Technical Papers
May 31, 2022

An Agent-Based Model for Contamination Response in Water Distribution Systems during the COVID-19 Pandemic

Publication: Journal of Water Resources Planning and Management
Volume 148, Issue 8

Abstract

Contamination events in water distribution systems (WDS) are emergencies that cause public health crises and require fast response by the responsible utility manager. Various models have been developed to explore the reactions of relevant stakeholders during a contamination event, including agent-based modeling. As the COVID-19 pandemic has changed the daily habits of communities around the globe, consumer water demands have changed dramatically. In this study, an agent-based modeling framework is developed to explore social dynamics and reactions of water consumers and a utility manager to a contamination event, while considering regular and pandemic demand scenarios. Utility manager agents use graph theory algorithms to place mobile sensor equipment and divide the network in sections that are endangered of being contaminated or cleared again for water consumption. The status of respective network nodes is communicated to consumer agents in real time, and consumer agents adjust their water demands accordingly. This sociotechnological framework is presented using the overview, design, and details protocol. The results comprise comparisons of reactions and demand adjustments of consumers to a water event during normal and pandemic times, while exploring new methods to predict the fate of a contaminant plume in the WDS.

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Data Availability Statement

All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors gratefully acknowledge the support provided by the United States-Israel Binational Science Foundation (BSF).

