Prediction of hydraulic conductivity of porous media using a statistical grain-size model. Issue 4 (4th February 2022)
- Record Type:
- Journal Article
- Title:
- Prediction of hydraulic conductivity of porous media using a statistical grain-size model. Issue 4 (4th February 2022)
- Main Title:
- Prediction of hydraulic conductivity of porous media using a statistical grain-size model
- Authors:
- Chandel, Abhishish
Sharma, Shivali
Shankar, Vijay - Abstract:
- Abstract: Hydraulic conductivity (K) estimation of porous media is of great significance in contaminant movement and groundwater investigations. The present study examines the influence of effective grain size (d10 ) and standard deviation ( σ ) on the K value of borehole soil samples using 5.08, 10.16, and 15.24 cm diameter permeameters. A statistical grain size model was developed and the feasibility of seven empirical equations was evaluated with the measured K values. The K of soil samples increases with the increase in the d10 grain size and decreases with the increase in the σ value. Evaluation of K using empirical equations establishes that the Hazen equation shows relatively good agreement with the measured K values. The study substantiates the efficacy of the developed model as the Kmodel and Kmeasured based R 2 (determination coefficient), MAE (mean absolute error), and RMSE (root mean square error) values are (0.982, 0.007, and 0.008), (0.972, 0.005, and 0.007), (0.953, 0.004, and 0.005) for 5.08, 10.16, and 15.24 cm diameter permeameters respectively. The developed model was validated by assessing its efficiency in the prediction of K values for independent soil samples. The developed model-based K accedes to the precise computation of the aquifer yield and groundwater recharge. HIGHLIGHTS: The study proposes a statistical grain size model for the computation of hydraulic conductivity of porous media by investigating the influence of the σ/d10 parameter onAbstract: Hydraulic conductivity (K) estimation of porous media is of great significance in contaminant movement and groundwater investigations. The present study examines the influence of effective grain size (d10 ) and standard deviation ( σ ) on the K value of borehole soil samples using 5.08, 10.16, and 15.24 cm diameter permeameters. A statistical grain size model was developed and the feasibility of seven empirical equations was evaluated with the measured K values. The K of soil samples increases with the increase in the d10 grain size and decreases with the increase in the σ value. Evaluation of K using empirical equations establishes that the Hazen equation shows relatively good agreement with the measured K values. The study substantiates the efficacy of the developed model as the Kmodel and Kmeasured based R 2 (determination coefficient), MAE (mean absolute error), and RMSE (root mean square error) values are (0.982, 0.007, and 0.008), (0.972, 0.005, and 0.007), (0.953, 0.004, and 0.005) for 5.08, 10.16, and 15.24 cm diameter permeameters respectively. The developed model was validated by assessing its efficiency in the prediction of K values for independent soil samples. The developed model-based K accedes to the precise computation of the aquifer yield and groundwater recharge. HIGHLIGHTS: The study proposes a statistical grain size model for the computation of hydraulic conductivity of porous media by investigating the influence of the σ/d10 parameter on hydraulic conductivity. The developed hydraulic conductivity model provides an efficient tool to compute the aquifer yield, groundwater recharge, and filter design with precise accuracy. Graphical Abstract … (more)
- Is Part Of:
- Water Supply. Volume 22:Issue 4(2022)
- Journal:
- Water Supply
- Issue:
- Volume 22:Issue 4(2022)
- Issue Display:
- Volume 22, Issue 4 (2022)
- Year:
- 2022
- Volume:
- 22
- Issue:
- 4
- Issue Sort Value:
- 2022-0022-0004-0000
- Page Start:
- 4176
- Page End:
- 4192
- Publication Date:
- 2022-02-04
- Subjects:
- effective grain size -- hydraulic conductivity -- porosity -- porous media
- DOI:
- 10.2166/ws.2022.043 ↗
- Languages:
- English
- ISSNs:
- 1606-9749
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 24560.xml