Technical Papers
Jan 25, 2017

Complex Adaptive Systems Framework to Simulate the Performance of Hydrant Flushing Rules and Broadcasts during a Water Distribution System Contamination Event

Publication: Journal of Water Resources Planning and Management
Volume 143, Issue 4

Abstract

In the event that a contaminant is introduced to a water distribution system, utility managers must respond quickly to protect public health. Mitigation strategies specify response actions, such as warning consumers to reduce water activities using the news media and flushing contaminated water at hydrants. The performance of alternative response actions may be influenced by sociotechnical dynamics, as consumer reactions to contaminant exposure and information about the event can change water demands, hydraulics, propagation of a contaminant plume, and public health consequences. This research develops a modeling framework to test and evaluate mitigation decisions that a utility manager may take to protect public health over a wide range of contamination events. An agent-based modeling framework is developed to integrate social behaviors with technical artifacts in a sociotechnical model to evaluate the public health consequences of a water event. Social actors, including consumers and utility managers, are represented as agents and are coupled with a water distribution network model and a news media model to evaluate the performance of response strategies. Strategies for flushing hydrants are encoded as decision trees that specify the location and timing of hydrant flushing, based on the activation of water-quality sensors. The agent-based model is described using the Overview, Design, and Details protocol and is demonstrated for a virtual midsized municipality, Mesopolis. Results compare the effectiveness of flushing hydrants using cautious and adaptive response strategies and the use of the news media to disseminate warning messages. The framework can be applied for cities to evaluate alternative management strategies.

