Affected by the severely cold climate， cold region tunnels are often faced with a series of frost damage problems， such as lining ice hanging， freeze-thaw damage or cracking， road icing and drainage system freezing failure， which pose great challenges to the construction and operation of tunnels. The sub-zero temperature environment is the necessary condition for frost damage in tunnels， thus mastering the longitudinal distribution of air temperature in tunnels is the basis and premise of frost damage research and engineering control measures in cold regions. However， various tunnels differ in environmental meteorology， engineering structure and traffic conditions significantly， resulting in obvious discrepancies in the longitudinal distribution characteristics of air temperature， causing many difficulties in accurately predicting and obtaining the longitudinal distribution of air temperature inside cold region tunnels. Therefore， in order to obtain the distribution characteristics and influence factors of air temperature in cold region tunnels， literature research and statistics and analysis methods were used to collect and sort the field measuring data and related influence factors of air temperature inside 52 cold region tunnels in China. According to the distribution characteristics of air temperature inside tunnels in cold regions， they are divided into three types： symmetric， asymmetric and cut-through type， and then the length and burial depth of each type of cold region tunnels are statistically analyzed. On this basis， the influential mechanism of temperature in tunnel site area， geothermal heat of surrounding rock and ventilation in tunnel on air temperature in the tunnels is discussed. Subsequently， the natural wind， engineering construction， mechanical ventilation and traffic factors that cause air flow inside the tunnel were analyzed， and then the primary and secondary influence order of each factor was pointed out. The research results indicate that when the natural environmental factors at both ends of the tunnel portal are basically the same and the elevation difference between the two ends of the entrance is not significant， the air temperature inside the tunnel usually shows a symmetrical distribution. When there is a significant slope inside the tunnel or it is affected by the prevailing wind direction outside the tunnel， the air temperature inside the tunnel often shows an asymmetric distribution. When the tunnel length is short， the burial depth is small and unidirectional wind is prevalent， the air temperature distribution inside the tunnel often presents a cut-through type. In addition， in terms of the primary and secondary factors affecting the temperature distribution inside cold region tunnels， the environmental temperature in the tunnel site area（tunnel entrance and exit） plays a decisive role in the distribution of temperature inside the tunnel， the burial depth of the tunnel determining the geothermal effect has an important impact on the temperature inside the tunnel， and ventilation is the key factor affecting the temperature inside the tunnel. Among the various factors affecting ventilation， natural wind and longitudinal slope design are the main factors influencing the longitudinal distribution of air temperature inside tunnels with slight entrance and exit elevation differences and short lengths and tunnels with significant entrance and exit elevation differences and long lengths respectively， while engineering ancillary structures， mechanical ventilation and traffic factors are relatively secondary. This research will provide reference for the study of frost damage， insulation laying design and operation and maintenance of cold region tunnels.

Climate change has the potential to alter the global water cycle， resulting in an uneven spatial and temporal distribution of water resources. Furthermore， climate change can result in an increased frequency of meteorological and hydrological disasters. The Qinghai-Xizang Plateau is the most unique geological-geographical-ecological-resource-climatic unit on the Earth， known as “Asia Water Tower” and “The Third Pole”. It is the source of more than ten major rivers in Asia and is known as the “Water Tower of Asia”. With the intensification of global warming， extreme hydrological and meteorological events become more frequent on the Qinghai-Xizang Plateau. However， the complex climate and underlying surface characteristics， including glaciers， snow cover， and permafrost， limit our understanding of the response of extreme runoff to extreme precipitation in this region. Against this background， this study taking the Yarlung Zangbo River basin in the southern part of the Qinghai-Xizang Plateau as an example， this study， based on daily precipitation and runoff data， improves the method of identifying extreme streamflow and utilizes correlation analysis to investigate the relationship between extreme streamflow and extreme precipitation at different probabilities. The results indicate that extreme streamflow typically last 1~2 days in the Yarlung Zangbo River basin， and as the probability decreases， the duration of events correspondingly shortens. Extreme streamflow events with probabilities of 10%， 5%， and 1% exhibit coefficients ranged from 0.07 to 0.28 （P<0.01） with extreme precipitation， and the relationship strengthens with increasing probability of extreme precipitation. At the Nuxia Hydrological Station， the response intensity of extreme streamflow to extreme precipitation in the upper stream of Nuxia Hydrological Station is greater than that at the Nuxia and Linzhi Meteorological Station， with a lag of one day. Additionally， the response of extreme streamflow to extreme precipitation is also influenced by moisture content， vegetation conditions， and soil moisture changes in the Yarlung Zangbo River basin. The improved methods of identifying extreme streamflow in this paper can effectively capture the extreme streamflow events influenced by extreme precipitation in the Yarlung Zangbo River basin， and improve the understanding of the relationship between extreme streamflow and extreme precipitation response in high-altitude basins with complex streamflow sources. At the same time， this paper offers significant theoretical support and scientific guidance for the management of water resources and the regional economic development of the Yarlung Zangbo River basin in the context of climate change.

Scientific data has become a strategic resource， and scientific data centers， as crucial entities for the long-term storage and open sharing of scientific data， support the development of science and technology innovation. With an accumulation of scientific data construction spanning over 30 years， the National Cryosphere Desert Data Center （NCDC，http：//www. ncdc.ac.cn） aggregates over 60% of scientific data in the domestic glacial， permafrost， and desert research field. In order to promote the open sharing of scientific data resources in these field， NCDC has researched the construction of the resource systems， mechanisms， and methods for scientific data in cold and arid regions. The overall development objective is to build a scientific data system encompassing ice， snow， permafrost， deserts， and related elements， advancing theoretical methods for scientific data and formulate key technologies for the collection， transmission， storage， management， analysis， sharing， application， and product development， creating an integrated scientific data application resource pool that combines data， models， and computation. Simultaneously， assembling a group of interdisciplinary data teams to drive innovative work and establishing a benign development and sharing service ecosystem for scientific data. Additionally， advancing the disciplines of data engineering， key technologies for data engineering applications， and an international alliance for scientific data， constructing research-oriented， production-oriented， and intelligent scientific data centers with international influence， and providing scientific data and decision support for scientific and technological activities， ecological civilization， engineering construction， disaster prevention and control， and diplomatic negotiations in cold and arid regions.This paper reviews the development process and construction strategies of NCDC， summarizing its research practices in the field of scientific data sharing in cold and arid zones， covering aspects such as the construction of standard specifications， data resource management， system platform construction， and the effectiveness and progress of shared services. Finally， future development prospects are provided for the sustainable development of the National Scientific Data Center.

Understanding the evolution history of rock glaciers is the key to reveal the response of periglacial environment to climate change. However， the chronology of rock glaciers is relatively inadequate due to the lack of suitable dating materials and other reasons. Quaternary glaciation and periglacial environment were widely developed in Zheduo Mountain， located on the southeastern margin of the Qinghai-Xizang Plateau， which provided conducive conditions for the formation of rock glaciers. Based on the geomorphological investigation and ¹⁰Be exposure dating， we accurately dated a moraine-type rock glacier in Zheduo Mountain and further discussed its formation age and development characteristics. The results show a formation time of rock glaciers in the Zheduo Mountain at about （11.8±0.3） ka， corresponding to the late period of the Last Deglaciation. Millennium-scale climatic cooling events during the Last Deglaciation led to multiple cold and warm climate changes， leading to repeated glacier advances and retreats. The transport and accumulation of a large number of moraines strongly shaped the geomorphic landscape， promoted the continuous expansion of permafrost scale， and also provided the material basis for rock glaciers. Based on the studies of stone glaciers in the Qinghai-Xizang Plateau and other parts of the Northern Hemisphere， it is found that the formation age and evolution characteristics of the rock glaciers during the Last Deglaciation are similar. During the large-scale retreats of the glacier， sudden cooling events lead to the glacier advance and the expansion of the periglacial area， and when the temperature rises， the deglaciated proglacial area becomes a new periglacial environment， and glacial meltwater and sediment are generated at the same time， which promotes the development of the rock glaciers. The glacial and periglacial geomorphological processes， such as the repeated advance and retreat of glaciers， the expansion of permafrost areas， and the development of rock glaciers， caused by climate change， to a certain extent， indicate that the interaction of glacial and periglacial geomorphological processes in the interglacial cycle is the key to understand the response of the cryosphere to climate change.

The utilization of wind energy resources is the top priority to achieve the “carbon peaking and carbon neutrality goals”. Based on daily wind speed observation and simulations from 5 CMIP6 models with 7 Shared Socioeconomic Pathways， this study constructs a database with 1 km horizontal resolution and analyses the spatiotemporal changes of the wind power in Qinghai Province during 1961—2022， “carbon peak” period of 2026—2035 and “carbon neutral” period of 2056—2065. The results show： （1） From 1961 to 2022， the average annual 10 m wind speed in Qinghai Province is 3.06 m·s^-1， the 100 m wind power densities is 125.14 W·m^-2， and the number of wind energy available days is 167. The wind power decreases gradually from the west to the east. The wind energy resources in Tsaidam Basin and Tanggula Mountains reach the suitable development standard， and the maximum value is in the west of Burhan Budai Mountains； （2） Wind power in Qinghai Province exhibits a decreasing trend. The reduction speed of 10 m wind speed is 2.08%·a^-1， the 100 m wind power density is 1.40%·a^-1 and the available days of wind energy is 0.88%·a^-1； （3） Compared with the historical period， the 10 m wind speed at is 2.52 m·s^-1 （2.39~2.63 m·s^-1） with a decrease of 3.53% （2.34%~5.24%）， the wind power density is 50.28 W·m^-2 （46.17~64.08 W·m^-2） with a decrease of 10.20% （6.69%~14.91%）， and the wind energy available days is 114 days （105~124 days） with a decrease of 7.58% （2.44%~11.05%） from 2026 to 2035. From 2056 to 2065， the wind speed at 10 m is 2.49 m·s^-1 （2.31~2.59 m·s^-1） with a decrease of 5.71% （5.21%~6.53%）， the wind power density is 47.75 W·m^-2 （38.89~54.79 W·m^-2） with a decrease of 15.79% （14.72%~18.32%）， and the wind energy available days is 111 days （99~120 days） with a decrease of 10.73% （8.39%~13.55%）； （4） From 2026 to 2035 and 2056 to 2065， the 10 m wind speed at low emission scenarios （SSP1-1.9， SSP1-2.6 and SSP4-3.4） is 1.75% and 5.16% higher than high emission scenarios （SSP3-7.0， SSP5-8.5）， the 100 m wind power density is 5.23% and 14.28% higher， and the wind energy available days is 3.32% and 9.71% more. In general， the wind power in western part of Qinghai Province， especially Tsaidam Basin and Tanggula Mountains， is most abundant with relatively minor reduction， which has broad prospects for development and utilization.

