Search Results (12)

Rock glaciers have been recognized as key indicators of geomorphic and climatic processes in high mountain environments. In this study, Sentinel-2 MSI imagery and topographic data were integrated to construct enhanced feature sets for rock glacier identification. Three state-of-the-art deep learning models (U-Net, DeepLabV3+, and HRnet) were employed to perform semantic segmentation for extracting rock glacier boundaries in the Hunza River Basin, located in the eastern Karakoram Mountains. The combination of spectral and terrain features significantly improved the differentiation of rock glaciers from surrounding landforms, establishing a robust basis for model training. A series of comparative experiments were conducted to evaluate the performance of each model. The HRnet model achieved the highest overall accuracy, exhibiting superior capabilities in high-resolution feature representations and generalization. Using the HRnet framework, a total of 597 rock glaciers were identified, covering an area of 183.59 km². Spatial analysis revealed that these rock glaciers are concentrated between elevations of 4000 m and 6000 m, with maximum density near 5000 m, and a predominant south and southwest orientation. These spatial patterns reflect the combined influences of topography, thermal conditions, and snow accumulation on the formation and preservation of rock glaciers. The results confirm the effectiveness of deep learning-based semantic segmentation for large-scale rock glacier mapping. The proposed framework establishes a technical foundation for automated monitoring of alpine landforms and supports future assessments of rock glacier dynamics under climate variability. Full article

Glacial hazards pose significant threats to millions globally, especially with rapid climate warming drawing increased attention. Understanding past glacial hazards on both global and regional scales is crucial for early warning systems. This study quantified glacier and glacial lake changes on the Tibetan Plateau (TP) over recent decades and analyzed the spatial and temporal distribution of major glacial hazards. It also focused on glacial lakes that have experienced outburst events by reconstructing long-term data for 48 lakes. Key findings include: (1) TP glaciers have generally shrunk, with glacier area decreasing from 57,100 km² in the first inventory to 44,400 km² in the second, primarily in the middle and eastern Himalayas between 5000 and 6000 m. Meanwhile, the number of glacial lakes increased from 14,487 in 1990 to 16,385 in 2020, expanding towards higher elevations and glacier melt zones. (2) Since 1900, 283 glacial hazards have occurred, including 97 glacier surges, 36 glacier-related slope failures, and 150 glacial lake outburst floods (GLOFs). Hazard frequency increased post-2000, especially in the Karakoram and eastern Himalayas, during June to September. (3) Changes in glacier numbers contribute most to hazard frequency (11.56%), followed by July’s temperature change (10.24%). Slope and June’s temperature changes combined have the highest interaction effect (37.59%). (4) Of the 48 lakes studied, four disappeared after outbursts, 38 remained stable, and six expanded. These insights aid in monitoring, early warnings, and disaster management. Full article

Mountain regions are particularly sensitive and vulnerable to the impacts of climate change. Over the past three decades, mountain temperatures have risen significantly faster than those in lowland areas. The Hindu Kush–Karakoram–Himalaya region, often referred to as the “water tower of Asia”, is the largest freshwater source outside the polar regions. However, it is currently undergoing cryospheric degradation as a result of climatic change. In this study, the Normalized Difference Glacier Index (NDGI) was calculated using Landsat and Sentinel satellite images. The results revealed that glaciers in Chitral, located in the Eastern Hindu Kush Mountains of Pakistan, lost 816 km² (31%) of their total area between 1992 and 2022. On average, 27 km² of glacier area was lost annually, with recession accelerating between 1997 and 2002 and again after 2007. Satellite analyses also indicated a significant increase in both maximum (+7.3 °C) and minimum (+3.6 °C) land surface temperatures between 1992 and 2022. Climate data analyses using the Mann–Kendall test, Theil–Sen Slope method, and the Autoregressive Integrated Moving Average (ARIMA) model showed a clear increase in air temperatures from 1967 to 2022, particularly during the summer months (June, July, and August). This warming trend is expected to continue until at least 2042. Over the same period, annual precipitation decreased, primarily due to reduced snowfall in winter. However, rainfall may have slightly increased during the summer months, further accelerating glacial melting. Additionally, the snowmelt season began consistently earlier. While initial glacier melting may temporarily boost water resources, it also poses risks to communities and economies, particularly through more frequent and larger floods. Over time, the remaining smaller glaciers will contribute only a fraction of the former runoff, leading to potential water stress. As such, monitoring glaciers, climate change, and runoff patterns is critical for sustainable water management and strengthening resilience in the region. Full article