References

Allgeier, S. C., J. Pulz, and R. Murray. 2006. “Conceptual design of a contamination warning system.” In Proc., Water Security Congress. Washington DC: American Water Works Association.
Asadi-Ghalhari, M., and R. Aali. 2020. “COVID-19: Reopening public spaces and secondary health risk potential via stagnant water in indoor pipe networks.” Indoor Built Environ. 29 (8): 1184–1185. https://doi.org/10.1177/1420326X20943257.
Athanasiadis, I. N., A. K. Mentes, P. A. Mitkas, and Y. A. Mylopoulos. 2005. “A hybrid agent-based model for estimating residential water demand.” Simulation 81 (3): 175–187. https://doi.org/10.1177/0037549705053172.
Balacco, G., V. Totaro, V. Iacobellis, A. Manni, M. Spagnoletta, and A. F. Piccinni. 2020. “Influence of COVID-19 spread on water drinking demand: The case of Puglia Region (Southern Italy).” Sustainability 12 (15): 5919. https://doi.org/10.3390/su12155919.
Berglund, E. Z. 2015. “Using agent-based modeling for water resources planning and management.” J. Water Resour. Plann. Manage. 141 (11): 04015025. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000544.
Berglund, E. Z., et al. 2021. “Water and wastewater systems and utilities: Challenges and opportunities during the COVID-19 pandemic.” J. Water Resour. Plann. Manage. 147 (5): 1–9. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001373.
Bonabeau, E. 2002. “Agent-based modeling: Methods and techniques for simulating human systems.” Proc. Natl. Acad. Sci. U.S.A. 99 (S3): 7280–7287. https://doi.org/10.1073/pnas.082080899.
Brumbelow, K., J. Torres, S. Guikema, E. Bristow, and L. Kanta. 2007. “Virtual cities for water distribution and infrastructure system research.” In Proc., 2007 World Environmental and Water Resources Congress: Restoring Our Natural Habitat. Reston, VA: ASCE.
Dryhurst, S., C. R. Schneider, J. Kerr, A. L. J. Freeman, G. Recchia, A. M. van der Bles, D. Spiegelhalter, and S. van der Linden. 2020. “Risk perceptions of COVID-19 around the world.” J. Risk Res. 23 (7–8): 994–1006. https://doi.org/10.1080/13669877.2020.1758193.
Eliades, D. G., M. Kyriakou, S. Vrachimis, and M. M. Polycarpou. 2016. “EPANET-MATLAB toolkit: An open-source software for interfacing EPANET with MATLAB.” Accessed March 23, 2017. https://zenodo.org/record/437751#.YnD3kdpBzcc.
Friedman, M., G. J. Kirmeyer, and E. Antoun. 2002. “Developing and implementing a distribution system flushing program.” J. Am. Water Works Assoc. 94 (7): 48–56. https://doi.org/10.1002/j.1551-8833.2002.tb09505.x.
Galán, J. M., A. López-Paredes, and R. Del Olmo. 2009. “An agent-based model for domestic water management in Valladolid metropolitan area.” Water Resour. Res. 45 (5): 1–17. https://doi.org/10.1029/2007WR006536.
Giacomoni, M. H., L. Kanta, and E. M. Zechman. 2013. “Complex adaptive systems approach to simulate the sustainability of water resources and urbanization.” J. Water Resour. Plann. Manage. 139 (5): 554–564. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000302.
Grimm, V., et al. 2006. “A standard protocol for describing individual-based and agent-based models.” Ecol. Modell. 198 (1–2): 115–126. https://doi.org/10.1016/j.ecolmodel.2006.04.023.
Grimm, V., U. Berger, D. L. DeAngelis, J. G. Polhill, J. Giske, and S. F. Railsback. 2010. “The ODD protocol: A review and first update.” Ecol. Modell. 221 (23): 2760–2768. https://doi.org/10.1016/j.ecolmodel.2010.08.019.
Hall, J., A. D. Zaffiro, R. B. Marx, P. C. Kefauver, E. Radha Krishnan, R. C. Haught, and J. G. Herrmann. 2007. “On-line water quality parameters as indicators of distribution system contamination.” J. Am. Water Works Assn. 99 (1): 66–77. https://doi.org/10.1002/j.1551-8833.2007.tb07847.x.
Janke, R., R. Murray, J. Uber, and T. Taxon. 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. 132 (4): 310–313. https://doi.org/10.1061/(ASCE)0733-9496(2006)132:4(310).
Kadinski, L., M. Rana, D. Boccelli, and A. Ostfeld. 2019. “Water distribution systems analysis.” In Proc., World Environmental and Water Resources Congress 2019, 536–542. Reston, VA: ASCE.
Kalbusch, A., E. Henning, M. P. Brikalski, F. V. de Luca, and A. C. Konrath. 2020. “Impact of coronavirus (COVID-19) spread-prevention actions on urban water consumption.” Resour. Conserv. Recycl. 163 (Dec): 105098. https://doi.org/10.1016/j.resconrec.2020.105098.
Kandiah, V. K., E. Z. Berglund, and A. R. Binder. 2019. “An agent-based modeling approach to project adoption of water reuse and evaluate expansion plans within a sociotechnical water infrastructure system.” Sustainable Cities Soc. 46 (Apr): 101412. https://doi.org/10.1016/j.scs.2018.12.040.
Kanta, L., and E. Zechman. 2014. “Complex adaptive systems framework to assess supply-side and demand-side management for urban water resources.” J. Water Resour. Plann. Manage. 140 (1): 75–85. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000301.
