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Influenced by global warming, glaciers in High Mountains Asia (HMA) generally show a trend of retreat and thinning, but in Karakoram, Pamir, and West Kunlun there is a trend of glacier stabilization or even a weak advance. In this study, using a bibliometric analysis, we systematically sorted the area, mass balance, and elevation changes of the glaciers in Karakoram and summarized the glacier surges in HMA. The study shows that, since the 1970s, the glaciers in the Karakoram region have experienced a weak positive mass balance, with weakly reducing area and the increasing surface elevation. The north slope of Chogori Peak and the Keltsing River Basin presented a glacier retreat rate with a fast to slow trend. The anomaly is mainly due to low summer temperatures and heavy precipitation in winter and spring in the Karakoram region. There are a large number of surging glaciers in the Karakoram Mountains, the Pamir Plateau, and the West Kunlun region in the western part of HMA, especially in the Karakoram Mountains and the Pamir Plateau, which account for more than 70% of the number of surging glaciers in the entire HMA. The glaciers in the Karakoram and Kunlun Mountains are mainly affected by the synergistic influence of various factors, such as hydrothermal conditions, atmospheric circulation, and topography. However, the glaciers in the Pamir region are mainly influenced by the thermal mechanism of the glacier surge. The glaciers in and around Karakoram are critical to the hydrological response to climate change, and glacial meltwater is an important freshwater resource in arid and semi-arid regions of South and Central Asia, as well as in western China. Therefore, changes in the Karakoram anomaly will remain a hot research topic in the future. [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA) is one of the concentrated areas of surging glaciers in the world. The dynamic movement of surging glaciers not only reshapes the periglacial landscape but also has the potential to directly or indirectly trigger catastrophic events. Therefore, it is crucial to understand the distribution patterns, periodicities, and occurrence mechanisms of surging glaciers. Based on Landsat TM/ETM+/OLI remote sensing images from 1986 to 2021, a total of 244 surging glaciers were identified in HMA in this study, covering an area of 11,724 km2 and accounting for 12.01% of the total area of glaciers in this region. There are 185 surging glaciers identified within the Karakoram Range and Pamirs, which constitute the primary mountainous regions in HMA. From 1986 to 2021, these surging glaciers advanced at least 2802 times and exhibited different temporal and spatial patterns. A total of 36 glaciers in HMA experienced 2 or more surges during this period, with the highest number observed in the Pamirs (19), followed by the Karakorum (13), with the other regions having fewer occurrences. Obvious differences exist in the surge phase and the quiescent phase of glaciers in different regions of HMA. The surge phase of surging glaciers in the Karakoram Range and Pamirs is generally short, mostly in the range of 2~6 years. The quiescent phase lasts for 5~19 years and the overall surge cycle ranges from 9 to 24 years. The complex nature of glacier surges in HMA suggests that multiple mechanisms may be at play, necessitating further research. [ABSTRACT FROM AUTHOR]

Due to the inability of remote sensing satellites to monitor avalanches in real time, this study focuses on the glaciers in the rear edge of Jialongcuo, Tibet, and uses infrasound sensors to conduct real-time monitoring of ice avalanches. The following conclusions are drawn: (1) In terms of waveform, compared to background noise, ice avalanche events have a slight left deviation and a slightly steep shape; compared to wind, rain, and floods events, ice avalanche events have less obvious kurtosis and skewness. (2) In terms of frequency distribution, the infrasound frequency generated by ice avalanche events is mainly distributed in the range of 1.5 Hz to 9.5 Hz; compared to other events, ice avalanche events differ some in frequency characteristics. (3) The model based on information entropy and marginal spectral frequency distribution characteristics of infrasound have higher accuracy in signal classification and recognition, as they can better represent the differences between infrasound signals of different events than other features. (4) Compared with the K-nearest neighbor algorithm and classification tree algorithm, the support vector machine and BP (Back Propagation) neural network algorithm are more suitable for identifying infrasound signals in the Jialongcuo ice avalanche. The research results can provide theoretical support for the application of infrasound-based ice avalanche monitoring technology. [ABSTRACT FROM AUTHOR]

Spatiotemporal studies of landscape pattern evolution in traditional villages are beneficial for addressing complex urbanization and global climate change. Using the traditional villages of Jiaxian and Linxian in the Jinshaan Gorge of the Yellow River Basin, this study employed a three-dimensional (3D) analysis involving three spatial scales (macro, meso, and micro), temporal scales (past, present, and future), and variables (humanity, society, and nature) based on the methods of spatiotemporal data analysis (SDA), geographic information system, remote sensing, and landscape pattern index (LPI) by Fragstats. On the macro scale, a significant turning point in ecological conservation awareness was indicated by LPI and SDA. Urban and rural construction land continuously increased because of urbanization. Plowland, grassland, and woodland were the main influencing factors in the evolution of rural settlements, with a 0.42% cumulative transformation rate. On the meso scale, the interactions and mutual promotion of mountain and aquatic environments, aquatic facilities, agricultural production, and cultural heritage have shaped the socioeconomic dimensions of evolution. On the micro scale, with urbanization, some traditional humanistic spaces have lost their original functions. A novel spatiotemporal-variable quantitative model explored the spatiotemporal evolution characteristics of human–land coupling, which can be used for the sustainable development of river basins worldwide. [ABSTRACT FROM AUTHOR]

In recent years, mountainous areas in China have faced frequent geological hazards, including landslides, debris flows, and collapses. Effective simulation of these events requires a solver for shallow water equations (SWEs). Traditional numerical methods, such as finite difference and finite volume, face challenges in discretizing convection flux terms, while theory-based models need to account for various factors such as shock wave capturing and wave propagation direction, demanding a high-level understanding of the underlying physics. Previous deep learning (DL)-based SWE solvers primarily focused on constructing direct input–output mappings, leading to weak generalization properties when terrain data or stress constitutive relations change. To overcome these limitations, this study introduces a novel SWE solver that combines theory and data-driven methodologies. The core idea is to use artificial neural networks to compute convection flux terms, and to reduce modeling complexity. Theory-based modeling is used to tackle complex terrain and friction terms for the purpose of ensuring generalization. Our method surpasses challenges faced by previous DL-based solvers in capturing terrain and stress variations. We validated our solver's capabilities by comparing simulation results with analytical solutions, real-world disaster cases, and the widely used Massflow software-generated simulations. This comprehensive comparison confirms our solver's ability to accurately simulate hazard scenarios and showcases strong generalization on varying terrain and land surface friction. Our proposed method effectively addresses DL-based solver limitations while simplifying the complexities of theory-driven numerical methods, offering a promising approach for hazard dynamics simulation. [ABSTRACT FROM AUTHOR]

This study investigated erosion during infiltration and overflow events and considered different grain sizes and hydraulic conductivity properties; four experimental cases were conducted under saturated conditions. The importance of understanding flow regimes during overflow experiments including their distinct flow characteristics, shear stresses, and erosion mechanisms in assessing the potential for levee failure are discussed. The failure mechanism of levee slopes during infiltration experiments involves progressive collapse due to piping followed by increased liquefaction and loss of shear stress, with the failure progression dependent on the permeability of the foundation material and shear strength. The infiltration experiments illustrate that the rate of failure varied based on the permeability of the foundation material. In the case of IO-E7-F5, where the levee had No. 7 sand in the embankment and No. 5 sand in the foundation (lower permeability), the failure was slower and limited. It took around 90 min for 65% of the downstream slope to fail, allowing more time for response measures. On the other hand, in the case of IO-E8-F4, with No. 8 sand in the embankment and No. 4 sand in the foundation (higher hydraulic conductivity), the failure was rapid and extensive. The whole downstream slope failed within just 18 min, and the collapse extended to 75% of the levee crest. These findings emphasize the need for proactive measures to strengthen vulnerable sections of levees and reduce the risk of extensive failure. [ABSTRACT FROM AUTHOR]

