Measurement scale, network sampling scale, and groundwater model parameters

Water Resources Research

Volumn 32, Issue 1, 1996, Pages 65-76

  Beckie, Roger ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

FIELD TESTS; GROUNDWATER; MODELS; NETWORKS; SAMPLING; SCALE EFFECTS;

GROUNDWATER; GROUNDWATER MODEL; PARAMETERIZATION; SAMPLING; SCALE EFFECT;

EID: 0029656431     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/95WR02921     Document Type: Article

References (44)

1. Ababou, R., and L. W. Gelhar, Self-similar randomness and spectral conditioning: Analysis of scale effects in subsurface hydrology, in Dynamics of Fluids in Hierarchical Porous Media, edited by J. H. Cushman, chap. 14, pp. 393-428, Academic, San Diego, Calif., 1990.
2. Baveye, P., and G. Sposito, The operational significance of the continuum hypothesis in the theory of water movement through soils and aquifers, Water Resour. Res., 20(5), 521-530, 1984.
3. Beckie, R., and B. Wang, A numerical method to characterize the averaging process invoked by a slug test, in Computational Methods in Water Resources X, edited by A. Peters et al., pp. 703-710, Kluwer Academic, Norwell, Mass., 1994.
4. Beckie, R., A. A. Aldama, and E. F. Wood, The universal structure of the groundwater flow equations, Water Resour. Res., 30(5), 1407-1419, 1994.
5. Bracewell, R., The Fourier Transform and Its Applications, McGraw-Hill, New York, 1965.
6. Brown, J. L., On the error in reconstructing a non-bandlimited function by means of the bandpass sampling theorem, J. Math. Anal. Appl., 18, 75-84, 1967.
7. Carr, J. R., Application of spatial filter theory to kriging, Math. Geol., 22(8), 1063-1079, 1990.
8. Chirlin, G. R., and E. F. Wood, On the relationship between kriging and state estimation, Water Resour. Res., 18(2), 432-438, 1982.
9. Cooper, H. H., Jr., J. D. Bredehoeft, and I. S. Papadopoulos, Response of a finite-diameter well to an instantaneous charge of water, Water Resour. Res., 3(1), 263-269, 1967.
10. Cushman, J. H., On unifying the concepts of scale, instrumentation, and stochastics in the development of multiphase transport theory, Water Resour. Res., 20(11), 1668-1676, 1984.
11. Cushman, J. H., On measurement, scale, and scaling. Water Resour. Res., 22(2), 129-134, 1986.
12. Davis, J. M., R. C. Lohmann, F. M. Phillips, J. L. Wilson, and D. W. Love, Architecture of the Sierra Ladrones formation, central New Mexico: Depositional controls on the permeability correlation structure, Geol. Soc. Am. Bull., 105, 998-1007, 1993.
13. Delhomme, J. P., Kriging in the hydrosciences, Adv. Water Resour., 1(1), 251-266, 1978.
14. Delhomme, J. P., Spatial variability and uncertainty in groundwater flow parameters: A geostatistical approach, Water Resour. Res., 15(2), 269-280, 1979.
15. Desbarats, A. J., Spatial averaging of hydraulic conductivity under radial flow conditions, Math. Geol., 26(1), 1-21, 1994.
16. Emsellem, Y., and G. de Marsily, An automatic solution for the inverse problem, Water Resour. Res., 7(5), 1264-1283, 1971.
17. Freeze, R. A., Stochastic-conceptual analysis of one-dimensional groundwater flow in nonuniform homogeneous media, Water Resour. Res., 11(5), 725-741, 1975.
18. Gardner, W. A., Statistical Spectral Analysis: A Nonprobabilistic Theory, Prentice-Hall, Englewood Cliffs, N. J., 1988.
19. Ginn, T. R., and J. H. Cushman, Inverse methods for subsurface flow: A critical review of stochastic techniques, J. Stoch. Hydrol. Hydraul., 4, 1-26, 1990.
20. Indelman, P., and G. Dagan, Upscaling of permeability of anisotropic heterogeneous formations, 1, The general framework, Water Resour. Res., 29(4), 917-924, 1993.
