Uncertainties, sensitivities and robustness of simulated water erosion in an EPIC-based global gridded crop model

Carr, T.W., Balkovič, J. ORCID: https://orcid.org/0000-0003-2955-4931, Dodds, P.E., Folberth, C. ORCID: https://orcid.org/0000-0002-6738-5238, Fulajtar, E., & Skalský, R. ORCID: https://orcid.org/0000-0002-0983-6897 (2020). Uncertainties, sensitivities and robustness of simulated water erosion in an EPIC-based global gridded crop model. Biogeosciences 17 (21) 5263-5283. 10.5194/bg-17-5263-2020.

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Abstract

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.

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