Supraglacial debris cover considerably influences sub-debris ablation patterns and the surface morphology of glaciers by modulating the land–atmosphere energy exchange. Understanding its spatial distribution and temporal variations is crucial for analyzing melting processes and managing downstream disaster mitigation efforts. In recent years, the overall slightly positive mass balance or stable state of eastern Pamir glaciers has been referred to as the “Pamir-Karakoram anomaly”. It is important to note that spatial heterogeneity in glacier change has drawn widespread research attention. However, research on the spatiotemporal changes in the debris cover in this region is completely nonexistent, which has led to an inadequate understanding of debris-covered glacier variations. To address this research gap, this study employed Landsat remote sensing images within the Google Earth Engine platform, leveraging the Random Forest algorithm to classify the supraglacial debris cover. The classification algorithm integrates spectral features from Landsat images and derived indices (NDVI, NDSI, NDWI, and BAND RATIO), supplemented by auxiliary factors such as slope and aspect. By extracting the supraglacial debris cover from 1994 to 2024, this study systematically analyzed the spatiotemporal variations and investigated the underlying drivers of debris cover changes from the perspective of mass conservation. By 2024, the area of supraglacial debris in eastern Pamir reached 258.08 ± 20.65 km², accounting for 18.5 ± 1.55% of the total glacier area. It was observed that the Kungey Mountain region demonstrated the largest debris cover rate. Between 1994 and 2024, while the total glacier area decreased by −2.57 ± 0.70%, the debris-covered areas expanded upward at a rate of +1.64 ± 0.10% yr⁻¹. The expansion of debris cover is driven by several factors in the context of global warming. The rising temperature resulted in permafrost degradation, slope destabilization, and intensified weathering on supply slopes, thereby augmenting the debris supply. Additionally, the steep supply slope in the study area facilitates the rapid deposition of collapsed debris onto glacier surfaces, with frequent avalanche events accelerating the mobilization of rock fragments. Full article

The Tibetan Plateau (TP) has the largest number of high-altitude glaciers on Earth. As a source of major rivers in Asia, this region provides fresh water to more than one billion people. Any terrestrial water storage (TWS) changes there have major societal effects in large parts of the continent. Due to the recent acceleration in global warming, part of the water environment in TP has become drastically unbalanced, with an increased risk of water disasters. We quantified secular and monthly glacier-mass-balance and TWS changes in water basins from April 2002 to December 2021 through the Gravity Recovery and Climate Experiment and its Follow-on satellite mission (GRACE/GRACE-FO). Adequate data postprocessing with destriping filters and gap filling and two regularization methods implemented in the spectral and space domain were applied. The largest glacier-mass losses were found in the Nyainqentanglha Mountains and Eastern Himalayas, with rates of −4.92 ± 1.38 Gt a⁻¹ and −4.34 ± 1.48 Gt a⁻¹, respectively. The Tien Shan region showed strong losses in its eastern and central parts. Furthermore, we found small glacier-mass increases in the Karakoram and West Kunlun. Most of the glacier mass change can be explained by snowfall changes and, in some areas, by summer rainfall created by the Indian monsoon. Major water basins in the north and south of the TP exhibited partly significant negative TWS changes. In turn, the endorheic region and the Qaidam basin in the TP, as well as the near Three Rivers source region, showed distinctly positive TWS signals related to net precipitation increase. However, the Salween River source region and the Yarlung Zangbo River basin showed decreasing trends. We suggest that our new and improved TWS-change results can be used for the maintenance of water resources and the prevention of water disasters not only in the TP, but also in surrounding Asian countries. They may also help in global change studies. Full article

Glacier velocity is the key to understanding the nature of glaciers. Its variation plays an important role in glacier dynamics, mass balance, and climate change. The Muztag-Kongur Mountains are an important glacier region in the Eastern Pamir Plateau. Under the background of global warming, the glacier velocity variation has been widely considered, but details of the inter-annual and intra-annual changes have not been clear. In this study, we explored the inter-annual and intra-annual variations in the glacier velocity from 1990 to 2021, and the influencing factors, based on Landsat images, Inter-Mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE), and Karakoram Highway (KKH) data product analysis. The results showed the following: (1) the glacier velocity has increased since 1990, and significant growth occurred in 1995–1996. (2) A transverse profile of two typical glaciers was used to analyze the monthly variation in glacier velocity during the year. The peaks of monthly velocity occurred in May and August. (3) Since 1990, the inter-annual precipitation has increased, and the temperature increase slowed down from 2000 to 2013. The trend of inter-annual glacier velocity variation was consistent with that of the precipitation. The glacier velocity peaked in 1996/1997 due to increased precipitation in 1995. The glacier velocity over the year was consistent with the monthly precipitation trends, which indicates that precipitation has a significant influence on the change in glacier velocity. (4) In addition to temperature and precipitation, the glacier velocity variation was moderately correlated with the glacier size (length and area) and weakly correlated with the slope. The spatial distribution of glaciers shows that the spatial heterogeneity of glaciers in the Muztag-Kongur Mountains is affected by the westerly circulation. The long-term glacier velocity variation research of the Muztag-Kongur Mountains will contribute to a better understanding of glacier dynamics within the context of climatic warming, and the different influencing factors were analyzed to further explain the glacier velocity variation. Full article

