Backward Probabilistic Modeling to Identify Contaminant Sources in Water Distribution Systems
Publication: Journal of Water Resources Planning and Management
Volume 136, Issue 5
Abstract
If a chemical or biological agent is released into a water distribution system, sensors that are installed in the pipe network may detect the contamination as it travels through the system. To minimize the adverse impact of the contaminant release, the source must be characterized to determine the extent of the contamination and to remediate the contaminated area. We present a backward modeling approach that uses the data collected by the sensors to obtain probability density functions that describe the random time in the past that the observed contamination was at a particular upgradient position. These probability density functions can be used to identify the source node and release time. The approach is developed for steady flow conditions with known system demands and for a single, instantaneous source of contamination. Using a hypothetical water distribution system and release scenario, we demonstrate that the backward model is an efficient and effective approach for identifying the source node and the release time.
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References
Austin, R. W., van Bloemen Waanders, B., McKenna, S., and Choi, C. Y. (2008). “Mixing at cross junctions in water distribution systems. II: Experimental study.” J. Water Resour. Plann. Manage., 134(3), 295–302.
Dawsey, W. J., Minsker, B. S., and VanBlaricum, V. L. (2006). “Bayesian belief networks to integrate monitoring evidence of water distribution system contamination.” J. Water Resour. Plann. Manage., 132(4), 234–241.
Di Cristo, C., and Leopardi, A. (2008). “Pollution source identification of accidental contamination in water distribution networks.” J. Water Resour. Plann. Manage., 134(2), 197–202.
Guan, J., Aral, M. M., Maslia, M. L., and Grayman, W. M. (2006). “Identification of contaminant sources in water distributions systems using simulation-optimization method: Case study.” J. Water Resour. Plann. Manage., 132(4), 252–262.
Laird, C. D., Biegler, L. T., and van Bloemen Waanders, B. G. (2006). “Mixed-integer approach for obtaining unique solutions in source inversion of water networks.” J. Water Resour. Plann. Manage., 132(4), 242–251.
Laird, C. D., Biegler, L. T., van Bloemen Waanders, B. G., and Bartlett, R. A. (2005). “Contamination source determination for water networks.” J. Water Resour. Plann. Manage., 131(2), 125–134.
Neupauer, R. M. (2010). “Adjoint sensitivity analysis of contaminant concentrations in water distribution systems.” J. Eng. Mech., (June 21, 2010).
Neupauer, R. M., and Ashwood, W. H. (2008). “Backward probabilistic modeling to identify contaminant sources in a water distribution system.” Proc., World Environmental and Water Resources Congress 2008, ASCE, Reston, Va.
Neupauer, R. M., and Lin, R. (2006). “Identifying sources of a conservative groundwater contaminant using backward probabilities conditioned on measured concentrations.” Water Resour. Res., 42, W03424.
Neupauer, R. M., and Records, M. K. (2009). “Conditioned backward probability modeling to identify contamination sources in a water distribution system.” Proc., World Environmental and Water Resources Congress 2009, ASCE, Reston, Va.
Neupauer, R. M., and Wilson, J. L. (1999). “Adjoint method for obtaining backward-in-time location and travel time probabilities of a conservative groundwater contaminant.” Water Resour. Res., 35(11), 3389–3398.
Preis, A., and Ostfeld, A. (2006). “Contamination source identification in water systems: A hybrid model trees-linear programming scheme.” J. Water Resour. Plann. Manage., 132(4), 263–273.
Preis, A., and Ostfeld, A. (2008). “Genetic algorithm for contaminant source characterization using imperfect sensors.” Civ. Eng. Environ. Syst., 25(1), 29–39.
Rossman, L. A. (2000). EPANET 2: User’s manual: EPA/600/R-00/057, United States Environmental Protection Agency, Cincinnati, Ohio.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 136 • Issue 5 • September 2010
Pages: 587 - 591
Copyright
© 2010 ASCE.
History
Received: Jun 5, 2009
Accepted: Oct 21, 2009
Published online: Oct 28, 2009
Published in print: Sep 2010
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