In recent years， the retreat of global glaciers has accelerated in the context of climate warming. However， there is a positive glacier mass balance anomaly in the West Kunlun Mountains of the northwestern Qinghai-Xizang Plateau. Previous studies found that the mass gain in this region started as early as 1970s， and several glaciers have recently surged. Many large-scale glaciers are concentrated in the main peak area of West Kunlun Mountains， and the mass balance anomaly of glaciers in the West Kunlun Mountains has attracted extensive attention. However， there many states of the glacier tongue simultaneously， such as advance （normal）， shrinkage， stable and surge. The advance and retreat of glaciers are not only related to the mass balance influenced by climate change， but also closely related to the glacier velocity. Previous studies mostly focused on the former， but less on the latter. Therefore， this study uses the ITS_LIVE v01 velocity product， combined with the glacier surface elevation changes and thickness to analyze the characteristics and possible causes of glacier surface velocity change with different states of terminus dynamic in the West Kunlun Mountains from 2000 to 2018， to further understand the glacier motion and velocity changes under the same climate change scenario. The results showed that during the study period， the mean velocity of glaciers in the West Kunlun Mountains was 6.35 m⋅a^-1， and showed a fluctuating upward trend， which was caused by the mass gain caused by the thickening of glacier ［（0.15±0.02） m⋅a^-1］. The mean velocity of advanced glacier was about 4.07 m⋅a^-1， and showed an increasing trend during the study period， which was resulted by the slight mass gain， the average velocity of retreat glacier was about 4.86 m⋅a^-1， and showed an decreasing trend， this was caused by the mass loss during the period， the mean velocity of stable glacier was 3.04 m⋅a^-1， and the mass balance of this type glacier was basically stable from 2000 to 2018. In the study area， the mean velocity of advanced glacier is smaller than the retreat glacier， because the value of retreat glacier is larger than the advanced glacier. From 2000 to 2018， seven glaciers surged， and the surge period was concentrated in 2010—2015. During the study period， the thickness of the surge-type glaciers increased significantly ［（0.35±0.02） m⋅a^-1］， resulting in an acceleration in velocity. The retreat glacier with a large length in the West Kunlun Mountains experienced a surge before 2000 and in a quiet period now， mass cannot be transported from the upstream to the downstream， leading to the thinning and retreat of the glacier tongue.

Small glaciers are very sensitive to climate change， and monitoring and quantitative assessment of this type of glacier changes can help to understand the magnitude and mechanism of glacier response to climate change. In this study， we combined multi-source remote sensing data （satellite and UAV data） and meteorological data to analyze the change in area of Kuoqionggangri No. 1 Glacier in the Nyainqêntanglha Mountains， Qinghai-Tibet （Xizang） Plateau over the past 50 years， and quantitatively evaluated the magnitude of recent elevation changes and the spatial distribution of Kuoqionggangri No. 1 Glacier. The study shows that the area of Kuoqionggangri small cirque glacier shrank from （1.444±0.013） km² to （0.712±0.001） km² during 1968—2021， with a shrinkage of 50.7%， and the average rate of glacier terminus retreat was （6.23±0.71） m⋅a^-1. Based on the high-precision UAV survey data from 2020 to 2021， we found that the average elevation difference of the ice surface of Kuoqionggangri No. 1 Glacier reached （-2.41±0.69） m⋅a^-1. The average ice surface elevation change at the glacier terminus was greater than 3 m， and a decrease in the central part of the glacier in the range of 1.5 to 3 m. The study also found that glacier supraglacial streams play an important role in the spatial variation of elevation. There are 13 supraglacial streams developed on the surface of this glacier， and the average offset of the streams to the northwest from 2020 to 2021 is about 2 m. Downward and lateral erosion of the supraglacial streams resulted in causing significant spatial differences ice elevation changes at the glacier terminate.

To investigate the spatial characteristics of total organic carbon （TOC） content in sediment in upper and tributary streams of the Yarlung Zangbo River （YZR） and its influencing factors， responses of TOC content in sediment on particle size were studied and effects of land use in the watershed on spatial trends of TOC were analyzed based on the random forest analysis （RFA）. The results indicate that the mean TOC ［（6.56±6.37） g·kg^-1］ in upper reaches of the YZR is lower than that of other large- and medium-sized rivers， which ranges from 5.95 to 49.06 g·kg^-1 with a mean value of （19.77±14.05） g·kg^-1. With the lowest TOC in sediment ［（2.57±0.97） g·kg^-1］ in headwater， TOC is highly positively correlated （r=0.64， P<0.01） with clay content in sediment in the YZR. Based on literatures and results of this study， a highly significant exponential correlation between TOC in sediment and the content of particles smaller than 63 μm （r=0.77， P<0.01） was found across rivers， and thus， the content of particles smaller than 63 μm could be an indicator of TOC in sediment in rivers. Furtherly， RFA results indicate that in upper reaches of the YZR， TOC in sediment is majorly terrestrially sourced from grassland （48.12%） and increased spatially along the direction of water flow due to transitioning of land use from low-coverage grassland and bare land in headwater to medium， high-coverage grassland， as well as to agricultural， pastoral， and industrial （Class M1） land in upper-middle and upper-end sections of the YZR. We， therefore， concluded that the lower TOC in upper reaches of the YZR can be generally attributed to less anthropogenic activities and predominant sandy texture.

The difference of slope aspect in high altitude permafrost region may cause the asymmetry of temperature field on the two slopes， and then cause uneven settlement and longitudinal cracks of infrastructure. At present， the research on the influence of slopes mainly focuses on the monitoring and simulation of the east and west slopes of the Qinghai-Xizang Railway， seldom on the other slopes. But the trend of the linear project in plateau may involve different directions， we cannot promise the railway always in one orientation in the linear engineering and the research on the status of the water and heat difference on other slope aspects is insufficient. In this study， to found a relationship of soil temperature and moisture content in Qinghai-Xizang Plateau， and study the influence of the different slopes. A monitoring entity with eight directions （known as an octagonal platform） was built in the Huashixia permafrost station， the base of the observation of the frozen soil in Qinghai-Xizang Plateau. Soil temperature and moisture content sensors were installed on the meddle of eight slopes in （10 cm， 20 cm， 30 cm） 3 depths near the surface and the top surface. To monitor and study the impact of slope aspect differences on the state of water and heat on the slope near surface. The results shew that the difference of the near surface temperature on the east to west slope was the smallest， the monthly average temperature difference from 0.1 ℃ to 2.3 ℃， and in this difference， the maximum temperature difference occurs in May； The temperature difference near the surface of the south to north slope was the largest， with the monthly average temperature difference of 1.3 ℃ to 7.7 ℃， and the maximum temperature difference occurs in February in this temperature difference. The remained near surface temperature difference of the other two relative slopes was between the east-west slope and south-north slope， and the temperature difference of the northeast-southwest slope was smaller than that of the northwest-southeast slope. From the perspective of temperature difference near the surface of slope， the north-south， whose thermal stability of linear engineering in high altitude permafrost region is better， followed by the northwest-southeast direction， the influence of slope was not significant and the temperature field was symmetrical. Similarly， the overall difference of near surface soil moisture content of the eight slopes， whose data came from 3 depths like the near surfaced soil temperature， and the device of the sensors was the same to the soil temperature， which was the smallest in the orientation of northeast-southwest， and the maximum monthly average moisture content difference was 0.06 m³·m^-3 during the melting period； The east-west slope surface difference was the largest， and the maximum monthly average water content difference in the same period was 0.11 m³·m^-3 This difference seemed on the opposite of the soil temperature. The difference of temperature and moisture content also causes a significant difference in the number of freeze-thaw cycles on different slopes， which has an important impact on the freeze-thaw damage of slope protection materials with rubble. In this research， south slope， whose freeze-thaw cycles times was the top one and higher than the west slope to 88 times， other slopes like east and northwest were close to 60 times， north slope and northeast slope were higher than west slope and northeast was higher than north. In this time， freeze-thaw cycles time in the top surface was the third high in all the slopes. The research results have a certain guiding significance for the future plateau linear engineering planning and the treatment of the different diseases of the solar and lunar slopes of the existing projects.

Through the collection of soil samples， this study analyzed the characteristics of stable isotope variations and their spatial distribution in soil water at different depths in the source region of Yangtze River. The sources of soil water were determined by the study using an end-element mixed runoff partition model. The findings revealed that within the range of 0~100 cm， soil temperature exhibited a decreasing trend， while the region of 0~80 cm and the range of 80~100 cm showed a rising tendency in soil moisture content. Within the depth range of 0~100 cm， the δ²H and δ¹⁸O values of soil water varied， and their trends were similar. The range of variation for the soil water’s δ²H and δ¹⁸O values was， respectively， -151.273‰ to -63.605‰ and -21.052‰ to -8.676‰. Spatially， soil water’s δ²H and δ¹⁸O content was often enhanced in the western and depleted in the southeast. The evaporative line （EL） was represented by δ²H = 7.23δ¹⁸O-5.27 （R²=0.88）. The altitude gradients and soil moisture content had an impact on the stable isotope composition of soil water. The contribution of precipitation to soil moisture increased with increasing altitude gradient， and it was greater than the input of meltwater from ice melt water. Precipitation accounted for 70% to 94% of the soil’s water content between 4 150~4 777 m above sea level. Between 4 150~4 555 m above sea level， ice melt water contributed 8% to 30% of soil water； between 4 613~4 777 m above sea level， it reduced to 6% to 8%. In an effort to improve our understanding of soil water circulation and stable isotope research in the source region of Yangtze River， this study provides a theoretical basis.

Against the backdrop of global climate warming， the activity of rock glaciers in the Qinghai-Xizang Plateau has been enhanced， leading to an increasing trend of disasters. By using methods such as remote sensing image analysis， field investigation， meteorological and runoff monitoring， characteristic data of the Wulian rock glacier in southeastern Qinghai-Xizang Plateau were obtained， and the triggering factors and processes of the formation of debris flows were analyzed. The findings indicate that the Wulian rock glacier’s mean velocity ranged from 1~3 m·a^-1 between 2010 and 2017， with the frontal velocity being substantially higher than that of the middle and rear. This advancement and associated instability of the rock glacier front can be attributed to the channel transportation of loose material sources. Notably， the rock glacier transported approximately 5 600~9 000 m³ of loose material， which triggered debris flow events in 2013 and 2014. The generation of such flows requires not only abundant loose sources but also sufficient water to initiate. In this study， the maximum runoff occurred during May and June， primarily driven by the melting of ice and snow resulting from elevated temperatures. By examining the two debris flow events， it was discovered that high temperature was the primary contributing factor， and the disaster mechanism involved the rapid melting of surface ice and snow due to elevated temperatures， causing the accumulation of meltwater in depressions on the rock glacier surface， resulting in a pond that， when discharged， caused loose material in front of the rock Glacier to form debris flow. As climate warming exacerbates in the future， rock glacier activity is anticipated to increase. Additionally， under the influence of rapid warming or heavy rainfall， the scale and frequency of debris flows may increase. Therefore， it is imperative to mitigate the risk of rock glacier disaster formation through debris flow prevention measures.