Glaciers are sensitive indicators of climate change, and investigation of their dynamics is crucial for ensuring regional ecological security as well as disaster prevention and mitigation measures. Based on Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) imagery, the outlines and length of glaciers in the West Kunlun Main Peak Area (WKMPA) during 2000–2020 were obtained by combining a band ratio method with manual interpretation and an automatic extraction method for the glacier centerline, respectively. There were 440 glaciers in the WKMPA in 2020, covering an area of 2964.59 ± 54.87 km2, with an average length of 2916 ± 60 m. The glacier count increased due to division, while the area and length all exhibited a declining trend from 2000 to 2020, at rates of −0.04%·a−1 (24.83 km2) and −0.11%·a−1 (66 m), respectively. Glacier retreat was primarily observed during the early period (2000–2005). Except for glaciers located above an elevation of 6250 m, the glacier area decreased with each altitude interval from 2000 to 2020, and the rate of relative change in glacier area generally decreased with increasing altitude. Moreover, except for a slight increase in north-facing glaciers, the area of glaciers facing other orientations decreased during 2000–2020. The accuracy of the empirical formula fit for glacier length was highly dependent on glacier class, with greater precision observed for smaller glaciers and lower precision for larger valley-basin glaciers due to their complex morphological structures being neglected and only a single quantitative relationship being considered. There was a time lag of 12 years between temperature changes and glacier area response in this region. The mechanism by which glacier division affects glacier change is complex, requiring dissection of multiple factors such as area, length, and terminal elevation before and after division. [ABSTRACT FROM AUTHOR]

Marine glaciers play a significant role in shaping landforms due to their erosive nature coupled with their surrounding environment. During this process, they pose a natural hazard threat to man-made infrastructure. The dynamic nature of these glaciers poses a particular threat, especially to railway infrastructure constructed in remote areas with glacial activity. Substantial research has been undertaken on the role of threats posed by marine glaciers to railway infrastructure. However, a detailed study of favorable glacier landforms prior to railway construction has yet to be explored. In this study, we propose a geospatial analysis-based method to determine the favorable most landforms shaped by marine glaciers for railway network route selection. This study provides a novel approach by first analyzing the availability of four major favorable landforms shaped by marine glaciers (glacier canyons, valley shoulders, moraine terraces, and ancient dammed lake basins), then proposes a railway route selection method for marine glacier distribution areas involving three steps. First, it is necessary to understand the basic situation of regional glaciers; then, to determine a feasible location for the railway based on judgment of the direct and indirect action areas of glaciers; and finally, through a thematic study of glacial geomorphology, to devise corresponding strategies for using glacial landforms to optimize the railway route. In order to verify the feasibility of the proposed method, it was implemented in the Palong Zangbo watershed of the Sichuan–Tibet railway network. Utilizing the power function method, the glacier basin areas of 22 glacier canyons along the Sichuan–Tibet railway line were identified and the maximum annual average velocity of 75 glaciers over the past ten years was calculated by offset tracking technology. The results indicate that the proposed optimization strategies utilizing glacier canyons for a short and straight route scheme and leveraging moraine terraces for a high-line scheme can provide comprehensive guidance for railway route selection in marine glacial areas. [ABSTRACT FROM AUTHOR]

Amid global concerns regarding climate change and urbanization, understanding the interplay between land use/land cover (LULC) changes, the urban heat island (UHI) effect, and land surface temperatures (LST) is paramount. This study provides an in-depth exploration of these relationships in the context of the Kamrup Metropolitan District, Northeast India, over a period of 22 years (2000–2022) and forecasts the potential implications up to 2032. Employing a high-accuracy supervised machine learning algorithm for LULC analysis, significant transformations are revealed, including the considerable growth in urban built-up areas and the corresponding decline in cultivated land. Concurrently, a progressive rise in LST is observed, underlining the escalating UHI effect. This association is further substantiated through correlation studies involving the normalized difference built-up index (NDBI) and the normalized difference vegetation index (NDVI). The study further leverages the cellular automata–artificial neural network (CA-ANN) model to project the potential scenario in 2032, indicating a predicted intensification in LST, especially in regions undergoing rapid urban expansion. The findings underscore the environmental implications of unchecked urban growth, such as rising temperatures and the intensification of UHI effects. Consequently, this research stresses the critical need for sustainable land management and urban planning strategies, as well as proactive measures to mitigate adverse environmental changes. The results serve as a vital resource for policymakers, urban planners, and environmental scientists working towards harmonizing urban growth with environmental sustainability in the face of escalating global climate change. [ABSTRACT FROM AUTHOR]

The glacial and torrential basin of Taconnaz (Mont-Blanc massif, France) dominates the Chamonix valley. It is one of the major paths for snow avalanches in the Alps, often triggered by serac falls from the Taconnaz glacier. On 24 November 2018, the basin's multi-risk nature was further accentuated by a new type of hazard with a rockfall triggered at c. 2700 m a.s.l. It travelled down over a distance of 1.85 km and stopped 165 m away from the construction site of a micro-hydroelectric power station. We studied the triggering conditions at the permafrost lower limit, the effects of the supra-glacial path on the flow patterns, and the fate of the scar and the deposit on torrential activity. By comparing a pre-event Structure from Motion model with a post-event LiDAR model, we estimated the volume of the scar to be 42,900 m3 (±5%). A numerical model was employed to simulate the rapid runout. It revealed the complexity of the flow, attributed to the sequestration of a part of the deposit in crevasses, the incorporation of a significant volume of ice resulting in a transition from a dry granular flow to a mud-like flow, and the presence of numerous deposit zones. Subsequent monitoring of the area after the event allowed for the documentation of the scar's evolution, including a landslide, as well as the progressive degradation and evacuation of the deposit by the torrent without producing debris flow. The study of the triggering factors indicated glacial retreat as the probable main cause, assisted by the melting of ice lenses left by the permafrost disappearance. Finally, we present replicable methods for managing risks at the site following the event. This event improves the understanding of cascading processes that increasingly impact Alpine areas in the context of climate change. [ABSTRACT FROM AUTHOR]

Mountain mudslides have emerged as one of the main geological dangers in the Yanshan region of China as a result of excessive rains. In light of this, a multi-step debris flow hazard assessment method combining optimal weights and a topological object metamodel is proposed based on game theory ideas. First of all, based on the geological environment research in Yanshan area, this paper determines the mudslide danger evaluation indexes according to the field investigation and remote sensing image data, then combines them with the theory of topological object element evaluation, utilizes the idea of game theory, and carries out the optimal combination of the weight coefficients derived from hierarchical analysis and the CRITIC method to obtain the final comprehensive weights of the indexes, and forms the combination-assigning topological object element of the mudslide danger topological model. The results suggest that improved weight coefficients can increase topological evaluation precision, which is more in line with objective reality than the traditional method and has some application utility. [ABSTRACT FROM AUTHOR]

Heavy rainfall induces shallow landslides in the mountainous areas of China. There is a need for regional slope stability prediction to reduce the damage to infrastructure, residents, and the economy. This study attempts to demarcate areas prone to rainfall-induced shallow landslides using the transient rainfall infiltration and grid-based slope stability (TRIGRS) model under different rainfall conditions. After inputting the engineering geological and geotechnical characteristic data of the area in China, the slope stability was simulated and verified by a deformation monitoring landslide. The slope stability gradually declined under the influence of precipitation from 5–8 July 2021. Slope stability gradually decreased under the predicted rainfall intensity of 60 mm/d for 6 days. The percentage of the slope area with a factor of safety (FS) less than 1.0 increased from 0.00% (1 d) to 3.18% (6 d). The study results could be used for hazards mitigation in this region. [ABSTRACT FROM AUTHOR]

From an extensive search of papers related to the comparison of Global Digital Elevation Models (hereinafter GDEMs), an analysis is carried out that aims to answer several questions such as: Which GDEMs have been compared? Where have the comparisons been made? How many comparisons have been made? How have the assessments been carried out? Which is the GDEM option with the lowest RMSE? Analysis shows that SRTM and ASTER are the most popular GDEMs, that the countries where more comparisons have been made are Brazil, India, and China, and that the main type of reference data for evaluations is the use of points surveyed by GNSS techniques. A variety of criteria have been found for the comparison of GDEMs, but the most used are the RMSE and the standard deviation of the elevation error. There are numerous criteria with a more user-centric character in thematic areas, such as morphometry, geomorphology, erosion, etc. However, in none of the thematic areas does there exist a standard method of comparison. This limits the possibilities of establishing a ranking of GDEMs based on their user-focused quality. In addition, the methods and reference data set are not adequately explained or shared, which limits the interoperability of the studies carried out and the ability to make robust comparisons between them. [ABSTRACT FROM AUTHOR]

