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.

Non debris cover-type glaciers， with minimal surface debris cover， can effectively reduce the interference of surface debris in the response to climate change， enabling glacier changes to more directly reflect climate signals. In this study， the geographical location， altitude， and scale of glaciers were comprehensively considered， and 54 non debris cover-type glaciers were selected as the study objects. Using Sentinel-2 and Landsat （5/7/8） remote sensing data， the spatiotemporal characteristics of glacier area changes from 2000 to 2021 were analyzed. In addition， the causes of glacier changes were examined using regional climate factors， long-term area variation data of typical glaciers， and glacier flow velocity data. The results showed that over the past 22 years， all 54 glaciers exhibited advancing trends， with area increases ranging from （0.02±0.81） km² to （35.07±0.01） km² （all change rates <25%）， and glacier flow velocities at elevations below 4 500 m increased. Regional annual air temperature increased （with minimal warming in summer）， annual precipitation increased， and cloud cover expanded， leading to a reduction in radiative flux and thereby slowing regional glacier ablation under these climate change conditions. The accelerated glacier terminus flow velocity caused the glaciers to be in an advancing state. The findings of this study provide a basic dataset for research on Karakoram glaciers， deepen the understanding of the “Karakoram anomaly”， and offer scientific guidance for glacier conservation and water resource management in alpine regions.

In the southeastern Qinghai-Xizang Plateau， the formation mechanisms of glacial debris flows have often been attributed to the phenomenon of rain-heat synchronization （simultaneous occurrence of high temperature and precipitation）. However， such explanations tend to neglect the indispensable role of sediment source conditions and their temporal evolution patterns， and rarely addresses the physical coupling mechanisms resulting from the interaction of long-term sediment accumulation and short-term meteorological driving forces. This study takes the glacial debris flow that occurred in the Dadalongba tributary on July 10， 2020 as a case study. By integrating multi-source remote sensing imagery and meteorological data， this study aims to reveal the mechanisms by which sediment source conditions and rainfall-temperature background jointly control debris flow occurrence. To investigate sediment source evolution， Landsat 8 and PlanetScope images from 2015 to 2023 were utilized. A target area at the glacier terminus was extracted， from which the areas of ice-snow and vegetation zones were subtracted to obtain the distribution of potential exposed sediment sources. By integrating a high-resolution digital elevation model （DEM）， the variation patterns of sediment source across different slope gradient ranges were further quantified. The results showed that in 2019， due to snow and ice melting and glacier retreat， the exposed moraine area in the Dadalongba tributary reached a temporary peak. Among these， sediment source was most concentrated on slopes of 30°~50°， which became the main material source for the 2020 debris flow. In 2020， continued high temperatures accelerated glacier retreat， leading to further exposure of moraines at the glacier terminus. This process established the essential material basis for a large-scale debris flow. In terms of meteorological conditions， using daily precipitation and temperature records from local stations and grids， this study revealed that in the 10 days preceding the event， the region experienced persistently high temperatures accompanied by frequent and intense rainfall events， forming a typical concurrent rainfall-temperature background. Persistent high temperatures accelerated glacier ablation and meltwater production， while multiple heavy rainfall events directly triggered slope instability. A comparison of the summer meteorological data from 2015 to 2023 indicated that concurrent rainfall-temperature conditions similar to that of 2020 also occurred in 2017 and 2021， but no large-scale debris flows occurred during those years. The critical difference lay in sediment source conditions. Only in 2020 did glacier retreat and concentrated moraine exposure reach a peak， which， combined with extreme meteorological inputs， ultimately exceeded the threshold for debris flow occurrence. This comparison demonstrated that extreme meteorological conditions alone were insufficient to induce debris flows. Rather， the coupling of long-term sediment accumulation and short-term extreme weather events served as the decisive factor. The results demonstrated that the 2020 Dadalongba glacial debris flow was not triggered solely by concurrent rainfall-temperature conditions， but it resulted from the combined effects of long-term sediment source evolution， sudden increase in moraine exposure， and extreme meteorological events. It was precisely this sediment source-meteorology coupling mechanism that made 2020 the only year among multiple years in which the disaster occurred. This finding suggests that hazard assessment of glacial debris flows should not rely solely on meteorological thresholds， but must also consider sediment source dynamics， slope gradient distribution， and their temporal evolution patterns. From a broader perspective， the Dadalongba case deepens our understanding of the physical formation mechanisms of glacial debris flows under concurrent rainfall-temperature backgrounds in the southeastern Qinghai-Xizang Plateau. It emphasizes that debris flow hazard assessments should go beyond relying solely on meteorological thresholds to explicitly incorporate sediment source dynamics， slope gradient distribution， and their temporal evolution. This integrated understanding is essential for predicting future debris flow occurrence in regions experiencing accelerated glacier retreat under climate change. In particular， the synergy between glacier ablation， moraine exposure， and extreme meteorological events is expected to become increasingly common， thereby increasing the risk of sudden debris flow disasters across the southeastern Qinghai-Xizang Plateau. Furthermore， by establishing a reproducible framework that combines multi-temporal remote sensing with meteorological analysis， this study offers both methodological and conceptual innovations.

In the context of global warming， alpine glaciers are melting at an accelerated rate， significantly increasing the frequency of glacial lake outburst flood （GLOF） disasters. GLOFs are sudden， large-scale， and highly destructive， often causing severe damage to downstream settlements， transportation networks， and infrastructure. In the Nyainqentanglha Mountains of the southeastern Qinghai-Xizang Plateau， both the number and area of glacial lakes have increased significantly since the 1980s. Similar to other high mountain regions in Asia， this area is characterized by high elevation， harsh climate， and limited accessibility， leading to scarce field observations and highly uncertain hydrological data， which constrain detailed analysis of GLOF processes. To overcome the problem of data scarcity， related studies in recent years have increasingly used multi-source data approaches to supplement and reconstruct the evolution and outburst processes of glacial lakes.Cuoga Glacial Lake is located in Banbar County， Qamdo， Xizang， at an elevation of about 4 774 m. It is a terminal-moraine-dammed valley lake directly connected to its feeding glacier. On 29 July， 2009， a GLOF occurred at Cuoga Glacial Lake， causing two deaths， damaging about 27 km of roads， destroying two steel bridges and four concrete bridges， and washing away two cars and 17 motorcycles. However， due to the lack of measured hydrological data， key hydrodynamic parameters， including discharge， flow depth， and flow velocity， had not been quantitatively reconstructed for this event.This study integrated multi-source data and numerical simulation methods to analyze the triggering mechanisms and reconstruct the evolution of the 2009 Cuoga GLOF. The data used included multi-temporal optical remote sensing imagery （Landsat， Sentinel-2， GeoEye-1， etc.）， an ALOS PALSAR DEM with 12.5 m resolution， ITS_LIVE glacier velocity products， and WheatA meteorological data， supplemented by field survey results.The analysis showed a pronounced pre-outburst warming period that accelerated glacier melt and increased lake storage. ITS_LIVE data indicated an increase in velocity near the glacier terminus， and interpretation of remote sensing imagery also identified clear evidence of ice collapse into the lake. On the basis of comprehensive assessment， the outburst was triggered by the combined effects of long-term glacier melt due to climate warming and short-term collapse of unstable ice into the lake. The ice collapse likely generated displacement waves in the lake， causing overtopping of the terminal moraine dam， which， under high hydraulic pressure， initiated progressive erosion and ultimately led to dam instability and failure.The outburst flood process was numerically simulated using the HEC-RAS 2D unsteady hydrodynamic model. The computational mesh had a base resolution of 20 m， with local refinement to 10 m. Based on elevation-area observation data， a lake storage capacity curve was constructed using the cumulative-maximum correction method. The corrected series was then fitted with a PCHIP monotonic spline， and the elevation-volume relationship was calculated via trapezoidal numerical integration. The simulation results showed that the total outflow volume was about 4.17×10⁶⋅m³， with a peak discharge of 3 432.11 m³⋅s^-1 occurring about 17 minutes after the outburst. Within the 12-hour simulation， the flood propagated 25.10 km downstream. The maximum flow velocity reached 26.42 m⋅s^-1 at about 1 km downstream of the breach， while the maximum flow depth of 22.51 m occurred 6.17 km downstream in a narrow valley. During the simulation， the flood did not reach the river section of Jagong Township， and the large elevation difference between settlements and the valley floor prevented direct impacts on local infrastructure. The results were consistent with historical records of the event. Sensitivity analysis indicated that， with the parameter settings adopted in this study （n = 0.05 and Δt = 0.5 s）， the CFL number was approximately 1.03， close to the theoretical stability limit， demonstrating that the model ensured both numerical stability and computational efficiency. Spatial consistency evaluation showed a good agreement between the simulated flood extent and flood traces interpreted from GeoEye-1 imagery， with F1-scores around 0.8 and Kappa coefficients ranging between 0.6 and 0.8. The total volume balance error was less than 0.1%， validating the reliability of the simulation results.The findings of this study fill the hydrodynamic data gap for this Cuoga Glacial Lake outburst flood event and demonstrate that integrating multi-source data with HEC-RAS numerical simulation is effective for reconstructing GLOFs in data-scarce regions. In the context of ongoing global warming， strengthening the dynamic monitoring and early warning systems of glacial lakes is essential for reducing the risk of future glacial lake outburst disasters.

