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The glaciers in southeastern Tibet Plateau (SETP) influenced by oceanic climate are sensitive to global warming, and there remains a notable deficiency in accurate multitemporal change analyses of these glaciers. We conduct glacier inventories in the Yigong Zangbo River Basin (YZRB) in SETP for the years 1988, 2015, and 2023 utilizing Landsat and Sentinel-2 imagery, and analyze the glacier spatiotemporal variation incorporating the existing glacier inventory data. Since the 1970s until 2023, the glaciers significantly retreated at a rate of 0.76 ± 0.11%·a−1, with the area decreasing from 2583.09 ± 88.80 km2 to 1635.89 ± 71.74 km2, and the ice volume reducing from 221.7017 ± 7.9618 km3 to 152.7429 ± 6.1747 km3. The most significant retreat occurred in glaciers smaller than 1 km2. Additionally, glaciers on southern aspects retreated slower than the northern counterparts. The glaciers in the western YZRB witnessed a significantly greater shrinkage rate than those in the eastern section, with the most pronounced changes occurring in Aso Longbu River Basin. Furthermore, severe glacier mass deficits were observed from 2000 to 2019, averaging a loss rate of 0.57 ± 0.06 m w.e. a−1. The continuous rise in air temperature has primarily induced a general widespread glacier change in the YZRB. However, diverse topography led to spatial variability in glacier changes with discrepancies as large as several times. The features of individual glaciers, such as glacier size, debris cover, and the development of ice-contact glacial lakes enhanced the local complexity of glacier change and elusive response behaviors to climate warming led by the different topographic conditions. [ABSTRACT FROM AUTHOR]

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock–ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate–cryosphere–hydrology–hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze–thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole. [ABSTRACT FROM AUTHOR]

This study presented detailed analysis of glacier surface extent in the Alaknanda river basin, Western Himalaya, using Landsat series data, land surface temperature and digital elevation model (DEM). The clean glaciers were delineated using automatic glacier extraction index (AGEI) and the debris-covered glaciers were extracted by utilizing slope and land surface temperature. The generated glaciers map was compared and cross-checked with Randolph Glacier Inventory (RGI v5.0) and sharp google earth image. The reduction in glacier surface area was observed by 367.364 sq. km from 1994 (1150.471 sq. km) to 2015 (783.107 sq. km) at the shrinkage rate of 1.45% per annum. The shrinkage rate was higher from 2006 to 2015 (2.43% per annum) than from 1994 to 2006 (0.78% per annum). The glacier count expanded from 314 (1994) to 360 (2015) due to the fragmentation of individual glaciers. The elevation range of 5000–5500 m above m.s.l. hosted maximum number of glaciers and glacial coverage. The debris-covered glaciers showed deglaciation at the rate of 0.59% per annum from 1994 to 2015. The total area occupied by glacier extent was about 25% of the total basin in the year 1994, 23% in the year 2006 and 17% in the year 2015. HIGHLIGHTS Mapped clean glaciers using automatic glacier extraction index.; Mapped debris-covered glaciers by intersecting slope and LST layers.; Detected shrinkage in glacier surface area during the analysis period.; Found higher shrinkage rate in the recent period than the older period.; Observed increase in count of glaciers due to fragmentation.;

The glaciers in southeastern Tibet Plateau (SETP) influenced by oceanic climate are sensitive to global warming, and there remains a notable deficiency in accurate multitemporal change analyses of these glaciers. We conduct glacier inventories in the Yigong Zangbo River Basin (YZRB) in SETP for the years 1988, 2015, and 2023 utilizing Landsat and Sentinel-2 imagery, and analyze the glacier spatiotemporal variation incorporating the existing glacier inventory data. Since the 1970s until 2023, the glaciers significantly retreated at a rate of 0.76 ± 0.11%·a−1, with the area decreasing from 2583.09 ± 88.80 km2 to 1635.89 ± 71.74 km2, and the ice volume reducing from 221.7017 ± 7.9618 km3 to 152.7429 ± 6.1747 km3. The most significant retreat occurred in glaciers smaller than 1 km2. Additionally, glaciers on southern aspects retreated slower than the northern counterparts. The glaciers in the western YZRB witnessed a significantly greater shrinkage rate than those in the eastern section, with the most pronounced changes occurring in Aso Longbu River Basin. Furthermore, severe glacier mass deficits were observed from 2000 to 2019, averaging a loss rate of 0.57 ± 0.06 m w.e. a−1. The continuous rise in air temperature has primarily induced a general widespread glacier change in the YZRB. However, diverse topography led to spatial variability in glacier changes with discrepancies as large as several times. The features of individual glaciers, such as glacier size, debris cover, and the development of ice-contact glacial lakes enhanced the local complexity of glacier change and elusive response behaviors to climate warming led by the different topographic conditions.

With global warming, changes in glaciers and glacial lakes on the Tibetan Plateau call for a serious inspection. The Southeastern Tibetan Plateau (SETP) is a typical monsoonal marine glacier area that is extremely vulnerable to climate change. It is affected by both humid and warm Indian Ocean currents. Outlines of glaciers and glacial lakes in SETP have been extracted from Landsat satellite images with an automatic extraction method based on image compositing with Google Earth Engine and Random Forest algorithm. Alongside the outlines, meteorological data have been collected from 1990 to 2021. The results show that since 1990 the glacier area of SETP has retreated by about 2165.33 km2 (~25.28%), the glacial lake area has increased by about 36.41 km2 (~21.45%), and their number has increased by 477 (~27.32%). The reliability and scientific validity of this study is proven by comparison with existing glacier inventories. By analyzing the meteorological data, the inverse correlation between the glacier area and temperature has been found. Despite decreases in cumulative precipitation, the glacial lake level rise and consequent area expansion have been observed. A fitting equation for the response pattern of glacier changes to temperature and precipitation change is presented and will provide a basis for future studies. [ABSTRACT FROM AUTHOR]

Debris-covered ice is widespread in mountain regions with debris an important control on surface ice melt and glacier retreat. Quantifying debris cover extent and its evolution through time over large regions remains a challenge. This study develops two Normalized Difference Supraglacial Debris Indices for mapping debris-covered ice based on thermal and near Infrared Landsat 8 bands. They were calibrated with field data. Validation suggests that they have a high level of accuracy. They are then applied to Landsat data for 2016 to produce the first detailed glacier inventory of the Afghanistan Hindu Kush Himalaya that includes debris cover. 3408 glaciers were identified which, for those ⩾0.01 km2 in area, gives an ice cover of 2,222 ± 11 km2 and a debris cover of 619 ± 40 km2. Principal components analysis was used to identify the most influential drivers of debris-covered ice extent. Lower proportions of debris cover were associated with glaciers with a higher elevation range, that were larger, longer and wider. These relations were statistically clearer when the dataset was broken down into climate and geological zones. A glaciers continue to shrink, the proportion of debris cover will become higher, making it more important to map debris cover reliably.

