A genetic algorithm-based framework for scenario-driven optimization of cropping patterns using water footprint economic value

Optimizing cropping patterns is an effective strategy for improving agricultural water productivity and supporting sustainable water management in arid and semi-arid regions. This study optimized the spatial cultivation pattern of wheat and barley in six counties of Alborz Province, Iran, using a Genetic Algorithm (GA) and the economic water footprint (WFe) as a decision-support indicator. Four management scenarios were developed to evaluate the effects of alternative resource constraints: Scenario 1 removed the cultivated-area constraint while maintaining water availability and minimum production at current levels; Scenario 2 maintained the current cultivated-area and minimum production requirements but removed the water constraint; Scenario 3 maintained current cultivated-area and water constraints while removing the production constraint; and Scenario 4 allowed the maximum available cultivated area while maintaining current water availability and minimum production requirements. The spatial analysis showed that the water footprint (WF) ranged from 0.57–1.07 m³ kg⁻¹ for wheat and 0.58–0.83 m³ kg⁻¹ for barley, indicating substantial spatial variability associated with local climatic conditions and irrigation requirements. Under the current cultivation pattern, WFe ranged from 1.11 m³ $⁻¹ in Karaj to 2.14 m³ $⁻¹ in Taleghan, demonstrating considerable spatial differences in economic water performance. Under Scenario 1, the optimized WFe ranged from 1.54 to 2.98 m³ $⁻¹, with most cultivated land allocated to barley except where production requirements necessitated wheat cultivation. Scenario 2 resulted in WFe values of 1.57–2.93 m³ $⁻¹ and concentrated wheat production in Nazarabad while increasing barley cultivation in other counties. Scenario 3 produced the highest reported WFe range (1.83–3.17 m³ $⁻¹), with the optimized solution allocating the available cultivated area and water resources predominantly to barley in the absence of a production constraint. Scenario 4 resulted in WFe values ranging from 1.64 to 3.00 m³ $⁻¹ under simultaneous land, water, and production constraints. Overall, the scenario analysis demonstrated that water availability and the interaction between cultivated-area and production constraints strongly influence the spatial allocation of crops and economic water performance. The results further indicate that relaxing production constraints can improve the economic water-efficiency objective but may lead to crop specialization and reduced maintenance of baseline production levels. Therefore, integrating water-footprint-based indicators with land, water, and production constraints can provide a useful decision-support framework for regional cropping-pattern planning in water-stressed agricultural systems.