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Influence of climate change on short term management of field crops – A modelling approach

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  • Aurbacher, Joachim
  • Parker, Phillip S.
  • Calberto Sánchez, Germán A.
  • Steinbach, Jennifer
  • Reinmuth, Evelyn
  • Ingwersen, Joachim
  • Dabbert, Stephan

Abstract

Climatic change is likely to have an influence on arable farms in Central Europe. We use a modelling approach to assess the effects of weather and its long term development due to climate change on short-term decisions like planting and harvesting, as well as yields. Two models are coupled, a farm management model FarmActor and the crop growth model system Expert-N to investigate the interplay between management and crop growth on a daily basis. We examine different methods of adapting expectations concerning the timing of cropping actions and annual yields to actual observed weather and yield data. Our study focuses on the two major crops winter wheat and silage maize in the Swabian Alb in southwestern Germany. Results show that the model can satisfactorily reproduce the development of planting and harvesting as well as yields that have occurred in the past. Different methods of expectation formation only show minor differences in their effect on action dates and yields. Future climatic change is likely to shift the timing of field actions. Assuming no change in technology (e.g. cultivars), summer crops may be seeded earlier while winter crops could tend to be sown later; harvest may occur earlier and yields might slightly decrease while showing more volatility. This modelling approach has the potential to increase the knowledge about risk profiles of short time agricultural management actions and to improve the land use modelling part of coupled earth system models.

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  • Aurbacher, Joachim & Parker, Phillip S. & Calberto Sánchez, Germán A. & Steinbach, Jennifer & Reinmuth, Evelyn & Ingwersen, Joachim & Dabbert, Stephan, 2013. "Influence of climate change on short term management of field crops – A modelling approach," Agricultural Systems, Elsevier, vol. 119(C), pages 44-57.
  • Handle: RePEc:eee:agisys:v:119:y:2013:i:c:p:44-57
    DOI: 10.1016/j.agsy.2013.04.005
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    2. Utomo, Dhanan Sarwo & Onggo, Bhakti Stephan & Eldridge, Stephen, 2018. "Applications of agent-based modelling and simulation in the agri-food supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 794-805.
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    5. Charlotte Till & Jamie Haverkamp & Devin White & Budhendra Bhaduri, 2018. "Understanding climate-induced migration through computational modeling: A critical overview with guidance for future efforts," The Journal of Defense Modeling and Simulation, , vol. 15(4), pages 415-435, October.
    6. Schönhart, Martin & Schauppenlehner, Thomas & Schmid, Erwin, 2014. "Integrated land use modelling of climate change impacts in two Austrian case study landscapes at field level," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182680, European Association of Agricultural Economists.
    7. Sylvie Geisendorf, 2018. "Evolutionary Climate-Change Modelling: A Multi-Agent Climate-Economic Model," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 921-951, October.
    8. El Chami, D. & Knox, J.W. & Daccache, A. & Weatherhead, E.K., 2015. "The economics of irrigating wheat in a humid climate – A study in the East of England," Agricultural Systems, Elsevier, vol. 133(C), pages 97-108.
    9. Robert, Marion & Thomas, Alban & Sekhar, Muddu & Badiger, Shrinivas & Ruiz, Laurent & Raynal, Hélène & Bergez, Jacques-Eric, 2017. "Adaptive and dynamic decision-making processes: A conceptual model of production systems on Indian farms," Agricultural Systems, Elsevier, vol. 157(C), pages 279-291.
    10. Sylvie Geisendorf, 2016. "The impact of personal beliefs on climate change: the “battle of perspectives” revisited," Journal of Evolutionary Economics, Springer, vol. 26(3), pages 551-580, July.
    11. Traore, Seydou & Zhang, Lei & Guven, Aytac & Fipps, Guy, 2020. "Rice yield response forecasting tool (YIELDCAST) for supporting climate change adaptation decision in Sahel," Agricultural Water Management, Elsevier, vol. 239(C).
    12. Aurbacher, Joachim & Rabenau, Philip, 2021. "Interactive Modelling with Agricultural Stakeholders using Bayesian Networks," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317058, German Association of Agricultural Economists (GEWISOLA).

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