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The landscape and landforms in permafrost regions are transforming due to climate change and permafrost thaw. This study uses optical and radar remote sensing, alongside spatial analysis, to examine thermokarst features and their driving factors in the source region of the Yangtze River (SRYR) on the central Tibetan Plateau. We analyse the distribution, interaction, and key environmental factors influencing thermokarst ponds and ground surface deformation, which are the two widespread and noticeable thermokarst features. Since the 1960s, the number of small water bodies has doubled from approximately ~2 × 104 to ~4 × 104 by the 2020s, with the median size of these water bodies decreasing from 2.3 × 104 m2 to 1.4 × 104 m2. The permafrost terrain has an average subsidence rate of 6.8 mm/a. About 50.9% of the SRYR exhibits evident thermokarst features. Surficial geological factors, especially geomorphology and slope, are primary factors in shaping the spatial distributions of thermokarst features. Both seasonal deformation and long‐term subsidence rates are more pronounced in areas with thermokarst ponds. However, once pond coverage exceeds around 5%, the amplifying effect on long‐term subsidence rates and seasonal deformation diminishes. The investigation further reveals that the relationship between seasonal deformation and long‐term subsidence is not strictly linear and that the combined increase in seasonal deformation and long‐term subsidence applies only to areas with seasonal deformation below approximately 20 mm. Beyond this threshold, the long‐term subsidence rate is no longer exacerbated by increased seasonal deformation. [ABSTRACT FROM AUTHOR]

Permafrost ground ice melting could alter hydrological processes in cold regions by releasing water. Currently, there is a lack of gridded data of ground ice from the Qinghai‐Tibet Plateau (QTP). Using 664 borehole sample records, we applied a random forest (RF) method to predict the ground ice content of permafrost between 2 and 10 m depth in three layers (2–3, 3–5, and 5–10 m) at a spatial resolution of 1 km. The RF predictions demonstrated an R2 value exceeding 0.80 for all three layers with a negligible positive overestimation (0.98%–1.85%). The ground ice content of the first layer (2–3 m) can be predicted primarily using climate variables, but the contribution of terrain and soil variables increases as the depth increases. The total water storage of ground ice across the QTP permafrost (2–10 m depth) is approximately 3330.0 km3, with 403.5 km3 in the 2–3 m layer, 857.2 km3 in the 3–5 m layer, and 2069.3 km3 in the 5–10 m layer. This study generated for the first time a gridded dataset of the shallow permafrost ground ice content across the entire QTP which can be used to improve simulations of hydrological processes in the permafrost regions. [ABSTRACT FROM AUTHOR]

The Qinghai‐Tibet Plateau (QTP) is the largest permafrost region in the world at low and middle latitudes and high elevation. Permafrost is being degraded on the QTP due to global warming, which has a significant effect on regional climate, hydrological, and ecological processes. This paper provides a summary of recent progress in methods used in permafrost research, the permafrost distribution, and basic data relevant to permafrost research on the QTP. The area of permafrost was 1.32 × 106 km2 over the QTP, which accounts for approximately 46% of the QTP. Moreover, simulation studies of the hydrothermal process and permafrost change were reviewed and evaluated the effect of permafrost degradation on hydrological and ecological processes. The results revealed that the effects of permafrost on runoff were closely related to soil temperature, and the effect of permafrost degradation on the carbon cycle requires further study. Finally, current challenges in simulation of permafrost change processes on the QTP were discussed, emphasizing that permafrost degradation under climate change is a slow and non‐linear process. This review will aid future studies examining the mechanism underlying the interaction between permafrost and climate change, and environmental protection in permafrost regions on the QTP. [ABSTRACT FROM AUTHOR]