Snow avalanches are one of the major natural hazards frequently occurring in the cryosphere， exerting significant impacts on the vegetation environment， transportation， infrastructure， and the safety of people living in cold regions. Therefore， it is urgent to gain a clear understanding of the dynamics of avalanche formation and to establish corresponding early warning systems. Dry snow slab avalanches， which often occur in snow-covered plateau mountainous areas， are the most common and dangerous type of avalanche. Dry snow slab avalanches are triggered by the failure of a weak layer buried beneath a cohesive slab. However， current research lacks an understanding of the dynamic crack propagation following weak layer failure and its response to snowpack parameters and terrain slope angles. In addition， the stress variations at the contact interface between the weak layer and the base layer remain unclear. In this study， a three-dimensional typical snowpack structure was established using the discrete element method， and the dynamic mechanism of dry slab avalanche formation was analyzed from a micromechanical perspective. The results showed that the failure of the weak layer led to the settlement and collapse of the overlying slab， exhibiting distinct spatiotemporal distribution characteristics. The settlement displacement increased with the thickness of the weak layer， slab density， and terrain slope angle. The critical crack length followed an exponential decay relationship and decreased with increasing snowpack parameters （slab density and the thickness of the weak layer） and slope angle. The crack propagation velocity was divided into three stages： initial propagation， dynamic propagation， and stable propagation. After reaching stable propagation， the velocity ranged between 10~40 m·s^-1. Stress analysis at the interface between the weak layer and the base layer indicated that the normal stress increased with increasing slab density， decreased with increasing slope angle， and was insensitive to the changes in the thickness of the weak layer. Numerical simulations based on microscopic mechanisms provide a deeper understanding of the avalanche formation process.

Glaciers are highly responsive to climate change， exhibiting rapid responses in both mass balance and extent. Meanwhile， runoff processes in glacierized catchments are undergoing significant changes. Accurate simulation and prediction of these changes are essential for the sustainable management of water resources and for mitigating the risks posed by glacial floods and debris flows. Based on observational records and remote sensing data from the Hailuogou Basin on the eastern slope of Mount Gongga， this study coupled the SWAT hydrological model with a glacier energy-mass balance model to simulate glacier mass balance and runoff dynamics. Furthermore， the driving factors of rapid glacier ablation and the impacts of runoff changes were analyzed. The results showed that the glaciers in the Hailuogou Basin experienced accelerated mass loss from 1990 to 2020， with an overall mean rate of -0.05 m w.e.·a^-1. The equilibrium-line altitude rose by nearly 400 m. Above the equilibrium-line altitude， mass accumulation declined （-0.22 m w.e.）， whereas ablation intensified below it. Influenced by debris cover， the mass balance within the ablation zone showed an initial increase followed by a decrease from the terminus. The main driving factors of rapid glacier ablation were rising temperatures， reduced solid precipitation supply， and declining surface albedo. The temporal pattern of glacial meltwater was consistent with that of runoff. During the summer months， glacial meltwater accounted for 36.4% of the total runoff. In the coupled SWAT-glacier modelling framework， glacial meltwater constituted 57.1% of the total runoff， exceeding the contributions from rainfall， snowmelt， and baseflow. Under the SSP2-4.5 and SSP5-8.5 scenarios， glacial runoff will decline persistently， consequently weakening its regulatory role in hydrological processes. This study provides effective scientific guidance for the management of glacial water resources and related hazard mitigation in the Mount Gongga region under climate change.

Although many existing studies have preliminarily examined the climatic characteristics of the Mingyong Glacier and Laohugou Glacier No. 12 regions， several critical research gaps remain. First， existing studies predominantly focus on the basic characteristics and long-term trends of climatic elements， while the analyses of the spatiotemporal characteristics of climatic abrupt changes and their periodic variation patterns remain relatively weak. Second， the lack of long-term continuous observational data in glacial regions significantly hinders the in-depth understanding of the relationship between climate change and glacial dynamic responses. Finally， there is a notable lack of systematic comparative research on climate change between maritime and continental glacier regions， which considerably constrains the accurate understanding of the mutual feedback mechanisms between different glacier types and the climate system. To address these research gaps， this study combined ERA5-Land reanalysis data with station observational data and established a statistical correction model between reanalysis data and observed data. On this basis， a long-term climate dataset was reconstructed covering the 65-year period from 1960 to 2024. Utilizing methods such as climate tendency rate， cumulative anomaly， Mann-Kendall mutation test， and Morlet wavelet analysis， this study systematically analyzed the variation trends， abrupt change characteristics， and periodic patterns of temperature and precipitation in the Mingyong Glacier （maritime glacier） and Laohugou Glacier No. 12 （continental composite valley glacier） regions. The results demonstrated that the annual average temperature in both glacier regions increased at the same rate of 0.14 °C·（10a）^-1， and temperatures in all seasons all showed a consistent warming trend. Regarding abrupt change characteristics， temperature in the Mingyong Glacier region underwent a significant abrupt change around 1992， while that in the Laohugou Glacier No. 12 region occurred around 2015， indicating differential response mechanisms between maritime and continental glacier systems. Analysis of precipitation patterns revealed substantial differences between the two glacial systems. The annual precipitation in the Mingyong Glacier region decreased significantly at a rate of -27.3 mm·（10a）^-1， with an abrupt change occurring in 2003. In contrast， the annual precipitation in the Laohugou Glacier No. 12 region increased slightly at a rate of 3.3 mm·（10a）^-1， with no significant abrupt changes identified during the entire study period. Periodicity analysis showed that the dominant periods of temperature change were 36 years for the Mingyong Glacier region and 35 years for the Laohugou Glacier No. 12 region. Precipitation change demonstrated even more substantial differences， with the Mingyong Glacier region showing a dominant 60-year cycle compared to a 36-year cycle for the Laohugou Glacier No. 12 region. The integrated assessment showed that the Mingyong Glacier and Laohugou Glacier No. 12 regions exhibited fundamentally different responses to climate change across multiple dimensions. The contrasting precipitation trends， combined with the distinct timing of temperature shifts and different cyclical patterns， collectively highlighted the complex， spatially heterogeneous impacts of climate change on western China’s glacial systems. The earlier and more pronounced climatic responses observed in the maritime Mingyong Glacier system reflected a heightened sensitivity to climate perturbations， whereas the delayed and moderated responses in the continental Laohugou Glacier No. 12 system demonstrated the buffering capacity of extreme continental climates. Furthermore， the changes in both glacier systems were driven by the synergistic effects of temperature and precipitation changes， albeit through different mechanistic pathways and operating at different temporal scales. This study systematically elucidates the differential characteristics of climate change impacts on continental versus maritime glacier regions， providing not only essential scientific evidence for understanding the heterogeneous responses of western China’s glaciers to global warming but also crucial practical guidance for glacier conservation， sustainable regional water resource management， and climate adaptation planning. The findings emphasize the necessity of implementing region-specific approaches for glacier monitoring and climate change adaptation in mountain systems， recognizing that standardized policies may be insufficient to address the diverse challenges faced by different glacier types in a rapidly warming world.

