Skip to main content
Journal cover image

Identification of hydraulic conductivity structure in sand and gravel aquifers: Cape Cod data set

Publication ,  Journal Article
Eggleston, JR; Rojstaczer, SA; Peirce, JJ
Published in: Water Resources Research
May 1, 1996

This study evaluates commonly used geostatistical methods to assess reproduction of hydraulic conductivity (K) structure and sensitivity under limiting amounts of data. Extensive conductivity measurements from the Cape Cod sand and gravel aquifer are used to evaluate two geostatistical estimation methods, conditional mean as an estimate and ordinary kriging, and two stochastic simulation methods, simulated annealing and sequential Gaussian simulation. Our results indicate that for relatively homogeneous sand and gravel aquifers such as the Cape Cod aquifer, neither estimation methods nor stochastic simulation methods give highly accurate point predictions of hydraulic conductivity despite the high density of collected data. Although the stochastic simulation methods yielded higher errors than the estimation methods, the stochastic simulation methods yielded better reproduction of the measured ln (K) distribution and better reproduction of local contrasts in ln (K). The inability of kriging to reproduce high ln (K) values, as reaffirmed by this study, provides a strong instigation for choosing stochastic simulation methods to generate conductivity fields when performing fine-scale contaminant transport modeling. Results also indicate that estimation error is relatively insensitive to the number of hydraulic conductivity measurements so long as more than a threshold number of data are used to condition the realizations. This threshold occurs for the Cape Cod site when there are approximately three conductivity measurements per integral volume. The lack of improvement with additional data suggests that although fine-scale hydraulic conductivity structure is evident in the variogram, it is not accurately reproduced by geostatistical estimation methods. If the Cape Cod aquifer spatial conductivity characteristics are indicative of other sand and gravel deposits, then the results on predictive error versus data collection obtained here have significant practical consequences for site characterization. Heavily sampled sand and gravel aquifers, such as Cape Cod and Borden, may have large amounts of redundant data, while in more common real world settings, our results suggest that denser data collection will likely improve understanding of permeability structure.

Duke Scholars

Published In

Water Resources Research

DOI

ISSN

0043-1397

Publication Date

May 1, 1996

Volume

32

Issue

5

Start / End Page

1209 / 1222

Related Subject Headings

  • Environmental Engineering
  • 4011 Environmental engineering
  • 4005 Civil engineering
  • 3707 Hydrology
  • 0907 Environmental Engineering
  • 0905 Civil Engineering
  • 0406 Physical Geography and Environmental Geoscience
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Eggleston, J. R., Rojstaczer, S. A., & Peirce, J. J. (1996). Identification of hydraulic conductivity structure in sand and gravel aquifers: Cape Cod data set. Water Resources Research, 32(5), 1209–1222. https://doi.org/10.1029/96WR00272
Eggleston, J. R., S. A. Rojstaczer, and J. J. Peirce. “Identification of hydraulic conductivity structure in sand and gravel aquifers: Cape Cod data set.” Water Resources Research 32, no. 5 (May 1, 1996): 1209–22. https://doi.org/10.1029/96WR00272.
Eggleston JR, Rojstaczer SA, Peirce JJ. Identification of hydraulic conductivity structure in sand and gravel aquifers: Cape Cod data set. Water Resources Research. 1996 May 1;32(5):1209–22.
Eggleston, J. R., et al. “Identification of hydraulic conductivity structure in sand and gravel aquifers: Cape Cod data set.” Water Resources Research, vol. 32, no. 5, May 1996, pp. 1209–22. Scopus, doi:10.1029/96WR00272.
Eggleston JR, Rojstaczer SA, Peirce JJ. Identification of hydraulic conductivity structure in sand and gravel aquifers: Cape Cod data set. Water Resources Research. 1996 May 1;32(5):1209–1222.
Journal cover image

Published In

Water Resources Research

DOI

ISSN

0043-1397

Publication Date

May 1, 1996

Volume

32

Issue

5

Start / End Page

1209 / 1222

Related Subject Headings

  • Environmental Engineering
  • 4011 Environmental engineering
  • 4005 Civil engineering
  • 3707 Hydrology
  • 0907 Environmental Engineering
  • 0905 Civil Engineering
  • 0406 Physical Geography and Environmental Geoscience