Multi-objective cropping pattern optimization and comparative assessment with the food-energy-water nexus

Agriculture is the largest consumer of water, accounting for nearly 70% of global freshwater consumption, and it also uses about 30% of the world’s energy. This creates an increasing challenge for the efficient use of water and energy resources while adequately meeting food demand. Therefore, understanding the interrelations between food, energy, and water resources is crucial. In this study, a multi-objective linear programming model was employed to identify alternative scenarios for optimal cropping areas that minimize water use in agriculture and maximize agricultural income. Different weight coefficients were assigned to these objective functions to generate various cropping scenarios. Once the optimal cropping patterns for each scenario were determined, parameters such as water use, energy requirements, agricultural revenue, and carbon dioxide emissions were calculated based on the food-energy-water nexus. The results for each alternative crop pattern scenario were then analyzed. The results indicate that prioritizing the objective of minimizing water use leads to an average reduction of 3.35% in water use, 1.18% in energy demand, and 0.26% in carbon dioxide emissions, while agricultural income increases by an average of 1% compared to the base scenario. Conversely, when maximizing agricultural income is prioritized, there is an average increase of 2.05% in agricultural income.