Against the backdrop of global climate warming and the warming effects induced by human activities， the permafrost on the Qinghai-Xizang Plateau is experiencing accelerated degradation， leading to frequent occurrences of retrogressive thaw slumps. This phenomenon not only directly impacts the regional ecological environment， but also poses a potential threat to the stability of engineering structures. This paper aims to provide a scientific basis for the prevention and prediction of thawing hazards and the assessment of climate change by reviewing the research progress on retrogressive thaw slumps in the permafrost regions of the Qinghai-Xizang Plateau by summarizing the formation mechanism， extraction methods， distribution characteristics， influencing mechanism， as well as the subsequent impacts of retrogressive thaw slumps on environment and engineering. It is concluded that the formation of retrogressive thaw slumps is the result of the interaction of various complex factors and long-term accumulation， often resulting in headward erosion， with diverse development shapes mainly controlled by slope gradients. They present various developmental shapes， mainly including elongated， branched， and multi-headed tongue shapes. Spatially， retrogressive thaw slumps show inhomogeneous distribution， which cluster in engineering corridors on the Qinghai-Xizang Plateau. Their spatial distribution is mainly controlled by terrain and permafrost conditions. Furthermore， retrogressive thaw slumps can alter soil structure and physicochemical processes， affecting regional carbon cycling， thereby increasing global or regional greenhouse gas emissions. Based on high spatial resolution remote sensing images interpretation and unmanned aerial vehicle （UAV） field verification， retrogressive thaw slumps was widespreadly monitored. Currently， research often combines Planet Cube Sat imagery with deep learning algorithms to achieve automatic identification and mapping of retrogressive thaw slumps in large-scale permafrost regions. Deep learning models such as Deep Lab V3+ show a better performance in future extensive studies of retrogressive thaw slumps. With the increasing demand for engineering construction and ecological environment protection on the Qinghai-Xizang Plateau， it is necessary to investigate the formation mechanisms， developmental characteristics， influencing mechanisms， and impacts on the environment and engineering of retrogressive thaw slumps， which will provide a theoretical foundation and scientific basis for engineering planning， prevention of retrogressive thaw slumps， and environmental protection on the Qinghai-Xizang Plateau.

Glaciers and snow are important components of the cryosphere. The subglacial topography， shallow structure of glaciers and snow， and snow thickness are of great significance for water resources investigation， glaciers and snow disaster early warning and global sea level prediction. Snow/ice detection radar has excellent penetration for semi-transparent media like glaciers or snow， and has become an important detection means in cryosphere fields. Radar tomography is a new technique for perspective three-dimensional imaging of snow and ice， with broad application prospects in key elements inversion such as snow/ice thickness and shallow structure. This paper first introduces the basic principles and methods of three kinds of tomography techniques based on ice radar and synthetic aperture radar （SAR）， and focuses on the research progress of the snow/ice penetrating radar tomography systems and their applications over the past 20 years on domestic and foreign ground-， air- and space-based platforms. The characteristics and applicability of three kinds of tomography techniques are summarized and analyzed， and the current challenges and development trends are discussed. This paper can provide references for the development of China’s snow/ice tomography radar system， the retrieval of global ice and snow key elements， and ice layer detection on the moon or Mars.

Based on a review of existing studies and recent work， this paper collects and organizes research findings on glacier mass balance from 2013 to 2023. It summarizes the current methods and models commonly used in glacier mass balance research and reviews the status of such research in China. The results indicate the following： The commonly used methods for glacier mass balance research can be classified into three categories： traditional glaciological methods， geodetic imaging methods， and satellite gravity monitoring methods. Additionally， glacier balance models， which focus on the relationship between glacier mass balance （the algebraic sum of accumulation and ablation） and meteorological variables， have been developed. These models are based on energy balance equations and can be further divided into three subcategories： semi-empirical glacier balance models—degree-day models， energy-balance models， and coupled glacier flow and mass balance models， such as the Open Global Glacier Model （OGGM）. Under the influence of global warming， glaciers in China exhibit an overall negative mass balance trend with significant regional variations. Specifically： The No.12 Glacier in Laohugou， Qilian Mountains， experienced a severe mass deficit， with a cumulative loss of -71 760 mm w.e. between 1991 and 2020. The Kunlun Mountains initially showed relatively stable mass balance， but a negative trend has emerged in recent years. For example， glaciers in the eastern Malan Mountains lost -300 to -180 mm w.e. from 2000 to 2020. Glaciers in the Tianshan Mountains are significantly affected by temperature changes， showing a pronounced negative mass balance trend. For instance， glaciers in the Manas River basin lost -9 811.19 mm w.e. from 2000 to 2016， while the Urumqi Glacier No.1 lost -17 351.5 mm w.e. from 1956 to 2016. Glaciers in the Tanggula Mountains exhibit changes in mass balance similar to those in the Kunlun Mountains but with a more pronounced negative trend. Glaciers in the Dongkemadi River basin lost -7 550 mm w.e. from 1966 to 2015. In the Himalayas， glaciers show a slight negative mass balance. For example， glaciers in the Yamdrok Lake basin experienced a cumulative loss of -930 mm w.e. from 1987 to 2021. Glaciers in the Altai Mountains also exhibit a negative mass balance， with greater losses observed during 2000—2010 compared to the post-2010 period.

Ice cores are an effective proxy for past climate changes， and high-resolution reconstruction necessitates precise dating methods. This study combines manual dating with an automated layer recognition algorithm （StratiCounter） based on a Hidden Markov Model （HMM） framework to test， validate， and analyse the performance of the algorithm in assisting the dating of Zuoqiupu， Dasuopu， and Anemaqen ice cores. The method reduces the time required for manual layer-by-layer identification during binding reference layers， synchronizing with other ice core records， and reviewing processes by automatically inferring layer positions and providing error ranges. Initially， a collection of fundamental dating templates and layer constraint points are manually provided. Next， the algorithm familiarises itself with the template for calculating the quasi periodic cycle of the ice core proxy variable. It then identifies the target paragraph and examines the presence of layer constraints. Perform a comprehensive search for potential points while considering layer constraints， and employ the maximum likelihood method to determine the most suitable solution from the available options. The findings show that for the upper sections of the Zuoqiupu and Dasuopu ice cores， the algorithm-assisted dating results have an accumulated error of less than 2 years （3%） when compared to known chronologies， indicating a high level of consistency. Even under simulated sample loss conditions and the absence of tie points， the algorithm remains operational， resulting in a cumulative error of less than five years. Further analysis of the upper section of the Anemaqen ice core reveals 1 to 2 year differences between algorithmic and manual dating results at specific sections e₁ ［2.07， 4.47］ and e₂ ［8.31， 9.71］. After using pollution layer data， the ice core at 56.48 metres was dated to 74 years with an error range of ±3 years. Integrating reference layer findings like β-activity and ¹³⁷Cs with δ¹⁸O counting layers helped determine the age sequence of the upper 0.05~56.48 m of the Anemaqen Ice Core， from 1947 to 2020 AD. The method combines the advantages of manual dating with the standardised hierarchical recognition capability of algorithms， thereby reducing the need for manual intervention in the age correction process. It also quantifies potential dating errors and， to some extent， improves the dating procedure.

As an important type of land cover， the change of snow cover has important feedback and regulation effects on the local hydrological environment and phenological changes. Based on the daily snow depth observation data of 62 meteorological observation stations in Heilongjiang Province from 1961 to 2020， the temporal and spatial variation characteristics of maximum snow depth in Heilongjiang Province and its relationship with atmospheric circulation， temperature and snowfall factors were analyzed by Mann-Kendall test， empirical orthogonal function （EOF）， correlation analysis and other methods. The results showed that the average maximum snow depth in Heilongjiang Province from 1961 to 2020 was 16 cm， 14 cm， 10 cm and 8 cm in autumn， respectively. The maximum snow depth in year， winter and spring showed a significant increase trend， with an increase rate of 1.40 cm⋅（10a）^-1 （P<0.01）， 1.51 cm⋅（10a）^-1 （P<0.01）， and 0.76 cm⋅（10a）^-1 （P<0.05）， with an insignificant increase trend in autumn. From 1961 to 2020， the maximum annual and seasonal maximum snow depth in Heilongjiang Province changed abruptly in the late 20th century and early 21st century， and the maximum snow depth showed an increase in annual variation after the mutation. The maximum snow depth in Heilongjiang Province showed the spatial distribution characteristics of mountains （Greater and Lesser Khingan Mountains， Wanda Mountains） than plains （Songnen Plain and Sanjiang Plain）， while the change rate was that the plain was larger than the mountainous area， among which the maximum snow depth in the Songnen Plain increased the most. There are two main changes in the maximum snow depth in Heilongjiang Province： east-west reverse type and southeast-northwest reverse type. Temperature， snowfall， polar vortex intensity in the northern hemisphere， and East Asian trough intensity all affected the maximum winter depth in Heilongjiang Province， and the influence of snowfall and polar vortex intensity in the northern hemisphere was greater than that of temperature and East Asian trough intensity. As the climate warms， the influence of temperature and the intensity of polar vortexes in the northern hemisphere on the maximum snow depth in winter becomes more pronounced.

The Pamir Plateau is the largest center of glaciation in the high mountain regions of Asia. Glacial melt water plays a key role in regional water resources and water cycle. However， in recent years， there are still controversies about the understanding of glacier changes in the Pamir Mountains. On the one hand， it is believed that there is an abnormal progression of glaciers in the Karakoram Pamir Mountains Plateau. On the other hand， it is believed that the glaciers in the Pamir Plateau are accelerating their retreat. The reasons for this are twofold： firstly， there is a mismatch in the spatiotemporal scope of the study， and secondly， there are differences in the definition of glaciers in the study. Based on this， in order to understand the trend and magnitude of glacier changes in the Pamir Mountains， this study， based on multi-source remote sensing images and the Google Earth Engine （GEE） platform， constructed a glacier discrimination method combining the multi temporal minimum NDSI and the classification algorithm of glacial surface moraine area， automatically extracted the area change sequence of debris-free glaciers in the Pamir Mountains from 1990 to 2020 without surface moraine coverage， and analyzed the spatio-temporal change characteristics and trends of debris-free glaciers in the region， And clarify whether there is a phenomenon of “Pamir Karakoram Glacier Anomaly”. This study provides a profound explanation of the current changes in glaciers in the Pamir region， which can effectively support regional water resources and ecological environment protection. In order to clarify the spatiotemporal changes of debris-free glaciers in the Pamir Mountains in the past three decades， this study， based on the GEE platform， combined image cloud cover， seasonal snow cover， moraine cover at the end of the glacier and other factors， obtained the spatiotemporal changes of high-resolution debris-free glaciers in the Pamir Mountains in the past 30 years. The results indicate that the combination of GEE cloud computing platform and glacier classification algorithm is effective and feasible for quickly extracting glaciers， improving the efficiency of long-term glacier change research. During 1990—2020， the area of debris-free glaciers on the Pamir Mountains showed a general shrinking trend. In the past 30 years， the area of debris-free glaciers has shrunk from （12 108.98±250.38） km² to （8 616.44±7.22） km²， with an average reduction rate of 116.42 km²·a^-1.The area of naked glaciers in the west of Pamir Mountains Plateau generally shows a shrinking trend， while the area of debris-free glaciers in the east of Pamirs is relatively stable， the shrinking rate is relatively small， and some regions show an increasing trend during 2000—2010. There is an abnormal phenomenon of Pamirs glaciers. Since 2010， the area of glaciers began to decrease， and the abnormal phenomenon of Pamirs glaciers no longer exists. Based on the analysis of DEM data in Pamir Mountains， it is found that the distribution of debris-free glacier area in Pamir Mountains is normal with altitude， and the largest debris-free glacier area occurs at 4 900~5 200 m altitude. Since 1990， the reduction in debris-free glacier area has mainly occurred in mid altitude areas of 4 600~5 500 m， and has decreased towards high and low altitude sides. Based on the analysis of climate and glacier elevation changes， it is concluded that the glacier anomaly on the Pamir Mountains from 1990 to 2010 is caused by the thinning of the glacier thickness and the glacier jumping at the end of the glacier. This article explores the combination and application of high-performance algorithms and large-scale remote sensing data resources from cloud computing platforms with traditional band combination algorithms， enabling GEE to play a more important role in large-scale research such as the entire high Asia region to global glacier changes， and providing new ideas for large-scale spatial scale research and efficient data processing.

