The geological and hydrogeological framework of the Panabako, Kodjari, and Bimbilla formations of the Voltaian supergroup – Revelations from groundwater hydrochemical data

This research demonstrates the utility of groundwater hydrochemical data for facilitating lithological mapping in a sedimentary terrain. Factor analysis and Q-mode Hierarchical Cluster Analysis (HCA) were applied to groundwater hydrochemical data from the Nasia Basin in Northern Ghana to determine the major sources of hydrochemical variation and the main spatial groundwater associations (groups). These analyses were complemented by mass balance hydrochemical modeling from PHREEQC and petrographical analysis of rock samples from the area. Rock samples from the study area were subjected to petrographical and geochemical analyses from a petrographic microscope and Scanning Electron Microscope (SEM) respectively. Four principal factors were distinguished from the factor analysis, highlighting four principal processes responsible for the observed hydrochemistry in the area. These four factors cumulatively account for over 79% of the total variance in the dataset. Factor scores were computed from the factor loadings matrix through a regression process, to highlight the spatial variations in the significance of each of the factors in the terrain. On the basis of the parameter loadings, the first factor, which has been noted to be pervasive throughout the terrain, has been interpreted to represent silicate mineral weathering. Both the geochemical data and petrographical analysis indicate the presence of silicate minerals indicating the plausibility of silicate mineral weathering. The process of silicate mineral weathering appears to be highly pervasive throughout the basin, indicating high factor scores in places. The trend of spatial variations in the scores of factor 1 clearly mimics the known geology of the terrain, indicating that the geology is the main controlling factor in the hydrochemistry of groundwater in the basin. This pattern, exhibited by the factor scores indicates that where adequate groundwater hydrochemical data is available, factor analysis would prove useful in mapping out lithological variations in an area. Two of the remaining factors have been observed to represent other specific geogenic processes. Mass balance hydrochemical modeling suggests that albite may be in active dissolution, presenting pervasively negative saturation indices (undersaturation), while kaolinite is extensively supersaturated. Five groundwater associations distinguished from the Q-mode HCA display a spatial pattern which identifies with the underlying geology.