📝 SummarXiv

Abstract

Water resource management is vital for sustainable irrigation and food security under growing climatic and economic pressures. In this study, we develop two single-objective optimization models for irrigation planning, one that maximizes net benefit and the other that minimizes environmental flow deficiency, and benchmark them against previous works. We then extend the analysis to a multiobjective linear programming formulation solved through different approaches to evaluate trade-offs. Numerical experiments on the Muhuri Irrigation Project reveal three outcomes: (i) a complete scenario view with profits ranging from $0.2 \times 10^9$ to $1.497\times 10^9$ and environmental flow deficits between 0 and 1200 GL, where the 1200 GL represents the theoretical annual maximum under a 100 GL uniform monthly target; (ii) explicit trade-offs showing higher profits correspond to greater ecological shortfalls; and (iii) an integration-based approach producing nearly 1000 Pareto-optimal solutions within seconds, greatly outperforming earlier studies.