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.

Snow ablation is a critical hydrological process in cold regions. Accurately quantifying the snow ablation process is key to revealing the effects of snow cover on regional hydrothermal dynamics and hydrological processes. Based on daily precipitation， air temperature， and snow depth data from 34 meteorological stations in the Greater Khingan Mountains area from 1974 to 2020， this study employed statistical methods to analyze the spatiotemporal distribution of frequency， intensity， and extreme values of snow ablation events， as well as their influencing factors. Definitions of key variables were as follows. A snow ablation event was identified when the snow depth on the second day minus that on the first day was negative， coupled with a daily maximum air temperature greater than 0 ℃ on the first day and no recorded precipitation on that day. Constraining the daily maximum air temperature to above 0 ℃ effectively mitigated the impact of snow compaction. The intensity of a snow ablation event was defined as the absolute value of the decrease in snow depth between two consecutive days. Extreme snow ablation events were determined using the percentile method. For each meteorological station， all snow ablation events from 1974 to 2019 were arranged in ascending order based on ablation intensity. The 95th percentile value of this ordered sequence was defined as the extreme threshold for that station. A snow ablation event was classified as extreme if its intensity exceeded the station-specific threshold. A rain-on-snow event was defined as a day with a snow depth greater than 0 cm， daily precipitation greater than 0 mm， and a daily average air temperature below the rain-snow threshold temperature. The rain-snow threshold temperature was calculated using elevation， latitude， longitude， annual total precipitation， and annual average air temperature. The results showed that the snow cover start date in the Greater Khingan Mountains area advanced with increasing latitude， the snow cover end date was delayed with increasing latitude， and the snow cover duration increased with increasing latitude. The frequency， intensity， and cumulative ablation of snow ablation exhibited distinct latitudinal gradients and significant north-south differences. Snow ablation events were more frequent and intense in the northern region than in the southern region. The snow ablation frequency exceeded 6 events⋅a^-1 in the northern region， but was generally less than 3 events⋅a^-1 in the southern region. Snow ablation intensity in the north typically exceeded 6 cm⋅d^-1， while it was less than 4 cm⋅d^-1 in the south. The annual average cumulative snow ablation in northern region exceeded 16 cm， while it was less than 8 cm at most stations in the southern region. Snow ablation events predominantly occurred in March and April in the Greater Khingan Mountains area. The extreme snow ablation threshold exceeded 6 cm in the northern region but remained below 5 cm in the southern region. Rain-on-snow events in the eastern part of the central Greater Khingan Mountains area contributed significantly to the frequency of extreme snow ablation events. Snow ablation frequency and intensity showed significant positive correlations with annual snowfall and annual average snow depth in the Greater Khingan Mountains area. Among these， annual snowfall and annual average snow depth showed stronger correlations with snow ablation frequency. Scatter plots demonstrated that most snow ablation events occurred mainly within the ranges of 5~30 cm for annual snowfall and 0~5 cm for annual average snow depth. During the cold season in the Greater Khingan Mountains area， snow ablation events occurred when the daily maximum air temperature ranged from -4 ℃ to 10 ℃ and the daily average air temperature ranged from -12.5 ℃ to 5 ℃. The highest frequency and intensity were distributed in the higher ends of these temperature ranges. The findings of this study can provide a scientific basis for water resource management and snowmelt flood prediction in the Greater Khingan Mountains area.

Snow cover serves as a sensitive and active factor in the cryosphere， playing an important role in regional water resource cycles， energy balance， and climate system in the context of global warming. Using MODIS cloud-free snow area data， meteorological data， digital elevation model （DEM）， and atmospheric circulation indices， this study defined the snow cover days （SCD）， fractional snow cover （FSC）， and snow cover year as key indicators. Sen’s slope and Mann-Kendall trend tests were used to analyze the variation trends and significance of snow cover patterns. Partial correlation coefficients were used to analyze the relationships between the SCD and meteorological factors， while Pearson correlation coefficients were used to assess the relationships between the maximum snow area ratio and atmospheric circulation indices in northwest Yunnan. The results indicated that： （1） Temporally， the SCD in northwest Yunnan fluctuated from 2000 to 2019， with an annual average of 20.3 days and a decreasing rate of -0.3 d·（10a）^-1. Spatially， the SCD in northwest Yunnan during this period showed a decreasing trend， with fewer areas experiencing increases. The number of days with high snow accumulation， typically exceeding 60 days， was mainly concentrated in the Dandanglika Mountain， Gaoligong Mountain， Nu Mountain， Yunling Mountain， Yulong Snow Mountain， Meili Snow Mountain， and Shangri-La Mountain Range. （2） The FSC ranged from 0% to 55.43% during this period， with a slight decadal change rate of -0.08%·（10a）^-1. The annual variation exhibited a single peak pattern， with the accumulation period extending from October to May of the following year. The FSC generally increased from October to February of the following year. Despite temporary reductions of snow cover observed between November 21 to December 9 and February 2 to 12， the overall trend was upward， peaking at 19.84% on February 18. The high snow cover predominantly occurred from January to March， and only minimal snow coverage was present from June to September. （3） Topographic differences significantly influenced SCD distribution. Areas at elevations between 4 000 and 6 000 m persistent snow cover exceeding 60 days annually， while regions below 3 000 m averaged fewer than 10 days. The most rapid decreases in SCD occurred in stable snow cover areas with the elevation range of 4 000~5 500 m. Both spatial distribution and temperature variation trends showed significant elevation dependence， with high-elevation areas experiencing more pronounced effects under climate warming. The most rapid decrease （-0.35 d·a^-1） occurred at 5 000~5 500 m elevation. East-facing slopes had the highest SCD （31 days） and also the fastest decreasing rate （-0.052 d·a^-1）. （4） Regional warming and drying trends during snow accumulation periods significantly contributed to FSC reduction. SCD showed a significant positive correlation with precipitation and negative correlation with temperature， with high-elevation areas demonstrating stronger responses to climate factors. The maximum FSC from October to January of the following year in northwest Yunnan was significantly positively correlated with the NAO during the same period. This study advances the understanding of spatiotemporal snow cover variations in northwest Yunnan and provides valuable reference for regional hydrological processes and climate change studies.

