Abstract:
Groundwater potentiality assessment is an effective tool for groundwater management.
This study explored the potential of a GIS-based FAHP technique in the field of
groundwater hydrology. The approach was applied to model aquifer potential
conditioning factors derived from interpreted geoelectrical parameters and remote
sensing data. 106 depth sounding (VES) data locations were identified in the Study
area. The acquired VES data were quantitatively interpreted to determine the subsurface
lithologic parameters in the form of resistivity and thickness. The interpreted results
were used to derive the groundwater potential conditioning factors (GPCFs), namely:
longitudinal conductance (Lc), transverse resistance (TR), transmissivity (T), aquifer
thickness (AQT), Aquifer resistivity (AQR) coefficient of anisotropy (COA) and Slope.
Using the derived geoelectrical-based GPCFs values, the GPCFs themes were produced
in the GIS platform. The produced GPCFs themes were multi-critically analyzed using
the mechanism FAHP data mining model algorithm to produce groundwater
potentiality indexing (GPI) map. Furthermore, to compare the performance of the
FAHP data mining model result, multi-criteria decision analysis-analytic hierarchy
process (MCDA-AHP) model was applied. The efficiency of the FAHP and MCDA-
AHP-based GPI maps were evaluated using well data records. The results of the well
data correlation with the predictive model maps show linear correlation of 0.87 and
0.76 for FAHP and MCDA-AHP data mining models, respectively. These results show
that both models have good performance in prediction of groundwater potential zones,
with the FAHP as a better alternative. These maps and models could be used as future
planning tool and part of vital supports for decision making for locating appropriate
positions of new productive wells in the study area.