The content variation of trace elements in mountain glaciers can be used as a good index to evaluate the impact of human activities on atmospheric environment. In order to illuminate the spatial distribution and the main sources of trace elements in snow ice of Qilian Mountains， on September 15， 2020， surface snow samples were collected from seven glaciers in the Qilian Mountains， including Aerjin Glacier， Zhazigou Glacier， Laohugou Glacier， Qiyi Glacier， Glacier No.4， Bayi Glacier， and Ningchanhe Glacier No.3. The samples were acidified to analyze the spatial distribution of trace elements and their primary sources. Using ICP-MS， the concentrations of 15 metallic elements （Al， Fe， As， Ba， Co， Cr， Cu， Li， Mn， Mo， Pb， Sr， Tl， Zn， and Cd） were measured， and the average trace element concentrations were compared using the Jonckheere-Terpstra nonparametric test. Higher trace element concentrations were found in Zhazigou Glacier and Laohugou Glacier in the western part of the Qilian Mountains， while lower concentrations were found in Ningchanhe Glacier No.3 in the eastern part. The overall spatial distribution trend of trace element concentrations was west>middle>east. Enrichment factors （EF） for total trace element concentrations were calculated， showing that elements Co， Cr， Cu， Tl， Fe， Li， Mn， Mo， and Sr were mostly influenced by natural dust input （EF<10）， whereas elements Pb， Cd， and Zn were more influenced by anthropogenic sources （EF>10）， such as industrial emissions， coal mining， and fossil fuel combustion. The trace element concentration data were subjected to Principal Component Analysis （PCA）， revealing that elements with high positive loadings on the total concentration in the first principal component mainly originated from natural dust sources， especially in the Xinjiang region. The second principal component represented varying degrees of anthropogenic source effects. Additionally， clustering analysis combined with a backward trajectory demonstrated that the study area is primarily influenced by the westerly circulation， and the natural input sources of trace elements mainly come from deserts and basins in central and northern Xinjiang. Anthropogenic sources include human activities in some cities along the Hexi Corridor， transportation emissions， mineral extraction， and metal smelting. This study provides data support for the impact of glacial human activities on the environment in various segments of the Qilian Mountains. These findings provide important scientific and technological support for the construction of ecological civilization and sustainable social and economic development in the Qilian Mountains.

Glaciers， as an integral part of the cryosphere， are highly susceptible to both local and global climate change. Ice crevasses， which are prominent features on the surface of glaciers and the important channels for glacier meltwater， play a crucial role in understanding the condition， stability， internal stress and mass balance of glaciers. Mountain glaciers are subject to cloud cover and area limitation， and the spatial resolution of traditional satellite remote sensing data is low， which is difficult to be used for extracting ice crevasses， so there are fewer studies related to ice crevasses on mountain glaciers. In this study， the objective was to address the challenge of identifying and extracting glacier crevasses quickly and accurately. This research takes the mountain glacier： Baishui River Glacier No.1 in Yulong Snow Mountain in Lijiang， Yunnan Province as the research object， and takes the cloud-free orthophotos of the glacier surface with a resolution of 0.12 m in 2021 and 2022 acquired by aerial photography of the DJI M300RTK drone as the data source， and applies the U-Net Deep Learning Network to carry out the extraction of ice crevasses of the Baishui River Glacier No.1.

The results demonstrate that the U-Net network outperforms traditional methods such as the Canny operator and SVM algorithm in terms of crevasse extraction accuracy. The overall accuracy can be as high as 93%. Furthermore， the U-Net network exhibits strong generalization capabilities， which can be used to automatically extract unmanned aerial imagery from different time periods. From the perspective of spatial distribution of ice crevasses， the crevasses observed on BRG1 predominantly consist of transverse crevasses， splaying crevasses， and En échelon crevasses， which show the typical characteristics of mountain glacier ice crevasses in the low advection lifecycle. As the altitude decreases， there is a gradual transition from transverse crevasses to splaying crevasses. From the perspective of temporal change of ice crevasses， comparing the extraction results from different time periods reveals an increase in the number and average length of crevasses. This proves that the ablation of BRG1 is intensifying， and the glacier mass is gradually losing. The orientation of the ice crevasses was almost unchanged， indicating that the stress inside the glacier didn’t change dramatically. In summary， the study of intelligent extraction of ice crevasses based on UAV images and deep learning methods creates new possibilities for extracting ice crevasses from mountain glaciers， and can provide technical support for monitoring glacier changes and their relationship with climate change.

In recent years， with the advancement of the western development strategy， China has undertaken extensive rock engineering construction in alpine and cold mountainous areas. During the construction process， inevitable engineering disasters such as slope instability and tunnel collapse have significantly compromised engineering safety. These disasters are usually caused by the gradual accumulation of damage and failure of rock under external load. In addition， low-temperature environmental factors will lead to the change of mechanical properties of rock， and then affect the load-failure process. Damage localization is the necessary stage and precursor of rock failure under load. In this paper， the damage localization of frozen rock under load is studied， and the influence of initial saturation degree is discussed. Uniaxial compression tests of frozen sandstone specimens with different initial saturation degrees were carried out at -20 ℃. The digital image correlation （DIC） and acoustic emission （AE） systems were used to collect surface deformation and AE signals during the test. Based on the mechanical test results， the mechanical and deformation characteristics of frozen sandstone are analyzed， and the influence of initial saturation degree on the mechanical properties of rock is demonstrated combined with the change of AE count distribution characteristics. Through the analysis of surface deformation， the surface strain localization mode of the specimen is divided into mode I （tensile strain localization）， mode II （shear strain localization） and mode III （mixed localization）. The initial saturation degree of 40% is the turning point from mode I to mode II， and mode III appears after the initial saturation degree exceeds 90%. All the modes can correspond to the final failure mode of the specimens. Based on the RA-AF analysis， the types of microcrack propagation in the rock during the strain localization process are shown： type I （tensile crack）， type II （shear crack） and type III （mixed crack）， which are basically consistent with the surface strain localization mode. Finally， combined with the changes of phase composition in the pores of frozen rocks at different initial saturation degrees， the influence of phase composition on the damage localization mode of frozen rocks is analyzed. That is， at low initial saturation degree， the ice content in the pores of frozen sandstone is small， and the external load is mainly borne by the rock skeleton. Because the tensile strength of the rock is usually lower than the shear strength， the rock will be tensile failure， and the damage localization mode is also tensile. At medium saturation degree， the ice content in the pores increases， and cements with the rock skeleton. The tensile strength of the ice helps the frozen sandstone resist tensile failure， and the damage localization mode becomes shear. At high initial saturation degree， the pore ice completely fills the microcracks， forcing them to expand， and a mixed damage localization mode is presented. This study helps to deepen the understanding of the mechanical properties of frozen rocks， and can provide important reference for the prediction of failure and instability of rock engineering in cold regions.

Global changes have led to increased temperatures and accelerated glacier retreat， and a large number of radioresistant-antioxidant microbial resources have evolved at the glacier foreland. As one of the important taxa influencing the successional process of glacier frontiers， the study of radiation-antioxidant bacteria in the newly melted moraine habitats in the ice tongue area of glacier frontiers is relatively rare. Based on the phylogeny of 16S rRNA gene sequences， this study not only investigated the diversity of culturable bacteria in moraine habitats in the glacier tongue at the frontier of the Lahugou No.12 Glacier， but also screened and evaluated the strains for their radiation-resistant and antioxidant capacity. The study showed that 259 bacterial strains isolated in the study area belonged to Actinobacteria， Proteobacteria， Bacteroidetes， Firmicutes and Deinococcus-Thermus， among which the highest number of strains was found in Actinobacteria， followed by Proteobacteria>Bacteroidetes>Firmicutes>Deinococcus-Thermus. In terms of species diversity， Actinobacteria and Proteobacteria had the highest species richness. TN， TOC， WC and pH were the main factors affecting the structure of culturable bacterial communities. The strains with D₁₀ （lethality of 10%） dose of UVC irradiation intensity higher than 100 J·m^-2 accounted for 94.9% of the total culturable bacteria， and the strains with D₁₀ dose of H₂O₂ tolerance concentration higher than 10 mmol·L^-1accounted for 100% of the total culturable bacteria； among them， there were 20 strains. And the survival rate after oxidative stress of the radiation-resistant strains was above 90%. In addition， the strains with higher survival rate than Deinococcus-radiodurans R1 after oxidative stress were all radiation-resistant strains with higher than 50% survival rate after 100 J·m^-2 UVC irradiation. This study can not only provide a theoretical basis for the diversity and ecological adaptation of bacteria in the glacier foreland environment， but also provide a rich resource of radiation-resistant and antioxidant glacier bacteria for the subsequent research on the protective mechanism of irradiation and oxidative damage.

As one of the major alpine ecosystems， the carbon-water balance status of alpine meadows during the non-growing season is of great significance to the whole ecosystem. However， little is known about the environmental drivers of carbon and water fluxes during this season. Therefore， this study investigates the carbon and water fluxes and their influencing factors during the non-growing season （from Nov. 2022 to Apr. 2023） in alpine meadows in the Qilian Mountains based on eddy observations and meteorological gradient towers. It was found that in the alpine meadow ecosystem of the Qilian Mountains， during the entire non-growing season， the net ecosystem carbon exchange （NEE）， gross primary productivity （GPP）， and ecosystem respiration （Reco） were -18.0574 mg CO₂⋅m^-2， 27.3565 mg CO₂⋅m^-2， and 9.2991 mg CO₂⋅m^-2， respectively. The total evapotranspiration （ET） was 74.8762 mm， which was 15.0762 mm lower than the total precipitation， and the water cycle of this ecosystem was relatively balanced. Normalised vegetation index， photosynthetically active radiation and soil temperature were the main factors affecting net ecosystem carbon exchange during the non-growing season. Whereas relative humidity， precipitation and net radiation were the main factors affecting evapotranspiration in the non-growing season. The results of this study revealed the characteristics of carbon dioxide fluxes and water fluxes during the non-growing season in alpine meadows in the Qilian Mountains and their influencing factors， which provide an important reference for understanding the carbon balance process and water balance in the region and its response to climate change.