The ground temperature at a fixed depth is a crucial boundary condition for understanding the properties of deep permafrost. However, the commonly used mean annual ground temperature at the depth of the zero annual amplitude (MAGTdzaa) has application limitations due to large spatial heterogeneity in observed depths. In this study, we utilized 231 borehole records of mean annual ground temperature at a depth of 15 meters (MAGT15m) from 2010 to 2019 and employed support vector regression (SVR) to predict gridded MAGT15m data at a spatial resolution of nearly 1 km across the Qinghai-Tibet Plateau (QTP). SVR predictions demonstrated a R2 value of 0.48 with a negligible negative overestimation (-0.01 °C). The average MAGT15m of the QTP permafrost was -1.85 °C (±1.58 °C), with 90% of values ranging from -5.1 °C to -0.1 °C and 51.2% exceeding -1.5 °C. The freezing degree days (FDD) was the most significant predictor (p<0.001) of MAGT15m, followed by thawing degree days (TDD), mean annual precipitation (MAP), and soil bulk density (BD) (p<0.01). Overall, the MAGT15m increased from northwest to southeast and decreased with elevation. Lower MAGT15m values are prevail in high mountainous areas with steep slopes. The MAGT15m was the lowest in the basins of the Amu Darya, Indus, and Tarim rivers (-2.7 to -2.9 °C) and the highest in the Yangtze and Yellow River basins (-0.8 to -0.9 °C). The baseline dataset of MAGT15m during 2010–2019 for the QTP permafrost will facilitates simulations of deep permafrost characteristics and provides fundamental data for permafrost model validation and improvement. [ABSTRACT FROM AUTHOR]

We develop a moving-mesh permafrost model that contains a ground subsidence computation module to estimate the effects of ground subsidence on permafrost simulation under different warming scenarios. Including the ground subsidence process in the permafrost simulation produces only a relatively small improvement in the simulation performance of the ground temperature field, as validated by observations from two sites on the Qinghai–Tibetan Plateau (QTP). It is shown that ignoring ground subsidence tends to achieve a larger active layer thickness (ALT) but a smaller original thickness of permafrost that has thawed when simulating permafrost changes in a warming climate. The heat consumed by permafrost changes will be underestimated in simulations that do not consider ground subsidence. The effects that ground subsidence exerts within the permafrost simulation are clearly demonstrated under a strong warming scenario, which will influence the global energy budget. Projections indicate that the permafrost in the continuous permafrost area of the QTP may be close to the phase transition temperature to become zero thermal gradients in 2030–2040 under the SSP5-8.5 scenario, and there will be a great risk of ground subsidence by that stage. For permafrost regions with rich ground ice, the downward propagating temperature signals caused by ground subsidence are more attenuated. However, the heat calculation error will be larger in a simulation that does not consider ground subsidence there. This study quantifies the effects of ground subsidence, which can provide a better understanding of the permafrost thaw and energy budget of the QTP. [ABSTRACT FROM AUTHOR]

The source region of the Yangtze River (SRYR, 1.4 × 105 km2 above Zhimenda station) on the Tibetan Plateau (TP) has 78% permafrost coverage. The streamflow depth increased at a rate of 2.5 mm/a since 2000. Quantification of the water contribution brought by permafrost thawing is a difficult task. In this study, we used Sentinel‐1 data and the SBAS‐InSAR technique to monitor terrain deformation from September 2016 to December 2021, and then utilized the long‐term deformation rate to assess ground ice meltwater release and the seasonal deformation to evaluate water storage in the active layer. Results reveal that 55.3% of the terrain in the SRYR has subsidence >2.5 mm/a, indicating widespread ground ice melting. The release rate of ground ice meltwater is 4.3 mm/a in the entire SRYR, above 6 mm/a at the Dangqu and Tuotuo River subbasins. The water release rate is relatively small (∼3%) in comparison to the streamflow depth of 151 mm per year during the investigation period of 2017–2021. We did not detect a strong increasing or decreasing trend among the 5‐year seasonal deformation, which reflects that the total soil water content in the active layer did not change significantly during the short investigation period. The results provide a data basis for ground ice richness and loss information in the SRYR and help to understand the impact of permafrost thawing on the regional water cycle in the permafrost environment. Plain Language Summary: The Yangtze River is the longest river in China; its source region (1.4 × 105 km2, above Zhimenda station) has 78% permafrost coverage and a 935 km3 ground ice reserve. The hydrological processes may have been significantly impacted by the permafrost degradation over the past few decades. This study presented a quantitative analysis of the effects of permafrost thawing on the water balance using terrain deformation derived from InSAR monitoring. Subsidence rates and seasonal deformation were first used combined to estimate permafrost thawing release water. The entire source region of the Yangtze River experienced extensive thaw subsidence and ground ice melting, and the rate of ground ice meltwater release was 4.3 mm per year during 2016–2021. The 5‐year seasonal deformation for 2017 to 2021 did not show strong increasing or decreasing trends. It suggests that the water storage in the active layer doesn't have significant changes. It may also suggest that most of the water from melting ground ice is released as surface or subsurface runoff and the supply to the active layer is small during the investigation period. Key Points: Quantitative analysis of the effects of permafrost thawing on the water balance in the permafrost‐affected watershedSubsidence rates and seasonal deformation were used combined to evaluate the amount of ground ice melting release waterRunoff depth of 4.3 mm/a by ground ice melting water and small variation of active layer water storage in the study area during 2016–2021 [ABSTRACT FROM AUTHOR]

