Floods are hydrometeorological hazard whose frequency and magnitude have been exacerbated by climate change. This study conducts a comprehensive flood hazard assessment in District Bannu, Pakistan, by integrating the Analytic Hierarchy Process (AHP) with Geographic Information Systems (GIS) to address regional research gaps. Utilizing Sentinel-1 C-band Synthetic Aperture Radar (SAR) data, the research delineates flood extent and identifies high-risk zones during the 2023 monsoon season. SAR imagery was processed via the Sentinel Application Platform (SNAP), utilizing orbit file application, thermal noise reduction, calibration, speckle filtering, and terrain correction. The AHP framework integrated twelve geo-environmental criteria, including elevation, slope, rainfall, flow accumulation, distance to river, drainage density, land cover, soil type, geology, NDVI, and curvature, to generate a multi-criteria flood hazard map. The findings reveal that in August 2023, 74.81 km2 was inundated, representing 6.06% of the study area within the Kurram River basin. Comparative analysis indicates that SAR-based mapping, supplemented by NDWI variables from Landsat sensors, provides a robust mechanism for flood monitoring in lowland regions. This study underscores the efficacy of microwave remote sensing in providing near real-time surface water information, offering a precise tool for water resource management, flood warning systems, and post-disaster damage assessment.