Environments 2016, 3(2), 10; https://doi.org/10.3390/environments3020010
Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps
E.J. Mirjam Blokker 1,*
, William R. Furnass 2, John Machell 2, Stephen R. Mounce 2, Peter G. Schaap 3 and Joby B. Boxall 2
, William R. Furnass 2, John Machell 2, Stephen R. Mounce 2, Peter G. Schaap 3 and Joby B. Boxall 2
1
KWR Watercycle Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, The Netherlands
2
Department of Civil and Structural Engineering, University of Sheffield, Mappin street, Sheffield s1 3jd, South Yorkshire, UK
3
PWN Water Supply Company North Holland, Postbus 2113, 1990 AC Velserbroek, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editors: Luigi Berardi and Daniele Laucelli
Received: 29 January 2016 / Revised: 11 April 2016 / Accepted: 13 April 2016 / Published: 20 April 2016
(This article belongs to the Special Issue Data-Modelling Applications in Water System Management)
Abstract
Understanding and managing water quality in drinking water distribution system is essential for public health and wellbeing, but is challenging due to the number and complexity of interacting physical, chemical and biological processes occurring within vast, deteriorating pipe networks. In this paper we explore the application of Self Organising Map techniques to derive such understanding from international data sets, demonstrating how multivariate, non-linear techniques can be used to identify relationships that are not discernible using univariate and/or linear analysis methods for drinking water quality. The paper reports on how various microbial parameters correlated with modelled water ages and were influenced by water temperatures in three drinking water distribution systems. View Full-TextKeywords:
drinking water distribution; water quality; water age; SOM
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Blokker, E.M.; Furnass, W.R.; Machell, J.; Mounce, S.R.; Schaap, P.G.; Boxall, J.B. Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps. Environments 2016, 3, 10.
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