Full control or flood damage management is not always practical through structural measures, due to economic, technological, environmental and social limitations. Therefore, often non-structural measures such(such as flood forecasting and warning to make effective decisions, and choosechoosing appropriate ways to deal with floodsfloods) play an important role in reducing casualties. The importance of advanced systems for short-term and long-term forecasting of floods and other hydrological events to reduce damage and loss due to floods is strongly emphasized. In this research, short-term flood forecasting is discussed using ensemble forecasting methods (EPSs) and the HEC-HMS hydrological model. Also, in order to achieve high accuracy in the assessment of flood-damaged areas, remote sensing techniques and satellite images have been used. The results show that the use of group forecasting methods has helped to improve the speed and accuracy of the forecasting model (R2 = 0.75). Also, with the use of Sentinel-1 radar satellite images and the simultaneous use of supervised learning algorithms, a suitable estimate of the damaged area has been made for three selected floods in the Ken basin in 2019, 2015 and 2014.