4.7 Article

Experimental study on soil erosion prediction model of loess slope based on rill morphology

期刊

CATENA
卷 173, 期 -, 页码 424-432

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.catena.2018.10.034

关键词

Rill erosion; Rainfall intensity; Morphological characteristic; Rainfall simulation; Prediction model

资金

  1. National Key R&D Program of China [2017YFC0504501]
  2. Natural Science Foundation of China [41877079, 41571276]
  3. China Postdoctoral Science Foundation [2018M630826]
  4. Key Laboratory of Soil and Water Loss Process and Control on the Loess Plateau of Ministry of Water Resources [201801]

向作者/读者索取更多资源

Rill erosion frequently occurs in agricultury disturbed dry areas. Despite many research efforts over recent decades, the characteristics of rill erosion and its intrinsic mechanisms remain unclear. The objectives of this study were to investigate the impacts of rill morphology evolution on rill erosion processes. A soil pan (5 m long, 1 m wide, and 0.6 m deep and with an adjustable slope gradient of 0-30 degrees) was subjected to rainfall simulation experiments under three intensities of representative erosive rainfall (66, 94, and 127 mm h(-1)). The rill morphology evolution exhibited significant nonlinear change regulation and the stronger the rainfall intensity, the clearer the nonlinear feature. The equation between rill morphological characteristics with geomorphological comentropy and bifurcation ratio was generated, which indicated that the contribution rate of geomorphological comentropy to sediment yield was 80%, and the contribution rate of bifurcation ratio was 20%. For the experimental treatments, a soil erosion model was constructed with and without rill development and the coefficient to describe the influence of rill development on slope erosion was obtained. The rill erosion coefficient was embedded into an existing soil erosion model for steep slopes. As a result, when rill erosion occurred on the slope, the contribution of the rill morphology to the rill erosion was fully realized by the model. Verification indicated that the accuracy of the model was significantly improved. In previous studies, the accuracy of slope water erosion prediction model was low because the evolution process of slope topography was not considered. Our results solve the spatial variability problem in the slope erosion prediction model, and improve the simulation accuracy of the soil erosion prediction model on a loess slope.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据