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New approach for estimation of detention time and prediction of quality in water networks
Author(s) -
B Amit,
Eyal Brill
Publication year - 2018
Publication title -
water quality research journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 44
eISSN - 2408-9443
pISSN - 1201-3080
DOI - 10.2166/wqrj.2018.034
Subject(s) - water quality , computer science , estimation , quality (philosophy) , variety (cybernetics) , statistical model , data mining , environmental science , hydrology (agriculture) , machine learning , artificial intelligence , engineering , ecology , philosophy , geotechnical engineering , systems engineering , epistemology , biology
A water quality model (WQM) is a tool used for the prediction of water quality in a water distribution network. Previous studies have proposed a variety of methods for computing WQMs. All of these are flow-based and thus require the use of a hydraulic model. The current paper proposes a new methodology for a WQM based on a statistical approach. The study suggests a methodology that predicts the change in both detention time and water quality between two locations in a branched network, without the use of a hydraulic model. The methodology was implemented at a large water utility and tested using real-time data. The model output was then examined and verified by conducting a statistical test to compare the detention time with that predicted using an existing hydraulic model. It was found that the proposed model can be effectively used as a WQM.

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