The stability of permafrost roadbeds is crucial for the safe operation of highways and railroads in cold regions. In order to comprehensively understand the current research status and development trend in the field of frozen soil roadbeds， CiteSpace was used to visualize and analyze the literature related to permafrost and seasonally frozen subgrade in the China National Knowledge Infrastructure （CNKI） and Web of Science databases. CiteSpace is a citation space metrics analysis tool that can help clarify the research trajectory， hot topics， and direction of development in a particular research area. Our search time range was from January 1， 2000 to August 31， 2023， and a total of 1 027 Chinese and 854 English documents were included. The current status and trend of research on permafrost roadbeds were illustrated by interpreting and analyzing the mapping of the number of publications， the mapping of authors’ cooperation relationship， the mapping of institutions’ cooperation relationship， the mapping of keyword clustering， and the mapping of keyword clustering timeline in the past five years. The results show that： since 2000， the publication volume of permafrost roadbed research has been on an overall growth trend. Starting from 2017， the number of English literatures gradually exceeded Chinese literatures， of which the publications of Chinese scholars in international journals accounted for about 80%. The cooperation between domestic research institutions is closer. As the core research institutions， the Northwest Institute of Ecology and Environmental Resources of the Chinese Academy of Sciences and Beijing Jiaotong University have formed a good cooperative relationship with other institutions， and have an important position in the journals concerning frozen soil roadbeds both at domestic and abroad. Among the foreign research institutions， Laval University and University of Manitoba in Canada have close cooperation. However， the cooperation between international institutions needs to be strengthened. The keyword clustering mapping shows that the research topics of permafrost roadbeds include three main topics， which are the stability of perennial permafrost roadbeds， the temperature field of permafrost roadbeds， and the diseases and prevention of roadbeds under freeze-thaw cycles. The successful operation of Qinghai-Tibet Railway has fully proved that active cooling measures such as thermosyphon， duct-ventilated embankments and crushed rock embankment can effectively maintain the stability of roadbed in perennial permafrost area. But the cooling effect of individual cooling techniques is limited in warm and ice-rich permafrost zones and wide roadbeds for highways； in these cases， stability requires composite roadbeds or new， more effective roadbed constructions. In the seasonal frozen soil area， the frost heave mechanics and engineering measures of roadbed are the emphasis of research. Three measures are usually used to prevent frost heave： soil replacement method， water proof and drainage， and heat insulation. On researching hot issues， permafrost experts and scholars have focused on the research of water and vapor migration mechanism of roadbed， frost heave prevention and control of high-speed rail roadbed， and new roadbed stabilization measures in permafrost region. New materials and technologies are constantly introduced into the research of frozen soil roadbed. Ground source heat pump technology， solar energy， etc. have been proved to be applied to the stability protection of roadbeds. Environmentally friendly materials such as ionic curing agent， microbial conditioning and fiber reinforced materials can be used as external admixtures to improve the freeze-thaw resistance of soil. In the future， with the integration of new generation technologies such as material science， BIM， artificial intelligence， new energy， interferometry synthetic aperture radar （InSAR） with mechanization， the stability reinforcing measures for permafrost roadbeds and the anti-freeze-thaw measures for seasonal permafrost roadbeds will be more environmentally friendly while improving the effect. The construction， management and monitoring of permafrost roadbeds will also continue to evolve towards digitalization and intelligence.

The headwaters of the Yellow River Basin （HYRB）， located in the northeastern part of the Qinghai-Xizang （Tibet） Plateau， serves as the main source of water and is highly sensitive to climate change. However， under the background of climate warming， understanding of shifts in precipitation types and the underlying causes remains limited. This study， focusing on this important scientific issue， utilized a parameterized model of wet-bulb temperature （a precipitation pattern recognition model using surface air temperature， surface pressure， relative humidity and elevation） to differentiate precipitation types across the HYRB from 1980 to 2015. Additionally， we analyzed changes in the annual mean precipitation， rainfall， snowfall and snowfall fraction during this period using the Mann-Kendall test and the Sen’ slope estimator. We especially focused on changes in snowfall fraction （SF， defined as snowfall/total precipitation） and analyzed spatial distribution of changes of SF. In order to reduce uncertainty in the differentiation of precipitation patterns by a single product， the analysis is based on weather station observations and multi-source high-resolution meteorological datasets， including the China Meteorological Forcing Dataset （CMFD）， the ECWMF ERA5-Land （ERA5-Land）， and the Multi-Source Weather （MSWX）. Further， we used the partial correlation analysis to conduct mechanism analyses of the underlying causes of long-term changes in SF in terms of both meteorological and circulation factors， including surface air temperature， relative humidity， precipitation， surface pressure， westerly winds， Indian monsoon， East Asian summer monsoon and ENSO. The results indicate that： （1） Annual mean SF exhibited significant （P<0.05） decreasing trends （0.002 a^-1）， because there was a decrease in snowfall， but rainfall increased significantly. The precipitation pattern shifted to rainfall. （2） Regionally， the percentage of grids with significant （P<0.05） decreasing trends in SF to the total grids of the HYRB was 98.31% for the ERA5-Land， 96.87% for the MSWX， and 67.62% for the CMFD. In particular， the west-central part of the HYRB exhibited a more rapid decline in SF， with Maduo （Madoi County） and Dari （Darlag County） experiencing the largest decreasing trends. （3） The three gridded datasets differed in their ability to capture the spatial variability of snowfall. Specifically， CMFD showed substantial spatial variation and presented well to spatial differences in trend of SF. MSWX was the second best， while ERA5-Land displayed a notable spatial homogeneity. （4） The annual mean SF was highly correlated with annual mean air temperature and precipitation （P<0.05）， with correlation coefficients r of -0.42 and -0.48. Moreover， westerlies also had a notable influence （r=-0.31， P=0.07）. Other factors had less effect on SF. These findings enhance our knowledge of the effects of climate warming on hydrometeorology. The identified trends and correlations offer theoretical support for the management of regional water resources in the Yellow River Basin and have important implications for water resources management across the HYRB.

In seasonally frozen ground region landslides are become a more common geological disaster， which has attracted widespread attention in the world. Whether the physical processes of snow ablation and soil freezing and thawing in seasonally frozen ground region， as opposed to the non-monsoon freezing zone， have an impact on landslides deserves further study. A giant loess landslide group （Galamput landslide group） occurred on May 9， 2002 in the Ili region of China provides an ideal case study. By using field survey， remote sensing image identification， meteorological data analysis and loess characteristic test， we attempt to explore the formation process and failure mode， and further reveal the instability mechanism of Galamput landslide group. The results show that the Garamput loess landslide group is composed of three landslides with a total volume of approximately 17.355 million m³. The formation and development of the landslide group was a multi-stage and multiple sliding failure process. The Galamput landslide was the coupling triggering result of early snowmelt and post rainstorm. The snowmelt infiltration and soil freeze-thaw cycle in spring played an important role in the evolution process of slope deformation. The rapid infiltration of extreme rainstorm was the ultimate triggering factor of the landslide. In addition， special slope structures and stratigraphic combinations provide a material structural basis for the occurrence of loess landslides. Combined with the slope deformation process we established a deformation failure model for loess slopes considering the effects of precipitation infiltration and freeze-thaw cycles， and proposed that the combination of static liquefaction on the slip surface and sliding liquefaction at the foot of the slope is an important mechanism inducing the occurrence of loess landslides. In the future， the risk of large-scale landslides in the Ten-zan’s seasonally frozen ground region is extremely high with climate warming. This study can provide a new perspective on the formation process and failure mechanism of loess landslides， and is of great significance for understanding the early warning and risk assessment of landslide disasters in seasonally frozen ground region.

Understanding the dynamics of glaciers is of paramount importance in the context of global climate change， as glaciers serve as sensitive indicators of environmental shifts. They are key components of the Earth’s freshwater reserves， influencing sea level， water resources， and the global climate system. The study of glaciers， therefore， extends beyond pure scientific inquiry； it has critical implications for predicting future water availability， assessing potential sea-level rise， and developing strategies for mitigating the impacts of climate change. Within this broader framework， glacier surface crevasses offer a window into the deeper processes at work within glaciers. These features are not merely physical anomalies but are indicative of the glacier’s internal and external dynamics. They provide insights into the stress and strain glaciers undergo as they move and deform， offering clues about the glacier’s velocity， the distribution of stresses within the ice， and the interaction between the glacier and its underlying bedrock. Moreover， crevasses influence the energy balance of a glacier’s surface by altering its albedo and affecting its meltwater dynamics， which in turn affects the glacier’s overall mass balance and movement. Thus， the detailed study of crevasses contributes significantly to our understanding of glacier mechanics and their response to climatic variations.This study focuses on the Yanong Glacier， located in the Kangri Karpo Mountain of the southeastern Qinghai-Xizang Plateau， an area noted for its complex terrain and significant glaciological interest. The deployment of Unmanned Aerial Vehicles （UAVs）， particularly the DJI M300 RTK UAV， has facilitated the acquisition of high-resolution orthophotos with a ground resolution of 0.03 m. This technological advancement enables the detailed mapping of glacier surface features， which is crucial for identifying and analyzing crevasse patterns and their distribution across the glacier’s surface.To address the challenges associated with crevasse detection， the study employs a sophisticated deep learning framework， marking a significant advancement over traditional analytical methods. The introduction of the Convolutional Block Attention Module （CBAM）-UNet model represents a novel approach in the field of remote sensing and glaciology. This model enhances the feature extraction capabilities of the conventional U-Net architecture by incorporating attention mechanisms that focus on relevant features for more accurate crevasse detection.The comparative analysis conducted in this study demonstrates the superiority of the CBAM-UNet model over established deep learning models such as U-Net， DeeplabV3+， PSPNet， and HRNet. Achieving a precision rate of 90.74% in identifying ice crevasses， the CBAM-UNet model proves to be exceptionally effective in the extraction of various crevasse types， including Transverse， Splaying， En Échelon， Marginal Crevasses， and Rifts. These crevasse types， indicative of the glacier’s dynamic behavior and influenced by the underlying topography， provide valuable information on the structural integrity and movement patterns of the glacier.The utilization of high-resolution UAV imagery in conjunction with advanced deep learning models offers a robust method for the detailed and accurate detection of glacier crevasses. This methodological approach not only enhances the precision of crevasse mapping but also facilitates the continuous monitoring of glacier transformations. Such advancements are instrumental in understanding the complex responses of glaciers to climate change， contributing essential knowledge to the fields of glaciology and climate science.Furthermore， this investigation sheds light on the potential applications of UAV technology and deep learning in glaciological research， highlighting the importance of interdisciplinary approaches in addressing environmental challenges. The findings of this study underscore the utility of combining high-resolution remote sensing data with machine learning techniques to improve the accuracy and efficiency of glacier monitoring efforts.In conclusion， the research presented herein exemplifies the significant contributions of technological innovations to the study of glacier dynamics. By enhancing our ability to accurately map and analyze glacier surface crevasses， this study offers valuable insights into glacier behavior， the impact of climate change on glacier systems， and the broader implications for water resources and sea-level rise. It is hoped that the methodologies and findings of this study will serve as a foundation for future research in glaciology， promoting further advancements in the understanding and preservation of these vital natural resources.

