Risk is an undeniable factor in agricultural activities, and its neglect can lead to inefficient resource allocation in the sector. Various theories and mathematical programming models have been developed to assist decision-making in crop pattern management under risk conditions. This study aimed to determine the optimal cropping pattern for Dehgolan Plain, Iran, using data from 2014 to 2023. A linear programming model was employed to maximize farmers' gross income, and the results were compared with those from a Quadratic Programming Model and the Minimization of Total Absolute Deviation (MOTAD) model, both incorporating risk minimization. The findings indicated that risk factor can significantly alter the cropping pattern, particularly, at the highest level of risk, the profit maximizing cropping pattern included only cucumber, alfalfa, and canola, reflecting a preference for higher-gross-income crops despite their greater water requirements. Incorporating risk led to an increase in the cultivation area of wheat and barley compared to the risk-agnostic scenario, indicating a shift toward lower-water-requirement crops at the expense of reduced gross income. These results highlight the necessity of balancing income maximization and risk management for more sustainable cropping pattern.
