Integrating Subseasonal-to-Seasonal Forecasts into Agricultural Decision Support Systems: A Critical Review and Research Agenda

Xin-Zhong Liang

doi:10.1016/j.eng.2026.05.015

Engineering ›› :202605015 DOI: 10.1016/j.eng.2026.05.015

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Integrating Subseasonal-to-Seasonal Forecasts into Agricultural Decision Support Systems: A Critical Review and Research Agenda

Xin-Zhong Liang ^a^,^b^,^*

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Abstract

Agricultural decision support systems (ADSS) are designed to translate complex data into actionable insights for farm management. However, a significant gap persists between the growing skill of subseasonal-to-seasonal (S2S) climate forecasts and their operational use in supporting tactical agricultural decisions. This review critically examines the current state and future trajectory of ADSS, with a focus on bridging this gap. The analysis reveals that while modern ADSS excel in operational and strategic planning using historical data, they largely fail to integrate operational S2S forecasts, leaving farmers vulnerable to near-term climate anomalies. Advances and challenges are synthesized across three interconnected fronts: the methodological pipeline for integrating S2S forecasts, including downscaling, bias correction, and uncertainty quantification; the imperative of participatory design and coproduction to enhance usability and adoption; and the transformative potential of artificial intelligence and machine learning under the emerging Agriculture 5.0 paradigm. The next generation of ADSS must evolve into interactive, uncertainty-aware platforms that facilitate exploratory decision-making through bidirectional feedback loops. By synthesizing these insights, this review proposes a conceptual framework and research agenda for developing ADSS capable of truly supporting climate-resilient agriculture.

Keywords

Agricultural decision support systems / Subseasonal-to-seasonal forecasts / Climate-resilient agriculture / Artificial intelligence and machine learning / Participatory design and coproduction

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Xin-Zhong Liang. Integrating Subseasonal-to-Seasonal Forecasts into Agricultural Decision Support Systems: A Critical Review and Research Agenda. Engineering 202605015 DOI:10.1016/j.eng.2026.05.015

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