Geospatial Engineering Geological Rock Mass Characterization and Classification using Multicriteria Analytical Hierarchy Decision Process (AHP-MCDA) in Ondo State, Southwestern Nigeria

Abstract

This study provides quantitative and qualitative information on the strength/competency of rock masses in Ondo State, southwestern Nigeria, for slope, foundation, and tunnel applications. In addition, parameters influencing the general behaviour/characteristics of the rock masses, as well as the most suitable rock classification system(s), were duly identified. The study employed nine systems (RMR, Q-system, modified Q-system, RMN, RMI, GSI, SMR, RSR, and RQD), which were ranked using the AHP-MCDA method. All the parameters required were obtained through engineering geological mapping and laboratory analysis. The AHP-MCDA generated a strength map that categorised the area into five classes, comprising very weak (8 %), moderately weak (23 %), moderately strong (37 %), strong (18 %), and very strong (14 %), with areal extents of 384 km2, 5399 km2, 6524 km2, 2232 km2, and 461 km2, respectively. The very strong rock masses usually have lower fracture frequency and are slightly weathered. These rocks are predominantly porphyritic granite, charnockite, granite gneiss, fine-grained granite, biotite granite, and gneisses. Among these rocks, the fine–medium and medium-coarse-grained granite (including aplites, dolerites, and some hypabyssal rocks occurring as dykes) showed the best geomechanical attributes and ranked very high by all the systems. The migmatite/migmatite gneiss, pegmatite, and some porphyritic granite constitute the moderately strong rocks. The quartz schist, mica – quartz schist, and the flaggy quartzite constitute the moderately weak rocks, while  Dahomey Basin deposits make up the very weak rock units. Within the adopted AHP framework, the most suitable system is the RMR, with a weight of 31.752 %, followed by the modified Q-system (23.365 %), Q-system (16.769 %), RMN (8.588 %), RMI (6.243 %), RSR (4.815 %), GSI (3.645 %), SMR (2.994 %), and RQD (1.828 %), respectively. Overall, the AHP-MCDA map zonation highlights the importance of composite evaluation rather than relying on a single system of characterisation and classification.