In order to explore the effects of hydrodynamic erosion factors on soil detachment rate of freeze-thaw slope

two slopes (10°

and 15°)

four flow rates (4.5

6.5

8.5 and 10.5 L/min)

and four original thaw depth (2

5

10 and 15 cm) were designed to simulate filed runoff. By means of BP Neural Network and Stepwise Regression Analysis

we analyzed the relationship between the soil detachment rate and 7 hydrodynamic erosion factors

including stream power

unit stream power

original thaw depth

flow shear stress

flow rate

flow velocity and slope. The results showed that the rank of influence significance of hydrodynamic erosion factors from high to low was flow stream power＞unit stream power＞original thaw depth＞flow shear stress＞flow rate＞flow velocity＞gradient. Furthermore

according to BP Neural Network model

the average error of soil detachment rate prediction was 2.848% (R2=0.954). In view of Stepwise Regression Analysis model

the average error was 4.820% (R2=0.925). According to Single Hydrodynamic Erosion Factors (Stream power) model

the average error was 5.298% (R2=0.867). In general

the prediction effect based on BP Neural Network was better than others. This study provides a new idea for the establishment of soil erosion prediction model under different original thaw depths in the spring thaw period.