A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018

Water clarity serves as a sensitive tool for understanding the spatial pattern and historical trend in lakes' trophic status. Despite the wide availability of remotely sensed data, this metric has not been fully explored for long-term environmental monitoring. To this end, we utilized Landsat top-of-atmosphere reflectance products within Google Earth Engine in the period 1984-2018 to retrieve the average Secchi disk depth (SDD) for each lake in each year. Three SDD datasets were used for model calibration and validation from different field campaigns mainly conducted during 2004-2018. The red / blue band ratio algorithm was applied to map SDD for lakes (> 0.01 km(2)) based on the first SDD dataset, where R-2 = 0.79 and relative RMSE (rRMSE) = 61.9 %. The other two datasets were used to validate the temporal transferability of the SDD estimation model, which confirmed the stable performance of the model. The spatiotemporal dynamics of SDD were analyzed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found the number of lakes with SDD <2 m accounted for the largest proportion (80.93 %) of the total lakes, but the total areas of lakes with SDD of <0.5 and >4 m were the largest, both accounting for about 24.00 % of the total lakes. During 1984-2018, lakes in the Tibetan-Qinghai Plateau region (TQR) had the clearest water with an average value of 3.32 +/- 0.38 m, while that in the northeastern region (NLR) exhibited the lowest SDD (mean 0.60 +/- 0.09 m). Among the 10 814 lakes with SDD results for more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia-Xinjiang region (MXR), more than half of the total lakes in every other region exhibited significant increasing trends. In the eastern region (ELR), NLR and Yungui Plateau region (YGR), almost more than 50 % of the lakes that displayed increase or decrease in SDD were mainly distributed in the area range of 0.01-1 km(2), whereas those in the TQR and MXR were primarily concentrated in large lakes (>10 km(2)). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset is freely available at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.271571, Tao et al., 2021).