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Simulation of global crop production with the ecosystem model DayCent

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  • Stehfest, Elke
  • Heistermann, Maik
  • Priess, Joerg A.
  • Ojima, Dennis S.
  • Alcamo, Joseph

Abstract

Agriculture has become a key element within the earth system as it changes global biogeochemical and water cycles, while global environmental change affects land productivity and thus future land-use decisions. To address these issues and their complex interdependency in a consistent modelling approach we adapted the agro-ecosystem model DayCent for the simulation of major crops at the global scale. Based on a global compilation of environmental and management data and an algorithm to calculate global planting dates, DayCent was parameterised and calibrated to simulate global yield levels for wheat, maize, rice and soybeans. Simulation results show that the DayCent model is able to reproduce the major effects of climate, soil and management on crop production. Average simulated crop yield per country agree well with agricultural statistics (Modelling efficiency is about 0.66 for wheat, rice and maize, and 0.32 for soybean) and spatial patterns of yields generally correspond to observed crop distributions and sub-national census data.

Suggested Citation

  • Stehfest, Elke & Heistermann, Maik & Priess, Joerg A. & Ojima, Dennis S. & Alcamo, Joseph, 2007. "Simulation of global crop production with the ecosystem model DayCent," Ecological Modelling, Elsevier, vol. 209(2), pages 203-219.
    • Handle: RePEc:eee:ecomod:v:209:y:2007:i:2:p:203-219
    DOI: 10.1016/j.ecolmodel.2007.06.028
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    2. Srivastava, Amit Kumar & Mboh, Cho Miltin & Gaiser, Thomas & Webber, Heidi & Ewert, Frank, 2016. "Effect of sowing date distributions on simulation of maize yields at regional scale – A case study in Central Ghana, West Africa," Agricultural Systems, Elsevier, vol. 147(C), pages 10-23.
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