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

Abstract

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.

Combined effects of climate change and agricultural intensification on soil erosion in uphill shifting cultivation in Northeast India

“…To set up the model for the topographic conditions of the study region, we tested all of the above erosion equations and found that RUSLE provided the lowest and most realistic soil loss, which is consistent with the findings by Carr et al (2020). We also tested several combinations of exponential coefficients in the RUSLE C ‐factor equation and applied the best‐performing combination as given in Supplementary Material (A4).…”

“…The calculation of the erosivity factor R depends on the specific erosion equation selected by the user, who can choose from seven equations. While the R ‐factor in the erosion equation USLE and its revisions (RUSLE, RUSLE2) is mainly driven by precipitation intensity, in MUSLE, MUST, and MUSS, it is driven by runoff variables, whereas the Onstad‐Foster equation applies a combination (Carr et al, 2020; Williams, 1995). The K ‐factor is computed based on sand, silt, clay, and organic carbon contents of the top soil horizon at the beginning of each simulation year, using the equation provided in Williams (1995).…”

“…We opted against a slope‐specific P ‐factor value because these were unavailable for the entire slope range analyzed in this study. Using a mean P ‐factor value, we also attenuate the effect that EPIC typically overestimates soil erosion on steep slopes (Carr et al, 2020).…”

Reproducibility, open science and progression in soil erosion research. A reply to “Response to ‘National-scale geodata describe widespread accelerated soil erosion’ Benaud et al. (2020) Geoderma 271, 114378” by Evans and Boardman (2021)

“…Furthermore, tackling environmental challenges in the Anthropocene requires interdisciplinary thinking. To this end, it is appropriate to consider how monitoring approaches and results in general can also be used to improve model accuracy and efficiency (Batista et al, 2019;Carr et al, 2020;Evans and Brazier, 2005). Through building a platform for sharing data and a criterion to increase reproducibility and transparency, our paper (Benaud et al, 2020) also aspired to be a stepping stone in the evolution of scientific and methodological process in this capacity.…”