Unraveling spatial patterns and source attribution of nutrient transport: Towards optimal best management practices in complex river basin

被引:4
|
作者
Sun, Huihang [1 ]
Tian, Yu [1 ,4 ]
Li, Lipin [1 ]
Zhuang, Yu [1 ]
Zhou, Xue [1 ]
Zhang, Haoran [1 ]
Zhan, Wei [1 ]
Zuo, Wei [1 ]
Luan, Chengyu [2 ]
Huang, Kaimin [3 ]
机构
[1] Harbin Inst Technol, Sch Environm, State Key Lab Urban Water Resource & Environm, Harbin 150090, Peoples R China
[2] Urban Water Resources Co Ltd, Harbin Inst Technol, Natl Engn Res Ctr, Harbin 150090, Peoples R China
[3] Guangdong Yuehai Water Investment Co Ltd, Shenzhen 518021, Peoples R China
[4] Harbin Inst Technol, Sch Environm, POB 2603,73 Huanghe Road, Harbin 150090, Heilongjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Nitrogen and phosphorus load; Spatiotemporal pattern; Pollution source attribution; SWAT; Best management practices; RSM-coupled NSGA-II; PHOSPHORUS; POLLUTION; NITROGEN; MODEL; SIMULATION; ALGORITHM;
D O I
10.1016/j.scitotenv.2023.167686
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A comprehensive understanding of nutrient transport patterns and clarification of pollutant sources' load contributions are critical prerequisites for developing scientific pollution control strategies in complex river basins. Here, we focused on the Minjiang River Basin (MRB) and employed the Soil and Water Assessment Tool (SWAT) model to systematically investigate the nitrogen (N) and phosphorus (P) loads from both point and non-point sources. Results revealed that the key source areas of N and P pollution in the MRB were predominantly located along the riverbanks, influenced by a combination of sediment, precipitation, agricultural activities such as fertilization. Our analysis indicated that soil nutrient loss, fertilization, and livestock farming were the major contributors to N and P inputs, accounting for over 70 % of the total input, followed by rural residential and urban point sources. Based on the identification of non-point source pollution as the primary load source, a multi objective optimization was conducted using response surface methodology (RSM) coupled with the non dominated sorting genetic algorithm-II (NSGA-II), resulting in the identification of optimal best management practices (BMPs) that achieve a reduction of 40.04 % in N load, 39.22 % in P load, and a net economic benefit of -1.13 billion yuan per year. Compared to the RSM and automated optimization results, the proposed management measures exhibited significant improvements in N and P load reduction and net benefits. Overall, the findings provide important insights for formulating agricultural management policies in the MRB and offering valuable implications for pollution management in other complex river basins.
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页数:14
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