Abstract
The design of contamination warning systems and the performance of forensic tools are dependent on the performance of the event detection algorithms (EDA). However, most current EDA evaluation approaches do not account for the actual changes of common water-quality parameters in response to a contaminant. Thus, the objective of the current study was to develop water-quality models to represent the dynamics of chlorine, hydrogen ion concentration (pH), and conductivity in response to two contaminants [potassium cyanide (KCN) and nicotine] using experimental data. For chlorine-contaminant dynamics, a two-species second-order model was used to represent the reactions between chlorine and the background dissolved organic carbon as well as the contaminant. To simulate the change in pH, an equilibrium model was used to account for various water-quality species and was coupled with the dynamic chlorine model. As for electrical conductivity (EC), a step response, which is a linear relationship to the amount of contaminant added, was used to simulate the change of EC. These water-quality dynamic models were incorporated into EPANET-MSX to more realistically simulate the responses of common water-quality parameters to a contamination event at a network scale, as well as assess current assumptions/evaluation techniques associated with risk assessment for sensor placement and EDA performance. Results demonstrated that the current EDA evaluation approaches, as well as contamination warning system (CWS) design assumptions, may not adequately represent the EDA performance under conditions likely to be observed within a distribution system.
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Acknowledgments
The authors sincerely thank U.S. EPA’s National Homeland Security Research Center for providing experiment data to conduct this study. We also would like to gratefully acknowledge the funding support provided by the CMMI Directorate, Civil Infrastructure Systems (NSF) through Grant No. #0900713.
References
Alexander, M. (2010). “An integrated field-scale assessment of chloramine dynamics, by-product formation, and nitrification modeling.” Master’s thesis, Dept. of Civil and Environmental Engineering, Univ. of Cincinnati, Cincinnati.
Allgeier, S. C., Pulz, J., and Murray, R. (2006). “Conceptual design of a contamination warning system.” Proc., Water Security Congress, AWWA, Washington, DC.
Berry, J., et al. (2012). “User’s manual: TEVA-SPOT toolkit 2.5.2.”, National Homeland Security Research Center, U.S. Environmental Protection Agency, Washington, DC.
Berry, J., Hart, W. E., Phillips, C. A., Uber, J. G., and Watson, J.-P. (2006). “Sensor placement in municipal water networks with temporal integer programming models.” J. Water Resour. Plann. Manage., 218–224.
Biswas, P., Lu, C., and Clark, R. M. (1993). “A model for chlorine concentration decay in pipes.” Water Res., 27(12), 1715–1724.
Boccelli, D. L., et al. (2004). “Tracer tests for network model calibration.” Proc., World Water and Environmental Resources Congress, ASCE, Salt Lake City.
Boccelli, D. L., Tryby, M. E., Uber, J. G., and Summers, R. S. (2003). “A reactive species model for chlorine decay and THM formation under rechlorination conditions.” Water Res., 37(11), 2654–2666.
Braun, M., Bernard, T., Ung, H., Piller, O., and Gilbert, D. (2015). “CFD modeling of contaminant mixing at junctions for an online security management toolkit in water distribution networks.” J. Water Supply: Res. Technol.–AQUA, 64(5), 504–515.
Byer, D., and Carlson, K. H. (2005). “Real-time detection of intentional chemical contamination in the distribution system.” J. Am. Water Works Assoc., 97(7), 130–133.
Clark, R., and Sivaganesan, M. (2002). “Predicting chlorine residuals in drinking water: Second order model.” J. Water Resour. Plann. Manage., 152–161.
Clark, R. M. (1998). “Chlorine demand and TTHM formation kinetics: A second-order model.” J. Environ. Eng., 16–24.
Dartmann, J., Sadlowsky, B., Dorsch, T., and Johannsen, K. (2010). “Copper corrosion in drinking water systems—Effect of pH and phosphate-dosage.” Mater. Corros., 61(3), 189–198.