Under the background of global warming， the cryosphere in the High Mountain Asia （HMA） is undergoing rapid degradation， altering slope stability in glacial basins and leading to a significant increase in the frequency and scale of glacial catastrophic multi-phase mass flow （CMMF） hazards， which mainly include ice/rock/snow avalanche-debris flows， glacial lake outburst flood-debris flows， and rainfall/meltwater-compounded glacial debris flows. These hazards pose severe threats to the sustainable development， infrastructure， and human security of the vulnerable mountain communities in HMA. However， research on glacial CMMF hazards still faces significant obstacles due to data scarcity and a lack of ground-based validation. This study reviews the current status of research on glacial CMMF hazards in HMA， aiming to achieve three main objectives： comprehensively analyze the spatiotemporal distribution patterns of historically documented glacial CMMF hazard events in HMA； elucidate in detail the unique formation mechanisms， triggering factors， kinematic dynamics， and hazard characteristics of each major hazard type （ice/rock/snow avalanche-debris flows， glacial lake outburst flood-debris flows， and rainfall/meltwater-compounded glacial debris flows）； and summarize key future research directions.This study compiles statistics on historical glacial CMMF hazard events in HMA and reveals their unique spatial patterns and temporal trends. The results indicate that a total of 1 972 glacial CMMF hazard events are recorded in HMA. Among them， ice/rock/snow avalanche-debris flows （668 events） are mainly distributed in the Pamir region and occur most frequently between January and March. Glacial lake outburst flood-debris flows （830 events） are distributed in the Karakoram， Tien Shan， and Himalayan regions， peaking between June and August. Rainfall / meltwater-compounded glacial debris flows （474 events） are most frequent in the southeastern Xizang and the Hindu Kush regions， occurring during the warm and rainy period from June to August. This reveals the unique spatial patterns and temporal trends of historical glacial CMMF hazard events in HMA. Secondly， a comparative analysis of the triggering factors， phase composition and transformation， and movement characteristics of different types of glacial CMMF hazards in HMA is conducted. The results demonstrate that global warming is the primary trigger for glacial CMMF hazards. Ice/rock/snow avalanche-debris flows are mainly triggered by a combination of internal factors such as drastic topographic changes and bedrock structure， and external factors such as earthquakes and glacial stress release. Glacial lake outburst flood-debris flows are mostly caused by dam instability induced by precipitation， ice/rock/snow avalanches， or high temperatures. Rainfall/meltwater-compounded glacial debris flows are driven by high temperatures and precipitation. Glacial CMMF hazards consist of multiphase materials including ice/snow， rock masses， supraglacial debris， and water. Their movement process involves phase transformation between water-rock flows， debris flows， and mudflows， characterized by enormous volumes （> 10⁶ m³）， high movement speeds （> 5 m·s^-1）， long hazard distances， and high energy. They also exhibit quasi-periodicity， high climate sensitivity， and susceptibility to disaster chain reactions. This review highlights the high and increasing vulnerability of HMA to diverse and increasingly frequent glacial CMMF hazards under current climate change. Although significant progress has been made in event documentation and understanding of fundamental processes， major challenges related to data scarcity and complex process remain. The comprehensive understanding of historical distribution patterns and detailed process characteristics provides a critical foundation for advancing research and disaster reduction efforts. The proposed future research directions， including database construction， comprehensive hazard assessment， monitoring and early warning， and a combined approach of engineering prevention and control， are crucial for significantly enhancing hazard prediction capabilities， mitigating disaster risks， and ultimately strengthening environmental resilience. The research findings and future research framework proposed in this study aim to provide a scientific basis for strengthening glacial CMMF hazard assessment systems， developing effective early warning systems， and formulating science-based risk governance and mitigation strategies tailored to the complex challenges in HMA. Furthermore， the insights gained and the methodologies discussed offer valuable reference and experience for other high-mountain regions globally facing similar cryospheric hazards， thereby making an important contribution to promoting broader developments in global cryospheric hazard research and climate change adaptation.

Global warming has led to glacier retreat， resulting in the extensive exposure of moraine. In the Yarlung Zangbo River Basin of southeastern Xizang， moraines formed through glacial erosion， transportation， and deposition constitute thick overburden layers characterized by high boulder content and strong cementation. However， these moraines exhibit an extremely wide particle size distribution and complex permeability characteristics， making them prone to forming seepage channels. This poses significant challenges for hydropower construction in the Yarlung Zangbo River Basin. The study area is located in the Yigong Zangbo Basin within the mountainous valley region of southeastern Xizang—a zone experiencing intense uplift and erosion of the Qinghai-Xizang Plateau. Characterized by glaciated terrain with dramatic relief and deeply incised valleys， it exhibits typical alpine canyon topography. During the Quaternary glaciation in this river basin， glaciers advanced extensively into the main valley. Notably， the preserved lateral moraine ridges extend to elevations as low as 2 400 m， directly overlapping with the study area’s elevation range of 2 400~2 700 m. The Xibengnongba Gully basin exhibits an elongated morphology， with its highest ridge crest reaching 5 578 m. Active modern glaciers remain in the upper reaches， where the glacier tongue ends at approximately 3 580 m. Downslope from the glacier tongue， prominent lateral moraine ridges （15~40 m high） flank the channel， extending to a minimum elevation of 3 070 m. Distinct geomorphic features of lateral and terminal moraine ridges formed by direct glacial action were clearly visible. Under glacial activity， moraine developed a densely compacted structure with porosity similar to that of sandy soil， averaging 26.14%. Constant head permeability tests under low hydraulic gradients measured initial hydraulic conductivity values ranging from 0.88 to 4.56 mm⋅s^-1. Permeability deformation tests on undisturbed samples provided the most accurate characterization of their permeability. However， conducting undisturbed tests at field sites was practically challenging， and transporting large-volume undisturbed moraine samples to laboratories over long distances was infeasible. Therefore， this study investigated the permeability and seepage stability of moraine deposits in the upper Yigong Zangbo Basin （a tributary of the Yarlung Zangbo River） through permeability deformation tests that maintained their natural structure. Five samples （S1~S5） collected from the Xibengnongba Gully yielded curvature coefficients of 1.03， 4.18， 2.07， 3.50， and 0.61， and uniformity coefficients of 64.52， 58.11， 16.58， 34.85， and 28.86， respectively. According to coarse-grained soil gradation criteria， S1 and S3 were classified as well-graded gravels， while S2， S4， and S5 were poorly graded gravels. The results showed that： （1） the moraine in the Xibengnongba Gully of the Yigong Zangbo Basin， Xizang， formed during the Quaternary glacial period. Modern glaciers in the upstream area were situated at elevations as low as 3 580 m， while distinct geomorphic features—including lateral moraine ridges （15~40 m high） and terminal moraine ridges shaped by direct glacial action—were evident downstream. It was inferred that after entering the Yigong Zangbo River， the moraine material primarily accumulated downstream from the gully mouth， resulting in spatial zonation of different lithologies within the moraine overburden of the Xibengnongba Gully. （2） In the thick moraine overburden of the upper Yigong Zangbo， prolonged overburden pressure and glacial static pressure compacted the deposits during accumulation， reducing interparticle porosity and enhancing physical cementation. This resulted in a critical hydraulic gradient as high as 1.75. During permeability deformation testing， progressive hydraulic gradient increases enabled stage division via the lgJ-lgv curve， revealing three sequential phases： stable seepage stage， internal instability stage， and seepage failure stage. Significant piping erosion was clearly observed on the moraine surface during the internal instability stage. （3） Spearman correlation analysis of particle gradation characteristics revealed that the seepage stability of moraine deposits was significantly influenced by the characteristic particle size d ₃₀ and the coefficient of uniformity （C _u）. Both the critical and failure hydraulic gradients exhibited significant negative correlations with C _u and d ₃₀， establishing d ₃₀ as a key indicator for determining piping in undisturbed moraine soil. This study not only elucidates the deformation and failure mechanisms of thick moraine deposits under seepage， but also provides theoretical support for seepage control in major hydropower projects in the Yarlung Zangbo River Basin.

