Risk-Cost Decision Framework for Aquifer Remediation Design
Publication: Journal of Water Resources Planning and Management
Volume 122, Issue 6
Abstract
The writers present a framework for increasing the effectiveness of remedial design decision-making at ground-water contamination sites where there is uncertainty in many parameters that affect remediation design. It is specifically designed for broad, “big picture” analyses, such as in the preliminary stages of remedial design. The presented framework is used to (1) select the best remedial design from a suite of possible ones; (2) estimate if additional data collection is cost-effective; and (3) determine the most important parameters to be sampled. The framework is developed by combining elements from Latin-Hypercube simulation of contaminant transport, economic risk-cost analysis, and regional sensitivity analysis (RSA). The framework is demonstrated using a hypothetical contamination problem where radionuclide strontium ( 90 Sr) is leaching from a trench into the ground water. Three remediation design alternatives are considered: monitoring only, isolating the source trench, and installing a plume containment and treatment system. Uncertainty in remediation design performance is due to uncertainty in 13 flow and transport parameters including hydraulic conductivity and source strength. The methodology can be applied to a variety of remediation problems.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Auslander, D. M., Spear, R. C., and Young, G. E.(1982). “A simulation-based approach to the design of control systems with uncertain parameters.”Trans. ASME, 104(1), 20–26.
2.
Beck, M. B.(1987). “Water quality modeling: a review of the analysis of uncertainty.”Water Resour. Res., 23(8), 1939–1442.
3.
Ben-Zvi, M., Berkowitz, B., and Kesler, S.(1988). “Preposterior analysis as a tool for data evaluation: application to aquifer contamination.”Water Res. Man., 2, 11–20.
4.
Christakos, G., and Killam, B. R.(1993). “Sampling design for classifying contaminant level using annealing search algorithms.”Water Resour. Res., 29(12), 4063–4076.
5.
Davis, D. R., Kisiel, C. C., and Duckstein, L.(1972). “Bayesian decision theory applied to design in hydrology.”Water Resour. Res., 8(1), 33–41.
6.
Freeze, R. A., Massmann, J., Smith, J. L., Sperling, T., and James, B. R.(1990). “Hydrogeological decision analysis. I: A framework.”Ground Water, 28(5), 738–766.
7.
Freeze, R. A., James, B., Massmann, J., Sperling, T., and Smith, L.(1992). “Hydrogeological decision analysis: 4. the concept of data worth and its use in the development of the site investigation strategies.”Ground Water, 30(4), 574–588.
8.
Gates, J. S., and Kisiel, C. C.(1974). “Worth of additional data to a digital computer model of a groundwater basin.”Water Resour. Res., 10(5), 1031–1038.
9.
Grosser, P. W., and Goodman, A. S.(1985). “Determination of groundwater sampling frequencies through Bayesian decision theory.”Civ. Engrg. Sys., 2(4), 186–194.
10.
Hornberger, G. M., and Spear, R. C.(1980). “Eutrophication in Peel Inlet I. the problem-defining behavior and a mathematical model for the phosphorous scenario.”Water Res., 14, 29–42.
11.
Iman, R. L., and Conover, W. J. (1980). “Small sample sensitivity analysis techniques for computer models, with an application to risk assessment.”Communications in Statistics. Part A: Theory and Applications, A9(17), 1749–1842.
12.
James, B. R., Gwo, J. P., and Toran, L. (1995). “An economic framework using modeling for improving aquifer remediation design.”Tech. Rep. No. 17, ORNL Groundwater Programs Ofc., Oak Ridge Nat. Lab., Oak Ridge, Tenn.
13.
James, B. R., and Freeze, R. A.(1993). “The worth of data in predicting aquitard continuity in hydrogeological design.”Water Resour. Res., 29(7), 2049–2065.
14.
James, B. R., and Gorelick, S. M.(1994). “When enough is enough: the worth of monitoring data in aquifer remediation design.”Water Resour. Res., 30(12), 3499–3514.
15.
Maddock III, T.(1973). “Management model as a tool for studying the worth of data.”Water Resour. Res., 9(2), 270–280.
16.
Press, W. H., Flannery, B. P., Teukolksy, S. A., and Vetterling, W. T. (1987). Numerical recipes, the art of scientific computing . Cambridge University Press, New York, N.Y.
17.
Rautman, C. A., McGraw, M. A., Istok, J. D., Sigda, J. M., and Kaplan, P. G. (1994). “Probabilistic comparison of alternative characterization technologies at the fernald uranium soils and integrated demonstration project.”Proc., Waste Mgmt. '94, R. G. Post, ed., Laser Options, Inc., Tucson, Ariz., 2117–2124.
18.
Spear, R. C., and Hornberger, G. M.(1980). “Eutrophication in Peel Inlet II. identification of critical uncertainties via generalized sensitivity analysis.”Water Res., 14, 43–49.
19.
Yeh, G. T. (1987). “3DFEMWATER: a three dimension finite element model of water flow through saturated-unsaturated media.”ORNL-6386, Oak Ridge Nat. Lab., Oak Ridge, Tenn.
20.
Yeh, G. T., and Gwo, J. P. (1990). “A lagrangian-eulerian approach to modeling multicomponent reactive transport.” G. Gambolati, A. Rinaldo, C. A. Brebbia, W. G. Gray, and G. F. Pinder, eds., Computational Methods in Subsurface Hydrology, Proc., VIII Int. Conf. on Comp. Methods in Water Resour., Springer-Verlag, New York, N.Y., 419–427.
Information & Authors
Information
Published In
Copyright
Copyright © 1996 American Society of Civil Engineers.
History
Published online: Nov 1, 1996
Published in print: Nov 1996
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.