As an approach with great potential, the interpretation of space-borne synthetic aperture radar (SAR) images has been applied for monitoring the dynamic evolution of the glacial lakes in recent years. Considering unfavorable factors, such as inherent topography-induced effects and speckle noise in SAR images, it is challenging to accurately map and track the dynamic evolution of the glacial lakes by using multi-temporal SAR images. This paper presents an improved neighborhood-based ratio method utilizing a time series of SAR images to identify the boundaries of the glacial lakes and detect their spatiotemporal changes. The proposed method was applied to monitor the dynamic evolution of the two glacial lakes with periodic water discharge at the terminus of the Gongba Glacier in the southeastern Tibetan Plateau by utilizing 144 Sentinel-1A SAR images collected between October of 2014 and November of 2020. We first generated the reference intensity image (RII) by averaging all the SAR images collected when the water in the glacial lakes was wholly discharged, then calculated the neighborhood-based ratio between RII and each SAR intensity image, and finally identified the boundaries of the glacial lakes by a ratio threshold determined statistically. The time series of areas of the glacial lakes were estimated in this way, and the dates for water recharging and discharging were accordingly determined. The testing results showed that the water of the two glacial lakes began to be recharged in April and reached their peak in August and then remained stable dynamically until they began to shrink in October and were discharged entirely in February of the following year. We observed the expansion process with annual growth rates of 3.19% and 12.63% for these two glacial lakes, respectively, and monitored a glacial lake outburst flood event in July 2018. The validation by comparing with the results derived from Sentinel-2A/B optical images indicates that the accuracy for identifying the boundaries of the glacial lakes with Sentinel-1A SAR images can reach up to 96.49%. Generally, this contribution demonstrates the reliability and precision of SAR images to provide regular updates for the dynamic monitoring of glacial lakes. [ABSTRACT FROM AUTHOR]

The evolution of a glacial lake is a true reflection of glacial and climatic change. Currently, the study of glacial lakes in the Altai Mountains is mainly concerned with the application of high-resolution remote sensing images to monitor and evaluate the potential hazards of glacial lakes. At present, there is no rapid and large-scale method to monitor the dynamical variation in glacial lakes in the Altai Mountains, and there is little research on predicting its future tendency. Based on the supervised classification results obtained by Google Earth Engine (GEE), combined with an analysis of meteorological data, we analyzed the spatial and temporal variations in glacial lakes in the Altai Mountains between 2000 and 2020, and used the MCE-CA-Markov model to predict their changes in the future. According to the results, as of 2020, there are 3824 glacial lakes in the Altai Mountains, with an area of 682.38 km2. Over the entire period, the glacial lake quantity growth rates and area were 47.82% and 17.07%, respectively. The distribution of glacial lakes in this region showed a larger concentration in the north than in the south. Most glacial lakes had areas smaller than 0.1 km2, and there was minimal change observed in glacial lakes larger than 0.2 km2. Analyzing the regional elevation in 100 m intervals, the study found that glacial lakes were predominantly distributed at elevations from 2000 m to 3000 m. Interannual rainfall and temperature fluctuations in the Altai Mountains have slowed since 2014, and the trends for the area and number of glacial lakes have stabilized. The growth of glacial lakes in both number and surface area is expected to continue through 2025 and 2030, although the pace of change will slow. In the context of small increases in precipitation and large increases in temperature, in the future, glacial lakes with faster surface area growth rates will be located primarily in the southern Altai Mountains. [ABSTRACT FROM AUTHOR]

With the changing climate, the frequency and intensity of extreme precipitation events are increasing. Climate change is projected to increase both mean and extreme precipitation. Socio-economic damages can be immense and require a difficult recovery, especially for developing countries such as Bhutan. Furthermore, changing precipitation patterns affect land productivity and water availability. The Experts Team on Climate Change Detection Indices (ETCCDI) is used to find the changes associated with extreme precipitation in Bhutan. The study of extreme precipitation is important for Bhutan, whose economy is dependent on agriculture and hydropower. Even for a small country, there were varying patterns of precipitation in different districts. Deothang district received less frequent and more intense rainfall, while Haa, Bumthang, Trashiyangtse, and Chukha received weak but persistent rainfall. Mann–Kendall trends revealed a drier climate for two districts, Dagana and Trashiyangtse, and a wetter climate for the Mongar district. Modeling of the extreme rainfall with extreme value theory (EVT) revealed that the generalized extreme value (GEV) distribution by their T = 50-year return value, indicating an increasing value of annual maximums for all stations. This study is the first of its kind for Bhutan, and the findings can be used for decision support and the planning of appropriate adaptation strategies for hydro-meteorological disasters, hydropower, and agriculture sectors in Bhutan. [ABSTRACT FROM AUTHOR]

Lake-terminating glaciers have some peculiar behaviors compared to land-terminating glaciers, but in-depth observation is still limited regarding their formation, which is crucial for understanding the glacier–lake interaction. Here, the long-term evolutions of Tanymas Lake and the Fedchenko Glacier were investigated based on Landsat images, Google Earth imagery, KH-9 images, glacier surface elevation and velocity change datasets, and meteorological records. The results indicate that Tanymas Lake is both an ice-contact proglacial lake and an ice-dammed lake. It covered an area of 1.10 km2 in September 2022, and it is one of the largest glacial lakes in Pamir and even in HMA. The initial basin of Tanymas Lake is a moraine depression in Tanymas Pass, and the blocked dam is the Tanymas-5 Glacier and its terminal moraine. Tanymas Lake was in an embryonic stage before August 2005, in a formation and expansion stage from August 2005 to September 2018, and in a new expansion stage after September 2018. In this process, the Tanymas terminus of the Fedchenko Glacier also transformed from a land terminus to a partial lake terminus, and then to a complete lake terminus. The formation of Tanymas Lake is associated with the accumulation of glacial meltwater and the blockage of drainage, while the slow expansion of Tanymas Lake is related to the cold climate and slight glacier mass loss of Central Pamir. In the coming decades, with the accelerated mass loss of the Tanymas terminus of the Fedchenko Glacier, the area, depth, and water storage of Tanymas Lake will continue to increase, accompanied by the growing GLOF risk. [ABSTRACT FROM AUTHOR]

Mt. Munkhkhairkhan is the most crucial region for understanding climate and glaciation changes in Mongolia. This study investigated the relationship between glacial area changes and the climate elements of Mt. Munkhkhairkhan in the Mongolian-Altai Mountains using a remote sensing approach, in-situ observations, the Mann–Kendall (MK) test, Innovative Trend Analysis Method (ITAM), Sen's slope estimator test, and statistical analysis. The study results showed that for the last 30 years, the annual average air temperature of Mt. Munkhkhairkhan has been slightly increasing. Total annual precipitation (mainly snow) in the mountain area decreased from 1990 to 2000, but since 2000, a significant increase in precipitation levels has appeared. For the last 30 years, the glacial area has decreased by 32% to 11.7 km2. Multiple regression results showed a strong correlation between Temperature, Precipitation, and Glaciers (Multiple R = 0.69, R2 = 0.48). Ruther indicated that Temperature (t = −2.332, p = 0.036) and Precipitation (t = −3.212, p = 0.007) were significant predictors in the model. Air temperature and precipitation explained 48 percent of the change in the glacier area, and R = 0.69 is a strong correlation. The glaciers and snow area in the study area have changed due to climate warming and precipitation changes and are located in arid and semi-arid regions of Central Asia. This study of Mt. Munkhairkhan shows that climate change significantly impacts glaciers and snow. [ABSTRACT FROM AUTHOR]

As a particular type of alpine glacier, debris-covered glaciers are essential for local water resources and glacial disaster warnings. The Eastern Tomur Peak Region (EPTR) is the most concentrated glacier in Tien Shan Mountain, China, where the glaciers have not been studied in detail. This paper evaluates the delineation accuracy of Landsat8 OLI, Sentinel-1A, and GF images for debris-covered glaciers in the EPTR. Each image uses the most advanced delineation method for itself to minimize the error of inherent resolutions. The results show that the accuracy of these images for delineating debris-covered glaciers is very high, and the F1 scores are expressed as 96.73%, 93.55%, and 95.81%, respectively. Therefore, Landsat images were selected to analyze the area change of EPTR from 2000 to 2022 over a 5-year time scale. The results indicate that glaciers of the EPTR decreased by 19.05 km2 from 2000 to 2020, accounting for 1.9% (0.08% a−1), and debris increased by 10.8%, which validates the opinion that the presence of debris inhibits glacier melting. The most varied time was 2010–2022, but it was much less than other Tien Shan regions. The lower glacier ablation rate in this area results from the combined effect of decreased bare ice and increased debris. The main reason for the change in debris-covered glaciers is the increase in temperature. [ABSTRACT FROM AUTHOR]