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.

Against the backdrop of an increasingly pronounced warming and humidification trend on the Qinghai-Xizang Plateau， snowmelt runoff in the source region of the Yangtze River， driven jointly by precipitation and meltwater from glaciers and snow， is likely to exhibit new variation characteristics. In this study， the daily snowmelt runoff contribution in the source region of the Yangtze River was calculated using the variable infiltration capacity （VIC） hydrological model and daily gridded meteorological data from 1980 to 2022. Furthermore， spatiotemporal patterns of snowmelt runoff variations from April to June were extracted using the rotated empirical orthogonal function （REOF） method， and the dominant influencing factors were subsequently identified. The results showed that over the past 43 years， snowmelt runoff during the key period from April to June in the source region of the Yangtze River showed no significant overall increasing or decreasing trend. However， pronounced spatial heterogeneity was observed， and the region could be divided into four typical spatial zones. In the western mountainous area with elevations above 4 800 m， including the Geladandong Glacier， the snowmelt runoff showed a continuous and significant increasing trend， with an annual increase rate of 1.02 m³⋅s^-1. The snowmelt runoff increased steadily from 15.82 m³⋅s^-1 in 1980 to 58.49 m³⋅s^-1 in 2022， representing an increase of nearly 3.7 times. In contrast， the central region with relatively flat terrain and its adjacent southeastern edge exhibited pronounced periodic variation characteristics. Before 2002， both regions maintained similarly stable and minimally changing characteristics. After 2002， however， they showed completely opposite trends， with a significant decreasing trend in the central region contrasting sharply with a rapid increase along the southeastern edge. Although the matching of water and thermal conditions is the fundamental cause of changes in snowmelt runoff in the source region of the Yangtze River， changes in snowmelt runoff across most areas except the northern part mainly depend on the amount of precipitation from April to June. Over the past 43 years， regions experiencing increased precipitation from April to June have witnessed a significant rise in snowmelt runoff， and vice versa. These inter-regional differences in multi-year precipitation result in significant spatial differentiation of snowmelt runoff changes.

As a key indicator of permafrost degradation， thermokarst lakes have a significant impact on the thermal state， hydrological processes， ecological environment， and the stability of permafrost engineering in the surrounding regions. However， existing studies on the identification of thermokarst lakes are constrained by the complex terrain and underlying surface of the Qinghai-Xizang Plateau， the widespread cloud， fog， snow， and ice， and the limitations of the identification methods and image resolution. As a result， there is a severe omission of small thermokarst lakes on the Qinghai-Xizang Plateau. In this study， the vegetation red edge based water index （RWI）—which exhibits high discrimination capability for the boundaries of small water bodies—was employed based on Sentinel-2 imagery. Supplemented by manual visual interpretation to exclude rivers and snow cover， this approach achieved accurate identification of thermokarst lakes on the Qinghai-Xizang Plateau. On this basis， the frequency ratio method was applied to assess the correlation between environmental factors and thermokarst lake development. By superimposing the weighted products of the frequency ratios of different environmental factors， a susceptibility zoning map for thermokarst lakes was established. The results showed that for thermokarst lake extraction， the RWI achieved an overall accuracy （OA） of 98.97%， a producer’s accuracy （PA） of 85.52%， a user’s accuracy （UA） of 83.12%， and a Kappa coefficient of 0.8118， demonstrating high identification accuracy. A total of 182 668 thermokarst lakes were identified on the Qinghai-Xizang Plateau， with a total area of 2 456.13 km². These lakes generally exhibited the characteristic that “small thermokarst lakes were numerous with a small proportion of the total area， while large ones were few but accounted for a large proportion of the total area”. The ranking of different environmental factors by their degree of influence on thermokarst lakes was as follows： slope > elevation > active layer thickness （ALT） > normalized difference vegetation index （NDVI） > ground ice content > precipitation > annual average ground temperature. The susceptibility zoning results of thermokarst lakes showed that the low-susceptibility zones accounted for the largest proportion of the area （31.01%） but contained only 4.04% of the thermokarst lakes， with a density of 2.01 lakes per 100 km². The combined area proportion of high and very high-susceptibility zones was only 25.19%， yet they concentrated 84.30% of the thermokarst lakes. Specifically， the point density in very high-susceptibility zones reached 77.92 lakes per 100 km²， which was 38.76 times that of low-susceptibility zones.

In the context of climate change， extreme flood events have occurred with increasing frequency in many regions， making rapid extraction of flood inundation extent essential for disaster monitoring， emergency response， and post-disaster assessment. The Aksu River Basin in northern Xinjiang is a typical flood-prone region that is frequently affected during summer by the combined effects of intense precipitation and accelerated glacier and snowmelt， often resulting in sudden flood events. Therefore， timely and accurate identification of surface water dynamics during flood processes is crucial for enhancing disaster response capacity， safeguarding lives and property， and supporting regional flood mitigation and risk management. In this study， the Aksu River Basin was selected as the study area， and the Google Earth Engine （GEE） cloud computing platform was employed to fuse Sentinel-1 synthetic aperture radar （SAR） data with Sentinel-2 optical imagery to construct a multi-source remote sensing feature set. A random forest （RF） classifier was applied to extract surface water bodies in 2024. Accuracy assessment indicated that the proposed method achieved an overall accuracy （OA） of 0.93 and an F1-score of 0.91， demonstrating good classification performance. Furthermore， multi-temporal remote sensing data were used to analyze the spatiotemporal variations in surface water area and to assess flood inundation extent within the river basin. The results showed that major flooding in 2024 was concentrated between June and September. Water extent began to increase in early June， reached its maximum between late July and early August， and then gradually declined. Flooding predominantly affected bare land and agricultural areas， with a total inundated area exceeding 100 km². This study demonstrates the effectiveness of multi-source remote sensing data fusion combined with cloud-based processing for rapid mapping of flood extent and provides technical support for regional flood monitoring and emergency management.

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.