Glacier mass balance is one of the most direct indicators reflecting corresponding climate change. In the context of global warming, most glaciers are melting and receding, which can have significant impacts on ecology, climate, and water resources. Thus, it is important to study glacier mass change, in order to assess and project its variations from past to future. Here, the Karakoram, one of the most concentrated glacierized areas in High-Mountain Asia (HMA), was selected as the study area. This study utilized SRTM_-C DEM and ICESat-2 to investigate glacier mass change in the Karakoram, and its response to climatic and topographical factors during 2000–2021. The results of the data investigation showed that, overall, the “Karakoram Anomaly” still exists, with an annual averaged mass change rate of 0.02 ± 0.09 m w.e.yr^-1. In different sub-regions, it was found that the western and central Karakoram glaciers gained ice mass, while the eastern Karakoram glaciers lost ice mass in the past two decades. In addition, it was discovered that the increasing precipitation trend is leading to mass gains in the western and central Karakoram glaciers, whereas increasing temperature is causing ice mass loss in the eastern Karakoram glacier. Generally, decreasing net shortwave radiation and increasing cloud cover in the Karakoram restricts ice mass loss, while topographical shading and debris cover also have dominant impacts on glacier mass change. Full article

The Himalayan, Karakoram, and Hindu Kush (HKH-TMHA) are the three main mountain ranges in the high-mountain Asia region, covering the China–Pakistan Economic Corridor (CPEC). In this study, we identified glacial lakes in the HKH-TMHA region based on multitemporal Landsat images taken from 1990 to 2020. We analyzed the spatial distribution and evolution of glacial lakes in the HKH-TMHA region from the perspective of their elevation, size, and terrain aspect; then, we described their temporal changes. The results showed that approximately 84.56% of the glacial lakes (84.1% of the total lake area) were located at elevations between 4000 m and 5500 m, and glacial lakes with areas ranging from 0.01–0.5 km² accounted for approximately 95.21% of the number and 63.01% of the total area of glacial lakes. The number (38.64%) and area (58.83%) of south-facing glacial lakes were largest in HKH-TMHA and expanded significantly over time. There were 5835 (664.84 ± 89.72 km²) glacial lakes in 1990; from 1990 to 2020, the number of glacial lakes in the HKH-TMHA region increased by 5974 (408.93 km²) in total; and the annual average increase in the area of glacial lakes reached 13.63 km² (11.15%). In 2020, the total number of glacial lake reached to 9673 (899.66 ± 120.63 km²). In addition, most glacial lakes were located in the Eastern Himalayan, China, and the Indus Basin. Based on the precipitation and temperature analyses performed in our study area, we found inconsistent climate characteristics and changes in the three mountain ranges. In general, the daily precipitation (temperature) increased by 1.0766 mm (1.0311 °C), 0.8544 mm (0.8346 °C), and 0.8245 mm (−0.1042 °C) on the yearly, summer, and winter scales, respectively. Glacial melting and climate change are common contributors to glacial lake expansion. The investigation of glacial lakes in this region can provide basic supporting data for research on glacial lake-related disasters, land cover, and climate change in the high-mountain Asia region. Full article