Mountainous regions are prone to dammed lake disasters due to their rough topography, scant vegetation, and high summer rainfall. By measuring water level variation, monitoring systems can detect dammed lake events when mudslides block rivers or boost water level. Therefore, an automatic monitoring alarm method based on a hybrid segmentation algorithm is proposed. The algorithm uses the k-means clustering algorithm to segment the picture scene in the RGB color space and the region growing algorithm on the image green channel to select the river target from the segmented scene. The pixel water level variation is used to trigger an alarm for the dammed lake event after the water level has been retrieved. In the Yarlung Tsangpo River basin of the Tibet Autonomous Region of China, the proposed automatic lake monitoring system was installed. We pick up data from April to November 2021, during which the river experienced low, high, and low water levels. Unlike conventional region growing algorithms, the algorithm does not rely on engineering knowledge to pick seed point parameters. Using our method, the accuracy rate is 89.29% and the miss rate is 11.76%, which is 29.12% higher and 17.65% lower than the traditional region growing algorithm, respectively. The monitoring results indicate that the proposed method is a highly adaptable and accurate unmanned dammed lake monitoring system. [ABSTRACT FROM AUTHOR]

The northern scenic area of Changbai Mountain is a high-incidence area of debris flow disasters, which seriously threaten the safety of tourist's lives and property. Monitoring debris flow and providing early warning is critical for timely avoidance. Monitoring the change of debris flow source is an effective way to predict debris flow, and the change of source can be reflected in the settlement deformation of the study area. The offset tracking technique (OT) is insensitive to the coherence of SAR images and can resist the decoherence of D-InSAR and SBSA-InSAR to a certain extent. It is a technical means for monitoring large gradient deformation. It has been widely used in the field of seismic activity, glaciers and landslides in recent years, but few scholars have applied this technique in the field of debris flow. In this paper, we use OT techniques in combination with field surveys, Google imagery and Sentinel-1 data to monitor surface deformation in the northern scenic area of Changbai Mountain in 2017 and use D-InSAR techniques to compare and complement the OT monitoring results. The results of this study show that for monitoring surface deformation in the study area after a mudslide, it is better to use both methods to determine the surface deformation in the study area rather than one, and that both methods have their own advantages and disadvantages and yet can complement each other. Finally, we have predicted the development trend of mudflows in the study area by combining the calculated single mudflow solids washout, which will help to improve the long-term monitoring and warning capability of mudflows in the study area. The study also enriches the application of offset-tracking technology and D-InSAR in the field of geohazard monitoring and provides new ideas and methods for the study of mudflow material source changes. [ABSTRACT FROM AUTHOR]

The retreats of the planet's tropical glaciers are natural indicators of the variation of precipitation, temperature, and other variables. The glaciers of the Alto Santa sub-basin are sources of freshwater storage for consumptive and non-consumptive use for different sectors. As a result of climatic variations, it is essential to analyze the dynamics of the snow cover area (SCA). The methodology consisted of processing 6578 MODIS Snow Cover MOD10A1 product images and generating 18-year time series using the Platform Google Earth Engine (GEE). Normalized Difference Snow Index (NDSI) was used to estimate the extent of snow cover, and to validate the MODIS snow cover product, we used the same overlapping date of Landsat 5 and 8 Surface Reflectance Tier 1, to examine the relationships between daily precipitation and temperature. The standardized correlation results gave good results with stations over 4500 m.a.s.l., such as Artesonraju AP2 (4828 m.a.s.l.) of −0.84 and −0.74, precipitation, and temperature. These results show coherent behaviors of the retreat due to the variation of the climatological variables. In some years, there were anomalies in the conduct of the three variables, but these originated from events of natural weather phenomena. Regarding the dynamics of the SCA in 18 years, it decreased from 649 km2 to 311.6. km2 between 2000 and 2017, representing a retreat of 41%; we can conclude and confirm that the glacier retreat is imminent due to the consequences of climate change, which would affect the security of freshwater from the tropical glaciers of the Peruvian Andes. [ABSTRACT FROM AUTHOR]

In a previous study two pairs of paleo-landslides within an 8 km reach of the upper Yellow River were studied and dated back to ca. 80 ka, however the relationship between these two pairs of paleo-landslides were not explored. This study inferred that the initial pair of landslides (Dehenglong and Suozi) appearing contiguously and forming an upstream 46 km-long lake along the river may be triggered by earthquake events from nearby capable faults. Subsequently, backwater inundating the valley floor as the dammed lake formed may cause shear stress of sediments lowered on steep slopes adjacent to the River, and eventually induce the other two additional landslides (Xiazangtan and Kangyang) ~8 km upstream. This could be inferred from two optically stimulated luminescence (OSL) samples yielding ca. 80 ka also, which were collected from asymmetric folds 10 to 30 cm in amplitude within the bedding plane between lake/lakeshore sediment and landslide mass at the front lobes of the two additional landslides. We estimated the maximum volume of this dammed lake was 38 km3 and may generate an outburst flood with an estimated peak discharge of 6.1 × 105 m3/s, which may cause massive geomorphic effects and potential disasters upstream and downstream. It is important to better understand the geomorphic process of this damming event in mountainous area with respect to reflecting tectonic uplift, paleoclimatic change and forecast and mitigate hazards on the northeast Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Recent studies have indicated that the accurate simulation of debris flows depends not only on the selection of numerical models but also on the availability of precise data on the initial source location and depth. Unfortunately, it is currently difficult to obtain quantitative data on source locations and depths during field investigations or model experiments of debris flow disasters. Therefore, in this study, we propose an integrated approach for simulating the debris-flow dynamic process that includes the physically based slope initiation source estimation and the entrainment-incorporated process simulation. We treat the potential slip surfaces' locations and depths as random variables to search for the critical surface corresponding to the minimum stability factor by Monte Carlo simulation. Using the spatial variation interval of the soil parameters, we estimate the range of possible critical slip surfaces and the interval of the initiation source volume. Moreover, we propose a wet/dry front treatment method applied to the finite difference scheme and integrate it into our entrainment-incorporated model to improve the stability and accuracy of the numerical solution over complex topography. The effectiveness of the method is demonstrated through a case study of the 2010 Hongchun debris flow event in Yingxiu town. The result indicates that our method is effective in simulating debris flow dynamics, including slope initiation source estimation and dynamic process simulation. [ABSTRACT FROM AUTHOR]

Owning to the nature of flood events, near-real-time flood detection and mapping is essential for disaster prevention, relief, and mitigation. In recent years, the rapid advancement of deep learning has brought endless possibilities to the field of flood detection. However, deep learning relies heavily on training samples and the availability of high-quality flood datasets is rather limited. The present study collected 16 flood events in the Yangtze River Basin and divided them into three categories for different purpose: training, testing, and application. An efficient methodology of dataset-generation for training, testing, and application was proposed. Eight flood events were used to generate strong label datasets with 5296 tiles as flood training samples along with two testing datasets. The performances of several classic convolutional neural network models were evaluated with those obtained datasets, and the results suggested that the efficiencies and accuracies of convolutional neural network models were obviously higher than that of the threshold method. The effects of VH polarization, VV polarization, and the involvement of auxiliary DEM on flood detection were investigated, which indicated that VH polarization was more conducive to flood detection, while the involvement of DEM has a limited effect on flood detection in the Yangtze River Basin. Convolutional neural network trained by strong datasets were used in near-real-time flood detection and mapping for the remaining eight flood events, and weak label datasets were generated to expand the flood training samples to evaluate the possible effects on deep learning models in terms of flood detection and mapping. The experiments obtained conclusions consistent with those previously made on experiments with strong datasets. [ABSTRACT FROM AUTHOR]

