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- W4384120587 abstract "The protection of the Yangtze River is an important national strategy in China, but it faces many problems such as difficult water environment protection, unclear pollution sources, and low integration of measures. Aimed at addressing watershed scale multi-source pollution together with facing the bottleneck method, by combining research data analysis, mechanism model, and intelligent algorithm optimization, this study built the framework for accurate pollution apportionment, measures evaluation, and overall measure optimization. Shun'an watershed in Tongling City of Anhui Province was set as an example for the application. The results showed that the new method could accurately quantify the impacts of planting industry, rural life, livestock and poultry breeding, aquaculture, industrial sewage, and domestic sewage in the watershed and evaluate the overall effects of various measures. The multi-objective optimization algorithm provided a cooperative multi-source pollution control scheme with higher cost performance and better environmental benefit by comparing the cost effectiveness of various schemes systematically. The optimization scheme showed that total nitrogen could be reduced by 1274.24 t·a-1 in wet years, 855.24 t·a-1 in normal years, and 381.96 t·a-1 in dry years. Total phosphorus was reduced by 321.42 t·a-1 in wet years, 159.80 t·a-1 in normal years, and 42.93 t·a-1 in dry years, such that the water quality reached the surface class Ⅲ water quality standard. These research results can be extended to other watersheds and provide a method reference for water environment protection under the background of the high-quality development of watersheds." @default.
- W4384120587 created "2023-07-14" @default.
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- W4384120587 date "2023-07-08" @default.
- W4384120587 modified "2023-10-16" @default.
- W4384120587 title "[Simulation of Pollution Apportionment and Optimization of Control Methods in Watershed Scale: A Case Study of the Shun'an Watershed in Tongling City]." @default.
- W4384120587 doi "https://doi.org/10.13227/j.hjkx.202207102" @default.
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