Simulation and Prediction of Soil Erosion in Daning River Basin

Abstract

Calculating soil erosion intensity and predicting its change trend is essential for the precise implementation of control measures. We had estimated and quantitatively analyzed the current situation of soil erosion in the Daning River Basin in 2008, 2013, and 2018 using the revised universal soil loss equation model. We also analyzed the correlation between distance from the river, elevation, and slope, followed by the analysis and prediction of the soil erosion in the Daning River Basin in 2023 by constructing a cellular automaton (CA)-artificial neural network (ANN)-Markov model. The results demonstrated the total soil erosion to be 798.49, 746.38, and 628.78 104 t in 2008, 2013, and 2018, respectively. The overall trend of soil erosion was found to be decreasing and the spatial distribution of soil erosion was strongly correlated with the distance from the river, elevation, and slope. Based on the CA-ANN-Markov model prediction, the trend of soil erosion from 2018 to 2023 is consistent with that from 2008 to 2013. Light, moderate, and intense erosion demonstrated an increasing trend, whereas slight, very intense, and intense erosion demonstrated a decreasing trend. By estimating and predicting soil erosion in the Daning River Basin, this article provides a reference for ecological restoration and the control of soil erosion in small watersheds under similar environments.

Keywords

• Cellular automaton (CA)-artificial neural network (ANN)-Markov
• Daning River Basin
• quantitative evaluation
• revised universal soil loss equation (RUSLE)
• soil erosion