Integrating hydrogeological and second-order geo-electric indices in groundwater vulnerability mapping: A case study...

AVI (Aquifer vulnerability index), GOD (groundwater occurrence, overlying lithology and depth to the aquifer), GLSI (geo-electric layer susceptibility indexing) and S (longitudinal unit conductance) models were used to assess economically exploitable groundwater resource in the coastal environment of Akwa Ibom State, southern Nigeria. The models were employed in order to delineate groundwater into its category of vulnerability to contamination sources using the first- and second-order geo-electric indices as well as hydrogeological inputs. Vertical electrical sounding technique employing Schlumberger electrode configuration was carried out in 16 locations, close to logged boreholes with known aquifer core samples. Primary or first-order geo-electric indices (resistivity, thickness and depth) measured were used to determine S. The estimated aquifer hydraulic conductivity, K, calculated from grain size diameter and water resistivity values were used to calculate hydraulic resistance (C) used to estimate AVI. With the indices assigned to geo-electric parameters on the basis of their influences, GOD and FSLI were calculated using appropriate equations. The geologic sequence in the study area consists of geo-electric layers ranging from motley topsoil, argillites (clayey to fine sands) and arenites (medium to gravelly sands). Geo-electric parametric indices of aquifer overlying layers across the survey area were utilized to weigh the vulnerability of the underlying water-bearing resource to the contaminations from surface and near-surface, using vulnerability maps created. Geo-electrically derived model maps reflecting AVI, BOD, FLSI and S were compared to assess their conformity to the degree of predictability of groundwater vulnerability. The AVI model map shows range of values of log C ( -3.46-0.07) generally less than unity and hence indicating high vulnerability. GOD model tomographic map displays a range of 0.1-0.3, indicating that the aquifer with depth range of 20.5 to 113.1 m or mean depth of 72. 3 m is lowly susceptible to surface and near-surface impurities. Again, the FLSI map displays a range of FLSI index of 1.25 to 2.75, alluding that the aquifer underlying the protective layer has a low to moderate vulnerability. The S model has values ranging from 0.013 to 0.991S. As the map indicates, a fractional portion of the aquifer at the western (Ikot Abasi) part of the study area has moderate to good protection (moderate vulnerability) while weak to poor aquifer protection (high vulnerability) has poor protection. The S model in this analysis seems to overstate the degree of susceptibility to contamination than the AVI, GOD and GLSI models. From the models, the categorization of severity of aquifer vulnerability to contaminations is relatively location-dependent and can be assessed through the model tomographic maps generated.