Glaciers are very sensitive to climatic and environmental changes， and are closely linked to changes in water resources and geological disasters. Under the influence of global warming， the melting of glaciers on the Qinghai-Xizang Plateau and its surrounding areas is on the increase. This paper addresses the problem that the large difference in the quality of ICESat-2 laser photon data under different terrain conditions leads to a large error in the glacier elevation change volume estimation when monitoring glacier elevation change using ICESat-2 satellite photon point cloud data， using Qiaqing Glacier， China’s largest oceanic glacier on the Qinghai-Xizang Plateau， as an example. Using ICESat-2 laser altimetry data and 30 m resolution SRTM DEM products， we propose a multifunction fitting glacier elevation change estimation error correction model with a robust estimation criterion that reduces the glacier elevation change estimation error caused by terrain slope； then， we estimate the elevation change and mass change of Qiaqing Glacier between 2000 and 2021. The results show that the multi-function correction models proposed in this paper can effectively improve the accuracy of the elevation change monitoring results. Meanwhile， the correction effect of the function model incorporating robust estimation is better compared with the corresponding traditional least squares estimation results. Subsequently， the effectiveness and feasibility of the error correction model can be demonstrated by cross-validating the correction results with multiple data. The model can effectively improve the accuracy of extracting glacier elevation and mass change information， and it was concluded that the glacier elevation change rate of the study area during the 21-year period was approximately （-0.52 ± 0.56） m⋅a^-1， and the glacier mass change was about -1 277.38 million tonnes. In addition， combined with the meteorological data， the annual and monthly average temperature and precipitation data are analyzed， and the overall temperature rise and precipitation fluctuation decline were the main reasons for glacier melting in 21 years. Combined with the data of glacier elevation changes in different seasons， it was also analyzed that spring and winter were the accumulation periods of glaciers， while summer and autumn were the melting periods of glaciers. At the same time， it can be predicted that the glacier will continue to melt in the short term in the future. The situation of continuous degradation and melting of the glaciers is not optimistic.

The climate change in the source region of the Yellow River Basin was projected from 2121 to 2060 using eight GCMS of the Coupled model inter-comparision project Phase 6 （CMIP6） and two shared socio-economic low-carbon paths （SSP1-2.6 and SSP2-4.5）. The inter-decadal variation of discharge in the source region of the Yellow River from 2021 to 2060 was predicted by using eight GCMs climate models to drive HBV and SWAT hydrological models. The results show that： （1） In comparison with the baseline period （1995—2014）， in terms of the ensemble mean， annual mean air temperature， annual precipitation will increase by 1.3 ℃ and 1.6 ℃， by 11.6% and 11.5% under SSP1-2.6 and SSP2-4.5 scenarios， respectively. And the warming and wetting trends become obvious from 2021—2060 under the SSP1-2.6 and SSP2-4.5 scenarios in the source region of the Yellow River. （2） The multi-models ensemble mean （MEM） multi-year mean annual discharge for 2021—2060 was expected to increase by 8.6% and 8.5% under the SSP1-2.6 scenario and the SSP2-4.5 scenario， respectively. It was projected to increase in each decade from the 2020s to the 2050s under the scenario of SSP1-2.6 and SSP2-4.5. The increase degree in 2040s and 2050s is higher than 2020s and 2030s. （3） The proportion of discharge was projected to decrease by 0.1%~1.0% from May to August during 2021—2060 under both scenarios but was projected to increase by 0.1%~2.1% from April to May and September to December for most GCM_S under the SSP1-2.6 scenario and the SSP2-4.5 scenario， respectively. （4） Extremely high monthly discharge was expected to increase by 2.5%~2.7% in the water storage season under two scenarios during 2021—2060 in the source region of the Yellow River whereas the extreme high discharge in the flood season increased by 0.1% under the SSP1-2.6 scenarios but decreased by 1.3% under the SSP2-4.5 scenarios， and decreased by 0.7%~1.0% in dry season under two scenarios in the next 40 years. Extremely low discharge was projected to increase by 0.8%~1.9% in the flood season and the dry season but to decrease by 1.8%~2.3% in the storage season under two scenarios in the study region.

Two-phase closed thermosyphons （TPCTs） play a significant role in permafrost regions due to their thermal semiconductor effect. Many TPCTs have been used to collect cold energy from the ambient air in permafrost regions to cool the underlying stratum. In this study， an ammonia-steel TPCT test bench suitable for permafrost regions was built to optimize the working conditions of the TPCT. The effects of filling rate and inclination angle on the heat transfer performance of low-temperature TPCTs were analyzed. Experiments were carried out at different filling rates （20%， 30%， 40%） and inclination angles （10°， 30°， 50°， 70°， 90°） under negative temperature conditions. To simulate low-temperature conditions， the ambient temperature difference between the evaporator section and the condenser section was set to 13 ℃. The heat transfer performance of the TPCT was evaluated based on the temperature distribution inside and outside the TPCT and the variation in the heat flux density of the outer wall. The heat transfer performance of the TPCT was evaluated using indexes such as isothermal characteristics， thermal resistance， and transfer efficiency. The experimental results show that， under three experimental filling rates， all TPCTs with an inclination angle of 10° have the best axial internal isothermal performance. The minimum thermal resistance occurs at an inclination angle of 50° when the TPCT filling rates were 30% and 40%， corresponding to the highest heat transfer efficiency. For the TPCT with a filling rate of 20%， the minimum thermal resistance and the highest heat transfer efficiency both occur at an inclination angle of 30°. Overall， the TPCT with a filling rate of 30% has the optimal heat transfer performance. It is recommended that the inclination angle of TPCTs is between 10° and 50°. This study provides meaningful reference for the best structural parameters in the design of TPCTs for cold regions engineering.

In high-altitude and high-altitude areas， the stability of steep mining slopes containing years of frozen layers is controlled by the mechanical properties of frozen rock layers. Excavation of the strata exposes the frozen rock layers to the air， and coupled with blasting vibrations or mechanical disturbances during excavation， the frozen rock layers gradually soften and heat melt， leading to a decrease in slope stability. With the continued global climate warming， the thermal thawing softening of frozen rock layers accelerates， further exacerbating the risk of instability in mining slopes. The strength of frozen rocks will soften during the hot melt process， which is the most susceptible stage to failure. Studying the thermal thawing softening law of frozen rocks is crucial for evaluating the stability and safety of frozen strata during the thawing process. This article conducted uniaxial compression tests on frozen rocks at different melting temperatures. Based on the restoration of rock pore structure and precise calibration of microscopic parameters， the particle flow software （PFC^2D） was used to simulate the compression failure process of frozen rocks. Based on the analysis of the initiation law and propagation law of microcracks， this paper explores the control effect of pore ice on the thermal thawing softening law of frozen sandstone. The research results indicate that： （1） the strength， elastic modulus and other parameters of frozen rock show a two-stage trend with the increase of temperature. There is a certain temperature between -4 ℃ and -2 ℃， which causes a sudden decrease in the strength and deformation parameters of the sample. （2） As the temperature increases， the failure of frozen rocks at peak stress gradually shifts from being dominated by mineral particle frameworks to being dominated by ice. When the temperature is less than -2 ℃， the degree of damage to the frozen rock skeleton is higher； When the temperature is greater than -2 ℃， the damage to porous ice is more significant. When the temperature is below -15 ℃， the initiation and propagation of microcracks are mainly controlled by the contact strength between mineral particles； When the temperature is between -2 ℃ and -15 ℃， it is mainly controlled by the contact strength between ice particles and ice minerals； When the temperature is greater than -2 ℃， it is mainly controlled by the contact strength between ice particles. （3） By analyzing the supporting and bonding effects of pore ice during the load failure process of frozen rocks， it was found that between -6 ℃ and -4 ℃， the bonding strength between ice particles and between ice minerals rapidly decayed， leading to a weakening of the supporting and bonding effects of ice， which is the essential reason for the rapid weakening of mechanical properties in this temperature range. For high-altitude and high-altitude areas， the thermal thawing softening of frozen rock layers is a core process related to their stability and safety. Therefore， studying the thermal thawing softening law and load failure process of frozen rocks is of great engineering significance.

The effect of pipeline insulation layer in permafrost area is closely related to the randomness of evaluation index changes， and the previous evaluation model of pipeline insulation layer effect in permafrost area has certain limitations and shortcomings. In order to improve the application effectiveness of insulation measures for pipelines in permafrost regions， based on the comprehensive evaluation method and combining the Driving force-State-Response （DSR） model theory， coefficient of variation weight theory and cloud model theory， in this paper a suitable comprehensive cloud model has been built for the evaluation of the thermal effect of insulated pipelines in permafrost regions. The DSR framework is used in the developed model to ensure the reliability of the index system. The weight of the index calculated by the coefficient of variation method ensures objectivity； the cloud model solves the randomness problem that cannot reflect the standard classification and index data acquisition of the environmental evaluation process of pipelines in permafrost regions. In order to validate the evaluation model of insulating effects for buried oil pipelines in permafrost regions， three representative monitoring sites at Kilometerage Posts MDX007， MDX113， MDX304 and MDX364 along the China-Russia Crude Oil Pipelines （Mo’he-Daqing Line or MDX） are taken as examples. The comprehensive cloud model is used for evaluating the thermal effect of pipeline insulation measures. The results show that the comprehensive model-based analysis can effectively guide the implementation plan of insulation measures for Russian-Chinese Crude Oil Pipelines， and give corresponding measure suggestions based on the corresponding insulation effect failure types. Based on the evaluation results， the implementation plan of insulation measures for the China-Russia Crude Oil Pipelines is analyzed and advised for optimizing the thermal effect of insulative measures. The comprehensive cloud model can combine the advantages of different theoretical models to take into full account of the effectiveness and soundness of the comprehensive analysis of cold regions engineering environment evaluation， with a promising application potential. The research results can provide strategic scientific support for the safe and stable operation and sustainable development of China-Russia Crude Oil Pipelines.

