Pan-European crop modelling with EPIC: Implementation, up-scaling and regional crop yield validation
Justifiable usage of large-scale crop model simulations requires transparent, comprehensive and spatially extensive evaluations of their performance and associated accuracy. Simulated crop yields of a Pan-European implementation of the Environmental Policy Integrated Climate (EPIC) crop model were satisfactorily evaluated with reported regional yield data from EUROSTAT for four major crops, including winter wheat, rainfed and irrigated maize, spring barley and winter rye. European-wide land use, elevation, soil and daily meteorological gridded data were integrated in GIS and coupled with EPIC. Default EPIC crop and biophysical process parameter values were used with some minor adjustments according to suggestions from scientific literature. The model performance was improved by spatial calculations of crop sowing densities, potential heat units, operation schedules, and nutrient application rates. EPIC performed reasonable in the simulation of regional crop yields, with long-term averages predicted better than inter-annual variability: linear regression R2 ranged from 0.58 (maize) to 0.91 (spring barley) and relative estimation errors were between ±30% for most of the European regions. The modelled and reported crop yields demonstrated similar responses to driving meteorological variables. However, EPIC performed better in dry compared to wet years. A yield sensitivity analysis of crop nutrient and irrigation management factors and cultivar specific characteristics for contrasting regions in Europe revealed a range in model response and attainable yields. We also show that modelled crop yield is strongly dependent on the chosen PET method. The simulated crop yield variability was lower compared to reported crop yields. This assessment should contribute to the availability of harmonised and transparently evaluated agricultural modelling tools in the EU as well as the establishment of modelling benchmarks as a requirement for sound and ongoing policy evaluations in the agricultural and environmental domains.
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- Reidsma, Pytrik & Ewert, Frank & Boogaard, Hendrik & Diepen, Kees van, 2009. "Regional crop modelling in Europe: The impact of climatic conditions and farm characteristics on maize yields," Agricultural Systems, Elsevier, vol. 100(1-3), pages 51-60, April.
- Wriedt, Gunter & van der Velde, Marijn & Aloe, Alberto & Bouraoui, Fayal, 2009. "A European irrigation map for spatially distributed agricultural modelling," Agricultural Water Management, Elsevier, vol. 96(5), pages 771-789, May.
- Schneider, Uwe A. & Havlík, Petr & Schmid, Erwin & Valin, Hugo & Mosnier, Aline & Obersteiner, Michael & Böttcher, Hannes & Skalský, Rastislav & Balkovic, Juraj & Sauer, Timm & Fritz, Steffen, 2011. "Impacts of population growth, economic development, and technical change on global food production and consumption," Agricultural Systems, Elsevier, vol. 104(2), pages 204-215, February.
- Franziska Strauss & Erwin Schmid & Elena Moltchanova & Herbert Formayer & Xiuying Wang, 2012. "Modeling climate change and biophysical impacts of crop production in the Austrian Marchfeld Region," Climatic Change, Springer, vol. 111(3), pages 641-664, April.
- Hansen, J. W. & Jones, J. W., 2000. "Scaling-up crop models for climate variability applications," Agricultural Systems, Elsevier, vol. 65(1), pages 43-72, July.
- Marijn Velde & Francesco Tubiello & Anton Vrieling & Fayçal Bouraoui, 2012. "Impacts of extreme weather on wheat and maize in France: evaluating regional crop simulations against observed data," Climatic Change, Springer, vol. 113(3), pages 751-765, August.
- Liu, Junguo & Williams, Jimmy R. & Zehnder, Alexander J.B. & Yang, Hong, 2007. "GEPIC - modelling wheat yield and crop water productivity with high resolution on a global scale," Agricultural Systems, Elsevier, vol. 94(2), pages 478-493, May.
- Cabelguenne, M. & Jones, C. A. & Marty, J. R. & Dyke, P. T. & Williams, J. R., 1990. "Calibration and validation of EPIC for crop rotations in southern France," Agricultural Systems, Elsevier, vol. 33(2), pages 153-171.
- Jones, C. A. & Dyke, P. T. & Williams, J. R. & Kiniry, J. R. & Benson, V. W. & Griggs, R. H., 1991. "EPIC: An operational model for evaluation of agricultural sustainability," Agricultural Systems, Elsevier, vol. 37(4), pages 341-350.
- Cabelguenne, M. & Debaeke, P. & Bouniols, A., 1999. "EPICphase, a version of the EPIC model simulating the effects of water and nitrogen stress on biomass and yield, taking account of developmental stages: validation on maize, sunflower, sorghum, soybea," Agricultural Systems, Elsevier, vol. 60(3), pages 175-196, June.
- Havlík, Petr & Schneider, Uwe A. & Schmid, Erwin & Böttcher, Hannes & Fritz, Steffen & Skalský, Rastislav & Aoki, Kentaro & Cara, Stéphane De & Kindermann, Georg & Kraxner, Florian & Leduc, Sylvain & , 2011. "Global land-use implications of first and second generation biofuel targets," Energy Policy, Elsevier, vol. 39(10), pages 5690-5702, October.
- Schönhart, Martin & Schauppenlehner, Thomas & Schmid, Erwin & Muhar, Andreas, 2011. "Integration of bio-physical and economic models to analyze management intensity and landscape structure effects at farm and landscape level," Agricultural Systems, Elsevier, vol. 104(2), pages 122-134, February.
- Bouman, B. A. M. & van Keulen, H. & van Laar, H. H. & Rabbinge, R., 1996. "The `School of de Wit' crop growth simulation models: A pedigree and historical overview," Agricultural Systems, Elsevier, vol. 52(2-3), pages 171-198.
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