Using microscope observations of thin sections to estimate soil permeability with the Kozeny-Carman equation

Citation
Mg. Schaap et I. Lebron, Using microscope observations of thin sections to estimate soil permeability with the Kozeny-Carman equation, J HYDROL, 251(3-4), 2001, pp. 186-201
Citations number
34
Categorie Soggetti
Environment/Ecology,"Civil Engineering
Journal title
JOURNAL OF HYDROLOGY
ISSN journal
00221694 → ACNP
Volume
251
Issue
3-4
Year of publication
2001
Pages
186 - 201
Database
ISI
SICI code
0022-1694(20011001)251:3-4<186:UMOOTS>2.0.ZU;2-K
Abstract
In this study we used the Kozeny-Carman (K-C) equation as a semi-physical m odel for estimating the soil permeability using data derived from microscop e observations. Specific surface areas and porosities were obtained from tw o-point correlation functions derived from scanning electron microscope ima ges of thin sections using a magnification of 50 and a resolution of 1.88 m um pixel(-1). Permeabilities were predicted using two published ('Ahuja' an d 'Berryman') and one generalized variant of the K-C equation. The latter m odel was similar to the Berryman variant, but used a free parameter C rathe r than a porosity dependent formation factor. All K-C model variants were o ptimized on measured permeabilities. The Ahuja and Berryman KC models perfo rmed relatively poorly with R-2 values of 0.36 and 0.57. respectively, whil e the generalized model attained R-2 values of 0.91. The parameter C was st rongly related to texture and, to a lesser extent, particle density. The ge neral model still required measured surface area and porosity. However, we showed that it was possible to estimate these parameters from texture resul ting in an R-2 of 0.87. A fully empirical model that did not assume K-C con cepts performed slightly worse (R-2 = 0.84). The results indicate that afte r developing the model using microscope information, only macroscopic data are necessary to predict permeability of soils in a semi-physical manner wi th the K-C equation. (C) 2001 Elsevier Science BN. All rights reserved.