Publication:
Optimal control of urban sewer systems under enhanced water quality modeling

dc.contributor.authorRathnayake, U. S
dc.date.accessioned2022-01-31T07:55:11Z
dc.date.available2022-01-31T07:55:11Z
dc.date.issued2014
dc.description.abstractAgricultural lands usually carry a considerable amount of phosphorous and nitrogen. This is due to the routinely added chemical fertilizers. Phosphorous is identified as a non-point source pollutant that causes eutrophication in surface waters. Even though, phosphorous is less mobile than nitrogen, soil erosion in agricultural lands leads to increase the phosphorous levels in surface water. Therefore, it is always better to consider phosphorous concentration when considering the receiving water quality due to combined sewer overflows (CSOs). Rathnayake and Tanyimboh’s optimal control model for urban sewer systems is capable of assessing water quality in receiving water due to CSOs. However, it only includes the concentrations of total suspended solids (TSS), chemical oxygen demand (COD), nitrates and nitrites (NOX), five-day biochemical oxygen demand (BOD) and total Kjeldahl nitrogen (TKN). Therefore, there is a necessity to improve the water quality analysis in Rathnayake and Tanyimboh’s optimal model. This paper presents an enhanced water quality approach, including phosphorous concentrations, in control of urban sewer networks. The enhanced model is applied to a real world combined sewer network. Results show that the enhanced model produces better approach compared to the existing Rathnayake and Tanyimboh’s control model.en_US
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/872
dc.language.isoenen_US
dc.publisher5th International conference on Sustainable Built Environmenten_US
dc.subjectCombined sewer overflowsen_US
dc.subjectcombined sewer systemsen_US
dc.subjectenhanced effluent quality indexen_US
dc.subjectmulti-objective optimizationen_US
dc.subjectNSGA IIen_US
dc.subjectphosphate concentrationen_US
dc.titleOptimal control of urban sewer systems under enhanced water quality modelingen_US
dc.typeArticleen_US
dspace.entity.typePublication

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