Abstract
The intrusion of a foreign substance into the water distribution system represents a serious threat to public health. Large-scale water distribution systems serve thousands of consumers who may be put at risk to exposure and ingestion of potentially harmful substances. For an authority managing a water distribution system, it is important to (1) detect a potential contamination, and (2) locate the point of intrusion. However, points of known water quality data are expected to be sparsely distributed throughout the water distribution system, and may not provide sufficient data to quickly and accurately localize a contamination event. In this work, an inline mobile sensor was employed for the contamination event localization task in a Bayesian framework, such that the water quality data acquired by the mobile sensor were used to update the contamination intrusion location probabilities in the water distribution system. Using the Bayesian localization method was shown to improve the localization accuracy of a contamination event, with substantial improvements in the precision of localization.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available in a repository or online at: https://tinyurl.com/Bayesian-Loc-Mobiles.
Acknowledgments
This study was supported by the United States–Israel Binational Science Foundation (BSF) and by the Technion Funds for Security research.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 145 • Issue 8 • August 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: May 2, 2018
Accepted: Dec 26, 2018
Published online: May 29, 2019
Published in print: Aug 1, 2019
Discussion open until: Oct 29, 2019
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