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References

AnyLogic 6.7.1 [Computer software]. XJ-Technologies, Orlando, FL.
Alfonso, L., Jonoski, A., and Solomatine, D. (2010). “Multiobjective optimization of operational responses for contaminant flushing in water distribution networks.” J. Water Resour. Plann. Manage., 48–58.
Baranowski, T. M., and LeBoeuf, E. J. (2008). “Consequence management utilizing optimization.” J. Water Resour. Plann. Manage., 386–394.
Davis, M. J., and Janke, R. (2009). “Development of a probabilistic timing model for the ingestion of tap water.” J. Water Resour. Plann. Manage., 397–405.
EPANET [Computer software]. U.S. Environmental Protection Agency, Washington, DC.
Friedman, M., Kirmeyer, G. J., and Antoun, E. (2002). “Developing and implementing a distribution system flushing program.” J. Am. Water Works Assoc., 94(7), 48–56.
Gavanelli, M., Nonato, M., Peano, A., Alvisi, S., and Franchini, M. (2012). “Genetic algorithms for scheduling devices operation in a water distribution system in response to contamination events.” Evolutionary computation in combinatorial optimization, J. K. Hao and M. Middendorf, eds., Springer, Berlin, 124–135.
Glouberman, S. (2001). “Walkerton water and complex adaptive systems.” Healthcare Q., 4(4), 28–31.
Greick, P. (2006). “Water and terrorism.” Water Policy, 8(6), 481–503.
Grimm, V., et al. (2006). “A standard protocol for describing individual-based and agent-based models.” Ecol. Modell., 198(1–2), 115–126.
Guan, J., Aral, M., Maslia, M., and Grayman, W. (2006). “Identification of contaminant sources in water distribution systems using simulation optimization method: Case study.” J. Water Resour. Plann. Manage., 252–262.
Holland, J. (1995). Hidden order: How adaptation builds complexity, Helix Books, New York.
Hrudey, S., and Hrudey, E. (2004). Safe drinking water: Lessons from recent outbreaks in affluent nations, International Water Association, Oxford, U.K.
Johnson, G., and Brumbelow, K. (2008). “Developing Mesopolis-A virtual city for research in water distribution system and interdependent infrastructures.” ⟨https://ceprofs.civil.tamu.edu/kbrumbelow/Mesopolis/index.htm⟩ (May 24, 2009).
Kroll, D. (2006). Security our water supply protecting a vulnerable resources, PennWell Publishers, Tulsa, OK.
Laird, C., Biegler, L., van Bloemen Waanders, B., and Bartlett, R. (2005). “Contamination source determination for water networks.” J. Water Resour. Plann. Manage., 125–134.
Lindell, M., Mumpower, J., Wu, H. C., and Huang, S.-K. (2010). “Perceptions and expected responses to a water contamination emergency.” Hazard Reduction and Recovery Center, Texas A&M Univ., College Station, TX.
Liu, L., Ranjithan, S., and Mahinthakumar, G. (2011). “Contamination source identification in water distribution systems using an adaptive dynamic optimization procedure.” J. Water Resour. Plann. Manage., 183–192.
Liu, L., Zechman, E. M., Mahinthakumar, G., and Ranji Ranjithan, S. (2012). “Identifying contaminant sources for water distribution systems using a hybrid method.” Civ. Eng. Environ. Syst., 29(2), 123–136.
Mayer, P., and DeOreo, W. (1999). Residential end uses of water. American Water Works Association, Denver.
Miller, J., and Page, S. (2007). Complex adaptive system, Princeton University Press, Princeton, NJ.
North, M. J., and Macal, C. M. (2007). Managing business complexity: Discovering strategic solutions with agent-based modeling and simulation, Oxford University Press, New York.
Perry, R. W., and Lindell, M. K. (2007). Emergency planning, Wiley, Hoboken, NJ.
Poulin, A., Mailhot, A., Grondin, P., Delorme, L., and Villeneuve, J. P. (2006). “Optimization of operational response to contamination in water networks.” Water Distribution Systems Analysis Symp. Proc., ASCE, Reston, VA, 1–15.
Preis, A., and Ostfeld, A. (2006). “Contamination source identification in water systems: A hybrid model trees linear programming scheme.” J. Water Resour. Plann. Manage., 263–273.
Rasekh, A., and Brumbelow, K. (2014). “Drinking water distribution systems contamination management to reduce public health impacts and system service interruptions.” Environ. Modell. Software, 51(0), 12–25.
Rasekh, A., Shafiee, M. E., Zechman, E. M., and Brumbelow, K. (2013). “Sociotechnical risk assessment for water distribution system contamination threats.” J. Hydroinf., 16(3), 531–549.
Sadiq, R., Kleiner, Y., and Rajani, B. (2008). “Simulation-based localized sensitivity analyses (SALSA): An example of water quality failures in distribution networks.” World Environmental and Water Resources Congress, ASCE, Reston, VA, 1–10.
Shafiee, M., and Berglund, E. (2015). “Real-time guidance for hydrant flushing using sensor-hydrant decision trees.” J. Water Resour. Plann. Manage., .
Shafiee, M. E. (2013). “Modeling sociotechnical water distribution system contamination events to evaluate and identify mitigation strategies.” North Carolina State Univ., Raleigh, NC.
Shafiee, M. E., and Berglund, E. Z. (2016). “Agent-based modeling and evolutionary computation for disseminating public advisories about hazardous material emergencies.” Comput. Environ. Urban Syst., 57, 12–25.
Shafiee, M. E., Berglund, E. Z., and Lindell, M. K. (2016). “An agent-based modeling framework for assessing the public health protection of water advisories.” Expert Syst. Appl., in press.
Shafiee, M. E., and Zechman, E. M. (2013). “An agent-based modeling framework for sociotechnical simulation of water distribution contamination events.” J. Hydroinf., 15(3), 862–880.
Smalley, B., Minsker, B., and Goldberg, D. (2000). “Risk-based in situ bioremediation design using a noisy genetic algorithm.” Water Resour. Res., 36(10), 3043–3052.
USEPA (United States Environmental Protection Agency). (2003). “Response protocol toolbox: Planning for and responding to drinking water contamination threats and incidents: Overview and application.”, Washington, DC.
Watts, D. J. (1999). Small Worlds: The dynamics of networks between order and randomness, Princeton University Press, Princeton, NJ.
Woo, D. M., and Kim, J. (2003). “Sociotechnical systems, risk management, and public health: comparing the North Battleford and Walkerton outbreaks.” Reliab. Eng. Syst. Saf., 80(3), 253–269.
Zechman, E. M. (2010). “Integrating complex adaptive system simulation and evolutionary computation to support water infrastructure threat management.” Proc., 12th Annual Conf. on Companion on Genetic and Evolutionary Computation, Vol. 10, ACM, New York, 1809–1816.
Zechman, E. M. (2011). “Agent-based modeling to simulate contamination events and evaluate threat management strategies in water distribution systems.” Risk Anal., 31(5), 758–772.
Zechman, E. M. (2013). “Integrating evolution strategies and genetic algorithms with agent-based modeling for flushing a contaminated water distribution system.” J. Hydroinf., 15(3), 798–812.
Zechman, E. M., and Ranjithan, S. R. (2009). “Evolutionary computation-based methods for characterizing contaminant sources in a water distribution system.” J. Water Resour. Plann. Manage., 334–343.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 143Issue 4April 2017

History

Received: Nov 1, 2015
Accepted: Sep 27, 2016
Published ahead of print: Jan 25, 2017
Published online: Jan 26, 2017
Published in print: Apr 1, 2017
Discussion open until: Jun 26, 2017

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Authors

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M. Ehsan Shafiee, M.ASCE [email protected]
Data Scientist and Hydraulic Engineer, Sensus, Inc., 8601 Six Forks Rd. #700, Raleigh, NC 27615 (corresponding author). E-mail: [email protected]
Emily Zechman Berglund, M.ASCE
Associate Professor, Dept. of Civil, Construction, and Environmental Engineering, North Carolina State Univ., 2501 Stinson Dr., 208 Mann Hall, Campus Box 7908, Raleigh, NC 27695.

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