Statistical analysis of subsoil geotechnical properties derived from Ogbagi Akoko and other parts of Southwestern Nigeria

• Published in: Bulletin of engineering geology and the environment 2023-06, Vol.82 (6), Article 225
• Main Authors: Ale, Temitayo Olamide, Ale, Taiwo Ayomide, Wilson, Jumoke Adeola, Ayeniyo, Olutayo Olawale
• Format: Article
• Language: English
• Subjects: Earth and Environmental Science; Earth Sciences; Foundations; Geoecology/Natural Processes; Geoengineering; Geotechnical Engineering & Applied Earth Sciences; Hydraulics; Nature Conservation; Review Paper
• ISSN: 1435-9529; 1435-9537
• DOI: 10.1007/s10064-023-03260-x

This research is aimed at using statistical analysis to predict the overall performance of subsoil derived from three rock types in Southwestern, Nigeria, for pre- and post-engineering construction. Twelve subsoil samples were obtained along Ogbagi Akoko road and thirty articles were reviewed for statistical analysis of Pearson correlation coefficient (PCC) and analysis of variance (ANOVA). Subsoil samples from Ogbagi are sufficiently good because they meet the Nigerian specification. Comparing the statistical values of the soil samples derived from the three rock types, igneous, metamorphic, and sedimentary rocks have combined strong positive and negative pairwise parameter values of 31, 25, and 14 respectively. Igneous rock derived soil has more positive pairwise PCC (20) and better ratings in 30 pairwise parameters when compared with the other two rock types. Two strong positive (PL-LL and FINES- LL) and one negative (COARSE–FINE) pairwise PCC of the same variables are common to the three rock types derived soils. For coefficient of determination ( r 2 ), igneous rock derived soil has excellent (> 75%) and good ( 75%) (COARSE-FINES) common to the three rock types derived soil. For ANOVA analysis, the critical r values of all the parameters are by far higher than the test values for all the parameters. We therefore fail to reject the null hypothesis.