Multiobjective Design of Dynamic Monitoring Networks for Detection of Groundwater Pollution
Publication: Journal of Water Resources Planning and Management
Volume 133, Issue 4
Abstract
A methodology is developed based on the solution of optimization models for optimal design of groundwater quality monitoring networks. The optimal monitoring network is time varying as the monitoring wells are installed in stages, considering the transient pollutant transport process. The monitoring locations specified as solution to the optimization model change with time. This ensures additional economy in the installation of the network, compared to a single stage network design. The optimization model incorporates uncertainties in prediction or estimation of some of the aquifer parameters such as hydraulic conductivity and dispersivity. Advective, dispersive, and radioactive decay processes of transport in a two-dimensional groundwater system are considered. Randomly generated aquifer parameter values are used to simulate different realizations of resulting pollutant plumes incorporating uncertainties in predicting the transport process. The simulated pollutant plume realizations are subsequently utilized to obtain cumulative distribution functions (CDFs) of actual concentrations at different spatiotemporal locations. These CDFs are incorporated as an approximated distribution function in the optimization model. These CDFs are used to define chance constraints with associated reliabilities. Both single and multiple objective nonlinear optimization models are developed. Performances of these models are evaluated for different specified values of reliabilities using illustrative problems considering tritium as the radioactive pollutant. This monitoring network design model is, in general, applicable to other types of pollutants as well.
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References
Angulo, M., and Tang, W. H. (1999). “Optimal ground-water detection monitoring system design under uncertainty.” J. Geotech. Geoenviron. Eng., 125(6), 510–517.
ASCE Task Committee on Long-Term Groundwater Monitoring Design. (2003). Long-term groundwater monitoring: The state of the art, Reston, Va.
Bear, J. (1979). Hydraulics of groundwater, McGraw-Hill, New York.
Ben-Jemaa, F., Marion, M. A., and Loaiciga, H. A. (1994). “Multivariate geostatistical design of ground-water monitoring networks.” J. Water Resour. Plann. Manage., 120(4), 505–522.
Candela, L., Olea, R. A., and Custodio, E. (1988). “Lognormal kriging for the assessment of reliability in groundwater quality control observation networks.” J. Hydrol., 103(1–2), 67–84.
Charnes, A., and Cooper, W. W. (1963). “Deterministic equivalents for optimizing and satisfying under chance constraints.” Oper. Res., 11(1), 18–39.
Cieniawski, S. E., Eheart, J. W., and Ranjithan, S. (1995). “Using genetic algorithm to solve a multiple objective groundwater monitoring problem.” Water Resour. Res., 31(2), 399–409.
Datta, B., and Dhiman, S. D. (1996). “Chance-constrained optimal monitoring network design for pollutants in ground water.” J. Water Resour. Plann. Manage., 122(3), 180–188.
Datta, B., and Purwar, D. K. (1992). “Optimal design of groundwater quality monitoring network incorporating uncertainties.” Proc., National Symp. on Environment, Bhabha Atomic Research Center, Bombay, India, 129–131.
Freeze, R. A. (1975). “A stochastic-conceptual analysis of one-dimensional groundwater flow in nonuniform homogeneous media.” Water Resour. Res., 11(5), 725–741.
Goode, D. J., and Konikow, L. F. (1989). “Modification of a method-of-characteristics solute-transport model to incorporate decay and equilibrium-controlled sorption or ion exchange.” Water-Resources Investigations Rep. No. 89-4030, U.S. Geological Survey, Reston, Va.
Hogg, R. V., and Craig, A. T. (1978). Introduction to mathematical statistics, Macmillan, New York.
Hudak, P. F., Loaiciga, H. A., and Marino, M. A. (1995). “Regional-scale ground water quality monitoring integer programming.” J. Hydrol., 164(1–4), 153–170.
Konikow, L. F., and Bredehoeft, J. D. (1978). “Computer model of two-dimensional solute transport and dispersion in groundwater.” Techniques of water resources investigation, Book 7, U.S. Geological Survey, Washington, D.C.
Konikow, L. F., Granato, G. E., and Hornberger, G. Z. (1994). “User’s guide to revised method-of-characteristics solute-transport model (MOC—Version 3.1).” Water-Resources Investigations Rep. No. 94–4115, U.S. Geological Survey, Reston, Va.
Lee, Y.-M., and Ellis, J. H. (1996). “Comparison of algorithms for nonlinear integer optimization: Application to monitoring network design.” J. Environ. Eng., 122(6), 524–531.
LINDO Systems Inc. (1999). LINGO user’s guide, Chicago.