Noijin Kangsang Region is one of the primary distribution areas of extremely high-altitude glaciers in the mountainous region of southern Xizang （Tibet）. It is situated adjacent to the 349 national highway from Lhasa to Shigatse. The status and changes of glaciers in this Region are of wide concern. Assessing the glacier changes in the region is of great significance for guiding local glacier development， as well as for monitoring and protection. Based on the remote sensing images of the historical period， the glacier boundary of Noijin Kangsang Region from 1976 to 2022 was extracted by using the band ratio and visual interpretation method. The characteristics of glacier area， surface velocity and thickness change in Noijin Kangsang Region were analyzed as a whole， and three typical glaciers in the region were selected for detailed analysis. Combined with factors such as climate， topography and glacier surface albedo， the reasons for glacier changes are explained. The results show that： From 1976 to 2022， the glacier area in Noijin Kangsang Region decreased by （17.88±6.75） km²， it accounted for （17.63±6.70）% of the glacier area in 1976. There are significant differences in the number and area changes of glaciers of different sizes， and the topographic characteristics of glaciers also lead to the heterogeneity of glacier changes. From 2000 to 2019， the average thinning rate of glaciers in Noijin Kangsang Region was 0.26 m·a^-1. Glacier thinning was most prominent during 2000—2004. In recent years， the thinning amount and thinning range of regional glaciers have shown a downward trend. From 1988 to 2018， about 62% of the glacier-covered areas in Noijin Kangsang Region showed a deceleration trend. Within the region， eight glaciers have shown significant acceleration， with topography being the primary driving factor for glacier acceleration， while the increase in liquid precipitation at high altitudes may be a major contributing cause to the acceleration. From 1968 to 2022， the three typical glaciers all showed a state of retreat， but the retreat， thinning and surface velocity changes of typical glaciers in different periods had distinctive characteristics. The warming of Noijin Kangsang Region in the past 20~30 years is the main reason for the retreat of glaciers， and the topography affects the retreat， thinning and surface velocity changes of regional glaciers. Simultaneously， the reduction in glacier surface albedo is also one of the reasons driving glacier melting.

Global warming has triggered significant changes in the cryosphere， manifested in phenomena such as glacier retreat， snowmelt， and permafrost degradation. These transformations accelerate the conversion of solid water resources into liquid water， disrupting the long-term stability of water resource allocation in the Qinghai-Xizang Plateau’s cold regions. This paper takes the perspective of hydrological effects of cryosphere changes in cold regions， reviewing recent advancements in the understanding of hydrological processes under climate change in the Qinghai-Xizang Plateau. We analyze the current challenges and hotspots in hydrological research specific to the Qinghai-Xizang Plateau. Given that hydrological modeling is a crucial tool for studying the hydrological cycle， the structure and functionality of these models significantly influence the accuracy and direction of hydrological research. This paper summarizes the advantages and limitations of hydrological model algorithms for simulating glacier and snowmelt runoff in the plateau cold regions， and the characteristics of glacier， snow， and permafrost modules in 10 typical hydrological models. We also distill the main issues affecting the simulation accuracy of hydrological process models in this region. Our findings indicate that the limited availability of meteorological observation stations in the Qinghai-Xizang Plateau contributes to uncertainties in data input and parameter estimation. Moreover， a lack of comprehensive understanding of the intrinsic physical mechanisms governing hydrological processes in the cryosphere results in incomplete model structures， further impacting the simulation accuracy of these hydrological models. Finally， we discuss strategies for enhancing the accuracy of hydrological models through the integrated application of multivariate data and machine learning algorithms in cold regions.

The Arctic Monitoring and Assessment Programme （AMAP） Workgroup released a scientific assessment of “Mercury （Hg） in the Arctic” in 2021， which evaluated the contents and storages of Hg over Arctic environmental media and predicted the potential future changes of Hg contents in Arctic environment based on the observational and modelling studies of Hg in Arctic environmental media from recent years. The report stated that global atmospheric Hg emissions originated mainly outside the Arctic （>98%）， and some of which could be transported over long distances in the atmospheric circulation and deposited in Arctic ecosystems， where them participated in the biogeochemical cycling of Hg in the Arctic. The 2/3 of the Arctic atmospheric Hg was deposited to terrestrial environments and 1/3 to marine environments. Hg in terrestrial environments was mainly stored in soils， glaciers， and snow， and could be transported to the Arctic Ocean by riverine transport and coastal erosion. Hg could also be transported into the Arctic Ocean by ocean currents. Hg stored in the Arctic Ocean could be removed by escaping into the atmosphere， burying on the continental shelf and in deep-sea basins， and outflowing by ocean currents. The Arctic environmental Hg was predominantly in inorganic form and could be partially converted to methylmercury （MeHg） by microbial methylation processes in anaerobic environments. Reductions in primary emissions will have a greater impact on future changes of Hg contents in Arctic environment than climate change. And thus stringent and feasible global anthropogenic Hg reduction policies are needed to reduce the ambient Hg levels in the Arctic over the next 20 years. The report also noted that in the future， better quantification of local Hg releases from the Arctic， enhanced research and modelling of key environmental processes for Hg， studies of microbial communities carrying Hg methylation and demethylation genes， consistent projections of primary emissions and climate change， and global inventories of anthropogenic Hg emissions are needed to accurately assess Hg cycling in the Arctic environment and predict changes in Arctic environmental Hg levels.

Snow plays a critical role in surface radiation， energy， and water cycles and is often used as an important indicator for global change assessment and monitoring. In northern pastoral areas of China， the winter snow depth and snow cover are extensive， with prolonged snow layer maintenance. Excessive snowfall can have disastrous impacts on livestock production， while the meltwater from snow contributes to the improvement of the ecological and hydrological conditions. On the other hand， the speed of snowmelt is a crucial indicator for assessing the occurrence of snowmelt-induced floods. Therefore， snow accumulation and its melting process， along with the influencing factors， are not only focal points for various industries related to ecological and socioeconomic development， but they also have direct implications for disaster prevention and pattern recognition. Since 2020， meteorological departments in Inner Mongolia have successively established and applied a batch of field automatic snow depth observation instruments， enabling the continuous hourly observation of snow depth at multiple forest land stations. This provides a valuable opportunity for analyzing the dynamic changes of snowmelt in forest land. Based on the hourly data from field automatic snow depth observation stations in Hulun Buir forest region of Inner Mongolia， this study， through the analysis of multiple locations and multiple snowmelt processes， as well as the results of regional common feature analysis， explores high-frequency dynamic snowmelt processes and their influencing factors. This research serves as a direct basis for a more accurate understanding of the dynamic patterns of snowmelt in northern forest land and dynamic predictions. The results indicate： （1） Winter snow in Hulun Buir forest region can persist for about 102 to 155 days， generally entering the melting period in early March. The snowmelt process typically lasts for 5 to 18 days and can be divided into continuous and rapid melting stages. （2） When the snow depth is less than 3 cm， the ground snow cover rapidly enters the melting stage. If the average temperature between 10：00 and 20：00 is above 0 ℃， forest snow cover will completely melt within 36 hours. （3） Snowmelt exhibits a pattern of gradual decline followed by a rapid decline and then a slow decline during the day. Compared to grasslands， the peak snowmelt period is delayed and occurs between 10：00 and 15：00. Thermal conditions are the primary influencing factor for snowmelt in Hulun Buir forest region， and when studying snow cover as the affected factor， it was found that the ground temperature at 14：00 is the dominant factor affecting the snowmelt process and rate. （4） Although temperature and snow surface temperature are closely related to snowmelt， ground temperature emerges as the most sensitive factor influencing snowmelt response during the snowmelt process. Ground temperature at 0 cm， at 14：00 and 18：00， is the key factor determining or affecting the snowmelt process and rate in the northern forest land of China. Additionally， snowmelt is largely determined by thermal conditions.

The young glacial erosional and depositional landforms beyond the modern glaciers on the Qinghai-Xizang Plateau and its surroundings are direct imprints of the glacier fluctuation during the past several decades or century， and contain important palaeoclimatic and palaeoenvironmental information. Studies of these landforms could provide insights into the spatiotemporal variations of these ancient glaciers. Improved logistics and the development and application of the terrestrial in situ cosmogenic nuclide （TCN） ¹⁰Be surface exposure dating techniques， are making it to be possible to investigate the young glacial landforms in the Mount Geladandong area， which locates in the west segment of the Tanggula Mountains， central Qinghai-Xizang Plateau. Here we report on ¹⁰Be surface exposure dating of six samples collected from modern glacial landforms associated with the Gangjiaquba Glacier on the eastern slope of Mount Geladandong. Dating results demonstrate that the boulders ［samples from G19-02 to G19-06 and their ages are （125±15） a、（65±13） a、（86±13） a、（96±15） a、（104±15） a］were almost not affected by nuclide inheritance， and the ¹⁰Be surface exposure ages could be used to constrain glacier fluctuations during the past century in this high-altitude area. However， a comparison of the ages of a glacially polished surface ［sample of G19-01 and its age is （11 076±688） a］ and boulders indicates that subglacial erosion by abrasion of the rock surface was insufficient （<2 m） to remove cosmogenic nuclide inventories. Thus， the apparent exposure age on the polished surface includes inheritance and overestimates the true age of this surface. Our study suggests that a cautious sampling and interpretation strategy should be adopted with bedrock samples， and the ¹⁰Be surface exposure dating techniques have potential applications for dating glacier fluctuations on a 10¹-year time scale in these high-altitude areas with high ¹⁰Be production rates. Meanwhile， this study also provides a new reference for the application of ¹⁰Be exposure dating technique in dating the young landforms in high altitude areas.

