Multi-objective multi-pollutant waste load allocation model for rivers using coupled archived simulated annealing algorithm with QUAL2Kw

A simulation-optimization approach is a suitable tool in waste load allocation problems when considering competing objectives and complex pollutant fate and transport processes in water bodies. Here, an archived multi-objective simulated annealing (AMOSA) algorithm is developed to determine various...

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Vydáno v:Journal of hydroinformatics Ročník 21; číslo 3; s. 397 - 410
Hlavní autoři: Saadatpour, Motahareh, Afshar, Abbas, Khoshkam, Helaleh
Médium: Journal Article
Jazyk:angličtina
Vydáno: London IWA Publishing 01.05.2019
Témata:
Algorithms
Annealing
Biochemical oxygen demand
Civil engineering
Coastal inlets
Coliforms
Computer simulation
Contamination
Costs
Dissolved oxygen
Effluents
Environmental engineering
Hydrology
Landfills
Leachates
Linear programming
Monitoring systems
Multiple objective analysis
Nitrates
Objectives
Optimization
Optimization algorithms
Phosphates
Pollutant load
Pollutant removal
Pollutants
Pollution dispersion
Pollution load
Problems
Quality management
Rivers
Science
Simulated annealing
Software
Soil sciences
Solid suspensions
Stream water
Suspended particulate matter
Total oxygen demand
Total suspended solids
Transport processes
Waste disposal sites
Waste load
Wastewater
Wastewater treatment
Wastewater treatment plants
Water pollution
Water quality
Water treatment
Iran
ISSN:1464-7141, 1465-1734
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Abstract A simulation-optimization approach is a suitable tool in waste load allocation problems when considering competing objectives and complex pollutant fate and transport processes in water bodies. Here, an archived multi-objective simulated annealing (AMOSA) algorithm is developed to determine various decision variables related to multi-pollutant waste load allocation (MPWLA) problems. The developed AMOSA algorithm has been coupled to QUAL2Kw in order to derive optimal MPWLA programs in Gheshlagh River, Kordestan, Iran. Minimizing wastewater treatment plant (WWTP) costs, improving the EquityMeasure, and enhancing water quality index (WQI) of the river have been considered as objective functions of MPWLA problems. The applied WQI integrates various water quality parameters (biochemical oxygen demand (BOD), dissolved oxygen (DO), NH4-N, NO3-N, PO4-P, total suspended solids (TSS), and Coliform) in monitoring stations along the river. Results show in the scenario with the best EquityMeasure, higher pollutant removal rates have been allocated to Sanandaj WWTP effluent and pollutant point source No. 7 (creek of landfill leachate) due to their greater contributions to Gheshlagh River contamination. Owing to high pollutant load effluents and unsuitable background conditions in Gheshlagh River, more specific studies show that the water quality index may not be improved over 0.22, no matter how much cost is incurred or equity is sacrificed.
AbstractList A simulation-optimization approach is a suitable tool in waste load allocation problems when considering competing objectives and complex pollutant fate and transport processes in water bodies. Here, an archived multi-objective simulated annealing (AMOSA) algorithm is developed to determine various decision variables related to multi-pollutant waste load allocation (MPWLA) problems. The developed AMOSA algorithm has been coupled to QUAL2Kw in order to derive optimal MPWLA programs in Gheshlagh River, Kordestan, Iran. Minimizing wastewater treatment plant (WWTP) costs, improving the EquityMeasure, and enhancing water quality index (WQI) of the river have been considered as objective functions of MPWLA problems. The applied WQI integrates various water quality parameters (biochemical oxygen demand (BOD), dissolved oxygen (DO), NH4-N, NO3-N, PO4-P, total suspended solids (TSS), and Coliform) in monitoring stations along the river. Results show in the scenario with the best EquityMeasure, higher pollutant removal rates have been allocated to Sanandaj WWTP effluent and pollutant point source No. 7 (creek of landfill leachate) due to their greater contributions to Gheshlagh River contamination. Owing to high pollutant load effluents and unsuitable background conditions in Gheshlagh River, more specific studies show that the water quality index may not be improved over 0.22, no matter how much cost is incurred or equity is sacrificed.
Author Khoshkam, Helaleh
Afshar, Abbas
Saadatpour, Motahareh
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  surname: Khoshkam
  fullname: Khoshkam, Helaleh
  organization: Civil and Environmental Engineering, College of Environment, Karaj, Alborz, Iran
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Snippet A simulation-optimization approach is a suitable tool in waste load allocation problems when considering competing objectives and complex pollutant fate and...
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SubjectTerms Algorithms
Annealing
Biochemical oxygen demand
Civil engineering
Coastal inlets
Coliforms
Computer simulation
Contamination
Costs
Dissolved oxygen
Effluents
Environmental engineering
Hydrology
Landfills
Leachates
Linear programming
Monitoring systems
Multiple objective analysis
Nitrates
Objectives
Optimization
Optimization algorithms
Phosphates
Pollutant load
Pollutant removal
Pollutants
Pollution dispersion
Pollution load
Problems
Quality management
Rivers
Science
Simulated annealing
Software
Soil sciences
Solid suspensions
Stream water
Suspended particulate matter
Total oxygen demand
Total suspended solids
Transport processes
Waste disposal sites
Waste load
Wastewater
Wastewater treatment
Wastewater treatment plants
Water pollution
Water quality
Water treatment
Title Multi-objective multi-pollutant waste load allocation model for rivers using coupled archived simulated annealing algorithm with QUAL2Kw
URI https://www.proquest.com/docview/2234336267
Volume 21
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