Himalayan glaciers have been shrinking and losing mass rapidly since 1970s with an enhanced rate after 2000. The shrinkage is, however, quite heterogeneous and it is important to document individual glacier characteristics and their changes at the basin scale. We present an updated glacier inventory of the Upper Alaknanda Basin (UAB), Central Himalaya for the year 2020 and report area, debris cover and length changes for the periods 1994–2006 and 2006–2020 based on remote-sensing data. We identified 198 glaciers, comprising an area of 354.6 ± 8.5 km2, and classified them according to their size and morphology. The glaciers of the basin lost 4.2 ± 2.9% (0.16 ± 0.11% a−1) of their frontal area (from 368.6 ± 9.2 to 353.0 ± 5.3 km2) from 1994 to 2020. The average retreat rate was higher in the period 2006–2020 (13.3 ± 1.8 m a−1) in comparison to 1994–2006 (9.3 ± 1.9 m a−1). However, the area change rate was similar for the two periods (0.14 ± 0.27% a−1 for 1994–2006 and 0.16 ± 0.19% a−1 for 2006–2020). The debris-covered area has increased by 13.4 ± 4.4% from 1994 to 2020. A comparison with previous studies in UAB indicates consistent area loss of ~0.15% a−1 since the 1960s.

Alpine glaciers are a fundamental component of the cryosphere and are significantly sensitive to climate change. One such region is the Hindukush Karakoram Himalaya (HKH) and Tibetan Plateau (TP) region, which contains more than 40,000 glaciers. There are more than 12 glacier inventories available covering parts of (or the entire) HKH region, but these show significant uncertainties regarding the extent of glaciers. Researchers have used different glacier inventories without assessing their accuracy. This study, therefore, assessed the implications of the accuracy of global glacier inventories in hydrological modeling and future water resource planning. The accuracy assessment of most commonly used two global glacier inventories (Global Land Ice Monitoring from Space-GLIMS v 2.0 and Randolph Glacier Inventory-RGI v 6.0) has been carried out for three sub-basins of the Upper Indus Basin—the Swat, the Chitral, and the Kabul River basins (combined, this is referred to as the Great Kabul River Basin)—with a total basin area of 94,552.86 km2. Glacier outlines have been compared with various Landsat 7 ETM+, Landsat 8, high-resolution Google Earth images, and manually digitized debris-covered glacier outlines during different years. The total glacier area for the Great Kabul River Basin derived from RGI and GLIMS is estimated to be 2120.35 km2 and 1789.94 km2, respectively, which was a difference of 16.9%. Despite being sub-basins of the Great Kabul River Basin, the Swat, and the Chitral River basins were different by 54.74% and 19.71%, respectively, between the two inventories, with a greater glacierized area provided by RGI, whereas the Kabul River basin was different by 54.72%, with greater glacierized area provided by GLIMS. The results and analysis show that GLIMS underestimates glacier outlines in the Swat and the Chitral basins and overestimates glacier extents in the Kabul River basin. The underestimation is mainly due to the non-representation of debris-covered glaciers. The overestimation in GLIMS data is due to the digitization of seasonal snow as part of the glaciers. The use of underestimated GLIMS outlines may result in 5–10% underestimation of glacier-melt contribution to flows in the Swat River basin, while an underestimation of 7% to 15% is expected in the Chitral River Basin, all compared to RGI v 6.0 outlines. The overestimation of glacier-melt contribution to flows in the Kabul River basin is insignificant (1% to 2%) using GLIMS data. In summary, the use of the GLIMS inventory will lead to underestimated flows and show that the Great Kabul River Basin (particularly the Chitral River Basin) is less sensitive to climate change effects. Thus, the current study recommends the use of RGI v 6.0 (best glacier inventory) to revisit the existing biased hydro-climate studies and to improve future hydro-climate studies with the concomitant rectification of the MODIS snow coverage data. The use of the best glacier inventory will provide the best estimates of flow sensitivity to climate change and will result in well-informed decision-making, precise and accurate policies, and sustainable water resource management in the study area. The methodology adopted in the current study may also be used in nearby areas with similar hydro-climate conditions, as well as for the most recently released RGI v 7.0 data. [ABSTRACT FROM AUTHOR]

Debris-covered ice is widespread in mountain regions with debris an important control on surface ice melt and glacier retreat. Quantifying debris cover extent and its evolution through time over large regions remains a challenge. This study develops two Normalized Difference Supraglacial Debris Indices for mapping debris-covered ice based on thermal and near Infrared Landsat 8 bands. They were calibrated with field data. Validation suggests that they have a high level of accuracy. They are then applied to Landsat data for 2016 to produce the first detailed glacier inventory of the Afghanistan Hindu Kush Himalaya that includes debris cover. 3408 glaciers were identified which, for those ⩾0.01 km2 in area, gives an ice cover of 2,222 ± 11 km2 and a debris cover of 619 ± 40 km2. Principal components analysis was used to identify the most influential drivers of debris-covered ice extent. Lower proportions of debris cover were associated with glaciers with a higher elevation range, that were larger, longer and wider. These relations were statistically clearer when the dataset was broken down into climate and geological zones. A glaciers continue to shrink, the proportion of debris cover will become higher, making it more important to map debris cover reliably. [ABSTRACT FROM AUTHOR]

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock–ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate–cryosphere–hydrology–hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze–thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole.

The Destination Earth (DestinE) European initiative has recently brought into the scientific community the concept of the Digital Twin (DT) applied to Earth Sciences. Within 2030, a very high precision digital model of the Earth, continuously fed and powered by Earth Observation (EO) data, will provide as many digital replicas (DTs) as the different domains of the earth sciences are. Considering that a DT is driven by use cases, depending on the selected application, the provided information has to change. It follows that, to achieve a reliable representation of the selected use case, a reasonable and complete a priori definition of the needed elements that DT must contain is mandatory. In this work, we define a possible theoretical framework for a future DT of the Italian Alpine glaciers, trying to define and describe all those information (both EO and in situ data) and relationships that necessarily have to enter the process as building blocks of the DT itself. Two main aspects of glaciers were considered and investigated: (i) the "metric quantification" of their spatial dynamics (achieved through measures) and (ii) the "qualitative (semantic) description" of their health status as definable through observations from domain experts. After the first identification of the building blocks, the work proceeds focusing on existing EO data sources providing their essential elements, with specific focus on open access high-resolution (HR) and very-high-resolution (VHR) images. This last issue considered two scales of analysis: local (single glacier) and regional (Italian Alps). Some considerations were furtherly reported about the expected glaciers-related applications enabled by the availability of a DT at regional level. Applications involving both metric and semantic information were considered and grouped in three main clusters: Glaciers Evolution Modelling (GEM), 4D Multi Reality, and Virtual Reality. Limitations were additionally explored, mainly related to the technical characteristics of available EO VHR open data and some conclusions provided. [ABSTRACT FROM AUTHOR]

Himalayan glaciers have been shrinking and losing mass rapidly since 1970s with an enhanced rate after 2000. The shrinkage is, however, quite heterogeneous and it is important to document individual glacier characteristics and their changes at the basin scale. We present an updated glacier inventory of the Upper Alaknanda Basin (UAB), Central Himalaya for the year 2020 and report area, debris cover and length changes for the periods 1994–2006 and 2006–2020 based on remote-sensing data. We identified 198 glaciers, comprising an area of 354.6 ± 8.5 km2, and classified them according to their size and morphology. The glaciers of the basin lost 4.2 ± 2.9% (0.16 ± 0.11% a−1) of their frontal area (from 368.6 ± 9.2 to 353.0 ± 5.3 km2) from 1994 to 2020. The average retreat rate was higher in the period 2006–2020 (13.3 ± 1.8 m a−1) in comparison to 1994–2006 (9.3 ± 1.9 m a−1). However, the area change rate was similar for the two periods (0.14 ± 0.27% a−1 for 1994–2006 and 0.16 ± 0.19% a−1 for 2006–2020). The debris-covered area has increased by 13.4 ± 4.4% from 1994 to 2020. A comparison with previous studies in UAB indicates consistent area loss of ~0.15% a−1 since the 1960s. [ABSTRACT FROM AUTHOR]

