IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v120y2013icp61-75.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X1300070X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2013.05.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Christine Heumesser & Sabine Fuss & Jana Szolgayová & Franziska Strauss & Erwin Schmid, 2012. "Investment in Irrigation Systems under Precipitation Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3113-3137, September.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Xiong, Wei & Holman, Ian & Conway, Declan & Lin, Erda & Li, Yue, 2008. "A crop model cross calibration for use in regional climate impacts studies," Ecological Modelling, Elsevier, vol. 213(3), pages 365-380.
    8. 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.
    9. 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.
    10. 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.
    11. Billen, Norbert & Röder, Clara & Gaiser, Thomas & Stahr, Karl, 2009. "Carbon sequestration in soils of SW-Germany as affected by agricultural management—Calibration of the EPIC model for regional simulations," Ecological Modelling, Elsevier, vol. 220(1), pages 71-80.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiong, Wei & Balkovič, Juraj & van der Velde, Marijn & Zhang, Xuesong & Izaurralde, R. César & Skalský, Rastislav & Lin, Erda & Mueller, Nathan & Obersteiner, Michael, 2014. "A calibration procedure to improve global rice yield simulations with EPIC," Ecological Modelling, Elsevier, vol. 273(C), pages 128-139.
    2. Wang, Zhiqiang & Ye, Li & Jiang, Jingyi & Fan, Yida & Zhang, Xiaoran, 2022. "Review of application of EPIC crop growth model," Ecological Modelling, Elsevier, vol. 467(C).
    3. Kirchner, Mathias & Mitter, Hermine & Schönhart, Martin & Schmid, Erwin, 2014. "Integrated land use modelling to analyse climate change adaptation in Austrian agriculture," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182944, European Association of Agricultural Economists.
    4. Kirchner, Mathias & Schmidt, Johannes & Kindermann, Georg & Kulmer, Veronika & Mitter, Hermine & Prettenthaler, Franz & Rüdisser, Johannes & Schauppenlehner, Thomas & Schönhart, Martin & Strauss, Fran, 2015. "Ecosystem services and economic development in Austrian agricultural landscapes — The impact of policy and climate change scenarios on trade-offs and synergies," Ecological Economics, Elsevier, vol. 109(C), pages 161-174.
    5. Feusthuber, Elisabeth & Mitter, Hermine & Schönhart, Martin & Schmid, Erwin, 2017. "Integrated modelling of efficient crop management strategies in response to economic damage potentials of the Western Corn Rootworm in Austria," Agricultural Systems, Elsevier, vol. 157(C), pages 93-106.
    6. Mitter, Hermine & Schmid, Erwin, 2019. "Computing the economic value of climate information for water stress management exemplified by crop production in Austria," Agricultural Water Management, Elsevier, vol. 221(C), pages 430-448.
    7. Karner, Katrin & Schmid, Erwin & Schneider, Uwe A. & Mitter, Hermine, 2021. "Computing stochastic Pareto frontiers between economic and environmental goals for a semi-arid agricultural production region in Austria," Ecological Economics, Elsevier, vol. 185(C).
    8. Mosnier, A. & Havlík, P. & Valin, H. & Baker, J. & Murray, B. & Feng, S. & Obersteiner, M. & McCarl, B.A. & Rose, S.K. & Schneider, U.A., 2013. "Alternative U.S. biofuel mandates and global GHG emissions: The role of land use change, crop management and yield growth," Energy Policy, Elsevier, vol. 57(C), pages 602-614.
    9. Tatiana Ermolieva & Petr Havlik & Andrey Lessa-Derci-Augustynczik & Stefan Frank & Juraj Balkovic & Rastislav Skalsky & Andre Deppermann & Mahdi (Andrè) Nakhavali & Nadejda Komendantova & Taher Kahil , 2024. "Tracking the Dynamics and Uncertainties of Soil Organic Carbon in Agricultural Soils Based on a Novel Robust Meta-Model Framework Using Multisource Data," Sustainability, MDPI, vol. 16(16), pages 1-23, August.
    10. Mitter, Hermine & Heumesser, Christine & Schmid, Erwin, 2014. "Modelling robust crop production portfolios to assess agricultural vulnerability to climate change," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182702, European Association of Agricultural Economists.
    11. Kieu N. Le & Manoj K. Jha & Jaehak Jeong & Philip W. Gassman & Manuel R. Reyes & Luca Doro & Dat Q. Tran & Lyda Hok, 2018. "Evaluation of Long-Term SOC and Crop Productivity within Conservation Systems Using GFDL CM2.1 and EPIC," Sustainability, MDPI, vol. 10(8), pages 1-17, July.
    12. Rodrigues, Gonçalo C. & Paredes, Paula & Gonçalves, José M. & Alves, Isabel & Pereira, Luis S., 2013. "Comparing sprinkler and drip irrigation systems for full and deficit irrigated maize using multicriteria analysis and simulation modelling: Ranking for water saving vs. farm economic returns," Agricultural Water Management, Elsevier, vol. 126(C), pages 85-96.
    13. Adam, M. & Van Bussel, L.G.J. & Leffelaar, P.A. & Van Keulen, H. & Ewert, F., 2011. "Effects of modelling detail on simulated potential crop yields under a wide range of climatic conditions," Ecological Modelling, Elsevier, vol. 222(1), pages 131-143.
    14. Henseler, Martin & Dechow, Rene, 2014. "Simulation of regional nitrous oxide emissions from German agricultural mineral soils: A linkage between an agro-economic model and an empirical emission model," Agricultural Systems, Elsevier, vol. 124(C), pages 70-82.
    15. Vázquez-Montenegro, Ranses José & Durán-Zarabozo, Odil & Baca, Marcio, 2015. "Modelos de impacto en la agricultura teniendo en cuenta los escenarios de la agricultura del cambio climático," Revista Iberoamericana de Bioeconomía y Cambio Climàtico, National Autonomous University of Nicaragua, Leon, vol. 1(1), pages 1-50, July.
    16. Le, Kieu N. & Jeong, Jaehak & Reyes, Manuel R. & Jha, Manoj K. & Gassman, Philip W. & Doro, Luca & Hok, Lyda & Boulakia, Stéphane, 2018. "Evaluation of the performance of the EPIC model for yield and biomass simulation under conservation systems in Cambodia," Agricultural Systems, Elsevier, vol. 166(C), pages 90-100.
    17. 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.
    18. Yan, Dan & Schneider, Uwe A. & Schmid, Erwin & Huang, He Qing & Pan, Lihu & Dilly, Oliver, 2013. "Interactions between land use change, regional development, and climate change in the Poyang Lake district from 1985 to 2035," Agricultural Systems, Elsevier, vol. 119(C), pages 10-21.
    19. Choruma, Dennis Junior & Balkovic, Juraj & Pietsch, Stephan Alexander & Odume, Oghenekaro Nelson, 2021. "Using EPIC to simulate the effects of different irrigation and fertilizer levels on maize yield in the Eastern Cape, South Africa," Agricultural Water Management, Elsevier, vol. 254(C).
    20. Pål Börjesson & Serina Ahlgren & Göran Berndes, 2012. "The climate benefit of Swedish ethanol: present and prospective performance," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 1(1), pages 81-97, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:120:y:2013:i:c:p:61-75. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.