Understanding the impact of snow phenology on vegetation carbon sequestration is crucial for evaluating ecosystem responses to climate change. This is particularly important in arid and semi-arid regions of Xinjiang， where snowmelt serves as one of the region’s major water resources. Based on global daily carbon flux simulation data from 2001 to 2018 and the AVHRR China snow phenology dataset， this study analyzed the spatiotemporal variation characteristics of vegetation carbon sequestration indicators such as gross primary production （GPP） and net primary production （NPP） in Xinjiang， and snow phenology parameters such as snow cover days （SCD）， snow cover start dates （SCS）， and snow cover melt dates （SCM） in Xinjiang using Theil-Sen Median trend analysis， Mann-Kendall test， geodetector， and partial correlation analysis. Additionally， the impact of snow phenology in Xinjiang on the spatial differentiation and temporal variation of vegetation carbon sequestration was explored. The results showed that： （1） From 2001 to 2018， the carbon sequestration of vegetation in Xinjiang showed an overall increasing trend. Among them， from 2001 to 2007， the GPP and NPP of vegetation in Xinjiang decreased at a temporal rate of 9.83 gC⋅m^-2⋅a^-1 and 5.1 gC⋅m^-2⋅a^-1， respectively， and the areas with significant spatial decreasing trends accounted for 38.78% and 36.50%， respectively. From 2007 to 2018， the GPP and NPP of vegetation in Xinjiang increased at a temporal rate of 6.62 gC⋅m^-2⋅a^-1 and 3.26 gC⋅m^-2⋅a^-1， respectively， with areas showing significant spatial increasing trends accounting for 48.05% and 49.84%， respectively. From 2001 to 2018， the SCS in Xinjiang showed a trend of first delaying and then advancing， the SCM showed a trend of first advancing and then delaying， and the SCD showed a trend of first decreasing and then increasing. （2） The results of the geodetector showed that the interaction between any two driving factors had a greater impact on GPP and NPP than a single factor， showing nonlinear enhancement or two-factor enhancement. Among them， the interactions between snow phenology and elevation， vegetation type， and temperature were mainly nonlinear enhancement， while the interaction with precipitation and solar radiation exhibited mainly two-factor enhancement. The interaction between topography and snow phenology had the highest explanatory power for the spatial differentiation of vegetation carbon sequestration. （3） Partial correlation results showed that the response of vegetation carbon sequestration in Xinjiang to snow phenology exhibited a “positive and negative coexistence” characteristic. Overall， vegetation GPP and NPP were mainly negatively correlated with the SCS， with the proportions of pixels showing significant negative correlation being 10.01% and 11.27%， respectively. Vegetation GPP and NPP were mainly positively correlated with the SCM， with the proportions of pixels demonstrating significant positive correlation being 13.73% and 10.86%， respectively. Additionally， vegetation GPP and NPP were primarily positively correlated with the SCD， of which the proportion of pixels with significant positive correlation was 11.14% and 13.35%， respectively. This indicated that an earlier SCS， a delayed SCM， and an increased SCD were more conducive to vegetation growth and carbon absorption. These findings help deepen our understanding of the impact of snow phenology on vegetation carbon sequestration under climate warming. They provide a reference for the evaluation of terrestrial carbon sinks and ecological support capacity， as well as for the formulation of ecologically sustainable development policies， offering a theoretical basis for ecological protection and sustainable development in Xinjiang.

The Laptev Sea， as a typical marginal sea of the Arctic Ocean， occupies a pivotal position within the Arctic climate system and marine environment. This region functions as a critical zone for Arctic sea ice formation， freshwater input， and land-ocean heat exchange. Its unique geographical location not only regulates the surface freshwater flux and heat budget of the North Atlantic but also modulates key biogeochemical processes in the Arctic， such as nutrient cycling， primary productivity， and carbon transport. Furthermore， as a strategic hub of the Arctic Northeast Passage， the dynamic characteristics of its sea ice directly determine the navigational potential of the route. Consequently， a comprehensive analysis and systematic review of the multi-dimensional characteristics of sea ice are imperative for fully understanding the mechanisms of sea ice change in the Laptev Sea. This study integrated multi-source observational data to systematically investigate the spatiotemporal evolution of total sea ice area， fast ice area， floating ice area， sea ice thickness， and sea ice age in the Laptev Sea from 1979 to 2024. Additionally， by incorporating model data， this study elucidated and summarized the driving mechanisms of sea ice change in this region and their ecological and environmental effects. The results showed that from 1979 to 2024， the total sea ice area in the Laptev Sea exhibited a significant decreasing trend during the melting season （June-October）， with the largest decline rate observed in October， reaching 0.95×10⁴ km² a^-1. Additionally， the fast ice area exhibited a continuous shrinking trend， with the most pronounced decrease in July， reaching 0.14×10 ⁴ km² a^-1. The fast-ice-free period extended from 78.4 days in the 1980s to 111.2 days in the past decade， and the date of complete ablation advanced by an average of 22.8 days. The floating ice area exhibited a significant decreasing trend during the melting season， whereas it showed an increasing trend during the freezing season （December-January）， reflecting an enhanced conversion from fast ice to floating ice. The floating ice thickness showed thinning trends of 0.13 m per decade in April and 0.23 m per decade in August， and the ice age structure exhibited a trend toward younger ice. Sea ice change in the Laptev Sea was jointly driven by coupled atmosphere-ocean forcing. Among atmospheric factors， offshore wind fields， the Arctic Oscillation （AO）， and the Arctic Dipole （AD） mode influenced sea ice dynamics through momentum and heat transport. At the oceanic level， the enhanced heat flux induced by Atlantification （with a 400% increase in winter over the past two decades） significantly altered the thermodynamic balance during the freezing season. The synergistic effects of meridional winds and warm， humid air masses during the melting season significantly accelerated sea ice ablation， whereas the freezing season was dominated by thermal processes. Due to its unique functions in sea ice export， entrainment of terrestrial sediments， and regulation of permafrost， the Laptev Sea has become a key node connecting the Arctic and the global climate system. The persistent retreat of sea ice in this region laid the foundation for the commercial operation of the Arctic Northeast Passage. Finally， this study summarized the key future research directions for sea ice in the Laptev Sea， including critical scientific issues such as the analysis of sea ice dynamic mechanisms， the feedback effects of sea ice anomalies on the Arctic climate system， and the prediction of route navigability. This study provides theoretical references and directional guidance for interdisciplinary research in the context of rapid Arctic change.

Against the backdrop of the ongoing implementation of the Belt and Road Initiative， infrastructure construction in cold regions of China has entered a phase of rapid development. Influenced by the unique climatic environment in cold regions， rock mass engineering faces severe challenges. Diurnal and seasonal freeze-thaw cycles cause repeated ice-water phase transitions in water contained within the pores and fractures of rock masses， generating frost heave stress accompanied by complex moisture migration. This leads to the initiation， propagation， and interconnection of micro-cracks inside the rocks， resulting in significant degradation of their macroscopic mechanical properties. Investigating the evolution mechanisms of mesoscopic structural damage in sandstone under the coupled action of freeze-thaw cycles and mechanical loading holds significant theoretical value and practical engineering implications. Taking freeze-thaw sandstone as the research object， in-situ CT monitoring tests on sandstone under freeze-thaw cycles were systematically conducted. Based on deep learning algorithms， a fully convolutional network （FCN） architecture was integrated with the representative elementary volume （REV） theory to develop a multiscale characterization method linking mesoscopic and macroscopic damage throughout the entire uniaxial compression process of freeze-thaw sandstone. This method accurately extracted the actual mesostructures of internal fractures and their geometric parameters in sandstone. It revealed the controlling mechanisms of freeze-thaw cycles on the anisotropic deterioration of the rock mass， and clarified the cross-scale correlation between micropore reorganization and macroscopic mechanical response. The main contributions and conclusions were as follows. （1） The freeze-thaw rock damage identification algorithm based on the FCN achieved high-precision automatic segmentation of the internal pore （fracture） network in freeze-thaw rocks， enabling quantitative identification of mesoscopic damage. （2） A voxel size of 350×350×350 was selected as the minimum REV. The variations in connected porosity across scanning layers of freeze-thaw sandstone under uniaxial compression were obtained. The sharp increase in internal connected pores of freeze-thaw rocks led to sudden failure under compressive loading. （3） Under identical loading conditions， sandstone subjected to a greater number of freeze-thaw cycles exhibited faster growth in bulk porosity and more rapid internal damage development. The sudden increase in bulk porosity was directly related to the loss of rock strength， serving as a sensitive indicator for predicting failure. （4） A pore-throat network model was established using the maximal ball method. Quantitative analysis of the three-dimensional reconstructed REV of freeze-thaw sandstone indicated that the number of pore-throats inside the rock samples increased significantly under freeze-thaw cycles. Pore-throats were the main pathways for the transmission of frost heave force and damage propagation. The pore-throat system evolved dynamically， transitioning from an increase in frost-induced small pores to an increase in load-assisted medium pores， and finally to large pores before peak stress. （5） The failure process of freeze-thaw rocks under uniaxial compressive loading was essentially the result of the synergistic evolution of pore structure expansion and throat network reorganization. This process induced progressive damage accumulation. Ultimately， dominated by the pore coalescence effect， the percolation channel network formed rapidly， leading to the instability and failure of the rock samples. The coupling action of freeze-thaw cycles and loading profoundly influenced the evolution path of pore structures and failure modes. These findings provide a scientific basis for the stability assessment of rock engineering in cold regions.

Snow Water Equivalent （SWE） is a critical hydrological variable for assessing the water content stored in snowpacks， particularly in alpine and high-altitude regions like the Qinghai-Xizang Plateau. Given the region’s complex topography， harsh climatic conditions， and the scarcity of in-situ snow measurements， SWE estimation remains a major scientific challenge. This study presents a novel hybrid framework that combines physical modeling and deep learning to simulate daily SWE across the Qinghai-Xizang Plateau， offering a new technical pathway for SWE estimation under data-scarce conditions. The proposed methodology integrates two core models. First， the Factorial Snow Model （FSM）， a physically based process model， is employed to simulate daily snow depth. FSM uses meteorological inputs including air temperature， precipitation， radiation， humidity， wind speed， and pressure to simulate key snowpack processes such as accumulation， compaction， energy exchange， and melt. Second， snow density is estimated using a CNN-BiLSTM-Attention model， which leverages Convolutional Neural Networks （CNN） to extract local spatiotemporal features， Bidirectional Long Short-Term Memory networks （BiLSTM） to capture forward and backward temporal dependencies， and an attention mechanism to dynamically emphasize the most influential features across time steps. Meteorological and snow density data were obtained from ERA5 reanalysis datasets spanning 1979 to 2014. Six key input variables were selected via Pearson correlation analysis： longwave radiation， snowfall， rainfall， temperature， wind speed， and relative humidity. The CNN-BiLSTM-Attention model was trained on data from 1979 to 2003 and tested on data from 2004 to 2014. The model achieved strong predictive performance， with MSE=71.66 kg⋅m^-3， RMSE=8.465 kg⋅m^-3， MAE=6.378 kg⋅m^-3， MAPE=4.556， and R ²=0.732， indicating its high accuracy in modeling snow density over long timescales. SWE was calculated by multiplying simulated snow depth from FSM with snow density predicted by the deep learning model. The daily SWE time series from 2006 to 2014 revealed clear seasonal patterns. SWE begins accumulating in October， peaks between December and February， and melts rapidly from March to May. The average daily SWE across the historical period was 0.278 cm， with a maximum of 0.838 cm observed in late December， reflecting the seasonal snow accumulation and melt dynamics typical of the region. The modeled SWE was further validated against two reference datasets： a high-resolution 0.01° SWE dataset and a 0.25° national fused SWE product. Comparisons showed that the proposed model closely tracked observed seasonal and interannual SWE trends， particularly during the critical accumulation and melt periods. It exhibited better agreement with high-resolution data than with coarser products， especially in representing peak values and transitional dynamics. This study introduces an effective and scalable method for SWE estimation in regions lacking dense observational networks. By decoupling the estimation of snow depth and snow density and applying specialized models to each， the framework combines the physical interpretability of FSM with the pattern recognition strength of deep learning. This hybrid modeling approach captures both the mechanistic and statistical characteristics of snowpack evolution， providing a reliable basis for snow resource evaluation. The CNN-BiLSTM-Attention model， which has rarely been applied to snow density modeling before， demonstrated a strong ability to model complex spatiotemporal interactions. When integrated with FSM， it forms a robust and adaptable modeling system that can be generalized to other alpine or cryospheric environments. The results provide valuable support for snow hydrology， water resource planning， and climate change impact assessment on the Qinghai-Xizang Plateau and similar high-mountain regions.

