Soil erosion and nutrient loss cause serious land degradation and environmental problems worldwide. A quantitative understanding of rainfall-induced sediment and nutrient transport is needed to mitigate these harmful effects. Here, we present a new analytical model of nutrient loss on sloping land during crop growth on the Chinese Loess Plateau, where human activities have intensified soil erosion and nutrient loss. The model's parameterization is based on crop conditions (crop height, crop coverage, above-ground biomass, and root weight density) and soil characteristics (soil bulk density and organic carbon content). To evaluate the model's performance, simulated rainfall experiments were conducted in the field during the 2016 and 2017 growing seasons with three crops (wheat, soybean, and millet). Path analysis indicated that crop coverage was the factor with the strongest effect on the runoff coefficient, sediment load, and nutrient loss. Crop coverage was also the factor with the greatest contribution to five model parameters, namely the topography and surface roughness coefficients, the calibration constants for runoff and splash erosion, and the exchange layer depth. The model's parameters were determined by least-squares fitting to the measured unit discharge, sediment load, and nutrient concentration measurements from 2016. These parameters showed decreasing trends over the growing season due to the dynamics of crop coverage. Empirical expressions for generating parameter values suitable for use with the model were established based on the 2016 crop conditions and soil properties. Independent data from 2017 were then used to assess the new model's accuracy. The predicted results agreed quite well with field observations (R2>0.73, RMSE < 0.07), indicating that the new model is an effective analytical tool for predicting plot-scale soil erosion and nutrient loss in sloping farmland on the Chinese Loess Plateau, and should be applicable to similar sites with proper parameterization. This model facilitates quantitative analysis of land development and degradation processes, and provides a theoretical framework for further use of watershed forecasting models in efforts to mitigate soil erosion and nutrient loss.
All Science Journal Classification (ASJC) codes
- Agronomy and Crop Science
- Soil Science
- Earth-Surface Processes