Geological and Geostatistical Appraisal of Disparities in Different Derived Lateritic Soils Around Akure, Southwestern, Nigeria

Abstract

This study evaluates the geological and geostatistical variability of lateritic soils derived from different parent rocks, with the aim of determining their suitability and reliability for engineering design applications. A total of forty (40) trial pits were excavated at 500 m intervals along the study corridor. Field investigations included moisture content determination, Dynamic Cone Penetrometer (DCP) testing, and bulk density measurements, while laboratory analyses comprised laboratory DCP and California Bearing Ratio (CBR) tests conducted on representative soil samples.

The analysis was based on comparative evaluation of field and laboratory results using geometrical curve assessment, coefficients of variation, percentage deviation, degrees of accuracy, and statistical correlations derived from CBR and Maximum Dry Density (MDD) parameters. Results indicate that increasing moisture content significantly influences geotechnical performance, particularly by reducing soil strength. Average coefficients of reduction in CBR values of 1.77 and 3.33 were obtained for field and laboratory data, respectively, demonstrating greater moisture sensitivity in laboratory-derived results. Statistical evaluation shows a strong correlation for field data (r = 0.80; R² = 0.65), whereas laboratory data exhibit a weak relationship (r = 0.17; R² = 0.03). Furthermore, an average percentage deviation of approximately 37% was observed between field and laboratory CBR results. Coefficients of variation of 64% and 117% were obtained for field and laboratory CBR data, respectively, while degrees of accuracy between CBR/MDD relationships were estimated at 90% for field data and 38% for laboratory data. These findings demonstrate that field-based measurements provide greater consistency and reliability for engineering design purposes than laboratory test results.

Keywords: Lateritic soils, Field testing, Laboratory testing, Coefficient of variation, Percentage deviation

DOI: 10.7176/JEES/16-1-04

Publication date: February 28^th 2026