[1]DENG Jingcheng,GAO Peng,MU Xingmin,et al.Study on Calibrating Parameters of SCS Model in Loess Area Under Simulated Rainfall[J].Research of Soil and Water Conservation,2018,25(05):205-210.
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
25
Number of periods:
2018 05
Page number:
205-210
Column:
Public date:
2018-09-06
- Title:
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Study on Calibrating Parameters of SCS Model in Loess Area Under Simulated Rainfall
- Author(s):
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DENG Jingcheng1, GAO Peng1,2, MU Xingmin1,2, ZHAO Guangju1,2, SUN Wenyi1,2, TIAN Peng1,3
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1. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A & F University, Yangling 712100, China;
2. Institute of Soil and Water Conservation, CAS and MWR, Yangling, Shaanxi 712100, China;
3. Resources and Environmental Science College, Northwest A & F University, Yangling, Shaanxi 712100, China
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- Keywords:
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SCS model; initial loss rates; runoff curve number; parameter calibration
- CLC:
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S715.55
- DOI:
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- Abstract:
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The study on runoff simulation is an important basis for the prediction and control of soil and water losses and soil erosion. The SCS model is a commonly used model of runoff calculation. The two parameters in the model, initial loss rates λ and runoff curve number CN, are important for the model to calculate the surface runoff accurately. By artificial simulated rainfall data of 22 different land use types in Yangqingchuan river basin, the initial loss rate and runoff curve number of the SCS model in this area were verified by using the method of exhaustion. The results show that:(1) the simulated runoff depth by SCS model under artificial rainfall is very large, and the simulation value is 1.1~3 mm larger than the measured value in the loess area; (2) the initial loss rate and the runoff curve number are the sensitivity parameters of the model and the sensitivity of λ is higher. (3) the optimal initial loss rate was 0.13, and the runoff curve number was 65 in the grassland; the optimum initial loss rate is 0.03, and the runoff curve is 83 in the bare land. The optimized model can better simulate the depth of runoff, RMSE and Re decrease significantly, and the Nash coefficient increases significantly.