Small and medium-sized towns in the high mountain regions of South Asia are characterised by rapid and mostly unplanned urbanisation processes, regularly resulting in an increased risk of urban agglomerations being exposed to natural hazards. After the administrative capital of Leh, Kargil town is the second-largest urban centre in the Union Territory (UT) of Ladakh. This article discusses the development and dynamics of the Trans-Himalayan town in terms of its historical development, expansion and population; land use and land cover (LULC) change; and the specific role of tourism. Based on a multi-temporal approach using high-resolution satellite images, statistical data and field surveys, the urban landscape dynamics of Kargil town are analysed. The total population of this town increased almost tenfold from 1681 in 1961 to 16,338 in 2011, which resulted in an increase in the urban population from 3.7% to 11.6%, while the population of the entire Kargil district only tripled from 45,064 to 140,802 over the same period. Migration from rural villages to Kargil town has been a major cause for the construction and growth of new residential colonies and settlements. The built-up area increased more than ninefold from 0.25 km2 (1.3%) to 2.30 km2 (11.7%) between 1965 and 2020. During the same period, irrigated land and hygrophilous vegetation increased considerably from 4.51 km2 (23.0%) to 8.56 km2 (43.6%) due to the construction of new water channels. Similarly, the barren area decreased significantly from 14.88 km2 (75.8%) to 8.78 km2 (44.7%) between 1965 and 2020. Moreover, the massive increase in tourist arrivals has led to the construction of more hotels, guesthouses and travel agencies. These key factors play a significant role in the emergence, growth and development of this high-mountain town. [ABSTRACT FROM AUTHOR]

Satellite radar altimetry has been widely utilized in hydrological research, particularly with the advent of Sentinel-3, a Synthetic Aperture Radar (SAR) altimeter operating globally and equipped with an innovative onboard tracking system referred to as the open-loop tracking command (OLTC). Utilizing a pseudo-DEM (Digital Elevation Model), controlled through the OLTC, holds significant promise for the reliable observation of inland water bodies. Nevertheless, the complex geographical conditions in high mountain and reservoir river basins pose challenges in defining an appropriate pseudo-DEM for hydrological targets, potentially leading to reduced performance of Sentinel-3. This study aims to comprehensively evaluate the performance of Sentinel-3 by selecting the Lancang and Nu River basins in southwest China as a case study. These two rivers have a similar natural environment, but cascade reservoirs distinguish the Lancang River basin. By analyzing waveform energy from echoes of virtual stations (VSs) in both river basins (27 VSs in the Lancang River basin and 39 VSs in the Nu River basin), the performance of Sentinel-3 in different tracking modes and OLTC versions were compared. The results indicated that the detection rate of Sentinel-3A increased when transitioning from the closed-loop mode to the open-loop mode and with the implementation of newer OLTC versions (36.8% increased to 47.4%, 60.5%, and 63.2% in OLTC V5.0, V6.0, and V6.1, respectively). Similarly, the detection rate of Sentinel-3B rose from 64.3% (OLTC V2.0) to 71.4% and 75.0% in OLTC V3.0 and V3.1, respectively. Additionally, the cascade reservoir causing river channel expansion results in a better performance of Sentinel-3A in the Lancang River compared to the Nu River in the closed-loop mode (13.0% and 35.7%, respectively). Nevertheless, the considerable fluctuations in water surface caused by reservoir impoundment led to a wrong pseudo-DEM, resulting in poor performance of Sentinel-3 in reservoir regions before OLTC V6.0 was updated. The detection rate of low altitude, broad water surfaces (>500 m) decreased from 100% in a closed-loop mode to 0% in an open-loop mode, but increased to 100% in OLTC V6.0 and V6.1, respectively. The detection rate of high altitude, narrow water surfaces (<500 m) increased from 0% in a closed-loop mode to 40.9% in OLTC V6.1. Although the detection ability of Sentinel-3 is improving with the implementation of newer OLTC versions, the seasonal variations (usually more than 60 m) of water levels in reservoirs exceeded the size of the range window (60 m), rendering a complete measurement impossible. [ABSTRACT FROM AUTHOR]

Debris flow, the most extensive and most severe geological hazard along the Karakoram Highway, frequently blocks the Karakoram Highway. Based on the methods of field measurement, indoor statistical analysis and theoretical research, this paper discusses the relationship between the four types of debris flow along the Karakoram Highway. The four types are the rain type, the rain glacier type, the glacier ice lake break type and the freeze–thaw type, and their particle characteristics and gully slope are also considered in the discussion. The results are as follows: (1) The provenance particle size of debris flow is controlled by the type of debris flow. Generally, the provenance average particle equivalent diameter of the debris flow induced by the glacier ice lake type is relatively small, followed by the freeze–thaw type and glacier ice lake break type, and the equivalent diameter of the debris flow induced by the rain type is relatively large; (2) The gully slope coefficient of the debris flow C along the Karakoram Highway is greater than 1, and it increases with the increase in gully slope α , that is, the larger C is, the steeper the gully slope will be; (3) The gully slope coefficient C and the average particle equivalent diameter D of the four types of debris flow are distributed in the ellipse with them as the axis. This ellipse quantitatively describes the relationship between the gully slope of the four types of debris flow and the corresponding provenance particle characteristics. This paper analyzes the formation and causes of debris flow along the Karakoram Highway. It accurately understands the scientific connotation of debris flow formation in the surface matrix layer and improves the diversity, stability, and sustainability of the ecosystem. The paper also proposes ideas and suggestions for promoting the ecological protection and restoration of the Karakoram Highway. Therefore, the research has a certain theoretical significance and practical application value for the appropriate selection and rational design of the debris flow prevention projects along the China–Pakistan Highway. [ABSTRACT FROM AUTHOR]

Even though surge-type glaciers make up only a small percentage of all glaciers, related research contributes considerably to the general understanding of glacier flow mechanisms. Recent studies based on remote sensing techniques aimed to disentangle underlying processes related to glacier surges. They have proven the possibilities yielded by combining high performance computing and earth observation. In addition, modelling approaches to surges have seen increasing popularity, yet large spatial and temporal data about timing of surge incites are missing. We aimed to develop an algorithm that not only detects surge type glaciers but also determines the timing of a surge onset, while being computationally inexpensive, transferable, and expandable in time and space. The algorithm is based on time series analyses of glacier surface velocity derived from Sentinel-1 data. After seasonal and trend decomposition, outlier detection is performed by the General Studentized Extreme Deviate Test, an iterative algorithm well suited for outlier detection in univariate time series. To determine surges, cluster analysis is performed to identify outlier clusters, which are linked to glacier surges. We demonstrate the viability on the Svalbard archipelago for the period 2015 to 2021 where we have identified 18 glacier surges and the timing of their active phase. [ABSTRACT FROM AUTHOR]

Local scour holes are erosional bed structures that are related to different scientific disciplines in Earth science and hydraulic engineering. Local scouring at naturally placed boulders is ubiquitous, but many competing factors make it difficult to isolate the effects of a given variable. This is especially true for local scouring at natural instream obstacles that are exposed to unsteady flow conditions in the course of flood hydrograph experiments. Experimental investigations in laboratory flumes offer the advantage that boundary conditions can be systematically varied. We present novel experimental data on the impact of the submergence ratio, hydrograph skewness, and flow intensity on local scouring at boulder-like obstacles during unsteady flow and evaluate the effect of discharge chronologies. In total, 48 flume experiments on subcritical clear-water conditions and channel degradation were performed. The experimental results reveal that local scouring dominantly occurred at the rising limb when flow depth was comparable to the obstacle size, so the obstacle was unsubmerged. The steeper the rising limb, the quicker the local scour hole matured. The experimental results are relevant for the hydraulic interpretation of local scour holes found at boulders in the field. They may be utilized as a proxy for the minimum duration of the beginning stage of a flood. [ABSTRACT FROM AUTHOR]