Snow depth is a fundamental parameter in hydrology， cryosphere science， weather forecasting， and climate modeling. Accurate monitoring of snow depth is essential for water resource management， natural hazard assessment， and climate change prediction. Passive microwave remote sensing， owing to its strong penetration capability， enables all-weather and all-time observation of the land surface， providing significant advantages for snow depth estimation. The first passive microwave snow depth retrieval algorithm was proposed by Chang et al. in 1987. Since then， numerous snow depth and snow water equivalent products based on passive microwave data have been developed. However， due to differences in retrieval algorithms， results from these snow products often show significant discrepancies. The Fengyun-3 （FY-3） satellite series， China’s first system to provide multi-frequency passive microwave remote sensing data， has played a vital role in improving the autonomy and reliability of climate monitoring. The operational satellites in this series currently include FY-3B， FY-3C， and FY-3D， each of which operates in both descending and ascending orbits. Snow depth retrieval algorithms have been developed using FY-3B and FY-3D microwave brightness temperature data， but their results are inconsistent. Furthermore， the compatibility of other snow depth retrieval algorithms with FY-3 series satellite data requires further investigation and validation. To explore the compatibility of different snow depth algorithms in China， this study applied three typical remote sensing algorithms—KELLY， CHE， and JIANG—to retrieve snow depth from FY-3 MWRI data. The accuracy of these algorithms was evaluated against in situ snow depth measurements from meteorological stations between 2010 and 2019， and the causes of discrepancies were analyzed. The performance and applicability of the KELLY， CHE， and JIANG algorithms were evaluated in three regions—Inner Mongolia-Northeast China， Qinghai-Xizang Plateau， and northern Xinjiang—using root mean square error （RMSE）， bias （Bias）， mean relative error （MRE）， and correlation coefficient （r）. Overall， the KELLY algorithm showed the lowest accuracy， significantly overestimating snow depths between 0 and 60 cm compared to the other two algorithms， with RMSE values ranging from 3.99 cm to 8.23 cm. The CHE and JIANG algorithms demonstrated comparable performance， with RMSEs of 2.78~5.48 cm and 2.88~4.99 cm， respectively. When in situ snow depth exceeded 60 cm， all algorithms tended to underestimate the depth， highlighting a limitation of brightness temperature gradient methods for snow depth retrieval. Regionally， in northern Xinjiang where snow cover was primarily distributed over mountainous terrain， all three algorithms exhibited underestimation in the ascending orbits of FY-3B and FY-3D because of daytime overpass. However， the KELLY algorithm showed relatively smaller underestimation in this region. For other orbits， the KELLY algorithm consistently demonstrated the lowest accuracy across all subregions. In contrast， the CHE and JIANG algorithms demonstrated comparable performance and achieved the highest accuracy in the Inner Mongolia-Northeast China region and the Qinghai-Xizang Plateau. Temporally， the CHE algorithm outperformed the JIANG algorithm during the shallow snow period （November to January）， while the JIANG algorithm outperformed the CHE algorithm during the deep snow period （January to March）. Both the CHE and JIANG algorithms achieved better performance in the Qinghai-Xizang Plateau and Northeast China than in northern Xinjiang. This was attributed to larger interannual snow variability and deep snow causing signal saturation in northern Xinjiang. Overall， the local algorithms （CHE and JIANG） were more suitable for snow depth estimation in China. However， due to variations in snow characteristics， these methods could not fully capture the seasonal patterns of snow depth. Additionally， although cross-platform calibration was conducted to reduce the systematic bias in brightness temperature， snow depth derived from different platforms still showed obvious disparities. In summary， these findings offer valuable insights and technical support for snow depth algorithm improvement and for the reasonable application of passive microwave remote sensing data.

Potentilla parvifolia is a typical alpine shrub widely distributed in the Qilian Mountains. In the context of climate change， it has accelerated its migration trend toward higher altitudes in recent years. Soil microorganisms， as crucial biological communities with transformation potential， are strongly influenced by the root activities of P. parvifolia. Therefore， this study aims to use Illumina Miseq high-throughput sequencing technology to analyze rhizosphere microbial communities and their functional transformation characteristics across different altitudinal habitats and identify the key driving factors， thereby providing an important basis for in-depth investigation of the mechanisms of soil ecological function evolution in alpine regions due to plant migration. The study found that at the low-altitude site （3 204 m）， the coverage of P. parvifolia significantly increased soil total carbon （TC）， available phosphorus （AP）， and nitrate nitrogen （NO₃ ^--N） contents， while enhancing the activities of sucrase （SUC）， urease （URE）， and cellobiohydrolase （CBH） （P<0.05）. The coverage of P. parvifolia increased the diversity and richness of soil microbial communities， with a more pronounced response observed in fungal communities compared to bacterial communities. Furthermore， P. parvifolia increased the relative abundances of Proteobacteria and Ascomycota. Analysis based on microbial community assembly revealed that stochastic processes dominated bacterial community assembly at low （3 204 m） and middle （3 550 m） altitudes， whereas deterministic processes prevailed at the high-altitude site （3 650 m）. In contrast， fungal community assembly was governed by deterministic processes across all three altitudes. A total of 23 conserved COG functional categories were identified through PICRUSt functional prediction. The coverage of P. parvifolia significantly increased the relative abundance of nitrogen cycle-related functional genes （gudB/rocG， nirK， narH/narY/nxrB） in the soil （P<0.001）， while the abundance of these genes generally decreased with increasing altitude. These findings indicate that P. parvifolia coverage positively affects soil ecological functions at high altitudes in the Qilian Mountains by improving soil physicochemical properties， enhancing key enzyme activities， altering microbial community structure， and regulating functional gene expression. The microbially mediated nitrogen cycling reinforcement may serve as a key driver for the successful migration and niche occupation of P. parvifolia.

In the context of global warming， the ice and snow in the source regions of the Yangtze River and the Yellow River are melting at an accelerated rate. Quantitatively evaluating the runoff effect of glacier melting is crucial for the management of water resources in high-altitude cold regions of the Qinghai-Xizang Plateau. The meteorological station data （daily precipitation and daily temperature） provided by the National Climate Data Center were used in combination with the 90 m×90 m digital elevation model （SRTM DEM） and the vector data of the second glacier inventory. Subsequently， a degree-day factor model was employed to reconstruct the multi-year glacial mass balance and the historical evolution characteristics of glacial meltwater runoff and its components in the source regions of the Yangtze River and the Yellow River from 1958 to 2022 （including rainfall runoff， snowmelt runoff， and ice melt runoff from glacial areas）. The extent of the impact of climate change on the melting of glaciers in the source regions was explored. The main findings were summarized as follows： （1） over the past 60 years， the glacier mass balance in the source regions of the Yangtze River and the Yellow River showed a significant negative equilibrium. The annual average glacier mass balance was -117.2 mm and -84.3 mm， respectively， and the cumulative mass balance was -7.03 m and -5.48 m， respectively. （2） The glacier equilibrium line altitudes （ELAs） in these two source regions showed a significant upward trend. The upward rates were 5.57 m·a^-1 and 3.93 m·a^-1， respectively， and the ELAs of the source regions of the Yangtze River and the Yellow River increased by 334.2 m and 313.6 m， respectively. （3） The total runoff of glacial meltwater in these source regions generally showed an increasing trend. The multi-year average total runoff of meltwater in the two source regions was 18.43×10⁸ m³ and 1.87×10⁸ m³， respectively. The variation trend of the ice melt runoff in the source regions was consistent with that of the total meltwater runoff， and its proportion showed an increasing trend year by year. The proportions of ice melt runoff in summer reached 91.88% and 90.95%， respectively. Snowmelt runoff showed a slight increase in the source region of the Yangtze River and a slight downward trend in the source region of the Yellow River. The seasonal distribution characteristics indicated that summer （June to August） was the primary period for glacial meltwater runoff， with its runoff volume accounting for 90.05% and 88.23% of the total annual runoff volume of the Yangtze River source and the Yellow River source， respectively. The proportions of runoff in spring and autumn decreased significantly. The spring runoff volumes of the Yangtze River source and the Yellow River source were 3.79% and 1.95%， respectively， and those in autumn were 6.17% and 9.82%， respectively. In winter （December to February）， there was basically no runoff generation. （4） The sensitivity of glacier mass balance to temperature was much higher than that to precipitation. The sensitivity of glaciers in the source region of the Yellow River to climate change was higher than that in the source region of the Yangtze River， which was related to the scale of glaciers in the source regions. In conclusion， this study systematically analyzes the variation patterns of glacial mass balance and meltwater runoff components under climate change， and quantifies the contribution of glacial ablation to streamflow. The findings provide critical insights into the implications of cryospheric changes for water security.

With the continuous expansion of global natural resource exploitation and infrastructure development into cold and high-altitude regions， the stability of geotechnical engineering under extremely low-temperature conditions has become a growing concern within the engineering community. Among the various challenges， frost heave damage is recognized as a critical factor affecting the service performance and operational safety of underground engineering. Its occurrence mechanism is closely related to the pore structure of rock mass and the state of pore water. Although previous studies have confirmed that the mechanical properties of frozen rocks are significantly influenced by temperature， pore size distribution， and water saturation， systematic investigations into the unfrozen water content during the freezing process remain limited. In particular， the mechanisms by which water-ice phase transitions at different pore scales contribute to frost heave damage are still unclear. In this study， low-field nuclear magnetic resonance （NMR） technology was employed as the primary analytical technique. Six representative sandstone samples from diverse geological backgrounds were selected and subjected to temperature-controlled freezing experiments from room temperature to -50 ℃. The dynamic evolution of pore water states was monitored in real time， with a focus on analyzing the variation of transverse relaxation time （T ₂ spectra） with temperature， thereby revealing the transformation trends and patterns of unfrozen water and ice content across different pore size ranges. The results showed that all samples exhibited typical bimodal T ₂ spectral distribution characteristics， with both peak positions and areas decreasing significantly as temperature dropped， indicating the progressive freezing of pore water. Water in larger pores froze almost completely at around -5 ℃， while in smaller pores， particularly those with diameters less than 0.1 μm， the freezing point was significantly depressed due to pore size effects. As a result， a considerable amount of water remained unfrozen in the form of bound water， even at temperatures below -20 ℃. Moreover， the rate of decrease in unfrozen water content and the freezing behavior varied significantly among the sandstone samples， which was closely related to their pore structure characteristics such as pore size distribution and connectivity. These results underscored the critical role of pore-scale features in governing the controlling phase transition process and the associated frost heave risk. This study not only deepens the understanding of the evolution of pore water states in frozen rocks but also elucidates the microscopic physical mechanisms underlying frost heave damage under low-temperature conditions. The findings provide a theoretical basis for evaluating the stability of rock masses in cold regions. Furthermore， the results offer valuable references for risk identification and structural optimization in the design phase of major cold-region infrastructure projects， including polar railways， highways， tunnels， and hydropower stations， and provide a theoretical basis for the development of materials and technologies for frost damage prevention and control.

Intensive freeze-thaw cycles and rainfall processes in the seasonally frozen loess zone of China’s Loess Plateau progressively weaken soil structure and aggravate soil erosion， highlighting the need for green stabilization technologies that can maintain performance under cyclic freezing. Microbially induced carbonate precipitation （MICP） has attracted considerable attention as an environmentally friendly ground-improvement method. However， in cold regions， its application is constrained by the brittleness of the calcium carbonate cement， the non-uniform spatial distribution of precipitates， and the rapid degradation of erosion resistance under repeated freeze-thaw cycles. To address these limitations， a composite stabilization scheme combining MICP with polyacrylamide （PAM）， a water-retentive polymer， was proposed. Its effectiveness in improving the freeze-thaw durability of loess was systematically evaluated through coordinated macro- and micro-scale testing. Remolded loess was prepared as untreated specimens， MICP-treated specimens， and MICP+PAM specimens with different PAM dosages （by dry soil mass）. Cylindrical specimens were used for disintegration tests， and shallow plate specimens were employed for micro-penetration and rainfall-erosion tests. All specimens were subjected to 3， 5， and 10 freeze-thaw cycles between -20 °C and 20 °C， with 12 h of freezing and 12 h of thawing in each cycle， to simulate the seasonal temperature regime of the Loess Plateau. After the designated cycles， macroscopic indicators including disintegration rate， penetration resistance at a depth of 10 mm， and cumulative soil loss under artificial rainfall were measured. In addition， scanning electron microscopy （SEM） was used to obtain representative images of the microstructure of untreated， MICP， and MICP+PAM specimens before and after freeze–thaw cycling， thereby providing qualitative support for the macroscopic observations and revealing the main features of structural evolution. The test results showed that for all treatment types， disintegration resistance， penetration strength， and erosion resistance decreased with increasing number of freeze-thaw cycles and gradually tended towards a stable level， reflecting progressive microstructural deterioration followed by a new quasi-equilibrium state. Among the tested PAM contents， a dosage of 0.3% in the MICP+PAM group yielded the best overall freeze-thaw performance. After 10 freeze-thaw cycles， the MICP+0.3% PAM specimens exhibited pronounced improvements compared with both untreated and MICP-only loess. Specifically， the final disintegration rate decreased by 85.87% and 83.44%， respectively. The penetration resistance increased to 1.77 and 1.25 times that of the corresponding untreated and MICP-treated specimens. The cumulative soil loss decreased by 51.70% and 38.73%. These results indicated that adding an appropriate amount of PAM significantly enhanced the freeze-thaw durability of MICP-stabilized loess in terms of both hydraulic stability and near-surface mechanical strength. However， insufficient PAM produced weak bridging and water-retention effects， while excessive PAM tended to form locally dense films and reduced the efficiency of composite cementation. SEM observations provided a concise microstructural explanation for these macroscopic trends. Compared with untreated and MICP-only specimens， loess treated with MICP+0.3% PAM exhibited a denser and more continuous cemented fabric， in which biogenic CaCO₃ and PAM jointly bridged particles and refined pores. The presence of PAM promoted a more homogeneous distribution of CaCO₃ and introduced flexible polymer films around particles， which buffered ice-induced stresses and limited the development of microcracks during freeze-thaw cycling. Consequently， the integrity of the cemented skeleton was better preserved， and the loss of strength and erosion resistance was effectively mitigated over repeated cycles. Overall， this study demonstrates that the MICP+PAM composite technique can effectively alleviate freeze-thaw-induced deterioration of loess and significantly improve its resistance to disintegration， penetration， and rainfall erosion compared with both untreated and conventionally MICP-stabilized loess. By clarifying the synergistic action of microbial mineral precipitation and polymer film formation and by identifying an optimal PAM content of about 0.3%， this study provides a mechanistic basis and key parameter reference for the application of MICP+PAM in slope protection and soil and water conservation projects in seasonally frozen loess regions. The findings highlight the potential of this composite bio-polymer technology as a green and durable alternative to traditional cement-based stabilizers in cold-region loess engineering， and also underscore the necessity for further studies on long-term performance under combined freeze-thaw and wetting-drying cycles and variable rainfall conditions， so as to more effectively translate laboratory results into field applications.