Frost heave of the unsaturated coarse-grained soil is the main disaster cause for the subgrade engineering in seasonally frozen soil regions， which is affected by the complex coupling of water， temperature and stress field. In order to investigate the frost heave deformation properties of unsaturated coarse-grained soil， a numerical model is proposed to describe the water vapor migration in unsaturated coarse-grained soil under temperature change based on Darcy’s law and Fourier’s law， which is solved by the coefficient partial differential equation of the finite element software COMSOL Multiphysics. The model comprehensively considers the influence of ice-water phase change and water vapor migration on the deformation of frozen soil， describing the hydrothermal vapor and mechanical effect of unsaturated frozen soil. The model introduces the dynamic relationship among pore ice content， soil negative temperature and water migration， and considers the influence of negative temperature on the soil water migration. The rationality and feasibility of the model is verified through the comparisons of calculated temperature， water and displacement filed with the indoor experimental results. The effect of vapor on water migration in the freezing process is comprehensively analyzed by analyzing gaseous and liquid water fluxes changes. The variation characteristics of water vapor migration and frost heave deformation of coarse-grained soil under different temperature gradients are further investigated by numerical experiments. The results found that under the action of uni-directional freezing， the temperature change process is divided into three stages： rapid cooling stage， slow cooling stage and stable stage. The water content reaches the extreme value at the freezing front. In the early stage of freezing， the frost heave rate is large， and the soil has a large deformation. As time increases， the deformation basically remains unchanged. During the freezing process of coarse-grained soil， in the unfrozen area （height 0~9 cm）， the temperature fluctuation is large， and the gaseous water flux is much smaller than the liquid water flux， indicating that in the unfrozen area， liquid water migration is dominant. In the range of freezing depth， the gaseous water has an obvious upward migration trend. The reason is the ice formed by the migration of liquid water here has little blocking effect on the migration of gaseous water. The gaseous water can continue to migrate upward through the ice layer， which has an important contribution to the frost heave deformation of the soil. Therefore， in the freezing process of unsaturated coarse-grained soil， there is an obvious gaseous water migration， which cannot be ignored. Through numerical experiments， it is found that different temperatures at the cold end have significant effects on soil sample temperature， water content and frost heave deformation. Under the action of temperature gradient， gaseous water moves upward， resulting in the migration of water within the soil towards the frozen area， resulting in frost heave deformation. The larger negative temperature will accelerate the movement speed of gaseous water flux and the freezing front significantly. Therefore， the frost heave deformation of the soil gradually increases with the decrease of cold end temperature. Under different cold end temperatures， the sample with a height of 20 cm reaches the maximum water content at a height of about 3 cm， and the maximum frost heave deformation on the surface can reach about 4 cm. The trend of the calculated value and the measured value is almost the same and the curve is in good agreement， which shows that the proposed model is suitable to simulate the phenomenon of soil frost heave. This model is beneficial for both the theoretical research and numerical implementation of the subgrade engineering in seasonally frozen soil regions.

Taking the unified strength theory as the yield criterion of frozen surrounding rock of tunnels in cold regions under the unloading state， taking into account the influence of the non-homogeneous of surrounding rock and the intermediate principal stress effect on the strength of frozen surrounding rock， an elastic-plastic mechanical model of stress displacement of tunnels in cold regions is established， and combining with the boundary conditions of each region， the elastic solution， the plastic unified solution and the implicit equation of the radius of the plastic zone under the homogeneous and non-homogeneous state of frozen surrounding rock are calculated， discussion and analysis of stress and displacement fields respectively. The research shows that considering the heterogeneity of frozen surrounding rock， the peak value of hoop stress in plastic zone increases by 40%， the range of plastic zone decreases by 40.4%， the displacement of inner wall decreases by 9.3%， the elastic ultimate bearing capacity increases by 41%， and the plastic ultimate bearing capacity increases by 14%， which has a significant impact. The intermediate principal stress effect can give full play to the bearing potential of frozen surrounding rock， the calculated bearing capacity is significantly increased， and the plastic radius is significantly reduced. The results can provide theoretical guidance for tunnel excavation and support design and numerical simulation in cold regions.

The freeze-thaw front within active layer is the interface between the frozen and the unfrozen soil layers during the freeze-thaw process， and the hydrothermal parameters of the soil layers on both sides of freeze-thaw front are significantly different. Therefore， the accurate simulation of the freeze-thaw front movement in the land surface model is essential to improve models both in simulating the hydrothermal characteristics of permafrost and simulating the energy-water balance of the land surface. In this study， the simulation depth of the Noah-MP land surface model was extended to 20 m， and the 4 soil layers of the Noah-MP land surface model was increased to 19 soil layers， and the organic matter scheme and vegetation root scheme were introduced. After these modifications， in order to strengthen the ability of the Noah-MP land surface model on simulating freeze-thaw front， the Stefan method was coupled. Then， the simulation effect of the augmented Noah-MP land surface model on the hydrothermal process of the Xidatan permafrost site was evaluated. Two experiments， CTL experiment （coupled Stefan method） and STE experiment （not coupled Stefan method）， were conducted to simulate the soil temperature and soil liquid water content of 0~20 m in 2012， and the simulation results were verified by the observed daily soil temperature and soil liquid water of 0~3.2 m and the observed yearly ground temperature of 3 m， 6 m and 10 m. The results showed that the freeze-thaw front （0 °C isotherm） obtained by interpolation of soil temperature simulation values had obvious step-like characteristics， and its maximum freeze-thaw depth was larger than the measured. Coupling Stefan method enhanced the ability of Noah-MP model to simulate the freeze-thaw front， so that the model was able to better simulate the change trend and maximum depth of the freeze-thaw front. At the same time， coupling Stefan method also improved the simulation of soil temperature. The mean RMSE and the mean MBE of the soil temperature in the soil layers of 0~3.2 m decreased to 0.89 ℃ （decreased by 44%） and -0.13 ℃ （decreased by 86%） respectively， and yearly ground temperature of 3~20 m was closer to the measured. And it also improved the simulation of the soil liquid water content. The mean RMSE and the mean MBE of the soil liquid water content in the soil layers of 0~3.2 m decreased to 0.06 m³·m^-3 （decreased by 33%） and -0.01 m³·m^-3 （decreased by 67%） respectively， and the soil water melting time of 20 cm， 40 cm， 80 cm and 120 cm in the active layer was closer to the observed. It can be seen that coupling the Stefan method that can better model the movement process of freeze-thaw front in the land surface model can greatly improve the simulation ability of the model， which is one of the effective ways to improve the land surface process model. The results of this study can provide a reference for improving the simulation of the land surface model in the permafrost area. This study will provide a reference for improving the ability of land surface model to simulate hydrothermal processes of permafrost.

To explore the influence of freeze-thaw cycles on the strength of moraine soil， this study established a prediction model of the strength deterioration of moraine soil under different numbers of freeze-thaw cycles. Taking the moraine soil in the western high-cold and high-altitude area as the research object， a total of more than 180 triaxial samples with a diameter of 101 mm were made by combining the indoor high-frequency freeze-thaw cycle test with the unconsolidated undrained triaxial test. The strength test was carried out after the high-frequency freeze-thaw cycle test with different frequencies. The test variables were the number of high-frequency freeze-thaw cycles， the initial water content of the sample， and the confining pressure of the triaxial test. The influence of the number of high-frequency freeze-thaw cycles， the initial water content， and the confining pressure on the failure strength of the moraine soil sample was mainly explored. A BP neural network prediction model with three layers of input and one layer of output was established by MATLAB software. The data obtained from the experiment were imported into the BP neural network model for learning and training. The strength degradation prediction model of moraine soil under high frequency freeze-thaw cycle was established. At the same time， the SSA algorithm was introduced to improve the model. The number of neurons， the number of neural network layers and the number of iterations in the BP neural network were optimized to improve the prediction accuracy of the model. The experimental results show that freeze-thaw cycles have a great influence on the strength of moraine soil. Under different testing conditions， the strength of moraine soil degrades in the range from 30% to 40%， and tends to stabilize after 15 to 20 freeze-thaw cycles. Based on the SSA-BP neural network model， the complex nonlinear relationship between the failure strength of moraine soil and the number of freeze-thaw cycles， initial water content and confining pressure can be reflected. The prediction error is significantly smaller than that of the BP neural network model， and the prediction results are more accurate. Comparing the SSA-BP neural network model with the Logistic model used in linear fitting， it is found that the two are in good agreement， which further illustrates the accuracy of the SSA-BP model. Through later verification， it is found that the output error of the model is small and has certain application prospects. This research can provide important parameters for engineering stability evaluation in western cold and high-altitude areas.

Snow cover is an essential component of the cryosphere， and it has low thermal conductivity， high reflectivity， and large latent heat of melting， playing an important role in the energy balance process of the Earth. There are significant spatial differences in the response of snow cover to climate change. Snow cover is widely distributed in mid to high latitudes mountainous areas in the Northern Hemisphere， and spatiotemporal variations in mountainous snow cover have important implications for human life， the economy， and ecosystems. The Altai， the Alps and the Cascade Mountains are respectively one of the most important mountains in Asia， Europe and North America. The three mountains are located in the mid to high latitudes of the Northern Hemisphere， with rich snow resources. The three mountains are the only three typical mountain ranges in the mid to high latitudes of the Northern Hemisphere that can be horizontally compared. Based on daily snow cover products from MODIS， four snow cover parameters of the Altai， the Alps and the Cascade Mountains after cloud removal processing were obtained， including snow cover fraction （SCF）， snow cover duration （SCD）， snow onset day （SOD）， and snow end day （SED）. A comparative analysis was conducted on the spatiotemporal distribution and trend of snow cover parameters in three mountain ranges from 2002 to 2021， and the impact of climate factors on snow cover parameters was studied using satellite and reanalysis data. The results indicate that： （1） The spatial distribution differences in snow parameters among the three mountain ranges are evident and closely related to elevation. The Altai Mountains exhibit the maximum snow cover fraction， the longest snow cover duration， the earliest snow onset day and the latest snow end day， which are 38.00%， 141 days， 66 days， and 207 days respectively. The Alps has intermediate values for snow cover parameters. The snow cover fraction， snow cover duration， snow onset day and snow end day in the Alps are 21.68%， 79 days， 97 days， and 194 days respectively. The Cascade Mountains show the minimum snow cover fraction， the shortest snow cover duration， the latest snow onset day and the earliest snow end day， which are 15.18%， 56 days， 103 days， and 183 days respectively. （2） In terms of trends， snow cover fraction increases in the Altai Mountains， with earlier snow onset and later snowmelt leading to an increase in snow cover duration. Conversely， the Alps experience a reduction in snow cover fraction due to earlier snowmelt， resulting in a decrease in snow cover duration. The Cascade Mountains exhibit an increase in snow cover fraction， with later snowmelt contributing to an increase in snow cover duration. （3） The land surface temperature and precipitation in the three mountain ranges are increasing. The land surface temperature and precipitation have a greater impact on snow cover fraction and snow cover duration of the three mountains. The correlation coefficient between land surface temperature and snow onset day， and the correlation coefficient between precipitation and snow onset day and snow end day are relatively smaller. Temperature has a greater impact on snow cover parameters in the three mountain ranges compared to precipitation.

