Determining hydraulic conductivity and porosity sensitivity of grain-size analysis methods using laboratory and small-scale model measurements

Abstract Hydraulic conductivity (K) is essential for determining seepage flow in porous media. In this study, a small-scale model (SSM) was tested using coarse sand (CS) and medium sand (MS) samples, designed according to the similarity model law. In the SSM, pumping tests were carried out in laboratory conditions to estimate K . This technique combines the advantages of field and laboratory measurements. The results of SSM measurements were validated by a constant head permeameter. Employing the validated SSM-based K values, 31 grain-size analysis methods (GSAMs) were compared and evaluated. For both soil samples, the US Bureau of Reclamation (USBR) method provided the best results. Sensitivity analysis for porosity was performed on 17 GSAMs using four theoretical and two laboratory methods. It was concluded that laboratory-based porosity measurements are recommended to obtain more accurate K values. Of the theoretical methods, Wooster gave the smallest relative difference for CS, whereas the Wu and Wang method performed best for MS. Considering the GSAMs, the Arshad, Carrier, Chapuis, Chapuis and Aubertin, Fair and Hatch, Kozeny-Carman, Mbonimpa, Pavchich, Sauerbrei, and Shahabi methods were found to be very sensitive to porosity, while the Kasenow and Koenders, and Williams methods are the least sensitive. For five GSAMs, the possibility arises that an added constant can be used to improve the calculated K values which was demonstrated in this study through a recommendation for the Kasenow constant.

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Publication Details

Journal
Hydrogeology Journal
Published
2026-07-28
DOI
https://doi.org/10.1007/s10040-026-03131-1
Primary Topic
Groundwater flow and contamination studies
Type
article
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article

Determining hydraulic conductivity and porosity sensitivity of grain-size analysis methods using laboratory and small-scale model measurements

Péter Torma, Daniel F. Farkas, Fanni Gazda
Hydrogeology Journal
Groundwater flow and contamination studies
article

Determining hydraulic conductivity and porosity sensitivity of grain-size analysis methods using laboratory and small-scale model measurements

Péter Torma, Daniel F. Farkas, Fanni Gazda
article en

Abstract

Abstract Hydraulic conductivity (K) is essential for determining seepage flow in porous media. In this study, a small-scale model (SSM) was tested using coarse sand (CS) and medium sand (MS) samples, designed according to the similarity model law. In the SSM, pumping tests were carried out in laboratory conditions to estimate K . This technique combines the advantages of field and laboratory measurements. The results of SSM measurements were validated by a constant head permeameter. Employing the validated SSM-based K values, 31 grain-size analysis methods (GSAMs) were compared and evaluated. For both soil samples, the US Bureau of Reclamation (USBR) method provided the best results. Sensitivity analysis for porosity was performed on 17 GSAMs using four theoretical and two laboratory methods. It was concluded that laboratory-based porosity measurements are recommended to obtain more accurate K values. Of the theoretical methods, Wooster gave the smallest relative difference for CS, whereas the Wu and Wang method performed best for MS. Considering the GSAMs, the Arshad, Carrier, Chapuis, Chapuis and Aubertin, Fair and Hatch, Kozeny-Carman, Mbonimpa, Pavchich, Sauerbrei, and Shahabi methods were found to be very sensitive to porosity, while the Kasenow and Koenders, and Williams methods are the least sensitive. For five GSAMs, the possibility arises that an added constant can be used to improve the calculated K values which was demonstrated in this study through a recommendation for the Kasenow constant.

Hydrogeology Journal
University of Szeged (HU), Budapest University of Technology and Economics (HU), MTA-SZTE Research Group on Artificial Intelligence (HU), Water Resources Research Centre (HU)
Life in Land
Openalex Percentile: Top 14%
Groundwater flow and contamination studies
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