A Multi-Objective BMP Optimization Framework for the Jing River Basin Offers Cost-Effective Strategies for Controlling Watershed Pollution

Effective watershed management often employs Biosecurity best practices (BMPs) for lowering pollution levels from non-point sources. It is critical to carefully evaluate the relative relevance of different goals and the integration restrictions before assigning Best Management Practices (BMPs). Decisions involving several qualities and random combinations of multiple Best Management Practices (BMPs) should be considered while investigating a geographically optimum allocation strategy. This framework achieves improved performance by combining the SWAT model with the NSGA-II algorithm. Finding effective water-scale pollution management methods is this research's primary objective. To do this, we will look at a lot of different things, such as how fast total nitrogen (TN) and total phosphorus (TP) is lowered and how much it costs to execute optimum management techniques (BMP). To determine how seriously to take TN and TP, the framework uses the TOPSIS method—which stands for Technique for Order Preference by Similarity to Ideal Solution and Embedded Entropy Weight—to rank them. The sub-basin characteristics are considered to improve the evaluation of regional appropriateness. Best Management Practices (BMPs) in four areas were studied in the Jing River Basin (JRB): tillage, fertilizer, vegetative filter strips, and landscape. Typical decrease rates after implementing these techniques were 9.77%, 10.53%, 16.40%, and 14.27%, correspondingly. Three distinct monetary contexts inform the BMP allocation methods that use multi-objective optimization. In the most affordable plan, which may be implemented with as little as 2 billion RMB, 28.81% of the sub-basins would participate in the Grain for Green program. The "grain for green" initiative is heavily emphasized in places with a slope more than 15° in the medium-cost scenario, which ranges from 2 to 6 billion RMB. This endeavor covers about 20% of the sub-basins. Because of all the interconnected steps, the high-cost scenario is more than 6 billion RMB. With these three design alternatives, decision-makers may weigh the effectiveness of emissions reduction against the costs of implementing the measures. Not only does the new framework make implementation more accessible and cheaper, but it also gives a realistic way for different locations to choose cost-efficient conservation methods.