A new vector-based framework combining AquaCrop, CROPWAT, WEAP, and multi-objective programming for optimizing crop allocation under water scarcity.

Effective crop land-use allocation requires evaluating both the potential of land units and the demand for various crops to identify optimal strategies. This paper presents a new vector-based framework that combines AquaCrop for crop-water requirement estimation, CROPWAT for reference evapotranspiration, GAMS for multi-objective optimization, and WEAP for basin-level water allocation. The model operates directly on agricultural-plot polygons to enable spatially explicit optimization that balances agricultural income and production costs. The model’s plausibility for real-world planning was validated by comparing simulated cultivated areas against official statistics, showing a close agreement with a total difference of only 0.2%. Application of the framework to the water-scarce Borkhar & Meymeh district in Isfahan Province, Iran, uncovered a severe baseline water deficit where a substantial portion of the crop water requirements remained unmet. To address this, the model evaluated management scenarios and identified that a 45% reduction in total cultivation area—when spatially optimized alongside crop suitability—could be effective. This strategy significantly improved system performance by reducing the unmet water requirement from 45.8% in the baseline to 26.5% in the most restrictive scenario. Overall, this spatial optimization resulted in a 19.3% improvement in system-wide water reliability compared to existing conditions. The proposed model provides a robust decision-support framework for improving agricultural productivity and designing adaptive management strategies in water-scarce regions.