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首页> 外文期刊>Hydrology and Earth System Sciences >Coupling the modified SCS-CN and RUSLE models to simulate hydrological effects of restoring vegetation in the Loess Plateau of China
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Coupling the modified SCS-CN and RUSLE models to simulate hydrological effects of restoring vegetation in the Loess Plateau of China

机译:结合改进的SCS-CN模型和RUSLE模型模拟中国黄土高原恢复植被的水文效应

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摘要

Predicting event runoff and soil loss under different land covers is essential to quantitatively evaluate the hydrological responses of vegetation restoration in the Loess Plateau of China. The Soil Conservation Service curve number (SCS-CN) and Revised Universal Soil Loss Equation (RUSLE) models are widely used in this region to this end. This study incorporated antecedent moisture condition (AMC) in runoff production and initial abstraction of the SCS-CN model, and considered the direct effect of runoff on event soil loss by adopting a rainfall-runoff erosivity factor in the RUSLE model. The modified SCS-CN and RUSLE models were coupled to link rainfall-runoff-erosion modeling. The effects of AMC, slope gradient and initial abstraction ratio on curve number of SCS-CN, as well as those of vegetation cover on cover-management factor of RUSLE, were also considered. Three runoff plot groups covered by sparse young trees, native shrubs and dense tussock, respectively, were established in the Yangjuangou catchment of Loess Plateau. Rainfall, runoff and soil loss were monitored during the rainy season in 2008-2011 to test the applicability of the proposed approach. The original SCS-CN model significantly underestimated the event runoff, especially for the rainfall events that have large 5-day antecedent precipitation, whereas the modified SCS-CN model was accurate in predicting event runoff with Nash-Sutcliffe model efficiency (EF) over 0.85. The original RUSLE model overestimated low values of measured soil loss and underpredicted the high values with EF values only about 0.30. In contrast, the prediction accuracy of the modified RUSLE model improved with EF values being over 0.70. Our results indicated that the AMC should be explicitly incorporated in runoff production, and direct consideration of runoff should be included when predicting event soil loss. Coupling the modified SCS-CN and RUSLE models appeared to be appropriate for evaluating hydrological effects of restoring vegetation in the Loess Plateau. The main advantages, limitations and future study scopes of the proposed models were also discussed.
机译:预测不同土地覆盖下的事件径流和土壤流失对于定量评估黄土高原植被恢复的水文响应至关重要。为此,该地区广泛使用了土壤保护服务曲线编号(SCS-CN)和修订的通用土壤流失方程(RUSLE)模型。这项研究在SCS-CN模型的径流生产和初始提取中纳入了前期水分条件(AMC),并通过在RUSLE模型中采用降雨径流侵蚀率因子来考虑径流对事件土壤流失的直接影响。修改后的SCS-CN模型和RUSLE模型被耦合到链接降雨径流侵蚀模型。还考虑了AMC,坡度和初始提取比对SCS-CN曲线数的影响,以及植被覆盖对RUSLE覆盖率的影响。黄土高原羊圈沟流域建立了三个径流样地群,分别由稀疏的幼树,原生灌木和茂密的草丛覆盖。在2008-2011年的雨季期间对降雨,径流和土壤流失进行了监测,以检验该方法的适用性。原始的SCS-CN模型显着低估了事件径流,特别是对于前5天降水量较大的降雨事件,而经过修改的SCS-CN模型在Nash-Sutcliffe模型效率(EF)超过0.85的情况下可以准确地预测事件径流。 。原始的RUSLE模型高估了测得的土壤流失的低值,而对EF值仅为0.30的高值却进行了低估。相反,当EF值超过0.70时,改进的RUSLE模型的预测精度会提高。我们的结果表明,AMC应明确纳入径流生产中,并在预测事件土壤流失时应直接考虑径流。修改后的SCS-CN和RUSLE模型的耦合似乎适合评估黄土高原恢复植被的水文影响。还讨论了所提出模型的主要优点,局限性和未来的研究范围。

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