Spatial mapping of geotechnical soil properties at multiple depths in Sialkot region, Pakistan

This paper aims to create spatial maps (SMs) using a spatial interpolation technique based on extensive geotechnical subsoil data derived from comprehensive field and laboratory investigations. Sialkot, a rapidly developing industrial and agricultural district, is used as a case study. The subsoil information was assessed in terms of Standard Penetration Test N-values (SPT-N), shear wave velocity, soil type, soil consistency, and chemical analysis. Using ArcGIS, the SMs were created by treating each depth level as a surface and using the Inverse Distance Weighting (IDW) interpolation technique. Correlations were also developed using linear regression analyses for SPT-N values, and soil consistency in conjunction with depth, allowing quick and reliable assessment of soil strength and stiffness, and soil consistency during the preliminary planning and design process of any proposed project in the study area. The results show that at shallow depth (i.e., up to 3 m) the fine-grained soil is predominant with a plasticity index (PI) ranged between 7 and > 17; SPT-N values between 2-8; and shear wave velocity between 138 and 195 m/s. Beyond, 3 m depth, the non-plastic coarse-grained soil is predominant exhibiting SPT-N values between 8 and > 16; and shear wave velocity between 195 and > 232 m/s. In addition, the correlation coefficient for SPT-N values exhibits good prediction accuracy, i.e., at shallow depth (up to 3 m) the correlation coefficient between actual and predicted value ranges between 82 and 90%; whereas beyond 3 m the correlation coefficient varies between 67 and 89%. Meanwhile, for PI value the correlation coefficient up to 9 m depth ranges between 82 and 94%. Moreover, the prediction accuracy for soil type using SMs is around 83%. This information enables engineers to construct a preliminary ground model for a new site using data derived from adjacent sites or sites with the same subsoils exposed to similar geological processes. Furthermore, having reliable information on the geometry and geotechnical properties of underground layers will make projects safer and more cost-effective.

Automated summary

This study creates spatial maps using spatial interpolation technique based on geotechnical subsoil data, allowing quick and reliable assessment of soil properties. Results show significant variations in soil types and properties at different depths, with high prediction accuracy.