Risk-Based Sensor Placement for Contaminant Detection in Water Distribution Systems
Publication: Journal of Water Resources Planning and Management
Volume 136, Issue 6
Abstract
A method for optimizing sensor locations to effectively and efficiently detect contamination in a water distribution network is presented here. The problem is formulated and solved as a twin-objective optimization problem with the objectives being the minimization of the number of sensors and minimization of the risk of contamination. Unlike past approaches, the risk of contamination is explicitly evaluated as the product of the likelihood that a set of sensors fails to detect contaminant intrusion and the consequence of that failure (expressed as volume of polluted water consumed prior to detection). A novel importance-based sampling method is developed and used to effectively determine the relative importance of contamination events, thus reducing the overall computation time. The above problem is solved by using the nondominated sorting genetic algorithm II. The methodology is tested on a case study involving the water distribution system of Almelo (The Netherlands) and the potential intrusion of E. coli bacteria. The results obtained show that the algorithm is capable of efficiently solving the above problem. The estimated Pareto front suggests that a reasonable level of contaminant protection can be achieved using a small number of strategically located sensors.
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Acknowledgments
The research work presented here was undertaken as part of the research project supported by the E.U. Socrates scheme, U.K. EPSRC Platform Grant, GR/T26054, and KWR, The Netherlands, which is gratefully acknowledged. The writers would also like to acknowledge the input provided by the three anonymous reviewers which helped to improve the quality of this paper.
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Information
Published In
Journal of Water Resources Planning and Management
Volume 136 • Issue 6 • November 2010
Pages: 629 - 636
Copyright
© 2010 ASCE.
History
Received: Feb 20, 2009
Accepted: Jan 8, 2010
Published online: Jan 11, 2010
Published in print: Nov 2010
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