Water erosion on arable land can reduce soil fertility and agricultural productivity. Despite the impact of water erosion on crops, it is typically neglected in global crop yield projections. Furthermore, previous efforts to quantify global water erosion have paid little attention to the effects of field management on the magnitude of water erosion. In this study, we analyse the robustness of simulated water erosion estimates in maize and wheat fields between the years 1980 and 2010 based on daily model outputs from a global gridded version of the Environmental Policy Integrated Climate (EPIC) crop model. By using the MUSS water erosion equation and country-specific and environmental indicators determining different intensities in tillage, residue handling and cover crops, we obtained the global median water erosion rates of 7 t ha⁻¹ a⁻¹ in maize fields and 5 t ha⁻¹ a⁻¹ in wheat fields. A comparison of our simulation results with field data demonstrates an overlap of simulated and measured water erosion values for the majority of global cropland. Slope inclination and daily precipitation are key factors in determining the agreement between simulated and measured erosion values and are the most critical input parameters controlling all water erosion equations included in EPIC. The many differences between field management methods worldwide, the varying water erosion estimates from different equations and the complex distribution of cropland in mountainous regions add uncertainty to the simulation results. To reduce the uncertainties in global water erosion estimates, it is necessary to gather more data on global farming techniques to reduce the uncertainty in global land-use maps and to collect more data on soil erosion rates representing the diversity of environmental conditions where crops are grown.

中文翻译：

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基于EPIC的全球网格化作物模型中模拟水蚀的不确定性，敏感性和鲁棒性

耕地的水蚀会降低土壤肥力和农业生产力。尽管水蚀对农作物有影响，但全球农作物总产量预测通常忽略了水蚀。此外，以前量化全球水蚀的努力很少关注田间管理对水蚀程度的影响。在这项研究中，我们根据环境政策综合气候（EPIC）作物模型的全球网格化版本的每日模型输出，分析了1980年至2010年之间玉米和小麦田模拟水蚀估算的稳健性。通过使用MUSS水蚀方程式以及确定耕种，残留物处理和覆盖作物的不同强度的国家特定和环境指标，我们得出了7 t ha的全球平均水蚀率^-1 一^-1玉米田和5吨公顷^-1 一^-1在麦田里。我们的模拟结果与现场数据的比较表明，大多数全球农田的模拟和实测水蚀值存在重叠。坡度和日降水量是确定模拟和实测侵蚀值之间一致性的关键因素，并且是控制EPIC中包括的所有水蚀方程式的最关键输入参数。全球范围内的田间管理方法之间存在许多差异，不同方程式的水蚀估算值不同，山区农田分布复杂，这给模拟结果增加了不确定性。为了减少全球水蚀估算的不确定性，