Monitoring Design for Source Identification in Water Distribution Systems
Publication: Journal of Water Resources Planning and Management
Volume 136, Issue 6
Abstract
The design of sensor networks for monitoring contaminants in water distribution systems is currently an active area of research. Much of the effort has been directed at the contamination detection problem and the expression of public health protection objectives. Monitoring networks once they are in place, however, are likely to be used to gather monitoring data for source inversion as well. Thus, the design of these networks with the unique objectives associated with source inversion problems in mind is a necessity. Source inversion problems in water distribution systems are inherently underdetermined and exhibit solution nonuniqueness; and moreover, the structure of the errors associated with a solution are a function of monitoring observations. Optimal inverse experiment design is investigated as an approach for improving solution quality. The approach involves the selection of monitoring locations that are best suited to the generation of a well-conditioned source identification inverse problem. The monitoring design problem is formulated as a nonlinear combinatorial optimization problem and solved using a genetic algorithm. The monitoring designs generated exhibit an optimal substructure that may be exploited to develop more efficient methods of solution. An analysis is conducted to evaluate the source inversion performance of an optimized monitoring network relative to networks designed using different methods. The results of the analysis demonstrate that when the source identification problem is underdetermined, the number of monitoring sensors installed in the network is more important than the method used to locate them.
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Acknowledgments
This work was partially funded under National Science Foundation Grant No. NSFBES-0238623. The writers would like to thank Dr. G. Mahinthakumar and his students for sharing the computational resources that made the analyses conducted possible. The content of this paper has undergone U.S. Environmental Protection Agency internal review. This, however, does not imply official endorsement of the views expressed herein.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 136 • Issue 6 • November 2010
Pages: 637 - 646
Copyright
© 2010 ASCE.
History
Received: Mar 31, 2009
Accepted: Feb 15, 2010
Published online: Feb 17, 2010
Published in print: Nov 2010
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