Strategic crop reallocation for reduced agricultural water footprints in semi-arid regions

Agricultural water use in semi-arid regions faces three critical challenges: stabilizing agricultural production, maintaining district-level revenues, and conserving increasingly scarce water resources. This study develops the first district-level water footprint (WF) optimization framework for Türkiye, covering 969 districts and 18 crops, while enforcing production quotas and revenue-neutrality constraints. Türkiye serves as a representative case study due to its semi-arid climate, extensive irrigated agriculture, and pronounced spatial heterogeneity in hydroclimatic conditions. District-level WF maps were constructed using meteorological data from 756 stations (2013–2022) and the FAO-56 methodology; they reveal that Türkiye’s agriculture consumes 106.2 Gm³ annually (67.3 Gm³ blue, 38.9 Gm³ green). Wheat and barley account for 60% of national use, with critical stress concentrated in Central Anatolia and the southeast, where efficiency gaps are most pronounced. Building on these spatial patterns, a strictly linear programming model (17,442 variables, 2,956 constraints, solved via MATLAB linprog) was developed to minimize blue water consumption while maintaining national production quotas and district-level revenues. Under idealized assumptions of perfect spatial flexibility, the optimization indicates potential efficiency gains: blue water use decreases by ≈ 32%, total WF by 25%, and cultivated area by 22%. Sensitivity analyses across interpolation methods, quota adjustments (± 10%), and climate perturbations indicate that these savings estimates and spatial efficiency rankings remain robust to methodological variations. The framework demonstrates how binding production and revenue constraints can be integrated into spatial WF optimization for semi-arid regions facing similar water-agriculture trade-offs.