The glacier snowline altitude (SLA) at the end of the melt season is an indicator of the glacier equilibrium line altitude and can be used to estimate glacier mass balance and reconstruct past climate. This study analyzes the spatiotemporal variability in glacier SLA across High Mountain Asia, including the Altai Mountains, Karakoram Mountains, Western Himalayas, Gongga Mountains, Tian Shan, and Nyainqentanglha Mountains, over the past 30 years (1989–2019) to better elucidate the state of these mountain glaciers. Remote-sensing data are processed to delineate the glacier SLA across these mountainous regions, and nearby weather station data are incorporated to determine the potential relationships between SLA and temperature/precipitation. The mean SLAs across the Altai and Karakoram mountains ranged from 2860 ± 169 m to 3200 ± 152 m and from 5120 ± 159 m to 5320 ± 240 m, respectively, with both regions experiencing an average increase of up to 137 m over the past 30 years. Furthermore, the mean glacier SLAs across the Western Himalayas and Gongga Mountains increased by 190–282 m over the past 30 years, with both regions experiencing large fluctuations. In particular, the mean glacier SLA across the Western Himalayas varied from 4910 ± 190 m in 1989 to 5380 ± 164 m in 2000, and that across the Gongga Mountains varied from 4960 ± 70 m in 1989 to 5330 ± 100 m in 2012. Correlation analyses between glacier SLA and temperature/precipitation suggest that temperature is the primary factor influencing glacier SLA across these High Mountain Asia glaciers. There is a broad increase in glacier SLA from the Altai Mountains to the Karakoram Mountains, with a decrease in glacier SLA with decreasing latitude across the Himalayas; the maximum SLA occurs near the northern slopes of the Western Himalayas. The glacier SLA is lower on the eastern side of the Tibetan Plateau and exhibits a longitudinal distribution pattern. These results are expected to provide useful information for evaluating the state of High Mountain Asia glaciers, as well as their response and feedback to climate change. Full article

The nature of hydrological seasonality over the Himalayan Glaciated Region (HGR) is complex due to varied precipitation patterns. The present study attempts to exemplify the spatio-temporal variation of hydrological mass over the HGR using time-variable gravity from the Gravity Recovery and Climate Experiment (GRACE) satellite for the period of 2002–2016 on seasonal and interannual timescales. The mass signal derived from GRACE data is decomposed using empirical orthogonal functions (EOFs), allowing us to identify the three broad divisions of HGR, i.e., western, central, and eastern, based on the seasonal mass gain or loss that corresponds to prevailing climatic changes. Further, causative relationships between climatic variables and the EOF decomposed signals are explored using the Granger causality algorithm. It appears that a causal relationship exists between total precipitation and total water storage from GRACE. EOF modes also indicate certain regional anomalies such as the Karakoram mass gain, which represents ongoing snow accumulation. Our causality result suggests that the excessive snowfall in 2005–2008 has initiated this mass gain. However, as our results indicate, despite the dampening of snowfall rates after 2008, mass has been steadily increasing in the Karakorum, which is attributed to the flattening of the temperature anomaly curve and subsequent lower melting after 2008. Full article

The Karakoram has had an overall slight positive glacier mass balance since the end of 20th century, which is anomalous given that most other regions in High Mountain Asia have had negative changes. A large number of advancing, retreating, and surging glaciers are heterogeneously mixed in the Karakoram increasing the difficulties and inaccuracies to identify glacier surges. We found two adjacent glaciers in the eastern Karakoram behaving differently from 1995 to 2019: one was surging and the other was advancing. In order to figure out the differences existing between them and the potential controls on surges in this region, we collected satellite images from Landsat series, ASTER, and Google Earth, along with two sets of digital elevation model. Utilizing visual interpretation, feature tracking of optical images, and differencing between digital elevation models, three major differences were observed: (1) the evolution profiles of the terminus positions occupied different change patterns; (2) the surging glacier experienced a dramatic fluctuation in the surface velocities during and after the event, while the advancing glacier flowed in a stable mode; and (3) surface elevation of the surging glacier decreased in the reservoir and increased in the receiving zone. However, the advancing glacier only had an obvious elevation increase over its terminus part. These differences can be regarded as standards for surge identification in mountain ranges. After combining the differences with regional meteorological conditions, we suggested that changes of thermal and hydrological conditions could play a role in the surge occurrence, in addition, geomorphological characteristics and increasing warming climate might also be part of it. This research strongly contributes to the literatures of glacial motion and glacier mass change in the eastern Karakoram through remote sensing. Full article

Climatic differences between monsoonal and cold-arid parts of the South Asian mountain arc account for the uncertainty regarding regional variations in glacier retreat. In this context, the upper Indus Basin of Ladakh, sandwiched between the Himalayan and Karakoram ranges, is of particular interest. The aims of the present study are threefold: to map the glaciers of central and eastern Ladakh, to describe their regional distribution and characteristics in relation to size and topography, and to analyze glacier changes in the selected ranges over the past five decades. The study is based on multi-temporal remote sensing data (Corona and Landsat), supported and validated by several field campaigns carried out between 2007 and 2016. A glacier inventory was carried out for the complete study area, which was subdivided into nine sub-regions for comparison. In general, the glaciers of Ladakh are characterized by their high altitude, as 91% terminate above 5200 m, and by their relatively small size, as 79% of them are smaller than 0.75 km² and only 4% are larger than 2 km². The glaciated area of central Ladakh totaled 997 km² with more than 1800 glaciers in 2002. Full article