This paper investigates the impact of floating beads on temperature dissipation during the construction stage and their influence on the effective compaction time of asphalt pavements. As a high thermal resistance material， floating beads have been used in asphalt pavements in permafrost region to reduce heat absorption and mitigate thawing induced settlement during the operational stage. However， limited research has focused on the influence of floating beads on temperature dissipation during the construction stage and their impact on the effective compaction time of asphalt pavement. The addition of floating beads alters the thermo-physical properties of the asphalt mixture， thereby affecting pavement compaction and heat transfer to the frozen soil subgrade. During the compaction process of asphalt mixtures， the material undergoes a transition from a loose state to a dense state， resulting in decreased porosity and increased strength. Consequently， the thermo-physical parameters of the asphalt mixture dynamically change throughout the construction stage of asphalt pavement. This study considers the asphalt mixture modified with floating beads as a composite material comprising coarse aggregates， asphalt matrix， and air. Laboratory tests are carried out to measure the thermo-physical parameters of the three components in the modified asphalt mixture. The Williamson formula is utilized to calculate the thermo-physical parameters of the modified asphalt mixture in both dense and loose states. To analyze the temperature field in the asphalt pavement and the heat flux entering the soil subgrade， a finite element model is developed. The model takes into account different floating bead contents and paving thicknesses. Based on the numerical results， a multivariate regression analysis is performed to identify the key factors influencing temperature fields during construction stage of asphalt pavement. This analysis leads to the derivation of an empirical equation for estimating the temperature of the asphalt mixture. The research findings reveal that the inclusion of 15% volume of floating beads reduces the thermal conductivity of the asphalt mixture by 78%， while exhibiting negligible changes in specific heat capacity （i.e.， less than 1%）. With an increase in air temperature 0 °C，10 °C，20 °C，30 °C， the addition of 15% floating beads enhances the effective compaction time by 21.1%， 20.2%， 17.5%， and 16.8% in the dense state， and by 21.6%， 21.2%， 20.3%， and 18.7% in the loose state. Compared to the dense state， the effective compaction time in the loose scenario is approximately 1.7 to 2.1 times longer. Hence， in low-temperature conditions， re-compaction and final compaction are crucial to be promptly and continuously completed to achieve the specified compaction level within the designated timeframe. Furthermore， the inclusion of 5%，10%，15% volume of floating leads to a reduction of 1.9%， 3.1%， and 6.4% in heat flow to the subgrade in the dense state， and a reduction of 3.5%， 7.3%， and 12.8% in the loose state. These results demonstrate the benefits of adding floating beads in mitigating heat disturbance to the soil subgrade during the construction stage. By minimizing heat flow， the potential adverse effects on the frozen soil subgrade are significantly reduced， contributing to the overall durability of the asphalt pavement. In conclusion， the addition of floating beads alters the thermo-physical properties of asphalt mixtures， thereby influencing the compaction process and heat transfer dynamics. The findings in this study provide valuable insights for optimizing construction practices of asphalt pavement， including adjusting compaction procedures and ensuring appropriate timeframes for effective compaction. Moreover， the benefits of floating beads in reducing heat flow to the subgrade indicate their potential for enhancing the long-term performance of asphalt pavements in challenging environmental conditions. Overall， this research contributes to the understanding of the thermo-physical behavior of asphalt mixtures containing floating beads and provides guidance for the design and construction of resilient asphalt pavement in permafrost regions.

The existing research on the macroscopic strength of frozen soil under the influence of macroscopic control factors mainly relies on experimental methods， and has achieved good results based on actual conditions. Generally speaking， both indoor and outdoor tests have shortcomings such as long cycle time and high cost. With the emergence of new technological means， exploring simpler methods and building predictive models has been a long-term endeavor of scientific researchers. At the same time， the influence of macroscopic control factors on the macroscopic strength of frozen soil is exerted through the medium of the internal characteristics of the soil. Since ultrasonic waves are a good carrier of relevant information such as the physical and mechanical properties of rock and soil media， ultrasonic testing can reflect the internal characteristics of the soil due to its non-destructive， fast and simple characteristics. Therefore， this paper designs a strength prediction model containing different types of parameters based on different ideas. Idea 1-macro-controlling factors to macro-strength characteristics， idea 2-macro-controlling factors to internal soil characteristics reflected by ultrasonic wave velocity and then to macro-strength properties. Through experiments， the ultrasonic wave velocity and uniaxial compressive strength of soils with different salt contents undergoing different freeze-thaw cycles were obtained as basic data. The experimental control variables are used as idea 1 parameters， the ultrasonic characteristic parameter group constructed with compressional and shear wave velocities is used as idea 2 parameters， and the combined two ideas parameters are used as model input. A BP neural network prediction model for uniaxial compressive strength was established， and the prediction model was evaluated using the default factor test method. Tests show that as the number of freezing and thawing times and the salt content increase， the uniaxial compressive strength decreases overall. The wave velocity fluctuates significantly in the early stages of freezing and thawing， slows down in the middle stage， and returns to near the initial value in the later stage. Under the action of controlling factors， the uniaxial compressive strength decreases step by step as the wave velocity increases. The idea 2 parameters after gray correlation and rough set optimization are used to establish a BP neural network model for the optimal subsequence responding to the internal characteristics of the soil. The average absolute error of the model is less than 0.05 kPa， the coefficient of determination is greater than 0.96， and the average sensitivity index of each parameter is 1.4251. Sensitivity analysis successfully verified the assumed status of controlling factors and optimal subsequences in the model building process. A single controllable parameter has a greater impact on uniaxial compressive strength than a single ultrasonic characteristic parameter. The 29 parameters can be divided into four levels according to their contribution weight to the model. In the subsequent dimensionality reduction and feature selection of the number of parameters， the fourth level parameters should be discarded first， and the third level parameters should be optimized through parameter construction innovation and data sample expansion. This can reduce the number of overall parameters and increase the contribution weight， thereby better optimizing the model. The BP neural network model of uniaxial compressive strength established based on the different ideas of ultrasonic testing has strong predictive ability and good interpretability of model parameters. The ultrasonic characteristic parameter group under the influence of control factors plays an important role in the construction of the strength model. It also verifies the reliability and effectiveness of the BP neural network model in predicting the uniaxial compressive strength of saline soil. The model has high accuracy and strong practicability， and can provide a reference for strength prediction and parameter selection of frozen soil models.

The vast territory of China covers a diverse range of climate types and topographical features， providing intricate environmental conditions for the precipitation recycling process. This diversity presents challenges in categorizing and comparing different regions when analyzing the characteristics of precipitation recycle ratio. This study employs an optimized precipitation recycle ratio evaluation model to calculate the precipitation recycle ratio in China and investigates its variation characteristics and response to global warming. The findings reveal that from 1979 to 2020， China experienced notable regional and seasonal differences in precipitation recycle ratios， with the Qinghai-Xizang Plateau exhibiting the highest value. Regions with high values and increase of precipitation recycle ratio were mainly located in the inland humid areas of non-monsoon regions； However， in the arid and semi-arid eastern part of Northwest China， despite a generally lower precipitation recycle ratio， there was a significant upward linear trend. The empirical orthogonal function （EOF） results indicate that the first mode of precipitation recycle ratio is dominated by a negative phase before 2000， shifting to a positive phase afterward. A nine-year moving average of the precipitation recycle ratio suggests an initial increase followed by a decline. This study categorizes China into four precipitation recycle ratio regions based on the magnitude of precipitation recycle ratio and its positive or negative climate tendency rate： the precipitation recycle ratio is relatively high and shows an upward trend （Class I）， the precipitation recycle ratio is relatively high and shows a downward trend （Class II）， the precipitation recycle ratio is relatively low and shows an upward trend （Class III）， and the precipitation recycle ratio is relatively low and shows a downward trend （Class IV）. Eight representative regions were selected from the four regions to study the response of precipitation recycle ratio to global warming. In Class I and Class II， precipitation is mainly affected by local evaporation， while in Class III and Class IV， the relationship between precipitation and external water vapor transport is closer. Within the same class， the response values of internal and external circulation variables to global warming are different. Changes in evaporation and water vapor flux divergence will affect the response strength of the contribution of low-level flow and local evaporation to global warming. Studying the distinct responses of internal and external cyclic variables to global warming across different regions in China can enhance our understanding of climate change impacts and provide a scientific basis for formulating corresponding climate adaptation strategies.

