Latin hypercube lattice sample selection strategy for correlated random hydraulic conductivity fields

Water Resources Research

Volumn 39, Issue 8, 2003, Pages

  Zhang, Yingqi ^a   Pinder, George ^a  

^a University of Vermont   (United States)

Author keywords

Groundwater; Latin hypercube; Permeability; Random fields

Indexed keywords

COMPUTATIONAL METHODS; CORRELATION METHODS; GROUNDWATER FLOW; HYDRAULIC CONDUCTIVITY; PROBABILITY; SAMPLING;

HYPERCUBE SAMPLING; LATTICE SAMPLING;

GROUNDWATER RESOURCES;

FLOW MODELING; GROUNDWATER; HYDRAULIC CONDUCTIVITY; PERMEABILITY; POLLUTANT TRANSPORT; SAMPLING;

EID: 1542546939     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2002WR001822     Document Type: Article

References (24)

1. Alabert, F., The practice of fast conditional simulations through the LU decomposition of the covariance matrix, Math. Geol., 19, 369-386, 1987.
2. Chilès, J. P., Geostatique des phenomenes non stationaires, these de docteur-ingenier, Univ. de Nancy, Nancy, France, 1977.
3. Clifton, P. M., and S. P. Neuman, Effects of kriging and inverse modeling on conditional simulation of the Avra Valley aquifer in southern Arizona, Water Resour. Res., 18, 1215-1234, 1982.
4. Davis, D., Production of conditional simulations via the LU triangular decomposition of the covariance matrix, Math. Geol., 19, 91-98, 1987.
5. Delhomme, J. P., Spatial variability and uncertainty in groundwater flow parameters: A geostatistical approach, Water Resour. Res., 15, 269-280, 1979.
6. Deutsch, C. V., and A. G. Journel, GSLIB: Geostatistical Software Library and User's Guide, Oxford Univ. Press, New York, 1998.
7. Elishakoff, L., Probability Methods in the Theory of Structures, John Wiley, Hoboken, N. J., 1983.
8. Hotchkiss, W. R., Selecting optimum data sites using geostatistics, Latin hypercube sampling, and ground-water modeling, Ph.D. dissertation, Colo. State Univ., Fort Collins, 1988.
9. Iman, R. L., and W. J. Conover, A distribution-free approach to inducing rank correlation among input variables, Commun. Stat., 11, 311-334, 1982.
10. Iman, R. L., and J. M. Davenport, An iterative algorithm to produce a positive definite correlation matrix from an approximate correlation matrix, SAND81-1376, Sandia Natl. Lab., Albuquerque, N. M., 1982.
11. Journel, A. G., and C. J. Huijbregts, Mining Geostatistics, Academic, San Diego, Calif., 1978.
12. Lahkim, M. B., L. A. Garcia, and J. R. Nuckols, Stochastic modeling of exposure and risk in a contaminated heterogeneous aquifer. 2: Application of Latin hypercube sampling, Environ. Eng. Sci., 16, 329-343, 1999.
13. Mantoglou, A., Digital simulation of multivariate two-and three-dimensional stochastic processes with a spectral turning bands method, Math. Geol., 19, 129-149, 1987.
14. Mantoglou, A., and J. L. Wilson, Simulation of random fields with the turning bands method, Tech. Rep. 264, Dep. of Civ. Eng., Mass. Inst. of Technol., Cambridge, 1981.
15. Mantoglou, A., and J. L. Wilson, The turning bands method for simulation of random fields using line generation by a spectral method, Water Resour. Res., 18, 1379-1394, 1982.
16. Matheron, G., The intrinsic random functions and their applications, Adv. Appl. Prob., 5, 439-468, 1973.
17. McKay, M. D., W. J. Conover, and R. J. Beckman, A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, 21, 239-245, 1979.
18. Owen, A. B., A central limit theorem for Latin hypercube sampling, J. R. Stat. Soc., Ser. B, 54, 541-551, 1992.
19. Owen, A. B., Controlling correlations in Latin hypercube samples, J. Am. Stat. Assoc., 89, 1517-1522, 1994.
20. Patterson, H. D., The errors of lattice sampling, J. R. Stat. Soc., Ser. B, 16, 140-149, 1954.
21. Pebesma, E., and B. M. Heuvelink, Latin hypercube sampling of Gaussian random fields, Technometrics, 41, 303-312, 1999.
22. Stein, M., Large sample properties of simulations using Latin hypercube sampling, Technometrics, 29, 143-152, 1987.
23. Tompson, A. F. B., R. Ababou, and L. W. Gelhar, Implementation of the three-dimensional turning bands random field generator, Water Resour. Res., 25, 2227-2243, 1989.
24. Zhang, D., Stochastic Methods for Flow in Porous Media Coping With Uncertainty, Academic, San Diego, Calif., 2002.