Explicit Water Quality Model Generation and Rapid Multiscenario Simulation
Publication: Journal of Water Resources Planning and Management
Volume 140, Issue 5
Abstract
Emerging applications in water distribution systems place new challenges on water quality modeling tools, including the need for an explicit mathematical representation and simulation of large ensembles of contamination scenarios. We present a computational framework, referred to as Merlion, that creates an explicit mathematical model for water quality in drinking water distribution systems that is appropriate for embedding within other numerical applications (e.g., optimization). This model is efficiently generated for large water distribution systems and represents an all-to-all mapping (inputs include injections at all possible nodes and time steps, and outputs include concentrations at all possible nodes and time steps), which is necessary for many security applications. The Merlion framework is compared to water quality simulations using EPANET on a set of network models ranging in size from 10 to approximately 13,000 nodes. The simulation results show excellent agreement. Furthermore, the explicit linear model can be used to evaluate a large number of tracer scenarios very quickly, speeding up current security tools by approximately an order of magnitude.
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Acknowledgments
This research was supported in part by the Office of Advanced Scientific Computing Research within the Department of Energy Office of Science as part of the Complex Interconnected Distributed Systems program.
References
Al-Omari, A., and Chaudhry, M. (2001). “Unsteady-state inverse chlorine modeling in pipe networks.” J. Hydraul. Eng., 669–677.
Berry, J., Boman, E., Riesen, L. A., Hart, W. E., Phillips, C. A., and Watson, J. P. (2011). User’s manual: TEVA-SPOT toolkit 2.5, Sandia National Laboratories, Albuquerque, NM.
Boulus, P., Altman, T., and Sadhal, K. S. (1992). “Computer modeling of water quality in large multiple-source networks.” Appl. Math. Model., 16(8), 439–445.
Davis, T. A. (2006). “Direct methods for sparse linear systems.” SIAM, Vol. 2.
Grayman, W. M., Clark, R. M., and Groodrich, J. A. (1988). “Modeling distribution system water quality: Dynamic approach.” J. Water Resour. Plann. Manage., 295–312.
Chung, G., Lansey, K. E., and Boulos, P. F. (2007). “Steady-state water quality analysis for pipe network systems.” J. Environ. Eng., 133(7), 777–782.
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.
Islam, M. R., Chaudhry, M. H., and Clark, R. M. (1997). “Inverse modeling of chlorine concentration in pipe networks under dynamic conditions.” J. Environ. Eng., 1033–1040.
Laird, C. D., Biegler, L. T., and van Bloemen Waanders, B. G. (2007). “Real-time, large scale optimization of water network systems using a subdomain approach.” SIAM Series in Computational Science and Engineering, L. T. Biegler, O. Ghattas, M. Heinkenschloss, D. Keyes, and B. van Bloemen Waanders, SIAM, 291–308.
Laird, C. D., Biegler, L. T., van Bloemen Waanders, B. G., and Barlett, R. A. (2005). “Contamination source determination for water networks.” J. Water Resour. Plann. Manage., 125–134.
Laird, C. D., Biegler, L. T., and van Bloemen Waanders, B. G. (2006). “Mixed-integer approach for obtaining unique solutions in source inversion of water networks.” J. Water Resour. Plann. Manage., 242–251.
Liou, C. P., and Kroon, J. R. (1987). “Modeling the propagation of waterborne substances in distribution networks.” J. Am. Water Works Assoc., 79(11), 54–58.
Males, R., Clark, R., Wehrman, P., and Gates, W. (1985). “Algorithm for mixing problems in water systems.” J. Hydraul. Eng., 206–219.
Mann, A. V., McKenna, S. A., E., H. W., and Laird, C. D. (2012). “Real-time inversion in large-scale water networks using discrete measurements.” Comput. Chem. Eng., 37, 143–151.
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.
Rossman, L. A., and Boulos, P. F. (1996). “Numerical methods for modeling water quality in distribution systems: A comparison.” J. Water Resour. Plann. Manage., 137–146.
Rossman, L. A. (2000). EPANET 2 users manual, USEPA, Cincinnati.
Shah, M., and Sinai, G. (1988). “Steady state model for dilution in water networks.” J. Hydraul. Eng., 192–206.
Shang, F., Uber, J. G., and Polycarpou, M. M. (2002). “Particle backtracking algorithm for water distribution system analysis.” J. Environ. Eng., 441–450.
Zierolf, M. L., Polycarpou, M. M., and Uber, J. G. (1998). “Development and autocalibration of an input–output model of chlorine transport in drinking water distribution systems.” IEEE Trans. Control Syst. Technol., 6(4), 543–553.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 140 • Issue 5 • May 2014
Pages: 666 - 677
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Apr 3, 2012
Accepted: Jul 30, 2012
Published online: Aug 17, 2012
Discussion open until: Jan 17, 2013
Published in print: May 1, 2014
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