This study investigates the potential of Sentinel-1 data in assisting flood modeling procedures. Two different synthetic aperture radar (SAR) processing methodologies, one simplified based on single-flood image thresholding and one automatic based on SAR statistical temporal analysis, were exploited to delineate the flooding caused by a storm event that took place in Spercheios River, Central Greece. The storm event was simulated by coupling a HEC-HMS hydrologic model and an integrated 1D/2D HEC-RAS hydraulic model. Both SAR methodologies were compared to each other and also used as a reference to test the sensitivity of the hydraulic model in the variation of upstream discharge and roughness coefficient. Model sensitivity was investigated with respect to the change in the derived inundation extent and three additional metrics: the Critical Success Index (CSI), the Hit Rate (HR), and the False Alarm Ratio (FAR). The model response was found to be affected in the following order: by the upstream inflow, and by the variation of the roughness coefficient in the main channel and in the land use “cultivated crops”. The discrepancies observed between model- and SAR-derived inundation products are associated with the uncertainty accompanying the SAR processing and the utilized satellite data itself, the underlying topography, and the structural uncertainty inherent in the modeling procedure. Regarding the SAR methodologies tested, the second one (FLOMPY approach) proved to be more suitable, yielding a more coherent and realistic flooded area. According to the applied metrics and considering as reference the FLOMPY result, model performance ranged between 22–27.5% (CSI), 36.9–60.4% (HR), and 62.1–68.2% (FAR).