While groundwater serves as a valuable resource, its infiltration poses significant challenges to urban infrastructure. This study develops and demonstrates a computationally efficient spatio-temporal analysis of groundwater infiltration (GWI) in urban facilities, specifically sewer networks (SNs), within the Lower River Otter Water Body, United Kingdom. To achieve this, the Fuzzy-Analytic Hierarchy Process (F-AHP) within a Geographic Information System (GIS) framework was employed, considering geology, geomorphology, hydrology, hydrogeology, climate, and topography. The proposed model encompasses 16 thematic maps, categorised into 6 groups: (1) groundwater (groundwater depth (GWD)); (2) altitude (elevation, slope, and topographic wetness index); (3) precipitation (monthly precipitation); (4) ground cover (rock permeability, alluvial permeability, soil type, land cover, and made ground); (5) earth movement (fault proximity, fault length density, and mass movement); and (6) runoff (river, flood potential, and drainage density). Expert judgment, F-analysis, and AHP were applied to the layers for classification, normalisation, and weight assignment, respectively. Verified by data from outfalls, GWI probability maps were generated considering the shallowest GWD and highest precipitation for temporal analysis. Overall, higher GWI probability scores were found in regions with shallower GWD, lower elevations, especially near river, and higher permeabilities. Assigning a probability score between 0 and 1 for each 1-metre area in each season, the vulnerability maps can guide water agencies in implementing protective strategies for infrastructure. The findings contribute to enhancing groundwater sustainability in urban areas, particularly in the face of potential climate change.