Optimal cropping patterns using linear programming and evaluation based on food-energy-water nexus

BACKGROUND AND OBJECTIVES: Agriculture plays a significant role in the overall consumption of freshwater resources, accounting for approximately ۷۰ percent of the total use. Energy is also essential at various stages of agriculture and the food chain. On a global scale, the agricultural and food industries account for approximately ۳۰ percent of the overall energy consumption, with a significant portion derived from fossil fuel sources. This underscores the intricate interconnection between food, energy, and water resources. This study utilizes a linear programming model to determine the optimal cropping pattern while minimizing water usage in agriculture. This study's primary contribution lies in its dual approach: it identifies the optimal cropping patterns for a specified objective function through linear programming while simultaneously conducting a comprehensive analysis of these patterns by integrating considerations of food, energy, and water nexus.METHODS: The constraints applied in linear programming involve maintaining nearly the same agricultural revenue, conserving the total cultivation area, and limiting the change intervals in cultivation area by ۵ percent. Using linear programming, crop patterns were determined for the periods of ۲۰۱۷, ۲۰۲۵-۲۰۵۰, ۲۰۵۰-۲۰۷۵, and ۲۰۷۵-۲۱۰۰. In each scenario, calculations were conducted to assess water consumption, energy demands, agricultural income, and carbon dioxide emissions, all framed within the context of the food-energy-water nexus. The various scenarios were subsequently analyzed to assess their effects. An evaluation was conducted regarding the sustainability of water usage in agricultural production.FINDINGS: All the scenarios examined resulted in lower water usage, reduced energy requirements, and decreased carbon dioxide emissions. Throughout various time periods, scenario ۶, which permits a ۵ percent variation in cultivation areas without imposing a total cultivation area limit, consistently proved to be the most favorable choice. It achieved an average reduction of ۳.۹۴ percent in water usage, ۲.۹۵ percent in energy requirements, and ۱.۶۲ percent in carbon dioxide emissions compared to the base scenario. Scenario ۱۱, allowing for a ۵ percent variation in cultivation areas while maintaining a total cultivation area limit, was evaluated as the second most effective scenario in terms of water conservation. It achieved an average reduction in water use of ۳.۴۵ percent, an average reduction in energy requirements of ۱.۸۵ percent, and a minimal reduction in carbon dioxide emissions of ۰.۱۱ percent across all time periods.CONCLUSION: The outcomes of this study reveal that the proposed model can play a crucial role in advancing sustainable agricultural management strategies. The obtained results indicate that significant reductions in water usage, energy requirements, and carbon dioxide emissions can be achieved simply by modifying the crop pattern, while agricultural income remains largely at the same level. The imposition of a constraint requiring the total cultivation area to be equal to or greater than that of the baseline scenario in the linear programming model has been found to restrict the extent of these reductions.

کلیدواژه ها:

Agricultural production planning ، Crop Pattern ، Linear Programming ، Food energy water nexus ، Optimization