TECHNICAL PAPERS
May 1, 1992

Systems Analysis in Ground‐Water Planning and Management

Publication: Journal of Water Resources Planning and Management
Volume 118, Issue 3

Abstract

The objective of this paper is to review the state of the art of systems analysis and optimization techniques developed in the field of water resources for the planning and management of a ground‐water system. The areas reviewed include the following: ground‐water management models, inverse solution techniques for parameter identification, and optimal experimental design methods. Emphasis is placed upon ground‐water supply management models, as opposed to models used for ground‐water quality management. The techniques that have been used in the optimization of ground‐water management include: linear programming, mixed‐integer and quadratic programming, differential dynamic programming, nonlinear programming, and simulation. The inverse problem of parameter identification pertains the optimal determination of model parameters using historical input and output observations. Because of data limitation in both quantity and quality, the inverse problem is inherently ill posed. This paper summarizes recent advances made in the inverse procedures and methods developed to alleviate the problems of instability ard nonuniqueness of the identified parameters. The optimal experimental design problem addresses the issue of data requirements and optimal sampling strategies for the purpose of parameter identification. A criterion must be established for the optimal design of a pumping test. The fundamental concept of optimal experimental design and various criteria used for optimization are reviewed.

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References

1.
Aquado, E., and Remson, I. (1974). “Groundwater hydraulics in aquifer management.” J. Hydr. Div., ASCE, 100(1), 103–118.
2.
Andricevic, R., and Kitanidis, P. K. (1990). “Optimization of pumping schedule in aquifer remediation under uncertainty.” Water Resour. Res., 26(5), 875–885.
3.
Carrera, J. (1988). “State of the art of the inverse problem applied to flow and solute transport equations.” Groundwater flow and quality modeling, E. Custodio, A. Gurgui, and J. P. Lobo Ferreira, eds., D. Reidel, Hingham, Mass., 549–583.
4.
Carrera, J., and Neuman, S. P. (1986a). “Estimation of aquifer parameters under transient and steady‐state conditions, 1, maximum likelihood method incorporating prior information.” Water Resour. Res., 22(2), 199–210.
5.
Carrera, J., and Neuman, S. P. (1986b). “Estimation of aquifer parameters under transient and steady‐state conditions, 3, application to synthetic and field data.” Water Resour. Res., 22(2), 228–242.
6.
Carrera, J., Usnoff, E., and Szidarovsky, F. (1984). “A method for optimal observation network design for groundwater management.” J. Hydrol, 73(1/2), 147–163.
7.
Casola, W. H., Narayanan, R., Duffy, C., and Bishop, A. B. (1986). “Optimal control model for groundwater management.” J. Water Res. Plng. and Mgmt., ASCE, 112(2), 183–197.
8.
Chu, W. S., Strecker, E. W., and Lettenmaier, D. P. (1987). “An evaluation of data requirements for groundwater contaminant transport modeling.” Water Resour. Res., 23(3), 408–424.
9.
Cleveland, T. G., and Yeh, W. W.‐G. (1991). “Optimal configuration and scheduling of groundwater tracer tests.” J. Water Resour. Plng. and Mgmt., ASCE, 117(1), 37–51.
10.
Cleveland, T. G., and Yeh, W. W.‐G. (1990). “Sampling network design for transport parameter identification.” J. Water Resour. Plng. and Mgmt., ASCE, 116(6), 764–783.
11.
Clifton, P. M., and Neuman, S. P. (1982). “Effects of Kriging and inverse modelingon conditional simulation of the Avra Valley aquifer in Southern Arizona.” Water Resour. Res., 18(4), 1215–1234.
12.
Dagan, G. (1985). “Stochastic modeling of groundwater flow by unconditional and conditional probabilities: The inverse problem.” Water Resour. Res., 21(1), 65–72.
13.
