Spatial distribution of water contaminants is essential for targeted water quality management in urban environments. This study investigates the spatial distribution patterns of physicochemical parameters and heavy metal contaminants in water sources across ten selected settlements within Ibadan metropolis, Nigeria: University of Ibadan community, Agbowo, The Polytechnic of Ibadan community, Akobo, Ashi, Sango, Adogba, Ojoo-Iwo, Obaleye, and Basorun. A total of ten water samples were collected and analyzed for pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness, bicarbonate, total alkalinity, fluoride, chloride, manganese, iron, zinc, chromium, and nickel. Geographic Information System (GIS) techniques specifically inverse distance weighting (IDW) interpolation were employed to generate spatial distribution maps for each parameter. Results revealed that physicochemical parameters (pH, EC, TDS, hardness, alkalinity, chloride, and fluoride) exhibited relatively uniform spatial distribution across the study area, with all values falling within WHO and SON permissible limits for drinking water. In contrast, heavy metals particularly chromium (Cr) and nickel (Ni) showed marked spatial heterogeneity and significantly elevated concentrations. Chromium ranged from 0.08 to 0.27 mg/L (permissible limit: 0.05 mg/L), while nickel ranged from 0.04 to 0.18 mg/L (permissible limit: 0.02 mg/L). Hotspots of Cr and Ni contamination were identified in Ojoo-Iwo (Cr: 0.27 mg/L, Ni: 0.18 mg/L) and The Polytechnic of Ibadan environs (Cr: 0.19 mg/L, Ni: 0.12 mg/L), corresponding to the highest Water Quality Index (WQI) values (1035 and 170 respectively). The contrasting spatial patterns uniform physicochemical parameters versus clustered heavy metal hotspots suggest different contamination sources: geogenic or diffuse sources for physicochemical parameters versus localized anthropogenic sources (industrial discharge, illegal dumping, or landfill leachate) for heavy metals. This study concludes that GIS-based spatial analysis is an effective tool for identifying pollution hotspots in urban water systems and recommends targeted remediation in high-risk zones rather than uniform city-wide interventions.