The tropical glaciers of the Cordillera Blanca have played host to some of the most significant mass movements ever recorded in the world and Peru; many proglacial lakes formed in this mountain range have natural dikes made of moraine material, which, if they collapse, would present a risk for the cities located downstream of a proglacial lake, where the proglacial lake Palcacocha has a remarkable background regarding floods. The Sentinel-2 MSI (Multi-Spectral Instrument, Level-2A) has a specific band for snow probability mapping that indicates glaciers and snow cover; this is effective for recognizing proglacial lakes by calculating the NDWIice. It is also helpful for lithology with SWIR for granite moraine deposits and slate moraines in the proglacial environment Palcacocha; these deposits surround the proglacial lake, with NDWIice determining the perimeter where sediment interacts with the rocks and meltwater. In addition, there are high radon concentrations made by ice avalanche impacts on the proglacial lake. Unstable glacier blocks cause ice avalanches into this proglacial lake, and the radon responds to flow variations from these high-impact avalanches. We used the device RadonEye PLus2, which allows real-time detection of radon flux changes in the proglacial environment. Our results indicated that ice avalanches making a high impact in the proglacial lake cause turbulent flow and generate radon concentration marks with a rising magnitude, while the absence of ice avalanches in the lake will cause the values to go down. The relationships of radon concentrations in the atmosphere for a tropical proglacial environment are radon and temperature (R2 = 0.364), radon and humidity (R2 = 0.469). In a passive proglacial environment with prolonged rainfall, radon concentrations tend to decrease, with an inversely proportional relationship between humidity and radon in the tropical proglacial environment. Proglacial lakes in the tropical zone often have large volumes of freshwater with high slopes from tropical glaciers, and climate change effects are an imminent danger for nearby cities. [ABSTRACT FROM AUTHOR]

Against the background of the ongoing atmospheric warming, the glacial lakes that are nourished and expanded in High Mountain Asia pose growing risks of glacial lake outburst floods (GLOFs) hazards and increasing threats to the downstream areas. Effectively extracting the area and consistently monitoring the dynamics of these lakes are of great significance in predicting and preventing GLOF events. To automatically extract the lake areas, many deep learning (DL) methods capable of capturing the multi-level features of lakes have been proposed in segmentation and classification tasks. However, the portability of these supervised DL methods need to be improved in order to be directly applied to different data sources, as they require laborious effort to collect the labeled lake masks. In this work, we proposed a simple glacial lake extraction model (SimGL) via weakly-supervised contrastive learning to extend and improve the extraction performances in cases that lack the labeled lake masks. In SimGL, a Siamese network was employed to learn similar objects by maximizing the similarity between the input image and its augmentations. Then, a simple Normalized Difference Water Index (NDWI) map was provided as the location cue instead of the labeled lake masks to constrain the model to capture the representations related to the glacial lakes and the segmentations to coincide with the true lake areas. Finally, the experimental results of the glacial lake extraction on the 1540 Landsat-8 image patches showed that our approach, SimGL, offers a competitive effort with some supervised methods (such as Random Forest) and outperforms other unsupervised image segmentation methods in cases that lack true image labels. [ABSTRACT FROM AUTHOR]

High-altitude and long-runout landslides, commonly forming chains of secondary disasters, frequently occur in the Yigong Zangbo Basin, which has a complex geologic background. Identifying the potential hazards posed by disaster chains plays a vital role in assessing geohazards. Analysis of the potential hazards related to a landslide that occurred on 9 April 2000, in Tibet, China, known as the Yigong landslide, is studied using remote sensing technology and numerical simulations. Due to the warming of the climate, more extreme dry–wet cycles, and frequent earthquakes, the Yigong landslide area became extremely fragile and more sensitive to perturbations. Based on multiphase optical remote sensing and InSAR (Interferometric Synthetic Aperture Radar) technology, risk monitoring and identification of the Yigong landslide was conducted. The results show that there are two displacement deformation areas. These areas have a maximum displacement deformation rate of 60 mm/year and a maximum accumulative displacement of 160 mm and are likely to reoccur. Additionally, the risks of deformation areas collapsing and blocking the river, which would likely form a disaster chain, were analyzed by prediction simulation based on the numerical back-analysis associated with the 2000 Yigong landslide. The results show that if only one displacement deformation area collapses, the maximum accumulation height would reach 76 m; if the displacement deformation areas both collapse, the maximum accumulation height would reach 106 m. Both conditions would set off disaster chains resulting in river blockages and subsequent flood disasters. Therefore, this work demonstrates that prediction analysis based on remote sensing technology and numerical simulations are effective methods for identifying potential geohazards. [ABSTRACT FROM AUTHOR]

The regional surge patterns and control mechanisms for glaciers in the western Pamirs are unclear. Using remote sensing, more surge-type glaciers have been discovered in the western Pamirs. This provides an opportunity to obtain the integral characteristics of glacier surging. Using Sentinel-1A, TSX/TDX and Landsat remote sensing data, the changes in surface velocity, surface elevation and surface features of five glaciers that have recently surged in the western Pamirs are obtained. The results show that (1) all glacier surges initiate gradually for several years and most form a surge front in the upper region of the glacier. (2) For most glaciers, the active phase of the surge is more than 2 years, except for one that is within several months. (3) The peak velocity mostly occurs in summer and autumn, and the maximum velocity is less than 8 m d−1. (4) There is sharp deceleration, such as the hydrologic controlled surge at the end of the surge. However, the surface flow of the transverse profiles shows no features of base sliding. Based on the comparison of surge patterns with other regions in High Mountain Asia, we conclude that the surging glaciers in the western Pamirs are triggered by thermal mechanisms under the control of sub-hydrological modulation. [ABSTRACT FROM AUTHOR]

Global atmospheric warming is causing physical and biotic changes in Earth's high mountains at a rate that is likely unprecedented in the Holocene. We summarize changes in the presently glacierized mountains of northwest North America, including a rapid and large reduction in glacier ice and permafrost, a related increase in slope instability and landslides, river re-routing and other hydrological changes, and changing aquatic ecosystems. Atmospheric greenhouse gas concentrations continue to rise and will likely do so for at least the next several decades, if not longer, and mountains will continue to warm, perhaps reaching temperatures up to several degrees Celsius warmer than present over the remainder of this century. As a result, the rate of physical and biotic changes documented in this paper is very likely to dramatically increase and transform high-mountain environments. [ABSTRACT FROM AUTHOR]

In the context of climate change, enhanced human activities and ecological changes, the danger level for mountain floods has increased significantly, posing direct or potential hazards to local residents. To determine the current status, focus and trends in mountain flood research, in this study, we visualize the number of publications and citations, the countries and institutions engaged in research, co-citations and key literature, keyword categories and research areas, using keyword timeline analysis and burst detection based on the bibliometric software CiteSpace and VOSviewer and the Web of Sciences core collection database. The results show that the total number of publications and citations in the mountain flood field has experienced rapid growth to date. The United States, China, Germany, the United Kingdom, and Switzerland are the main countries driving the development of the field. The field is of great interest within multiple disciplinary categories and is characterized by multiple research hotspots, multiple research objectives, and cross-fertilization of multiple disciplinary categories. Analysis of the keyword timeline network and highlighted words show that disaster risk evaluation based on remote-sensing technology, the alpine region of the Himalayas, the response mechanisms of heavy rainfall to mountain floods, and the construction of hydrological models, will be research hotspots in the future. [ABSTRACT FROM AUTHOR]

The stability and kinematics of rock slopes are widely considered to be functions of lithological, structural, and environmental features. Conversely, slope damage features are often overlooked and considered as byproducts of slope deformation. This paper analyzes and discusses the potential role of slope damage, its time-dependent nature, and its control on both the stability of rock slopes and their kinematics. The analysis of several major landslides and unstable slopes, combined with a literature survey, shows that slope damage can play an important role in controlling short- and long-term slope stability. Seasonal and continuously active events cause permanent deformation within the slope due to the accumulation of slope damage features, including rock mass dilation and intact rock fracturing. Rock mass quality, lithology, and scale control the characteristics and complexity of slope damage, as well as the failure mechanism. The authors propose that the role of slope damage in slope kinematics should always be considered in slope stability analysis, and that an integrated characterization–monitoring–numerical modelling approach can enhance our understanding of slope damage, its evolution, and the controlling factors. Finally, it is emphasized that there is currently a lack of guidelines or frameworks for the quantitative assessment and classification of slope damage, which requires a multidisciplinary approach combining rock mechanics, geomorphology, engineering geology, remote sensing, and geophysics. [ABSTRACT FROM AUTHOR]

