Abstract
The frequency and intensity of heavy rainfall on the Chinese Loess Plateau (CLP) are increasing due to global climate change, which has caused severe soil erosion. However, precise evaluation of heavy rainfall-induced soil erosion, deposition, and related topographical changes at the catchment scale is lacking, and there is uncertainty as to how effectively trees can inhibit erosion, especially during heavy rainfall. In this study, we selected a pair of catchments with afforestation and natural grassland restoration on the CLP. Precise evaluation of erosion and topographic changes induced by heavy rainfall was conducted based on airborne light detection and ranging (LiDAR) data. In the grassland catchment, the gully bed area increased by 17.6 %, the gully slope and inter-gully land area decreased by 1.4 %, and the length of the gully shoulder line decreased by 4.4 %. Conversely, the forestland catchment experienced a decrease in gully bed area of 8.8 %, an increase in gully slope area of 5.3 %, a decrease in inter-gully land area of 9.9 %, and a decrease in the length of the gully shoulder line of 11.4 %. Following heavy rainfall, both catchments experienced a substantial increase in terrain relief. Soil erosion in the gully slope accounted for >90 % of the total erosion in both catchments, while deposition in the same area contributed to >75 % of the total deposition. The grassland catchment experienced a unit area erosion of 233,908 m3 km−2, which was 4.7 times greater than that of the forestland catchment (49,768 m3 km−2). In both catchments, erosion predominantly transpired in the steep slope region adjacent to the gully shoulder line, accounting for >15 % of the gully slope erosion area. The grassland catchment exhibited a continuous distribution pattern of erosion and deposition, whereas the forestland catchment exhibited a scattered and intertwined distribution pattern. This study is essential for further research on erosion and topographic changes induced by extreme weather events and to determine appropriate measures.
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