Floods are among the most devastating natural disasters, causing widespread damage to life, property, and infrastructure. Rapid and accurate flood detection and mapping are essential for effective emergency response and mitigation. Synthetic Aperture Radar (SAR) data, with its ability to penetrate cloud cover and operate in all weather conditions, plays a crucial role in real-time flood assessment and management. The present study uses Synthetic Aperture Radar (SAR) Sentinel-1A and Sentinel-1C (10 M resolution) datasets provided by the European Space Agency (ESA) to assess the extent of flooding in the Dharali Region of Uttarkashi, Uttarakhand, India. During the flood event, extensive cloud cover limits the applicability of optical imagery; therefore, microwave SAR data are used in the present investigation. The flood-affected zone in the Dharali region is relatively small, making change detection using 10-meter-resolution SAR data challenging. The challenges posed by comparatively low-resolution data can be addressed using threshold-based band-filtering techniques and RGB composites. The present study uses Sentinel-1A and Sentinel-1C data to detect changes in the flooded area before and after the event. The data are preprocessed using an orbit file application, geometric correction, radiometric calibration, speckle noise reduction, and terrain correction, all of which are essential for accurate geospatial analysis. A threshold-based band-filtering technique and RGB composite images are employed to detect change. This study provides useful data for rapid response in disaster management and flood mapping in the Dharali region of Uttarkashi, Uttarakhand, India, during the flash floods that occurred on 5th August 2025.