Flood, a distinctive natural calamity, has occurred more frequently in the last few decades all over the world, which is often an unexpected and inevitable natural hazard, but the losses and damages can be managed and controlled by adopting effective measures. In recent times, flood hazard susceptibility mapping has become a prime concern in minimizing the worst impact of this global threat; but the nonlinear relationship between several flood causative factors and the dynamicity of risk levels makes it complicated and confronted with substantial challenges to reliable assessment. Therefore, we have considered SVM, RF, and ANN—three distinctive ML algorithms in the GIS platform—to delineate the flood hazard risk zones of the subtropical Kangsabati river basin, West Bengal, India; which experienced frequent flood events because of intense rainfall throughout the monsoon season. In our study, all adopted ML algorithms are more efficient in solving all the non-linear problems in flood hazard risk assessment; multi-collinearity analysis and Pearson's correlation coefficient techniques have been used to identify the collinearity issues among all fifteen adopted flood causative factors. In this research, the predicted results are evaluated through six prominent and reliable statistical ("AUC-ROC, specificity, sensitivity, PPV, NPV, F-score") and one graphical (Taylor diagram) technique and shows that ANN is the most reliable modeling approach followed by RF and SVM models. The values of AUC in the ANN model for the training and validation datasets are 0.901 and 0.891, respectively. The derived result states that about 7.54% and 10.41% of areas accordingly lie under the high and extremely high flood danger risk zones. Thus, this study can help the decision-makers in constructing the proper strategy at the regional and national levels to mitigate the flood hazard in a particular region. This type of information may be helpful to the various authorities to implement this outcome in various spheres of decision making. Apart from this, future researchers are also able to conduct their research byconsidering this methodology in flood susceptibility assessment. [ABSTRACT FROM AUTHOR]

Natural hazards are dynamic and unpredictable events that are a continuous threat to global socio-economic development. Humans' reactions to these catastrophes are influenced by their proximity to the hazards and their ability to anticipate, resist, cope with, and recover from their consequences. Due to climatic changes, the risk of multiple natural hazards is expected to increase in several regions of Pakistan. There is a pressing need to understand the spatial discrepancies of natural hazards due to climate change and identifying the regions that require special measures to increase resilience, achieve adaptation, and sustainable development goals. This paper synthesizes the related literature to understand spatial variations of natural hazards due to climate changes across Pakistan. The Emergency Events Database (EM-DAT), National Aeronautics and Space Administration Global Landslide Catalog (NASA-GLC), National Disaster Management Authority (NDMA), and Pakistan Meteorological Department (PMD) are utilized to analyze spatial discrepancies and vulnerabilities to natural hazards. This study unveils that Pakistan's current risk analysis and management strategies seem to be obsolete compared to global trends. Because of spatial variations of hazards, most research work on hazard risk assessments and risk management focuses on a single hazard, neglecting the co-occurrence impact of different natural hazards. Very limited studies are included in comprehensive multi-hazard risk strategies. Therefore, in Pakistan, risk management would require integrated multi-hazard risk assessment approaches to detect, analyze, measure, and evaluate various natural hazards, their effects, and interconnections. Moreover, the Pakistan governmental institutes dealing with natural hazards should focus on pre-disaster mitigation and resilience techniques instead of investing only in post-disaster relief activities. [ABSTRACT FROM AUTHOR]

In recent years, drought events have influenced agriculture, water-dependent industries, and energy supply in many parts of the world. The China–Pakistan Economic Corridor (CPEC) is particularly susceptible to drought events due to large-scale monsoon circulation anomalies. Using the 0.5 × 0.5 resolution rainfall and potential evapotranspiration data set from the Climatic Research Unit (CRU), we assessed the changes in seasonal drought variation and effects of climate variables on drought over the CPEC for the period of 1980 to 2018 using the Standardized Precipitation Evapotranspiration Index (SPEI). Our results show a statistically significant negative trend of SPEI over the hyper-arid region for two monsoons (December–February and June–September) and intra-monsoonal seasons (March–May and October–November), suggesting that the hyper-arid region (southern and southwestern part of the CPEC) is experiencing more frequent drought. A high probability for the occurrence of winter (30–35%) and summer (20–25%) droughts are observed in hyper-arid regions and gradually decreases from south to north of the CPEC. Decreasing seasonal rainfall and increasing potential evapotranspiration with increasing temperature in hyper-arid and arid regions resulted in frequent drought events during the winter monsoon season (from December to February). The findings from this study provide a theoretical basis for the drought management of the CPEC and a framework for understanding changes in drought in this region from climate projections. [ABSTRACT FROM AUTHOR]

Increased and enhanced utilisation of remote sensing and robotics in the Arctic can further enhance cultural safety and well-being and reduce the risks posed to archaeologists, heritage workers and others in the field. In this preliminary scoping survey, the authors review the current use of these technologies and consider a range of related issues, from cultural safety to nefarious use by criminals. Initial discussions with experts have informed areas of concern; and the potential for further integration. In the future, the University of Tromsø's new Tromsø Arctic Simulation Integration Centre (TASIC) will be utilised to evaluate a range of scenarios to inform risk analysis and contribute towards safety enhancement in the Arctic Heritage at Risk Project (Arctic-HARP). The following is an overview of the significant state-of-the-art technologies and related matters. [ABSTRACT FROM AUTHOR]

The southeast region of Tibet experiences frequent glacial lake outburst disasters, and disaster warning systems are thus crucial for disaster prevention and mitigation in the area. In this study, based on remote sensing images and historical data, 20 glacial lakes in southeast Tibet were selected as samples for risk analysis. A probability model of glacial lake outburst floods (GLOFs) in southeast Tibet was established using logistic regression for seven selected prediction indexes. By calculating the sensitivity and specificity of the model, the probability of identifying GLOFs was found to be 60%, with an identification degree of 86%. The under the ROC (receiver operating characteristic) curve index was prominently larger than 0.5, indicating the applicability of logistic regression for predicting GLOFs in southeast Tibet. The probability equation of the model shows that the area of the glacial lake, the distance of the glacial lake from the glacier, the slope of the glacier, the slope of the glacier tongue, and the dam backwater slope have a great influence on the probability of GLOFs. The results can provide a reference for the local governments to prevent disasters and reduce the damage of GLOFs. [ABSTRACT FROM AUTHOR]

A glacial lake outburst flood (GLOF) is a phenomenon that is widely known by researchers because such an event can wreak havoc on the natural environment as well as on manmade infrastructure. Therefore, a GLOF risk assessment is necessary, especially within river basins with hydropower plants, and may lead to a tremendous amount of socioeconomic loss if not done. However, due to the subjective and objective limitations of the available GLOF risk assessment methods, we have proposed a new and easily applied method with a wider application and without the need for adaptation changes in accordance with the subject area, which also allows for the repeated use of this model. In this study, we focused our efforts on the Upper Arun Hydroelectric Project (UAHEP) in the Arun River Basin, and we (1) identified 49 glacial lakes with areas greater than 0.1 km2; (2) geographically represented and analyzed these 49 glacial lakes for the period of 1990–2018; (3) analyzed the correlation between the temperature and precipitation trends and the occurrence of recorded GLOF events in the region; (4) proposed a new method based on the documented affected lengths and volumes derived from historical GLOF events to identify 4 potentially critical lakes; and (5) evaluated the discharge profiles using widely used empirical methods and further discussed the physical properties, triggering factors, and outburst probability of the critical lakes. To achieve these objectives, a series of intensive and integrated desk studies, data collections, and GLOF simulations and analyses were performed. [ABSTRACT FROM AUTHOR]

Alpine lakes, which include glacial and nonglacial lakes, are widely distributed in high mountain areas and are sensitive to climate and environmental changes. Remote sensing is an effective tool for identifying alpine lakes over large regions, but in the case of small lakes, the complex terrain and extreme weather make their accurate identification extremely challenging. This paper presents an automated method for alpine lake identification developed by leveraging deep learning algorithms and multi-source high-resolution satellite data. The method is able to detect the outlines and types of alpine lakes from high-resolution optical and Synthetic Aperture Radar (SAR) satellite data. In this study, a total of 4584 alpine lakes (including 2795 glacial lakes) were identified in the Eastern Himalayas from Sentinel-1 and Sentinel-2 data acquired during 2016–2020. The average area of the lakes was 0.038 km2, and the average elevation was 4974 m. High accuracy was reported for the dataset for both segmentation (mean Intersection Over Union (MIoU) > 72%) and classification (Overall Accuracy, User's and Producer's Accuracies, and F1-Score are all higher than 85%). A higher accuracy was found for the combination of optical and SAR data than relying on single-sourced data, for which the MIoU increased by at least 12%, suggesting that the combination of optical and SAR data is critical for improving the identification of alpine lakes. The deep learning-based method demonstrated a significant improvement over traditional spectral extraction methods. [ABSTRACT FROM AUTHOR]