In the fields of national defense and civil engineering， such as the explosion-proof structure design of tunnels， railways， highways， and pipeline networks in cold regions， and the vertical shaft excavation using the freezing method in coal mines， frozen soil is often subjected to impact loading during activities like drilling and blasting construction， weapon damage， and seismic events. Investigating the strength characteristics， deformation and failure mechanisms， and stress wave propagation patterns of frozen soil within a high strain rate range is of great theoretical and practical significance for improving the efficiency of frozen soil excavation and fragmentation and for analyzing the safety and stability of frozen soil masses. This study summarizes the research status of the dynamic characteristics of frozen soil under impact loading from three aspects： frozen soil SHPB test system and data processing， laboratory SHPB tests on frozen soil， and dynamic constitutive relationship of frozen soil. First， the advantages and disadvantages of the developed temperature-controlled SHPB test system for frozen soil are analyzed. It is found that the current temperature control system has disadvantages such as large temperature fluctuations， cumbersome test process， and low refrigerant utilization efficiency. Second， the effects of parameters such as temperature， strain rate， stress state， moisture content， and fracture distribution on the dynamic strength， deformation modulus， and failure characteristics of frozen soil are systematically summarized. It is found that frozen soil exhibits typical characteristics of “freezing brittleness” and “dynamic brittleness”. Confining pressure and axial pressure help enhance the dynamic compressive strength of frozen soil. The presence of prefabricated fissures significantly reduces the bearing capacity of frozen soil specimens. Finally， the methods for establishing constitutive models of frozen soil and their advantages and disadvantages are summarized and evaluated. It is concluded that the Z-W-T model can better characterize the relationship between the strength and deformation of frozen soil under impact loading. Based on the summary of existing research， prospects are provided for the urgent problems to be solved and future research directions in frozen soil dynamics.

Thermokarst lakes are typical representatives of severe degradation of permafrost， where dissolved organic matter （DOM） from permafrost enters thermokarst lakes. Due to intense solar radiation on the Qinghai-Xizang Plateau， DOM in thermokarst lakes undergoes significant photodegradation processes. However， few studies have reported the photodegradation characteristics of DOM in thermokarst lakes on the Qinghai-Xizang Plateau， which may lead to bias in understanding carbon cycle and carbon-climate feedback under permafrost degradation. This study sampled water from thermokarst lakes under four distinct vegetation types on the Qinghai-Xizang Plateau， including alpine wet meadows， alpine meadows， alpine steppes and alpine deserts. For each vegetation type， dark control and light-exposed groups were established to conduct in-situ photodegradation experiments. By measuring dissolved organic carbon （DOC） concentrations， ultraviolet-visible absorption spectra， and three-dimensional fluorescence spectra—coupled with parallel factor analysis （3D-EEM-PARAFAC）， to investigates the effects of solar radiation on DOM content， optical properties， and composition in thermokarst lakes on the Qinghai-Xizang Plateau. Results show that after 10 days of in-situ experiments， DOM in thermokarst lakes under dark conditions exhibited limited changes across all four vegetation types. Although no significant variation in DOM content was observed under light exposure， significant alterations occurred in DOM optical properties and composition under light treatment. Chromophoric dissolved organic matter （CDOM） decreased by 23.6% to 36.7%， indicating that sunlight radiation significantly degrades the CDOM content in DOM. Under the same ultraviolet radiation intensity， the degree of CDOM photodegradation is greater in systems with low DOC concentrations. The decrease in surface water CDOM content may lead to enhanced photodegradation in deep water， resulting in more organic carbon being released into the atmosphere. The aromatic index （SUVA₂₅₄） decreases by 18.9% to 37.1%， indicating that sunlight radiation degrades aromatic compounds in DOM； while the spectral slope ratio （S _R） increases by 45.5% to 124.2%， indicating that sunlight radiation converts high molecular weight DOM to low molecular weight DOM. The significant decrease in humification index （HIX） indicates that solar radiation substantially reduced the humification degree of DOM， while the significant increase in freshness index （BIX） suggests that solar radiation promoted the production of more fresh DOM. These findings are consistent with the decreasing trend of humic-like components and the increasing trend of protein-like components under light exposure. Humic-like substances （C1， C3） exhibit greater photosensitivity than protein-like substances （C2， C4）， with C3 being lost faster than C1， and C2 accumulating faster than C4. Moreover， allochthonous DOM component C3 shows greater photoreactivity than the autochthonous DOM component C2. The study supports the idea that a portion of the protein-like component C4 is a photodegradation product of terrestrial humic component C3. The above findings demonstrate that during the 10-day in-situ observation period， the photochemical mineralization quantum yield of DOC was evidently low. This may be attributed to the relatively static conditions of thermokarst lakes in permafrost regions during summer， combined with prolonged water residence times， which collectively constrain the photomineralization of DOM in these water bodies-otherwise， DOM mineralization would be significantly more pronounced. The photobleaching effect led to a reduction in the absorption coefficient of CDOM， thereby increasing the maximum depth of light penetration in the water column. This phenomenon consequently exerts significant influence on the structure and function of aquatic ecosystems. Solar radiation preferentially degrades terrestrially-derived humic substances in Tibetan Plateau thermokarst lakes， thereby promoting the photodegradation of DOM in these water bodies. These observations collectively indicate that solar radiation plays a crucial role in the migration and transformation of DOM in thermokarst lakes. Under future climate warming and permafrost degradation scenarios， substantial quantities of DOM from thermokarst lakes will be introduced into aquatic ecosystems and exposed to solar radiation， creating favorable conditions for DOM photodegradation and significantly altering its migration and transformation behaviors.

The Qinghai-Xizang Plateau experiences frequent geological disasters due to its unique geographical environment and intense tectonic activity. Among these， disaster chains such as glacial lake outburst floods triggered by landslides and collapses are particularly prominent. Therefore， systematic research on the formation mechanisms of such disaster chains holds significant theoretical and practical value for regional disaster prevention and mitigation. This study focused on the landslide on the north side of Tangzhen Co in Damxung County on the Qinghai-Xizang Plateau. Based on detailed field geological surveys and remote sensing interpretation， the basic characteristics， deformation-failure mechanisms， and main influencing factors of the landslide were comprehensively analyzed. Using the Massflow numerical simulation platform and considering the actual conditions of the disaster chain， the calculation program was secondarily developed. This enabled dynamic simulation and quantitative prediction of the entire process from landslide initiation， movement into the lake， glacial lake outburst， to flood propagation. The study area is located on the northwestern margin of the Ningzhong Basin within the Yangbajain-Damxung-Gulu graben system in the hinterland of the Qinghai-Xizang Plateau. The region is tectonically active， with frequent occurrences of collapse and landslide disasters. The landslide on the north side of Tangzhen Co is an ancient landslide. In plan view， it exhibits an “armchair” shape， with an average slope gradient of about 30° and a main sliding direction of 185°. The sliding body has an average thickness of approximately 11 m and a total volume of about 11.55×10⁴ m³， classifying it as a medium-sized landslide. The landslide material is mainly glacial till， and the underlying bedrock consists of feldspathic quartz sandstone. Investigations show that the landslide is currently in an accelerated creep stage. The main cracks at the rear and on both sides are connected， shear feather cracks have formed on both flanks， and bulging cracks and discontinuous radial cracks appear at the front. The overall stress environment of the slope is gravitational stress. Due to stress redistribution， the maximum principal stress is nearly parallel to the slope surface， forming a tensile stress concentration zone in the middle-upper part of the slope and a shear stress concentration zone at the toe. This pattern manifests as “tension at the rear and shear at the front”， leading to a creep-tension deformation and failure mode of the landslide. The stability of the landslide is jointly controlled by gravitational stress， rainfall infiltration， freeze-thaw cycles， fault activity， and groundwater. It is prone to overall instability under extreme rainfall or seismic conditions. Once the landslide fails， it will further entrain slope deposits， mobilizing a volume far greater than that of the landslide itself. Upon entering the lake， it will generate surge waves. The surge waves may overtop the existing spillway and flow downstream， forming floods or even debris flows. Additionally， a large flood may remobilize existing loose deposits in the downstream channel， thereby forming larger debris flows， posing a severe threat to the downstream Qucai Village. This study employed a depth-integrated continuum mechanics model and the MacCormack-TVD finite difference algorithm to numerically simulate the disaster chain in segments. First， the Coulomb friction model was used to simulate landslide motion and entrainment. Subsequently， the model was switched to the Manning model to simulate the outburst flood propagation process. Key parameters were set based on experimental and back-analysis results from similar landslides in the region to ensure that their values conformed as closely as possible to the conditions of the actual disaster chain. The simulation results showed that the entire landslide movement process lasted about 200 s， reaching a maximum velocity of 39 m·s^-1. After 800 s， the flood reached the downstream Qucai Village， with a maximum flow velocity of 11 m·s^-1 and a maximum inundation depth of 4.2 m， ultimately inundating about 80% of the village area. By integrating geological mechanism analysis with dynamic process simulation， this study systematically reveals the disaster-causing mechanisms and spatiotemporal evolution patterns of the Tangzhen Co landslide-glacial lake disaster chain， providing quantitative predictions of motion parameters and risk zones. The proposed “sliding-entrainment-surge-dam breach” chain disaster process and parameterized simulation method offer essential references for early warning and engineering prevention and mitigation of the landslide on the north side of Tangzhen Co and other similar landslide-glacial lake disaster chains on the Qinghai-Xizang Plateau.

Compared with single snowstorm or gale disasters， wind-snow compound extreme weather events are more likely to cause extreme disaster losses. This study selected data including daily temperature， snowfall， minimum visibility， and maximum wind speed in Jilin Province from 1980 to 2023. The snowstorm weather index （SWI） was used to characterize the wind-snow compound extreme weather events. The random forest （RF） model was utilized to construct an extended sequence of the maximum wind speed. Furthermore， combined with the Mann-Kendall trend test and correlation analysis， the spatiotemporal variation characteristics of wind-snow compound extreme events in Jilin Province and their correlations with various meteorological and topographic factors were systematically analyzed. The results showed that the random forest model performed well in extending the maximum wind speed time series， with an R² exceeding 0.90. The number of snowstorm days （SD） at all intensity levels showed a fluctuating upward trend during the study period， and there was an abrupt change around 2020. Snowstorms could occur from October to March of the following year. The proportion of stations experiencing moderate or stronger snowstorms was highest in November and lowest in December and January. In terms of spatial distribution， snowstorms occurred mostly in the central and eastern parts of Jilin Province， especially in the eastern and southern regions where strong and extremely strong snowstorms were more likely to occur. The SWI in the eastern region showed a decreasing trend with high variability. Additionally， the SWI in the southern region demonstrated an increasing trend with low variability. The snowfall showed the strongest correlation with SWI， followed by minimum temperature and maximum wind speed. All three factors passed the significance tests with SWI， providing valuable indicators for evaluating future wind-snow compound extreme events.

Water resources， as a fundamental strategic resource， play a decisive role in the sustainable development of regional economy and society. In the context of intensifying global climate change， water scarcity has become a key bottleneck restricting the sustainable development of arid and semi-arid regions. Gansu Province， located in the arid and semi-arid areas of northwest China， has an inherent deficiency in water resources and an extremely uneven spatiotemporal distribution， with a water shortage rate reaching 14.1%. In recent years， with the rapid development of the regional economy and society， the contradiction between water supply and demand has become increasingly prominent. Especially under the dual-driven development model of industrialization and urbanization， the efficient allocation and sustainable utilization of water resources are not only crucial for the stable operation of the regional economy and society， but also hold significant strategic importance for maintaining the ecological security barrier in northwestern China and ensuring national ecological security. Against this backdrop， in-depth research on the characteristics and sustainability of water resource utilization in Gansu Province is of great theoretical and practical value for achieving coordinated development of high-quality regional growth and ecological civilization construction. Based on water footprint theory， this study systematically calculated the spatiotemporal evolution of the regional water footprint （WFP） in Gansu Province from 2011 to 2023， and developed a comprehensive evaluation indicator system for the sustainable utilization of water resources from four dimensions： water footprint structure， water footprint benefit， water resource ecological security， and water resource sustainability， aiming to reveal the characteristics and driving mechanisms of water resource utilization. Furthermore， the logarithmic mean Divisia index （LMDI） model was used to quantitatively decompose the contribution of population， economy， and technical efficiency to changes in WFP， thereby providing a scientific basis for the optimal management of water resources in Gansu Province. The results showed that： （1） the WFP in Gansu Province showed a significant upward trend， increasing from 310.57×10⁸ m3 in 2011 to 432.15×10⁸ m³ in 2023， with an average annual growth rate of 2.79%， demonstrating continuously increasing pressure on water demand. Significant spatial differences were observed， with Tianshui City having the highest average annual WFP （42.36×10⁸ m³）， while Jiayuguan City had the lowest （2.62×10⁸ m³）. The WFP structure was dominated by agricultural use， with agricultural water footprint （AWF） accounting for 92.15%， indicating that agricultural water conservation remained critical. （2） The water self-sufficiency rate （WSS） in Gansu Province remained above 96%， and the economic value of water footprint （EVWFP） showed a significant upward trend， increasing to 27.45 yuan·（m³）^-1 in 2023. However， the water scarcity index （WSI） and water pressure index （WPI） fluctuated within the range of 88.98% and 194.68%. During the “12th Five-Year Plan” period， the water resource status in Gansu Province was unsustainable. However， after implementing a series of water-saving measures， the water resource status improved to a sustainable state during the “13th Five-Year Plan” period. Nevertheless， in the early stage of the “14th Five-Year Plan”， the problem of water shortage became increasingly prominent， and the sustainable utilization of water resources faced significant challenges. （3） The LMDI model analysis indicated that economic and population effects positively drove changes in WFP， with the economic effect being the main driving factor （accounting for 58.47% of the contribution）， while the technical effect had a negative driving effect， accounting for 40.05% of the total effect. The inhibitory effect of technological progress on WFP was significant. The findings provide a theoretical basis and decision-making support for Gansu Province to formulate scientific and reasonable water resource management policies， optimize water resource allocation， and promote the sustainable utilization of water resources， thereby facilitating the coordinated development of water resources， economy， and ecology in Gansu Province.

