Reliability and Remediation Cost of Optimal Remediation Design Considering Uncertainty in Aquifer Parameters
Publication: Journal of Water Resources Planning and Management
Volume 134, Issue 5
Abstract
Reliability of a “preassumed” optimal remediation design using a pump and treat method is evaluated. A “true” hydraulic conductivity field with a certain spatial correlation is supposed. Hydraulic conductivity values are sampled at several locations from the true field. The preassumed remediation design is optimized in the hydraulic conductivity field composed by interpolation of the sampled data. This design is applied to random conductivity fields generated by using conditional simulations in which the conductivity values sampled from the true field are used as the conditioning points. The remediation costs for each generated conductivity field are computed when a preassumed optimal remediation design is applied. The cumulative distribution functions (CDFs) of the required remediation costs are obtained. The CDFs of the remediation cost show that the density of sampling and concentrated sampling in a highly contaminated zone have a great influence on the reliability and uncertainty of the preassumed optimal remediation design.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The writers are grateful to the two anonymous reviewers. This paper was supported by the Sustainable Water Resources Research Center of the 21st Century Frontier Research Program (No. 3-4-3), Advanced Environment Biotechnology Research Center (AEBRC) at POSTECH, and partly by the Korean Energy Management Corporation (KEMCO) through KIGAM.
References
Ahlfeld, D. P., and Mulligan, A. E. (2000). Optimal management of flow in groundwater systems, Academic, San Diego.
Bakr, M. I., te Strost, C. B. M., and Meijerink, A. (2003). “Stochastic groundwater quality management: Role of spatial variability and conditioning.” Water Resour. Res., 39(4), 1078.
Chan Hilton, A. B., and Culver, T. B. (2000). “Constraint handling for genetic algorithms in optimal remediation design.” J. Water Resour. Plann. Manage., 126(3), 128–137.
Dougherty, D. E., and Marryott, R. A. (1991). “Optimal groundwater management: 1. Simulated annealing.” Water Resour. Res., 27(10), 2497–2508.
Feyen, L., and Goelick, S. M. (2005). “Framework to evaluate the worth of hydraulic conductivity data for optimal groundwater resources management in ecologically sensitive areas.” Water Resour. Res., 41(2), W03019.
Freeze, R. A., and Gorelick, S. M. (1999). “Convergence of stochastic optimization and decision analysis in the engineering design of aquifer remediation.” Ground Water, 37(6), 934–954.
Freeze, R. A., Massmann, J., Smith, L., Sperling, T., and James, R. (1990). “Hydrogeological decision analysis: 1. A framework.” Ground Water, 28(5), 738–766.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning, Addison-Wesley Inc., Reading, Mass.
Goovaerts, P. (1997). Geostatistics for natural resources evaluation, Oxford University Press, New York.
Gorelick, S. M. (1983). “A review of distributed parameter ground water management modeling method.” Water Resour. Res., 19(2), 305–319.
Gren, I.-M., Destouni, G., and Tempone, R. (2002). “Cost effective policies for alternative distributions of stochastic water pollution.” J. Environ. Manage., 66, 145–157.
Guan, J., and Aral, M. M. (2004). “Optimal design of groundwater remediation systems using fuzzy set theory.” Water Resour. Res., 40(1), W01518.
Harbaugh, A. W., and McDonald, M. G. (1996). “User’s documentation for MODFLOW-96, an update to the U.S. Geological Survey modular finite-difference ground-water flow model.” U.S. Geological Survey Open-File Report 96-485, U.S. Geological Survey, Reston, Va.
Hsiao, C.-T., and Chang, L.-C. (2002). “Dynamic optimal groundwater management with inclusion of fixed cost.” J. Water Resour. Plann. Manage., 128(1), 57–65.
Huang, C., and Mayer, A. S. (1997). “Pump-and-treat optimization using well locations and pumping rates as decision variables.” Water Resour. Res., 33(5), 1001–1012.
Johnson, V. M., and Rogers, L. L. (1995). “Location analysis in groundwater remediation using neural networks.” Ground Water, 33(5), 749–758.
Karatzas, G. P., and Pinder, G. F. (1996). “The solution of groundwater quality management problems with nonconvex feasible region using a cutting plane optimization technique.” Water Resour. Res., 32(4), 1091–1100.
Khan, F. I., Husain, T., and Hejazi, R. (2004). “An overview and analysis of site remediation technologies.” J. Environ. Manage., 71, 95–122.
Ko, N. Y., Lee, K. K., and Hyun, Y. (2005). “Optimal groundwater remediation design of a pump and treat system considering clean-up time.” Geosci. J., 9(1), 23–31.
Olea, R. A. (1999). Geostatistics for engineers and earth scientists, Kluwer Academic, Norwell, Mass.
U.S. Environmental Protection Agency (USEPA). (1999). “Groundwater cleanup: Overview of operating experience at 28 sites.” Office of Solid Waste and Emergency Response, Washington, D.C.
U.S. Environmental Protection Agency (USEPA). (2004). “Treatment technologies for site cleanup: Annual status report.” 11th Ed., Office of Solid Waste and Emergency Response, Washington, D.C.
Wagner, B. J. (1995). “Recent advances in simulation-optimization groundwater management modeling.” Review of Geophysics, U.S. National Report to International Union of Geodesy and Geophysics 1991–1994, 1021–1028.
Wagner, J. M., Shamir, U., and Nemati, H. R. (1992). “Groundwater quality management under uncertainty: Stochastic programming approaches and the value of information.” Water Resour. Res., 28(5), 1233–1246.
Wang, M., and Zheng, C. (1997). “Optimal remediation policy selection under general condition.” Ground Water, 35(5), 757–764.
Wang, T. A., and McTernan, W. F. (2002). “The development and application of a multilevel decision analysis model for the remediation of contaminated groundwater under uncertainty.” J. Environ. Manage., 64, 221–235.
Zheng, C., and Wang, P. P. (1998). MT3DMS: A modular three-dimensional multispecies transport model for simulation of advection, dispersion, and chemical reactions of contaminants in groundwater systems: Documentation and user’s guide, U.S. Army Corps of Engineers, Vicksburg, Miss.
Zheng, C., and Wang, P. P. (2002). “A field demonstration of the simulation optimization approach for remediation system design.” Ground Water, 40(3), 258–265.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 134 • Issue 5 • September 2008
Pages: 413 - 421
Copyright
© 2008 ASCE.
History
Received: Mar 2, 2006
Accepted: Dec 27, 2007
Published online: Sep 1, 2008
Published in print: Sep 2008
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.