Assessing the value of adapting irrigation strategies within the season

Optimization of irrigation scheduling is a widely proposed solution to enhance agricultural water productivity and mitigate water scarcity. However, there is currently a lack of knowledge about how to most effectively optimize and adapt irrigation decisions under weather and climate uncertainty, or about how the benefits of adaptive irrigation scheduling compare to fixed heuristics commonly used by farmers. In this article, we assess the added value of in-season adaptation of irrigation strategies in comparison to a fixed irrigation strategy that maximizes average profits over a range of plausible weather outcomes, but is not adjusted year-to-year. To perform this assessment, the AquaCrop-OSPy crop-water model is used to simulate a case study of irrigated maize production in a water scarce region in the central United States. Irrigation strategies are defined that maximize mean seasonal profit over a range of historical years. This baseline profit is then compared to the case of adaptive strategies, where the irrigation strategy is re-optimized at multiple stages within each season. Our analysis finds that fixed irrigation heuristics on average achieve over 90 % of potential profits attained with perfect seasonal foresight. In-season adaptation marginally increased agricultural profitability, with greater benefits found when re-optimization occurs more frequently or is accompanied by reliable forecasts of weather for the week ahead. However, the overall magnitude of these additional benefits was small (<5 % further increase in average profits), highlighting that fixed irrigation scheduling rules can be near-optimal when making realistic assumptions about farmers' potential knowledge of future weather. Since fixed irrigation strategies are easier to design, commu-nicate and implement than data-driven adaptive management strategies, we suggest that implementing these fixed strategies be prioritized over the development of more complex adaptive strategies.