From grain to ground: How hydrologic uncertainty drives shifts in crop patterns across the Yellow River Basin

China’s arable land exploitation has intensified water scarcity, threatening food security. To address the interdependent land-water-food nexus, this study develops a robust bi-objective optimization model for agricultural resource allocation under hydrologic uncertainty. Applied to the Yellow River Basin, the model balances water use efficiency with land productivity. Results indicate that (1) optimal planting patterns vary significantly across regions to balance efficiency and equity; (2) under 10–30 % water reduction scenarios, water-intensive paddy areas decrease by up to 15 %, while wheat and maize expand by 5–12 %, particularly in arid regions; (3) higher risk-awareness reduces overall efficiency but enhances inter-provincial fairness; and (4) irrigation technology innovation serves as a transformative pathway to sustain productivity under climate risk. By integrating hydrologic uncertainty into a comprehensive land-water-food framework, this research offers robust, policy-relevant solutions for safeguarding food security, promoting sustainable land use, and improving water management practices in water-limited regions, thereby supporting global sustainability transitions. • A robust bi-objective model optimizes regional agricultural water allocation under uncertainty. • Crop pattern shifts reveal trade-offs between water productivity (efficiency) and provincial equity. • Increasing hydrologic uncertainty decreases overall system efficiency but enhances fairness in water use. • Advanced irrigation technology is a key strategy to improve both water productivity and fairness simultaneously. • Model provides practical, risk-aware water management strategies for the Yellow River Basin.