As a key sensitive area of global climate change， the Qinghai-Xizang Plateau is characterized by widespread permafrost and massive ground ice reserves. Their formation， distribution， and changes are of great significance to regional ecohydrology， engineering stability， and permafrost evolution. However， due to the significant spatial heterogeneity of ground ice distribution， studies on its spatial patterns， depth distribution characteristics， recharge sources， and formation processes remain limited. Based on field drilling and stable isotope （δ ¹⁸O， δD） techniques， this study conducted a systematic investigation of the distribution， ice content， isotopic composition， and formation processes of ground ice in the Beiluhe located in the hinterland of the Qinghai-Xizang Plateau. The results showed that： （1） the ground ice in the Beiluhe region exhibited a vertical pattern characterized by high ice content in shallow layers， which gradually decreased with depth. Notably， a significant enrichment of ground ice was observed within the depth range of 2.4~3.2 m， with high-ice-content layers occurring within fine-grained silty clay strata. （2） Stable isotope analysis revealed that the ground ice was mainly recharged by atmospheric precipitation， with lake water and spring water also contributing to some extent. （3） The formation processes of deep ground ice， dominated by pore ice and cemented ice， occurred through rapid freezing under cold climatic conditions， whereas the formation of segregated ice was dominated by slow freezing. This study preliminarily reveals the recharge sources and formation processes of ground ice in the Beiluhe River of the Qinghai-Xizang Plateau， providing important data support and a theoretical basis for assessing the hydrological effects of permafrost degradation and tracking permafrost evolution. It is of great significance for a deeper understanding of the formation and evolution of ground ice in permafrost regions.

Glacier tourism is one of the ecological services provided by glaciers to humans. It serves as an important support for socio-economic development in mountainous regions worldwide and is profoundly influenced by glacier change. This study uses glaciers as the link， with the main theme being “glacier change-glacier tourism-glacier tourism research”. Based on the latest facts of glacier change globally and in China and current domestic and international research findings on glacier tourism， this study elaborates on the logical connection between glacier change and glacier tourism， analyzes the stages of glacier tourism research， and outlines the new trends emerging in this field. This study aims to provide valuable insights for the sustainable development of glacier tourism in China. The latest facts of glacier change demonstrate that its trends are consistent globally and in China， characterized by significant mass loss and accelerated melting rates. The logical relationship between glacier change and glacier tourism is complex. Glacier change not only leads to the aesthetic degradation of glaciers and increases related hazard risks but also shapes new glacial landform landscapes， exerting both positive and negative impacts on glacier tourism. Glacier change directly affects the attributes and travel routes of glacier tourism destinations and indirectly affects tourist demand and behavioral intentions， thereby influencing the entire glacier tourism industry. Glacier tourism research is a new field with distinct stage-specific characteristics. Before 2015， research primarily featured descriptive empirical studies with relatively basic content. Since 2015， the field has grown exponentially， with a greater emphasis on glacier tourism services and sustainable development， climate change impacts and adaptation， tourist behavior and motivation， and future development trajectories. These studies have expanded the breadth， enhanced the depth， and increased the scholarly impact of glacier tourism research. The research focus differs between China and the international community. Chinese research primarily concentrates on resource assessment， development， planning， service evaluation， and value estimation of glacier tourism. In contrast， international research places greater emphasis on visitor-level studies， adaptation strategies for various stakeholders， and future development directions. Consequently， China needs to strengthen its research on aspects such as the tourist demand， behavioral motivations， choice preferences， and willingness to pay， while enhancing studies on adaptation to glacier tourism and its future development. In recent years， four new trends have emerged in glacier tourism research： glacier tourism services as a new research perspective； last chance tourism as a new hotspot in tourist motivation studies； international initiatives and government actions for glacier protection as a new driving force for adaptation research； and the shift from last chance tourism to dark tourism as a new direction for future development. The accelerated glacial retreat profoundly affects global glacier tourism. Both current last chance tourism and dark tourism in the post-glacial era aim to raise public awareness of environmental protection and promote the effective implementation of glacier protection strategies.

Glacial erosion is a key process shaping high-altitude and high-latitude regions and plays a pivotal role in the coupled evolution of the climate-tectonic-surface system. Accurate quantification of glacial erosion processes is essential for understanding landscape evolution across glacial-interglacial cycles and for predicting topographic responses to future climate change. Numerical models have become vital tools for simulating the spatiotemporal dynamics of glacial erosion and integrating ice-flow dynamics with the tectonic context. However， due to the difficulty of directly observing subglacial environments， these models inevitably rely on empirical parameters and simplified assumptions， leading to significant uncertainties in their predictions.This study systematically reviews the developmental trajectory of numerical models for glacial erosion， spanning from physically based abrasion and quarrying equations to catchment-scale numerical modeling frameworks. It focuses on two representative catchment-scale models： （1） The iSOSIA model， which uses a higher-order shallow ice approximation coupled with ice-flow dynamics to achieve high-fidelity simulation of erosion processes； and （2） OpenLEM， which employs a simplified empirical power-law relationship and is designed for efficient simulation of long-term landscape evolution. Although modeling studies have made significant progress， their reliability remains constrained by poorly defined key parameters （such as the erosion coefficient k_g and the velocity exponent l） and necessary simplifications of critical processes （such as subglacial hydrology and the coupling of abrasion and quarrying）.Calibrating and validating these models urgently requires independent， precise observational data as constraints. Erosion rates， as a fundamental quantitative indicator of glacial erosional capacity， naturally serve as a key benchmark for model validation. This study comprehensively reviews methods for estimating glacial erosion rates across timescales from annual to million-year scales， including direct observation， morphometric analysis of glacial valleys， repeat topographic surveys， sediment flux monitoring， cosmogenic nuclide analysis， and low-temperature thermochronology. Each method has its unique spatiotemporal resolution and applicability. However， all share a common fundamental challenge of erosion signal mixing. Specifically， observational data from these methods are typically a composite of signals derived from multiple processes， including glacial erosion， periglacial activity， fluvial incision， and hillslope processes. This integration makes it exceptionally difficult to isolate the pure glacial erosion signal that is essential for robust model validation.To overcome the dual challenges of model uncertainty （from inadequate validation） and erosion signal mixing （from process mixing）， this study explores emerging techniques with the potential to separate erosion signals and reconstruct high-resolution glacial erosion histories. It highlights the potential of the cosmogenic nuclide depth-profile method applied to continuous sedimentary sequences. By analyzing the vertical distribution of cosmogenic nuclide concentrations （e.g.， ¹⁰Be） in continuous strata such as river terraces， this method can reconstruct temporal variations in catchment-averaged erosion rates. Importantly， when combined with provenance-tracing techniques， it enables the quantitative separation of the relative contributions of glacial and non-glacial erosion to sediments， thereby extracting a purer glacial erosion signal.Building on these advances， this study proposes a synergistic research framework for glacial erosion studies. This framework promotes a closed-loop integration that uses high-quality， process-interpretable observational data to drive model optimization and， simultaneously， employs validated， physically reliable models to deepen data interpretation. By deeply integrating refined erosion rate estimation （for example， through novel methods such as cosmogenic nuclide depth-profile method） with next-generation numerical models， this framework systematically enhances the quantitative rigor， mechanistic understanding， and predictive capability of glacial erosion research. Ultimately， this synergistic pathway enables a more accurate depiction of the role of glaciers in the long-term evolution of Earth’s surface.

