A dataset of lake level changes in China between 2002 and 2023 using multi-altimeter data

Lake water levels are an important indicator of water balance and water cycles, and are essential for climate and environmental change studies and water resource evaluation. Currently, lake level measurements are scarce or inconsistent throughout the country, and traditional gauge measurements of many lakes are not feasible, so satellite altimetry is a vital alternative to gauge lake levels. However, the accuracy and sampling frequency of lake level time series are usually low because of time and space coverage limitations; therefore, it is necessary to utilize multi-altimeter data to monitor lake levels and obtain lake level changes over long time series. In this study, we extracted the water level changes in 988 lakes (>10 km2) in China between 2002 and 2023 based on ICESat/-2, Cryosat-2, Jason-1/2/3, and Sentinel-3A/3B altimetry data using waveform retracking, lake level extraction, lake level time series construction, the fusion of multi-altimeter lake level time series, and outlier removal. A total of 55% of the lakes in this dataset have been monitored for more than 10 years, and 34% have more than 12 times the annual average water level monitoring. At the same time, in situ data from 21 lakes were used for validation, and the average root mean square error (RMSE) for each of the datasets of ICESat/-2, Cryosat-2, Jason-1/2/3, and Sentinel-3A/3B versus the in situ lake levels are 0.223 m, 0.163 m, 0.207 m, 0.596 m, 0.295 m, 0.275 m, 0.243 m, and 0.317 m, respectively, and the mean RMSE of the fused lake levels reaches 0.332 m. During the monitoring period, the water levels in Chinese lakes generally increased. The overall annual average rate of change at the 20 and 10-year scales was 0.123 m/a and 0.151 m/a, respectively, among which the overall water levels in large lakes increased significantly. The lakes with a faster rate of decline in the water level were primarily small. The water storage in each lake region in China shows an upward trend, with the most significant increase in the Tibetan Plateau region, where the average annual water level change rate has remained above 0.15 m/a over the past two decades. This dataset has high spatiotemporal coverage and accuracy and can support the estimation of changes in lake water storage, analysis of lake level trends, plateau flooding, and the relationship between lake ecosystems and water resources.