Soil Conservation Service Curve Number (SCS-CN) is a popular surface runoff prediction method because it is simple in principle, convenient in application, and easy to accept. However, the method still has several limitations, such as lack of a land slope factor, discounting the storm duration, and the absence of guidance on antecedent moisture conditions. In this study, an equation was developed to improve the SCS-CN method by combining the CN value with the tabulated CN₂ value and three introduced factors (slope gradient, soil moisture, and storm duration). The proposed method was tested for calibration and validation with a dataset from three runoff plots in a watershed of the Loess Plateau. The results showed the model efficiencies of the proposed method were improved to 80.58% and 80.44% during the calibration and validation period, respectively, which was better than the standard SCS-CN and the other two modified SCS-CN methods where only a single factor of soil moisture or slope gradient was considered, respectively. Using the parameters calibrated and validated by dataset of the initial three runoff plots, the proposed method was then applied to runoff estimation of the remaining three runoff plots in another watershed. The proposed method reduced the root-mean-square error between the observed and estimated runoff values from 5.53 to 2.01 mm. Furthermore, the parameters of soil moisture (b₁ and b₂) is the most sensitive, followed by parameters in storm duration (c) and slope equations (a₁ and a₂), and the least sensitive parameter is the initial abstraction ratio λ on the basis of the proposed method sensitivity analysis. Conclusions can be drawn from the above results that the proposed method incorporating the three factors in the SCS method may estimate runoff more accurately in the Loess Plateau of China.

Erosive rainfall results in the loss of both soil and nutrients, which indirectly triggers soil deterioration and a reduction in land productivity. However, how rainfall affects runoff, soil erosion, and nutrient loss under different crop rotation patterns and topographic factors remains unclear. This experiment observed nine runoff-erosion plots on the Chinese Loess Plateau (CLP) from 2019 to 2020 to determine the effects of crop type, rotation pattern, and slope gradient and length on runoff, soil erosion, and nutrient loss. Runoff, soil erosion, and nutrient loss were highest for the fallow plots; values for these variables for spring corn and winter wheat plots were not significantly different. Crop rotation generated greater runoff, soil erosion, and nutrient loss compared to non-rotation. Soil erosion and associated nutrient loss increased, but not significantly, with slope for gradients of 0.5°, 1°, and 3°, while runoff and associated nutrient loss did not increase. In addition, soil erosion and associated nutrient loss were significantly greater for slope lengths of 20 m vs. 50 m. A structural equation model showed rainfall characteristics significantly impacted runoff and soil erosion and subsequently affected nutrient loss. This study increases the understanding of runoff, soil erosion, and nutrient loss from cropland with gentle slopes on the CLP.