Soil erosion models, typically applied at basin and watershed scales, are rarely evaluated at agricultural field scales due to the lack of spatially-distributed time series data. A novel unmanned aerial vehicle (UAV) methodology was used to quantify farm-field soil erosion from nine UAV surveys and structure-from-motion (SfM). Using a semi-distributed approach, we evaluated soil erosion estimates from the Universal Soil Loss Equation (USLE) and Water Erosion Prediction Project (WEPP). The annual erosion rate, measured with the UAV methodology, was 18.83 t ha⁻¹ yr⁻¹, with USLE and WEPP predictions of 26.23 t ha⁻¹ yr⁻¹ and 16.41 t ha⁻¹ yr⁻¹, respectively. Modelled annual and sub-annual erosion rates with WEPP were within the upper-limit of predictive accuracy, while the USLE tended to systematically overestimate soil erosion rates. These outcomes have implications on the efficacy of conservation efforts, which is highlighted through a discussion and comparison of different best-management practice applications.

由于缺乏空间分布的时间序列数据，通常在流域和流域尺度上应用的土壤侵蚀模型很少在农业领域尺度上进行评估。一种新颖的无人飞行器（UAV）方法用于从九次UAV调查和动静结构（SfM）中量化农田土壤侵蚀。使用半分布式方法，我们根据通用土壤流失方程（USLE）和水蚀预测项目（WEPP）评估了土壤侵蚀估算。用无人机方法测得的年侵蚀率是18.83 t ha ^-1 yr ^-1，USLE和WEPP预测为26.23 t ha ^-1 yr ^-1和16.41 t ha ^-1 yr ^-1， 分别。用WEPP建模的年和次年侵蚀速率在预测精度的上限之内，而USLE则倾向于系统地高估土壤侵蚀速率。这些结果对保护工作的有效性产生了影响，通过对不同最佳管理实践应用的讨论和比较来强调这一点。