An optimized method for extracting slope length in RUSLE from raster digital elevation

通用土壤流失方程 数字高程模型 曲率 地表径流 仰角(弹道) 数学 光栅图形 腐蚀 地形 切断 分水岭 土壤科学 水文学(农业) 几何学 地质学 遥感 土壤流失 地貌学 计算机科学 岩土工程 地理 生态学 物理 量子力学 人工智能 机器学习 生物 地图学
作者
Dong Liang,Chenyu Ge,Hongming Zhang,Zihan Liu,Qinke Yang,Bei Jin,C.J. Ritsema,Violette Geissen
出处
期刊:Catena [Elsevier BV]
卷期号:209: 105818-105818 被引量:9
标识
DOI:10.1016/j.catena.2021.105818
摘要

The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) have been widely used for predicting average soil loss. Slope length is an important topographical parameter of the L factor in USLE/RUSLE. Among the widely studied GIS procedures for extracting slope length, the distributed watershed erosion slope length (DWESL) based on the unit contributing area estimation method, which considers two-dimensional runoff process and cutoff factors, is a relatively complete model for calculating slope length. Slope length in the DWESL model is primarily calculated using conventional flow direction algorithms such as D8, Dinf, MS and MFD-md. However, DWESL outputs require further improvement due to the errors in the usual estimates of the uphill contributing area and the effective contour length of discrete elements. Combined with a theoretical differential equation of specific catchment area on hillsides, the calculation of the DWESL model was optimized without estimating the uphill contributing area or the effective contour length for each cell. The proposed integration method based on the topographical features slope line, contour curvature and cutoff factors (ITF method) was used to extract slope length from the raster digital elevation. Slope length extracted using the ITF method had the smallest error in verification of mathematical surfaces (average RRMSE = 0.0573), and its spatial distribution was more consistent with the structure of the terrain surface for all test data, relative to the conventional flow direction algorithms in the original DWESL model. The proposed ITF method could provide a reference for predicting soil erosion using the USLE/RUSLE model.
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