Evaluation and modeling of a major coastal aquifer’s vulnerability to contamination with the use of GOD and AVI models as indicators in South-eastern Nigeria
Keywords:
Aquifer vulnerability index (AVI), GOD index, groundwater, contaminants, resistivityAbstract
Geophysical techniques were employed to evaluate the extent of a major coastal aquifer’s vulnerability to near-surface and subsurface contamination with the use of GOD and AVI vulnerability models in Akwa Ibom State, Southern-eastern Nigeria. The study area is strongly dependent on groundwater resources, hence it was important to evaluate the extent of aquifer vulnerability. Interpretations of the resistivity inversion models, constrained by well information, indicated the presence of three lithological layers (motley top soil, fine sand, and coarse sand). The resistivities of the first layer were generally larger than those of the underlying subsurface layers, indicating the percolation of contaminant material into the surrounding aquifer. The resistivity of the geological layers ranged from 1.3- 626 Ωm. Contour maps were used to illustrate the variations of various geological and geo-electrical parameters obtained at the study location. Resistivity data was also used to generate aquifer hydraulic data from which the aquifer vulnerability indices were determined to evaluate the vulnerability of the aquifer to pollutant contamination. The vulnerability indices used to determine the extent of aquifer vulnerability to contamination were the Aquifer Vulnerability Index (AVI) model and the Groundwater occurrence, Overlying layer and Depth to groundwater (GOD) model. The GOD indices ranged from 0.54 to 0.63 with a mean of 0.55, implying a high vulnerability to near-surface and subsurface contaminants. The AVI values had a range of 0.3 to 1.13with a mean value of 0.65, and based on AVI classification tables, the aquifer units have a very high vulnerability to contamination. These results corresponded with what was obtained from the GOD models showing that in general, the research area is highly susceptible to contamination.
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