Fisher, I., Kohpaei, A. J., and Sathasivan, A. (2010). “Comment on ‘Using Bayesian statistics to estimate the coefficients of a two-component second-order chlorine bulk decay model for a water distribution system’ by Huang, J. J., McBean, E. A.” Water Res., 44(10), 3309–3310.
Gang, D. D., Segar, R. L., Clevenger, T. E., and Banerji, S. K. (2002). “Using chlorine demand to predict TTHM and HAA9 formation.” J. Am. Water Works Assoc., 94(10), 76–86.
Gerritsen, C. M., and Margerum, D. W. (1990). “Non-metal redox kinetics: Hypochlorite and hypochlorous acid reactions with cyanide.” Inorg. Chem., 29(15), 2757–2762.
Haas, C., and Karra, S. (1984). “Kinetics of wastewater chlorine demand exertion.” J. Water Pollut. Control Fed., 56(2), 170–173.
Hall, J., et al. (2007). “On-line water quality parameters as indicators of distribution system contamination.” J. Am. Water Works Assoc., 99(1), 66–77.
Hall, J. S., Szabo, J. G., Panguluri, S., and Meiners, G. (2009). “Distribution system water quality monitoring: Sensor technology evaluation methodology and results.”, Office of Water, U.S. Environmental Protection Agency, Cincinnati.
Hart, D. B., and McKenna, S. A. (2012). “CANARY user’s manual version 4.3.2.”, National Homeland Security Research Center, U.S. Environmental Protection Agency, Washington, DC.
Helbling, D. E., and VanBriesen, J. M. (2008). “Continuous monitoring of residual chlorine concentrations in response to controlled microbial intrusions in a laboratory-scale distribution system.” Water Res., 42(12), 3162–3172.
Ho, C. K., and O’Rear, L., Jr. (2009). “Evaluation of solute mixing in water distribution pipe junctions.” J. Am. Water Works Assoc., 101(9), 116–127.
Hu, J., Song, H., and Karanfil, T. (2010). “Comparative analysis of halonitromethane and trihalomethane formation and speciation in drinking water: The effects of disinfectants, pH, bromide, and nitrite.” Environ. Sci. Technol., 44(2), 794–799.
Huang, J. J., and McBean, E. A. (2007). “Using Bayesian statistics to estimate the coefficients of a two-component second-order chlorine bulk decay model for a water distribution system.” Water Res., 41(2), 287–294.
Janke, R., et al. (2010). “Threat ensemble vulnerability assessment—Sensor placement optimization tool (TEVA-SPOT) graphical user interface user’s manual.”, National Homeland Security Research Center, U.S. Environmental Protection Agency, Cincinnati.
Jonkergouw, P. M., Khu, S.-T., Savic, D. A., Zhong, D., Hou, X. Q., and Zhao, H.-B. (2009). “A variable rate coefficient chlorine decay model.” Environ. Sci. Technol., 43(2), 408–414.
Kastl, G. J., Fisher, I. H., and Jegatheesan, V. (1999). “Evaluation of chlorine decay kinetics expressions for drinking water distribution systems modelling.” J. Water Supply: Res. Technol. Aqua, 48(6), 219–226.
Kim, E. J., Herrera, J. E., Huggins, D., Braam, J., and Koshowski, S. (2011). “Effect of pH on the concentrations of lead and trace contaminants in drinking water: A combined batch, pipe loop and sentinel home study.” Water Res., 45(9), 2763–2774.
Klosterman, S. T., Uber, J. G., Murray, R., and Boccelli, D. L. (2013). “An adsorption model for arsenate transport in corroded iron pipes, with application to a simulated intrusion in a water distribution network.” J. Water Resour. Plann. Manage., 649–657.
Kohpaei, A. J., and Sathasivan, A. (2011). “Chlorine decay prediction in bulk water using the parallel second order model: An analytical solution development.” Chem. Eng. J., 171(1), 232–241.
McKenna, S. A., Hart, D., Klise, K., Cruz, V., and Wilson, M. (2007). “Event detection from water quality time series.” Proc., World Water and Environmental Resources Congress, ASCE, Reston, VA.