The study of glaciers in remote regions improves our understanding of global glacier change. With an area of 149.31 ± 1.84 km2, the Santa Inés Icefield constitutes one of the largest and least studied and explored glaciated areas of Southern Patagonia. We study the extent and glacier variations of the Santa Inés Icefield over the last 75 years, and we generate the most detailed glacier inventory to date of its 24 constituting glaciers. We estimate surface elevation changes between 2000 and 2014 using Shuttle Radar Topography Mission (SRTM) and TanDEM-X digital elevation models. Our results show a generalized trend of retreat, with a glacier area loss of −9.78 ± 1.52 km2 between 1998 and 2020, with annual rate increase from −0.15 ± 0.01 km2 a−1 (1998–2005) to −0.58 ± 0.10 km2 a−1 (2005–2020), and an average thinning of 0.60 ± 0.26 m a−1 (2σ) between 2000 and 2014. No clear correlation was found between retreat or thinning rates and Accumulation Area Ratio (AAR), terminus slope, aspect, or glacier type. While ERA5 reanalysis data shows no significant climatic trends in temperature or precipitation, a small warming trend below our detection record is the most likely cause of the observed retreat and thinning of the Santa Inés Icefield.

Glaciers in the Pamir are the water tower of arid Central Asia, and more than 50 million people depend on meltwater from them. Many studies have reported glacier changes in the Pamir, but the glacier inventories employed in the previous investigations are both outdated and lack comparability. In this study, we present a new multitemporal glacier inventory for the Pamir based primarily on the Landsat ETM+/OLI scenes from the period around 2000 and 2017. Glacier outlines in 2000 and 2017 were delineated manually using Landsat images, SRTM digital elevation model (DEM), and high-resolution Google Earth images, using the same criteria and methods. We mapped 12,186 glaciers covering 10,396.20 ± 421.16 km2 in 2017 for the Pamir and demonstrated that the Pamir lost 124.28 ± 81.33 km2 of its glacier areas with a shrinkage rate of 1.17 ± 0.77 percent or 0.07 ± 0.05 percent·a−1 from 2000 to 2017. Based on the new inventories and the existing elevation change data sets of High Mountain Asia (HMA) from 2000 to 2016, we calculated a weaker glacier mass loss of −0.05 ± 0.06 m w.e. a−1. Spatial heterogeneity of glacier changes has been found in both the area and mass balance, but our results still suggest that the Pamir glaciers changed slightly since 2000.

Rock glaciers are an integral part of the periglacial environment. At the regional scale in the Greater Caucasus, there have been no comprehensive systematic efforts to assess the distribution of rock glaciers, although some individual parts of ranges have been mapped before. In this study we produce the first inventory of rock glaciers from the entire Greater Caucasus region—Russia, Georgia, and Azerbaijan. A remote sensing survey was conducted using Geo-Information System (GIS) and Google Earth Pro software based on high-resolution satellite imagery—SPOT, Worldview, QuickBird, and IKONOS, based on data obtained during the period 2004–2021. Sentinel-2 imagery from the year 2020 was also used as a supplementary source. The ASTER GDEM (2011) was used to determine location, elevation, and slope for all rock glaciers. Using a manual approach to digitize rock glaciers, we discovered that the mountain range contains 1461 rock glaciers with a total area of 297.8 ± 23.0 km2. Visual inspection of the morphology suggests that 1018 rock glaciers with a total area of 199.6 ± 15.9 km2 (67% of the total rock glacier area) are active, while the remaining rock glaciers appear to be relict. The average maximum altitude of all rock glaciers is found at 3152 ± 96 m above sea level (a.s.l.) while the mean and minimum altitude are 3009 ± 91 m and 2882 ± 87 m a.s.l., respectively. We find that the average minimum altitude of active rock glaciers is higher (2955 ± 98 m a.s.l.) than in relict rock glaciers (2716 ± 83 m a.s.l.). No clear difference is discernible between the surface slope of active (41.4 ± 3°) and relict (38.8 ± 4°) rock glaciers in the entire mountain region. This inventory provides a database for understanding the extent of permafrost in the Greater Caucasus and is an important basis for further research of geomorphology and palaeoglaciology in this region. The inventory will be submitted to the Global Land Ice Measurements from Space (GLIMS) database and can be used for future studies. [ABSTRACT FROM AUTHOR]

Knowledge about glacier extent, dynamics, and characteristics are important for climate change attribution and prediction. Understanding on long-term dynamics and glacier inventory is crucial, particularly for the melt-dominated and latitudinally-diverse western Himalayan glacier basins. In this study, a temporal inventory is prepared for Warwan-sub basin (WSB), utilizing satellite imageries since the 1993 (Landsat TM: 1993; ETM+: 2001, 2008; OLI: 2020) and elevation model (SRTM DEM: 2000). The base inventory was generated for the year 2001 and systematically adjusted to the glacier situations in 1993, 2008, and 2020. Results indicate that in the year 2001, WSB in the western Himalaya included 84 glaciers (> 0.02 km2) covering an area of 187.9 ± 5.8 km2. The mapping (2001) further revealed a supraglacial debris cover of 15% of the glacierized area (28.2 ± 0.9 km2). Overall, the debris cover increased by 6% between 1993 and 2020. Temporal analyses clearly suggest a period of gain in the glacierized area (2001–2008) interspersed by the two phases of decline (1993–2001 and 2008–2020). Results specify a stronger decline in the glacierized area during 1993 to 2001 (197.03 ± 6.1 to 187.9 ± 5.8 km2) than between 2008 and 2020 (188.4 ± 5.9 to 182.8 ± 5.66 km2). Remarkably, the glacierized area increased from 187.9 ± 5.8 to 188.4 ± 5.8 km2 during 2001 to 2008. In view of widespread recession of regional glaciers, the gain in the area between 2001 and 2008 represents a peculiar characteristic of WSB that needs further detailed investigation. Further analyses suggest that low-altitude, east-facing, debris-free, steep-sloped, and small glaciers experienced greater loss in the area than large, debris-covered, north-facing, gently sloped, and high-altitude glaciers. Overall, the study at the sub-basin scale reveals inherent glacier dynamics with periodic increase and decrease in the glacierized area and a notable influence of non-climatic factors in regulating spatial heterogeneity and the rate of glacier changes. [ABSTRACT FROM AUTHOR]

