As floods pose an increasing threat to our society, insights into their occurrence and dynamics are of major importance for emergency relief, damage assessment, the optimization of predictive models, and spatial planning. Due to their capability of providing synoptic observations independent of cloud cover and daylight, synthetic-aperture radar (SAR) sensors are an invaluable tool for flood mapping and monitoring. In this study, the potential of SAR, and more specifically Sentinel-1, for automated flood monitoring in Flanders is assessed. Its capability to detect floods with varying characteristics is investigated, and an approach for automated monitoring is presented. This approach, combining thresholding and region growing, requires a SAR image pair and several ancillary data layers, including elevation, land cover, and flood risk, as input. The resulting map discriminates permanent water, open flooding, long-term flooding, possible flooding, flooded vegetation, and possibly flooded forests from dry land. Invisible forested areas are indicated as well. A quantitative and qualitative accuracy assessment, based on 17 and 138 flood maps, respectively, highlights the approach's robustness and improved accuracy compared to benchmark techniques. Furthermore, main sources of confusion are identified and suggestions for future improvements are listed.