Frozen soil is widely distributed in Northwest China， and its physicochemical properties strongly affect the stability and durability of engineering structures in cold regions. It is highly sensitive to ambient temperature， often exhibiting significant differences before and after freezing. Therefore， evaluating the properties of frozen soil is a prerequisite for the remediation of frozen soil-related engineering hazards. Electrochemical impedance spectroscopy （EIS）， a non-destructive method， is widely used to evaluate the physical and chemical properties of porous geotechnical materials and to characterize the phase transition of pore water in frozen soil. As the pore water freezes or the ice melts with the fluctuations in the surrounding temperature， it is crucial to investigate the influence of pore water state on the EIS of soil. To investigate the variations in the electrochemical characteristics of soil during freezing， the EIS of silty clay in Qinghai-Xizang Plateau was measured under different moisture contents and temperatures. The field-collected soil samples were first leached to remove salts， preventing the initial salt content from affecting the test results. Subsequently， the salt-free soil was dried in the oven at 105 ℃ for 12 hours. The dried soil was crushed and sieved to obtain the test soil. Considering the test soil properties， four moisture contents were set as 10%， 15%， 20%， and 25%， respectively. The soil specimens were then compacted into cubes with a side length of 7 cm， and two copper sheets with a smooth surface were placed on its both sides as the two side electrodes for EIS measurement. The soil temperature was controlled by a cooling bath （TMS8035-R40） at a temperature range of 30 ~ -30 ℃， and a stepwise cooling method was adopted for temperature reduction. When the soil temperature was stable， the electrochemical test was conducted with CS353 AC impedance tester， and the frequency range was set from 10^-2 to 10⁵ Hz. The DC potential was 0.05 V， and the AC amplitude was 10 mV. Finally， ZSimpWin software was used to analyze the measured data. The results showed that the mobility of ions in pore water slowed down as the temperature decreased， leading to an increase in the soil impedance value and a gradual expansion of the capacitive reactance arc radius. The pore water was basically frozen at -30 ℃. However， due to the presence of residual ions in the pore water， ion migration occurred in the soil with 10% moisture content， resulting in a diffusion phenomenon， which was manifested as a diagonal line close to 45° in the low-frequency region in the Nyquist plot. The impedance modulus tended to stabilize at a frequency of 10⁵ Hz， and the impedance modulus at this frequency was selected for further analysis. Under the positive temperature condition， the impedance modulus increased linearly with decreasing temperature. The pore water froze at 0 ℃， and the formation of ice crystals was accompanied by volume expansion， causing changes in the internal structure of the soil and a significant increase in the impedance modulus values. In addition， an equivalent circuit model was established by analyzing the conductive pathways within the soil. The EIS data were fitted using ZSimpWin software with good fitting results， obtaining the changes in equivalent components of soil with different moisture contents during the cooling process. Taking the equivalent resistance element R ₁ as an example， it can be concluded that the numerical change of the equivalent resistance element can effectively reflect the freezing process of pore water in the soil. This study transforms the analysis of the electrochemical characteristics of the soil from a qualitative approach to a quantitative one， which holds significant importance for understanding the electrochemical characteristics of soil during the freezing process.

Permafrost is widely distributed on the Qinghai Plateau， particularly in the South Qinghai Plateau and Qilian Mountains regions. The frozen soil environment is highly sensitive to climate change. However， current understanding of the spatiotemporal variation patterns and driving mechanisms of the freeze-thaw process on a large scale remains insufficient， especially regarding how geographic and climatic factors influence the freeze-thaw process. Based on data from 42 meteorological stations in Qinghai Province from 1961 to 2023， this study employed spatial variation analysis and climate abrupt-change testing to statistically analyze the spatiotemporal characteristics of the freeze-thaw index. The results indicated that： （1） the air freezing index （AFI） and number of freezing days （NF） in Qinghai Province exhibited a spatial distribution pattern increasing from north to south and from east to west， while the air thawing index （ATI） and number of thawing days （NT） showed the opposite trend. Over the past 63 years， AFI and NF decreased significantly ［with climatic tendency rates of -72.8 ℃·d·（10a）^-1 and -3.7 d·（10a）^-1， respectively］， while ATI and NT increased significantly ［69.5 ℃·d·（10a）^-1 and 3.7 d·（10a）^-1］. （2） The year 1997 marked an abrupt change in the freeze-thaw index. During the post-abrupt-change period （1997—2023）， AFI decreased by 236.5℃·d， and ATI increased by 205.9 ℃·d. Before the 1980s， the AFI anomaly showed a positive tendency， which shifted to negative after the 1990s， with the opposite pattern observed for ATI. Spatially， the high-altitude areas of the Three-River Source Region experienced the largest decrease in AFI， indicating greater sensitivity of freezing processes to climate warming at higher altitudes. The eastern agricultural area and the Qaidam Basin showed a significant increase in ATI， reflecting a more pronounced impact of warming on thawing processes at lower altitudes. （3） AFI showed a significant negative correlation with air temperature （T）， while ATI showed a highly significant positive correlation with T. Altitude was the primary geographic factor influencing the spatiotemporal variation of the freeze-thaw index. AFI exhibited a highly significant positive correlation with altitude and a significant negative correlation with longitude， with correlation coefficients of 0.792 and -0.437， respectively. ATI was significantly positively correlated with longitude and latitude， and highly significantly negatively correlated with altitude， with correlation coefficients of 0.332， 0.269， and -0.991， respectively. Altitude was the main geographic factor affecting the spatiotemporal variation of the freeze-thaw index. For every 100 m increase in altitude， AFI and NF increased by 92.7 ℃·d and 6.3 d， respectively， while ATI and NT decreased by 80.9 ℃·d and 6.3 d， respectively. Among atmospheric circulation influencing factors， the Tibet Circulation-2， East Asian trough intensity， northern boundary of the Northern Hemisphere subtropical high， and Northern Hemisphere polar vortex intensity showed significant relationships with changes in the freeze-thaw index in Qinghai Province. Accurately quantifying the spatiotemporal characteristics of the freeze-thaw index on the Qinghai Plateau provides solid data support and theoretical foundation for a holistic understanding of multi-sphere interactions on the plateau.

Though rare， snowstorm in western South Xinjiang frequently cause severe damage to local economies and livelihoods， leading to substantial losses. To gain a more comprehensive understanding of its formation mechanisms and enhance operational capabilities， this study， using NCEP/NCAR reanalysis data， employed the Eulerian method and the HYSPLIT （hybrid single particle Lagrangian integrated trajectory） model to conduct a detailed analysis of the circulation background and the sources， transport， and contributions of water vapor from different regions during the 15 snowstorm days that occurred in western part of South Xinjiang from 1980 to 2022. The results showed that the primary influencing system on snowstorm days in this region was the Central Asian vortex （trough） type， with the water vapor mainly sourced from the Red Sea and its coastal areas—the Persian Gulf， Iran， Afghanistan， the key water vapor region—to the snowstorm areas. Before the snowstorm， the western boundary contributed the most to water vapor input， while during the event， the lower levels of the eastern boundary accounted for the majority of the water vapor input， which was closely related to the low-level easterly airflow and the complex topography of the South Xinjiang Basin. Analysis using the HYSPLIT model revealed that the primary water vapor sources affecting the snowstorm days in this region were Southwest Asia， the Mediterranean， Black Sea， and their vicinity， as well as Central Asia. Their contributions to the snowstorm areas were significantly higher in the lower troposphere than in the middle troposphere. The specific humidity and contribution rate of water vapor originating from Central Asia were significantly higher in mountainous areas than in plain areas. Below 700 hPa， water vapor from Southwest Asia and Central Asia was primarily transported to the snowstorm areas from heights below 1 500 meters. During the transport process， the specific humidity gradually decreased， which was inconsistent with the typical pattern of increasing specific humidity with decreasing height. After the water vapor reached the key region from its source via the westerly airflow， it was transported to the snowstorm areas at 500 hPa along a predominantly westerly path. At 700 hPa and below， the water vapor was primarily input into the snowstorm areas via both westerly and easterly paths， with the former being dominant. Water vapor transport at 850 hPa in the plain area was influenced by topography， resulting in relatively complex pathways， which should be given significant attention in practical operations. This study revealed that water vapor originating from the northeastern part of North America， the Norwegian Sea， the Arctic Ocean， and the southwestern part of Ili Prefecture could affect the western part of South Xinjiang under certain circulation conditions， with the moisture from the southwestern Ili Prefecture contributing significantly to the lower troposphere. Additionally， this study identified the key water vapor regions affecting snowstorm days in this area.

Since 2000， influenced by both climate change and human activities， the area of Chagan Nuur Lake has sharply shrunk from 105.3 km² to 30 km²， with a reduction rate of over 71%. Challenges such as water resource scarcity， soil salinization， and ecological degradation have become increasingly severe， posing a significant threat to regional ecological security. In this context， analyzing the hydrochemical characteristics of lakeshore zone water of Chagan Nuur Lake is of great significance for understanding the hydrogeochemical processes and their ecological effects in cold and arid regions. Ice-water samples were collected from 21 sites in the lakeshore zone water of Chagan Nuur Lake during the non-ice-covered period （June 27， 2023） and the ice-covered period （January 17， 2024）， including groundwater （well and spring water） and surface water （lake， river， and reservoir water）. By using methods such as Piper trilinear diagrams， Gibbs model， and ion ratios， the hydrochemical characteristics and their controlling factors were investigated. The results showed that： （1） significant seasonal variations were observed in ion concentrations in the lake’s ice-water system. The concentrations of non-ice-covered-period water were 1.32 times， 15.17 times， 17.01 times， and 12.51 times higher than those of ice-covered-period water， ice surface， ice interior， and ice-bottom water， respectively. （2） The cation distribution in the lakeshore zone of Chagan Nuur Lake followed the order： Na⁺ > Mg²⁺ > Ca²⁺ > K⁺， while the anions were mainly Cl⁻ > HCO₃⁻ > SO₄ ²⁻ > CO₃ ²⁻. （3） The hydrochemical characteristics of the ice-covered and non-ice-covered periods were generally similar， but significant differences were observed among water types： spring water was SO₄-Ca·Mg type， river and reservoir water were Cl·SO₄-Ca·Mg type， and lake water， lake ice， and well water were all Cl-Na type. （4） In terms of controlling mechanisms， lake water was primarily influenced by evaporation concentration （non-ice-covered period） and freezing concentration （ice-covered period）， showing a strong trend of sodium salt enrichment， indicating that the lake was evolving towards a salt lake. Spring water was mainly controlled by carbonate weathering and enriched in Mg²⁺. River and reservoir waters were influenced by both weathering and human activities. Well water was mainly controlled by the combined effects of carbonate weathering and albite dissolution. （5） Future research should focus on the combined effects of climate and human activities， establish a “water-salt-carbon-biology” coordinated management system， and use cross-scale models to achieve dynamic maintenance and early warning of lake water-salt balance. This will provide theoretical basis and practical references for ecological restoration of degraded lakes and sustainable regional water resource utilization.

In recent years， scholars have conducted extensive research in the field of frozen soil mechanics， establishing a systematic theoretical framework and laying a solid foundation for frozen soil engineering. However， current studies mainly focus on the mechanical properties of frozen soil within the temperature range of -30 ℃ and above. Faced with the increasingly frequent extremely low temperature environments in cold regions and the extreme temperature conditions encountered in deep space exploration， research on the mechanical behavior of frozen soil at ultra-low temperatures remains limited. With the advancement of national strategies such as “Xinjiang-Xizang Connectivity”， “Polar Security”， and “Deep Space Exploration”， research on ultra-low-temperature frozen soil mechanics has become a critical foundation for ensuring engineering safety in cold regions and exploring planetary cryospheres. This field represents a novel frontier in the study of frozen soil mechanics. Nevertheless， limited testing platforms and underdeveloped methodologies have confined this research to an exploratory stage， with systematic theoretical models yet to be defined and current capabilities being insufficient to meet the requirements of major engineering requirements. This study first systematically reviews the experimental devices and methods for studying the mechanical properties of frozen soil under ultra-low temperature environments. Existing studies have shown that the accuracy of mechanical testing equipment for frozen soil is significantly affected by ultra-low temperature environments， and that standardized testing protocols are still underdeveloped. Furthermore， at ultra-low temperatures， the temperature sensitivity of frozen soil compressive strength decreases， and failure modes generally exhibit more brittle characteristics. The stress-strain relationships demonstrate distinct stress-decay phases. Subsequently， the mechanisms underlying the change of mechanical properties of frozen soil at ultra-low temperatures are explored， followed by a review of the challenges faced in the research on ultra-low-temperature frozen soil mechanics and prediction methods applied in this field. Finally， future research directions for frozen soil mechanics at ultra-low temperatures are proposed， aiming to provide scientific references for theoretical advancement and critical engineering applications in extremely low temperature environments.

Seasonal freeze-thaw cycles in alpine soil play a pivotal role in regulating ecohydrological processes in cold regions. However， the spatial heterogeneity of hydrothermal dynamics under the combined effects of frozen soil degradation and vegetation change remains insufficiently understood. This study investigated the effects of alpine meadow degradation on the hydrothermal regime and freeze-thaw characteristics of shallow soil （0~60 cm） in the source region of the Heihe River， located in the northeastern Qinghai-Xizang Plateau. Using a space-for-time substitution approach， four sampling plots were established， each representing a different degradation stage： lightly degraded （LD）， moderately degraded （MD）， heavily degraded （HD）， and extremely degraded （ED）. This study conducted continuous monitoring of precipitation， air temperature， air humidity， soil temperature and moisture at multiple depths （5， 10， 30， and 60 cm） to explore the soil thermal and moisture dynamics in response to vegetation degradation. The results showed that although atmospheric conditions across the sites were generally similar， internal soil hydrothermal processes varied significantly along the degradation gradient. As degradation severity increased， the annual average soil temperature increased significantly. For instance， the surface soil temperature at the ED site was 15.4% higher than at the LD site. The amplitude of temperature fluctuation also increased， particularly in shallow layers. Soil moisture content declined markedly with degradation， and the vertical distribution pattern shifted. LD and MD sites had higher moisture in deeper layers， while HD and ED sites had higher moisture in surface layers， indicating weakened infiltration and water storage capacity in severely degraded soil. Freeze–thaw patterns also shifted. The onset of soil thawing occurred earlier and freezing was delayed with increasing degradation severity. At the 60 cm depth， the thawing date at the ED site was up to 34 days earlier than at the LD site. Correspondingly， the duration of freezing decreased， especially in deeper soil layers. Thawing–freezing ratio （TFR） values exceeded 1 at the MD， HD， and ED sites， indicating that heat accumulation dominated during the thawing period. This shift suggested reduced energy release during freezing and enhanced heat retention， potentially destabilizing frozen soil and accelerate its degradation. These changes in physical properties might further intensify soil temperature fluctuations and compromise the thermal stability of the underlying frozen soil. In conclusion， alpine meadow degradation exerts a pronounced influence on the hydrothermal dynamics and freeze–thaw processes of shallow soil in frozen soil-affected regions. These changes， including higher soil temperatures， reduced moisture content， shortened freezing durations， and increased heat accumulation， collectively contribute to an increased risk of frozen soil degradation. This study provides empirical evidence for understanding the coupled response of soil-vegetation-frozen soil systems to environmental disturbances and highlights the necessity of alpine meadow conservation and adaptive management strategies under a warming climate.