In the water cycle， water bodies show different characteristics of stable hydrogen and oxygen isotopes （δ¹⁸O and δ²H） in different processes of evaporation， transport， convection， and condensation due to the influences of isotope fractionation. Therefore， δ¹⁸O and δ²H is widely used in the study of paleoclimate and modern hydrological processes. Previous studies mainly focused on the variations of precipitation stable isotopes in the low-altitude regions in the Lhasa River basin， a critical area for the studies of the progressing and evolution of monsoon and westerly wind systems. In contrast， studies on δ¹⁸O and δ²H data obtained from the alpine regions are largely lacking. In this study， we analyzed 347 event scale precipitation samples collected at three sampling sites in the Kuoqionggangri Glacier region from July 2020 to July 2023. The spatial and temporal variations of precipitation δ¹⁸O， the local meteoric water lines， the relationship between precipitation δ¹⁸O and meteorological factors， and the relationship between precipitation δ¹⁸O and convective activity are investigated to understand the influences of the Indian monsoon and westerly wind on the precipitation δ¹⁸O and δ²H in the Kuoqionggangri Glacier region at the source of the Lhasa River of the southern Qinghai-Xizang Plateau. Besides， the backward trajectory of water vapor was further demonstrated through correlation analysis and cluster analysis， so as to reveal sources of water vapor. The results showed that there was little difference in temperature， relative humidity， and precipitation among the three fixed points located in different altitudes in this study area from July 2020 to July 2023 （the glacier terminus （5 544.5 m a.s.l.）， the basin source （5 374.0 m a.s.l.） and the basin export （4 941.3 m a.s.l.））. In addition， the precipitation δ¹⁸O and local meteoric water lines were similar among these three sampling sites from July 2020 to August 2020. This suggested that the climate conditions remained relatively identical within the Kuoqionggangri glacier region. According to the above results， we put emphasis on data of the precipitation δ¹⁸O collected at the basin export from July 2020 to July 2023. The results revealed a two-stage pattern of changes in daily precipitation δ¹⁸O： a higher value before mid-June followed by a lower value. The monthly precipitation δ¹⁸O shows the highest value in June and the lowest value in September. The slope and intercept of the local meteoric water line during the monsoon period （8.12， 11.78） were obviously smaller than those during the non-monsoon period （8.79， 23.18）， indicating that the water vapor source of the precipitation during the monsoon period possessed a higher relative humidity compared with that during the non-monsoon period. The slope and intercept of the local meteoric water line around the year （8.27， 15.10） were more similar to those in the monsoon period. This phenomenon might be due to the large contribution of precipitation in the monsoon period around the year in this region. Monthly precipitation δ¹⁸O exhibited a significant dependence on temperature in the monsoon period. Specifically， the monthly precipitation δ¹⁸O and temperature are positively correlated. Daily precipitation δ¹⁸O were significantly dependent on precipitation amount around the year. Specifically， the daily precipitation δ¹⁸O and precipitation amount are negatively correlated. The convection activity taking place 1~6 days before the precipitation event would deplete the precipitation δ¹⁸O. This influence on the precipitation δ¹⁸O was mainly concentrated in the monsoon period. Results of the backward trajectory tracking analysis indicated that water vapor transported by the Indian monsoon contributed the most to the precipitation of the region throughout the year， which depleted the precipitation δ¹⁸O. This study preliminarily reveals the spatial and temporal variations of precipitation δ¹⁸O and its main influencing factors in the alpine mountains of the southern Qinghai-Xizang Plateau. Results of the current work can provide basic data for the study of water cycle in the alpine regions.

Climate change （CC） and land use/cover change （LUCC） have been identified as the two main drivers of global hydrological dynamics. Investigating the impact of these factors on watershed hydrological processes is of great significance in unraveling regional hydrological and environmental transformations. In this study， we focus on the Zamu River basin， a representative region in arid Northwest China， and adopt a comprehensive approach utilizing multi-source remote sensing images， hydrometeorological site monitoring， reanalysis product data， the Soil and Water Assessment Tool （SWAT） model， the Mann-Kendall （M-K） trend test， and land use dynamic degree analysis. By integrating these methods， we aim to provide a more accurate and comprehensive understanding of how CC and LUCC affect hydrological processes in the Zamu River basin. By isolating the driving factors of hydrological processes and considering the baseline period， as well as the separate and combined influence of CC and LUCC， we investigate the response characteristics and driving mechanisms of hydrological processes to these factors in the Zamu River basin. The research findings were as follows： （1） Over the period of 1980 to 2014， the annual precipitation， average temperature and runoff in the basin exhibited an upward trend， with increasing rates of 0.47 mm·a^-1， 0.067 °C·a^-1 and 1.43 mm·a^-1， respectively. （2） The distribution of land use types in the basin displays spatial heterogeneity， with grassland， woodland， and unused land being the predominant land uses. The comprehensive land-use dynamic degree was 2.91%， and construction land has the highest single land-use dynamic degree. （3） Aside from the single effect of LUCC， the runoff of the basin decreased by 0.12 mm， while the runoff of the single effect of CC and the combined effect of CC and LUCC increased by 6.27 mm and 6.15 mm， respectively. The evapotranspiration of each scenario showed an increasing trend. CC was identified as the primary driving force for watershed runoff and evapotranspiration. Management strategies for water resources， that enhance the adaptability of the basin to CC， were critical to promote the rational allocation of water resources in the upstream， midstream， and downstream of the basin， in the future.

The active layer， which is the primary area for permafrost and atmosphere to exchange heat and water， and its morphological changes have a significant impact on ecosystems， topography and geomorphology， surface and subsurface hydrological processes， carbon cycle， and safety of engineering structures in cold climates. In this paper， the spatial distribution characteristics of active layer thickness in the Three River Source Region （TRSR） and its future changes are studied based on the modified Stefan model， and the factors that may affect the variation of active layer thickness are discussed. The results show that the thickness of active layer has been increasing at a rate of 7.2 cm∙（10a）^-1 from 1981 to 2018， and will continue to increase in the future， most significantly in the central part of the TRSR. From 2006 to 2049， the active layer thickness increases at a rate of 4.3 cm∙（10a）^-1 （RCP6.0） to 6.8 cm∙（10a）^-1 （RCP8.5）； from 2050 to 2099， it increases at a rate of 0.04 cm∙（10a）^-1 （RCP2.6） to 4.8 cm∙（10a）^-1 （RCP8.5）， which is significantly less than the rate of increase in the previous 50 years. The rate of increase in active layer thickness has slowed down. Analysis of the factors influencing the variation of active layer thickness shows that the greatest influence is on mean annual air temperature， while the influence of annual precipitation is not significant， and NDVI has some influence on active layer thickness. This result will have an important impact on the water conservation， climate regulation， and ecological security of the TRSR.

Glacial lake outburst floods （GLOFs） are a unique type of natural hazard in the cryosphere that may result in catastrophic fatalities and damages. The Himalayas and Nyainqentanglha are second in the world regarding the frequency and severity of the GLOFs after the Peruvian Andes. Slope movements such as ice avalanches， landslides， and rockfalls have been blamed for most GLOF triggers. Despite the intuitive simplicity of the idea behind catastrophic erosional incision by a large wave， this explanation has many possible difficulties. The moraine-dammed lakes are shallow-long lakes， and the solitary displacement wave is the only type wave may be produced by massflows. The overtopping of the moraine dam may be only the first solitary displacement wave because the amplitude damping of the wave is more than 63% during two reflections if the losses of reflections were not considered. However， the erosion is usually a slow process on the hydrodynamic timescale that characterizes the passage of a displacement wave， it is not sufficient that erosion could occur during the relatively fast traversal of the dam. The erosion caused by a single wave was too small to breach the dam. However， it was far easier for a constant water flow to breach the dam by overflowing than for erosion to breach the dam by wave overtopping. A giant wave must be generated by a giant volume of ice avalanches or landslides entering a lake， and result a large water level increasing. The overflowing high water level was the reason for the breaching of moraine dams. Six moraine lakes， drained or undrained， were investigated in Xizang， China. The particle size of armor layers on the surface and the slope angle of these moraine dams and their spillway were measured. A series of laboratory experiments on armor initiated by overflow in the spillway of the moraine dam were conducted. The four statuses of moraine lake were simulated during the experiments. The moraine dam drained when the armor was removed by overflow. The initial model and the critical water depth of the moraine dam breaching were obtained. The initial armor models were the fluvial transport and bed failure models according to the bed slope range. The initial armor model was the fluvial transport model when the bed slope was less than 19.6°. The bed failure model occurred when the bed slope was over 25.2°. When the bed slope was in the range of 19.6°~25.2°， the initial model was a mixed regime. The depth of overflow on the armor and the gradient differences between the upstream and downstream of the knick point were the key parameters to initiate the armor in the fluvial transport model. The relative degree of exposure at the knick point was less and resulted in the first coarse particle initiated by the fluvial transport model occurring at the knick point. The larger the gradient difference between the upstream and downstream of the knick point， the smaller the relative degree of exposure value was. The ratio of the moraine dam’s critical water depth to the armor diameter was inversely proportional to the gradient differences between the upstream and downstream of the knick point in the fluvial transport model. For the bed failure model， the depth of overflow on the armor， the internal friction angle of saturated armor， the bed slope of armor， and the saturated density of the armor were the key parameters to initiate the armor. For the bed failure model of the armor initiation， the ratio of the moraine dam’s critical water depth to the armor’s diameter was a fixed value. The moraine dam breaching prediction model was validated reasonably well by the field data in Xizang， China， and British Columbia， Canada.

The Svalbard Archipelago is one of the most climate-sensitive areas in the world. Affected by the Arctic amplification effect， most of glaciers there have been undergoing significant shrinkage. Previous studies indicated that mass loss of glaciers in Svalbard accelerated in the past decades， but the ice mass loss caused by surge-type glaciers in the region remains unclear. Based on the high-precision observations from ICESat-2 laser altimetry， this study utilizes an improved classification method to investigate the elevation changes of the Svalbard’s glacier during the period from March 2019 to June 2022. The results show that， from 2019 to 2022， the elevation change of glaciers in the Svalbard shows a declining trend， with an average elevation change rate of （-0.94±0.23） m·a^-1， corresponding to a volume change rate of （-31.62±7.73） km³·a^-1. Among them， the surging glaciers occupy about 22% of the area， with a volume change rate of -13.23 km³·a^-1， accounting for 42% of the total volume change in the glacial area. Therefore， changes in surging glaciers are one of the main factors leading to the whole ice volume reduction in the region. As the largest surging glacier in the Svalbard， Storisstraumen Glacier has expanded its surge area by about 284 km² in the past 20 years， with a volume change rate of -5.67 km³·a^-1， accounting for 18% of the total ice volume loss in the area. Further analysis suggests that the increase in temperature may play a dominant role in triggering the surging of Storisstraumen glacier. This study not only reveals the elevation change characteristics of glaciers in Svalbard during the span from 2019 to 2022， but also quantifies the contribution from surge-type glaciers to the total ice mass loss in Svalbard， which may provide a reference for deep understanding the varying elevation change of glaciers in the region.

The evolution of the East Antarctic Ice Sheet can significantly affect global climate change since deglaciation could contribute much to sea-level dynamics. Thus， studying ice sheet history in this region is the key to understanding the Quaternary global and regional climate change. In recent years， in-situ Terrestrial Cosmic Nuclides （TCN） exposure dating has been gradually applied to the dating of glacial dynamics in the Larsemann Hills area. The data of Quaternary glacial chronology in this area can be employed further to understand the changes in the Antarctic Ice Sheet， and the dating results from this method currently require further refinement. This study summarized and homogenized 196 ¹⁰Be exposure dating data from 1997 to 2022 of the Larsemann Hills and adjacent areas. These areas include the Larsemann Hills， Vestfold Hills and Rauer Group， Prince Charles Mountains， and Grove Mountains. The sampling information such as sample type， altitude， latitude， elevation， shielding factors， thickness， erosion rate， density， and AMS results were also counted. Based on distinguishing erratic and bedrock samples， we applied the newest model to all of the sample data and recalculated them. Meanwhile， the onset of biogenic sedimentation in the Larsemann Hills has been recorded with bedrock exposure data for further discussion. The results showed that the minimum exposure age of the Larsemann Hills was （4.05±0.81） ka， and the maximum exposure age was （147.01±11.80） ka. The minimum age of exposure in its adjacent areas ranged from （0.32±0.20） ka to （4 096±2 404） ka. The earliest date reaches the mid-Pleistocene， specifically MIS Gi24， spanning the entire Quaternary period. Among all the samples discussed， 17.86% have an exposure age of less than 11 ka， 83.16% have an exposure age of less than 600 ka， and 98.47% have an exposure age of less than 2.8 Ma. We divided the chronology into the Holocene （approximately 11 ka， MIS 1）， the mid to late Pleistocene （approximately 11 ka to 600 ka， MIS 1 to MIS 15）， and the early Pleistocene to late Pliocene （600 ka to 4 000 ka， MIS 15 to MIS Gi24）. We reviewed and summarized the glacial evolution history of the Larsemann Hills and adjacent areas over these periods. For the samples from the Larsemann Hills， we conducted a detailed discussion on the impact of erosion rates. We recalculated the exposure ages of the samples using erosion rates of 0 mm·a^-1， 0.0007 mm·a^-1， and 0.0015 mm·a^-1 （modern erosion rates）. The results showed that erosion rates lead to a significant overestimation of exposure ages， and using modern erosion rates for correction resulted in model saturation. Finally， we discussed the relationship between exposure age and altitude by region. There was a clear pattern in the Prince Charles Mountains and Grove Mountains （alpine setting） but in the Larsemann Hills， Vestfold Hills， and Rauer Group （coastal setting）， glaciers primarily retreated horizontally， showing no obvious pattern. We compared the multi-source homogenized data from different regions， and the following are reached： （1） 17.86% of the samples have exposure ages less than 11 ka， 83.16% of the samples have exposure ages less than 600 ka， and 98.47% of the samples have exposure ages less than 2.8 Ma. In some regions， there are still controversies regarding the ice retreat time determined by ¹⁰Be exposure dating. （2） The resultant increase amounts to 51.57% when the erosion rate reaches 0.007 mm·a^-1. When calculating exposure ages， it is important to consider reasonable erosion rates. （3） The exposure age tends to decrease with decreasing altitude. However， in low-altitude coastal areas， this trend may be offset by various factors， which require further research to explain. Future dating work in this area should be further promoted， and attention should be paid to erosion rate selection.

