Inline Mobile Sensors for Contaminant Early Warning Enhancement in Water Distribution Systems
Publication: Journal of Water Resources Planning and Management
Volume 143, Issue 2
Abstract
Prompt detection of intentional or accidental contamination of the public water supply is vital to maintain public health in any centralized water distribution system. Being able to quickly detect a system contamination event may be the single most influential factor to reduce possible contamination fallout. Consequently, major research has explored how to best protect a water distribution system (WDS) through strategic placement of fixed water quality monitoring stations. Although fixed monitoring stations within a wireless sensor network (WSN) are robust with respect to hydraulic conditions, the stations are expensive to place, and may not provide the highest spatial and temporal resolution of contamination detection. This work sets to build the understanding of a mobile wireless sensor network (MWSN) where inline mobile sensors function within water in pipes to monitor water quality and to wirelessly transmit data to fixed transceivers in real time. Mobile sensor behavior was modeled alongside contamination simulations and the deployment of fixed and mobile sensors was together optimized to minimize the affected population prior contamination event detection constrained by a total system cost. Results show a MWSN to be highly sensitive to sensor battery life, transceiver network coverage, and total system cost. Future obstacles for implementation of a MWSN are highlighted and discussed to be address in future work.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This study was supported by the United States - Binational Science Foundation (BSF), by the Technion Funds for Security research, by the joint Israeli Office of the Chief Scientist (OCS) Ministry of Science, Technology and Space (MOST), and by the Germany Federal Ministry of Education and Research (BMBF), under project no. 02WA1298.
References
Banks, M., Pekarek, S., Porterfield, M., Brovont, A., Salim, A., and Wu, R. (2012). “Development of mobile self-powered sensors for potable water distribution.” ⟨https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/display.abstractDetail/abstract/9458/report/2012⟩ (Mar. 12, 2013).
Foran, J. A., and Brosnan, T. M. (2000). “Early warning systems for hazardous biological agents in potable water.” Environ. Health Perspect., 108(10), 993–995.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning, Addison-Wesley, Boston.
Goldberg, D. E., Korb, B., and Deb, K. (1989). “Messy genetic algorithms: Motivation, analysis, and first results.” Complex Syst., 3(5), 493–530.
Gong, W., et al. (2016). “Mobile sensor networks for optimal leak and backflow detection and localization in municipal water networks.” Environ. Model. Software, 80, 306–321.
Halhal, D., Walters, G. A., Ouazar, D., Savic, D. A. (1997). “Water network rehabilitation with structured messy genetic algorithm.” J. Water Resour. Plan. Manage., 137–146.
Hart, W. E., 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.
Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence, University of Michigan Press, Oxford, England.
Kessler, A., Ostfeld, A., and Sinai, G. (1998). “Detecting accidental contaminations in municipal water networks.” J. Water Resour. Plann. Manage., 192–198.
Kim, J.-H., Sharma, G., Boudriga, N., and Iyengar, S. S. (2010). SPAMMS: A sensor-based pipeline autonomous monitoring and maintenance system, IEEE, New York, 1–10.
Lai, T. T.-T., Chen, W.-J., Li, K.-H., Huang, P., and Chu, H.-H. (2012). TriopusNet: Automating wireless sensor network deployment and replacement in pipeline monitoring, ACM, New York, 61–72.
Lai, T.-T. T., Chen, Y.-H. T., Huang, P., and Chu, H.-H. (2010). PipeProbe: A mobile sensor droplet for mapping hidden pipeline, ACM, New York, 113–126.
Lee, B., and Deininger, R. (1992). “Optimal locations of monitoring stations in water distribution system.” J. Environ. Eng., 4–16.
Murray, R., et al. (2010a). “Water quality event detection systems for drinking water contamination warning systems—Development, testing, and application of CANARY.” U.S. Environmental Protections Agency, Office of Research and Development, National Homeland Security Research Center, Cincinnati.
Murray, R., Haxton, T., Janke, R., Hart, W. J., Berry, J., and Phillips, C. (2010b). “Sensor network design for drinking water contamination warning systems. A compendium of research results and case studies using the TEVA-SPOT software.”, U.S. Environmental Protection Agency, Cincinnati.
Oliker, N., and Ostfeld, A. (2015). “Inclusion of mobile sensors in water distribution system monitoring operations,” J. Water Resour. Plann. Manage., .
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.
Ostfeld, A., and Salomons, E. (2004). “Optimal layout of early warning detection stations for water distribution systems security.” J. Water Resour. Plann. Manage., 377–385.
Perelman, L., and Ostfeld, A. (2013). “Operation of remote mobile sensors for security of drinking water distribution systems.” Water Res., 47(13), 4217–4226.
Rasekh, A., Wu, R., Salim, W. W. A. W., and Banks, M. K. (2014). “Operation of mobile sensors for monitoring municipal drinking water distribution systems.” World Environmental and Water Resources Congress, ASCE, Reston, VA, 362–367.
Rathi, S., and Gupta, R. (2013). “Monitoring stations in water distribution systems to detect contamination events.” ISH J. Hydraul. Eng., 20(2), 142–150.
Rathi, S., and Gupta, R. (2014). “Sensor placement methods for contamination detection in water distribution networks: A review.” Procedia Eng., 89, 181–188.
Rossman, L. A. (2000). “EPANET 2. Users manual.” U.S. Environmental Protection Agency (EPA), Cincinnati.
Rossman, L. A., and Boulos, P. F. (1996). “Numerical methods for modeling water quality in distribution systems: A comparison.” J. Water Resour. Plan. Manage., 137–146.
Rossman, L. A., Boulos, P. F., and Altman, T. (1993). “Discrete volume-element method for network water-quality models.” J. Water Resour. Plann. Manage., 505–517.
Suresh, M. A., Stoleru, R., Zechman, E. M., and Shihada, B. (2013). “On event detection and localization in acyclic flow networks.” Trans. IEEE Syst. Man Cybern.: Syst., 43(3), 708–723.
Szabo, J., and Hall, J. (2014). “On-line water quality monitoring for drinking water contamination.” Comprehensive water quality and purification, S. Ahuja, ed., Vol. 2, Elsevier, Amsterdam, Netherlands, 266–282.
Thomson, J., and Wang, L. (2009). “Condition assessment of ferrous water transmission and distribution systems state-of-technology review report.”, U.S. Environmental Protection Agency, National Risk Management Research Laboratory, Cincinnati.
Todini, E., and Pilati, S. (1987). “A gradient method for the analysis of pipe networks.” Proc., Int. Conf. on Computer Applications for Water Supply and Distribution, Leicester Polytechnic, Leicester, U.K.
Trinchero, D., and Stefanelli, R. (2010). “Microwave mobile sensor networks within underground conduits filled of fluids.” 2010 URSI Int. Symp. on Electromagnetic Theory, IEEE, New York, 148–151.
USEPA (U.S. Environmental Protection Agency). (2005). “Water sentinel online water quality monitoring as an indicator of drinking water contamination.” ⟨http://www.epa.gov/watersecurity/pubs/watersentinel_wq_monitoring.pdf⟩ (Jan. 8, 2016).
USEPA (U.S. Environmental Protection Agency). (2008). “EPANET.” ⟨https://www.epa.gov/water-research/epanet⟩ (May 14, 2014).
Information & Authors
Information
Published In
Copyright
©2016 American Society of Civil Engineers.
History
Received: Jan 21, 2016
Accepted: Aug 17, 2016
Published online: Oct 14, 2016
Published in print: Feb 1, 2017
Discussion open until: Mar 14, 2017
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.