Contamination Source Identification in Water Distribution Systems Using an Adaptive Dynamic Optimization Procedure
Publication: Journal of Water Resources Planning and Management
Volume 137, Issue 2
Abstract
Contamination source identification involves the characterization of the contaminant source based on observations that stream from a set of sensors in a water distribution system (WDS). The streaming data can be processed adaptively to provide an estimate of the source characteristics at any time once the contamination event is detected. In this paper, an adaptive dynamic optimization technique (ADOPT) is proposed for providing a real-time response to a contamination event. A new multiple population–based search that uses an evolutionary algorithm (EA) is investigated. To address nonuniqueness in the initial stages of the search and prevent premature convergence of the EA to an incorrect solution, the multiple populations are designed to maintain a set of alternative solutions that represent various nonunique solutions. As more observations are added, the EA solutions not only migrate to better solution states but the number of solutions decreases as the degree of nonuniqueness diminishes. This new algorithm adaptively converges to the solutions that best match the available observations. The use of the developed method is demonstrated for two WDS networks.
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Acknowledgments
This work is supported by National Science Foundation (NSF) under Grant No. NSFCMS-0540316 under the DDDAS program.
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Information
Published In
Journal of Water Resources Planning and Management
Volume 137 • Issue 2 • March 2011
Pages: 183 - 192
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Nov 19, 2009
Accepted: Jun 14, 2010
Published online: Jun 25, 2010
Published in print: Mar 1, 2011
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