Under global climate change and China’s Western Development Strategy， engineering construction in frozen soil regions faces significant challenges. In pile foundation in regions with frozen soil， long-term stability issue has become a critical technological challenge for infrastructure development in cold regions. Particularly， the shear creep effect at the frozen soil-structure interface significantly influences the performance of pile foundations and other engineering systems. Under dynamically varying loads and temperature fields， progressive damage induced by shear creep at the interface poses serious threats to structural performance. Due to the temperature sensitivity and seasonal deformation behavior of frozen soil， pile foundations are especially affected by freeze-thaw cycles. These foundations are subjected to the combined effects of temperature， stress， and displacement over long periods， which makes the creep behavior at the pile-soil interface increasingly complex. This often leads to a reduced pile bearing capacity and uneven settlement of structures， resulting in engineering deterioration. However， current research on the shear creep at the frozen soil-structure interface has several limitations. First， traditional experimental devices， such as direct shear and single-shear devices， can generally simulate two-dimensional shear conditions， making it difficult to replicate the three-dimensional complex stress state and true mechanical response of pile foundations and other engineering structures. Second， existing studies primarily focus on the creep characteristics of the frozen soil itself， with limited systematic understanding of the creep behavior and response mechanisms. Third， current constitutive models are insufficient in characterizing the nonlinear accelerated creep phase， making it difficult to accurately predict the creep behavior of interfaces under different engineering conditions. To address these limitations， this study investigated the mechanical behavior of the frozen soil-steel interface through triaxial shear creep tests on saturated frozen soil under different surface roughness， temperature， and confining pressure conditions. The experiments investigated the patterns of creep deformation， creep rate， and time variation， thereby revealing the shear creep mechanism at the interface under the influence of various factors. Additionally， a mathematical model based on the Burgers model was established to describe the accelerated creep phase of the saturated frozen soil-steel interface. The results indicated that in the triaxial shear creep tests with graded loading， the deformation process under different temperature conditions followed a four-stage evolution pattern： instantaneous creep， primary （transient） creep， steady-state creep， and accelerated creep. Shear stress， temperature， and roughness were identified as the dominant factors affecting shear creep. The deformation behavior was controlled by shear stress levels. Under low stress conditions， steady-state creep predominated， ensuring long-term interface stability. Under high stress conditions， creep intensified， leading to interface failure. Lower temperatures significantly reduced both deformation magnitude and rate at the interface. Smooth interfaces exhibited rapid increases in shear displacement during initial loading， exhibiting significantly higher creep rates and deformation compared to rough interfaces. Creep deformation showed a distinct nonmonotonic trend with increasing interface roughness—first decreasing， then increasing—indicating the existence of a critical roughness that optimized inte rface performance. The effect of confining pressure was relatively small. The proposed model effectively characterized the viscoelastic behavior during the non-accelerated phase and captured the displacement jump observed in the accelerated creep phase. The systematic analysis of the data revealed the effects of different conditions on the shear creep parameters of the frozen soil-steel interfaces. These patterns provide valuable insights for understanding and predicting interface behavior under similar conditions and offer references for engineering applications. In conclusion， this study provides important experimental evidence and theoretical support for establishing pile foundation design theories that consider interface creep effects and for developing methods for long-term stability evaluation of cold-region engineering.

Polycyclic aromatic hydrocarbons （PAHs） are a critical class of persistent organic pollutants （POPs） that can be transported over long distances by atmospheric circulation and are present in low-temperature environments such as the North and South Poles and the Qinghai-Xizang Plateau. Global warming accelerates the melting of snow and ice， leading to the exposure of PAHs and affecting human health. Microorganisms serve as the primary degraders of PAHs， with extensive research reported on their degradation. However， studies on PAHs-degrading microorganisms in low-temperature environments have mainly emerged in the past two decades. In this study， the diversity of PAHs-degrading microorganisms in low-temperature environments， their degradation mechanisms， and the responses of microbial biodegradation to low temperatures are systematically summarized and reviewed. Additionally， further research directions and prospects for microbial degradation of PAHs in low-temperature environments are proposed， providing theoretical support for the source prevention and ecological remediation of PAHs contamination in low-temperature environments in the future.

In cold regions， asphalt stabilized macadam layers are commonly used as typical flexible base materials in pavements， but they can suffer severe and progressive deterioration under cyclic freeze-thaw actions， where water infiltration， repeated ice formation， and volumetric expansion synergistically cause microstructural damage—manifested as increased void connectivity， interfacial debonding at aggregate-asphalt interfaces， and microcrack propagation—ultimately compromising pavement structural integrity and triggering premature distress. However， comprehensive macro-mechanical quantification of this asphalt stabilized macadam damaged by freeze-thaw cycles and robust predictive models for long-term service performance remain inadequately developed， particularly for modified asphalt stabilized macadam engineered for enhanced frost resistance. To fill this critical gap， this study systematically investigated the freeze-thaw damage evolution of dense-graded ATB-25 through multi-scale experimental characterization and established a continuum damage mechanics model， while rigorously evaluating the effectiveness of low-dose styrene-butadiene-styrene （SBS） copolymer modification. The study prepared two primary ATB-25 mixtures： a conventional one using 90# penetration-grade asphalt binder， and a low-dose SBS-modified one incorporating 2% linear SBS copolymer via a direct dry-blending methodology during production. Both mixtures used identical andesite coarse aggregates， fine aggregates， and limestone mineral filler， and were designed according to the median gradation recommended in the standard ATB-25 specifications. They were compacted into specimens following Marshall mix design protocols， which yielded optimal binder contents of 3.4% for the conventional ATB-25 and 3.5% for the SBS-modified ATB-25， respectively. These specimens then underwent accelerated laboratory-simulated freeze-thaw cycling comprising 25 complete cycles. Each cycle consisted of vacuum saturation （15 minutes） followed by ambient-pressure water immersion （30 minutes） to ensure full moisture conditioning， then freezing （-18 ℃ for 8 hours） and thawing （60 ℃ water bath for 4 hours） phases， simulating extreme field thermal transitions. Mechanical performance degradation was tracked subjected to 0， 3， 6， 9， 12， 15， 20， and 25 freeze-thaw cycles through a battery of standardized tests. Uniaxial compression tests at 15 ℃ were conducted to determine the compressive strength and elastic modulus under static loading. Indirect tensile tests at 15 ℃ were performed with a loading rate of 50 mm⋅min^-1 to evaluate the splitting tensile strength and calculate the stiffness modulus. Dynamic modulus tests were conducted within an environmental temperature range （-10 ℃， 5 ℃， 20 ℃， 35 ℃， 50 ℃） and six loading frequencies （0.1 Hz to 25 Hz） to simulate traffic-induced viscoelastic responses， enabling the construction of master curves and the sensitivity analysis of freeze-thaw damage， thereby reflecting realistic dynamic loading conditions. The results showed that the mechanical properties of conventional ATB materials experienced significant deterioration. After 25 freeze-thaw cycles， compressive strength degraded by 41.2%， splitting strength by 30.5%， stiffness modulus by 45.8%， while dynamic modulus under moderate-temperature， traffic-representative conditions （20 ℃， 5 Hz） suffered a dramatic reduction of 64.55%， highlighting that dynamic mechanical properties exhibited exceptional vulnerability to freeze-thaw damage， which may be attributed to amplified stress concentrations under oscillatory loading exacerbating existing microdamage. Notably， low-dose SBS modification significantly enhanced the freeze-thaw resistance of ATB. The SBS-modified ATB exhibited considerably lower performance deterioration—compressive strength loss limited to 33.93% （17.7% relative improvement）， splitting strength loss limited to 22.5%， dynamic modulus loss at 20 ℃/5 Hz constrained to 53.93% （10.6% improvement）. This was attributed to multifaceted mechanisms wherein the SBS copolymer formed a resilient， flexible three-dimensional polymer network within the asphalt matrix， significantly enhancing binder elasticity， ductility， and viscosity， thereby producing thicker， more continuous asphalt films enveloping aggregates that physically obstructed water intrusion pathways at critical interfaces. Meanwhile， SBS promoted excellent physicochemical bonding to aggregate surfaces through polar interactions and reduced surface energy， drastically suppressing moisture-induced debonding. Moreover， SBS imparted exceptional stress relaxation and elastic recovery capabilities， enabling the modified asphalt binder to absorb and dissipate damaging internal stresses generated by ice crystallization pressures within aggregate pores and microcracks， thereby delaying crack initiation. To holistically quantify damage progression， this study developed a continuous damage mechanics evolution model， defining damage variables as key mechanical properties. The model parameters were optimized using nonlinear regression techniques， successfully predicting damage trajectories with high fidelity—particularly for splitting strength-based damage （correlation coefficient 0.954）—and validating its capability to capture the nonlinear， cumulative nature of performance degradation under freeze-thaw cycles. Notably， all damage evolution curves confirmed that SBS-modified ATB consistently exhibited slower damage accumulation rates， quantitatively validating its enhanced durability. This study draws three main conclusions. Dynamic mechanical properties （dynamic modulus） are identified as sensitive indicators of freeze-thaw damage in ATB. It is demonstrated that low-dose （2%） SBS modification—deployable without major process alterations—significantly enhances ATB frost resistance through synergistic mechanisms of binder reinforcement， interface performance enhancement， and stress relaxation. It provides a mechanics-based predictive framework for estimating the service life of ATB in cold environments， thereby offering pavement engineers in cold regions a theoretical basis for material design and a pathway for material optimization.

As a vital component of the terrestrial water cycle， snow is one of the most critical freshwater resources in arid and semi-arid regions， playing an irreplaceable role in regulating surface hydrological processes， maintaining ecosystem stability， and ensuring regional water supply. Located in the arid interior of Northwest China， Xinjiang features a typical arid and semi-arid climate， with a high dependence on snowmelt. In recent years， as climate change intensifies， Xinjiang has experienced significant increases in temperature， leading to a marked reduction in snow cover extent and duration， with the phenomenon of “snow drought” becoming increasingly prominent. However， a reasonable snow drought classification system based on Xinjiang’s unique snow and climate characteristics has not yet been established. Based on this， the ERA5 reanalysis dataset， China’s daily precipitation dataset， and China’s 25 km daily snow water equivalent （SWE） product were utilized. By comprehensively considering the key climatic conditions and characteristics during snow formation and ablation， four climate indicators—snow water equivalent， precipitation， thawing degree， and radiation—were selected to classify snow drought in Xinjiang.Given that snow accumulation primarily occurred in autumn and winter and ablation primarily in spring， this study focused on the meteorological conditions during the cold season and their impact on snow changes in the classification of snow drought. Therefore， the cold season （from November 1 to April 1 of the following year） of each hydrological year was selected as the study period to systematically analyze the snow distribution characteristics and drought evolution processes during this period. Based on this， snow drought during the cold season in Xinjiang was categorized into three types： warm type， dry type， and warm-dry type. The spatiotemporal evolution characteristics of snow drought during the cold season in Xinjiang from 1980 to 2020 were systematically analyzed. The results indicated that snow drought during the cold season in Xinjiang exhibited significant spatial variability， with a distribution pattern of higher occurrence frequency south of the Tianshan Mountains and lower frequency north of the Tianshan Mountains. Specifically， the average occurrence frequency of snow drought in the area south of the Tianshan Mountains was approximately 38%， significantly higher than the 18% in the area north of the Tianshan Mountains， demonstrating a pronounced pattern of “higher in the south， lower in the north”. Among them， the Tarim Basin and its surrounding areas experienced the highest occurrence frequency of snow drought， reaching up to 47%. In contrast， regions such as the Ili River Valley and the northern margin of the Junggar Basin， influenced by moisture conditions and orographic lifting， exhibited relatively favorable snow conditions and the lowest occurrence frequency of snow drought， at only about 7%.Different types of snow drought also showed significant differences in their long-term trends. Over the past four decades， the maximum area proportions of warm-type and dry-type snow drought significantly decreased from 53.91% and 59.04% to 17.61% and 6.98%， respectively， with their occurrence ranges continuously shrinking at rates of 275 km²⋅a^-1 and 87.5 km²⋅a^-1. In contrast， the area proportion of warm-dry snow drought steadily increased from 22.41% to 47.11%， expanding by approximately 31.25 km² per year， gradually becoming the dominant type of snow drought during the cold season in Xinjiang.Further analysis indicated that the formation mechanisms of different types of snow drought were significantly different， with distinct dominant driving factors. Warm type snow drought was driven by the combined effects of multiple climatic factors， exhibiting pronounced multi-factor driving characteristics. Dry type snow drought was primarily governed by precipitation conditions and was more sensitive to anomalies in cold-season precipitation. Warm-dry type snow drought， however， was mainly driven by rising temperatures， which shortened snow cover duration and triggered earlier snowmelt， making it a representative compound snow drought type under climate warming.Overall， this study develops a snow drought classification indicator and system tailored to the snow and climate distribution characteristics of Xinjiang. The findings provide a scientific basis for an in-depth understanding of the evolution patterns and formation mechanisms of snow drought in Xinjiang under climate change， and also offer crucial theoretical support for the rational allocation of water resources， snow disaster prevention and control， and ecological security in arid and semi-arid regions.