Dagan, G., and Rubin, Y. (1988). “Stochastic identification of recharge, transmissivity, and storativity in an aquifer transient flow: A quasi‐steady approach.” Water Resour. Res., 24(10), 1698–1710.
14.
Danskin, W. R., and Gorelick, S. M. (1985). “A policy evaluation tool: management of a multiaquifer system using controlled stream recharge.” Water Resour. Res., 21(11), 1731–1747.
15.
Deninger, R. A. (1970). “Systems analysis of water supply systems.” Water Resour. Bull., 6(4), 573–579.
16.
Gorelick, S. M. (1983). “A review of distributed parameter groundwater management modeling methods.” Water Resour. Res., 19(2), 305–319.
17.
Gorelick, S. M., and Remson, I. (1982). “Optimal dynamic management of groundwater pollutant resources.” Water Resour. Res., 18(1), 71–76.
18.
Gorelick, S. M., Remson, I., and Cottle, R. W. (1979). “Management model of a groundwater system with a transient pollutant source.” Water Resour. Res., 15(5), 1243–1249.
19.
Gorelick, S. M., Voss, C. I., Gill, P. E., Murray, M., Saunders, M. A., and Wright, M. M. (1984). “Aquifer reclamation design: the use of contaminant transport simulation combined with nonlinear programming.” Water Resour. Res., 20(4), 415–427.
20.
Hoeksema, R. J., and Kitanidis, P. K. (1984). “An application of the geostatistical approach to the inverse problem in two‐dimensional groundwater modeling.” Water Resour. Res., 20(7), 1003–1020.
21.
Hoeksema, R. J., and Kitanidis, P. K. (1985a). “Analysis of the spatial structure of properties of selected aquifers.” Water Resour. Res., 21(4), 563–572.
22.
Hoeksema, R. J., and Kitanidis, P. K. (1985b). “Comparison of Gaussian conditional mean and Kriging estimation in the geostatistical solution of the inverse problem.” Water Resour. Res., 21(6), 825–836.
23.
Hsu, N. S., and Yen, W. W.‐G. (1989). “Optimum experimental design for parameter identification in groundwater hydrology.” Water Resour. Res., 25(5), 1025–1040.
24.
Jones, L., Willis, R., and Yen, W. W.‐G. (1987). “Optimal control of nonlinear groundwater hydraulics using differential dynamic programming.” Water Resour. Res., 23(11), 2097–2106.
25.
Kitanidis, P. K., and Vomvoris, E. G. (1983). “A geostatistical approach to the inverse problem in groundwater modeling (steady state) ana one‐dimensional simulations.” Water Resour. Res., 19(3), 677–690.
26.
Knopman, D. S., and Voss, C. I. (1987). “Behavior of sensitivities in the one‐dimensional advection‐dispersion equation: implications for parameter estimation and optimal design.” Water Resour. Res., 23(2), 253–272.
27.
Knopman, D. S., and Voss, C. I. (1988). “Discrimination among one‐dimensional models of solute transport in porous media: implications for sampling design.” Water Resour. Res., 24(11), 1859–1876.
28.
Loaiciga, H. A. (1989). “An optimization approach for groundwater quality monitoring network design.” Water Resour. Res., 25(8), 1771–1782.
29.
Loaiciga, H. A., and Marino, M. A. (1987a). “Groundwater management and the inverse problem.” Stochastic Hydrol. and Hydr., 1(3), 161–168.
30.
Loaiciga, H. A., and Marino, M. A. (1987b). “Parameter estimation in groundwater: classical, Bayesian, and deterministic assumptions and their impact on management policies.” Water Resour. Res., 23(6), 1027–1035.
31.
Maddock, T. III. (1972). “Algebraic technological function from a simulation model.” Water Resour. Res., 8(1), 129–134.
32.
Makinde‐Obusola, B. A., and Marino, M. A. (1989). “Optimal control of groundwater by the feedback method of control.” Water Resour. Res., 25(6), 1341–1352.
33.
McCarthy, J. M., and Yeh, W. W.‐G. (1990). “Optimal pumping test design for parameter estimation and prediction in groundwater hydrology.” Water Resour. Res., 26(4), 779–791.
34.
Meyer, P. D., and Brill, E. D., Jr. (1988). “A method for locating wells in a groundwater monitoring network under conditions of uncertainty.” Water Resour. Res., 24(8), 1277–1282.
35.
