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High-temporal-resolution Water Level and Storage Change Datasets for Lakes on the Tibetan Plateau Published

The Tibetan Plateau has a wide range of lakes and has shown a rapid trend of expansion in recent years. Information on water levels and storage changes in these lakes is important for understanding regional hydro-climatic interactions and their evolutionary patterns.

A high-temporal-resolution water level and storage change dataset for lakes on the Tibetan Plateau from 2000 to 2017, was recently published in Earth System Science Data by LI Xingdong (first author), LONG Di (correspondent author) from Tsinghua University and other collaborators. With Landsat archives and altimetry data, they developed water levels from lake shoreline positions and serve as an ideal reference for merging multisource lake water levels with systematic biases being removed. The dataset contains lake water level and storage change time series at weekly to monthly timescales for 52 large lakes (50 lakes larger than 150 km2 and 2 lakes larger than 100 km2) on the Tibetan Plateau during 2000–2017.

The results of field experiments and theoretical analyses consistently show that the RMSE (Root Mean Square Error) of the water level is in the range of 0.1-0.2 m, which is comparable to the accuracy of the in situ measurements, and that the uncertainty of the measured water level is also included in the dataset. This dataset can be applied to water resources and water safety management, lake basin hydrological analysis, water balance analysis, etc., with particular potential for lake overflow flood monitoring.

Spatial distribution of trends in lake storage on the Tibetan Plateau during 2000-2017

Currently, this dataset has been published in the National Tibetan Plateau Data Center and is freely available. The results were published in Earth System Science Data, in an article entitled as "High-temporal-resolution water level and storage change data sets for lakes on the Tibetan Plateau during 2000-2017 using multiple altimetric missions and Landsat-derived lake shoreline positions".

This research was funded by the National Natural Science Foundation of China (Grant No. 91547210) and the National Key R&D Program (Grant No. 2017YFC0405801), among other projects.

Data available at: https://data.tpdc.ac.cn/en/data/a319ca66-f8ff-4734-8565-474bfb30ca86/

Full-text available at: https://www.earth-syst-sci-data.net/11/1603/2019