21. Jerri, A. J., Error analysis in application of generalizations of the sampling theorem, in Advanced Topics in Shannon Sampling and Interpolation Theory, edited by R. J. Marks, chap. 7, pp. 219-298, Springer-Verlag, New York, 1993.
22. Journel, A. G., Geostatistics: Models and tools for the Earth sciences, Math. Geol., 18(1), 119-140, 1986.
23. Journel, A. G., and C. J. Huijbregts, Mining Geostatistics, Academic, San Diego, Calif., 1978.
24. Kimeldorf, G., and G. Wahba, A correspondence between Bayesian estimation on stochastic processes and smoothing by splines, Ann. Math. Stat., 41, 495-502, 1970.
25. Kitanidis, P. K., Parameter uncertainty in estimation of spatial functions: Bayesian analysis, Water Resour. Res., 22(4), 499-507, 1986.
26. Marks, R. J., Introduction to Shannon Sampling and Interpolation Theory, Springer-Verlag, New York, 1991.
27. Masry, E., Alias-free sampling: An alternative conceptualization and its applications, IEEE Trans. Inf. Theory, IT-24(3), 317-324, 1978.
28. McLaughlin, D. B., and E. F. Wood, A distributed parameter approach for evaluating the accuracy of groundwater model predictions, 1, Theory, Water Resour. Res., 24(1), 1037-1047, 1988.
29. Mohanty, B. P., M. D. Ankeny, R. Horton, and R. S. Kanwar, Spatial analysis of hydraulic conductivity measured using disc infiltrometers, Water Resour. Res., 30(9), 2489-2498, 1994.
30. Olea, R. A., Sampling design optimization for spatial functions, Math. Geol., 16(4), 369-392, 1984.
31. Oliver, D. S., The averaging process in permeability estimation from well-test data, SPE Form. Eval., 5, 319-324, 1990.
32. Phillips, F. M., and J. L. Wilson, An approach to estimating hydraulic conductivity spatial correlation scales using geological characteristics, Water Resour. Res., 25(1), 141-143, 1989.
33. Rajaram, H., and D. B. McLaughlin, Identification of large-scale spatial trends in hydrologie data, Water Resour. Res., 26(10), 2411-2424, 1990.
34. Rubin, Y., and J. J. Gómez-Hernández, A stochastic approach to the problem of upscaling of conductivity in disordered media: Theory and unconditional numerical simulations, Water Resour. Res., 26(4), 691-702, 1990.
35. Russo, D., and W. A. Jury, A theoretical study of the estimation of the correlation scale in spatially variable fields, 2, Nonstationary fields, Water Resour. Res., 23(7), 1269-1279, 1987a.
36. Russo, D., and W. A. Jury, A theoretical study of the estimation of the correlation scale in spatially variable fields, 1, Stationary fields, Water Resour. Res., 23(7), 1257-1268, 1987b.
37. Rybicki, G. B., and W. H. Press, Interpolation, realization, and reconstruction of noisy, irregularly sampled data, Astrophys. J., 398, 169-176, 1992.
38. Schweppe, F. C., Uncertain Dynamic Systems, Prentice-Hall, Englewood Cliffs, N. J., 1973.
39. Silverman, B. W., Spline smoothing: The equivalent variable kernel method, Ann. Stat., 12(3), 898-916, 1984.
40. Smith, L., and R. A. Freeze, Stochastic analysis of steady state groundwater flow in a bounded domain, 2, Two-dimensional simulations, Warer Resour. Res., 15(6), 1543-1559, 1979.
41. Wahba, G., Smoothing noisy data with spline functions, Numer. Math., 24, 383-393, 1975.
42. Watson, G. S., Smoothing and interpolation by kriging and with splines, Math. Geol., 16, 601-615, 1984.
43. 1 parameter estimator for model fitting in groundwater flow and solute transport simulation, Water Resour. Res., 29(6), 1661-1674, 1993.
44. Yeh, W. W.-G., Review of parameter identification procedures in groundwater hydrology: The inverse problem, Water Resour. Res., 22(2), 95-108, 1986.