Glacial lakes are a sensitive indicator of regional climate change and one of the initiators of glacier disasters. It is of great significance to understand the spatial distribution and change characteristics of glacial lakes for exploring their response patterns to climate change and assessing the glacial lake outburst flood (GLOF) susceptibility. Based on Gaofen-1/6 PMS, Sentinel-2A/2B MSI and Landsat TM/ETM+/OLI images from 2000 to 2020, we integrated geographic information technology and mathematical and statistical methods to analyze the spatial and temporal distribution of glacial lakes in Nepal and their dynamic changes, and further discriminated and evaluated the GLOF susceptibility of glacial lakes. The results show that there were 2420 glacial lakes in Nepal in 2020, mainly distributed within the 4500~5500 m, with an area of 87.21 km² and a water storage of 1921.72 × 10⁶ m³. The number and area of glacial lakes with each area above 0.01 km² in Nepal showed an increasing trend from 2000 to 2020, while 499 new glacial lakes were born, 139 lakes disappeared, the area and water storage increased by 19.46 km², 403.07 × 10⁶ m³, respectively. Glacial lakes at altitudes <3000 m were relatively stable, while the number and area of glacial lakes at altitudes within 4500~5500 m increased rapidly. We assessed the GLOF susceptibility of 40 moraine-dammed glacial lakes with an area above 0.2 km² in Nepal, and found that there were 8, 12, 14 and 6 glacial lakes with low, medium, high and very high susceptibility, respectively. Among glacial lakes with very high GLOF susceptibility, potential GLOF events of Tsho Rolpa glacial lake, Lower Barun glacial lake and glacial lake with code of GL87091E27797N will cause great harm to downstream regions. GLOFs in Nepal will be in an active status in the future, therefore, the dynamics of glacial lakes and their surroundings should be continuously monitored.

In the climatic context of warming and humidification in Northwest China, most lakes in Qinghai Province experienced a rising water level and expanding area, inundating grassland and infrastructure around lakes, and even extreme events such as lake outburst floods. Based on Landsat TM/ETM+/OLI and GF PMS images, lake water level data, SRTM digital elevation model (DEM), GlobeLand30 and meteorological data used in this study, we analyzed the area change of Xiao Qaidam Lake in Qaidam Basin with its causes, factors and potential hazards. The results show that the area of Xiao Qaidam Lake increased by 60.42 km² (85.43%) from 1990 to 2020, which can be roughly divided into three stages: fluctuation decline in 1990–2001 (−1.89 km²/a); relatively stable in 2002–2014; and rapid expansion in 2015–2020 (8.54 km²/a). In 2020, the water level and water volume of Xiao Qaidam Lake increased by 3.62 m and 0.39 km³, respectively, compared with 2015, resulting in the inundation of an area of 54.55 km² of grassland around the lake and a direct threat to the Liuge and Dexiao Expressways. Both the increase in annual precipitation (12.63 mm/10a) and the decrease in potential evapotranspiration (−13.38 mm/10a) since 1990 are the main reasons for the rapid expansion of Xiao Qaidam Lake, and the increasing trend of climate warming and humidification will lead to the continuous expansion of Xiao Qaidam Lake in the next decades. According to the water volume growth rate from 2015 to 2020, it is predicted that by 2024 the area and water level of Xiao Qaidam Lake will reach 154 km² and 3180 m, respectively, and part of Liuge and Dexiao Expressways will be submerged. Therefore, it is urgent to strengthen the monitoring of Xiao Qaidam Lake and formulate corresponding disaster prevention and reduction measures.

Located in the northeastern part of the Qinghai-Tibetan Plateau, Qinghai Province (31°39′–39°19′N, 89°35′–103°04′E) is the source region of the Yangtze River, the Yellow River and the Lantsang River. It is known as the China Water Tower. Contemporary survey of lakes in Qinghai Province is of great significance for understanding the impacts of climate change and promoting the ecological civilization construction. Based on Sentinel-2A/2B MSI images acquired in 2020, we first extracted the pixels of water body on account of the feature that the normalized difference water index (NDWI) greater than the normalized difference vegetation index (NDVI). Then we built the vector dataset of lake boundary with an area above 1.0 km2 in Qinghai Province after manual inspection and revision. Some attributes of the lake including its name, area, elevation, basin, administration and date were also attached. This dataset reflects the distribution of lakes in Qinghai Province in 2020, and can be used as a data source and scientific basis for researches on lake ecological protection, rational use of regional water resources, disaster prevention and mitigation in Qinghai Province.