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Evaluating the utility of weather generators in crop simulation models for in-season yield forecasting

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Listed:
  • Nandan, Rohit
  • Bandaru, Varaprasad
  • Meduri, Pridhvi
  • Jones, Curtis
  • Lollato, Romulo

Abstract

Crop yield forecasting is crucial for ensuring food security and adapting to the impacts of climate change, as it provides early insights into potential harvest outcomes and helps farmers and policymakers make informed decisions in the face of changing environmental conditions. The accuracy of the crop model–based yield forecasting frameworks is affected by the uncertainty in future weather data, which is often substituted with synthetic weather realizations generated by stochastic weather generators.

Suggested Citation

  • Nandan, Rohit & Bandaru, Varaprasad & Meduri, Pridhvi & Jones, Curtis & Lollato, Romulo, 2024. "Evaluating the utility of weather generators in crop simulation models for in-season yield forecasting," Agricultural Systems, Elsevier, vol. 220(C).
    • Handle: RePEc:eee:agisys:v:220:y:2024:i:c:s0308521x24002324
    DOI: 10.1016/j.agsy.2024.104082
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    References listed on IDEAS

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    1. Capa-Morocho, Mirian & Ines, Amor V.M. & Baethgen, Walter E. & Rodríguez-Fonseca, Belén & Han, Eunjin & Ruiz-Ramos, Margarita, 2016. "Crop yield outlooks in the Iberian Peninsula: Connecting seasonal climate forecasts with crop simulation models," Agricultural Systems, Elsevier, vol. 149(C), pages 75-87.
    2. Lecerf, Rémi & Ceglar, Andrej & López-Lozano, Raúl & Van Der Velde, Marijn & Baruth, Bettina, 2019. "Assessing the information in crop model and meteorological indicators to forecast crop yield over Europe," Agricultural Systems, Elsevier, vol. 168(C), pages 191-202.
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