The thermal stability of permafrost, a foundation for engineering infrastructure in cold regions, is increasingly threatened by the dual stressors of climate change and anthropogenic disturbance. This study investigates the dynamics of the crushed rock revetted embankment at the Kunlun Mountain Section of the Qinghai-Tibet Railway, systematically investigating the coupled impacts of climate warming and engineering activities on permafrost thermal stability using borehole temperature monitoring data (2008-2024) and climatic parameter analysis. Results show that under climate-driven effects, the study area experienced an air temperature increase of 0.2 degrees C per decade over the 2015-2024. Concurrently, the mean annual air thawing degree-days (TDD) rose by 13.8 degrees C center dot d/a, leading to active-layer thickening at a rate of 3.8 cm center dot a- 1at natural ground sites. From 2008 to 2024, the active layer had thickened by 0.7-0.8 m. At the embankment toe (BH 5), the active-layer thickening rate (3.3 cm center dot a- 1) was 25 % lower than that at the natural ground borehole (3.8 cm center dot a- 1); correspondingly, the underlying permafrost temperature increase rate at the toe (0.3 degrees C per decade) was lower than that at the natural borehole (0.5-0.6 degrees C per decade). Permafrost warming rates decreased with depth. Shallow layers (above -2 m) were significantly influenced by climate, with warming rates of 0.3-0.6 degrees C per decade. In contrast, deep layers (below -10 m) showed warming rates converging with the background atmospheric temperature trend (0.2 degrees C per decade). Thermal regime disturbance was most pronounced at horizontal distances of 3.0-5.0 m from the embankment. Nevertheless, the crushed-rock revetment maintained a permafrost table 0.6 m shallower than that of natural ground, confirming its thermal diode effect (facilitating convective cooling in winter), which partially offset climate warming impacts. This study provides critical empirical data and validates the cooling mechanism of crushed-rock revetment, which is essential for predicting the long-term thermal stability and informing adaptive maintenance strategies for railway infrastructure in warming permafrost regions.

The response of Arctic vegetation to climate warming exhibits pronounced spatial heterogeneity, driven partly by widespread permafrost degradation. However, the role of thermokarst lake development in mediating vegetation-climate interactions remains poorly understood, particularly across heterogeneous landscapes of northeastern Siberia. This study integrated multi-source remote sensing data (2001-2021) with trend analysis, partial correlation, and a Shapley Additive Explanation (SHAP)-interpreted random forest model to examine the drivers of normalized difference vegetation index (NDVI) variability across five levels of thermokarst lake coverage (none, low, moderate, high, very high) and two vegetation types (forest, tundra). The results show that although greening dominates the region, browning is disproportionately observed in areas with high thermokarst lake coverage (>30%), highlighting the localized reversal of regional greening trends under intensified thermokarst activity. Air temperature was identified as the dominant driver of NDVI change, whereas soil temperature and soil moisture exerted secondary but critical influences, especially in tundra ecosystems with extensive thermokarst lake development. The relative importance of these factors shifted across thermokarst lake coverage gradients, underscoring the modulatory effect of thermokarst processes on vegetation-climate feedbacks. These findings emphasize the necessity of incorporating thermokarst dynamics and landscape heterogeneity into predictive models of Arctic vegetation change, with important implications for understanding cryospheric hydrology and ecosystem responses to ongoing climate warming.

The Three-Rivers Headwater Region (TRHR) is located on the Tibetan Plateau, within a transitional zone between seasonally frozen ground and continuous permafrost. Over 70 % of the region is predominantly covered by alpine grasslands, a vulnerable ecosystem increasingly threatened by ongoing permafrost degradation. This study utilized satellite data to analyze permafrost degradation by measuring active layer thickness (ALT) and the soil non-frozen period (NFP), and to investigate their impacts on alpine grassland growth. Results showed significant permafrost degradation from 2000 to 2020, with ALT thickening at a rate of 7.79 cm/decade (p < 0.05) and NFP lengthening by 1.1 days/yr (p < 0.05). Simultaneously, grassland vegetation exhibited a significant greening trend (0.0014 yr(-1), p < 0.01). Using the partial least squares (PLS) regression method, the study evaluated the relationships between grassland dynamics and permafrost degradation, while jointly accounting for climate variables (temperature, precipitation, and sunshine duration). ALT thickening was the dominant explanatory variable for grassland growth in 11.09 % of the region, and it was positively correlated in relatively cold western and alpine areas, but negatively correlated in the relatively warm eastern and central regions. NFP extension was the dominant explanatory variable for grassland growth in 10.38 % of the region, although its positive correlation weakened as climate conditions transitioned from relatively cold-dry to relatively warm-wet. Although permafrost degradation was positively correlated with grassland greening in relatively cold regions, the diminishing benefit of NFP extension and the adverse effects of ALT thickening may increasingly undermine grassland stability in relatively warm regions under further climate warming.

