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 R²=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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 R₁ 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.

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 （T₂ 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 T₂ 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.

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.

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.

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.

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⁻ > SO₄²⁻ > CO₃²⁻. （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.

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.

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.

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.

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.