Rapid socio-economic development has intensified the conflict between supply and demand for regional water resources, necessitating optimized water resource allocation to enhance water security. This study establishes a multi-objective water resource optimization model by comprehensively considering economic, social, and ecological benefits. Based on the Non-dominated Sorting Genetic Algorithm-III (NSGA-III), we propose the I-NSGA-III algorithm by integrating reference point improvement strategies, dynamic retention of high-quality solutions, and optimized selection strategies to solve the multi-objective optimization model. A multi-system coupling coordination evaluation model is constructed to assess the final allocation schemes. Compared with some commonly used multi-objective algorithms and tested using the DTLZ series functions, the proposed algorithm demonstrates improved overall performance. Specifically, the IGD indicator decreases by 5.17–50.22%, and the HV indicator increases by 2.71–25.51% compared to NSGA-III. The proposed model is applied to Jinzhong City, China, with four scenarios set for the years 2030 and 2035 at P = 50% and P = 75% to derive reasonable water resource allocation schemes. The results show that the economic benefits range from 161.94 × 10⁸ to 212.74 × 10⁸ CNY, the water shortage rate is controlled between 1.38% and 10.86%, and COD emissions are maintained between 6.03 × 10⁴ and 6.91 × 10⁴ tons. Except for the 2030 drought scenario (P = 75%) with a coordination degree of 0.7847, classified as a medium coordination level, all other scenarios have coordination degrees greater than 0.8, indicating a good coordination level. The optimized allocation scheme can serve as a reference for the rational allocation of water resources in Jinzhong City. Moreover, the method proposed in this paper is a general approach that can be extended to other similar water-scarce cities with appropriate parameter adjustments, contributing to the sustainable development of urban water resources.