Investigating Effectiveness of Sensor Placement Strategies in Contamination Detection within Water Distribution Systems
Publication: Journal of Water Resources Planning and Management
Volume 144, Issue 4
Abstract
Water quality sensors placed in water distribution systems (WDSs) are critical for detecting accidental or intentional contamination intrusion. This motivates research to optimally place a limited number of sensors for a given WDS aimed to maximize the detection effectiveness (e.g., the detection likelihood and time to detection). Typically, effectiveness of a sensor placement strategy (SPS) is assessed using the expected impact across a number of contamination scenarios. Despite the value of such an approach, it may provide limited information on the SPS’s comprehensive properties in detection, such as the SPS’s ability to detect events with different levels of consequences, or to reduce the impacts from undetectable events. To address this limitation, this study investigates the underlying characteristics of the SPS’s effectiveness for contamination detection using a set of metrics focusing on detection time, consumption of contaminated water, the number of contaminated demand nodes, and the contaminated spatial distance. The former two are derived from detectable contamination scenarios and the latter two are computed from both detectable and undetectable contamination scenarios. The proposed method is illustrated for two real-world WDSs, and the results reveal the underlying properties of the SPS’s utility in contamination detection, which is significantly more informative than the measure of expected impacts. Such improved understanding provides guidance for selecting the most appropriate SPS and for improving preparedness for contamination events.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This work is supported by the Fundamental Research Funds for the Central Universities (No. 2017FZA4021).
References
Banik, B. K., Alfonso, L., Cristo, C. D., Leopardi, A., and Mynett, A. (2017). “Evaluation of different formulations to optimally locate sensors in sewer systems.” J. Water Resour. Plann. Manage., 04017026.
Beijing Youth Daily. (2016). “Contaminated drinking water.” ⟨http://www.chinanews.com/sh/2016/05-25/7883161.shtml⟩ (Jun. 27, 2016).
Ehsani, N., and Afshar, A. (2010). “Optimization of contaminated sensor placement in water distribution networks.” Proc., Water Distribution System Analysis (WDSA) 2010, Environmental and Water Resources Institute of ASCE, New York, 338–346.
EPANET version 2.0 [Computer software]. U.S. Environmental Protection Agency, Washington, DC.
Hart, W., and Murray, R. (2010). “Review of sensor placement strategies for contamination warning systems in drinking water distribution systems.” J. Water Resour. Plann. Manage., 611–619.
Janke, R., Murray, R., Uber, J., and Taxon, T. (2006). “Comparison of physical sampling and real-time monitoring strategies for designing a contamination warning system in a drinking water distribution system.” J. Water Resour. Plann. Manage., 310–313.
Kim, J. H., Tran, T. V. T., and Chung, G. (2010). “Optimization of water quality sensor locations in water distribution systems considering impact mixing.” Proc., Water Distribution System Analysis (WDSA) 2010, Environmental and Water Resources Institute of ASCE, New York, 317–326.
Krause, A., and Guestrin, C. (2009). “Robust sensor placement for detecting adversarial contaminations in water distribution systems.” Proc., 8th Annual Water Distribution Systems Analysis Symp., ASCE, Reston, VA.
Ostfeld, A., et al. (2008). “The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms.” J. Water Resour. Plann. Manage., 556–568.
Rathi, S., Gupta, R., and Ormsbee, L. (2015). “A review of sensor placement objective metrics for contamination detection in water distribution networks.” Water Sci. Technol. Water Supply, 15(5), 898–917.
Storey, M. V., Gaag, B. V. D., and Burns, B. P. (2011). “Advances in on-line drinking water quality monitoring and early warning systems.” Water Res., 45(2), 741–747.
Watson, J., Murray, R., and Hart, W. (2009). “Formulation and optimization of robust sensor placement problems for drinking water contamination warning systems.” J. Infrastruct. Syst., 330–339.
Watson, J. P., Greenberg, H. J., and Hart, W. E. (2004). “A multiple-objective analysis of sensor placement optimization in water networks.” Proc., ASCE World Water and Environmental Resources, Environmental and Water Resources Institute of ASCE, New York, 456–465.
Wu, Z. Y., and Walski, T. (2006). “Multi-objective optimization of sensor placement water distribution systems.” Water Distribution Systems Analysis Symp., ASCE, Reston, VA.
Yang, X., and Boccelli, D. (2016). “Model-based event detection for contaminant warning systems.” J. Water Resour. Plann. Manage., 04016048.
Zhao, Y., Schwartz, R., Salomons, E., Ostfeld, A., and Poor, H. V. (2016). “New formulation and optimization methods for water sensor placement.” Environ. Modell. Software, 76, 128–136.
Zheng, F., Simpson, A. R., and Zecchin, A. C. (2011). “Dynamically expanding choice-table approach to genetic algorithm optimization of water distribution systems.” J. Water Resour. Plann. Manage., 547–551.
Zheng, F., Zecchin, A., Simpson, A., and Lambert, M. (2014). “Noncrossover dither creeping mutation-based genetic algorithm for pipe network optimization.” J. Water Resour. Plann. Manage., 553–557.
Information & Authors
Information
Published In
Copyright
©2018 American Society of Civil Engineers.
History
Received: Sep 12, 2016
Accepted: Oct 9, 2017
Published online: Jan 30, 2018
Published in print: Apr 1, 2018
Discussion open until: Jun 30, 2018
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.