Water scarcity poses a significant threat to global food security, with the agricultural sector being the largest consumer of freshwater resources. In arid and semi-arid regions, this challenge is exacerbated by inefficient irrigation practices. Despite global promotion of pressurized irrigation systems, traditional surface methods, particularly border irrigation, remain dominant due to their low cost and operational simplicity. However, these systems often suffer from low application efficiency and non-uniform water distribution, leading to substantial water losses and reduced agricultural productivity. This thesis addresses the critical research gap in the holistic optimization of border irrigation systems by developing a novel hydraulic-economic simulation-optimization model. The proposed framework integrates an advanced hydraulic simulation module, based on a modified Soil Conservation Service (SCS) infiltration model, with a comprehensive economic analysis module. The hydraulic module accurately simulates the key phases of irrigation—advance, recession, and infiltration—to compute performance indicators such as Application Efficiency (Ea), Distribution Uniformity (DU), and Deep Percolation Ratio (DPR). The economic module aggregates costs related to water, labor, fertilizer (lost through leaching), and drainage over an entire irrigation season. The core of the model lies in its coupling with the Non-dominated Sorting Genetic Algorithm II (NSGA-II), a robust multi-objective meta-heuristic algorithm. This integration allows for the simultaneous optimization of conflicting objectives: minimizing a composite hydraulic inefficiency index (zHyd) and minimizing the total economic cost (zEco). The model was applied to both the design of new systems and the evaluation and optimization of existing ones. The results demonstrate the model's transformative potential. For a new system design, optimization led to a configuration with a milder slope and shorter border length, which improved Application Efficiency from 42.1% to over 89% and reduced economic costs by approximately 63%. For an existing system, operational optimization identified a "low inflow rate, long duration" strategy that achieved near-perfect efficiency (Ea and DU of 100%) and reduced costs by up to 69.5%. The study generates Pareto-optimal solutions, providing a clear decision-support tool for stakeholders to balance water conservation with economic profitability based on local priorities. In conclusion, this research provides a scientifically rigorous and practically applicable framework for enhancing the sustainability of border irrigation. By bridging the gap between theoretical hydraulic modeling and on-farm economic realities, it offers a viable pathway for significantly improving water productivity and strengthening agricultural resilience in water-scarce regions.
