The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated this map using various ground-based data sets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and soil properties (moisture content and bulk density). The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution. Permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06 × 10⁶ km² (0.97–1.15 × 10⁶ km², 90 % confidence interval) (40 %), 1.46 × 10⁶ (56 %), and 0.03 × 10⁶ km² (1 %), respectively, excluding glaciers and lakes. Ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) were used to validate the model. Validation results showed that the kappa coefficient varied from 0.38 to 0.78 with a mean of 0.57 for the five IRs and 0.62 to 0.74 with a mean of 0.68 within the three transects. Compared with earlier studies, the TTOP modelling results show greater accuracy. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.

Permafrost has great influences on the climatic, hydrological, and ecological systems on the Qinghai–Tibet Plateau (QTP). The changing permafrost and its impact have been attracting great attention worldwide like never before. More observational and modeling approaches are needed to promote an understanding of permafrost thermal state and climatic conditions on the QTP. However, limited data on the permafrost thermal state and climate background have been sporadically reported in different pieces of literature due to the difficulties of accessing and working in this region where the weather is severe, environmental conditions are harsh, and the topographic and morphological features are complex. From the 1990s, we began to establish a permafrost monitoring network on the QTP. Meteorological variables were measured by automatic meteorological systems. The soil temperature and moisture data were collected from an integrated observation system in the active layer. Deep ground temperature (GT) was observed from boreholes. In this study, a comprehensive dataset consisting of long-term meteorological, GT, soil moisture, and soil temperature data was compiled after quality control from an integrated, distributed, and multiscale observation network in the permafrost regions of QTP. The dataset is helpful for scientists with multiple study fields (i.e., climate, cryospheric, ecology and hydrology, meteorology science), which will significantly promote the verification, development, and improvement of hydrological models, land surface process models, and climate models on the QTP. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center (https://data.tpdc.ac.cn/en/disallow/789e838e-16ac-4539-bb7e-906217305a1d/, last access: 24 August 2021, https://doi.org/10.11888/Geocry.tpdc.271107, Lin et al., 2021).

Selin Co, located within permafrost regions surrounded by glaciers, has exhibited the greatest increase in water storage among all the lakes on the Tibetan Plateau over the last 50 years. Most of the increased lake water volume has been attributed to increased precipitation and the accelerated melting of glacier ice, but these processes are still not sufficient to close the water budget with the expansion of Selin Co. Ground ice meltwater released by thawing permafrost due to continuous climate warming over the past several decades is regarded as another source of lake expansion. This study presents the first attempt to quantify the water contribution of ground ice melting to the expansion of Selin Co by evaluating the ground surface deformation. We monitored the spatial distribution of surface deformation in the Selin Co basin using the small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) technique and compared the results with the findings of field surveys. Then, the ground ice meltwater volume in the watershed was calculated based on the cumulated settlement. Finally, this volume was compared with the lake volume change during the same period, and the contribution ratio was derived. SBAS-InSAR monitoring during 2017–2020 illustrated widespread and large subsidence in the upstream section of the Zhajiazangbu subbasin, where widespread continuous permafrost is present. The terrain subsidence rate was normally between 5 and 20 mm a⁻¹, indicating rapid ground ice loss in the region. The ground ice meltwater was released at a rate of $\sim \mathrm{57}\times {\mathrm{10}}^{\mathrm{6}}$ m³ a⁻¹, and the rate of increase in lake water storage was $\sim \mathrm{485}\times {\mathrm{10}}^{\mathrm{6}}$ m³ a⁻¹ during the same period, with ground ice meltwater contributing ∼12 % of the lake volume increase. This study contributes to explaining the rapid expansion of Selin Co and equilibrating the water balance at the watershed scale. More importantly, the proposed method can be extended to other watersheds underlain by permafrost and help in understanding the hydrological changes in these watersheds.