Damming events are a driving force in shaping the geomorphic evolution of mountainous regions and can better reveal the formation mechanisms of modern fluvial landforms. The Parlung Zangbo River is located north of the Great Bend of Yarlung Zangbo River. During the Last Glaciation， glaciers in this river basin were highly active. This study took nine typical glacial valleys in the Parlung Zangbo River Basin as research objects. Methods including V-index analysis and PalaeoIce model simulations were comprehensively applied to analyze the variations in glacier scale and valley morphological characteristics， and to explore the relationship between glacial activity and damming events. The results showed that： （1） glacial model simulation results indicated that during the Last Glaciation， the nine glaciers in the Parlung Zangbo River Basin had a relatively large scale. At present， the area of the nine glaciers is 270.86 km²， and their total volume is 15.56 ± 2.11 km³. The palaeo-glaciers covered a total area of 722.66 km²， which was 2.6 times that of modern glaciers. The total volume of the palaeo-glaciers was （92.23 ± 12.9） km³， which was 5.9 times that of modern glaciers. The accumulation area ratio （AAR） method was used to calculate the equilibrium line altitude （ELA）， with an AAR value of 0.60. The mean ELA of the nine modern glaciers was 4 822 m a.s.l.， and the ELA of palaeo-glaciers during the Last Glaciation was 4 504 m a.s.l.， which was 318 m lower than the present ELA. （2） Valley topography significantly constrained the differentiation of glacier morphology and movement patterns. The V-index analysis confirmed that in the Parlung Zangbo River Basin， valley morphology resulted from the combined effects of glacial erosion and subsequent fluvial modification. Variations in terrain slope have also led to diverse glacial development patterns： steep short valleys， composite valleys， and gentle long valleys. （3） By combining simulation results with analyses of terminal moraine landforms， glacial expansion provided the geomorphological conditions and material basis for river damming， indicating widespread potential for damming landforms. However， the formation of ancient dammed lakes was influenced by multiple factors， including glacier characteristics， valley landforms， and river incision. Few lacustrine sediments were preserved upstream of the studied valleys. This study provides new evidence for understanding the role of glaciers in the evolution of river landforms in the southeastern Qinghai-Xizang Plateau.

Debris-covered glaciers represent a special type of mountain glacier. Debris cover affects both glacier mass balance and hydrological processes within glacier basins by influencing glacier melt rates， while its transport and deposition provide material sources for periglacial ecosystems and the development of glacier-related hazards. The extent and thickness of debris vary with glacier dynamics. However， the accuracy and timeliness of existing publicly available debris distribution datasets remain limited. Therefore， it is necessary to conduct an updated investigation based on recent archived and consistent remote sensing images to obtain a comprehensive understanding of the current distribution of debris-covered glaciers and their debris. Based on a combination of Landsat 8/9 remote sensing images and multi-source high-resolution composite images around 2023， this study interpreted the debris cover extent of debris-covered glaciers in western China using both visual interpretation and a threshold method， and analyzed the spatial distribution patterns and regional variations of debris-covered glaciers. Additionally， the overall data accuracy and uncertainties were evaluated. The sources of debris supply were examined， and the ecological， hydrological， and hazard-related implications of debris cover within glacier basins were discussed. The results showed that there were 1 571 glaciers covered by debris in western China， of which 476 glaciers had a debris cover ratio of less than 10%， while 1 095 glaciers had a debris cover ratio greater than 10%. The total debris-covered area amounted to about 2 263.02 km²， with individual glacier areas ranging from 0.14 km² to 359.98 km². These glaciers were primarily distributed across the Trans-Himalaya and western Tianshan， whereas debris cover was very limited in the interior of the Qinghai-Xizang Plateau. Among these glaciers， those with an area smaller than 10 km² were the most numerous， while glaciers with areas ranging from 10 km² to 100 km² contributed the largest proportion of the total debris-covered area， accounting for approximately 45.5%. There were 12 debris-covered glaciers larger than 100 km²， mainly distributed across the western Tianshan， Karakoram， Pamir Plateau， southeastern Xizang， and Hengduan Mountains. In addition， 23 glaciers became detached from their parent glaciers at scarps due to rapid downwasting， forming independent debris-covered glaciers downstream （with a debris cover ratio of 100.0 %） in the low-altitude， debris-covered sections， with sizes ranging from 0.14 km² to 4.10 km². In terms of area-elevation distribution characteristics， debris-covered glaciers were primarily located at elevations between 2 375 and 8 731 m in western China， while the debris layers were mainly distributed between 2 375 and 6 532 m. Debris was most concentrated within the elevation band of 4 700~4 900 m. Within the elevation range of 2 300~4 700 m， the debris-covered area exhibited an increasing trend with elevation， accounting for approximately 59.21% of the total debris-covered area. These findings indicate that the spatial differences in the extent and distribution characteristics of debris cover are closely related to glacier size， physical properties， local topographic conditions， and the material supply characteristics of the debris layer. The dynamic changes of debris cover will directly influence the ablation processes of regional glaciers and their response to climate change， while also exerting significant direct impacts on ecology and mountain hazard risks. Therefore， although the identification and extraction of debris-covered glaciers still face many practical challenges， accurate and timely mapping and inventorying of debris-covered glaciers and precise delineation of debris cover extent remain fundamental for conducting glacier ablation modeling， assessing ecological impacts， and mitigating glacier-related hazards in a warming climate. The dataset obtained in this study demonstrates overall good consistency with publicly available debris-cover datasets， while offering improved timeliness and accuracy. It can generally represent the current status of debris-covered glaciers in western China and serves as a reliable foundation for understanding their distribution characteristics， as well as for studies on glacier ablation modeling and hazard risk assessment under different future warming scenarios.

Supraglacial debris is a prevalent surface feature in the ablation zones of numerous glaciers across the Qinghai-Xizang Plateau and its surrounding regions. In contrast to clean ice or snow， supraglacial debris exhibits distinct thermodynamic processes due to its inherent physical properties， which significantly regulate ice melt rates and their spatial patterns. These processes exert profound impacts on the mass balance response mechanisms of debris-covered glaciers （DCGs）， watershed hydrological processes， and the evolution of associated hazards. Against the backdrop of climate warming and rapid glacier retreat in the Qinghai-Xizang Plateau， supraglacial debris cover on glaciers continues to expand and thicken， making the spatial distribution of key parameters of the debris cover and its increasingly prominent impacts a major focus of scientific research. However， systematic observations of supraglacial debris and its associated physical properties across glaciers in the Qinghai-Xizang Plateau and its surrounding regions remain relatively limited， which hinders the improved understanding of the responses of DCGs to climate change and their associated impacts， as well as the ability of glacier numerical models to account for debris cover effects. This review addresses this limitation in DCG research by using the thermal resistance of the debris layer to achieve an accurate representation of the spatial heterogeneity of supraglacial debris and its properties. This parameter is defined as the debris thickness divided by the thermal conductivity of the debris layer. This study centers on the theoretical framework， model assumptions， and inherent uncertainties of estimating the thermal resistance of the debris layer. It systematically reviews the development history， methodological evolution， and application progress of quantitatively retrieving key parameters of the debris with remote sensing-derived thermal resistance as the core. In addition， it provides an in-depth analysis of the critical scientific issues and challenges currently faced by algorithms for remote sensing inversion of the thermal resistance of the debris layer. Based on this， future research directions for the refined inversion of the thermal resistance of supraglacial debris are proposed from three dimensions： multi-source data fusion， inversion algorithm optimization， and the construction of a comprehensive database of key supraglacial debris parameters. Collectively， these efforts mark an important step forward in advancing knowledge of remote sensing inversion of the thermal resistance of the debris layer and its applications. This review aims to provide essential data support and scientific references for accurately assessing changes in debris-covered glaciers and their cascading effects in the Qinghai-Xizang Plateau and its surrounding regions under ongoing climate change.