Deep hot-water drill is an important tool for clean drilling and sampling of subglacial lakes in polar regions. The underground return-water system is the key component of the deep hot-water drill， which mainly contains the return-water hose， heat-injection hose， submersible pump and water cavity. The return-water hose is used to extract molten water from the water cavity to the surface for recycling， while the heat-injection hose is used to inject surface hot water into the water cavity to prevent it from freezing. The thermal and flow characteristics of return-water hose and heat-injection hose are very important for the design of the downhole return-water system， however， it is not be the systematically researched and the variation of pressure loss and temperature loss is still not clear at present. In the paper， the theoretical calculation method of thermal and flow characteristics of return-water hose and heat-injection hose was firstly proposed based on Darcy-Weisbach formula and Sukhov's temperature-drop formula. Then， the numerical simulation method of thermal and flow characteristics of the two hoses was established in COMSOL Multiphysics 5.6 software， and the numerical results matched well with the theoretical calculation results. Finally， this paper systematically analyzed the influence of the factors， such as flow rate， inner diameter， length， water temperature at inlet， thermal conductivity， roughness of inner wall， ice temperature and wall thickness on the pressure and temperature loss of return-water hose and heat-injection hose. The results shows that the pressure and temperature in the return-water hose and heat-injection hose decreases linearly. In common， flow rate， inner diameter and length are the main factors affecting the pressure loss of return-water hose and heat-injection hose， while air temperature， flow rate， inner diameter and length are the main factors affecting the temperature loss. In addition， roughness of inner wall has little influence on the thermal and flow characteristics of the two hoses. When designing the downhole return-water system， the inner diameter of the return-water hose and the heat-injection hose should be increased as much as possible， and the construction depth of the return-water chamber should be reduced. The water temperature at inlet has bigger influence on the thermal and flow characteristics of the heat-injection hose compared with the return-water hose. Generally， the thermal conductivity of 0.4 W·（m·K）^-1 can ensure the return-water hose and the heat-injection hose have good thermal insulation performance and it is no longer necessary to increase the wall thickness to enhance its thermal insulation performance. The temperature loss of the return-water hose is generally not more than 2 ℃， while the temperature loss of the heat-injection hose is about 10~20 ℃. The conclusions above provided an important basis for designing a safe and efficient downhole return-water system.

Significant warming in the Arctic has led to the rapid degradation of permafrost， resulting in the development of a large number of thermokarst lakes and ponds， which are hotspots for greenhouse gas emissions. Based on the published results of methane （CH₄） in Arctic thermokarst lakes and ponds from 1992 to March 2022， this paper systematically investigated the CH₄ emission characteristics， carbon dynamics process， and the microbial mechanism of thermokarst lakes and ponds in the Arctic. The results showed that the annual CH₄ emission flux in the Arctic was about （7.78±19.60） g CH₄·m^-2·a^-1， with significant differences among sub-regions. High CH₄ emission ［（23.40±26.50） g CH₄·m^-2·a^-1 to （11.00±26.40） g CH₄·m^-2·a^-1］ were recorded in Eastern Siberia and Alaska. Bubble emission was the main pathway of CH₄ emission from Arctic thermokarst lakes and ponds， with an annual emission flux of about （13.80±27.80） g CH₄·m^-2·a^-1， accounting for 52.02% of the total CH₄ emissions. The type of lake sediment significantly influences CH₄ emissions from thermokarst lakes and ponds. Emissions from yedoma-type permafrost areas are （17.90±32.90） g CH₄·m^-2·a^-1， which is 3.24 times that of non-yedoma permafrost areas. However， the main pathways and changes of CH₄ emissions from peatland thermokarst lakes and ponds remain highly uncertain. The expansion and drainage trends of thermokarst lakes and ponds and the production and oxidation processes of CH₄ also have important impacts on the potential CH₄ emissions. There is still a lack of systematic observation for multiple CH₄ emissions pathways from thermokarst lakes and ponds in the Arctic， especially in understanding the microbial process of CH₄ production and oxidation. This study improved our understanding of the emission characteristics and mechanisms of CH₄ from thermokarst lakes and ponds in the Arctic， providing valuable insights into the potential impact of CH₄ emissions from this region and its impacts on climate change.

Snowfall is a common form of precipitation in mid-high latitudes during winter. Intense snowfall can lead to thick snow cover and trigger snow disasters， so it is one of the significant natural hazards in northern China and the Tibetan Plateau during the winter season. Past studies on snow density in snow-covered areas mainly focused on the overall snow cover condition over a certain period， but few focused on the newly-added snowfall. In this study， the observation data including precipitation， snow depth， temperature， wind speed， and weather phenomena from 50 meteorological stations in Jilin Province from 1961 to 2021 are utilized. After rigorous data verification and preliminary calculations， the sequence of newly-added snow depth of moderate to heavy snowfall events is obtained. Furthermore， the relationship between snowfall and newly-added snow depth is investigated， and then the causes of this relationship are analyzed. The results show that for the moderate to heavy snowfall events in Jilin Province， there is a correlation coefficient of 0.78 between snowfall （S） and newly-added snow depth （D）， which has passed the significance testat99.9% confidence level. The average ratio of newly-added snow depth to snowfall （Rds） is 0.96 cm·mm^-1. The Rds is small in western areas and large in eastern areas. In most stations of western areas， the multi-year average Rds ranges from 0.82 to 0.99 cm·mm^-1.In most parts of Changchun City and Siping City， and the entire Liaoyuan City， the Rds is from 1.01 to 1.10 cm·mm^-1. For the southern and most central-eastern areas of Jilin Province， the Rds is between 1.11 cm·mm^-1 and 1.25 cm·mm^-1. The Rds exhibits distinct monthly， annual and decadal variations. The monthly variations follow an asymmetric parabolic pattern， with December and January being the peak periods. The multi-year average Rds ranges from 1.22 to 1.24 cm·mm^-1. The Rds is lower during November and February （from 1.07 to 1.10 cm·mm^-1）， and is the lowest in October and April with an average of 0.89 cm·mm^-1. Over the past 60 years， the Rds has decreased with a rate of -0.01 cm·mm^-1·（10a）^-1， which has passed the significance test at the 95% confidence level. The Rds is relatively greater （1.16 cm·mm^-1） in the 1970s and 1980s， slightly lower （from 1.13 to 1.14 cm·mm^-1） in the 1960s and 2000s， and the lowest in the 1990s （1.09 cm·mm^-1） and 2010s （1.05 cm·mm^-1）. In the past 60 years， the Rds variation in December has contributed the greatest to the Rds variation in the whole snow season in Jilin Province. The monthly average difference of Rds between 1970s and 2010s （typical years） is larger than that between 1961—1990 and 1991—2020 （standard climatic periods）. Moreover， most months during the snow season have played an important role in the variations of the average Rds in typical years. The decrease of Rds in Jilin Province over the past 60 years has shown consistent spatial variation. The range and magnitude of the Rds decrease is larger in typical years than in the standard climatic periods. The Rds on snowfall days exhibits a clear negative correlation with temperature. Within the temperature range of -12 ℃ to 0 ℃， the Rds significantly decreases as temperature rises. Global warming， increased precipitation， and reduced wind speed are direct factors contributing to the interdecadal variations of the relationship between snowfall and newly-added snow depth. Understanding the relationship between snowfall and newly-added snow depth is important in comprehending the characteristics and formation mechanisms of snowfall and snow cover in mid-high latitudes of Northeast Asia. We hope the results may provide some valuable insights for predicting snow depth， snowfall parameterization， and snow disaster mitigation.

Geoengineering， as a potential avenue for tackling climate change， seeks to address global climate change scenarios， manage the pace of global warming， and counteract human-induced impacts on the climate. This paper， utilizing bibliometrics， systematically dissects the trajectory of international research in the realm of geoengineering， shedding light on scientific and technological frontiers through metrics such as publication numbers， global collaboration， and frequently employed terms. In recent years， the overall global scientific research in the field of geoengineering has shown a growing trend， and countries such as China， the United States of America and the United Kingdom are in a world-leading position in this field， with strong scientific research level. Geoengineering research predominantly resides in the realm of model simulation and assessment at this juncture. A significant portion of the research lacks tangible， analyzed data， and some geoengineering methods and technologies probably pose potential threats to the natural environment and society. Solar radiation management technologies stand out as potentially menacing to global and regional climate patterns， while carbon dioxide removal technologies are marked by unintended environmental consequences and uncertainty regarding their long-term impacts on the Earth’s climate system. Furthermore， glacier geoengineering is emerging as a focal point in the cryosphere discipline and the broader field of global change. Applied research in this domain has commenced in polar ice caps and select mountain glaciers， guided by geoengineering principles. However， the majority of efforts involve numerical simulations and scenario design， with only a handful of field experiments conducted. Looking ahead， the trajectory of geoengineering research will pivot towards securing financial and technical support for experimental endeavors. This shift aims to enhance modeling capabilities and furnish empirical and theoretical foundational data for technical analyses. This evolution is expected to facilitate the transition of geoengineering from its current phase of model simulation to large-scale commercial demonstration. The development of geoengineering requires ethical and moral guidance， combined with energy transformation strategy in China， and may be based on international cross-disciplinary cooperation development and deployment to help protect the environment and improve human well-being.

As one of the three major snow regions in China， the snow variation on the Qinghai-Xizang Plateau plays a crucial role in the climate system， hydrogeology， and ecological environment. Existing passive microwave snow depth （SD） inversion methods face challenges such as low resolution and high uncertainty， making them unsuitable for the complex mountainous terrain of the Qinghai-Xizang Plateau. Therefore， this study develops a downscaling SD inversion model for the Qinghai-Xizang Plateau based on FY-3B passive microwave data. Utilizing machine learning algorithms， the selected brightness temperature differences are used as input parameters. Additionally， features such as elevation， latitude， longitude， fractional vegetation cover （FVC）， fractional snow cover （FSC）， and snow cover days （SCD） are introduced. The final SD mapping is conducted at a resolution of 500 m. Results demonstrate that the Extreme Gradient Boosting （XGBoost） algorithm exhibits superior performance with a coefficient of determination （R²） of 0.762 and a Root Mean Square Error （RMSE） of 5.732 cm， outperforming support vector regression and random forest algorithms. We investigated the variation in model accuracy from three perspectives： SCD， FSC， and FVC. The findings indicate that the model performs well when the SCD is between 30 and 60 days， with the lowest Mean Relative Error （MRE） at 36.79% and RMSE at 2.78 cm. As FSC increases， the model’s RMSE gradually increases， reaching 39.97% for MRE and 3.12 cm for RMSE in the FSC range of 0.25 to 0.50. The impact of FSC on model accuracy is complex and may be related to specific land cover types. Within the range of 0.25 to 0.5 for FVC， the model demonstrates higher accuracy， with MRE and RMSE at 32.77% and 2.94 cm， respectively.

