Monitoring the dynamic changes of water area in Dongting Lake is of great significance for flood control， ecosystem stability and biodiversity. The deep learning algorithm represented by the classic Unet the innovative HRNet has become an efficient way to obtain remote sensing image information. Taking Sentinel-1A SAR image as the main data source， this paper qualitatively and quantitatively analyzes the water extraction results of SDWI index method （Sentinel-1 Dual-Polarized Water Index，SDWI）， object-oriented classification method， UNet network model and HRNet network model. Based on the best water extraction method， the temporal and spatial variation characteristics of water area in the flood season （April to October） of Dongting Lake from 2016 to 2021 are analyzed. The results show that ： ① The deep learning algorithm represented by HRNet and Unet has better water extraction effect than traditional methods. Among them， HRNet has superior performance in noise suppression and shadow resistance， and the F1 score， MRate and MIoU are 0.961 6， 0.007 8 and 0.958 6， respectively. ② During the flood season， the water area of Dongting Lake shows the characteristics of “ increase-full-decrease ” in the monthly variation. The lake surface begins to expand from April to May， and the water area maintained at a high level from June to August. Since then， due to the decrease of inflow， the water area gradually decreases from September to October. The 2 263.90 km² at July 30， 2020 is the largest water area monitored during the study period. ③ The submerged frequency of water body in flood season of Dongting Lake gradually decreases from the center of the lake body and the main stream. The distribution patterns of submerged frequency in different lake areas are different. The submerged frequency of East Dongting Lake is higher than that of South Dongting Lake and West Dongting Lake. In summary， the combination of Sentinel-1A SAR image and deep learning technology can realize the efficient acquisition of water information and high-frequency monitoring of the water surface area at Dongting Lake， providing a new idea for the high dynamic lake water monitoring.