In the context of climate warming and humidification on the Qinghai-Xizang Plateau， the Qinghai-Xizang Railway （QXR）， as a railway on plateau crossing the frozen soil regions， faces significant stability challenges-particularly the frozen soil subgrade-due to the presence and dynamics of surrounding surface water bodies. Based on remote sensing data， this study obtained the distribution of surface water bodies within a 1 000 m buffer zone along the QXR from 2006 to 2021 and analyzed their spatiotemporal distribution characteristics. Combined with case studies， this study investigated the impact of water ponding along the sides of the railway on the deformation stability of the frozen soil subgrade and its macroscopic manifestations. The results revealed distinct patterns in the distribution of surface water near the QXR. Quantitatively， water bodies smaller than 0.5 hm² dominated the landscape， accounting for the majority. Spatially， the distribution of these water bodies showed a pronounced orientation， primarily aligned along a southeast-northwest direction relative to the railway. Temporally， significant changes were observed during the study period. The total number of identifiable surface water bodies exhibited a consistent upward trend， increasing from 1 809 in 2006 to 2 170 in 2021， representing an increase of 19%. Concurrently， the area of these water bodies expanded. Notably， the proportion of larger-area water bodies （exceeding 2 hm²） within the total count increased from 6.91% to 7.74%， indicating a trend toward both more numerous and larger-area surface water features along the railway. Furthermore， detailed case analyses provided compelling evidence that water ponding adjacent to the railway subgrade profoundly influenced the deformation stability of the underlying frozen soil subgrade. A critical feedback mechanism-an interaction loop among the frozen soil layer， surface ponding， and the railway subgrade-was identified. Both engineering disturbances （primarily associated with the construction and presence of the railway） and ongoing climate change served as key drivers triggering the degradation of the subgrade’s supporting frozen soil. Crucially， this degradation of frozen soil caused depressions and altered local hydrological conditions， directly leading to the formation of surface water ponding. The presence of this ponded water served as a significant secondary driver， accelerating further thermal erosion and degradation of the adjacent and underlying frozen soil through enhanced heat transfer into the ground. This positive feedback loop， where frozen soil thaw led to water ponding that in return accelerated thaw， inevitably exacerbated subgrade deformation. The case studies highlighted a particularly hazardous scenario： when water ponding was concentrated predominantly on one side of the railway subgrade. This asymmetrical saturation induced a thermal imbalance across the subgrade. The side exposed to water experienced significantly accelerated frozen soil thaw and ground weakening compared to the drier side. This disparity led to pronounced uneven subsidence or differential settlement of the railway track， posing a serious threat to track geometry， alignment， and overall operational safety. Such deformation represented a macroscopic manifestation of the destabilizing influence of unilateral water ponding. Consequently， this study emphasizes that the effective management and mitigation of water ponding near the subgrade must become a priority for ongoing engineering maintenance and operational safety protocols of the QXR. Proactive measures to monitor， drain， or prevent the formation of such water bodies are essential to interrupt the identified frozen soil-degradation feedback loop and ensure the long-term stability of the infrastructure. In summary， this study provides critical empirical data derived from remote sensing on the evolving distribution of surface water near the QXR. Through case studies， it elucidates the mechanistic link between roadside ponding and the instability of frozen soil subgrade. The findings provide substantial data support and case references to directly inform and enhance engineering maintenance strategies crucial for preserving the structural integrity and operational reliability of this vital high-altitude railway in a changing climate.

Engineering construction in permafrost regions inevitably alters the thermal regime of the underlying permafrost， thereby threatening the bearing capacity of the permafrost foundation and the long-term stability of overlying artificial structures. Despite increasing infrastructure demands in cold regions， hydraulic engineering projects in permafrost regions remain scarce， with limited field monitoring data available. Consequently， the thermal impact of engineering construction activities， especially in combination with flowing water， on permafrost foundations is still not well understood. This study focused on a hydraulic channel project located in a continuous permafrost region in the hinterland of the Qinghai-Xizang Plateau. To investigate the thermal response of permafrost to engineering disturbance and hydrological processes， continuous ground temperature monitoring was conducted at four strategically selected boreholes—natural ground， channel slope， channel slope toe， and channel center—to a depth of 20 meters over a four-year observation period from 2020 to 2024. A systematic analysis was performed on variations in active layer thickness， shallow and deep permafrost temperatures， and near-surface energy budget processes under different surface conditions and proximity to the water flow. The results showed that， under the influence of heat carried by the flowing water， the onset of freezing at the channel center and channel slope toe boreholes was significantly delayed compared with that at the natural ground and channel slope boreholes. Channel excavation and the heat carried by the flowing water induced degradation of the underlying and surrounding permafrost. During the monitoring period， the active layer thickness at the natural ground borehole increased from 3.9 to approximately 4.5 m， whereas those at the channel slope， channel slope toe， and channel center boreholes increased year by year. Permafrost within a 10-meter depth range at the channel slope， channel slope toe， and channel center boreholes exhibited different degrees of warming during the monitoring period， and the closer a borehole was to the center of the flow section， the more pronounced the thermal erosion effect on the underlying soil. In terms of near-surface soil temperature and energy budget， the annual average shallow ground temperature at the channel center borehole was 3.4 to 5.2 ℃ higher than that at the natural ground borehole.The channel center borehole consistently remained in a state of heat absorption， with the maximum annual heat absorption reaching 7.9507×10⁴ kJ⋅m^-2. These findings， based on long-term field monitoring data， provide essential references for future analyses of the thermal stability of channel foundations in permafrost regions.

Under ongoing global warming， the frequency and intensity of extreme weather and climate events have increased significantly， exerting a profound impact on the cryosphere. Compared with changes in mean climate conditions， extreme events often act on glacier systems in an intense and short-term manner， triggering rapid and non-linear responses in glacier mass balance. As highly sensitive indicators of climate change， glaciers respond directly to extreme variations in temperature and precipitation， particularly manifested in the significant enhancement of ablation processes. However， existing studies have mostly focused on glacier responses under mean climatic conditions or at the regional scale， while assessments of the impact of extreme weather and climate events on glacier mass balance at the interannual scale remain relatively limited， especially for continental glaciers in arid and semi-arid regions. The Qiyi Glacier， a typical continental glacier located in the Beida River Basin of the central Qilian Mountains， is selected as the study object. This glacier is a typical continental glacier and possesses relatively abundant long-term observational data， providing favorable conditions for investigating glacier-climate interactions under both mean and extreme climate conditions. The primary objectives of this study are： to reconstruct the mass balance series of the Qiyi Glacier over the past five decades， to characterize the long-term evolution of extreme temperature and precipitation events in the study area， and to quantitatively assess the relative contributions and potential non-linear impacts of extreme weather and climate events， particularly extreme high-temperature events， on glacier mass balance. To achieve these objectives， the Open Global Glacier Model （OGGM） was employed to simulate the annual mass balance of the Qiyi Glacier for the period 1974—2024. Glacier outlines were derived from the Randolph Glacier Inventory （RGI 6.0）， and historical climate forcing data were obtained from the bias-corrected W5E5 reanalysis dataset. Model parameters， including temperature sensitivity， precipitation correction factor， and temperature bias， were calibrated using geodetic data and measured mass balance data. Based on daily meteorological observational data， extreme temperature and precipitation events were quantified using indices recommended by the Expert Team on Climate Change Detection and Indices （ETCCDI）. In addition， the degree-day factor approach was applied to distinguish the relative contributions of extreme high-temperature days and non-extreme days to glacier ablation. Statistical methods， including trend analysis， abrupt change detection， correlation analysis， first-difference analysis， and regression modeling， were employed to systematically explore the relationships between extreme climate indices and glacier mass balance. The results indicated that： （1） over the past five decades， the mass balance of the Qiyi Glacier exhibited an overall negative trend， with an overall rate of -0.102 m w.e.⋅a^-1. During 1974—1993， the glacier experienced a state of net mass accumulation， with a rate of +0.259 m w.e.⋅a^-1. An abrupt change occurred in 1993， after which the glacier transitioned into a phase of rapid mass loss， with a loss rate of -0.336 m w.e.⋅a^-1. （2） During the study period， the climate in the Qiyi Glacier region experienced a pronounced warming and wetting trend. Specifically， warm extreme indices increased markedly， while cold extreme indices declined significantly. The diurnal temperature range （DTR） showed an overall weak decreasing trend， with a rate of -0.08 ℃⋅（10a）^-1， and the decreasing rate accelerated markedly after the 1990s， reaching -0.29 ℃⋅（10a）^-1. The regional wetting trend was evident， with annual total precipitation increasing significantly at a rate of 34.73 mm⋅（10a）^-1. （3） Extreme high-temperature events were identified as the dominant driver of the accelerated mass loss of the Qiyi Glacier by enhancing ablation processes. Their annual average contribution to glacier ablation reached 21.3%， and approached nearly 50% in years with a high frequency of extreme high-temperature events. Preliminary regression analyses based on short-term observational data indicated a pronounced non-linear impact of extreme high-temperature events on glacier mass balance. In contrast， the regulating effect of precipitation on glacier ablation was relatively limited and gradually weakened with the increasing frequency of extreme high-temperature events. This study provides a preliminary quantitative assessment of the impact of extreme weather and climate events， particularly extreme high-temperature events， on glacier mass balance， offering a useful reference for deepening the understanding of glacier response mechanisms under extreme climate conditions and for future research on glacier evolution under climate change scenarios.

As an important water system in the inland river basin of the Hexi Corridor， the Shiyou River originates from the northern foot of the Qilian Mountains， with numerous glaciers in its upper reaches and a unique geographical environment in its runoff formation area. It serves as a typical basin for exploring the evolution of inland river water resources in cold and arid regions. The river provides essential water resources for industrial and agricultural development in Yumen and other regions in the middle and lower reaches， and plays a critical role in maintaining regional ecological security. This study aims to investigate the evolution patterns of runoff under changing environments， thereby providing theoretical support for the sustainable management of water resources in the Shiyou River. Based on monthly runoff data from the Yumen hydrological station and monthly-scale meteorological data， methods including concentration degree， Mann-Kendall trend test， Pettitt change-point test， wavelet analysis， and Budyko model were employed to analyze the intra-annual distribution characteristics， interannual trends， abrupt changes， and periodic variation of river basin runoff， and to quantify the driving effects of climate and underlying surface changes on runoff. The results showed that the intra-annual distribution of runoff in the Shiyou River became more uniform， the concentration period was delayed， and runoff exhibited a pattern of high flow in summer and low flow in winter. From 1978 to 2024， variations in runoff and precipitation in the Shiyou River differed. Runoff exhibited an insignificant increasing trend at a rate of 0.013×10⁸ m³∙10a^-1， while precipitation showed a significant decreasing trend. The abrupt change year for runoff was 2005， after which runoff increased by 25.48%. The abrupt change for precipitation occurred in 1984. The first dominant periods for annual runoff and precipitation were 10 years and 21 years， respectively. Correlation analysis showed that the correlation coefficient of precipitation and runoff before runoff abrupt change was 0.45， and the correlation coefficient after runoff abrupt change was 0.69. The fitting relationship between runoff and precipitation after runoff abrupt change was significantly improved. During the change period of 2005—2024， the elasticity coefficients of runoff to underlying surface parameter， precipitation， and potential evapotranspiration were -1.86， 1.56， and -0.56， respectively. Analysis of the elasticity coefficients indicated that runoff was most sensitive to changes in the underlying surface parameter， followed by precipitation， and least sensitive to potential evapotranspiration. Attribution analysis based on the Budyko model and the double mass curve method yielded consistent results. The contribution rates of underlying surface changes to runoff changes were 126.84% and 110.18%， respectively. In addition， temperature in the Shiyou River Basin showed a significant increasing trend at a rate of 0.31 °C∙10a^-1， and glacier area in the upper reaches of the river basin continued to shrink in response to rising temperatures， decreasing from 17.75 km² in the 1980s to 7.71 km² in the 2020s—a reduction of 10.04 km² over 40 years. These findings indicate that changes in the underlying surface are the dominant factor driving the increase in runoff in the Shiyou River. Specifically， these underlying surface changes are manifested as the conversion of grassland to bare land and the reduction of glacier area caused by rising temperatures. Therefore， future water resource management in the river basin should give high priority to the hydrological effects of human activities.

Glaciers act as temporary reservoirs for atmospherically deposited nitrogen and serve as important environmental media for nitrogen in the geochemical cycle. With climate warming， meltwater from glaciers carries a substantial amount of nitrogen-containing substances into rivers， becoming an important exogenous input that affects the material cycle of river ecosystems and the supply of NO₃ ^-， potentially impacting downstream ecosystems. Investigating the variations and sources of NO₃ ^- in glacial meltwater runoff in high-altitude regions is crucial for understanding regional and global nitrogen cycling processes under climate warming. However， research on the sources of NO₃ ^- in aquatic systems on the Qinghai-Xizang Plateau remains limited， and previous studies often analyze NO₃ ^- variations and sources from a spatial perspective， lacking a temporal dimension. Therefore， this study focused on the Rongbuk River on the northern slope of Mount Qomolangma， primarily recharged by glacial meltwater. The temporal variations in NO₃ ^- concentration and its isotopes in the Rongbuk River water during the glacier ablation period from July 12 to October 15， 2023 were investigated. The Mann-Kendall test was used to analyze the temporal variation characteristics of NO₃ ^- concentration， δ ¹⁸O-NO₃ ^-， Δ¹⁷O-NO₃ ^-， and δ ¹⁵N-NO₃ ^-. Combined with an isotope mass balance model， the contribution proportions of atmospheric and terrestrial NO₃ ^- sources to the Rongbuk River water were quantitatively calculated. The results showed that： （1） NO₃ ^- concentration and its nitrogen and oxygen isotopes in the Rongbuk River water exhibited temporal variation patterns. From July 12 to October 15， 2023， the NO₃ ^- concentration， δ ¹⁸O-NO₃ ^-， and Δ¹⁷O-NO₃ ^- in the Rongbuk River water generally showed decreasing trends， while δ ¹⁵N-NO₃ ^- exhibited an overall increasing trend. Turning points from high to low were identified for NO₃ ^- concentration， δ ¹⁸O-NO₃ ^-， and Δ¹⁷O-NO₃ ^- on September 2， July 25， and July 25， respectively. For δ ¹⁵N-NO₃ ^-， a turning point from high to low to high was observed on October 5. （2） The NO₃ ^- in the Rongbuk River water originated from both atmospheric and terrestrial sources. The contribution proportion of atmospheric NO₃ ^- was （34.96 ± 9.63）%， which decreased from July 12 to August 25， 2023， and then increased from August 25 to October 1， 2023. The contribution proportion of terrestrial NO₃ ^- was （65.04 ± 9.63）%， primarily derived from surrounding soil nitrogen and NH₄ ⁺ in precipitation through nitrification. No sources such as chemical fertilizers， manure， or domestic wastewater were detected in the measured samples. （3） The variations in NO₃ ^- and its isotopes in the Rongbuk River water were mainly influenced by atmospheric input （snowmelt， ice melt， or direct dry/wet deposition） and terrestrial input. The decrease in NO₃ ^- concentration resulted from the combined effect of reduced atmospheric input and weakened nitrification. The decreases in δ ¹⁸O-NO₃ ^- and Δ¹⁷O-NO₃ ^- were closely related to the decrease in the contribution proportion of atmospheric NO₃ ^-. The increase in δ ¹⁵N-NO₃ ^- indicated a shift in NO₃ ^- sources from atmospheric dominance to microbial transformation in soil. This study， for the first time， reveals the temporal variation patterns of nitrogen and oxygen isotopes of NO₃ ^- and NO₃ ^- sources in the Rongbuk River water， addressing the limitation of previous studies that focused only on spatial analysis. This study provides a new scientific basis for studying nitrogen cycling processes in rivers on the Qinghai-Xizang Plateau.