The significant retreat of glaciers in terms of climate change compels researchers to increase the frequency of studies regarding the transformations occurring in glacier boundaries. In this study, we provided glacier area delineation of Ala-Archa valley glaciers by using a Sentinel-1 SAR dataset and the InSAR Coherence technique. Since glaciers have specific patterns of movement, the low coherence method signals the presence of ice. The analysis used the pair of Sentinel-1 datasets for the summer, to ensure the lowest coherence and provide an areal estimation during the peak of ablation. The independence of the SAR images from cloud and light conditions permits us to acquire the images in a timely manner, which highly affects the results of glacier monitoring. This method has shown high potential in the mapping of debris-covered ice and the indication of dead ice. To identify and separate areas of low coherence, such as glacier lakes and unstable slopes, we used object-based mapping by using the geomorphological features of the ice. In this study, we defined a coherence value of less than 0.3 in the glacier area. Our research identified a number of 56 glaciers within the study area of 31.45 km2 and obtained highly accurate glacier maps for the glaciers with a smooth terminus. The analysis shows that automatic and manual delineation of the glaciers' boundaries have certain limitations, but using the advantages of both scientific approaches, further studies will generate more accurate results. [ABSTRACT FROM AUTHOR]

Here, we present a detailed analysis of glaciers in the Alaknanda Basin, Central Himalaya, starting with a novel glacier inventory for 1968 and 2020 using high-resolution datasets of Corona and Sentinel-2A. Primarily, we examine the factors influencing changes in glacier characteristics. Results show that glacier area reduced to 683 ± 47.81 km² from 742 ± 44.4 km2, and the number of glaciers increased to 116 from 98 between 1968 and 2020. The annual average recession of glaciers in the basin is 11.75 ± 1.6 m/ year for the corresponding period. Also noted is a significant increase (∼38%) in supraglacial debris cover extent of the glaciers during 2000–2020. Interestingly, smaller glaciers (< 5 km² ) with lower altitude snout and higher slope have registered more significant area loss and higher retreat rate. Alongside topographic parameters, the significant deglaciation and fragmentation observed in the basin are augmented by the increase in wintertime temperature (0.03 C/year) between 1968 and 2020. [ABSTRACT FROM AUTHOR]

Monitoring of glaciers of the Subansiri River Basin, regardless of geopolitical distribution, is pivotal, as the Subansiri River is one of the most important tributaries of the Brahmaputra River. However, the existing inventories in Eastern Himalayas mostly covered the Indian side, while most of the glacier regions are located in Tibet. For the first time, we constructed a complete, validated glacier and lake inventory using Landsat satellite data. We report 390 glaciers, where 191 are hanging glaciers, 59 ice aprons, 52 cirques, 40 niches, 37 valley glaciers, 9 icecaps and 2 outlet glaciers. The snow‐covered region occupies 0.96% of the total basin area. The study also reports that there are 52 glacial lakes, covering a cumulative area of 3.358 km2. Furthermore, the 37 valley glaciers cover an area of ~144 km2, with lengths ranging between 1.3 and 15.3 km, and a total ice reserve of ~11.95 km3. The largest glacier of the basin is the Daisaphu Glacier, which has an ice reserve of ~2.70 km3. We calculated the retreat of the Daisaphu Glacier to be 16 ma−1 between 1989 and 2014. However, the retreat has been seen to be enhanced, up to 21 ma−1 after 2009. We also estimated the recession rate of 27 other valley glaciers, apart from the Daisaphu Glacier. The recession rate of the glaciers ranges between 2 and 51 ma−1, where 30% of glaciers have retreated at a rate of <10 ma−1, 55% of glaciers have retreated at a rate of >10 ma−1 and 15% of glaciers show no frontal changes since 1985. The pro‐glacial moraine‐dammed lake of the Daisaphu glacier shows growth of 0.471 km2 in area, and an increase of 0.0833 km3 in water volume between 1978 and 2014. This inventory should help in the assessment of future water scenarios and climate change, as it will impact a large community downstream which is dependent on the glaciers which lie across two countries. [ABSTRACT FROM AUTHOR]

Alpine glaciers are a fundamental component of the cryosphere and are significantly sensitive to climate change. One such region is the Hindukush Karakoram Himalaya (HKH) and Tibetan Plateau (TP) region, which contains more than 40,000 glaciers. There are more than 12 glacier inventories available covering parts of (or the entire) HKH region, but these show significant uncertainties regarding the extent of glaciers. Researchers have used different glacier inventories without assessing their accuracy. This study, therefore, assessed the implications of the accuracy of global glacier inventories in hydrological modeling and future water resource planning. The accuracy assessment of most commonly used two global glacier inventories (Global Land Ice Monitoring from Space-GLIMS v 2.0 and Randolph Glacier Inventory-RGI v 6.0) has been carried out for three sub-basins of the Upper Indus Basin—the Swat, the Chitral, and the Kabul River basins (combined, this is referred to as the Great Kabul River Basin)—with a total basin area of 94,552.86 km2. Glacier outlines have been compared with various Landsat 7 ETM+, Landsat 8, high-resolution Google Earth images, and manually digitized debris-covered glacier outlines during different years. The total glacier area for the Great Kabul River Basin derived from RGI and GLIMS is estimated to be 2120.35 km2 and 1789.94 km2, respectively, which was a difference of 16.9%. Despite being sub-basins of the Great Kabul River Basin, the Swat, and the Chitral River basins were different by 54.74% and 19.71%, respectively, between the two inventories, with a greater glacierized area provided by RGI, whereas the Kabul River basin was different by 54.72%, with greater glacierized area provided by GLIMS. The results and analysis show that GLIMS underestimates glacier outlines in the Swat and the Chitral basins and overestimates glacier extents in the Kabul River basin. The underestimation is mainly due to the non-representation of debris-covered glaciers. The overestimation in GLIMS data is due to the digitization of seasonal snow as part of the glaciers. The use of underestimated GLIMS outlines may result in 5–10% underestimation of glacier-melt contribution to flows in the Swat River basin, while an underestimation of 7% to 15% is expected in the Chitral River Basin, all compared to RGI v 6.0 outlines. The overestimation of glacier-melt contribution to flows in the Kabul River basin is insignificant (1% to 2%) using GLIMS data. In summary, the use of the GLIMS inventory will lead to underestimated flows and show that the Great Kabul River Basin (particularly the Chitral River Basin) is less sensitive to climate change effects. Thus, the current study recommends the use of RGI v 6.0 (best glacier inventory) to revisit the existing biased hydro-climate studies and to improve future hydro-climate studies with the concomitant rectification of the MODIS snow coverage data. The use of the best glacier inventory will provide the best estimates of flow sensitivity to climate change and will result in well-informed decision-making, precise and accurate policies, and sustainable water resource management in the study area. The methodology adopted in the current study may also be used in nearby areas with similar hydro-climate conditions, as well as for the most recently released RGI v 7.0 data.

