• Economic and Environmental Geology
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• v.46 no.3
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• pp.215-220
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• 2013

We estimated the hydraulic conductivity of the sediments using constant-head permeability tests and electrical resistivity measurements with Jumoonjin standard sand of a uniform size and glass beads of different grain sizes. In this study, we determined the variations of the porosity, the hydraulic conductivity, and the resistivity in case 1 (changing the packing of the Jumoonjin standard sand) and in case 2 (varying the size of the glass beads). The results of case 1 showed that the hydraulic conductivity decreased with an increase in the electrical resistivity. This occurred because the sand grain while packing became rhombohedral with the a decrease of both the pore size and porosity. The results of the case 2 showed that the hydraulic conductivity increased due to the increase in the pore size as caused by the increased glass bead size. In addition, the porosity decreased and the electrical resistivity increased. Therefore, the relationship between the hydraulic conductivity and the electrical resistivity is negatively proportional as regards the grain packing with a change from cubic to rhombohedral whereas this relationship is positively proportional to the increase in the grain size.

• Journal of the Korean Geotechnical Society
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• v.39 no.2
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• pp.31-42
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• 2023

A study was conducted to use soil color obtained from digital im ages as an indicator of soil water content. Digital images of Jumoonjin standard sand with five different water contents were captured under nine different lighting conditions. Through digital image processing, the soil color of the sample was obtained based on the CIELAB color system, and the effect of lighting conditions and water content on the soil color was analyzed. The results indicated that L^* showed a high correlation with illuminance, whereas a^* and b^* showed a high correlation with color temperature. As the water content increased, L^*, which represents the brightness of the soil color, decreased, and a^* and b^* increased. Therefore, the soil color changed from green and blue to red and yellow. Based on the regression analysis results of lighting conditions, water content, and soil color, a water content predicting method based on the soil color of silica-based sand photographed under irregular light conditions was proposed. The proposed method can predict the water content with a m axim um error of 0.29%.