Murtagh, B. A., and Saunders, M. A. (1982). “A projected Lagrangian algorithm and its implementation for sparse nonlinear constraints.” Mathematical programming study 16, North‐Holland Publishing Company, Amsterdam, The Netherlands.
36.
Neuman, S. P., and Yakowitz, S. (1979). “A statistical approach to the inverse problem of aquifer hydrology, 1, theory.” Water Resour. Res., 15(4), 845–860.
37.
Nishikawa, T., and Yeh, W. W.‐G. (1989). “Optimal pumping test design for the parameter identification of groundwater systems.” Water Resour. Res., 25(7), 1737–1747.
38.
Noel, J. E., and Howitt, R. E. (1982). “Conjunctive multibasin management: An optimal control approach.” Water Resour. Res., 18(4), 753–763.
39.
Rosenwald, G. W., and Green, D. W. (1974). “A method for determining the optimum location of wells in a reservoir using mixed‐integer programming.” Society of Petroleum Engrs. J., 14(1), 44–54.
40.
Rubin, Y., and Dagan, G. (1987a). “Stochastic identification of transmissivity and effective recharge in steady groundwater flow, 1, theory.” Water Resour. Res., 23(7), 1185–1192.
41.
Rubin, Y., and Dagan, G. (1987b). “Stochastic identification of transmissivity and effective recharge in steady groundwater flow, 2, case study,” Water Resour. Res., 14(6), 1035–1044.
42.
Shoemaker, C., Chang, L. C., Liao, L. Z., and Liu, P. (1989). “Supercomputers and optimal control of groundwater quality.” Proc. 16th Annual Conf. on Water Resour. Plng. and Mgmt., ASCE, May 21–25, 129–132.
43.
St. John, R. C., and Draper, N. R. (1975). “D‐optimality for regression designs: a review.” Technometrics, 17(1), 15–23.
44.
Steinberg, D. M., and Hunter, W. G. (1984). “Experimental design: review and comment.” Technometrics, 26(2), 71–91.
45.
Sun, N. Z., and Yeh, W. W.‐G. (1990). “Coupled inverse problems in groundwater modeling, 2, identifiability and experimental design.” Water Resour. Res., 26(10), 2527–2540.
46.
Tung, Y. K. (1986). “Groundwater management by chance‐constrained model.” J. Water Resour. Plng. and Mgmt., ASCE, 112(1), 1–19.
47.
Wagner, B. J., and Gorelick, S. M. (1987). “Optimal groundwater quality management under parameter uncertainty.” Water Resour. Res., 23(7), 1162–1174.
48.
Wanakule, N., Mays, L. W., and Lasdon, L. S. (1986). “Optimal management of large‐scale aquifers: methodology and applications.” Water Resour. Res., 22(4), 447–465.
49.
Willis, R. (1976). “Optimal groundwater quality management: well injection of waste water.” Water Resour. Res., 12(1), 47–53.
50.
Willis, R. (1979). “A planning model for the management of groundwater quality.” Water Resour. Res., 15(6), 1305–1312.
51.
Willis, R. (1984). “A unique approach to regional groundwater management.” Groundwater hydraulics, J. S. Rosenshein and G. D. Bennet, eds., American Geophysical Union, Washington, D.C.
52.
Willis, R., and Yeh, W. W.‐G. (1987). Groundwater systems planning and management. Prentice‐Hall, Englewood Cliffs, N.J.
53.
Yeh, W. W.‐G. (1986). “Review of parameter identification procedures in groundwater hydrology: the inverse problem.” Water Resour. Res., 22(2), 95–108.
54.
Yeh, W. W.‐G. (1987). “On the ill‐posedness of the inverse problem.” Proc. XXII Congress, Int. Assoc. for Hydr. Res., Topics in Hydr. Modeling, International Association for Hydraulic Research, Aug. 31–Sep. 4, 397–401.
55.
Yeh, W. W.‐G., and Sun, N. Z. (1984). “An extended identifiability in aquifer parameter identification and optimal pumping test design.” Water Resour. Res., 20(12), 1837–1847.
56.
Yeh, W. W.‐G., and Yoon, Y. S. (1981). “Aquifer parameter identification with optimal dimension in parameterization.” Water Resour. Res., 17(3), 664–672.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 118Issue 3May 1992
Pages: 224 - 237

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Published online: May 1, 1992
Published in print: May 1992

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William W.‐G. Yeh, Member, ASCE
Prof., Dept. of Civ. Engrg., Univ. of California, Los Angeles, CA 90024

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