Glaciers are important sentinels of a changing climate, crucial components of the global cryosphere and integral to their local landscapes. However, many of the commonly used methods for mapping glacier change are labor-intensive and limit the temporal and spatial scope of existing research. This study addresses some of the limitations of prior approaches by developing a novel deep-learning-based method called GlacierCoverNet. GlacierCoverNet is a deep neural network that relies on an extensive, purpose-built training dataset. Using this model, we created a record of over three decades long at a fine temporal cadence (every two years) for the state of Alaska. We conducted a robust error analysis of this dataset and then used the dataset to characterize changes in debris-free glaciers and supraglacial debris over the last ~35 years. We found that our deep learning model could produce maps comparable to existing approaches in the capture of areal extent, but without manual editing required. The model captured the area covered with glaciers that was ~97% of the Randolph Glacier Inventory 6.0 with ~6% and ~9% omission and commission rates in the southern portion of Alaska, respectively. The overall model area capture was lower and omission and commission rates were significantly higher in the northern Brooks Range. Overall, the glacier-covered area retreated by 8425 km2 (−13%) between 1985 and 2020, and supraglacial debris expanded by 2799 km2 (64%) during the same period across the state of Alaska. [ABSTRACT FROM AUTHOR]

Glaciers in the Himalayan arc are receding rapidly in the eastern and western parts as compared to other regions. Contrararily, the glaciers in the Trans-Himalayan region of Ladakh are comparatively stable. The differential retreat could be due to various climatic, topographic, and geologic influences. The use of multi-source remotely sensed imagery from open-source platforms and the GlabTop model has been discussed in this paper. This paper draws insights from a recently published paper which details the recession of 87 glaciers in the Trans Himalayan region of Ladakh using remote sensing data [1]. The use of remote sensing data from USGS and Planet Labs for assessing glacier area changes, frontal retreat, debris cover, topographic characteristics, and comparison with existing inventories has been discussed in this study. The geodetic mass changes have been assessed using SRTM and TanDEM-X of 2000 and 2012 respectively. The use of remotely sensed data discussed in this article will help glaciologists to better characterize and understand the glacier recession in the region. The GlabTop model has been used to simulate proglacial lake expansion to understand glacier-bed overdeepenings of four glaciers in the region. The GlabTop simulations will help disaster managers to better quantify the vulnerability and risk of downstream population and infrastructure to Glacial Lake Outburst Floods (GLOFs).

Mountain glaciers are an important component of the global hydrological cycle. Existing research about glacier changes in the Altai focused on limited regions. Study about recent glacier changes in the entire Altai Mountains is still lacking. We presented a consistent method for identifying glacier margins. The two new glacier inventories in 2000 and 2020 were derived from Landsat satellite imagery. Glacier surface elevation change and mass balance were obtained by comparing the 2000 Shuttle Radar Topography Mission (SRTM) and 2020 Digital Elevation Models (DEMs) generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. The spatial pattern of glacier changes was discussed in conjunction with climate trends. We mapped a total area of 1,096.06 ± 53.32 km2 around 2020, which amounts to 1,927 glaciers in the Altai Mountains. That was 12.02 ± 3.01% (or 0.60 ± 0.15%·a−1) less than the 1,245.75 ± 58.52 km2 around 2000. The geodetic mass balance of the monitoring glaciers in the Aktru basin for the period 2000–2011 was used to validate the geodetic survey. The average geodetic mass balance of -0.32 ± 0.09 m w. e.·a−1 on monitoring glaciers was slightly exaggerated than the observed mass balance of -0.26 m w. e.·a−1, but it was proved that the geodetic mass balance could reflect glacier changes in the Altai Mountains. An average mass loss of 14.55 ± 1.32 m w. e. (or 0.74 ± 0.07 m w. e.·a−1) was found during 2000–2020 in the Altai Mountains. Although the glacier area changes and mass balance were characterized by spatial heterogeneity, the glaciers in the Altai had experienced an accelerated shrinkage from 2000 to 2020 compared to the 20th century. The rising temperature is the foremost reason for glacier area shrinkage and mass loss according to the Climatic Research Unit (CRU) reanalysis data.

The Destination Earth (DestinE) European initiative has recently brought into the scientific community the concept of the Digital Twin (DT) applied to Earth Sciences. Within 2030, a very high precision digital model of the Earth, continuously fed and powered by Earth Observation (EO) data, will provide as many digital replicas (DTs) as the different domains of the earth sciences are. Considering that a DT is driven by use cases, depending on the selected application, the provided information has to change. It follows that, to achieve a reliable representation of the selected use case, a reasonable and complete a priori definition of the needed elements that DT must contain is mandatory. In this work, we define a possible theoretical framework for a future DT of the Italian Alpine glaciers, trying to define and describe all those information (both EO and in situ data) and relationships that necessarily have to enter the process as building blocks of the DT itself. Two main aspects of glaciers were considered and investigated: (i) the “metric quantification” of their spatial dynamics (achieved through measures) and (ii) the “qualitative (semantic) description” of their health status as definable through observations from domain experts. After the first identification of the building blocks, the work proceeds focusing on existing EO data sources providing their essential elements, with specific focus on open access high-resolution (HR) and very-high-resolution (VHR) images. This last issue considered two scales of analysis: local (single glacier) and regional (Italian Alps). Some considerations were furtherly reported about the expected glaciers-related applications enabled by the availability of a DT at regional level. Applications involving both metric and semantic information were considered and grouped in three main clusters: Glaciers Evolution Modelling (GEM), 4D Multi Reality, and Virtual Reality. Limitations were additionally explored, mainly related to the technical characteristics of available EO VHR open data and some conclusions provided.

Rock glaciers are an integral part of the periglacial environment. At the regional scale in the Greater Caucasus, there have been no comprehensive systematic efforts to assess the distribution of rock glaciers, although some individual parts of ranges have been mapped before. In this study we produce the first inventory of rock glaciers from the entire Greater Caucasus region—Russia, Georgia, and Azerbaijan. A remote sensing survey was conducted using Geo-Information System (GIS) and Google Earth Pro software based on high-resolution satellite imagery—SPOT, Worldview, QuickBird, and IKONOS, based on data obtained during the period 2004–2021. Sentinel-2 imagery from the year 2020 was also used as a supplementary source. The ASTER GDEM (2011) was used to determine location, elevation, and slope for all rock glaciers. Using a manual approach to digitize rock glaciers, we discovered that the mountain range contains 1461 rock glaciers with a total area of 297.8 ± 23.0 km2. Visual inspection of the morphology suggests that 1018 rock glaciers with a total area of 199.6 ± 15.9 km2 (67% of the total rock glacier area) are active, while the remaining rock glaciers appear to be relict. The average maximum altitude of all rock glaciers is found at 3152 ± 96 m above sea level (a.s.l.) while the mean and minimum altitude are 3009 ± 91 m and 2882 ± 87 m a.s.l., respectively. We find that the average minimum altitude of active rock glaciers is higher (2955 ± 98 m a.s.l.) than in relict rock glaciers (2716 ± 83 m a.s.l.). No clear difference is discernible between the surface slope of active (41.4 ± 3°) and relict (38.8 ± 4°) rock glaciers in the entire mountain region. This inventory provides a database for understanding the extent of permafrost in the Greater Caucasus and is an important basis for further research of geomorphology and palaeoglaciology in this region. The inventory will be submitted to the Global Land Ice Measurements from Space (GLIMS) database and can be used for future studies.

