Integrated magnetic and electrical resistivity investigation for assessment of the causes of road pavement failure along the Ife-Osogbo Highway, Southwestern Nigeria

Abstract

This study combined magnetic and electrical resistivity investigations to assess the reasons for the persistent failure of road pavement along the Ife-Osogbo highway, southwestern Nigeria. Three traverses, each covering both stable and failed road segments, were established for ground magnetic, 2D dipole–dipole electrical resistivity imaging (ERI) and 1D Schlumberger vertical electrical sounding (VES) surveys. Data correction involving diurnal effect and offset were carried out on the magnetic data and the corrected data were presented as profiles and then modeled for 2D subsurface images. The VES and 2D ERI data were respectively modeled for layer geoelectric parameters and 2D resistivity images. The magnetic profiles and 2D magnetic subsurface models identified geologic structures (fault/fracture/contact zones) that are inimical to road pavement foundation beneath the investigated traverses. Subsurface sequences underlying the road segments are topsoil, lateritic layer, weathered layer, partly weathered/fractured basement and the fresh basement rock. Laterite, typical of competent subgrade for road pavement foundation, was generally observed beneath the stable segments while clayey weathered layer characterized the failed segments. From 2D resistivity images (upper 5 m), low resistivities (< 100 Ωm), typical of expansive clay, were observed partly beneath the stable but predominately beneath the failed road segments. Generally, it was observed that road segments founded on relatively high resistivity/lateritic layer were stable while the failed segments were associated with significantly thick and low resistivity weathered layer with thin/no lateritic topsoil cover. It was therefore concluded that the persistent road pavement failure along the Ife-Osogbo highway were caused by the clayey nature of the subsoil and the underlying geologic features.