Based on the Gradient Lifting Tree Model (GBDT), a hydrological experimental dataset from the Zizhou Runoff Experimental Station in the Yellow River Basin was used to model and analyze hydraulic erosion on sloping farmland. The results showed that: 1. The coefficient of variation for secondary rainfall erosion (0-122.72 t/km2), runoff depth (0.02-17.20 mm), rainfall duration (2-1410 min), and average rainfall intensity (0.02-4.63mm) in the dataset are all greater than 1, indicating high variability. Most variables exhibit a right-skewed distribution.2. When dividing the dataset into training and testing sets, the model''s accuracy in predicting soil erosion during secondary rainfall (R2=0.81) is slightly higher than that of the runoff depth prediction model (R2=0.80). However, the number of layers in the secondary erosion model (8 layers) exceeds that of the runoff depth prediction model (5 layers), suggesting a more complex erosion mechanism compared to the runoff mechanism. 3. The prediction results are not ideal for small secondary erosion amounts and runoff depths due to limitations in feature extraction. Future research should explore additional combinations of independent variables to identify more relevant factors. 4. The main influencing variables differ between the erosion runoff and sediment production processes. Precipitation characteristics play a major role in runoff production, while erosion sediment production is mainly influenced by the combined effects of precipitation and terrain-related independent variables. This study, being data-driven, provides insights into the erosion mechanism of slope farmland in the Loess Plateau and serves as a scientific basis for sustainable regional development.