Prediction model of hydraulic conductivity for sedimentary residual soil mixed bentonite as compacted clay liner

Abstract

Abstract This paper describes a development of regression model on predicting the hydraulic conductivity value for sedimentary residual soil mixed bentonite. The data for required parameter for model development was based on the laboratories testing such as compaction testing and hydraulic conductivity testing. The multiple linear regression model (MLR) was selected to develop a hydraulic conductivity model (k-model). The empirical model was developed based on the 45 datasets from experimental studies encompassing range of maximum dry density (MDD), optimum moisture content (OMC), effective stress and bentonite content. The model developed in this study has met the conditions and has been verified according to the statistical validity requirements. The result shows that the fitted regression model has the reasonably good regression model for R2 = 79%. Meanwhile, the validation shows the small deviation discrepancy from Mean Square Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) with a determination coefficient, R2 = 82%. In conclusion, the develop k-model in this study present a good prediction for hydraulic conductivity value.