Regional water resource allocation has emerged as a critical challenge worldwide due to increasing water scarcity, growing population, and competing demands from various sectors. This study develops a comprehensive multi-objective optimization model for regional water resource allocation that simultaneously considers economic efficiency, social equity, and environmental sustainability. The model incorporates three objective functions: maximizing net economic benefits from water use across agricultural, industrial, domestic, and ecological sectors; minimizing water shortage ratios to ensure supply reliability; and minimizing pollutant emissions to protect water quality. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to solve the multi-objective optimization problem, generating a Pareto front of non-dominated solutions that represent optimal trade-offs among the conflicting objectives. The methodology is applied to a representative water-scarce region characterized by diverse water sources including surface water, groundwater, and reclaimed water. Scenario analyses are conducted under different hydrological conditions (wet, normal, dry, and drought years) and planning horizons (short-term 2028 and long-term 2035) to evaluate the robustness and adaptability of allocation strategies. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is integrated with coupling coordination degree measurement to identify the most balanced allocation scheme from the Pareto solution sets. Results demonstrate that the proposed model effectively resolves conflicts among competing objectives, with optimal allocation schemes achieving economic benefits ranging from 165.78 × 10⁸ to 218.45 × 10⁸ CNY, water shortage rates controlled between 1.42% and 11.23%, and pollutant emissions maintained between 5.89 × 10⁴ and 7.12 × 10⁴ tons across different scenarios. The coupling coordination degrees for most scenarios exceed 0.8, indicating good coordination among economic, social, and environmental systems. This research provides a scientific basis and practical decision-support tool for regional water resource managers facing complex trade-offs under uncertainty.

Yunbo Pu. Research on Regional Water Resource Allocation Based on Multi-Objective Optimization Model. International Journal of New Developments in Engineering and Society (2026), Vol. 10, Issue 1: 39-45. https://doi.org/10.25236/IJNDES.2026.100106.

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