The Arctic region is recognized as one of the most climate-sensitive areas， with tundra ecosystems playing a vital role within the Arctic ecosystem. This study employed the ecological niche model named MaxEnt. Utilizing species occurrence data and environmental information， we modeled the current （1970—2000） potential distributions of six dominant tundra species in Alaska and projected their changes under different scenarios （SSP1-2.6， SSP2-4.5， SSP3-7.0， and SSP5-8.5） for the period 2021—2040. The primary factors determining species distribution were identified based on their contribution rates. The results indicate that temperature is the most important environmental factor affecting species distribution， with spatial heterogeneity observed in the changes in suitable habitats for dominant species. Compared to the current climate， the dominant shrub species， Arctous alpina， have shown a decrease in their distribution area. In contrast， the dominant lichen species， Cladina rangiferina， and the dominant sedge species， Eriophorum vaginatum， have exhibited an overall increase in their distribution areas. Under the low radiative forcing scenario （SSP1-2.6）， the suitable habitat areas for Arctous alpina and the creeping dwarf shrub species， such as Dryas integrifolia， have expanded. However， in scenarios with medium， medium-high， and high radiative forcing， which exacerbate global warming， the suitable habitat areas have decreased. Regarding the semi-creeping dwarf shrub species， including Cassiope tetragona， and the dominant moss species， Hylocomium splendens， their suitable habitat areas displayed irregular changes across different climate scenarios. However， it was consistently observed that the low-suitability habitat areas decreased， with a tendency to shift towards moderate to high-suitability regions. Simultaneously， dominant species are shifting towards higher latitudes and elevations.

Glaciers are transformed from snowflakes formed by the condensation of atmospheric water vapor at low temperatures. In general， the transformation of snowflakes to glaciers contains three processes. To begin with， the snowflakes falling on the surface of glaciers are automatically rounded and transformed into firn because a system is more stable when its surface free energy is lower. The subsequent step is firn densification， a lengthy and challenging process that turns firn into glacier ice. During firn densification， firn density increases with depth and time due largely to overburden stress from the accumulation of new snow. Finally， glacier ice flows and progressively converts into glaciers under the force of gravity. Firn densification is a highly complicated process since several physical mechanisms operate simultaneously during densification and dominant mechanisms differ at different stages. Understanding the evolution of density and the physics of firn densification is essential for several applications of glaciology. A firn densification model that can simulate the density evolution of firn is crucial for assessing glacier mass balance accurately via the satellite altimetry method. In this method， the differencing of digital elevation models provides a change in glacier volume， which needs to be converted to a mass change by a density model or assumption. The paleoclimate reconstruction of the ice core requires calculating the age difference between the ice and the air trapped in it. A firn densification model is necessary to determine the age of the ice when the bubbles are close-off， which can be coupled to a firn-air model to calculate the age difference. This paper comprehensively analyzes the research methodology and the latest progress on firn densification in polar ice sheets. Numerous firn densification models have been proposed in recent years. These models are categorized as either empirical models （including semi-empirical models） or physical models. Empirical models are often based upon a steady-state assumption. They are formulated as a function of temperature， accumulation rate （which serves as a proxy for stress）， and several tuning parameters. The temperature sensitivity has been improved by taking the effects of seasonal and interannual temperature variations into account. More recently， the impact of surface meltwater on firn densification rates， including meltwater percolation， retention， and refreezing， has been added into firn densification models. Physical models are built upon physical principles by analyzing the change in grain microstructure and its underlying physical mechanism during firn densification. These models were formulated by microscopic parameters （for example， grain radius， bond radius， and viscosity）. Physical models are currently scarce since the physics of firn densification is not fully understood， and the data needed to develop a purely physical model are still lacking. Up to now， the snow-firn transition is based on the theory describing grain-boundary sliding； the firn-ice transition is based on the theory explaining the pressure sintering of spherical powders. Overall， the study of firn densification in polar ice sheets has made great strides over the past few decades. On a macroscopic scale， the growth and deformation of grains are mainly affected by their microstructure. Both empirical and physical models are unsatisfactory because previous studies on firn densification have not yet fully clarified the microstructure of firn and its connection to the macroscopic process. For the empirical models， the theory of wet firn densification is still incomplete. And the applicability of empirical models is limited due to the neglect of the specific physical mechanisms. In addition， it may fail to generalize the steady-state assumption directly to transient scenarios. The physical models employed today are mainly based on idealized assumptions， which may be speculative and unreliable because the physics of firn densification is still uncertain.

The warming of the Qinghai-Xizang Plateau has led to glacier retreat， permafrost melting， and an increase of meteorological and derived disasters， capturing widespread attention across society. In recent years， the warming of the Qinghai-Xizang Plateau has intensified further. In 2022， the summer was the warmest since 1961， with the average summer maximum temperature （T_max） and minimum temperature （T_min） in the central and eastern Qinghai-Xizang Plateau being 2.37 ℃ and 2.51 ℃ higher than that during the period of 1961—1990. The attribution technique， combining model evaluation and reconstruction， was employed to detect and analyze the anthropogenic influence on the extreme temperature events of the summer 2022 over the Qinghai-Xizang Plateau， utilizing CMIP6 model simulation data. The results indicated that greenhouse gases emissions from human activities significantly heightened the probability of maximum temperature extreme events during the summer 2022 over the Qinghai-Xizang Plateau. The probability of extreme T_max events occurring with and without the influence of human activities was 3.67% and 0.012%， respectively. The contribution of human activities to extreme T_max events in summer 2022 was estimated to be 1.26 ℃ （90% CI： 0.86~1.68 ℃）. The probability of extreme T_min events occurring with and without human activities is 23.5% and 0， respectively. The contribution of human activities to extreme T_min events in summer 2022 was estimated to be 2.35 ℃ （90% CI： 1.89~2.81 ℃）. The CMIP6 model underestimated the observed temperature changes over the Qinghai-Xizang Plateau. The simulation deviation of the model is calibrated based on the attribution constraint method， and the projected summer maximum and minimum temperature over the Qinghai-Xizang Plateau are expected to continue to increase in the future under the medium emission SSP2-4.5 scenario of shared socioeconomic path. The risk of extreme T_max and T_min events similar to those in 2022 occurring on the Qinghai-Xizang Plateau in the future is increasing.

Based on the temperature and precipitation observation daily data of 99 meteorological stations in Xinjiang from 1961 to 2020， the characteristics of regional strong cold air and cold wave in Xinjiang were analyzed by using correlation analysis and linear trend analysis， as well as the dry and wet conditions of strong cold air and cold wave in Xinjiang were recognized using the precipitation data. The results showed that： （1） The frequency of regional strong cold air and cold wave in Xinjiang showed a decreasing trend， which was mainly manifested in the decrease of the frequency of strong cold air and cold wave in autumn， especially in 2010s. （2） The occurrence frequency of cold wave in Xinjiang was relatively close during the three months of winter. In spring and autumn the cold wave occurred most in November， followed by March and April. The occurrence time of super strong cold wave mainly concentrated in December and January， and the frequency of strong cold wave was the highest in February. （3） During the cold wave in Xinjiang， the minimum temperature increased and the cooling amplitude decreased， respectively， and both the mean and maximum precipitation increased significantly since the 1990s. Meanwhile， the cooling amplitude of the regional cold wave in Xinjiang in winter was about 1 ℃ larger than that in spring and autumn. （4） The minimum temperature and the maximum precipitation during cold wave process occurred in the Altai Mountains and Tianshan Mountains. In spring and autumn the cold wave in Xinjiang was usually normal or dry process， while in winter 76.4% processes were normal dry， and 85.7% of the wet and wet processes were concentrated in the 1990s. The preliminary identification of the dry and wet conditions of the cold wave was helpful to understand the new climate characteristics of the cold wave in Xinjiang more comprehensively and serve for disaster prevention and mitigation. （5） In winter， most stations in Northern Xinjiang and Tianshan Mountains reached the cold wave standard in 72 hours， while in Southern Xinjiang， most stations reached the cold wave standard in 24 hours.

In recent years， typical landslide-mudflow disaster chain events induced by strong earthquakes and extreme weather in loess areas have become more frequent. Compared with single disasters， chain geological disasters have stronger concealment， wider spread， higher damage degree and more serious losses. Therefore， the research on the prevention and control of chain geological disasters has always been a hot and difficult point in disaster prevention and reduction. At 23：59 on December 18， 2023， an M_s 6.2 magnitude earthquake struck Jishishan County， Linxia Prefecture， Gansu province， at a depth of 10 km， killing 151 people. The strong earthquake triggered a landslide-mudflow chain disaster in Caotan Village and Jintian Village， Zhongchuan Town， Minhe County， Qinghai Province， resulting in a total of 20 deaths， the disaster chain fatality rate accounted for 13.5% of the total number of earthquake fatalities. After the disaster， a comprehensive and systematic study on the landslide-mudflow disaster chain was carried out by means of remote sensing image processing and interpretation， literature sorting and screening， UAV photographic aerial survey， detailed field survey and visit， and on-site sampling and analysis testing， so as to recover and reappear the start-slide-flow-accumulation process of the landslide-mudflow disaster chain. This paper discusses and puts forward nine major coupling and disaster-causing effects such as surface freezing blocking water retention in the slip source area， gully leveling backfill water retention in the slip source area， platform irrigation seepage filling effect in the slip source area， vibration liquefaction screening effect in the slip source area， growth rate of the funnel closure in the slip source area， soil differential flow sorting effect in the flow area， collapse recharge effect in the flow area， acceleration effect of ice filling water at the bottom of the flow area， and upstream seepage recharge and range extension effect in the accumulation area. The Zhongchuan landslide-mudflow chain disaster caused by the M_s 6.2 earthquake in Jishishan， Gansu Province is a typical secondary geological disaster of the same earthquake， which is transformed into a disaster by the coupling and superposition of multiple disasters such as earthquake， landslide and mudflow， and its impact and effect are much greater than that of a single disaster， and it has the comprehensive characteristics of suddenness， high speed， concealment， confusion， destruction and remoteness. The Zhongchuan coseismic landslide-mudflow chain disaster with nine linkage coupling disaster-causing effects is obviously different from the traditional geological disasters such as landslides and debris flows， and the transformation of disasters and disaster-causing factors are complex and unique. In the process of promoting the construction of beautiful villages and the Belt and Road， the relevant land use development and engineering construction planning must fully consider the risks of regional landslides， debris flows， mountain floods and their coupling disasters， scientifically and rationally lay out land and engineering planning and design， ensure the flooding and silting of valleys， and reserve safe transition areas， so as to prevent disasters and avoid damage to the greatest extent. Long-term and large-scale agricultural irrigation is the most important source of recharge for the loess layer with large thickness and high water content to saturation in the gentle slope area of the high terraces of the Yellow River， and chain disasters occur under the action of strong earthquakes. Therefore， under the condition of ensuring water for agricultural production， strengthening the drainage of the slope zone in the irrigation area， optimizing the irrigation method， and lowering the groundwater level are effective measures to prevent the occurrence of similar landslides and chain disasters and ensure the safety of the geological environment in the loess gentle slope plateau area. The research can provide a scientific reference for the formation mechanism and prevention and control of chain geological hazards.