Changes in glacier resources and their meltwater runoff contributions in Xinjiang are significant to the hydrological processes and water resources utilization. This study used the first and second Chinese Glacier Inventory, geomorphological and meteorological data. GIS spatial analysis technology was used to explore the characteristics of glacier change and its response to topography and climate change in Xinjiang in the last 50 years. The results show that there are currently 20,695 glaciers in Xinjiang with a total area of 22,742.55 km2 and ice reserves of about 2229.17 km3. Glaciers in Xinjiang are concentrated at 5100–6000 m. The Tianshan mountains have the largest number of glaciers. However, the Kunlun mountains have the largest glaciers and ice reserves. The scale of glaciers is significantly larger in the south than that in the north. The changes in glaciers in Xinjiang during the last 50 years are mainly receding and splitting, and their number, area, and ice reserves have decreased by 1359, 7080.12 km2 and 482.65 km3, respectively. Small glaciers are more sensitive to climate change. Glaciers are basically unchanged in regions above 6000 m. The glaciers on the south slope of mountains are more susceptible to climate change. The phenomenon of an increase in the number of glaciers but decreasing total area in the southern mountains is related to glacier extinction and splitting. Glacier development and formation are determined by the combination of topography and hydrothermal material conditions. The change of glacier areas in Xinjiang is jointly affected by climatic conditions (53.45%) and topographic conditions (46.55%), among which climatic conditions are more prominent. [ABSTRACT FROM AUTHOR]

A glacier inventory contains data that are important for understanding the hydrology, water resources, and impacts of climate change in glaciated regions. Ten glacier inventories have been created for the Third Pole Region (TPR) or high-mountain Asia, but they vary largely in spatial coverage area and data quality. Therefore, it is necessary to assess the data quality to help potential users choose the right glacier inventories for their research. Using the analytical hierarchy process, this study selects eight assessment factors and quantifies the quality of eight glacier inventories of the TPR. The eight glacier inventories that we assessed are the Randolph Glacier Inventory (RGI), the Glacier Area Mapping for Discharge in Asian Mountains (GGI18), the Second Chinese Glacier Inventory (CGI-2), the Glacier Inventory of the Hindu Kush–Himalayan Region (HKHGI), the Glacier Inventory for the Western Himalayas (WHGI), the Glacier Inventory for the Karakoram and Pamir Region (KPGI), the Second Glacier Inventory of Pakistan (PGI-2) and the Glacier Inventory for the Southeastern Tibetan Plateau (SETPGI). The assessment results indicate that the overall quality of the small-scale glacier inventories of WHGI, KPGI, PGI-2, and SETPGI is higher than that of the large-scale inventories of RGI, GGI18, CGI-2, and HKHGI. For the large-scale inventories, the quality-ranking order from high to low is CGI-2, GGI18, RGI, and HKHGI. However, the comprehensive quality of CGI-2 and GGI18 is comparable over the area covered by CGI-2. The comprehensive quality of CGI-2, GGI18, and RGI exhibits clear spatial differences. Overall, the data quality is higher for the inner TPR than for the surrounding areas. By merging the products of the eight glacier inventories, a new glacier inventory product of the best comprehensive quality was derived for the entire TPR. This new product resembles the spatial distribution of the best-quality glacier inventories of the regions where the different products overlap. In terms of specific regions, the CGI-2 and GGI18 are the best products for most parts of the TPR in China, except for an area of southeastern Tibet where the highest-quality data are from the SETPGI. The other main distributions of the best products are the WHGI for the western Himalayas, the GGI18 and HKHGI for the Hindu Kush and the middle and eastern Himalayas, the PGI-2 for Pakistan, the KPGI for the Karakorum–Pamir area, and the GGI18 and CGI-2 for the Tianshan Mountains. The new data product greatly promotes the quality of a single glacier inventory for the entire TPR. This database will meet the needs of a variety of potential researchers, including those who prefer to get information for a particular parameter from a single glacier inventory (http://data.tpdc.ac.cn/en/data).

The study of glaciers in remote regions improves our understanding of global glacier change. With an area of 149.31 ± 1.84 km², the Santa Inés Icefield constitutes one of the largest and least studied and explored glaciated areas of Southern Patagonia. We study the extent and glacier variations of the Santa Inés Icefield over the last 75 years, and we generate the most detailed glacier inventory to date of its 24 constituting glaciers. We estimate surface elevation changes between 2000 and 2014 using Shuttle Radar Topography Mission (SRTM) and TanDEM-X digital elevation models. Our results show a generalized trend of retreat, with a glacier area loss of -9.78 ± 1.52 km² between 1998 and 2020, with annual rate increase from -0.15 ± 0.01 km2 a-1 (1998-2005) to -0.58 ± 0.10 km² a-1 (2005-2020), and an average thinning of 0.60 ± 0.26 m a-1 (2s) between 2000 and 2014. No clear correlation was found between retreat or thinning rates and Accumulation Area Ratio (AAR), terminus slope, aspect, or glacier type. While ERA5 reanalysis data shows no significant climatic trends in temperature or precipitation, a small warming trend below our detection record is the most likely cause of the observed retreat and thinning of the Santa Inés Icefield. [ABSTRACT FROM AUTHOR]

Glaciers depicted on old maps reveal their historical extents, before the advent of aerial and satellite remote sensing. Digital glacier inventories produced from these maps can be employed in assessments of centennial-scale glacier change. This study reconstructs the ~1899 (covering the period 1882–1916) glacier extent in Nordland, northern Norway, from historical gradteigskart maps, with an emphasis on examining the accuracy of the mapped glaciers. Glacier outlines were digitised from georectified scans of the analogue maps in a raster graphics editor and were subsequently inventoried in a GIS. The accuracy of the historical glacier extent was established from written descriptions and landscape photographs created during the original field surveys, and further validated against independent glacier outlines of (1) the maximum Little Ice Age extent derived from geomorphological evidence, and (2) the 1945 extent derived from vertical aerial photographs. An overall uncertainty of ±17% is associated with our inventory. Nordland's glaciers covered an area of 1712 ± 291 km2 in 1899. By 2000, total ice cover had decreased by 47% (807 ± 137 km2) at a rate of 6% 10 a−1 (80 ± 14 km2 10 a−1). The approach presented here may serve as a blueprint for future studies intending to derive glacier inventories from historical maps.

The significant retreat of glaciers in terms of climate change compels researchers to increase the frequency of studies regarding the transformations occurring in glacier boundaries. In this study, we provided glacier area delineation of Ala-Archa valley glaciers by using a Sentinel-1 SAR dataset and the InSAR Coherence technique. Since glaciers have specific patterns of movement, the low coherence method signals the presence of ice. The analysis used the pair of Sentinel-1 datasets for the summer, to ensure the lowest coherence and provide an areal estimation during the peak of ablation. The independence of the SAR images from cloud and light conditions permits us to acquire the images in a timely manner, which highly affects the results of glacier monitoring. This method has shown high potential in the mapping of debris-covered ice and the indication of dead ice. To identify and separate areas of low coherence, such as glacier lakes and unstable slopes, we used object-based mapping by using the geomorphological features of the ice. In this study, we defined a coherence value of less than 0.3 in the glacier area. Our research identified a number of 56 glaciers within the study area of 31.45 km2 and obtained highly accurate glacier maps for the glaciers with a smooth terminus. The analysis shows that automatic and manual delineation of the glaciers’ boundaries have certain limitations, but using the advantages of both scientific approaches, further studies will generate more accurate results.

