The monitoring of rivers based on remote sensing data provides an opportunity for the observation of the natural dynamics of water and flood conditions. Taking advantage of the availability of radar data, we describe a methodology used to detect the river’s water surface flooding patterns and the size of floods using observations from Sentinel-1 imagery. With the proposed methodology, characteristics of the river’s normal average riverbed surface are determined, as well as the flood footprint. As a case study, it shows the annual and interannual water variability at the lower Coatzacoalcos Basin in the state of Veracruz, Mexico. This site was chosen after considering the evidence of seasonal flooding and the changes that happened during the 2015 to 2017 period. Our paper details the results on surface changes during this time period. The results on water surface cover have been validated through different sources of information to confirm the ability to differentiate flood areas and know the maximum flood extensions. An agreement above 92% is estimated to be reached with the use of the evaluated maps of binary water/no-water. Recurrent flood areas were detected where water remained during one or several weeks during the month of October, both in 2015 and 2017. Finally, a change in the extent of water maps in the framework of the Sustainable Development Goals is achieved with the integration of historical data over time and space of the natural behavior of the rivers in the case study.