Evolution of Surface Drainage Network for Spoil Heaps under Simulated Rainfall

Water

Dongkai Chen¹  Han Luo¹  Yongsheng Xie¹  Jiaorong Lv² 

[1] Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China;Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610000, China;

关键词: spoil heap;    flow paths;    roughness;    simulated rainfall;    fractal dimensions;   

DOI  :  10.3390/w13233475

来源: DOAJ

【 摘 要 】

Spoil heaps laid from the infrastructure building sites or the mining sites are confoundedly prone to accelerated soil erosion and inducing debris flows on extreme rainfall occasion, thus threatening water quality and personal safety. In present study, the roughness and drainage network evolution of the loess spoil heap (a 33° slope gradient) were investigated via indoor simulation experiment under three rainfall intensities (60, 90, and 120 mm/h). A detailed scan of the slope using laser scanner, topographic analysis based on ArcGIS software, and statistical analyses were the main methods utilized in the study. The results showed that surface roughness increased with cumulative rainfall. For three rainfall intensity treatments, the proneness of shallow landslide under 90 mm/h intensity resulted in the largest roughness. The drainage density and stream frequency of the spoil heap slope both decreased with cumulative rainfall and negatively correlated with surface roughness, which indicated the convergence of the drainage network. Meanwhile, the individual flow paths presented an increasing sinuosity and a decreasing gradient with cumulative rainfall. However, drainage network features varied in a less marked degree during different rainfall intensities, showing comparable fractal dimensions of 1.350–1.454, 1.305–1.459, and 1.292–1.455 for the three rainfall intensities. Evaluating the response of four hydrodynamic characteristics of runoff to the drainage network evolution, stream power was found to be most sensitive. The linearity of the relationships between stream power and drainage density and that between stream sinuosity and gradient were estimated to have R² between 0.961 and 0.979.

【 授权许可】

Unknown