As the Third Pole of the Earth and the Water Tower of Asia, the Tibetan Plateau (TP) nurtures large numbers of glacial lakes, which are sensitive to global climate change. These lakes modulate the freshwater ecosystem in the region but concurrently pose severe threats to the valley population by means of sudden glacial lake outbursts and consequent floods (GLOFs). The lack of high-resolution multi-temporal inventory of glacial lakes in TP hampers a better understanding and prediction of the future trend and risk of glacial lakes. Here, we created a multi-temporal inventory of glacial lakes in TP using a 30-year record of 42,833 satellite images (1990–2019), and we discussed their characteristics and spatio-temporal evolution over the years. Results showed that their number and area had increased by 3285 and 258.82 km2 in the last 3 decades, respectively. We noticed that different regions of the TP exhibited varying change rates in glacial lake size; most regions show a trend of expansion and increase in glacial lakes, while some regions show a trend of decreasing such as the western Pamir and the eastern Hindu Kush. The mapping uncertainty is about 17.5%, which is lower than other available datasets, thus making our inventory reliable for the spatio-temporal evolution analysis of glacial lakes in the TP. Our lake inventory data are publicly published, it can help to study climate change–glacier–glacial lake–GLOF interactions in the Third Pole and serve as input to various hydro-climatic studies. [ABSTRACT FROM AUTHOR]

The ancient Aniangzhai (ANZ) landslide in Danba County, Sichuan Province of southwest China was reactivated after a series of complex hazard events that occurred in June 2020. Since then, and until June 2021, emergency engineering work was carried out to prevent the further failure of the reactivated landslide. This study investigates the potential of joint use of time series Interferometric Synthetic Aperture Radar (InSAR) and optical pixel offset tracking (POT) to assess deformation characteristic and spatial-temporal evolution of the reactivated ANZ landslide during the post-failure stage. The relationships between sun illumination differences, temporal baseline of correlation pairs and the uncertainties were deeply explored. Surface deformation along the line-of-sight (LoS) direction was retrieved by the time series InSAR processing with the two Sentinel-1 datasets, revealing a maximum deformation rate up to 190 mm/year. The large horizontal displacements were also detected from the POT processing using 11 optical images acquired by the PlanetScope satellite (3 m spatial resolution), showing a significant increase of about 24 m between 24 June 2020 and 11 June 2021. The time series analysis from the InSAR and optical POT results revealed that the reactivated ANZ landslide body is gradually slowing down to a steady deformation status since its occurrence in August 2020, indicating the effectiveness of engineering work on the prevention of further landslide. A slight acceleration was detected from both InSAR and optical POT time series analysis between May 2021 and June 2021, which could be caused by the increased rainfall in May 2021. [ABSTRACT FROM AUTHOR]

Circular landscape features, including kettle lakes, sinkholes, pingos, calderas, and craters, develop from a variety of different geomorphic processes on Earth. On many rocky extraterrestrial surfaces, including Mars, the most common circular landscape features are craters, and the density of these craters is commonly used to estimate the age of the surface. On planetary bodies where fluvial, volcanic, and glacial geomorphic processes are not present, alternative interpretations of circular features can safely be ignored. However, Mars once hosted an Earth-like climate and many elements of the Martian landscape that are visible today were formed by ancient fluvial, glacial, or volcanic processes. In this work, we focus on the potential presence of postglacial kettle hole depressions on Mars. We explore the size and density distribution of kettle lakes in three analog postglacial landscapes on Earth and discuss the implications for planetary surface age dating if kettles and craters are present together in the landscape on Mars. [ABSTRACT FROM AUTHOR]

One of the main glacier-related natural hazards that are common to alpine locations is the occurrence of glacial lake outburst floods (GLOFs), which can seriously harm downstream towns and infrastructure. GLOFs have increased in frequency in the central Himalayas in recent years as a result of global warming, and careful management of glacial lakes is a crucial step in catastrophe prevention. In this study, field surveys were conducted on 28 August 2020 and 1 August 2021 with the help of an unmanned aerial vehicle (UAV) and a boat bathymetric system on an unmanned surface vessel (USV), combined with 22 years of Landsat series imagery and Sentinel-2 MSI imagery data. Spatial analysis was then used to investigate changes in lake surface conditions, dam stability, and surrounding topography before and after an integrated project of the Jialong Co lake. The results show that: (1) from 2000 to 2020 (before engineering management), the area of the Jialong Co glacial lake increased from 0.2148 ± 0.0176 km2 to 0.5921 ± 0.0003 km2. The glacial lake expansion rate from 2000 to 2010 (0.0145 km2/a) was greater than the rate from 2011 to 2020 (6.92 × 10−6 km2/a). In 2021 (after engineering treatment), the glacial lake perimeter, area, and volume decreased by 0.6014 km, 0.1136 km2, and 1.90 × 107 m3, respectively. The amount of excavation during the project treatment was 8.13 million square meters, and the amount of filling was 1.24 million square meters. According to the results of the unmanned surface vessel (USV), the elevation of the lake surface dropped from 4331 m to 4281 m, and the water level dropped by 50 m (the designed safe water level line dropped by 30 m). (2) The results of the UAV topographic survey and geomorphological analysis showed that the engineered reinforcement of the outlet channel and surrounding dam effectively mitigated severe scouring of the foot of the final moraine at the outlet of the spillway, as well as the likelihood of glacial lake outbursts caused by ice avalanches and landslides. (3) The comprehensive engineering treatment of this typical glacial lake effectively lowered the water level and improved the stability of the moraine ridge and lake dam, providing a scientific foundation for other glacial lake outburst risk assessments and disaster mitigation and management measures. Thus, it is critical to evaluate the impact of comprehensive engineering management of key glacial lakes to support glacial lake management. [ABSTRACT FROM AUTHOR]

Flood events have long been very frequent along the Yangtze River in Chongqing, China. A complete sedimentary sequence of alluvia, found in the Yuxi profile (YXP) was applied to explore features of the palaeoflood layers that maintained records related to the contexts of flooding hydroclimate. The AMS14C dating results dependent on animal bones from the YXP validate that the chronology of the palaeoflood layers was dated, between ca. 8200 and 6400 a BP, and multiple cultural layers were intercut among these palaeoflood layers. By means of particle size and end-member analyses for the palaeoflood sediments, the fractions of fine silt and clay in deposits account for a high proportion of the flood sediments, suggesting that the overbank flood was the main power in building the palaeoflood layers. Due to the climatic episodes defined by pollen assemblages, the thickness of the flood layers is positively correlated with soil erosion because of different hydrothermal conditions. The wavelet spectra of the mean particle-size series also suggest that there may be two major palaeoflooding cycles of ~700 and ~30 years. Despite the sustained palaeoflooding, the Yuxi Culture grew from small to big, and was never broken off, in terms of the findings of artificial remains in the YXP. [ABSTRACT FROM AUTHOR]

Urban pluvial flooding has become an important factor in urban casualties and economic losses, thus, there is an urgent need to strengthen urban emergency management research and improve emergency response capabilities to flooding. The SCS–CN hydrological model combined with GIS spatial analysis were used to assess the spatial accessibility of the emergency response to key urban public services (medical and fire) for different pluvial flooding scenarios of the Jiaozuo urban area. The results show that the coverage area of the public service department (medical and fire) emergency response decreases as the period of pluvial flooding recurrence increases. The accessibility of the public service department (medical and fire services) emergency response shows a gradual decline from the center of the Jiaozuo urban area to the periphery. The depth and area of water accumulation in the northern part of the Zhongzhan District, the northeastern part of the Macun District, and the southwestern part of the Shanyang District gradually increased as the heavy rainfall recurrence period increased. Emergency response from public services (medical and fire services) could not arrive within 15 min. [ABSTRACT FROM AUTHOR]