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

ABSTRACT

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.

KEYWORDS:

• Lake level
• multi-altimeter
• China
• spatiotemporal variation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are openly available in the Science Data Bank at https://doi.org/10.57760/sciencedb.10395

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/20964471.2023.2295632.

Additional information

Funding

This research was supported by the National Natural Science Foundation of China [Grant 41871256].

Notes on contributors

Shanmu Ma

Shanmu Ma received the B.S. and M.S. degrees at China University of Geosciences, Beijing, respectively in 2019 and 2022. Currently, he is working toward the Ph.D. degree in cartography and geography information system at the Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. His research interests include satellite altimetry and hydrologic modeling.

Jingjuan Liao

Jingjuan Liao received the B.S. and M.S. degrees in geosciences from Nanjing University, respectively in 1987 and 1990, and the Ph.D. degree in geophysics from the Institute of Geophysics, Chinese Academy of Sciences in 1993. Since 1993, she has been working on radar remote sensing applications as a researcher at the Institute of Remote Sensing Applications, Chinese Academy of Sciences. She has rendered the institute great service in a number of research projects. Since 2007, she has been working on microwave remote-sensing application as a Professor with the Center for Earth Observation and Digital Earth and the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences. She is currently working at the Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. She has completed several research projects, and published more than 100 paper in relevant journals. Her current research interests include microwave scattering model, data processing, and surface parameters estimation.

Ruofan Jing

Ruofan Jing received his B.E. degree in Remote Sensing Science and Technology from China University of Geosciences, Wuhan, in 2023. Currently, he is pursuing the Ph.D. degree in cartography and geography information system at the Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. His research interests primarily focus on the altimetry data for land applications, especially on the lakes and rivers.

Jiaming Chen

Jiaming Chen received his M.S. degree at the Aerospace Information Research Institute, Chinese Academy of Sciences, China, in 2021. Currently, he is pursuing the Ph.D. degree with the Institute of Geodesy and Geoinformation, University of Bonn. His research interests primarily focus on monitoring water resource using SAR altimetry, including river discharge and lake volume changes.