New Empirical Approach for the Estimation of Soil Cohesion and Friction Angle in 2D Form for Site Investigations

This paper presents the multiple linear regression (MLR) models developed from electrical resistivity and seismic refraction surveys for quick prediction of subsurface soil's shear strength parameters. A total of four parameters have been considered with electrical resistivity and seismic refraction velocity as the independent variables: and soil cohesion and internal friction angle as the dependent variables. In order to mitigate the effects of nonlinearity of resistivity and velocity, both datasets were initially log-transformed to conform with the fundamental assumptions of regression analysis. Two models were therefore built based on the strong multiple linear relationships between explanatory and response variables, with coefficient of determination (R-2), 0.777, p-values, < 0.050, Durbin-Watson value, 1.787 and multicollinearity, 1.185. The obtained models 'coefficients were transferred and used for the estimation of 2D models soil cohesion and internal angle of friction for validation. Thereafter, the developed models demonstrated good performance, having subjected to accuracy assessment with results at < 5%, and < 10% for the root mean square error (RMSE) and weighted mean absolute percentage error (MAPE) respectively. Therefore, the new developed soil's shear strength MLR models have provided continual description of soil properties in two-dimensional form, enhancing the subsurface information for site investigations as compared, to one-dimensional information from the invasive method.