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Allocating Water Environmental Capacity to Meet Water Quality Control by Considering Both Point and Non-Point Source Pollution Using a Mathematical Model: Tidal River Network Case Study

1
Jiangsu Provincial Key Laboratory of Environmental Engineering, Nanjing 210036, China
2
Jiangsu Provincial Academy of Environmental Sciences, Nanjing 210036, China
3
Environment College, Hohai University, Nanjing 210098, China
4
Jiangsu Engineering Consulting Center, Nanjing 210000, China
5
Yellow River Institute of Hydraulic Research, Zhengzhou 450003, China
6
College of Science, Hohai University, Nanjing 210098, China
7
Academy of Environmental Planning and Design, Nanjing University, Nanjing 210093, China
*
Author to whom correspondence should be addressed.
Water 2019, 11(5), 900; https://doi.org/10.3390/w11050900
Received: 21 February 2019 / Revised: 9 April 2019 / Accepted: 26 April 2019 / Published: 29 April 2019
(This article belongs to the Section Water Quality and Ecosystems)
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Abstract

Based on the principles of fairness and feasibility, a nonlinear optimization allocation method for pollutants was developed based on controlled section water quality standards, considering the synergetic influence of point and surface sources. The maximum allowable emission of pollutants from point and surface sources were taken as the objective function. The water quality attainment rate of controlled sections, the control requirements of pollution sources, and technical parameters of pollution control engineering were taken as constraints. A nonlinear optimization allocation model was established, and a genetic algorithm was used to solve the problem. As an example, the model was applied to a certain area in the Taihu Lake basin, southern Jiangsu province, China. The analysis results showed that the annual number of days for ammonia-nitrogen and total phosphorus meeting the standard were 334 and 332 days, respectively, under maximum allowable emissions for each pollutant, and the water quality compliance rates of the control section were 91.5% and 91%, respectively. The ammonia-nitrogen and total phosphorus concentrations in the controlled section achieved related water quality compliance rate targets of 90%. These all met the water quality compliance rate requirements of the control section. The results indicate that this method reflects the feasibility of optimizing the total allocation results systematically and intuitively, overcomes the insufficiency in the feasibility of the optimized allocation method, and provides effective and reliable technical support for control and management of the total pollutant amount based on water quality improvement. View Full-Text
Keywords: total allocation; water environment capacity; point and non-point sources; guarantee rate; genetic algorithm total allocation; water environment capacity; point and non-point sources; guarantee rate; genetic algorithm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Chen, L.; Han, L.; Ling, H.; Wu, J.; Tan, J.; Chen, B.; Zhang, F.; Liu, Z.; Fan, Y.; Zhou, M.; Lin, Y. Allocating Water Environmental Capacity to Meet Water Quality Control by Considering Both Point and Non-Point Source Pollution Using a Mathematical Model: Tidal River Network Case Study. Water 2019, 11, 900.

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