using rectangular and triangular synthetic hyetographs as well as 100 maximum annual storms selected from synthetic rainfall time series. When applied to extreme precipitation events, which are characterized by predominant peaks of rainfall, the CN4GA appears to be rather insensitive to the input hydraulic parameters of the soil, which is an interesting feature of the CN4GA approach and makes it an ideal candidate for the rainfall excess estimation at sub‐daily temporal resolution at ungauged sites. Copyright © 2013 John Wiley & Sons, Ltd. |
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| Keywords: | rainfall– runoff modeling SCS‐CN method infiltration Green– Ampt equation ungauged basin sensitivity analysis |
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