In permafrost regions， the long-term stability of subgrade engineering faces significant challenges. Due to the impact of climate change and engineering activities， permafrost degradation frequently leads to subgrade settlement， deformation， and other distresses， seriously threatening the safe operation of transportation lines. Thermosyphons， serving as a key technology for efficiently regulating the temperature of permafrost subgrades， are widely used in subgrade engineering in permafrost regions owing to their significant advantages of high efficiency and environmental friendliness. Their core working principle relies on the evaporation-condensation cycle of an internal low-boiling-point working fluid， which efficiently transfers heat from deep layers of the foundation to dissipate into the surface air. This actively lowers the foundation temperature， elevates the permafrost table， and maintains the thermal stability of the permafrost beneath the subgrade. However， the engineering cost of thermosyphon embankments is relatively high， and their installation spacing directly affects both the cooling performance and economic efficiency. Excessive spacing leads to insufficient cooling and ineffective suppression of permafrost degradation， while overly dense spacing is economically inefficient. Therefore， scientifically determining the optimal thermosyphon installation spacing is crucial for balancing cooling performance and economic efficiency. It holds significant theoretical and practical importance for ensuring the long-term stability of permafrost subgrades and optimizing engineering investments. Based on the thermosyphon project along the Genhe-Labudalin Highway and using the area’s typical geological characteristics and meteorological data as references， this study employed finite element analysis to establish two-dimensional numerical models for both the cross-section and longitudinal section of a thermosyphon-reinforced subgrade. The models fully accounted for key properties of frozen soil， including the latent heat of phase change， specific heat capacity， thermal conductivity， and unfrozen water migration， as well as the seasonal variations in surface boundary conditions. Through numerical simulations， this study systematically investigated the variations in the subgrade’s temperature field， thawing depth， and heat flux under different thermosyphon spacings （3 m， 4 m， 5 m， and 6 m）， thereby revealing the regulatory mechanism of spacing parameters on permafrost thermal stability. Corresponding model validation was performed to ensure reliability. The results showed that thermosyphons could significantly cool the subgrade. During the cold season， thermosyphons operated at higher power， effectively lowering the temperature of the surrounding soil and increasing subsurface cold storage. During the warm season， the stored cold gradually dissipated outward， delaying the trend of bidirectional thawing in the subgrade and thus maintaining its stability. Furthermore， different installation spacings had a significant impact on the subgrade temperature field. As the spacing increased， the temperature at the subgrade center gradually rose， the thawing depth increased， thermal stability decreased， and the overall cooling effectiveness of the thermosyphons on the surrounding soil gradually weakened. When the thermosyphon spacing was less than 4 m， it could effectively reduce the subgrade temperature， control thawing depth， and ensure thermal stability. After medium-term cumulative effects， thermosyphons spaced at 3~4 m exerted a more pronounced cooling effect on deeper soil layers. Analyzing the application effectiveness over ten years， thermosyphons could significantly raise the permafrost table beneath the subgrade. Smaller installation spacings led to a more pronounced rise. By the 10th year， a stable frozen soil formed between thermosyphons when spaced at 3~4 m. For the specific geological and climatic conditions and thermosyphon type used in the test section of the Genhe-Labudalin Highway， soil temperature changes over time within a 1.7 m radius around a thermosyphon were relatively significant. The effective cooling radius was approximately 2 m， indicating a reasonable spacing range between thermosyphons of 3.4 m to 4 m. Through systematic and in-depth analysis， this study quantitatively reveals the core mechanism by which thermosyphon installation spacing controls their cooling effectiveness on subgrades. Spacing selection requires refined design based on a deep understanding of the thermosyphon’s effective cooling radius， cooling superposition effect， and the concept of “critical spacing”. The findings provide crucial theoretical foundations and practical design references for thermosyphon-reinforced subgrade engineering.

Snow data are crucial for research on climate change， hydrological processes， and disaster assessment. However， obtaining accurate snow cover data in terms of spatial distribution remains a challenge at present. This is primarily due to the dynamic characteristics of snow cover， making acquiring related data more difficult. Traditional field measured data offer high accuracy but are limited in providing large-scale spatiotemporal distribution information of snow cover. Satellite remote sensing can obtain snow cover data with large spatial coverage and long observation periods but is greatly affected by weather and terrain. Additionally， snow cover simulations using models are constrained by differences in model structures and driving data. Reanalysis data， which integrate remote sensing， model simulations， and observational data， can provide accurate snow cover data and offer the potential to capture spatiotemporal variations of snow cover precisely. However， their applicability in specific regions still requires validation. To address this issue， this study conducted a comparative analysis of snow cover percentage （SCP） between MODIS data and reanalysis data at daily， interannual， and intra-annual scales during the hydrological years from 2000 to 2020. Based on defined snow parameters， this study calculated snow cover days （SCD）， snow onset date （SOD）， snow end date （SED）， and snow duration days （SDDs）. The Theil-Sen trend analysis and Mann-Kendall significance test were used to comprehensively compare the spatial variation patterns and significance of snow-related parameters derived from remote sensing and reanalysis data. Using meteorological station data from ground observations， this study compared and analyzed the correlation coefficient （r）， mean bias error （MBE）， and root mean square error （RMSE） between the snow depth from reanalysis data at the corresponding station coordinates and the observed snow depth at the stations. The applicability of ERA5-Land reanalysis snow cover and snow depth data in Xinjiang was assessed. The results showed that： （1） ERA5-Land and MODIS exhibited consistent trends in daily snow cover variations， reflecting seasonal snow cover variations in Xinjiang. In months with low snow cover percentages， ERA5-Land showed good agreement with MODIS. However， notable differences occurred during months with high snow cover （around January）. The two datasets exhibited strong positive correlation and small systematic bias， although ERA5-Land tended to slightly underestimate snow cover. （2） Variations in snow parameters from ERA5-Land were highly consistent with MODIS. ERA5-Land showed a larger area of unstable snow cover and tended to underestimate stable snow cover. In some low-altitude areas， ERA5-Land had delayed SOD and SED compared to MODIS， and SDDs were shorter than those from MODIS. In high-altitude areas， ERA5-Land simulated SOD， SED， and SDDs with higher accuracy： SOD was not significantly delayed， SED was not significantly advanced， and SDDs were not significantly shortened. （3） Comparison between ERA5-Land reanalysis snow depth data and station data showed that the correlation was the weakest at the Tianshan Daxigou station （r=-0.16）. Although the MBE （2.85 cm） and RMSE （8.91 cm） were relatively small， there was an overall overestimation. At other stations， ERA5-Land demonstrated good correlation with observed snow depth， with correlation coefficients ranging from 0.42 to 0.94. Although ERA5-Land captured the variation trend of snow depth （mean r=0.72）， there were significant differences in correlation and errors among different stations. Overall， ERA5-Land slightly overestimated snow depth （mean MBE=6.46 cm）， indicating the need for further optimization to improve simulation accuracy. Snow cover in Xinjiang is not only a crucial source of freshwater but also a key factor in regulating regional climate and maintaining ecological balance. Therefore， accurate monitoring and assessment of snow dynamics are crucial for the sustainable development of Xinjiang. As the latest global reanalysis dataset， ERA5-Land provides long-term and large-scale data support for snow cover-related research. However， although widely used globally， its applicability in Xinjiang has not been thoroughly assessed. Xinjiang’s unique topography and climatic conditions may significantly influence the accuracy of reanalysis data assessment. Therefore， a systematic assessment of ERA5-Land’s applicability in Xinjiang holds important scientific and practical significance. In the context of global climate change， this study provides a scientific basis for the selection and application of ERA5-Land data in snow cover hydrological modeling in Xinjiang， aiming to provide references for related research on snow cover hydrology using reanalysis data in Xinjiang.

In the context of global warming， the degradation of permafrost on the Qinghai-Xizang Plateau has altered the hydrothermal dynamics of the active layer and the surface energy balance， exerting significant impacts on regional ecology， engineering infrastructure， and global climate. Conducting relevant research is of great significance for the safety and stability of alpine ecosystems on the plateau. Due to the complex terrain of the Qinghai-Xizang Plateau and the limited number of monitoring stations， numerical modeling has become a commonly used research approach. However， existing models still have room for improvement in simulating soil moisture. GEOtop is a process-based distributed hydrological model that enhances the simulation of water movement by solving three-dimensional flow equations， yet its application in the permafrost regions of the Qinghai-Xizang Plateau remains relatively limited. Taking the Tanggula station， located in the permafrost region of the Qinghai-Xizang Plateau， as the research object， this study systematically analyzed the variation characteristics of active layer hydrothermal processes and surface energy fluxes based on observational data from 2005 to 2006， and conducted numerical simulation experiments using the GEOtop model. The results showed that soil temperature in the active layer in the Tanggula region exhibited a sinusoidal pattern， with decreasing amplitude and increasing phase lag with depth. Soil moisture displayed pronounced seasonal variations that were closely synchronized with precipitation. The freeze-thaw process was characterized by “unidirectional thawing and bidirectional freezing”. All surface energy fluxes varied seasonally， and sensible and latent heat showed distinct seasonal alternation patterns. In addition， the GEOtop model could well simulate the dynamic variations of soil temperature and moisture， with average correlation coefficients （r） above 0.94. The simulation of the active layer thawing process was also relatively accurate， with a deviation of only 4% in the simulated active layer thickness. Regarding surface energy fluxes， the GEOtop model performed well in simulating net radiation， sensible heat， and latent heat， but its simulation of surface soil heat flux had certain limitations due to the simplified model assumptions. Overall， the GEOtop model can accurately describe the surface-active layer hydrothermal processes in the Tanggula permafrost region， demonstrating certain applicability in permafrost regions on the Qinghai-Xizang Plateau.

Global warming has profoundly altered carbon cycling processes in peatlands of permafrost regions. Against the dual backdrop of climate change and China’s strategic goals of carbon peaking and carbon neutrality， soil organic carbon （SOC） loss from peatlands in permafrost regions have become a critical research focus. However， current studies on SOC in permafrost peatlands of the Da Xing’anling Mountains， Heilongjiang Province， China， remain limited by the lack of high-precision and region-specific SOC databases and predictive models calibrated based on local data. Moreover， research on the coupled carbon-nitrogen-water cycle and its biological regulatory mechanisms in peatland ecosystems remains incomplete， and in situ controlled field experiments remain largely absent. On this basis， this study systematically reviews the spatiotemporal characteristics and primary driving mechanisms of SOC loss from permafrost peatlands in the Da Xing’anling Mountains under climate warming. The results indicate significant spatial heterogeneity in SOC loss across different permafrost regions of the Da Xing’anling Mountains. （1） In continuous permafrost regions， SOC storage is generally high. However， with climate warming causing significant thickening of the active layer and progressive permafrost degradation， SOC mineralization and loss rates have increased significantly. The deepening of the active layer exposes previously frozen carbon pools to microbial decomposition， which may turn these vast carbon reservoirs into enhanced carbon sources. （2） In discontinuous permafrost regions， SOC loss are jointly regulated by air temperature， hydrological dynamics， and vegetation changes. Rising air temperatures directly stimulate microbial activity， while variations in soil moisture critically control anaerobic and aerobic decomposition pathways. Concurrently， changes in vegetation composition and productivity further influence carbon loss. （3） In island permafrost regions， ground temperatures rise more rapidly and permafrost patches are shrinking， and SOC decomposition and lateral transport rates increase significantly. Intense hydraulic erosion and thermokarst development promote both physical migration and biogeochemical processes of SOC. Current studies suggest that this region is particularly vulnerable and may become a substantial carbon source in the future. The temporal variation characteristics of SOC in this region are the core mechanisms controlling its decomposition， mineralization， and migration. Pronounced peaks of carbon dioxide （CO₂） and methane （CH₄） loss occur during the spring thaw period. Snowmelt and changes in surface hydrodynamics increase the export of dissolved organic carbon （DOC） from peatlands. Freeze-thaw cycles affect soil microbial community structure， thereby affecting SOC stability and degradation rates. Freeze-thaw cycles physically disrupt soil aggregates， release protected SOC， and significantly alter soil microbial community structure and function， ultimately influencing SOC stability and subsequent decomposition processes. Therefore， understanding SOC dynamics across temporal scales is essential. SOC loss are driven by the coupled effects of multiple factors， including temperature， soil moisture variability， vegetation type， microbial processes， and soil physicochemical properties such as texture， cation exchange capacity （CEC）， and mineral composition. The complex interactions among these factors ultimately determine the magnitude and pathways of SOC loss. Future research should prioritize the establishment of long-term monitoring networks， the development of high-resolution datasets， and the construction of mechanistic models integrating hydrological， thermal， and biogeochemical processes. The incorporation of isotope tracing techniques and the strengthening of multi-method experimental integration are also needed to systematically elucidate the coupled carbon-nitrogen-water processes and their microbial regulatory mechanisms in peatlands of permafrost regions， thereby providing a more comprehensive understanding of SOC loss dynamics. It is crucial to conduct more in situ controlled field experiments to predict SOC loss patterns under projected future climatic and hydrological changes. This study aims to provide a scientific basis for carbon loss mitigation and climate response research in high-latitude regions under China’s carbon peaking and carbon neutrality strategy.

