A hybrid optimization approach to the estimation of distributed parameters in two-dimensional confined aquifers

Journal of the American Water Resources Association

Volumn 34, Issue 4, 1998, Pages 909-920

  Heidari, Manoutchehr ^a   Ranjithan, S Ranji ^b  

^a ILLINOIS STATE GEOLOGICAL SURVEY   (United States)

^b North Carolina State University   (United States)

Author keywords

Automatic differentiation; Calibration; Confined aquifer; Genetic algorithm; Maximum likelihood; Optimization; Sensitivity analysis; Truncated Newton Method

Indexed keywords

ENVIRONMENTAL MONITORING; MODEL;

AQUIFERS; DIFFERENTIATION (CALCULUS); GENETIC ALGORITHMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMIZATION; PARAMETER ESTIMATION; SENSITIVITY ANALYSIS;

TRUNCATED-NEWTON METHOD;

GROUNDWATER FLOW;

AQUIFER; GROUNDWATER; MODELING; PARAMETERIZATION; PHREATIC ZONE;

EID: 0032143681     PISSN: 1093474X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1752-1688.1998.tb01525.x     Document Type: Article

References (34)

1. Bischof, C., A. Carle, G. Coreliss, A. Griewank, and P. Hovland, 1992. ADIFOR-Generating Derivative Codes From FORTRAN Programs. Scientific Programming 1(1):1-29.
2. Carrera, J., 1984. Estimation of Aquifer Parameters Under Transient and Steady-State Conditions. Ph.D. Thesis, University of Arizona, 258 pp.
3. Carrera, J. and S. P. Neuman, 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.
4. Carrera, J. and S. P. Neuman, 1986b. Estimation of Aquifer Parameters Under Transient and Steady State Conditions: 2. Uniqueness, Stability, and Solution Algorithms. Water Resour. Res. 22(2):211-227.
5. Carrera, J. and S. P. Neuman, 1986c. 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. Carter, R. D., L. F. Kemp, Jr., A. C. Pearce, and D. L. Williams, 1974. Performance Matching With Constraints. Soc. Pet. Eng. J. 14(2):187-196.
7. Cieniawski, S., J. W. Eheart, and S. Ranjithan, 1995. Using Genetic Algorithms to Solve a Multi-Objective Groundwater Monitoring Problem. Water Resoures Research 31(2):399-410.
8. Cooley, R. L., 1982. Incorporation of Prior Information on Parameters Into Nonlinear Regression Groundwater Flow Models: 1. Theory. Water Resour. Res. 18(4):965-976.
9. Cooley, R. L., 1983. Incorporation of Prior Information on Parameters Into Nonlinear Regression Groundwater Flow Models: 2. Application. Water Resour. Res. 19(3):662-676.
10. Dettinger, M. D. and J. L. Wilson, 1981. First-Order Analysis of Uncertainty in Numerical Models of Groundwater Flow: 1. Mathematical Development. Water Resour. Res. 17(1):149-161.
11. Gill, P. E. and W. Murray, 1979. Conjugate-Gradient Methods for Large-Scale Nonlinear Optimization. Report SOL 79-15, Operations Research Dept., Stanford Univ., Stanford, California.
12. Gill, P. E., W. Murray, and M. H. Wright, 1981. Practical Optimization. Academic Press, New York, New York, 401 pp.
13. Goldberg, D. E., 1989. Genetic Algorithm in Search Optimization and Machine Learning. Addison-Westly, Reading, Massachusetts, 412 pp.
14. Haimes, U. U., R. L. Perrine, and D. A. Wisemer, 1968. Identification of Aquifer Parameters by Decomposition and Multilevel Optimization. U.C.L.A., Water Resources Center, Report 67-63, 53 pp.
15. Heidari, M., 1992. Estimation of Parameters for Local and Regional Aquifer Systems. Proceedings of 85th Annual Meeting and Exhibition of Air and Water Management Association, Paper No. 92.4-11, Kansas City, Missouri.
16. Hillstrom, K. E., 1982. JAKEF - A Portable Symbolic Differentiator of Functions Given by Algorithms. Technical Report ANL-82-48, Mathematics and Computer Science Division, Argonne National Laboratories, Argonne, Illinois.
17. Himmelblau, D. M., 1972. Applied Nonlinear Programming. McGraw-Hill, 498 pp.
18. Holland, J. H., 1975. Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, Michigan, 1983 pp.
19. Istok, J., 1989. Groundwater Modeling by the Finite Element Method. American Geophysical Union, Water Resour. Monograph 13, 495 pp.
20. Jacquard, P. and C. Jain, 1965. Permeability Distribution From Field Pressure Data. Soc. Pet. Eng. J. 5:281-294.
21. Jahns, Hans O., 1966. A Rapid Method for Obtaining a Two-Dimensional Reservoir Description From Field Pressure Data. Soc. Pet. Eng. J. 6:315-327.
22. Judge, G. G., R. C. Hill, W. E. Griffith, H. Lutkepohl, and T. C. Lee, 1988. Introduction to the Theory and Practice of Econometrics (Second Edition). Wiley, 570 pp.
23. Juedes, D., 1991. A Taxonomy of Automatic Differentiation Tools, In: Automatic Differentiation of Algorithms: Theory, Implementation, and Application, Andreas Griewank and George F. Corliss (Editors). SIAM, Philadelphia, Pennsylvania, pp. 315-329.
24. Knowles, T. R., B. J. Claborn, and D. M. Wells, 1972. A Computerized Procedure to Determine Aquifer Characteristics. Texas Tech. University Water Resources Center, 72(5):103.
25. McKinney, D. C. and M. Lin, 1989. Genetic Algorithm in Groundwater Flow Optimization. EOS, Transaction of American Geophysical Union, pp. 73-43.
26. Nash, S. G. and J. Nocedal, 1991. A Numerical Study of the Limited Memory BFGS Method and the Truncated-Newton for Large Scale Optimization. SIAM J. Optimization 1(3):358-372.
27. Nash, S. G., 1985. Preconditioning of Truncated-Newton Methods. SIAM Journal of Sci. Stat. and Computation 6(3):599-616.
28. Neuman, S. P., 1973. Calibration of Distributed Parameter Groundwater Flow Models Viewed as a Multiple-Objective Decision Process Under Uncertainty. Water Resour. Res. 9(4):1006-1021.
29. Ranjithan, S., J. W. Eheart, and J. C. Liebman, 1992. Incorporating Fixed-Cost Component of Pumping Into Stochastic Groundwater Management: A Genetic Algorithm-Based Optimization Approach. EOS, Transaction of the American Geophysical Union 73(14).
30. Ritzel, B. J., J. W. Eheart, and S. Ranjithan, 1994. Using Genetic Algorithms to Solve Multiple Objective Groundwater Pollution Containment Problem. Water Resoures Research 30(5):1589-1603.
31. Saleem, Z. A., 1970. A Computer Method for Pumping Test Analysis. Groundwater 8(5):21-24.
32. Sun, Ne-Zheng, 1994. Inverse Problems in Groundwater Modeling. Kulwer Academic Publication, 337 pp.
33. Wang, Q. J., 1991. The Genetic Algorithm and Its Application to Calibrating Conceptual Rainfall-Runoff Models. Water Resour. Res. 27(9):2467-2471.
34. Yeh, William W-G, 1986. Review of Parameter Identification Procedures in Groundwater Hydrology: The Inverse Problem. Water Resour. Res. 22(2):95-108.