Abstract
Water utilities have large amounts of data at their disposal, which are seldom being used to their full potential. Integrating water billing records with land-use and demographic data organizes information and makes inherent correlations easier to understand, facilitating communication to stakeholders. This data was integrated for three Ontario (Canada) municipalities, Barrie, Guelph, and London. A summary tool was created, with proposed metrics and charts, that facilitates comparisons between cities, definition of benchmarks, and identification of targets for conservation. More than 60% of consumption in these cities is residential, and mostly lies below the Ontario average of . Water user clusters were created through self-organizing maps, K-means, and hierarchical clustering, and selected according to their pseudo-F and Rand statistics. Users within the same or similar property codes were found to cluster together. The application of data-mining methods provides actionable information for utilities seeking to reduce demands and increase system sustainability.
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Acknowledgments
This paper is partly based on case study research conducted within the project “Integrated Water Mapping: Enhancing Decision Support for Sustainable Water Planning with Municipal Data,” by Cities Centre and the Canadian Urban Institute, and funded by the Ontario Ministry of Environment through the Showcasing Water Innovations program. However, the findings, interpretations, and conclusions in this document are entirely those of the authors, and should not be attributed to the aforementioned organizations. The authors acknowledge the inputs of Tom Weatherburn, Kathryn Grond, Wayne Galliher, Matt Feldberg, and Barry Thompson.
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Published In
Journal of Water Resources Planning and Management
Volume 141 • Issue 4 • April 2015
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Jan 22, 2014
Accepted: May 15, 2014
Published online: Jul 21, 2014
Discussion open until: Dec 21, 2014
Published in print: Apr 1, 2015
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