The source region of the Yellow River (SRYR) is situated on the permafrost boundary in the northeast of the Qinghai-Tibet Plateau (QTP), which is an area highly sensitive to climate change. As a result of increasing global temperatures, the permafrost in this region has undergone significant degradation. In this study, we utilized Sentinel-1 to obtain ground surface deformation data in the SRYR from June 2017 to January 2022. We then analyzed the differences in terrain deformation under various environmental conditions. Our findings indicated an overall subsidence trend in the SRYR, with a long-term deformation velocity of −4.2 mm/a and seasonal deformation of 8.85 mm. Furthermore, the results showed that terrain deformation varied considerably from region to region, and that the Huanghe' yan sub-basin with the highest permafrost coverage among all sub-basins significantly higher subsidence rates than other regions. Topography strongly influenced ground surface deformation, with flat slopes exhibiting much higher subsidence rates and seasonal deformation. Moreover, the ground temperature and ground ice richness played a certain role in the deformation pattern. This study also analyzed regional deformation details from eight boreholes and one profile line covering different surface conditions, revealing the potential for refining the permafrost boundary. Overall, the results of this study provide valuable insights into the evolution of permafrost in the SRYR region. [ABSTRACT FROM AUTHOR]

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, 10.11888/Geocry.tpdc.271107, Lin et al., 2021). [ABSTRACT FROM AUTHOR]

Permafrost on the Qinghai–Tibet Plateau (QTP) has undergone degradation as a result of recent climate change. This may alter the thermo‐hydrological processes and unlock soil organic carbon, and thereby affect local hydrological, ecological, and climatic systems. The relationships between permafrost and climate change have received extensive attention, and in this paper we review climate change for permafrost regions of the QTP over the past 30 years. We summarize the current state and changes in permafrost distribution and thickness, ground temperature, and ground ice conditions. We focus on changes in permafrost thermal state and in active‐layer thickness (ALT). Possible future changes in ground temperature and ALT are also discussed. Finally, we discuss the changes in hydrological processes and to ecosystems caused by permafrost degradation. Air temperature and ground temperature in the permafrost regions of the QTP have increased from 1980 to 2018, and the active layer has been thickening at a rate of 19.5 cm per decade. The response of permafrost to climate change is not as fast as in some reports, and permafrost degradation is slower than projected by models that do not account for conditions deep in permafrost. [ABSTRACT FROM AUTHOR]

Warming permafrost on a global scale is projected to have significant impacts on engineering, hydrology and environmental quality. Greater warming trends are predicted on the Qinghai–Tibetan Plateau (QTP), but most models for mountain permafrost have not considered the effects of water phase change and the state of deep permafrost due to a lack of detailed information. To better understand historical and future permafrost change based on in situ monitoring and field investigations, a numerical heat conduction permafrost model was introduced which differentiated the frozen and thawed state of soil, and considered unfrozen water content in frozen soil, distribution of ground ice and geothermal heat flow. Simulations were conducted at two sites with validation by long‐term monitoring of ground temperature data. After forcing with reconstructed historical ground surface temperature series starting from 1966, the model predicted permafrost changes until 2100 under different RCP scenarios. The results indicate a slow thermal response of permafrost to climate warming at the two investigated sites. Even under the most radical warming scenario (RCP8.5), deepening of the permafrost table is not obvious before 2040. At both sites, the model indicates that shallow permafrost may disappear but deep permafrost may persist by 2100. Moreover, the simulation shows that the degradation modes may differ between zones of discontinuous and continuous permafrost. The main degradation mode of the site in the discontinuous zone appears to be upward thawing from the permafrost base, while that of the site in the continuous zone is downward thawing at the permafrost table with little change at the permafrost base. [ABSTRACT FROM AUTHOR]