A decision support tool for sustainable cropping pattern and irrigation management under water and nitrogen trade offs

Sustainable water and nitrogen management has become a major challenge for agricultural systems, particularly in regions facing increasing water scarcity and environmental degradation. Hence, this study integrated the Decision Support System for Agrotechnology Transfer (DSSAT) with a multi-objective optimization framework to evaluate optimal cropping patterns in the Darion Plain, Fars Province, Iran, during the 2022–2023 growing season. Unlike traditional single-objective approaches, the augmented ε-constraint method was employed to generate Pareto-optimal solutions that maximize economic profitability and minimize water loss, while nitrogen leaching was evaluated as an environmental outcome under a fixed nitrogen application rate. The results showed that current management practices lead to unnecessary water consumption and elevated nitrogen leaching, while optimized cropping patterns can substantially reduce environmental impacts without imposing major economic losses. In addition, water loss is translated into an implicit economic cost using a shadow price approach, allowing the economic value of water-saving scenarios to be explicitly assessed across alternative cropping patterns. Overall, this research develops a decision-support tool that helps farmers and policymakers identify cropping strategies that balance profitability with long-term environmental sustainability.