A Multi-Objective Trade-Off Analysis with NSGA-II and Pareto Strategies for Total Phosphorus Load Allocation and Engineering Configuration in Yangcheng Lake Basin

Yangcheng Lake, the third largest freshwater lake in the Taihu Plain (118.68 km²), serves critical functions in drinking water supply, aquaculture, and ecological regulation. This study aims to address the challenge of optimizing total phosphorus load allocation and engineering project configuration in the Yangcheng Lake basin by developing a multi-objective optimization model that integrates environmental, social, and economic dimensions with the goal of achieving three specific objectives: (1) maximizing ecological benefits, (2) minimizing life-cycle costs, and (3) minimizing the environmental Gini coefficient. The NSGA-II algorithm was used, with hyperparameters calibrated via orthogonal experiments and HV-GD evaluation. Under a normal flow year scenario, total phosphorus (TP) load allocation was optimized for an agricultural watershed where livestock manure contributes 86.5% of TP pollution. Five selection strategies (Economic Priority, Ecological Priority, Equity Priority, Ideal Point Method, Game Theory) were applied to the Pareto front. Results show synergy between ecological and equity objectives, both competing with economic cost. Optimal hyperparameters were a population size of 1000 and 1000 iterations. Among strategies, the Ideal Point Method achieved the best compromise (economic cost: 5772.7; Gini coefficient < 0.30). The proposed framework provides scientific support for pollution load allocation in plain river network regions, helping decision-makers balance economic development, ecological protection, and social equity.