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• Chinese soil loss equation model was used to estimate long-term soil erosion. • Soil erosion rates increased in the basin from 2010 to 2017. • Interactions between main driving factors analyzed using boosted regression trees. • The B factor was the primary driver of soil erosion. Soil erosion reduces soil fertility and land productivity while enhancing desertification, which seriously threatens ecological security, carbon sequestration, and sustainable economic and social development. Therefore, it is fundamental to precisely assess the long-term dynamics of soil erosion and explore its drivers to control the risk of soil erosion. Currently, machine learning-based analyses of the factors driving soil erosion are lacking in the Beiluo River Basin (BRB), China. This paper aimed to investigate the spatiotemporal dynamics of soil erosion by the Chinese soil loss equation coupled with the gully erosion factor, and then reveal its driving factors using the Boosting Regression Tree method (BRT) and estimate the influence of drivers' interactions on soil erosion in the BRB between 1990 and 2017. The findings demonstrated that the expanded Chinese soil loss equation accurately explained the variations in soil erosion in the BRB. The range of average soil erosion rates was 2,852.83–800.35 t km−2 a−1. Steep gully farmland, particularly areas with relatively rough terrain, was more vulnerable to intense erosion. Soil erosion rates for different geomorphologies decreased as follows: hilly–gully areas > gully–plateau areas > alluvial river plains > Rocky Mountains. The major drivers affecting the soil erosion rate were the biomass control factor (B) and slope, followed by slope length (L) and slope steepness (S). B–soil erodibility (1990), B–LS (2000), LS–rainfall erosivity (2010), and slope–rainfall erosivity (2017) interactions had the greatest influence on soil erosion, with interaction intensities of 32.3%, 17.75%, 46.05%, and 35.69%, respectively. The average soil erosion rates according to land classification types decreased as follows: farmland > grassland > forest. The results indicate that water and soil conservation in the study area benefited greatly from implementation of the Grain for Green Program, with forests reducing erosion more effectively than grassland. [ABSTRACT FROM AUTHOR]