Lake Water Footprint Determination Using Linear Clustering-Based Algorithm and Lake Water Changes in the Tibetan Plateau from 2002 to 2020

Satellite altimetry is an effective technique for monitoring water level changes in inland lakes in remote areas, such as the Tibetan Plateau. Lake water footprint (LWF) determination from tracks of satellite altimetry data is a preliminary step for generating lake water level sequences. However, the traditional method of LWF determination using accurate lake boundaries extracted from remote sensing images is laborious, and the images do not always exist. Another method dedicated to a single satellite altimeter sensor; i.e., physical parameter-based algorithm has been designed, but this method sometimes fails when data are influenced by surroundings such as wetlands or glaciers. To overcome these problems, we present a novel linear clustering-based approach for LWF determination to generate a time series of lake water levels by using multi-mission satellite altimetry data sets over typical lakes of the Tibetan Plateau. Our method projects all footprints onto two matrices. This approach is then illustrated using Ice, Cloud, and land Elevation Satellite, Environmental Satellite, and CtyoSat-2 altimetry data sets for four typical lakes in the Tibetan Plateau. Among all the methods, our method performs best in terms of accuracy. Finally, the time series lake water levels of 179 lakes in the Tibetan Plateau were extracted using our method. The results indicate that from 2002 to 2020, the average water level of most lakes increased by 0.167 +/- 0.155 m/a, whereas a decreasing trend of 0.066 +/- 0.047 m/a was observed in the Yarlung Zangbo river basin. The different precipitation conditions in the inner basin and the Yarlung Zangbo river basin are suggested to be the major reasons for the opposite trends. The proposed method performs well for Tibetan lakes with planar water stages and small seasonal fluctuations but is not applicable for lakes with other conditions, which requires further study.

Automated summary

Satellite altimetry is an effective technique for monitoring water level changes in remote inland lakes, such as the Tibetan Plateau. A novel linear clustering-based approach for lake water footprint (LWF) determination using multi-mission satellite altimetry data sets is proposed. The method performs best in terms of accuracy and shows that most lakes on the Tibetan Plateau have seen an increase in water level while the Yarlung Zangbo river basin has experienced a decreasing trend, which is attributed to different precipitation conditions.