Abstract
Due to global warming and climate change, affected by climate anomalies, Yangtze River basin in China experienced the strongest high-temperature process since the complete meteorological observation records in 1961. This process led to the continuous low water level of Yangtze River tributaries and the rare phenomenon of "anti-depletion of flood season" in Poyang Lake and Dongting Lake, both of which were influenced by this climate event. Lakes are indicators of global climate change, and water area changes in lakes have become one of the sensitive indicators of regional ecological environment and climate change. In this study, we used the GEE cloud computing platform to call Sentienl-1 SAR data to calculate the sentinel-1 dual-polarized water index (SDWI). Then, we determined the optimal threshold value using the OTSU algorithm to obtain the final water change monitoring data at 10m resolution for the main body of Poyang Lake, Dongting Lake and their surrounding areas during extremely high temperatures in 2022. This dataset has been validated to with an overall accuracy of over 96% and a Kappa coefficient of 0.92. The dataset includes spatiotemporal variations in arid water bodies in the middle and lower reaches of the Yangtze River during extremely high temperatures in 2022. The dataset can offer data support and serve as a scientific foundation for sustainable lake water resources during extreme weather events, as well as for research on global climate change and the ecological evolution of lakes.
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