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Use of on-line water quality monitoring data to predict bacteriological failures

Lookup NU author(s): Professor Catherine Biggs

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

Variations in continuously monitored on-line water quality data were investigated to establish whether they could be linked to coliform detections at regulatory monitoring points. We focussed on chlorine residual, turbidity and flow rate at water treatment works (WTW)-A. Archived on-line monitoring data from WTW-A were analysed using cross-correlation and self-organising maps in MATLABĀ® to identify trends in the data running up to coliform detections. The results show that these tools could be developed to help manage WTWs to reduce the number of bacteriological failures. A fingerprint of WTW conditions relating to coliform failures was identified for this case study.


Publication metadata

Author(s): Ellis K, Mounce S, Ryan B, Templeton MR, Biggs CA

Publication type: Article

Publication status: Published

Journal: Procedia Engineering

Year: 2014

Volume: 70

Pages: 612-621

Print publication date: 01/01/2014

Online publication date: 23/04/2014

Acceptance date: 01/01/2014

Date deposited: 06/08/2019

ISSN (electronic): 1877-7058

Publisher: Elsevier

URL: https://doi.org/10.1016/j.proeng.2014.02.067

DOI: 10.1016/j.proeng.2014.02.067


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