Articles | Volume 17, issue 21
https://doi.org/10.5194/bg-17-5263-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-17-5263-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Nov 2020
Research article |
| 05 Nov 2020
| 05 Nov 2020
Uncertainties, sensitivities and robustness of simulated water erosion in an EPIC-based global gridded crop model
Tony W. Carr
CORRESPONDING AUTHOR
University College London, Institute for Sustainable Resources,
London, United Kingdom
Juraj Balkovič
International Institute for Applied Systems Analysis, Ecosystem
Services and Management Program, Laxenburg, Austria
Department of Soil Science, Faculty of Natural Sciences, Comenius
University in Bratislava, Bratislava, Slovak Republic
Paul E. Dodds
University College London, Institute for Sustainable Resources,
London, United Kingdom
Christian Folberth
International Institute for Applied Systems Analysis, Ecosystem
Services and Management Program, Laxenburg, Austria
Emil Fulajtar
International Atomic Energy Agency, Joint FAO/IAEA Division of
Nuclear Techniques in Food and Agriculture, Vienna, Austria
Rastislav Skalsky
International Institute for Applied Systems Analysis, Ecosystem
Services and Management Program, Laxenburg, Austria
National Agricultural and Food Centre, Soil Science and Conservation
Research Institute, Bratislava, Slovak Republic
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Short summary
We generate 30-year mean water erosion estimates in global maize and wheat fields based on daily simulation outputs from an EPIC-based global gridded crop model. Evaluation against field data confirmed the robustness of the outputs for the majority of global cropland and overestimations at locations with steep slopes and strong rainfall. Additionally, we address sensitivities and uncertainties of model inputs to improve water erosion estimates in global agricultural impact studies.
We generate 30-year mean water erosion estimates in global maize and wheat fields based on daily...
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