A Novel Hybrid Model for Developing Groundwater Potentiality Model Using High Resolution Digital Elevation Model (DEM) Derived Factors

The present work aims to build a unique hybrid model by combining six fuzzy operator feature selection-based techniques with logistic regression (LR) for producing groundwater potential models (GPMs) utilising high resolution DEM-derived parameters in Saudi Arabia’s Bisha area. current focuses exclusively on the influence of GPMs modelling, without considering other variables. AND, OR, GAMMA 0.75, 0.8, 0.85, and 0.9 are based selection. were validated using empirical binormal receiver operating characteristic curves (ROC). An RF-based sensitivity analysis was performed order examine GPM settings. Six algorithms one have predicted 1835–2149 km2 as very 3235–4585 regions. AND (ROCe-AUC: 0.81; ROCb-AUC: 0.804) outperformed ROC’s area under curve (AUC). A novel constructed (considering variables) LR model. AUC ROCe ROCb revealed that existing fuzzy-based (ROCe: 0.866; ROCb: 0.892). With parameters, will help improve effectiveness developing sustainable management plans.