Vegetation restoration dominated the attenuated soil loss rate on the Loess Plateau, China over the last 50 years

The Chinese Loess Plateau has experienced large-scale land use changes in the past few decades. Understanding how land use change affects soil erosion is critical in the region's ecological construction and land management. In this study, the Beiluo River Basin in the core area of the Loess Plateau was selected to investigate the effects of land use changes on soil loss rates over the last 50 years. Results show that the land use has changed considerably, mainly reflected in the upper reaches. From 1970 to 2020, cropland in the upper reaches decreased by 54 %, directly leading to a 9.1-fold increase in forested land. Landsat-NDVI shows vegetation coverage increased from 21.1 % to 69.9 % over time. The Chinese Soil Loss Equation (CSLE) was used and confirmed to be satisfactory with a high coefficient of determination (R2, 0.89) and a strong Nash–Sutcliffe efficiency coefficient (0.72), although an underestimation exists. The specific soil loss simulated in the upper reaches maintained a high rate of around 8,000 t·km−2·yr−1 from the 1970s to the 1990s, dramatically dropping to 3,058 t·km−2·yr−1 in the 2000s, then attenuated to 1,321 t·km−2·yr−1 in the 2020s. For the entire basin, soil loss rates dropped from 4,090 to 1,848 and 890 t·km−2·yr−1 from the 1970s to the 2000s and 2020s, respectively. Attribution analysis showed that the dominant factor of the change in soil loss rates in the 1980s and 1990s relative to the 1970s was the change in rainfall erosivity for the entire watershed. However, vegetation restoration rapidly converted to the dominant factor contributing 78.3 % to soil loss decrease in the 2000s. The shift is evident in each reach of the basin except the terrain-plain area with the majority of farmland. The findings are helpful for sustainable land use planning and socio-economic development on the Loess Plateau and in similar areas.

This research was jointly supported by the National Key R&D Program of China (Grant No. 2022YFE0115300), and National Natural Science Foundation of China (Grant No. 41877083 and 41440012).

Peer reviewed