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Pan-European crop modelling with EPIC: Implementation, up-scaling and regional crop yield validation

Author

Listed:
  • Balkovič, Juraj
  • van der Velde, Marijn
  • Schmid, Erwin
  • Skalský, Rastislav
  • Khabarov, Nikolay
  • Obersteiner, Michael
  • Stürmer, Bernhard
  • Xiong, Wei

Abstract

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.

Suggested Citation

  • Balkovič, Juraj & van der Velde, Marijn & Schmid, Erwin & Skalský, Rastislav & Khabarov, Nikolay & Obersteiner, Michael & Stürmer, Bernhard & Xiong, Wei, 2013. "Pan-European crop modelling with EPIC: Implementation, up-scaling and regional crop yield validation," Agricultural Systems, Elsevier, vol. 120(C), pages 61-75.
  • Handle: RePEc:eee:agisys:v:120:y:2013:i:c:p:61-75
    DOI: 10.1016/j.agsy.2013.05.008
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. repec:eee:ecomod:v:213:y:2008:i:3:p:365-380 is not listed on IDEAS
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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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    1. Dono, Gabriele & Cortignani, Raffaele & Giraldo, Luca & Doro, Luca & Roggero, Pier Paolo, 2014. "Assessing the awareness of climate change as a factor of adaptation in the agricultural sector," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173110, Italian Association of Agricultural and Applied Economics (AIEAA).
    2. Wolf, Verena & Deppermann, Andre & Tabeau, Andrzej & Banse, Martin & van Berkum, Siemen & Haß, Marlen & Havlik, Petr & Philippidis, George & Salamon, Petra & Verma, Monika, 2016. "Linking three market models to project Russian and Ukrainian wheat markets till 2030," 155th Seminar, September 19-21, 2016, Kiev, Ukraine 245878, European Association of Agricultural Economists.
    3. Choi, Hyung Sik & Schneider, Uwe A. & Rasche, Livia & Cui, Junbo & Schmid, Erwin & Held, Hermann, 2015. "Potential effects of perfect seasonal climate forecasting on agricultural markets, welfare and land use: A case study of Spain," Agricultural Systems, Elsevier, vol. 133(C), pages 177-189.
    4. Amit Kumar Srivastava & Thomas Gaiser & Frank Ewert, 2016. "Climate change impact and potential adaptation strategies under alternate climate scenarios for yam production in the sub-humid savannah zone of West Africa," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(6), pages 955-968, August.
    5. Dono, Gabriele & Cortignani, Raffaele & Dell'Unto, Davide & Deligios, Paola & Doro, Luca & Lacetera, Nicola & Mula, Laura & Pasqui, Massimiliano & Quaresima, Sara & Vitali, Andrea & Roggero, Pier Paol, 2016. "Winners and losers from climate change in agriculture: Insights from a case study in the Mediterranean basin," Agricultural Systems, Elsevier, vol. 147(C), pages 65-75.
    6. Bhattarai, Mukesh Dev & Secchi, Silvia & Schoof, Justin, 2017. "Projecting corn and soybeans yields under climate change in a Corn Belt watershed," Agricultural Systems, Elsevier, vol. 152(C), pages 90-99.
    7. repec:eee:ecomod:v:273:y:2014:i:c:p:128-139 is not listed on IDEAS
    8. Kluts, Ingeborg & Wicke, Birka & Leemans, Rik & Faaij, André, 2017. "Sustainability constraints in determining European bioenergy potential: A review of existing studies and steps forward," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 719-734.
    9. Tatsumi, Kenichi, 2016. "Effects of automatic multi-objective optimization of crop models on corn yield reproducibility in the U.S.A," Ecological Modelling, Elsevier, vol. 322(C), pages 124-137.
    10. Bao, Yawen & Hoogenboom, Gerrit & McClendon, Ron & Vellidis, George, 2017. "A comparison of the performance of the CSM-CERES-Maize and EPIC models using maize variety trial data," Agricultural Systems, Elsevier, vol. 150(C), pages 109-119.

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