The occurrence of floods and droughts in Lake Poyang is becoming increasingly frequent as a consequence of climate change and human activities, with severe repercussions for the ecological environment of the Lake Poyang basin. The objective of this study is to accurately monitor the spatial and temporal dynamics of the Lake Poyang watershed area in all weather conditions using radar remote sensing technology. This will provide a scientific basis for the assessment of water resources and early warning of droughts and floods in Lake Poyang. The single-band threshold method, dual-polarized water body index and inter-spectral relationship method, when combined with the maximum interclass variance method, were used to adaptively determine the threshold value for the extraction of water bodies. The optimal extraction method was selected through the evaluation of the accuracy and applied to the all-weather extraction of the water area of Lake Poyang. The relationship between water level change and lake watershed area was revealed when the data from Xingzi Station and Hukou Station were combined. The resulting dataset which includes the raster data of the waters of Lake Poyang, represents the daily water level-area data for Lake Poyang under all-weather conditions. The data set comprises a total of 424 periods from 2014 to 2023, including the area of the water and the water level data from Xingzi Station and Hukou Station. The data set is stored in the .tif and .xlsx formats. Furthermore, the disturbance event identification method of lake watershed area time series curve was employed to identify the main factors of sudden area changes in 2020 and 2022. The results demonstrated that the inter-spectral relationship method, when combined with the threshold segmentation method utilising maximum interclass variance, exhibited optimal extraction accuracy (overall accuracy ＞95%). Additionally, the watershed area of Lake Poyang displayed notable intra-annual fluctuations during the 2016-2023 period, with the majority of these variations concentrated in the river and the middle portion of the lake. The changes in water level and area tended to be consistent. Furthermore, when the water level was ≥14 m, there was a significant positive correlation between the changes in water level and lake watershed area. The classification of the lake time series perturbation results indicated that the primary driver of the lake watershed area expansion in 2020 was natural, whereas the primary driver of the sudden decrease in 2022 was anthropogenic.