GIS-based mapping of geotechnical and geophysical properties of Lahore soils

To accurately determine subsurface soil type and condition for engineering projects, structural safety, and foundation design under static and seismic loading conditions, it is necessary to have a comprehensive workflow that maps and explores the interrelationships between geotechnical and geophysical properties of soil. Although multiple interpolation techniques and mathematical correlations are available for this purpose, there is no globally accepted workflow yet. This study proposes a GIS-based workflow for selecting an interpolation technique and establishing interrelationships among SPT N values, bearing capacity, shear wave velocity (Vs), and groundwater using data from sixty-five boreholes in Lahore city. By evaluating Kriging and Inverse distance weighting (IDW) interpolation techniques using GIS software, the study finds that IDW is more effective than Kriging, with lower mean root mean square error (RMSE) for all studied geotechnical properties. The correlation coefficient of 0.77 between measured and interpolated SPT N values, Vs, and bearing capacity increases confidence in the estimated properties at unsampled locations. Additionally, cross-plots between geotechnical properties demonstrate that they are interdependent and vary with soil type and groundwater depth, which can be helpful for soil characterization, shallow foundation design, and seismic microzonation in the study area. The geotechnical maps and cross-plots produced by this study for Lahore soils are new and consistent with soil types, demonstrating the suitability of the proposed workflow for global use.

Automated summary

This study proposes a GIS-based workflow for accurately determining soil type and condition, as well as the interrelationships between groundwater and geotechnical properties. The study finds that the Inverse distance weighting (IDW) interpolation technique is more effective than Kriging, as it has a lower mean root mean square error (RMSE). The correlation coefficient between measured and interpolated values increases confidence in the estimated properties at unsampled locations. Additionally, the cross-plots between geotechnical properties demonstrate their interdependence and variation with soil type and groundwater depth.