McKenna, S. A., Wilson, M., and Klise, K. A. (2008). “Detecting changes in water quality data.” J. Am. Water Works Assoc., 100(1), 74–85.
Morel, F., and Hering, J. (1993). Principles and applications of aquatic chemistry, Wiley, New York.
Murray, R., Uber, J., and Janke, R. (2006). “Model for estimating acute health impacts from consumption of contaminated drinking water.” J. Water Resour. Plann. Manage., 293–299.
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.
Paine, J. G. (2003). “Determining salinization extent, identifying salinity sources, and estimating chloride mass using surface, borehole, and airborne electromagnetic induction methods.” Water Resour. Res., 39(3), 10.
Peinado-Guevara, H., et al. (2012). “Relationship between chloride concentration and electrical conductivity in groundwater and its estimation from vertical electrical soundings (VESs) in Guasave, Sinaloa, Mexico.” Ciencia E Investigacion Agraria, 39(1), 229–239.
Piller, O., Deuerlein, J., Gilbert, D., and Weber, J.-M. (2015). “Installing fixed sensors for double calibration and early-warning detection purposes.” Procedia Eng., 119, 564–572.
Preis, A., Whittle, A., and Ostfeld, A. (2008). “Multi-objective sensor network design for water distribution systems.” J. Water Resour. Plann. Manage., 366–377.
Propato, M. (2006). “Contamination warning in water networks: General mixed-integer linear models for sensor location design.” J. Water Resour. Plann. Manage., 225–233.
Romero-Gomez, P., Lansey, K. E., and Choi, C. Y. (2011). “Impact of an incomplete solute mixing model on sensor network design.” J. Hydroinf., 13(4), 642–651.
Rossman, L. A. (2000). “EPANET 2 users manual.” National Risk Management Research Laboratory, U.S. EPA, Cincinnati.
Rossman, L. A., Clark, R. M., and Grayman, W. M. (1994). “Modeling chlorine residuals in drinking-water distribution systems.” J. Environ. Eng., 803–820.
Schwartz, R., Lahav, O., and Ostfeld, A. (2014). “Integrated hydraulic and organophosphate pesticide injection simulations for enhancing event detection in water distribution systems.” Water Res., 63, 271–284.
Shang, F., Uber, J. G., and Rossman, L. A. (2007). “EPANET multi-species extension user’s manual.” National Risk Management Research Laboratory and National Homeland Security Research Center, U.S. EPA, Cincinnati.
Shen, H., Huang, J. J., and McBean, E. A. (2011). “Reply to comment on ‘Using Bayesian statistics to estimate the coefficients of a two-component second-order chlorine bulk decay model for a water distribution system’ by Huang, J. J., McBean, E. A. Water Research. (2007).” Water Res., 45(6), 2355–2357.
Tzatchkov, V. G., Aldama, A. A., and Arreguin, F. I. (2002). “Advection-dispersion-reaction modeling in water distribution networks.” J. Water Resour. Plann. Manage., 334–342.
U.S. EPA. (2005). “Chemical assessment summary: Chlorine cyanide.” Washington, DC.
U.S. EPA. (2010). “Toxicological review of hydrogen cyanide and cyanide salts.” Washington, DC.
Yang, X., and Boccelli, D. L. (2012). “Model-based event detection in distribution systems.” Proc., World Water and Environmental Resources Congress, ASCE, Reston, VA.
Yang, Y. J., Haught, R. C., and Goodrich, J. A. (2009). “Real-time contaminant detection and classification in a drinking water pipe using conventional water quality sensors: Techniques and experimental results.” J. Environ. Manage., 90(8), 2494–2506.
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Published In
Journal of Water Resources Planning and Management
Volume 142 • Issue 10 • October 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Aug 13, 2015
Accepted: Mar 2, 2016
Published online: Jun 9, 2016
Published in print: Oct 1, 2016
Discussion open until: Nov 9, 2016
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