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

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  • Xu, Zhongwen
  • Tan, Shiqi

Abstract

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.

Suggested Citation

  • Xu, Zhongwen & Tan, Shiqi, 2026. "From grain to ground: How hydrologic uncertainty drives shifts in crop patterns across the Yellow River Basin," Agricultural Water Management, Elsevier, vol. 323(C).
    • Handle: RePEc:eee:agiwat:v:323:y:2026:i:c:s0378377425007723
    DOI: 10.1016/j.agwat.2025.110058
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    References listed on IDEAS

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