Application of probabilistic bankruptcy method in river water quality management

被引:0
作者
S. Z. Farjoudi
A. Moridi
A. Sarang
B. J. Lence
机构
[1] Shahid Beheshti University,Water Resources Engineering and Management, Department of Civil, Water, and Environmental Engineering
[2] Shahid Beheshti University,Department of Civil, Water, and Environmental Engineering
[3] University of Tehran,Faculty of Environment
[4] University of British Columbia,Department of Civil Engineering
来源
International Journal of Environmental Science and Technology | 2021年 / 18卷
关键词
Bankruptcy rules; Monte Carlo; Particle Swarm Optimization; QUAL2Kw; Water quality management;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper, a probabilistic water quality management model is developed to present strategies using bankruptcy rules for solving conflicts between the Environmental Protection Agency and polluters in river systems. The bankruptcy concepts are adapted to the water quality aspect, Dissolved Oxygen as the water quality factor, and the pollutant concentration refers to the asset and stakeholders' claim. Bankruptcy rules are developed to allocate wastewater cooperatively and improve the water quality at the checkpoint. Therefore, a simulation–optimization model, including QUAL2Kw and Particle Swarm Optimization, is used to optimize the bankruptcy method’s waste load allocation. In the probabilistic model, the effect of river flow uncertainty on the optimal solution is investigated by Monte Carlo and Latin Hypercube Sampling. The optimal Dissolved Oxygen values are obtained corresponding to the possibility of river flows under the bankruptcy rules. The results of deterministic and probabilistic models show that the methodology reduces the waste load by 65–94% and increases Dissolved Oxygen from 0.9 to 5 mg/L. However, the streamflow uncertainty benefits polluters and allows them to release pollution more than twice the deterministic model. Analyzing the rules reveals that the Talmud rule outperformed others with higher Dissolved Oxygen and waste load criterion. This reliable probabilistic model can be used when the parties' performance is not cooperative, leading to more adaptability with real situations.
引用
收藏
页码:3043 / 3060
页数:17
相关论文
共 50 条
[31]   Numerical models in water quality management: A case study for the Yamuna river (India) [J].
Kazmi, AA ;
Hansen, IS .
WATER SCIENCE AND TECHNOLOGY, 1997, 36 (05) :193-200
[32]   An Integrated Decision Support System for Water Quality Management of Songhua River Basin [J].
Zhang, Haiping ;
Yin, Qiuxiao ;
Chen, Ling .
2ND INTERNATIONAL SYMPOSIUM ON AQUA SCIENCE, WATER RESOURCE AND LOW CARBON ENERGY, 2010, 1251 :400-403
[33]   Water quality management in the Crocodile River catchment, Eastern Transvaal, South Africa [J].
Ashton, PJ ;
vanZyl, FC ;
Heath, RG .
WATER SCIENCE AND TECHNOLOGY, 1995, 32 (5-6) :201-208
[34]   Development of water quality management strategies for an urban river reach: A case study of the river Yamuna, Delhi, India [J].
Nibedita Verma ;
Geeta Singh ;
Naved Ahsan .
Arabian Journal of Geosciences, 2022, 15 (24)
[35]   Application of Molecular Biotechnology for Monitoring and Management of Harmful Algae and Water Quality [J].
Chiu Y.-T. ;
Whang L.-M. ;
Lin T.-F. .
Journal of the Chinese Institute of Civil and Hydraulic Engineering, 2020, 32 (03) :303-309
[36]   A fuzzy equilibrium strategy for sustainable water quality management in river-reservoir system [J].
Hasanzadeh, Sepideh Kheirkhah ;
Saadatpour, Motahareh ;
Afshar, Abbas .
JOURNAL OF HYDROLOGY, 2020, 586
[37]   A stochastic conflict resolution model for water quality management in reservoir-river systems [J].
Kerachian, Reza ;
Karamouz, Mohammad .
ADVANCES IN WATER RESOURCES, 2007, 30 (04) :866-882
[38]   Water Quality Risk Assessment for the Laoguanhe River of China Using a Stochastic Simulation Method [J].
Hu, J. ;
Sun, L. ;
Li, C. H. ;
Wang, X. ;
Jia, X. L. ;
Cai, Y. P. .
JOURNAL OF ENVIRONMENTAL INFORMATICS, 2018, 31 (02) :123-136
[39]   An Optimal Model and Application of Hydraulic Structure Regulation to Improve Water Quality in Plain River Networks [J].
Huang, Fan ;
Zhang, Haiping ;
Wu, Qiaofeng ;
Chi, Shanqing ;
Yang, Mingqing .
WATER, 2023, 15 (24)
[40]   A Simulation-Based Optimization Approach for Water Quality Management of Xiangxihe River Under Uncertainty [J].
Li, Haizhou ;
Li, Yongping ;
Huang, Guohe ;
Xie, Yulei .
ENVIRONMENTAL ENGINEERING SCIENCE, 2012, 29 (04) :270-283