Snow cover is one of the most active factors in the cryosphere， directly affecting the energy exchange between the atmosphere and the Earth. Snow depth （SD） is an important attribute to describe the temporal and spatial variation of snow cover， and is an important input parameter for models such as basin water balance， and the simulation of snow runoff. Passive microwave remote sensing utilizes the strong correlation between the differences in snow scattering characteristics and snow depth at different frequency brightness temperatures （BT） for snow depth inversion. It is widely used to study the temporal and spatial variations of snow depth at global or regional scales. However， due to the strong spatial and temporal heterogeneity of snow cover in mountainous areas， the spatial distribution is uneven， the temporal variation is different， so these passive microwave remote sensing snow depth products with coarse spatial resolution are greatly limited. Especially in the mountainous areas of the Qinghai-Xizang Plateau， due to the spatial discontinuity and heterogeneity， these data are insufficient to represent the snow conditions at a regional scale. This study is based on MODIS fractional snow cover dataset， and uses empirical fusion rules and snow decay curves to perform spatial downscaling on the two sets of snow depth products of "the long-term series of daily snow depth dataset in China". The first set of snow depth product， referred to as Che_SSMI/S products， is inverted from SMMR， SSMI， and SSMI/S， while the second set， Che_AMSR2 products， is inverted from AMSR-2 brightness temperature. Ultimately， the 500 m downscaled snow depth data （Che_SSMI/S_NSD and Che_AMSR2_NSD） of the Qinghai-Xizang Plateau were obtained. There are significant differences between the two sets of snow depth data after downscaling. Utilizing 6 scenes of Landsat-8 images， we conducted a comparative analysis of the downscaled snow depth data from the two sets， it was found that both sets of downscaled data had a high degree of agreement with the spatial distribution of snow cover in Landsat-8 images. The Che_AMSR2_NSD product was compared with the snow depth data of 29 meteorological stations and found that the data were closer to the measured snow depth data， the correlation coefficient （R） was 0.72 and the root mean square error （RMSE） was 3.21 cm， while the correlation coefficient between Che_SSMI/S_NSD and the measured snow depth is 0.67， the RMSE is 4.44 cm. It is speculated that the reason for this discrepancy may be due to the difference in the accuracy of the two sets of original snow depth products with brightness temperature data from different sensors. In addition， the experimental results show that the downscaled accuracy of passive microwave snow depth products is also affected by factors such as snow depth and snow cover period. The results show that the accuracy of downscaled snow depth is different at different snow depth and different snow cover periods. Specifically， when the snow cover is accumulation period and stable period， the downscaled accuracy of the two sets of snow depth products is higher， while when they are in the snow ablation period， the accuracy gradually decreases. The highest downscaled accuracy for both sets of snow depth products occurs， when the snow depth is less than 10 cm. Conversely， the accuracy of the snow depth is significantly reduced when the snow depth exceeds 30 cm， which may be due to the saturation issues in passive microwave snow depth inversion. Through the comparative evaluation of the two sets of downscaled snow depth products， it is helpful to understand the temporal and spatial distribution of snow depth more comprehensively over the Qinghai-Xizang Plateau， and provide snow depth data support for its application.

Net shortwave radiation provides the main melting energy for mountain glaciers， which is modulated by a combination of glacier surface albedo and incoming shortwave radiation. Glacier mass balance， as a link between atmosphere and glaciers， is an important glacier parameter that characterize glacier accumulation and melting， and is sensitive to climate change. Many scholars have used the albedo method to study mass balance for an individual glacier， but less attention has been given to large-area glaciers. This study helps to understand that glacier melting is a result of climate and atmospheric changes， as well as feedback from glacier surface albedo. In order to investigate variations of glacier surface albedo from 2000 to 2022 in the Sawir Mountains and further estimate annual mass balance， two models （A-Ms and A-Mr） between albedo and mass balance were established based on MOD10A1 and MYD10A1 snow products retrieved glacier surface albedo， geodetic mass balance in the Sawir Mountains， in situ measured albedo and mass balance on Muz Taw Glacier. During ablation season， glacier albedo decreased by 0.035 in the Sawir Mountains at the rate of 0.0015 a^-1， and dates of minimum albedo appeared to have a shift towards earlier at the rate of 10 d·（10a）^-1. The A-Ms model established a linear relationship between albedo and mass balance on Muz Taw Glacier at the 95% confidence level， and indicated that a strong linear coefficient （R²=0.84） was found between albedo changes and mass balance. For A-Mr model， the R² between albedo and mass balance in cirque， valley and hanging glaciers in the Sawir Mountains were 0.81， 0.74 and 0.72 at the 99% confidence level， respectively. The reconstructed two albedo-mass balance relationships can be used to retrieve glacier mass balance. Furthermore， average annual mass balance in the Sawir Mountains estimated from A-Ms and A-Mr models were -1.24 m w.e.·a^-1 and -0.90 m w.e.·a^-1， respectively. Mass balance estimated from A-Mr model was closer to geodetic mass balance， which could better reflect mass loss in the Sawir Mountains. In addition， compared with glaciers in High Mountain Asia， glacier mass loss in the Sawir Mountains was the greatest. Glacier mass loss in the northern and western regions of High Mountain Asia was smaller than that in the southeast， and in recent years， glacier mass in High Mountain Asia had been in a state of severe loss.

Glacier is an important component of cryosphere. As an important fresh water resource in arid area of western China， the vulnerability of glacier change is closely related to regional social and economic development. Based on remote sensing images， this paper analyzed the characteristics of glacier change in the Chinese Altai Mountains from 1990 to 2020， constructed the evaluation framework and index system of glacier change vulnerability， demonstrated the temporal and spatial evolution pattern of glacier change vulnerability in the Chinese Altai Mountain from 2000 to 2020， and explored deeply the influencing factors of glacier change adaptability by using the obstacle degree model. The results showed that： （1） In the past 30 years from 1990 to 2020， the glacier area and volume in the Chinese Altai Mountains had decreased by about 20%， and there were significant differences in the change rate of glacier area in different counties and cities. The glacier area reduction rate in Qinghe was the largest， reaching 73%， while that in Burqin was the smallest， only 18%. （2） The glacier change vulnerability in the Chinese Altai Mountains decreased slowly at first and then experienced an accelerated increase over time， with the regional differences decreasing continuously. In spatial distribution， the glacier change vulnerability in the northwest and east was moderately high； the glacier change vulnerability in southwest was low； the vulnerability in central was the lowest. （3） The improvement of adaptability can effectively reduce the glacier change vulnerability in the Chinese Altai Mountains. Taking 2010 as the boundary， the glacier change adaptability in the Chinese Altai Mountains depended on the improvement of the regional economy and water resources in the early stage， and the improvement of adaptability in the later stage was significantly inclined towards social public income， investment， and public service quality. The ways to improve adaptability in counties and cities became more diversified and balanced.

With global warming， Arctic temperature is increasing， and melt pond has become an important feature of Arctic sea ice. Due to the positive feedback of ice surface albedo， sea ice is melting rapidly， and thus the size and shape of melt pond are very important for the simulation of Arctic sea ice change and further for the validation of existing remote sensing algorithms. In the present study， 6 103 images of sea ice were obtained onboard the icebreaker R/V Xuelong 2 during the 12th Chinese National Arctic Research Expedition， 5 489 of them remain after excluding invalid images such as uneven illumination and blurring， and then the spatial distribution and statistical characteristics of melt pond size and morphological parameters are investigated. The watershed algorithm is applied to segment the images into 9 uniform copies， and the random forest algorithm classifies the segmented images and creates a training set. Each image is classified into three surface categories including water， ice， and melt pond by the automated method， and the area fraction of each category as well as the size and shape of individual melt pond is calculated after tilt correction. The results show that the area fraction of melt pond increases and then decreases with increasing latitude， and the area fraction of ponded ice decreases with increasing latitude. The shorter melting time and earlier refreezing result in lower area fraction of melt pond at higher latitudes. The area， perimeter， and mean clamp diameter of the melt pond have similar patterns of change with increasing latitude. All of them rise first and then drop， indicating that the parameters of melt pond size have good consistency. The median value of melt pond area is significantly lower than the mean value indicating that there are more relatively small melt ponds. The frequency distribution of different sizes of melt pond areas is consistent with the power-law function， and the indices fitted to different observations are in the range of 1.4~1.8， with some similarity. The fractal dimension of the melt pond is more evenly distributed with increasing latitude， indicating that the melt ponds at different locations and evolutionary stages have some similarity. There is a significant difference in convexity values between melt ponds and circles at different latitudes， which indicates that the edges of the melt ponds form many concave shapes， and are more jagged due to the inconsistent melting rate of the edge line or the uneven depression of the sea ice surface. The perimeter-to-area ratio varies more with latitude， which indicates the difference in the number density of small melt ponds. And the average value of roundness of the melt ponds at various latitudes is 2.39±0.23， when the melt pond shape is close to a long rectangle， indicating the non-round shape and geometric complexity of the melt pond. The roundness and convexity of the melt pond are positively proportional to its area， while the perimeter-area ratio is inversely proportional to the melt pond area， indicating that the melt pond shoreline will become longer and more curved with increase of the melt pond area， and jaggedness of the edge is more obvious. There is no obvious relationship between fractal dimension and melt pond area， which is more uniformly distributed. The average sea surface albedo caused by changes in melt ponds varies between 0.24 and 0.67 with increasing latitude， and is highly correlated with the latitudinal variation of ice area fraction， with a rate of change of 0.10 （° N）^-1 from 81.7° N to 86.2° N. The melt pond size and morphological parameters studied in this paper can be used for numerical simulation of melt pond evolution and to complement and validate remote sensing algorithms.

Analyzing the evolution characteristics of dissolved organic matter （DOM） in glaciers is an important basis for evaluating the biogeochemical effect of glacier melting on downstream ecological environment. However， the evolution characteristics of DOM in surface snow in winter and spring are still unclear. In this study， the surface snow of Dagu Glacier and glacial runoff in winter and spring was studied， and DOM in the surface snow was characterized at molecular level by using Fourier transform ion cyclotron resonance mass spectrometry （FT-ICR MS）. The results indicate that the chemical composition of DOM in the surface snow of Dagu Glacier during winter and spring exhibits a diverse range， primarily consisting of lipids， peptide-like， unsaturated compounds， and minor quantities of polyphenolic， condensed aromatics， and sugars compounds. The sources of these components include both microbial and terrestrial origins. The main source of DOM in spring runoff is terrestrial inputs， which is greatly affected by human activities. The molecular composition of DOM in surface snow in different seasons was analyzed， and it was concluded that the low temperature environment in winter was conducive to the enrichment of aliphatic， peptide-like and S-containing DOM molecules in surface snow， and the higher temperature in spring was conducive to the enrichment of peptide-like， unsaturated hydrocarbons and N- containing DOM molecules in surface snow. Comparing the molecular composition of DOM in spring runoff and surface snow， it was found that the content of heteroatomic DOM in runoff decreased， the content of aliphatic and peptide-like DOM from microbial source decreased， and the content of terrestrial sources of polyphenolic and condensed aromatics significantly increased， indicating that the biological activity of DOM in runoff decreased and the photoreactive activity increased. The continuous melting of glaciers leads to the influx of a significant amount of glacial meltwater into downstream water environments. This influx， combined with microbial activities and light reaction processes， results in an increased emission of greenhouse gas CO₂ and intensifies the greenhouse effect.

