SCS模型在鲁中南低山丘陵区径流估算中的 优化及应用评价

doi:10.16843/j.sswc.2019.02.014

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Abstract [Background] Runoff prediction is the basis of soil and water loss monitoring and prediction, and selecting suitable runoff prediction models for different regions can provide convenience for better soil and water conservation work in the river basin.[Methods] Based on the principle of SCS model, this study discussed the method of forecasting runoff for different land use types in the mid-southern hilly region of Shandong province. This study selected the runoff plots of four land use types (sloping farmland, level terrace, bare land and grassland) in the small watershed as the research object. Based on the data of runoff and rainfall observed in 2012-2015 years in the Yaoxiang small watershed, the initial loss rate and runoff curve number of the standard SCS-CN model and its modified form (MS model) in this area were calibrated by using the particle swarm optimization (PSO), then the optimized parameters were taken into the original model for runoff prediction, and the application results of initial model was compared with the optimized model. The measured runoff and other data in 2016 year were used to verify the models. Then the pass percent of model, the Nash-Sutcliffe efficiency coefficient (NSE), RMSE and the coefficient of determination (R²) were selected for evaluation indicators, and the model evaluation system was established based on the principle of TOPSIS method to quantitatively evaluate the application effect of different models.[Results] The application effect of standard SCS-CN model in four land use types was not applicable, and all evaluation indexes were deviated to a greater degree. The particle swarm optimization in 1stOpt software was used to optimize the standard SCS-CN model and MS model, forming the SCS-CN_Les model and MS_Les model, and the initial loss rate and runoff curve number in the optimized model had certain validity. In the model rate period and the model validation period, the application results of SCS-CN_Les model and MS_Les model were all fine, and the evaluation indexes of each model were higher than that of standard SCS-CN model. The TOPSIS comprehensive evaluation system was established for analysis. The result showed that the application effect of the MS_Les model in the level terrace was the best, the qualified rate of the model was 100%, the NSE value was 0.70, the coefficient of determination was 0.77, and the RMSE value was 0.87. And followed by was the SCS-CN_Les model in the grassland, the qualified rate of the model also was 100%, the NSE value was 0.53, the coefficient of determination was 0.83, and the RMSE value was 1.03.[Conclusions] The results show that MS_Les model may be applied to forecast the actual runoff to some extent in the level terrace in the mid-southern hilly region of Shandong province, and relevant results can provide theoretical reference for follow-up research of runoff prediction in this area.

Key words： SCS model land use types parameter optimization evaluation mid-southern hilly region of Shandong province

Received: 12 April 2018

PACS:	S157.1
	P334+.92

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	Articles by authors
	LI Yiran
	ZHANG Xinggang
	CHENG Tiantian
	ZHANG Yongtao

Cite this article:

LI Yiran,ZHANG Xinggang,CHENG Tiantian, et al. Optimization of SCS model to estimate runoff in the mid-southern hilly region of Shandong province and evaluation of applying it[J]. SSWC, 2019, 17(2): 112-120.

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http://journal12.magtechjournal.com/Jweb_stbc/EN/10.16843/j.sswc.2019.02.014 OR http://journal12.magtechjournal.com/Jweb_stbc/EN/Y2019/V17/I2/112

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