Kirstein, J. K., H. J. Albrechtsen, and M. Rygaard. 2014. “Simplification of water distribution network simulation by topological clustering–Investigation of its potential use in Copenhagen’s water supply monitoring and contamination contingency plans.” Procedia Eng. 89: 1184–1191. https://doi.org/10.1016/j.proeng.2014.11.248.
Kirstein, J. K., H. J. Albrechtsen, and M. Rygaard. 2015. “Topological clustering as a tool for planning water quality monitoring in water distribution networks.” Water Sci. Technol. Water Supply 15 (5): 1011–1018. https://doi.org/10.2166/ws.2015.056.
Klise, K. A., D. Hart, D. Moriarty, M. L. Bynum, R. Murray, J. Burkhardt, and T. Haxton. 2017. Water network tool for resilience (WNTR) user manual disclaimer. Washington, DC: USEPA.
Koutiva, I., and C. Makropoulos. 2016. “Modelling domestic water demand: An agent based approach.” Environ. Modell. Software 79 (May): 35–54. https://doi.org/10.1016/j.envsoft.2016.01.005.
Koutiva, I., and C. Makropoulos. 2017. “Exploring the effects of domestic water management measures to water conservation attitudes using agent based modelling.” Water Sci. Technol. Water Supply 17 (2): 552–560. https://doi.org/10.2166/ws.2016.161.
Lindell, M. K., J. L. Mumpower, C. S. Prater, H.-C. Wu, and S.-K. Hwang. 2010. Perceptions and expected responses to a water contamination emergency. College Station, TX: Texas A&M Univ. Hazard Reduction & Recovery Center.
Lüdtke, D. U., R. Luetkemeier, M. Schneemann, and S. Liehr. 2021. “Increase in daily household water demand during the first wave of the COVID-19 pandemic in Germany.” Water 13 (3): 260. https://doi.org/10.3390/w13030260.
Masad, D., and J. Kazil. 2015. “Mesa: An agent-based modeling framework.” In Proc., 14th PYTHON in Science Conf., 51–58. Buffalo, NY: Univ. at Buffalo.
Monroe, J., E. Ramsey, and E. Berglund. 2018. “Allocating countermeasures to defend water distribution systems against terrorist attack.” Reliability Eng. Syst. Saf. 179 (Nov): 37–51. https://doi.org/10.1016/j.ress.2018.02.014.
Müller, B., F. Bohn, G. Dreßler, J. Groeneveld, C. Klassert, R. Martin, M. Schlüter, J. Schulze, H. Weise, and N. Schwarz. 2013. “Describing human decisions in agent-based models—ODD+D, an extension of the ODD protocol.” Environ. Modell. Software 48 (Oct): 37–48. https://doi.org/10.1016/j.envsoft.2013.06.003.
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. 134 (6): 556–568. https://doi.org/10.1061/(ASCE)0733-9496(2008)134:6(556).
Ostfeld, A., and E. Salomons. 2004. “Optimal layout of early warning detection stations for water distribution systems security.” J. Water Resour. Plann. Manage. 130 (5): 377–385. https://doi.org/10.1061/(ASCE)0733-9496(2004)130:5(377).
Perelman, L., J. Arad, M. Housh, and A. Ostfeld. 2012. “Event detection in water distribution systems from multivariate water quality time series.” Environ. Sci. Technol. 46 (15): 8212–8219. https://doi.org/10.1021/es3014024.
Perelman, L., and A. Ostfeld. 2011. “Topological clustering for water distribution systems analysis.” Environ. Modell. Software 26 (7): 969–972. https://doi.org/10.1016/j.envsoft.2011.01.006.
Perelman, L., and A. Ostfeld. 2012. “Water-distribution systems simplifications through clustering.” J. Water Resour. Plann. Manage. 138 (3): 218–229. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000173.
Pesantez, J., F. Alghamdi, S. Sabu, G. Mahinthakumar, and E. Z. Berglund. 2021. “Using a digital twin to explore water infrastructure impacts during the COVID-19 pandemic.” Sustainable Cities Soc. 77 (Feb): 103520. https://doi.org/10.1016/j.scs.2021.103520.
Pohl, I. 1969. Bi-directional and heuristic search in path problems. Menlo Park, CA: Stanford Linear Accelerator Center.
Qiu, M., and A. Ostfeld. 2020. “Dynamic clustering for water distribution system water quality management.” In Proc., World Environmental and Water Resources Congress 2020: Hydraulics, Waterways, and Water Distribution Systems Analysis: Selected Papers from the Proceedings of the World Environmental and Water Resources Congress 2020, 318–328. Washington, DC: American Geophysical Union.
Qiu, M., E. Salomons, and A. Ostfeld. 2021. “An analytical model for the decontamination of water distribution systems using slug-feed method of disinfection.” Water Resour. Res. 57 (3): e2020WR028277. https://doi.org/10.1029/2020WR028277.
Rasekh, A., M. E. Shafiee, E. Zechman, and K. Brumbelow. 2014. “Sociotechnical risk assessment for water distribution system contamination threats.” J. Hydroinf. 16 (3): 531–549. https://doi.org/10.2166/hydro.2013.023.
Robles, F., and N. Perlroth. 2021. “‘Dangerous stuff’: Hackers tried to poison water supply of Florida town.” The New York Times, February 3, 2022.
Rogers, G. O., and J. H. Sorensen. 1991. “Diffusion of emergency warning: Comparing empirical and simulation results.” In Proc., Risk Analysis Prospects and Opportunities, 117–134. New York: Plenum Press.