Thawing permafrost, driven by climate change and anthropogenic activities, presents escalating challenges for infrastructure in northern regions. Traditional design strategies focused on maintaining frozen ground are increasingly unsustainable due to accelerated warming and extreme weather events. This paper introduces a Thaw Settlement Evaluation Framework for assessing thaw settlement at regional and site-specific scales. The framework comprises (1) regional thaw settlement hazard assessments to identify zones prone to thaw settlement and (2) site-specific thaw strain estimations for quantitative settlement predictions. By consolidating established methodologies, such as thaw hazard indices and empirical thaw strain estimation tools, the framework provides adaptable workflows tailored to the specific needs and data availability of the project. Key outputs include thaw settlement hazard levels, thaw strain estimation, and stress-strain characterization, which together offer actionable insights to support infrastructure planning, design, and maintenance in permafrost regions. By consolidating resources and streamlining decision-making, the framework equips practitioners, planners, and decision-makers with practical guidance to address challenges of thawing permafrost.

Understanding soil organic carbon (SOC) distribution and its environmental controls in permafrost regions is essential for achieving carbon neutrality and mitigating climate change. This study examines the spatial pattern of SOC and its drivers in the Headwater Area of the Yellow River (HAYR), northeastern Qinghai-Xizang Plateau (QXP), a region highly susceptible to permafrost degradation. Field investigations at topsoils of 86 sites over three summers (2021-2023) provided data on SOC, vegetation structure, and soil properties. Moreover, the spatial distribution of key permafrost parameters was simulated: temperature at the top of permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freezing depth (MSFD) using the TTOP model and Stefan Equation. Results reveal a distinct latitudinal SOC gradient (high south, low north), primarily mediated by vegetation structure, soil properties, and permafrost parameters. Vegetation coverage and above-ground biomass showed positive correlation with SOC, while soil bulk density (SBD) exhibited a negative correlation. Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. These findings likely enhance the understanding of carbon storage controls in vulnerable alpine permafrost ecosystems and provide insights to mitigate carbon release under climate change.

Aeolian sand, as a primary medium of desertification, changes surface energy budgets and consequently affects both ecological systems and infrastructure stability on the Tibetan Plateau. Accurate interpretation of upper boundary conditions is critical for assessing aeolian sand's effects on subsurface hydrothermal processes. Nevertheless, current numerical simulations typically rely on empirical thermal boundaries and neglect surface radiation components and latent heat exchange, causing, significant deviations between simulations and field observations. This study establishes a thermal boundary model to calculate net surface energy (Q) based on energy balance theory and 13 sets of reflectance experiments. Using meteorological data from 2003 to 2019, soil temperature evolution was simulated under three aeolian sand coverage conditions: dry, 5 % moisture, and 10 % moisture. Results indicated that the simulated outputs exhibit strong correlations with observed data in terms of trend direction, phase timing of peaks and troughs, and temperature amplitude (R > 0.93, p < 0.0001). At the sand-atmosphere interface (-0.05 m), the annual mean temperature under dry aeolian sand cover reached 5.300 degrees C, which is 4.823 degrees C higher than that of the exposed surface (0.477 degrees C) during 2005-2006. When including moisture, the latent heat-driven cooling effect became evident, and the annual mean temperature at the sand surface dropped significantly to 0.930 degrees C (5 % moisture) and 1.461 degrees C (10 % moisture). More importantly, moisture cooling effects in shallow layers (-0.05 to-0.4 m) exhibit non-monotonic behavior: 10 % moisture yields higher annual mean temperatures than 5 % moisture (e.g., 1.370 degrees C vs. 0.858 degrees C at-0.2 m), suggesting aeolian sand's thermal impact on underlying permafrost involves critical moisture thresholds.