Loaiciga, H. A. (1989). “An optimization approach for groundwater quality monitoring network design.” Water Resour. Res., 25(8), 1771–1782.
Loaiciga, H. A., Charbeneau, R. J., Everett, L. G., Fogg, G. E., Hobbs, B. F., and Rouhani, S. (1992). “Review of ground-water quality monitoring network design.” J. Hydraul. Eng., 118(1), 11–37.
Mahar, P. S., and Datta, B. (1997). “Optimal monitoring network and ground-water–pollution source identification.” J. Water Resour. Plann. Manage., 123(4), 199–207.
Massmann, J., and Freeze, R. A. (1987). “Groundwater contamination from waste management sites: The interaction between risk-based engineering design and regulatory policy. I: Methodology.” Water Resour. Res., 23(2), 351–367.
McKinney, D. C., and Loucks, D. P. (1992). “Network design for predicting groundwater contamination.” Water Resour. Res., 28(1), 133–147.
Meyer, P. D., and Brill, E. D., Jr. (1988). “A method for locating wells in a groundwater pollution monitoring network under conditions of uncertainty.” Water Resour. Res., 24(8), 1277–1282.
Meyer, P. D., Valocchi, A. J., and Eheart, J. W. (1994). “Monitoring network design to provide initial detection of groundwater contamination.” Water Resour. Res., 30(9), 2647–2659.
Montas, H. J., Mohtar, R. H., Hassan, A. E., and AlKhal, F. A. (2000). “Heuristic space-time design of monitoring wells for contaminant plume characterization in stochastic flow fields.” J. Contam. Hydrol., 43(3–4), 271–301.
Morgan, D. R., Eheart, J. W., and Valocchi, A. J. (1993). “Aquifer remediation design under uncertainty using a new chance constrained programming technique.” Water Resour. Res., 29(3), 551–561.
Nunes, L. M., Cunha, M. C., and Ribeiro, L. (2004a). “Groundwater monitoring network optimization with redundancy reduction.” J. Water Resour. Plann. Manage., 130(1), 33–43.
Nunes, L. M., Cunha, M. C., and Ribeiro, L. (2004b). “Optimal space-time coverage and exploration costs in groundwater monitoring networks.” Environ. Monit. Assess., 93(1–3), 103–124.
Passarella, G., Vurro, M., D’Agostino V., and Barcelona, M. J. (2003). “Cokriging optimization of monitoring network configuration based on fuzzy and non-fuzzy variogram evaluation.” Environ. Monit. Assess., 82(1), 1–21.
Pinder, G. F., and Bredhoeft, J. D. (1968). “Application of the digital computer for aquifer evaluation.” Water Resour. Res., 4(5), 1069–1093.
Reed, P., and Minesker, B. S. (2004). “Striking the balance: Long-term groundwater monitoring design for conflicting objective.” J. Water Resour. Plann. Manage., 130(2), 140–149.
Reed, P., Minesker, B. S., and Goldberg, D. (2000a). “Designing a competent simple genetic algorithm for search and optimization.” Water Resour. Res., 36(12), 3757–3761.
Reed, P., Minesker, B. S., and Goldberg, D. (2003). “Simplifying multiobjective optimization: An automated design methodology for nondominated sorted genetic algorithm—II.” Water Resour. Res., 39(7), 1196, .
Reed, P., Minesker, B. S., and Valocchi, A. J. (2000b). “Cost-effective long term groundwater monitoring design using genetic algorithm and global mass interpolation.” Water Resour. Res., 36(12), 3731–3741.
Ritzel, B. J., Eheart, J. W., and Ranjithan, S. (1994). “Using genetic algorithm to solve a multiple objective groundwater pollution containment problem.” Water Resour. Res., 30(5), 1589–1603.
Singh, O. (1993). “Optimal design of a time varying monitoring network for radioactive pollutants in groundwater.” MTech thesis, Indian Institute of Technology, Kanpur, India.
Tung, Y. K. (1986). “Groundwater management by chance constrained model.” J. Water Resour. Plann. Manage., 112(1), 1–19.
Wagner, B. J. (1995). “Sampling design methods for groundwater modeling under uncertainty.” Water Resour. Res., 31(10), 2581–2591.
Wu, J., Zheng, C., and Chien, C. C. (2005). “Cost-effective sampling network design for contaminant plume monitoring under general hydrogeological conditions.” J. Contam. Hydrol., 77(1–2), 41–55.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 133 • Issue 4 • July 2007
Pages: 329 - 338
Copyright
© 2007 ASCE.
History
Received: Jun 23, 2005
Accepted: Jul 5, 2006
Published online: Jul 1, 2007
Published in print: Jul 2007
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