In 2015, AES undertook EPIC simulations for its 17 calibrated crops, forcing the model with management options along the crop intensification gradient (Figure 1). This work can be used to inform the GLOBIOM model about crop yields under agricultural intensification, estimating environmental impacts , resource use, and ecosystem services , evaluating the drivers of crop yields , and optimizing crop production for minimization of environmental impacts. AES also continued with the ongoing collaboration with the AgGRID initiative, which aims to improve global gridded crop modeling .
EPIC was also employed by AES for the IMPACT2C, AGRICISTRADE, Unlocking Forest Finance (UFF), and IMBALANCE-P projects. For IMPACT2C, EPIC was forced with EURO-Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) climate projections to estimate the impacts of future climate on: crop production, regional adaptations, crop vulnerability, and production risks in Europe. For AGRICISTRADE, AES investigated agricultural production in the Commonwealth of Independent States. For UFF, AES simulated management options for future soybean, maize, and cotton production in agricultural hot-spots in Brazil. Finally, for IMBALANCE-P, AES focused on EPIC scenarios for future phosphorus depletion and nitrogen and phosphorus imbalances, as well as the further development of the model towards introducing biogeochemical processes in manure.
Figure 1. Maize yields (ton/ha) under five nitrogen application rates (i.e., N01, N25, N100, N200, and N400 representing 0.1, 25, 100, 200, and 400kg N/ha) and three irrigation strategies (i.e. B00, B05, and B10 representing rainfed, partially and fully irrigated systems) simulated with EPIC-IIASA under the hypercube initiative.
The AES team continued assessment of climate change impacts on crop production in the major bread baskets of the world. A special focus was paid to crop vulnerability to extreme events and climate-related changes in soil productivity, including soil erosion, soil organic carbon, and water supply. For example, a new generation of downscaled and bias-corrected climate change projections from EURO-CORDEX was used to estimate future crop calorie yields (Figure 2) and yield variability as a response to climate change and crop management in Europe. The EPIC model was used to decouple crop vulnerability due to climate extremity, accelerated soil erosion, and declining soil productivity, from the mean climate change impact. AES also analyzed adaptation measures including reduced till and no-till practices, and crop residue managements.
Figure 2. Business as usual crop calorie yield (a), and calorie yield potential (b) simulated for a 2°C global warming target (calculated from 10 most important crops).
AES contributed to the interactive IMPACT2C web-atlas that shows the impacts of a 2°C global warming on various European sectors and some key vulnerable regions outside Europe. The web-atlas contributes to background knowledge about consequences of a 2°C global warming, supporting the accord achieved during the climate summit in Paris.
 Elshout PMF, van Zelm R, Balkovič J, Obersteiner M, Schmid E, Skalský R, van der Velde M, Huijbregts MAJ (2015). Greenhouse-gas payback times for crop-based biofuels. Nature Climate Change, 5: 604–610.
 Rosenzweig C, Elliott J, Deryng D, Ruane AC, Mueller Ch, Arneth A, Boote KJ, Folberth Ch, et al. (2014). Assessing agricultural risks of climate change in the 21st century in a global gridded crop model inter-comparison. PNAS, 111(9):3268-3273.
 Ma K, Liu J, Balkovič J, Skalský R, Azevedo LB, Kraxner F (2016). Changes in soil organic carbon stocks of wetlands on China’s Zoige plateau from 1980 to 2010. Ecological modeling, (in press).
 Folberth C, Skalský R, van der Velde M, Moltchanova E, Balkovič J, Azevedo LB, Obersteiner M. Uncertainty in soil data outweighs climate impact signals in global crop yield simulations. (under review).
United States Department of Agriculture (USDA), USA
University of Chicago and Argonne National Laboratory (ANL) Computation Institute, USA
NASA GISS Climate Impacts Group, USA
Helmholtz-Zentrum Geesthacht (HZG) , Germany
Radboud University Nijmegen, the Netherlands
China Agricultural University (CAU), China
School of Nature Conservation, Beijing Forestry University, China
Department of Geography, Ludwig Maximilian University, Germany
School of Mathematics and Statistics, University of Canterbury, New Zealand
Agribenchmark Cash Crop Network, Thünen Institute of Farm Economics, Germany
Last edited: 15 March 2016
International Institute for Applied Systems Analysis (IIASA)
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