Application of GIS-Based Evidential Belief Function Model to Regional Groundwater Recharge Potential Zones Mapping in Hardrock Geologic Terrain

The evidential belief function - Dempster-Shafer theory (EBF-DST) model was applied and validated for groundwater recharge potential zoning in the hard-rock geologic terrain, southwestern Nigeria, using geographic information systems (GIS). Data about related factors, including satellite imagery, climate and geology were collected and input into a spatial database. In addition, groundwater well yield data inventory of the area were collected from 78 well locations. The groundwater well yield data were partitioned into two data sets, using partitioning criterion ratio of 70 to 30 for training and validation of the model. By using the constructed spatial database, six groundwater recharge conditioning factors such as slope, drainage density, lineament density, lineament intersection density, lithology and rainfall were extracted. The relationships between the well locations and the factors were identified and quantified by using the EBF-DST model. Four belief function series were calculated: belief (Bel), disbelief (Dis), uncertainty (Unc), and plausibility (Pls). The integrated belief function was used to produce the groundwater recharge potential prediction index (GRPPI) map. Furthermore, to compare the performance of the EBF-DST result, multi-criteria decision analysis - analytic hierarchy process (MCDA-AHP) model was applied. The success-rate and prediction-rate curves were computed to estimate the efficiency of the proposed EBF-DST model compared to the MCDA-AHP model. The validation results demonstrated that the success-rate for EBF-DST and MCDA-AHP models were 89 and 82 %, respectively. The area under the curve (AUC) of prediction-rate for both EBF-DST and MCDA-AHP models were calculated as 89 and 78 %, respectively. The outputs accomplished from the current research proved the efficacy of EBF-DST model in groundwater recharge potential zones mapping.