Lake ice phenology is the seasonal change of lake freezing， melting and other phenomena， which plays an important role in indicating regional climate change. This article is based on Google Earth Engine （GEE）， using 250 m spatial resolution MODIS surface reflectance products MOD09GQ and MYD09GQ， and Landsat series remote sensing data to analyze the lake conditions of 10 large lakes （area greater than 200 km²） on the Mongolian Plateau from 2000 to 2021. Ice phenology changes were studied， and their correlation with changes in temperature， precipitation， and Mongolian high pressure was analyzed using meteorological data. The results show that： （1） All lakes begin to freeze from November to mid-to-early December， and are completely frozen from mid-November to late December， entering the lake freeze period； they begin to melt in late April of the following year， and all lakes are completely frozen by the end of May. After thawing， the average lake freeze period for the 10 lakes is 151 days. （2） The overall phenology of lake ice in the study area shows the trend of delayed freezing date， advanced melting date， complete lake freezing period， and shortened lake ice existence period. The specific performance is that the average change rate between the day of initial freezing and the day of complete freezing is 1.88 d·（10a）^-1 and 1.91 d·（10a）^-1， respectively； the average rate of change on the day of initial thawing and complete thawing is -3.45 d·（10a）^-1 and -3.41 d·（10a）^-1； the average change rates of the lake ice existence period and complete freezing period are -5.32 d·（10a）^-1 and -5.37 d·（10a）^-1，respectively. （3） Climate change will affect the phenological changes of lake ice in the study area， and temperature is the key factor affecting the phenological changes of lake ice. Rising temperatures lead to a delay in the freeze-up start date （FUS） of lake ice， an advance in the break-up start date （BUS）， and a shortening of the complete freezing duration （CFD）. At the same time， the phenological properties of lake ice in some lakes will be affected by the Mongolian high pressure in winter， which will bring the cold air will cause the lake ice break-up duration （BUD）， lake ice cover duration （ICD）， and complete freezing duration （CFD） to increase.

Surface energy balance is an important part of the land-atmosphere interaction， which is of great significance for the study of energy exchange， water cycle， climate change and biodiversity. The Qinghai Lake watershed is an important barrier for the ecological security of the Qinghai-Xizang Plateau， and the swamp wetland is the main ecosystem type in the basin. However， there has been little research on the energy balance of swamp wetlands in the Qinghai Lake watershed. Based on this， this study analyzed the variation characteristics of surface energy balance of alpine swamp wetland in Qinghai Lake watershed by using the observed data obtained from the Wayanshan site in 2019. The results show that the surface radiation flux of the swamp wetland at the Wayanshan site has seasonal variation characteristics， and the downward and upward shortwave radiation values are highest in spring and lowest in winter. The net radiation， upward and downward longwave radiation fluxes are the largest in summer， followed by spring and autumn， and the smallest in winter. The net radiation is mainly consumed by latent heat flux and sensible heat flux， accounting for 60.6% and 35.3% of the annual effective energy， respectively. The effective energy is mainly consumed by latent heat flux in summer and autumn， and by sensible heat flux in winter and spring. Compared with other underlying surfaces of the Qinghai-Xizang Plateau， the surface latent heat flux consumes a larger proportion （>75%） of the effective energy in the swamp wetland in summer and autumn. The annual surface energy closure rate of swamp wetlands was 0.69， and the closure rates during the freezing and non-freezing periods were 0.51 and 0.74， respectively.

In the context of climate change and intensive human activities， the water environment problem of watershed is still one of the severe challenges faced by watersheds management in China and abroad. The Taohe River basin is a typical alpine ecologically fragile basin in China， and the study of changes in water environment elements and their driving mechanisms in Taohe River basin is of great significance to the management of water environment in Taohe River basin. In this paper， the characteristics of precipitation and temperature change trends and mutation features in the Taohe River basin during the period 1990—2018 were analyzed by statistics， linear fitting and M-K trend and mutation tests. The land use transfer matrix was used to analyze the land use change characteristics of the Taohe River basin in 1990 and 2018， and the hydrological and meteorological dynamic characteristics of the Taohe River basin were revealed. On this basis， the SWAT hydrological model database was constructed by DEM， land use， soil and meteorological data， and the monthly scale simulation of runoff and water quality in the Taohe River basin was carried out. The model divided the Taohe River basin into 24 sub-basins. The meteorological data of temperature， precipitation， relative humidity， wind speed and solar radiation were input， and the weather generator was constructed by SWAT-Weather. The runoff simulation period was 1988—2018， and 1988—1989 was set as the preheating period. Due to the limited measured data， the DO simulation period is 2015—2018， and the NH₃-N simulation period is 2018. The simulation calibration and verification were carried out by using the SUFI-2 calibration method in SWAT-CUP， and the R²， NSE and PBIAS indexes were selected to evaluate the simulation accuracy of the model. In order to improve the accuracy of the simulation， 22 runoff-related parameters and 37 water quality-related parameters were selected. Based on the simulation results of SWAT model， the temporal and spatial variation trend of runoff in Taohe River basin is analyzed by using water yield index and Slope trend. Finally， by setting different input conditions of precipitation， temperature and land use type， the scenario simulation was carried out for climate change， land use change and comprehensive change of climate and land use， and the driving mechanism of runoff and water quality in Taohe River basin is analyzed based on the scenario simulation results. The results show that： （1） During the past 30 years in the Taohe River basin， The interannual variation of precipitation fluctuates greatly， and the overall trend is upward， with a linear trend of 20.16 mm⋅（10a）^-1； There is no significant mutation in temperature， and the overall trend is upward， with a linear trend of 0.55 °C⋅（10a）^-1. The land use types in the Taohe River basin are mainly agricultural land， grassland and forest land. All land use types have changed， but the area changed slightly. （2） The SWAT model has good applicability to simulate long-term monthly runoff in the Taohe River basin； the R² and NSE are generally above 0.6， and the absolute value of PBIAS remains within 15% The accuracy of monthly scale short-term simulation of DO is relatively high， and the accuracy of monthly scale short-term simulation of NH₃-N is slightly lower， but the results in the middle and lower reaches meet the simulation accuracy requirements. The water yield in the upper reaches of the Taohe River basin is the highest， and the trend of increase is larger. The water yield in the middle and lower reaches is negatively correlated with the trend of increase in water yield. （3） Runoff is positively correlated with and controlled by precipitation， but negatively correlated with temperature. The runoff yield of each land use is agricultural land > grassland > forest land. The concentration of NH₃-N is negatively correlated and controlled by temperature， but positively correlated with precipitation. The conversion of agricultural land to forest land and agricultural land to grassland significantly reduce the concentration of NH₃-N. The concentration of DO is negatively related to temperature. and is almost unaffected by the other factors.

As a sensitive region to global climate change， the climate of the Tibetan Plateau has gradually changed to a warm and humid state in recent decades， and this change and the resulting permafrost changes have directly affected the hydrothermal conditions for vegetation growth. The normalized difference vegetation index （NDVI） is an important variable to characterize the growth of vegetation， and its time-series variation can well reflect the response of vegetation to natural factors. In order to more accurately characterize the impact of climate change on vegetation growth in the permafrost areas of the Qinghai-Tibet Plateau， this study selected the source of the Tuotuo River， where permafrost is relatively continuous， as the study area. Based on Landsat NDVI data， trend analysis， partial correlation analysis， and geographic detectors were used to analyze the response characteristics of NDVI in the vegetation growing season （May-September） in the study area from 2000—2021 to climate change and different terrains and vegetation types. The results show that： （1） NDVI in the growing season in the source area of the Tuotuo River showed an overall fluctuating growth trend during 2000—2021， with a growth rate of 0.013 （10a）^-1， of which the NDVI growth rate was faster during the period of 2000—2010 ［0.019 （10a）^-1］， and then slowed down to half of the growth rate of NDVI during the period of 2011—2021 ［0.011 （10a）^-1］. The interannual changes of NDVI in different vegetation types were analyzed， and it was found that the better the vegetation development， the faster the growth rate of NDVI， among which the fastest growth rate was found in alpine swamp meadow ［0.018 （10a）^-1］ and alpine meadow ［0.017 （10a）^-1］， followed by alpine grassland ［0.015 （10a）^-1］， and the slowest growth rate of NDVI was found in alpine desert grassland ［0.009 （10a）^-1］. The analysis of the inter-annual changes of NDVI in different terrain areas showed that the growth rate of NDVI increased and then decreased with the elevation， and the growth rate was faster between 4 700~5 300 m ［>0.02 （10a）^-1］；The growth rate of NDVI showed a trend of increasing first and then decreasing with the change of slope， and the fastest growth rate ［0.023 （10a）^-1］ was found in the gentle slope area with a slope of 2°~6°； the growth rate of NDVI decreased with the increase of the thickness of the active layer of permafrost， and the fastest growth rate ［0.029 （10a）^-1］ was found when the thickness of the active layer was less than 150 centimeters. （2） On the spatial scale， the areas with an increasing trend of NDVI in the growing season in the source area of the Tuotuo River during the period of 2000—2021 accounted for a total of 82.1% of the total area of the study area， and the area with a highly significant increasing trend accounted for 27.0%， which was mainly distributed on both sides of the river at lower elevations and in the areas near the glacier； and the areas with decreasing trend of NDVI accounted for 16.0%， which was mainly distributed in the northern part of the study area in the alpine desert grassland areas in the northern part of the study area. （3） From 2000—2021， the source area of the Tuotuo River showed an overall trend of warming and humidification， and precipitation， air temperature， solar radiation and soil water content all showed fluctuating upward trends in the growing season. 2000—2021 NDVI changes in the source area of the Tuotuo River in the growing season were most significantly affected by soil water content， and warmer temperatures would prompt the melting of the cryosphere and increase soil water content， which would improve the growth status of the vegetation； NDVI changes in the growing season showed the same trend as precipitation； NDVI changes in the growing season showed the same trend as precipitation. NDVI changes in the growing season were positively correlated with precipitation； the correlation between NDVI changes in the growing season and air temperature varied widely in space， with 55.4% of the regions showing a positive correlation and 43.8% showing a negative correlation； and NDVI changes in the growing season were negatively correlated with the solar radiation as a whole. Increased precipitation in the growing season in the source area of the Tuotuo River promoted vegetation growth in the meadow area more than in the grassland area； changes in air temperature promoted vegetation growth in the meadow area more than in the grassland area， and inhibited vegetation growth in the grassland area more than in the grassland area. （4） The spatial differentiation of NDVI in the study area is mainly influenced by soil water content， climate factors and slope， and the influence is greatest when soil water content and slope interact. This paper quantifies the effects of climatic factors and their interactions on vegetation changes using various methods through the study of NDVI changes in the source area of the Yangtze River， which further reveals the influence mechanism of regional climatic and environmental factors on NDVI changes， and provides a new basis for the study of vegetation changes and ecological environmental protection in the Tibetan Plateau region.

