Crop simulation models are important tools for yield projection and analysis but are rarely used for real-time decision support due to persistent bottlenecks in data management and processing workflows to generate input datasets. We present a blueprint for a semi-automated data management workflow that enables high-throughput simulation, integrating diverse source data into a rapid, scalable pipeline. The modular workflow leverages established standards in geospatial science, agronomy, and crop modeling to assemble high-quality inputs for crop models. The blueprint outlines the technical requirements to operationalize crop models, enabling broader applications as decision-support tools.
Leroy et al. (Thu,) studied this question.
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