An improved vegetation cover and management factor for RUSLE model in prediction of soil erosion
2021
Bai, Yu | Cui, Haifeng
Soil erosion and runoff of cultivated land will cause farmland to be degraded and the downstream to be contaminated, which has aroused extensive attention worldwide. The conventional soil loss prediction model revised universal soil loss equation (RUSLE) is capable of more significantly simulating and predicting the amount of soil loss, but this model often cannot achieve the satisfied prediction accuracy when the rainfall distribution of 1 year is significantly inconsistent with the annual distribution law. In this study, the 3-year field experiments were performed in Jilin, China. Besides, an improved revised universal soil loss equation (IRUSLE) was provided with a novel vegetation cover and management factor (C). It considered the interaction between rainfall distribution and normalized difference vegetation index (NDVI) by theoretical analysis and the genetic algorithm. It was reported that IRUSLE model can achieve more effective simulation result than RULSE model, as well as laying a theoretical basis for soil loss prediction.
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