Gridded crop modeling

Progress with EPIC crop modeling in 2013 allowed the Agro-Economic Systems (AES) group to join the international Ag-GRID initiative which aims to improve global gridded crop modeling.

Crops © Biletskiy_Evgeniy | iStock

Crops

Pan-European EPIC [1] was extended and validated for major crops grown across Europe.

The EU-EPIC was integrated with the EURO-CRODEX climate domain [2], allowing AES to step into internationally coordinated climate change impact and adaptation studies at the pan-EU scale (such as CARBO-Extreme or IMPACT2C).

In 2013 major crops were integrated into global EPIC using the most complete global information currently available, and several calibration and up-scaling procedures were developed and implemented to improve gridded crop modelling [3].

This progress allowed AES to join the international Ag-GRID initiative which aims to improve global gridded crop modeling. The initiative brings together an international community of crop modelers who collaborate on coordinated global climate impact assessments on global food production. AES's contribution to the extensive Ag-GRID crop model inter-comparison has been evaluation of crop models forced with harmonized management and climate data.

The IIASA EPIC model was also used to assess numerous aspects of agricultural systems:

  1. GEO and weather forecasts in Africa (GEOSAF, FarmSupport project),
  2. crop yields under increasingly unbalanced N and P consumption [4],
  3. future climate variability impacts on potential erosion and SOC (CARBO-Extreme), and
  4. global crop production potentials and management flexibility under the Representative Concentration Pathways (RCPs) (see wheat sample in figure below).
Figure 1

Figure 1. The level of confidence for climate change impacts on wheat yield potential for the 2090s (obtained from RCP 2.6, 4.5, 6.0 and 8.5 emission scenarios).


References

[1] Balkovič J, van der Velde M, Schmid E, Skalský R, Khabarov N, Obersteiner M, Stürmer B, Xiong W (2013). Pan-European crop modelling with EPIC: Implementation up-scaling and regional crop yield validation. Agricultural Systems 120: 61–75.
[2] Jacobs D, Petersen J, Eggert B, Alias A, Christensen OB, Bouwer LM, Braun A, Colette A , Deque M , Georgievski G, Georgopoulou E, Gobiet A, Menut L, Nikulin G, Haensler A, Hempelmann N, Jones C, Keuler K, Kovats S, Kroner N, Kotlarski S, Kriegsmann A, Martin E, van Meijgaard E , Moseley C , Pfeifer S, Preuschmann S, Radermacher C, Radtke K, Rechid D, Rounsevell M, Samuelsson P, Somot S, Soussana J –F, Teichmann C, Valentini R, Vautard R, Weber B, Yiou P (2013). EURO-CORDEX: New high-resolution climate change projections for European impact research. Regional Environmental Change in press doi: 10 1007/s10113-013-0499-2.
[3] Xiong W, Balkovič J, van der Velde M, Zhang X, Izaurralde RC, Skalský R, Lin E, Mueller N, Obersteiner M (2014). A calibration procedure to improve global rice yield simulations with EPIC. Ecological Modelling 273 128–139.
[4] Van der Velde M, Folberth M, Balkovič J, Ciais P, Fritz S, Janssens IA, Obersteiner M, See L, Skalský R, Xiong W, Peñuelas J (2014). African crop yield reductions due to increasingly unbalanced Nitrogen and Phosphorus consumption. Global Change Biology in press doi: 10 1111/gcb 12481

Collaborators

University of Chicago and Argonne National Laboratory (ANL) Computation Institute, USA;
NASA GISS Climate Impacts Group, USA;
Potsdam Institute for Climate Impacts Research (PIK), Germany.


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Last edited: 22 May 2014

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Ecosystems Services and Management

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