Glaciers in Xinjiang， northwestern China， have experienced drastic retreat phenomena due to climate warming in recent decades. Glacier retreats have led to an increase in glacial meltwater runoff and accelerated the formation and expansion of glacial lakes. Especially in the core area of the Silk Road Economic Belt and climate change-sensitive areas， ice-marginal compound disasters， such as glacial surges and glacial lake outburst floods （GLOFs）， have entered a period of high incidence and acceleration. The resulting economic losses and potential risks will also become increasingly severe and prominent. Accurate mapping and monitoring of these glacial lakes is therefore critical to understanding the response of GLOF hazards to climate change. In this study， we conducted a detailed mapping of glacial lakes in Xinjiang from April to October 2022 using the DUNet semantic segmentation model and Sentinel-2 imagery， extracted the maximum boundaries of glacial lakes in Xinjiang from April to October 2022， and manually inspected to exclude non-glacial lakes and supplement glacial lakes missed due to shading. We used three-level basins to divide distribution area of glacial lakes in Xinjiang into 11 subregions. We assigned detailed attribute information to each glacial lake， such as center coordinates， perimeter， area， elevation of the center point of the glacial lake， subregion name， subregion code， absolute error， relative error， and so on. In addition， we screened out glacial lakes with an area greater than 0.06 hm². We analyzed spatial distribution of these lakes and trend of change over the past decade in conjunction with the existing inventory of glacial lakes. Results showed that the glacier mapping based on Sentinel-2 got more lake numbers and achieved lower relative errors than the existing Landsat-based inventories， with average relative errors of large （>10 hm²）， medium （>1~10 hm²）， and small （≤1 hm²） lakes are 2.29%， 10.02%， and 27.71%， respectively. The relative error of this glacial lake dataset with an area larger than 0.81 hm² is 18.36%， which meets the mapping accuracy of monitoring glacial lake changes in Xinjiang for more than 20 years. About 6 854 glacial lakes with a total area of 200.36 km² were mapped throughout Xinjiang. Specifically， small glacial lakes accounted for 70.32% of the total number of glacial lakes but only 7.51% of the total glacial lake area； medium glacial lakes and large glacial lakes accounted for 29.68% of the total number of glacial lakes， but the area accounted for 92.49% of the total area. The patterns of lake distribution are heterogeneous in different mountainous areas， and the glacial lakes are numerous in the Altai Mountains （1 474）， western Tianshan （Ili River basin） （1 170）， and southwest Tianshan （Tarim inflow area） （915）. The number of glacial lakes peaks in the altitude range of 3 300~3 600 meters. In the last 30 years， glacial lakes with areas of less than 10 hm² increased significantly in number and area， especially in the Altai and the Western Tianshan Mountains. Therefore， the regional differences in the distribution of glacial lakes in Xinjiang are significant， with a large number of small glacial lakes， which tend to be more sensitive to climate change and change more drastically and can effectively reflect the changes in regional climate and glaciers. This study provides an important dataset for monitoring and disaster assessment of glacial lakes in Xinjiang， which is essential for a deeper understanding of the response of glacial lakes to climate change and the development of effective coping strategies. Future studies will improve the construction of a multi-period glacial lake catalog database， further analyze the changing characteristics of glacial lakes in Xinjiang， and explore GLOF disaster and its coupling relationship with climate， glaciers， and other elements.

Slope aspect and position are important factors influencing the infiltration of soil moisture in slope active layer， but there is currently limited research on the infiltration characteristics of soil moisture in different slope aspect and position under the influence of freeze-thaw cycles in the active layer of permafrost region. This study establishes field experimental sites with different spatiotemporal conditions， enabling a more comprehensive analysis of the spatiotemporal variations in the soil moisture infiltration process within the active layer of permafrost region on the Qinghai-Tibet （Xizang） Plateau. We select the active layer soil on the slope surface of the alpine meadow in the Fenghuoshan basin， located in the hinterland of the Qinghai-Tibet Plateau， and set observation points at different slope aspects （sunny and shady slopes） and positions （top and middle of slopes） to analyze the infiltration characteristics and spatiotemporal differences of soil moisture on the slope surface during complete thawing period （July to August） and initial freezing period （September to October） of the active layer soil， and evaluate the applicability of different infiltration models in the study area. The results indicate that the infiltration characteristics of soil moisture in slope active layer in permafrost region exhibit significant spatiotemporal variations. The infiltration process of soil water can be divided into three stages： infiltration transient stage （0~30 min）， infiltration gradual stage （30~100 min）， and infiltration steady stage （>100 min）. The infiltration rate shows as follows： sunny slope > shady slope， top of slope > middle of slope， complete thawing period > initial freezing period， infiltration transient stage > infiltration gradual stage > infiltration steady stage. By using five models to simulate the infiltration process， the results show that the Horton model has the best simulation effect for the infiltration process of soil water in permafrost regions of the Qinghai-Tibet Plateau. However， the general empirical model and Jiang Dingsheng’s formula has almost identical fitting curves and statistical parameters for infiltration， but the model expressions are different. The simulation and analysis of soil moisture infiltration in permafrost region of Qinghai-Tibet Plateau in this study will provide data support for parameterization of land hydrological model under different spatiotemporal conditions.

Debris flows pose a significant geological hazard， inflicting severe damage to infrastructure such as buildings and roads in eastern region of the Qinghai-Tibet （Xizang） Plateau. Considering the background of global warming， the likelihood of potential debris flow occurrences in the mountainous areas of the Qinghai-Tibet Plateau is expected to rise. Therefore， a quantitative assessment of debris flow susceptibility assumes great importance as the primary approach for implementing regional disaster reduction and prevention measures. The formation of debris flows is influenced by source conditions， terrain conditions， and water conditions. In this study， we focus on the variability of source and terrain conditions while temporarily assuming constant water conditions within a small area. Specifically， we address the challenge of determining and quantifying source conditions by examining the freeze-thaw erosion type provenance in the Gonjo （Gongjue） area of eastern Tibet. Through detailed field investigations and comprehensive research， we calculate the freeze-thaw erosion intensity （DR） to represent the source conditions of debris flows. To evaluate debris flow susceptibility， we select eight factors related to source and terrain conditions， including freeze-thaw erosion intensity （DR）， elevation （H）， plane curvature （Pl_cv）， profile curvature （Pr_cv）， slope （Slope）， stream power index （SPI）， topographic wetness index （TWI）， and terrain characterization index （TCI）. The weight values of these eight evaluation factors are determined using the analytic hierarchy process （AHP） and principal component analysis （PCA） methods. The susceptibility of debris flow in Gonjo area of eastern Tibet is then evaluated using the weighted information method. Additionally， the study divides the watershed units into four groups based on different flow thresholds （5 000， 10 000， 20 000， and 40 000） and analyzes and compares the susceptibility evaluation results of each group. The evaluation results are further validated using the receiver operating characteristic curve （ROC） analysis. The main findings of this study are as follows： Firstly， among the selected evaluation factors， freeze-thaw erosion intensity （DR）， terrain characterization index （TCI）， and plane curvature （Pl_cv） exhibit the highest weight values， with their cumulative weights exceeding 0.5. This indicates that these three factors are more sensitive to debris flow formation in the study area and contribute significantly to debris flow susceptibility. Secondly， based on the susceptibility evaluation results of the four groups of watershed units， the group G2 （flow threshold 5 000） demonstrates the highest area under the curve （AUC） value， followed by groups G3 and G4， while group G1 exhibits the lowest AUC value. These results highlight the efficacy of employing the G2 group to divide watershed units when conducting debris flow evaluations in the study area and surrounding regions， as it yields relatively accurate evaluation outcomes. Lastly， the study establishes a debris flow susceptibility evaluation model incorporating freeze-thaw erosion type provenance and topographic hydrological factors， which yields satisfactory evaluation results. This indicates the viability of integrating freeze-thaw erosion intensity to characterize source factors and underscores the feasibility of a susceptibility evaluation system primarily driven by provenance and topography in Gonjo area of eastern Tibet. In conclusion， this study introduces novel methodologies and concepts for assessing debris flow susceptibility in the region， where freeze-thaw erosion phenomena are prevalent. The findings significantly contribute to the theoretical research and hold practical implications for guiding local authorities in disaster prevention and mitigation efforts.

The presence of supraglacial debris profoundly influences the energy transfer processes between the atmosphere and glaciers， fostering the development of supraglacial ponds and ice cliffs， and significantly altering the glacier ablation processes and hydrological patterns. Modeling the interactions and feedback processes among climate， supraglacial debris， and glaciers by various parameters of debris deepens our understanding of the process and mechanism of debris-covered glaciers change， aiding in the accurate estimation and prediction of glacier mass balance， and then assisting in assessing the future evolution trend of glacier morphology. This paper systematically summarizes and compares various techniques for identifying the extent of debris cover， extracting glacier flow velocities， and obtaining physical parameters of supraglacial debris. Additionally， it introduces the principles and applications of glacier ablation models incorporating supraglacial debris cover effects. Furthermore， the limitations and future developments of these methods or models are discussed. Debris-covered glaciers situated in mountainous terrains with complex surface changes， posing several challenges for remote sensing methods to identify the extent of debris cover and extract glacier flow velocities： the existing supraglacial debris identification methods are still unable to overcome the influence of inherent disturbing factors； The flow velocity extraction methods should have a strong anti-interference ability， and the time baseline for paired images need to be as short as possible. The present state of research on debris-covered glaciers reveals significant data gaps in key parameters and data. Nevertheless， it is expected that these deficiencies will be addressed in the future， resulting in more refined models describing glacier dynamics and the change processes of supraglacial debris. Consequently， assessments and predictions of glacier mass balance， runoff， and other indicators are anticipated to become more realistic and accurate.