Glaciers on the Qinghai-Xizang Plateau constitute a crucial part of the “Asian Water Tower”. Their accelerated melt driven by climate warming directly affects water security for hundreds of millions of people in surrounding regions. Despite substantial progress in monitoring recent glacial changes， the understanding of long-term glacial evolution on the Qinghai-Xizang Plateau （particularly in the Himalayas） remains severely constrained by the scarcity of early field observation and remote sensing imagery prior to the 1960s. This study aims to address this critical knowledge gap by reconstructing a comprehensive 65-year record of glacier changes in the central Himalayas from the 1960s to 2025， with particular emphasis on quantifying and explaining the north-south differences in retreat patterns observed across this climatically sensitive mountain range. To this end， this study developed an innovative multi-temporal remote sensing framework integrating early declassified satellite imagery （KH series） with modern satellite imagery. For the 1960s baseline reconstruction， a rigorous image selection protocol was applied， identifying 32 high-quality summer KH images with minimal cloud cover and optimal surface texture clarity. The fundamental challenge of distinguishing glacier ice from seasonal snow in these single-band historical images was addressed through a novel multi-temporal intersection analysis. Snow and ice cover were extracted from all available KH images within specific two-year windows， and their spatial intersection was calculated to effectively isolate persistent glacial ice from transient snow cover. This automated approach was complemented by systematic expert visual interpretation， where glacier boundaries were refined based on morphological characteristics， flow patterns， and topographic relationships. Geometric accuracy was ensured through precise georeferencing against Landsat TM baselines， with controlled experiments demonstrating that approximately 50 well-distributed ground control points per image achieved optimal balance between positional accuracy （mean error of 4.7 m） and processing efficiency. The resulting 1960s glacier inventory was then integrated with glacier extents for 1995 and 2025， derived from Landsat TM and OLI imagery， respectively， using the normalized difference snow index （NDSI） with expert-assisted corrections for debris-covered ice and seasonal snow. To analyze the climatic drivers of the observed changes， this study utilized the high-resolution CRU TS reanalysis dataset， extracting and statistically evaluating temperature and precipitation trends specifically for the northern and southern slopes of the study area. The results revealed a pattern of substantial and accelerating glacial retreat across the central Himalayas. The total glacier area decreased from 5 749.12 km² in the 1960s to 4 519.84 km² in 2025， representing an overall reduction of 21.38%. More significantly， the rate of loss accelerated markedly， with area reductions of 9.33% during 1960s—1995 increasing to 13.29% during 1995—2025. A particularly striking observation was the pronounced spatial divergence in retreat behavior between the northern and southern slopes. Glaciers on the southern slope， influenced by the Indian monsoon system， experienced a distinct “warm-dry” climatic pattern characterized by a 2.3 ℃ increase in summer temperatures and a 12% decrease in precipitation from the 1960s to 2025. These glaciers exhibited rapid and accelerating retreat， with area reductions of 12.61% （1960s—1995） and 17.03% （1995—2025）， accompanied by severe morphological fragmentation as large contiguous ice masses disintegrated into numerous smaller glaciers. In contrast， glaciers on the northern slope， dominated by westerly circulation， experienced a “warm-wet” climatic pattern， with a more moderate 1.7 ℃ temperature increase and an 8% precipitation increase over the same period. Correspondingly， these glaciers retreated more gradually， with area reductions of 5.16% and 8.92% during the respective periods， while generally maintaining greater structural integrity. In summary， as the only high-resolution satellite data source available in the early period， KH imagery， using the 1960s as a baseline， quantitatively captures the accelerated process and spatial heterogeneity of glacier changes in the central Himalayas. This study highlights the critical influence of two climate patterns—“warm-dry” and “warm-wet”—on glacier dynamics， deepens the understanding of atmosphere-glacier interactions， and provides additional historical data support for elucidating the long-term driving mechanisms of regional climate change on glaciers.

The Ranwu-Tongmai section of the Parlung Zangbo serves as a critical strategic corridor connecting Xizang with inland China. This area is characterized by complex landforms， deeply incised valleys， widely distributed maritime glaciers and seasonally frozen soil， and high sensitivity to climate change. In the context of global climate change， the region experiences severe freeze-thaw erosion and frequent landslide hazards， which often damage roads， disrupt traffic， and cause significant losses. With China’s continuously increasing investment in Xizang’s infrastructure development， the exchange of personnel and goods through this corridor has undergone rapid growth. Consequently， there is an urgent need to systematically identify potential landslide hazards and implement specifically targeted risk prevention measures to effectively reduce regional landslide risks. This study utilized multi-temporal sub-meter high-resolution remote sensing images archived in Google Earth from 2015 to 2023. Based on interpretation indicators such as color variations， drainage patterns， landform characteristics， and vegetation changes， landslides were identified and delineated through visual interpretation. The final landslide inventory was determined through a field investigation conducted in April 2024， with remote sensing interpretations rigorously validated via on-site inspections to ensure accuracy. Twelve landslide-related characteristic variables， including the freeze-thaw intensity index （FTI） and summer rainfall， were selected. Correlation analysis was conducted to remove variables with high collinearity， and the remaining variables were used to construct the dataset. A 90 m grid cell was selected as the evaluation unit. The landslides involved 3 271 grid cells in total， which were set as positive samples with a label value of 1. An equal number of non-landslide grid cells were randomly selected within the study area as negative samples， resulting in a total of 6 542 samples. Seventy percent of both positive and negative samples were randomly allocated to construct the training dataset， while the remaining 30% were reserved exclusively for the testing dataset. Both training and testing datasets maintained an identical 1∶1 ratio of positive to negative samples. Three machine learning models—random forest （RF）， support vector machine （SVM）， and multilayer perceptron （MLP）—were trained and validated using these datasets to assess regional landslide susceptibility. The importance of each characteristic variable obtained from the RF algorithm and correlation analysis was used to analyze the main controlling factors. The results showed that the study area had abundant rainfall and contained 296 landslides in total， predominantly small to medium in size. These landslides were mainly distributed within the elevation range of 3 500~4 500 m， on sunny slopes （67.5°~202.5°）， and in regions with FTI values greater than 0.6. All three algorithms—RF， SVM， and MLP—demonstrated robust landslide prediction performance. Among these， RF achieved superior performance indicators： Accuracy （0.82）， Recall （0.85）， F1-score （0.83）， Jaccard Index （0.70）， and AUC （0.90）， outperforming SVM （AUC = 0.87） and MLP （AUC = 0.86）. Feature importance analysis revealed four main controlling factors on landslide susceptibility： slope aspect （25.63%）， elevation （18.82%）， summer rainfall （14.05%）， and freeze-thaw intensity index （9.83%）. Among them， elevation and slope aspect determined the material basis and energy conditions for slope landslides， while rainfall and freeze-thaw cycles were external triggering factors for landslide development. The susceptibility assessment results from the RF， SVM， and MLP models showed that the distribution of high and very high susceptibility zones was basically consistent， and the areas of very high susceptibility zones were nearly identical. The study area was divided into two target zones for landslide hazard mitigation. For the Guxiang-Tongmai section， special attention should be given to the impact of rainfall， with landslide mitigation focusing on improving water-catching structures and drainage systems. Meanwhile， for the Ranwu-Yupu section， landslide mitigation should prioritize the effects of freeze-thaw cycles， implementing measures such as insulation and seepage prevention to enhance the frost resistance of the geotechnical materials. These findings not only contribute to the risk prevention and control of potential landslide hazards along the Ranwu-Tongmai section of the Parlung Zangbo in the high-altitude alpine mountainous areas， but also provide a reference for subsequent engineering decision-making in disaster mitigation and prevention for regional landslide hazards.

Saline soils are widely distributed in China’s seasonally frozen soil regions. In recent years， the construction scale of major infrastructure projects such as airport runways， highway subgrades， and transmission tower foundations in saline soil areas has continuously expanded， often partially or completely covering the saline soil foundation. Under the repeated action of seasonal freeze-thaw cycles， water and salt within the saline soil foundation gradually migrate downward beneath the cover layer and continuously accumulate， thereby inducing the cover effect. This effect is the primary cause of engineering distresses such as frost boiling， differential settlement， and salt heave， posing a serious threat to the long-term stability and service safety of engineering structures in cold regions. Therefore， investigating the evolution patterns of water and salt migration in unsaturated sulfate saline soil under the cover effect during freeze-thaw cycles holds significant scientific research value and engineering practical significance. Such investigation is crucial for deeply revealing the mechanisms underlying these engineering distresses and for refining the theoretical framework for preventing and controlling engineering hazards in saline soils in cold regions. To investigate the water and salt migration patterns in unsaturated sulfate saline soil under the cover effect during freeze-thaw cycles， soil column tests were conducted under sealed conditions to analyze the characteristics of water and salt migration within the saline soil subjected to multiple freeze-thaw cycles. Subsequently， based on the principles of heat and mass conservation and incorporating a salt crystallization kinetics model， a coupled water-vapor-heat-salt mathematical model for unsaturated sulfate saline soil considering the cover effect was developed. The numerical solution of this model was obtained using the COMSOL Multiphysics software. By comparing the simulation results with the experimental data from the soil column tests， the reliability of the established model was validated. Then， the numerical model was employed to further reveal the variation patterns of the moisture field， temperature field， and salt field within the soil column during the freeze-thaw process. The results indicated that under the action of freeze-thaw cycles， both the liquid water content and salt concentration in the surface soil layer increased with the number of cycles. By the 10th freeze-thaw cycle， the liquid water content and salt concentration in the surface soil layer at a depth of 0.35 m increased by 2.5% and 5.5 kg·m^-³， respectively， compared to their initial values. During the freezing period， the liquid water flux in the surface soil layer was zero， while the liquid water in the underlying unfrozen zone migrated upward. During the thawing period， the liquid water in the surface soil layer migrated downward. During the freezing period， the water vapor flux in the surface soil layer was significantly greater than the liquid water flux， indicating that vapor migration was the dominant mechanism for moisture accumulation in the surface soil. The matric suction of the surface soil layer generally decreased with an increasing number of freeze-thaw cycles， while that of the deeper soil layer increased overall. The matric suction gradient formed between the surface and deeper soil layers served as the key driving force for water and salt migration. Through a combination of laboratory experiments and numerical simulations， this study revealed the patterns of water and salt migration in unsaturated sulfate saline soil under the cover effect during freeze-thaw cycles， and clarified the dominant role of vapor migration and the driving effects of the matric suction gradient. The research findings not only deepen the understanding of the mechanisms underlying engineering distresses in saline soils in seasonally frozen soil regions， but also provide an important theoretical basis and data support for developing effective mitigation measures， such as optimizing drainage systems， installing barrier layers， or regulating the properties of cover materials.

Traditional laboratory tests for determining the shear strength of frozen soil are time-consuming， labor-intensive， and unable to meet the dynamic prediction requirements of cold-region engineering. To address these limitations， this study aims to develop an efficient and interpretable prediction framework for frozen soil shear strength based on ensemble learning techniques. Specifically， four ensemble strategies—Boosting， Bagging， Stacking， and Voting—were employed to integrate multiple base learners and to investigate the effects of different ensemble mechanisms on model performance. Silty sand collected from the Inner Mongolia region was selected as the research material. Through a series of laboratory direct shear tests， a dataset containing 768 samples was established， with freezing time， freezing temperature， moisture content， axial pressure， and shear strength serving as key features. A total of 27 models， including single base models， Bagging ensembles， and Boosting ensembles， were constructed and compared in terms of predictive accuracy. The nine best-performing models were then selected as base learners for constructing Stacking and Voting ensemble models. Model performance was comprehensively evaluated using the coefficient of determination （R ²）， mean absolute error （MAE）， and mean squared error （MSE）， and the influence of each feature was examined through feature importance analysis. The results demonstrate that the Stacking model achieved superior overall performance （R ²=0.998， MAE=1.7091， MSE=6.4233）， outperforming the Voting model （R ²=0.9979， MAE=1.6864， MSE=6.7903）. Both models exhibited consistent feature importance rankings， namely： moisture content > freezing time > freezing temperature > axial pressure. These findings indicate that moisture content and freezing time are the dominant factors controlling the shear strength of frozen soil. In conclusion， this study confirms that an appropriately designed ensemble learning strategy can achieve high-accuracy predictions using a small number of easily measurable parameters. The proposed approach not only reduces the cost and time of traditional testing but also enhances model interpretability. It provides an effective， economical， and scientifically robust method for predicting the shear strength of frozen soil， offering valuable insights for stability assessment and design optimization in cold-region geotechnical engineering.

Glacial lake outburst flood （GLOF） is one of the most destructive glacier hazards. Under the influence of global climate warming， the risk of GLOF hazards has increased due to the intensified glacier ablation， increase in the number and size of glacial lakes， reduced stability of alpine slopes， and the expansion of human activities into mountainous areas. Bibliometric analysis， characterized by objectivity， comprehensiveness， and efficiency， is applied in this study based on the CNKI and WOS databases to systematically review the development trends， major research institutions and researcher groups， and core research themes related to GLOF. Additionally， this study further reviews and summarizes research progress on global GLOF inventory data sources and methods， spatiotemporal distribution characteristics， types of outburst glacial lakes and their influencing factors， the simulation of GLOF process chain， hazard assessment， early warning， and mitigation strategies. The results show that GLOF research has received widespread academic attention since 2010， with the number of publications increasing rapidly. The GLOF records have shifted from investigations and qualitative descriptions of individual or localized glacial lakes to the systematic inventory of global events， with a gradual expansion of inventory attributes. The Andes and High Mountain Asia regions have the highest number of outburst glacial lakes， while the northwestern North America has the highest frequency of GLOF events. Global GLOF events have been increasing at a rate of 37 events·（10a）^-1， with July and August being the peak occurrence periods. GLOF simulation has transitioned from qualitative descriptions and empirical models to quantitative whole-process chain simulations based on physical models， enhancing the understanding and predictive capability of hazard evolution mechanisms. However， the acquisition， validation， and calibration of key model parameters remain major focus areas and challenges in current research， and are key directions for future breakthroughs. Governments and management authorities prevent and mitigate GLOF disasters mainly through risk and hazard mapping， early warning systems， and engineering and non-engineering measures.