Data Mining to Identify Attributes Associated with Drinking Water Advisories in First Nations Communities
Publication: Journal of Water Resources Planning and Management
Volume 145, Issue 11
Abstract
Maintaining acceptable drinking water quality in First Nations communities has been an ongoing issue in Canada, resulting in frequent drinking water advisories (DWAs). Information about drinking water systems on reserves was combined with historical advisory data to investigate the relationships between system attributes and DWAs using data mining. Decision trees were developed to identify key factors linked to the occurrence, frequency, duration, and causes of DWAs. The results showed that trends varied considerably by province, despite federal management. Operator treatment certification was shown to be associated with the duration of advisories, where systems with fully trained operators were less likely to have long-lasting DWAs. The findings from data mining can be useful for informing future regulatory and funding decisions in efforts to reduce DWAs.
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Data Availability Statement
All models generated during the study appear in the article’s Supplemental Data section. All data used during the study are available from the corresponding author by request.
Acknowledgments
This research was made possible by funding from the Natural Sciences and Engineering Research Council and Res’Eau National Centre of Excellence on small drinking water systems.
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©2019 American Society of Civil Engineers.
History
Received: Mar 16, 2017
Accepted: Mar 21, 2019
Published online: Sep 6, 2019
Published in print: Nov 1, 2019
Discussion open until: Feb 6, 2020
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