2014 GSA Annual Meeting in Vancouver, British Columbia (19–22 October 2014)

Paper No. 156-9
Presentation Time: 3:15 PM

ESTIMATING HYDRAULIC CONDUCTIVITY USING GRAIN SIZE DISTRIBUTION IN AN ALLUVIAL SYSTEM IN MATLAB, BANGLADESH


ALAM, Md. Samrat, Earth & Atmospheric Sciences, University of Alberta, 1-26 Earth Sciences Building, University of Alberta, Edmonton, AB T6G 2E3, Canada, AHMED, Kazi Matin, Department of Geology, University of Dhaka, Dhaka, 1000, Bangladesh, HASAN, M. Aziz, Department of Geology, University of Dhaka, Bangladesh, Dhaka-1000, Bangladesh and HOSSAIN, Mohammed, KTH-International Groundwater Arsenic Research Group, Dept of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Teknikringen 76, Stockholm, SE-10044, Sweden, mdsamrat@ualberta.ca

In many areas of geologic and geotechnical investigation and management, it’s very important to have the ability to predict the hydraulic conductivity (K) of porous media, such as unconsolidated sediments. Estimation of hydraulic conductivity is not only important to address geotechnical problems, but also for the development, management, and protection of groundwater resources. The relation between hydraulic conductivity and the grain-size distribution of granular porous media has long been recognized. Predicting hydraulic conductivity using grain size distribution could be an economical and alternative method to pumping test. In this study, our goal was to estimate the hydraulic conductivity using grain size distribution and to investigate how effective the results in compare to pumping test results.

Several empirical equations to calculate hydraulic conductivity using grain size distribution of unconsolidated aquifer materials from Matlab, Bangladesh, have been evaluated in this study. About 60 sediment samples of different depth from 10 test wells were analyzed (i.e. grain size) to estimate the hydraulic conductivity Based on grading analyses of soil samples extracted from test holes during groundwater investigations and particle size distribution characteristics, hydraulic conductivities were computed. Results showed that all seven empirical formulae used reliably estimated hydraulic conductivities of the various soil samples within known ranges. The Kozeny-Carman formula proved to be the best estimator of most samples analyzed. By using the USRB and Kozeny-Carman formulae from grain size analysis, it is shown that in shallow aquifers (50-60m), hydraulic conductivities are 55-190 m/day and 20-200 m/day, respectively, which are similar to the historical pumping test data (18 -181.44m/day) of the same region.

From the comparison of grain size analysis and pumping test result, it is evident that grain size analysis can be an effective method to estimate hydraulic conductivity.