The cryosphere—encompassing ice sheets， glaciers， sea ice， seasonal snow， permafrost， and river and lake ice—is one of the most sensitive components of Earth’s climate system and a key interface linking atmospheric forcing， hydrological variability， and ecological responses. Rapid cryospheric change under ongoing warming has intensified impacts on global sea level， regional water resources， ecosystem stability， and disaster risk in polar and high-mountain environments. Meanwhile， cryospheric research has entered an era characterized by the simultaneous expansion of data-intensive observations （e.g.， satellite remote sensing， in situ monitoring， and UAV surveys） and increasingly sophisticated numerical modeling. However， the field faces persistent challenges： exponential growth of heterogeneous data streams， fragmentation of domain knowledge across languages and formats， limited scalability of historical data recovery， and high technical thresholds for model development and reproducibility.Large language models （LLMs） have recently demonstrated strong capabilities in semantic understanding， reasoning， and code generation. However， general-purpose LLMs remain constrained in scientific contexts by factual hallucinations， insufficient physical consistency， and semantic gaps between unstructured language and specialized multimodal scientific data. Against this backdrop， this study aims to systematically evaluate the potential roles of LLMs in cryospheric science and to propose a forward-looking pathway toward cryosphere-specific large language models （CryoLLMs） that are more reliable， physically grounded， and workflow-oriented. Objective The core objective of this study is to clarify how LLMs can be mapped onto critical cryospheric research needs—ranging from literature synthesis to model development and hazard communication—while identifying the principal technical bottlenecks and ethical boundaries that must be addressed for responsible deployment. It further proposes a development blueprint for CryoLLMs， emphasizing multimodal alignment， retrieval grounding， physical constraints， and multi-agent orchestration as key design principles.Methods （review and framework construction）　Methodologically， this study conducts a structured review and conceptual synthesis. Specifically， it （i） summarizes foundational mechanisms through which LLMs acquire and manipulate knowledge， with emphasis on their capacity for long-context understanding， semantic abstraction， and tool-augmented reasoning； （ii） organizes potential cryospheric applications into a coherent “data-to-knowledge-to-decision” intelligent workflow； and （iii） develops a problem-driven framework that links cryospheric tasks to enabling AI modules （e.g.， retrieval-augmented generation， multimodal representation learning， code agents， and multi-agent systems）.Key findings　The analysis identifies multiple high-value application directions for LLMs in cryospheric science. First， LLMs can accelerate knowledge integration and frontier detection by automating multi-document understanding and synthesis across rapidly expanding， multilingual literature， reducing the manual burden of tracking evolving themes and conceptual linkages.Challenges and proposed CryoLLMs pathway　The study summarizes challenges across four dimensions—data， algorithms， engineering integration， and ethics/governance—highlighting that cryospheric deployment is constrained by multimodal semantic misalignment， lack of built-in physical constraints， disconnection from established research toolchains， and uneven regional data coverage. From an ethical perspective， it emphasizes the importance of verifiability， traceable evidence， and uncertainty reporting； data sovereignty and privacy in cross-border collaborations； and fairness concerns arising from geographic imbalances in training data. To address these issues， the proposed CryoLLMs pathway focuses on： （1） building high-quality multilingual and multimodal corpora and domain knowledge graphs for semantic alignment； （2） integrating retrieval-augmented generation and physics-aware constraints to improve factual and physical consistency； and （3） adopting multi-agent architectures to transition from isolated tasks to automated， end-to-end research workflows.Conclusions and significance　Overall， the study concludes that LLMs can reshape cryospheric research by improving literature synthesis， historical data recovery， model development efficiency， early-stage mechanism discovery， and risk communication， provided that reliability， physical consistency， workflow integration， and responsible governance are prioritized as core requirements. Additionally， it points out several limitations. The AI landscape is evolving rapidly， which may lead to shifts in specific technical routes. Cryosphere-specific evaluation benchmarks and real-world validations remain insufficient， indicating that many projections are still conceptual and require systematic empirical testing.

Accurate precipitation measurement is essential for understanding the hydrological cycle， optimizing water resource management， supporting meteorological forecasting， and enhancing disaster early warning capabilities. High-altitude regions， which serve as critical water source areas for extensive downstream regions， place particularly stringent requirements on the accuracy of precipitation observations. However， these regions have long been plagued by sparse precipitation gauge networks， complex precipitation phases， and strong wind disturbances， leading to large measurement errors and substantial uncertainties in traditional precipitation gauges. Although the Parsivel² laser disdrometer offers advantages under such conditions， its observations are also susceptible to strong wind effects， which can distort the observed drop size distribution （DSD） and consequently lead to biases in precipitation calculation. To address this issue， this study used continuous observation data collected from the Dadongshu Mountain Yakou Station in Qilian County， Qinghai Province from January 2024 to July 2025. Periods were identified when the precipitation measured by Parsivel² was notably higher than that measured by the Geonor T200B weighing precipitation gauge within the double fence intercomparison reference （DFIR） system. Based on this， abnormal particle identification and filtering were applied to the observed DSD data. Considering that strong winds and turbulent effects may induce non-physical particle fall behaviors， some particles appeared in the diameter-velocity space as low-velocity large particles or high-velocity small particles that did not conform to physical laws. Such particles generally did not represent the actual fall characteristics of precipitation particles， but resulted from the combined effects of factors such as wind-induced disturbances， particle overlap， and fragmentation. To address these abnormal features， reasonable diameter-velocity constraints were established to eliminate particles that clearly deviated from the physically plausible range， thereby reducing the impact of abnormal observations on the overall DSD structure. Based on the initial filtering of abnormal particles， the theoretical terminal velocities of typical precipitation particles were further introduced as physical constraints to classify and process the remaining valid particles. According to differences in density， morphology， and fall characteristics among different precipitation types， the observed particles were categorized accordingly， and the average fall velocity of each category was calculated. Subsequently， taking the theoretical terminal velocity of the corresponding precipitation type as a reference， targeted corrections were applied to the observed average fall velocities， making the statistical characteristics of particle velocities closer to their physically reasonable values. Compared with simple empirical corrections or uniform threshold approaches， this method effectively preserved valid observational information while substantially reducing the systematic influence of wind speed on particle velocity distribution， thereby significantly improving the overall physical consistency of the DSD and providing a more reliable data basis for subsequent precipitation recalculation based on the DSD. To evaluate the calibration results， the variation characteristics of the DSD were systematically analyzed. The results indicated that after calibration， abnormal particles were effectively eliminated， while the remaining valid particles became more concentrated around the theoretical velocity curves， resulting in a DSD more consistent with microphysical laws. Finally， using the 30-min precipitation from the DFIR system as a reference， precipitation was recalculated by combining the calibrated DSD with five density models and compared with the original Parsivel² output. The results indicated that although the Parsivel² original output exhibited a strong correlation with the precipitation from the DFIR system， the calculated precipitation values derived from the calibrated DSD combined with reasonable density models had a more concentrated distribution and lower dispersion. Further analysis showed that the recalculated precipitation during moderate and heavy snowfall periods remained higher than that recorded by the DFIR system， whereas the estimated precipitation during intense soft hail periods was generally lower. These discrepancies may arise from both the underestimation of the DFIR system and uncertainties of the models. Therefore， further comprehensive analyses incorporating additional independent observation methods are required to improve the precipitation calculation method of the Parsivel².