Application of extreme gradient boosting and parallel random forest algorithms for assessing groundwater spring potential using DEM-derived factors

•Spotting high potential areas for groundwater exploitation.•Application of two state-of-the-art machine learning algorithms.•Feeding only DEM-derived factors to the algorithms to determine groundwater potential.•Extreme gradient boosting and parallel random forest yielded AUC values of about 86%•Convergence, TWI, river density, and altitude are the most important factors.