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Effects of soil depth spatial variation on runoff simulation, using the Limburg Soil Erosion Model (LISEM), a case study in Faucon catchment, France

机译:土壤深度空间变化对径流模拟的影响,使用林堡土壤侵蚀模型(LISEM),以法国Faucon流域为例

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Soil depth is an important parameter for models of surface runoff. Commonly used models require not only accurate estimates of the parameter but also its realistic spatial distribution. The objective of this study was to use terrain and environmental variables to map soil depth, comparing different spatial prediction methods by their effect on simulated runoff hydrographs. The study area is called Faucon, and it is located in the southeast of the French Alps. An additive linear model of “land cover class” and “overland flow distance to channel network” predicted the soil depth in the best way. Regression kriging (RK) used in this model gave better accuracy than ordinary kriging (OK). The soil depth maps, including conditional simulations, were exported to the hydrologic model of LISEM, where three synthetic rainfall scenarios were used. The hydrographs produced by RK and OK were significantly different only at rainfalls of low intensity or short duration.
机译:土壤深度是地表径流模型的重要参数。常用的模型不仅需要参数的准确估计,还需要其实际的空间分布。这项研究的目的是使用地形和环境变量来绘制土壤深度图,通过比较不同的空间预测方法对模拟径流水文图的影响来比较它们。研究区域称为Faucon,位于法国阿尔卑斯山的东南部。 “土地覆被类别”和“陆路到管道网的地面流动距离”的加性线性模型以最佳方式预测了土壤深度。此模型中使用的回归克里金法(RK)比普通克里金法(OK)具有更好的准确性。将包括条件模拟在内的土壤深度图导出到LISEM的水文模型,其中使用了三种合成降雨方案。 RK和OK产生的水文图仅在强度低或持续时间短的降雨时才显着不同。

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