Declining groundwater levels and spatially heterogeneous recharge in semi-arid regions necessitate a reliable delineation of groundwater potential recharge zones (GWPRZ) at the basin scale. Although GIS-based multi-criteria decision analysis is widely applied, most studies are confined to small watersheds and lack of long-term field validation. This study evaluates groundwater recharge potential across the Yamuna Basin (similar to 366,000 km(2)) using two decision-making frameworks: the Analytic Hierarchy Process (AHP) and the Multi-Influencing Factor (MIF) method. Nine thematic datasets: geology, geomorphology, soil, slope, topography, rainfall, land use/land cover, drainage density, and lineament density were integrated within a harmonised GIS environment. AHP employed pairwise comparisons to derive factor weights, while MIF quantified direct and indirect factor influences. Model outputs were validated using long-term groundwater level data (2014-2023) from approximately 2,400 observation wells. Results show that AHP classified 20.5% of the basin as high to very high recharge potential, compared to 16.7% using MIF. The AHP model exhibited stronger agreement with observed groundwater level fluctuations (R-2 = 0.829, Po +/- 1 = 75.8%, AUC = 0.725) than MIF (R-2 = 0.769, Po +/- 1 = 75.0%, AUC = 0.719). Despite pronounced hydrogeological heterogeneity, both approaches demonstrated robust performance, highlighting their applicability for basin-scale groundwater recharge assessment and decision support.