Glaciers in Switzerland are shrinking rapidly in response to ongoing climate change. Repeated glacier inventories are key to monitor such changes at the regional scale. Here we present the new Swiss Glacier Inventory 2016 (SGI2016) that has been acquired based on sub-meter resolution aerial imagery and digital elevation models, bringing together topographical and glaciological approaches and knowledge. We define the process, workflow and required glaciological adaptations to compile a highly detailed inventory based on the digital Swiss Topographic Landscape model. The SGI2016 provides glacier outlines (areas), supraglacial debris cover and ice divides for all Swiss glaciers referring to the years 2013–2018. The SGI2016 maps 1,400 individual glacier entities with a total surface area of 961 ± 22 km2, whereof 11% (104 km2) are debris-covered. It constitutes the so far most detailed cartographic representation of glacier extent in Switzerland. Interpretation in the context of topographic parameters indicates that glaciers with moderate inclination and low median elevation tend to have highest fractions of supraglacial debris. Glacier-specific area changes since 1973 show the largest relative changes for small and low-elevation glaciers. The analysis further indicates a tendency for glaciers with a high share of supraglacial debris to show larger relative area changes. Between 1973 and 2016, an area change rate of –0.6% a−1 is found. Based on operational data sets and the presented methodology, the Swiss Glacier Inventory will be updated in 6-yr time intervals, leading to a high consistency in future glacier change assessments.

Glaciers are important sentinels of a changing climate, crucial components of the global cryosphere and integral to their local landscapes. However, many of the commonly used methods for mapping glacier change are labor-intensive and limit the temporal and spatial scope of existing research. This study addresses some of the limitations of prior approaches by developing a novel deep-learning-based method called GlacierCoverNet. GlacierCoverNet is a deep neural network that relies on an extensive, purpose-built training dataset. Using this model, we created a record of over three decades long at a fine temporal cadence (every two years) for the state of Alaska. We conducted a robust error analysis of this dataset and then used the dataset to characterize changes in debris-free glaciers and supraglacial debris over the last ~35 years. We found that our deep learning model could produce maps comparable to existing approaches in the capture of areal extent, but without manual editing required. The model captured the area covered with glaciers that was ~97% of the Randolph Glacier Inventory 6.0 with ~6% and ~9% omission and commission rates in the southern portion of Alaska, respectively. The overall model area capture was lower and omission and commission rates were significantly higher in the northern Brooks Range. Overall, the glacier-covered area retreated by 8425 km2 (−13%) between 1985 and 2020, and supraglacial debris expanded by 2799 km2 (64%) during the same period across the state of Alaska.

The study evaluates the global glacier inventories available for the study area viz., RGI, GAMDAM and ICIMOD, with the newly generated Kashmir University Glacier Inventory (KUGI) for three Himalaya basins; Jhelum, Suru and Chenab in the north-western Himalaya, comprising of 2096 glaciers spread over an area of 3300 km². The KUGI was prepared from the Landsat data supplemented by Digital Elevation Model, Google Earth images and limited field surveys. The KUGI comprises of 154 glaciers in the Jhelum, 328 in the Suru and 1614 in the Chenab basin, corresponding to the glacier area of 85.9±11.4 km², 487±16.2 km² and 2727±90.2 km² respectively. The investigation revealed that most of the glaciers in the study area are <1 km² in size, however, the glaciers in 1-5 km² size class cover most (55.8%) of the glacier area. Majority of the glaciers, both in terms of number and area, are at 4500-5500 m asl except in the Jhelum where the glaciers are mostly situated between 4000-5000 m asl altitude. The glaciers in the three basins mainly harbor slopes ranging from 10-30°. It was also observed that the southern aspects host more number of large-sized glaciers than the northern aspects. Comparative analyses of the inventories revealed that the GAMDAM (??????=0.75) and RGI(??????=0.73) inventories are consistent with the KUGI. However, discrepancies were observed in the debris-covered and shadowed glaciers particularly in the ICIMOD inventory. The glacier elevation changes were also estimated for glaciers in the three basins using the Tandem-X and SRTM-C DEMs from 2000 to 2012. The investigation revealed a strong control of glacial morphology, topography, and debris cover on glacier thinning. Glacier elevation change of - 1.33±0.8 m a-1 was observed in the Jhelum basin but a similar glacier elevation changes of - 1.08±0.7 m a-1 and -1.09±0.8 m a-1 was observed in the Suru and Chenab basins respectively. Evaluation of the glacier inventories and assessment of glacier elevation change in the datascarce Himalaya, reported in this article, would constitute a reliable database for research particularly in hydrology, glaciology, and climate change. The dataset is freely available at http://doi.org/10.5281/zenodo.4461799 (Romshoo et al., 2021). [ABSTRACT FROM AUTHOR]

Mountain glaciers are useful climatic indicators in alpine regions where instrumental climate observations are sparse. Here we review the state of understanding of past and present glaciation in North Island, New Zealand. During the last glacial, mountain glaciers descended to ∼1200 m on both Ruapehu and Tongariro. Glacier modelling indicates that air temperatures during the Last Glacial Maximum were 5–7°C lower than present. Under such conditions, favourable topoclimatic mass balance processes (e.g. snowblow, shading) may have promoted marginal glaciation in lower-elevation North Island mountain ranges. The timing and magnitude of North Island glacier changes are broadly consistent with moraine chronologies and climatic reconstructions from glaciers in the Southern Alps. As of 2016, several glaciers and multi-year snow patches persist in North Island (totalling 3.0 km2 – a 25% reduction in area since 1988), all situated on the summit region of Ruapehu volcano. Mass balance of these glaciers is modulated by topoclimatic factors and debris cover, which may reduce rates of mass loss in the near term. However, given the proximity of the present equilibrium line altitude to the summit elevation of Ruapehu, complete loss of the present glaciers is probable under even moderate warming scenarios predicted for the coming decades. [ABSTRACT FROM AUTHOR]

Based on the recently released National Glacier Inventory (NGI), we analyzed the characteristics and the mass balance rates of ice masses in the Argentinean Central Andes (ca. 30°–37° S). The NGI provides unprecedented information on area, number and distribution of different ice masses, including debris-covered glaciers and rock glaciers. In the Central Andes, a number of 8,076 ice masses were identified covering a total area of 1767 km2. For the period 2000–2018, a general lowering of the ice surface was observed with a region-wide mass balance rate of −0.18 ± 0.19 m w.e. yr−1. Clear differences depending on the debris coverage of the different ice masses were identified, with mass balance rates ranging from −0.36 ± 0.19 m w.e. yr−1 for partly debris-covered glaciers to −0.02 ± 0.19 m w.e. yr−1 for rock glaciers. Considering different sub-periods, the region-wide mass balance rate was slightly positive (+0.12 ± 0.23 m w. e. yr−1) from 2000 to 2009 and negative (−0.21 ± 0.30 m w.e. yr−1) from 2009 to 2018. A comparison with the Randolph Glacier Inventory (RGI version 6.0) indicates that the NGI provides more detailed information regarding different type of ice masses whereas region-wide mass balance rates show limited sensitivity to the choice of the inventory. The inclusion of rock glaciers and “debris-covered ice with rock glacier” in the NGI causes mass balance rates to be slightly less negative than when using the RGI. Since the Central Andes are experiencing an unprecedented decade-long drought, our study provides crucial information to estimate current and future hydrological contribution of the different type of ice masses to river discharge in the arid subtropical Andes.