Rossman, L. A. 2000. Epanet 2 user ’s manual. Cincinnati: National Risk Management Research Laboratary Office of Research and Development.
Sankary, N., and A. Ostfeld. 2016. “Inline mobile sensors for contaminant early warning enhancement in water distribution systems.” J. Water Resour. Plann. Manage. 143 (2): 1–12.https://doi.org/10.1061/(ASCE)WR.1943-5452.0000732.
Sankary, N., and A. Ostfeld. 2017. “Inline mobile sensors for contaminant early warning enhancement in water distribution systems.” J. Water Resour. Plann. Manage. 143 (2): 04016073. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000732.
Schwarz, N., and A. Ernst. 2009. “Agent-based modeling of the diffusion of environmental innovations—An empirical approach.” Technol. Forecasting Soc. Change 76 (4): 497–511. https://doi.org/10.1016/j.techfore.2008.03.024.
Shafiee, M. E., and E. Z. Berglund. 2016. “Agent-based modeling and evolutionary computation for disseminating public advisories about hazardous material emergencies.” Comput. Environ. Urban Syst. 57 (May): 12–25. https://doi.org/10.1016/j.compenvurbsys.2016.01.001.
Shafiee, M. E., and E. Z. Berglund. 2017. “Complex adaptive systems framework to simulate the performance of hydrant flushing rules and broadcasts during a water distribution system contamination event.” J. Water Resour. Plann. Manage. 143 (4): 04017001. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000744.
Shafiee, M. E., E. Z. Berglund, and M. K. Lindell. 2018. “An agent-based modeling framework for assessing the public health protection of water advisories.” Water Resour. Manage. 32 (6): 2033–2059. https://doi.org/10.1007/s11269-018-1916-6.
Shafiee, M. E., and E. M. Zechman. 2013. “An agent-based modeling framework for sociotechnical simulation of water distribution contamination events.” J. Hydroinf. 15 (3): 862–880. https://doi.org/10.2166/hydro.2013.158.
Sowby, R. B. 2020. “Emergency preparedness after COVID-19: A review of policy statements in the U.S. water sector.” Util. Policy 64 (Jun): 101058. https://doi.org/10.1016/j.jup.2020.101058.
Spearing, L. A., N. Thelemaque, J. A. Kaminsky, L. E. Katz, K. A. Kinney, M. J. Kirisits, L. Sela, and K. M. Faust. 2021. “Implications of social distancing policies on drinking water infrastructure: An overview of the challenges to and responses of U.S. utilities during the COVID-19 pandemic.” ACS ES&T Water 1 (4): 888–899. https://doi.org/10.1021/acsestwater.0c00229.
Strickling, H., M. F. DiCarlo, M. E. Shafiee, and E. Berglund. 2020. “Simulation of containment and wireless emergency alerts within targeted pressure zones for water contamination management.” Sustainable Cities Soc. 52 (Jan): 101820. https://doi.org/10.1016/j.scs.2019.101820.
Tarjan, R. 1971. “Depth-first search and linear graph algorithms.” SIAM J. Comput. 1 (2): 114–121. https://doi.org/10.1137/0201010.
Watts, D. J., and S. H. Strogatz. 1998. “Collective dynamics of ‘small world’ networks.” Nature 393 (6684): 440–442. https://doi.org/10.1038/30918.
Wu, L., W. W. A. Wan Salim, S. Malhotra, A. Brovont, J. H. Park, S. D. Pekarek, M. K. Banks, and D. M. Porterfield. 2013. “Self-powered mobile sensor for in-pipe potable water quality monitoring.” In Proc., 17th Int. Conf. on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2013, 14–16. San Diego: Chemical and Biological Microsystems Society.
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. https://doi.org/10.1111/j.1539-6924.2010.01564.x.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 148Issue 8August 2022

History

Received: Aug 30, 2021
Accepted: Mar 11, 2022
Published online: May 31, 2022
Published in print: Aug 1, 2022
Discussion open until: Oct 31, 2022

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Leonid Kadinski, S.M.ASCE [email protected]
Ph.D. Student, Faculty of Civil and Environmental Engineering, Technion—Israel Institute of Technology, Haifa 32000, Israel. Email: [email protected]
Professor, Dept. of Civil, Construction, and Environmental Engineering, North Carolina State Univ., 2501 Stinson Dr., 208 Mann Hall, Campus Box 7908, Raleigh, NC 27695. ORCID: https://orcid.org/0000-0001-9005-9468. Email: [email protected]
Professor, Faculty of Civil and Environmental Engineering, Technion—Israel Institute of Technology, Haifa 32000, Israel (corresponding author). ORCID: https://orcid.org/0000-0001-9112-6079. Email: [email protected]; [email protected]

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  • Coupling Machine Learning and Agent-Based Modeling to Characterize Contamination Sources in Water Distribution Systems for Changing Demand Regimes, World Environmental and Water Resources Congress 2023, 10.1061/9780784484852.082, (881-890), (2023).

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