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

Rohit Nandan, Varaprasad Bandaru, Pridhvi Meduri, Curtis Jones and Romulo Lollato

Agricultural Systems, 2024, vol. 220, issue C

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.

Keywords: Stochastic weather generators; Yield forecasting; Crop model; K-nearest neighbor; Vector-autoregressive (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:220:y:2024:i:c:s0308521x24002324

DOI: 10.1016/j.agsy.2024.104082

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