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

• Published in: Catena (Giessen) 2019-02, Vol.173, p.424-432
• Main Authors: Zhang, Pan, Yao, Wenyi, Liu, Guobin, Xiao, Peiqing
• Format: Article
• Language: English
• Subjects: Morphological characteristic; Prediction model; Rainfall intensity; Rainfall simulation; Rill erosion
• ISSN: 0341-8162; 1872-6887
• DOI: 10.1016/j.catena.2018.10.034

Rill erosion frequently occurs in agriculturally 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°) 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. •A quantitative method for rill morphology is constructed by geomorphological comentropy and bifurcation ratio.•The rill morphology evolution exhibited significant nonlinear change regulation.•The stronger the rainfall intensity the clearer the nonlinear feature of the rill morphology.•The rill erosion coefficient was embedded into an existing soil erosion model.