Highlights What are the main findings? A density-based Freeze-Thaw Disturbance Index (FTDI) was proposed to quantify the spatial clustering of disturbance features. Higher FTDI values indicate a greater likelihood of surface thawing processes triggered by rising temperatures. What are the implications of the main findings? Regions with relatively high FTDI values often contain substantial amounts of organic carbon and may experience delayed vegetation green-up despite general warming trends. FTDI reflects the impact of potential freeze-thaw dynamic phase changes on the geomorphology and offers a new perspective for monitoring permafrost degradation.Highlights What are the main findings? A density-based Freeze-Thaw Disturbance Index (FTDI) was proposed to quantify the spatial clustering of disturbance features. Higher FTDI values indicate a greater likelihood of surface thawing processes triggered by rising temperatures. What are the implications of the main findings? Regions with relatively high FTDI values often contain substantial amounts of organic carbon and may experience delayed vegetation green-up despite general warming trends. FTDI reflects the impact of potential freeze-thaw dynamic phase changes on the geomorphology and offers a new perspective for monitoring permafrost degradation.Abstract The soil freeze-thaw process is a dominant disturbance in the seasonally frozen ground and the active layer of permafrost, which plays a crucial role in the surface energy balance, water cycle, and carbon exchange and has a pronounced influence on vegetation phenology. This study proposes a novel density-based Freeze-Thaw Disturbance Index (FTDI) based on the identification of the freeze-thaw disturbance region (FTDR) over the Qinghai-Tibet Plateau (QTP). FTDI is defined as an areal density metric based on geomorphic disturbances, i.e., the proportion of FTDRs within a given region, with higher values indicating greater areal densities of disturbance. As a measure of landform clustering, FTDI complements existing freeze-thaw process indicators and provides a means to assess the geomorphic impacts of climate-driven freeze-thaw changes during permafrost degradation. The main conclusions are as follows: the FTDR results that are identified by the random forest model are reliable and highly consistent with ground observations; the FTDRs cover 8.85% of the total area of the QTP, and mainly in the central and eastern regions, characterized by prolonged freezing durations and the average annual ground temperature (MAGT) is close to 0 degrees C, making the soil in these regions highly susceptible to warming-induced disturbances. Most of the plateau exhibits low or negligible FTDI values. As a geomorphic indicator, FTDI reflects the impact of potential freeze-thaw dynamic phase changes on the surface. Higher FTDI values indicate a greater likelihood of surface thawing processes triggered by rising temperatures, which impact surface processes. Regions with relatively high FTDI values often contain substantial amounts of organic carbon, and may experience delayed vegetation green-up despite general warming trends. This study introduces the FTDI derived from the FTDR as a novel index, offering fresh insights into the study of freeze-thaw processes in the context of climate change.

Suprapermafrost groundwater (SPG) plays a critical role in hydrological and ecological functioning of permafrost regions, yet its spatiotemporal dynamics and controlling mechanisms remain poorly understood on the Qinghai-Tibet Plateau (QTP). Here, we integrated in situ observations, geophysical surveys, and machine learning (ML) models (including XGBoost, LightGBM, and RandomForest) to investigate the seasonal variation, drivers, and projections of SPG dynamics in alpine meadow (AM) and alpine wet meadow (AWM) ecosystems. Results showed that SPG tables ranged from -1.1 to -0.1 m in AM and from -1.3 to -0.2 m in AWM during the warm season. SPG fluctuations were primarily driven by thaw depth (TD) and rainfall infiltration and exhibited similar seasonal patterns across both ecosystems. A greater TD was associated with a deeper SPG table, as deeper thawing expanded the unsaturated zone and enhanced vertical drainage, indicating an exponential relationship between TD and SPG table position, and a linear relationship with aquifer thickness. In contrast, rainfall infiltration increased shallow soil moisture and elevated SPG tables, with responses influenced by rainfall intensity, duration, and infiltration pathways. Spatial heterogeneity in SPG distribution was further shaped by vegetation structure and microtopographic variation. Furthermore, ML models projected that mean summer SPG table depths in the 2090s would increase by 0.06 m under SSP126 and 0.64 m under SSP585 in AWM ecosystems, and by 0.37 m under SSP126 and 0.87 m under SSP585 in AM ecosystems. These findings provide new insights into how climate warming affects hydrological processes in permafrost regions of the QTP.

Thawing permafrost alters climate not only through carbon emissions but also via energy-water feedback and atmospheric teleconnections. This review focuses on the Tibetan Plateau, where strong freeze-thaw cycles, intense radiation, and complex snow-vegetation interactions constitute non-carbon climate responses. We synthesize recent evidence that links freeze-thaw cycles, ground heat flux dynamics, and soil moisture hysteresis to latent heat feedback, monsoon modulation, and planetary wave anomalies. Across these pathways, both observational and simulation studies reveal consistent signals of feedback amplification and nonlinear threshold behavior. However, most Earth system models underrepresent these processes due to simplifications in freezethaw processes, snow-soil-vegetation coupling, and cross-seasonal memory effects. We conclude by identifying priority processes to better simulate multi-scale cryosphere-climate feedback, especially under continued climate warming in high-altitude regions.

Permafrost degradation, driven by the thawing of ground ice, results in the progressive thinning and eventual loss of the permafrost layer. This process alters hydrological and ecological systems by increasing surface and subsurface water flow, changing vegetation density, and destabilising the ground. The thermal and hydraulic conductivity of permafrost are strongly temperature-dependent, both increasing as the soil warms, thereby accelerating thaw. In addition, thawing permafrost releases large quantities of greenhouse gases, establishing a feedback loop in which global warming both drives and is intensified by permafrost loss. This paper reviews the mechanisms and consequences of permafrost degradation, including reductions in strength and enhanced deformability, which induce landslides and threaten the structural integrity of foundations and critical infrastructure. Permafrost has been investigated and modelled extensively, and various approaches have been devised to address the consequences of thawing permafrost on communities and the built environment. Some techniques focus on keeping the ground frozen via insulation, while others propose local replacement of permafrost with more stable materials. However, given the scale and pace of current changes, systematic remediation appears unfeasible. This calls for increased efforts towards adaptation, informed by interdisciplinary research.