.

For the purpose of meeting the demand for fresh groundwater globally, the schemes of potentiality and vulnerability evaluations of groundwater become an increasingly important approaches for implementing a successful groundwater resources management programs. A study involving selected data mining models subjected for constructing groundwater potentiality and vulnerability maps apt for groundwater sustainability management is a timely venture for this task. For the potentiality, the evidential belief function (EBF) and analytical hierarchical process (AHP) models were examined while, the DRASTIC and OWA-DRASTIC methods were studied for the vulnerability analysis.  Six groundwater potentiality conditioning factors (GPCFs) including aquifer layer thickness; aquifer layer resistivity; overburden material resistivity; overburden material thickness; hydraulic conductivity; transmissivity and seven pollution potential conditioning factors (PPCFs) namely: water table depth; recharge rate; aquifer media; soil media; topography; impact of vadose zone; hydraulic conductivity were considered. Using these conditioning factors as input to the data mining models’ algorithms, groundwater potential index (GWPI) maps and groundwater vulnerability to pollution index (GVPI) maps were produced. Applying the reacting operating characteristics (ROC) technique using ratio 70:30 of the occupied 28 borehole wells, the EBF and AHP models’ produced maps were validated. The analyzed groundwater quality data results were also used for the DRASTIC and OWA-DRASTIC method’s validation. The ROC results established the success rate and prediction rate of 88 % and 89 % and 53 % and 68 % for the EBF and AHP models, respectively. Similarly, the validation results for the DRASTIC and OWA-DRASTIC methods revealed 64.29% and 85.71%, respectively. Based on the results obtained, about 63% of the area is zoned to be of medium/high potentiality while about 73 % of the area is estimated for good groundwater quality zones. The information from these models’ maps can be harnessed by the local authorities to enhance groundwater sustainability management in the area.

Keywords: Geophysical, groundwater, data mining, AHP, EBF, DRASTIC, Vulnerability