Changes in glacier resources and their meltwater runoff contributions in Xinjiang are significant to the hydrological processes and water resources utilization. This study used the first and second Chinese Glacier Inventory, geomorphological and meteorological data. GIS spatial analysis technology was used to explore the characteristics of glacier change and its response to topography and climate change in Xinjiang in the last 50 years. The results show that there are currently 20,695 glaciers in Xinjiang with a total area of 22,742.55 km2 and ice reserves of about 2229.17 km3. Glaciers in Xinjiang are concentrated at 5100–6000 m. The Tianshan mountains have the largest number of glaciers. However, the Kunlun mountains have the largest glaciers and ice reserves. The scale of glaciers is significantly larger in the south than that in the north. The changes in glaciers in Xinjiang during the last 50 years are mainly receding and splitting, and their number, area, and ice reserves have decreased by 1359, 7080.12 km2 and 482.65 km3, respectively. Small glaciers are more sensitive to climate change. Glaciers are basically unchanged in regions above 6000 m. The glaciers on the south slope of mountains are more susceptible to climate change. The phenomenon of an increase in the number of glaciers but decreasing total area in the southern mountains is related to glacier extinction and splitting. Glacier development and formation are determined by the combination of topography and hydrothermal material conditions. The change of glacier areas in Xinjiang is jointly affected by climatic conditions (53.45%) and topographic conditions (46.55%), among which climatic conditions are more prominent.

Glaciers depicted on old maps reveal their historical extents, before the advent of aerial and satellite remote sensing. Digital glacier inventories produced from these maps can be employed in assessments of centennial-scale glacier change. This study reconstructs the ~1899 (covering the period 1882–1916) glacier extent in Nordland, northern Norway, from historical gradteigskart maps, with an emphasis on examining the accuracy of the mapped glaciers. Glacier outlines were digitised from georectified scans of the analogue maps in a raster graphics editor and were subsequently inventoried in a GIS. The accuracy of the historical glacier extent was established from written descriptions and landscape photographs created during the original field surveys, and further validated against independent glacier outlines of (1) the maximum Little Ice Age extent derived from geomorphological evidence, and (2) the 1945 extent derived from vertical aerial photographs. An overall uncertainty of ±17% is associated with our inventory. Nordland's glaciers covered an area of 1712 ± 291 km2 in 1899. By 2000, total ice cover had decreased by 47% (807 ± 137 km2) at a rate of 6% 10 a−1 (80 ± 14 km2 10 a−1). The approach presented here may serve as a blueprint for future studies intending to derive glacier inventories from historical maps. [ABSTRACT FROM AUTHOR]

Based on the revised First Chinese Glacier Inventory (FCGI), the Second Chinese Glacier Inventory (SCGI) and Landsat OLI images for 2015–2016, we analyzed the spatial-temporal variation characteristics of glaciers in the Gangdisê Mountains from 1970 to 2016. The results showed that there were 3953 glaciers with a total area of 1306.45 km2 and ice volume of ~58.16 km3 in the Gangdisê Mountains in 2015–2016. Glaciers with sizes of 0.1–5 km2 and <0.5 km2 accounted for the largest area and the most amounts of glaciers in the Gangdisê Mountains, respectively. Over the past five decades, the area of glaciers in the Gangdisê Mountains decreased by 854.05 km2 (−1.09%a−1), accounting for 39.53% of the total glacier area in 1970. The increase in temperature during the ablation period was the most important cause for glacier retreat. Compared to other mountains in western China, the Gangdisê Mountains have experienced the strongest glacial retreat, and the rate of recession has increased in recent years. The decrease of glacier area was mainly concentrated at elevations of 5600–6100 m, and no change in glacier area was observed at elevations above 6500 m. The number and area of glaciers decreased in all orientations in the Gangdisê Mountains except for south- and southeast-oriented glaciers. Among them, north-oriented glaciers suffered the largest loss of glacier area, while glacier retreat saw the fastest in northwest-oriented glaciers. The rate of glacier retreat increased from west to east in the Gangdisê Mountains. The relative rate of glacier area change was the highest in the eastern section of the Gangdisê Mountains (−1.72%a−1), followed by the middle section (−1.67%a−1) and the western section (−0.83%a−1). [ABSTRACT FROM AUTHOR]

Changes in sizes of the Klyuchevskaya volcanic group's glaciers had been estimated for the period from 1949–1950 to 2010–2015 using results of analysis of current satellite imagery, data of field observations and historic records. Changes in front positions for some glaciers were analyzed for different periods of time. According to results of comparison between our data and similar ones from the Glacier Inventory the glacier areas decreased by 0.7%. Calculations made with corrected data demonstrated the total increase of the glaciation area by 4.3%. Glaciation of the Klyuchevskoy volcano is characterized by dynamic instability and significant changeability. The Erman glacier, the largest one in this region, did constantly advance since 1945. In 1949‑2015, its area at the front increased by 4.96±0.39 km2, while the front advanced along the valley of the Sukhaya River by approximately 3675±15 m and by 3480±20 m along the valley of the Krutenkaya River. A number of «wandering glaciers» located on the North‑Eastern and Eastern slopes of the volcano, on the contrary, significantly reduced their areas. At the same time, formation of new flows of ice is noticed within the «ice belt». Under the influence of active volcanic processes, the configuration of glacier boundaries on the slopes of Klyuchevskoy volcano does actively change in not only the tongue areas but also in the accumulation areas. Changes in dynamics of the glaciation areas of the Klyuchevskaya group of volcanoes don’t correspond to the present‑day climate changes. The interaction of modern volcanism and glaciation in the area as a whole is conducive to the preservation and development of glaciers, despite the deterioration of climatic conditions of their existence.

Knowledge on ice thickness distribution and total ice volume is a prerequisite for computing future glacier change for both glaciological and hydrological applications. Various ice thickness estimation methods have been developed but regional differences in fundamental model parameters are substantial. Parameters calibrated with measured data at specific points in time and space can vary when glacier geometry and dynamics change. This study contributes to a better understanding of accuracies and limitations of modeled ice thicknesses by taking advantage of a comprehensive data set of in-situ ice thickness measurements from 58 glaciers in the Austrian Alps and observed glacier geometries of three Austrian glacier inventories (GI) between 1969 and 2006. The field data are used to calibrate an established ice thickness model to calculate an improved ice thickness data set for the Austrian Alps. A cross-validation between modeled and measured point ice thickness indicates a model uncertainty of 25–31% of the measured point ice thickness. The comparison of the modeled and measured average glacier ice thickness revealed an underestimation of 5% with a mean standard deviation of 15% for the glaciers with calibration data. The apparent mass balance gradient, the primary model parameter accounting for the effects of surface mass balance distribution as well as ice flux, substantially decreases over time and has to be adjusted for each temporal increment to correctly reproduce observed ice thickness. This reflects the general stagnation of glaciers in Austria. Using the calibrated parameter set, 93% of the observed ice thickness change on a glacier-specific scale could be captured for the periods between the GI. We applied optimized apparent mass balance gradients to all glaciers of the latest Austrian glacier inventory and found a volume of 15.9 km3 for the year 2006. The ten largest glaciers account for 25% of area and 35% of total ice volume. An estimate based on mass balance measurements from nine glaciers indicates an additional volume loss of 3.5 ± 0.4 km3 (i.e., 22 ± 2.5%) until 2016. Relative changes in area and volume were largest at glaciers smaller than 1 km2, and relative volume changes appear to be higher than relative area changes for all considered time periods.