As an important part of the cryosphere， under the background of global warming， this paper studies the freeze-up dates of major rivers in Heilongjiang Province， so as to provide a scientific basis for disaster prevention and mitigation. Based on the observation data of the freeze-up dates of the hydrological observation stations in Heilongjiang Province from 1962 to 2020， this paper used the Mann-Kendall mutation test and linear trend analysis method to explore the characteristics of the river freeze-up dates of Heihe Station of Heilongjiang River， Harbin Station of Songhua River， Jiangqiao Station of Nenjiang River and Raohe Station of Wusuli River with the influence of meteorological factors. The freeze-up date， average temperature， surface temperature， minimum temperature， average wind speed and average sunshine hours were analyzed， and the freeze-up dates of Heihe Station， Harbin Station， Jiangqiao Station and Raohe Station were simulated and predicted by information diffusion theory and multiple linear regression analysis method. The results showed that： （1） From 1962 to 2020， the average freeze-up date of Harbin Station， Jiangqiao Station， Heihe Station and Raohe Station was between November 12 and November 22. The results of Mann-Kendall mutation test showed that from 1962 to 2020， Harbin Station， Jiangqiao Station， Heihe Station and Raohe Station all had mutation dates， and the mutation years were 1970， 2005， 2000 and 2012， respectively. Over the past 59 years， the freeze-up dates of Jiangqiao Station and Heihe Station have been significantly postponed （P<0.05）， with a change rate of 2.46 d·（10a）^-1， 1.35 d·（10a）^-1， which was postponed by 15 d and 8 d， respectively. （2） The results of correlation analysis show that the average temperature， surface air temperature and minimum temperature are the key factors affecting the freeze-up date of Heihe Station， Harbin Station， Jiangqiao Station and Raohe Station. Specifically， the freeze-up dates of Jiangqiao Station and Heihe Station in relatively high latitude areas are mainly affected by the average temperature， surface temperature and minimum temperature in early November， while the Harbin Station and Raohe Station are mainly affected by the average temperature， surface temperature and minimum temperature in mid-November. （3） According to the information diffusion theory， when the negative accumulated temperature is -180 °C， the probability of river freeze-up at Heihe Station， Harbin Station， Jiangqiao Station and Raohe Station reaches 80%~90%， and when the negative accumulated temperature reaches -240 °C， the rivers of Heihe Station， Harbin Station， Jiangqiao Station and Raohe Station are basically frozen. （4） Based on the key factors such as mean temperature， surface air temperature and minimum temperature， this paper uses multiple linear stepwise regression analysis to simulate and predict the freeze-up dates of Harbin Station， Jiangqiao Station， Heihe Station and Raohe Station. The forecast accuracy of the constructed multiple linear regression model for river freeze-up forecast is more than 80%. It has a good effect on predicting the freeze-up date of Harbin Station， Jiangqiao Station， Heihe Station and Raohe Station， which provides a scientific basis for disaster prevention and mitigation in this area.

In recent decades， with the global warming and the enhancement of human activities， the trend of permafrost degradation is significant. This process changes the hydrogeological conditions of the cold region， thus causing a series of ecological environment changes. Thermokarst lakes are the product of permafrost degradation and active thermokarst lakes indicate the decrease of permafrost stability. Thermokarst lakes are also a major source of greenhouse gases， which are important in the carbon cycle in cold regions. The formation and development of thermokarst lakes will cause the change of frozen soil environment， which will affect the global climate change. Therefore， in view of the increasingly serious thermokarst phenomenon in the process of permafrost degradation， and the resulting problems such as permafrost thawing penetration， groundwater level change， thermokarst lake expansion and so on， the current research status of the hydrology change of thermokarst lake in permafrost area is analyzed and sorted out. This paper mainly discusses from the following five aspects： （1） Analysis of the main factors of the formation and evolution of the thermokarst lake； （2） Analysis of temporal and spatial variation of thermokarst lake hydrological process and its influencing factors； （3） Thermokarst lake water balance process and influencing factors； （4） Influence of thermokarst lake changes on regional water quality； （5） Influence of thermokarst lake on carbon cycle. Finally， the main problems in the field of thermokarst lakes are discussed： there are some defects in the identification of thermokarst lakes； the factors related to the area change of thermokarst lake are single. There is still a gap in understanding the broader relationship between permafrost gradient， permafrost degradation， and the corresponding hydrological response of thermokarst lakes. Knowledge of the effects of permafrost degradation on lake water chemistry is limited. Based on the existing problems， it is proposed that isotope technology should be used to fully consider the surrounding environment of the pond in the later research， and multi-factor analysis should be carried out in combination with climate change and permafrost degradation， in order to provide reference for further research on the frozen soil hydrological process， regional water resources evolution and the impact on the ecological environment under the background of permafrost degradation.

In the boreal permafrost region， forest fires not only affect the soil properties of forest ecosystems， but also the permafrost environment， soil organic carbon （SOC） and total nitrogen （TN） contents and storages. The permafrost region in Northeast China is located at the southern margin of Eurasia permafrost zone， which is undergoing extensive degradation under the influence of climate change and human activities. This affects carbon emissions， carbon and nitrogen storages in permafrost region， creating a positive feedback effect on climate warming. In this study， we selected the burned area in 2009 in Alongshan， northern Da Xing’anling Mountains， and the unburned site as a control to study the effects of different fire severity （light and severe burn） on the SOC and TN contents and storages in the permafrost region. The results showed that： （1） SOC and TN contents and storages varied significantly at different fire severities sites， and gradually decreased with increasing fire severity. Compared with the unburned site， SOC contents decreased by 9.78% and 65.11%， respectively； SOC stocks decreased by 9.29% and 68.48%， respectively； TN contents decreased by 1.99% and 52.49%， respectively； and TN stocks decreased by 3.23% and 51.61% at the light and severe burned sites， respectively. With the increase of soil depth， SOC and TN content gradually decreased； SOC storages showed a fluctuation pattern at burned site， increased first and then decreased at light burned site， and gradually decreased at severe burned site； TN storages showed a fluctuation pattern at unburned and light burned sites， and gradually decreased at severe burned site. （2） Soil temperature increased gradually with increasing fire severity. At depths of 0~100 cm， compared with the unburned sites， soil temperatures increased by （0.87±0.18） ℃ and （9.09±0.37） ℃ at light and severe burned sites， respectively； soil moisture contents （SMC） increased by （17.79±3.36）% at light burned site and decreased by （16.71±2.92）% at the severe burned site. Soil temperature and SMC decreased with increasing soil depth. （3） Redundancy analysis （RDA） showed that soil microbial biomass nitrogen （MBN） was the key factor affecting post-fire soil carbon and nitrogen contents and storages， with an explanatory rate of 65.6% （P=0.002）. SOC and TN contents were significantly positively correlated with soil temperature， SMC， NH₄⁺-N， microbial biomass carbon （MBC） and MBN， and significantly negatively correlated with fire severity， soil depth， and pH. SOC and TN storages were significantly negatively correlated with fire severity， soil depth， soil temperature， soil bulk density， and NO₃^--N. In summary， forest fire has a significant effect on SOC and TN storages， resulting in the loss of SOC and TN storages， altering the distribution pattern of carbon and nitrogen pools， and reducing the stability of soil carbon and nitrogen pools. The study of forest fires on SOC and TN contents and storages is of great significance to the ecosystem carbon balance and the management of ecological environment in the cold region， and it can provide important data references for the SOC and TN storages in the boreal permafrost region.

In order to reveal the influence of the initial stress state on the dynamic characteristics of frozen clay under the condition of principal stress shaft rotation， a circular stress path of pure principal stress rotation was realized by using the frozen hollow cylindrical apparatus（FHCA）， and a series of hollow torsional shear tests in laboratory were carried out on the basis of the circular stress path， and the effects of the initial stress state on the cumulative plastic strain， stress-strain hysteresis loop and dynamic modulus of frozen clay were studied. The results show that the greater the initial stress of the specimen under the condition of pure principal stress rotation， the faster the cumulative plastic strain development rate of the frozen clay hollow cylindrical specimen， and the greater the final cumulative plastic strain generated. In addition， it is found that with the increase of the initial stress under the pure principal stress rotation condition， the inclination of the axial stress-strain and shear stress-strain hysteresis curves of the frozen clay specimen increases， and the axial resilience modulus and shear modulus of the frozen clay specimen also increase， and there is a linear relationship between the axial resilience modulus and shear modulus and the static deviation stress ratio under different cyclic stress ratios. This research results are helpful to improve the design theory of cold region engineering and artificial freezing engineering.

The accurate simulation and projection of hydrological processes are of great significance for the management and protection of water resources in the Qinghai-Xizang Plateau. However， the limited and uneven distribution of national meteorological observation stations brings a great challenge to the accurate simulation of hydrological processes in plateau areas. Utilizing multi-source precipitation data is an effective means to improve simulation accuracy. In this study， the Golmud River basin in the northern Qinghai-Xizang Plateau was selected as a case study area. The VIC-CAS model was employed using three precipitation products （ERA5， WorldClim， and TPHiPr） to represent the multi-year monthly average precipitation as the background field. The meteorological forcing data was derived through interpolation of observed data from meteorological stations， enabling simulation and analysis of the runoff process in the Golmud River basin. Additionally， future runoff predictions were made by downscaling CMIP6 climate model data. The results showed that the meteorological forcing data obtained by using the annual average precipitation of ERA5 as covariate and TPS interpolation method has the most effective simulation results， The Nash efficiency coefficient （NSE） were 0.71 and 0.70 in the calibration and validation period. The contribution of glacier meltwater and snow meltwater to annual runoff in Golmud River basin is about 14.9% and 32.5% respectively. From 1971 to 2019， under the background of slow increase of annual precipitation and significant trend of temperature rise， the increase rates of snowmelt runoff and glacier runoff were 0.28×10⁸ m³⋅（10a）^-1 and 0.03×10⁸ m³⋅（10a）^-1， respectively. The annual runoff increased at a rate of 0.54×10⁸ m³⋅（10a）^-1， and the increase of snowmelt runoff contributed more than 50%. Under the SSP2-4.5 and SSP5-8.5 scenarios， the average annual runoff of Golmud River basin from 2025 to 2100 is projected to be 10.92×10⁸ m³ and 11.51×10⁸ m³， with an increase rate of 0.38×10⁸ m³⋅（10a）^-1 and 0.51×10⁸ m³⋅（10a）^-1， respectively. Furthermore， it is projected that snowmelt runoff and glacier runoff in the future period will reach their inflection points in the 2020s and 2030s under both SSP2-4.5 and SSP5-8.5 scenarios， followed by a significant decrease by the end of the 21st century. This study provides valuable insights for simulating runoff in other data-scarce regions of the Qinghai-Xizang Plateau.