Comment on essd-2022-311

Differential surface melting of a debris-covered glacier and its geomorphological control — A case study from Batal Glacier, western Himalaya

Abstract. The Himalaya mountain range is characterized by highly glacierized, complex, dynamic topography. The ablation area of Himalayan glaciers often features a highly heterogeneous debris mantle comprising ponds, steep and shallow slopes of various aspects, variable debris thickness, and exposed ice cliffs associated with differing ice ablation rates. Understanding the composition of the supraglacial debris cover is essential for a proper understanding of glacier hydrology and glacier-related hazards. Until recently, efforts to map debris-covered glaciers from remote sensing focused primarily on glacier extent rather than surface characteristics and relied on traditional whole-pixel image classification techniques. Spectral unmixing routines, rarely used for debris-covered glaciers, allow decomposition of a pixel into constituting materials, providing a more realistic representation of glacier surfaces. Here we use linear spectral unmixing of Landsat 8 Operational Land Imager (OLI) images (30 m) to obtain fractional abundance maps of the various supraglacial surfaces (debris material, clean ice, supraglacial ponds and vegetation) across the Himalaya around the year 2015. We focus on the debris-covered glacier extents as defined in the database of global distribution of supraglacial debris cover. The spectrally unmixed surfaces are subsequently classified to obtain maps of composition of debris-covered glaciers across sample regions. We test the unmixing approach in the Khumbu region of the central Himalaya, and we evaluate its performance for supraglacial ponds by comparison with independently mapped ponds from high-resolution Pléiades (2 m) and PlanetScope imagery (3 m) for sample glaciers in two other regions with differing topo-climatic conditions. Spectral unmixing applied over the entire Himalaya mountain range (a supraglacial debris cover area of 2254 km2) indicates that at the end of the ablation season, debris-covered glacier zones comprised 60.9 % light debris, 23.8 % dark debris, 5.6 % clean ice, 4.5 % supraglacial vegetation, 2.1 % supraglacial ponds, and small amounts of cloud cover (2 %), with 1.2 % unclassified areas. The spectral unmixing performed satisfactorily for the supraglacial pond and vegetation classes (an F score of ∼0.9 for both classes) and reasonably for the debris classes (F score of 0.7). Supraglacial ponds were more prevalent in the monsoon-influenced central-eastern Himalaya (up to 4 % of the debris-covered area) compared to the monsoon-dry transition zone (only 0.3 %) and in regions with lower glacier elevations. Climatic controls (higher average temperatures and more abundant precipitation), coupled with higher glacier thinning rates and lower average glacier velocities, further favour pond incidence and the development of supraglacial vegetation. With continued advances in satellite data and further method refinements, the approach presented here provides avenues towards achieving large-scale, repeated mapping of supraglacial features.

<p indent="0mm">This dataset provides the latest glacier inventory for the southeastern Qinghai- Tibet Plateau based on multi-temporal Landsat images acquired during 2011 – 2014, L-band PALSAR data obtained during 2009 – 2010, and the modified SRTM (Shuttle Radar Topography Mission) Digital Elevation Model (DEM). Within the spatial extent of 28°N – 31°N and 92°E – 97°E, the region covers the central and eastern Nyainqêntanglha and western Hengduan mountains, with a total area of around <sc>115,000 km2.</sc> Three sub-datasets are provided: ① extent of the study region in shapefile format, ② glacier outlines in shapefile format, and ③ parameter statistics for each individual glacier. The parameters for each glacier include the glacier area, maximum and minimum elevation, mean elevation, mean slope, mean aspect, flag indicating presence or absence of debris cover, and area of debris-covered glaciers. To mitigate influences of cloud cover on optical images, we adopted semi-automated identification of cloud cover and clean snow/ ice to combine observations from multi-temporal Landsat images. Debris-covered glaciers were separately determined with a semi-automated method that integrates information derived from Landsat images, coherence information generated from PALSAR (Phased Array type L-band Synthetic Aperture Radar) image pairs, and slope information. In the post-processing stage, we performed manual editing of the glacier outlines to improve the data quality, for example, to ensure seamless shared boundaries between clean-ice glaciers and their debris-covered parts, to adjust the individual ice divides, and to correct the effect of shadow and water bodies. Compared with manually digitized glacier outlines, this dataset has an overall error within 3%. The quality of the latest glacier inventory was improved; it has less uncertainty associated with cloud and seasonal snow cover in glacier maps and is a fundamental dataset for future glacier-related studies.

Continental glacier melts directly influence the environment, resulting in sea-level rise affecting the settlements along the coast. The increase in global warming and constant change in the glacier mass grabbed the attention of researchers in understanding the evolution and distribution of glaciers. Despite the increase in the number of glacier studies, the difficulty is experienced by the researchers in understanding the supra-glacial debris cover and its characteristics. Supraglacial debris cover affects surface melt by increasing and decreasing ablation under thin and thick debris cover. In the present study, estimation of supraglacial debris cover (SDC) over Austre Brøggerbreen and Vestre Brøggerbreen glaciers of Ny-Ålesund is carried out with the aid of Landsat 5/7/8 datasets between 2000 and 2020. Supraglacial debris-cover is mapped using NDSI and band ratio techniques based on thresholding and it is estimated that Austre Brøggerbreen and Vestre Brøggerbreen glaciers are covered by 7.29% and 15.19% of SDC respectively. Results obtained are validated by a field visit to Arctic glacier, which is the first of its kind enhancing India's scientific credentials in Polar research.

&amp;lt;p&amp;gt;Glacier extents are mainly mapped by a semi-automated classification of multispectral satellite images (e.g. Landsat, Sentinel-2) with manual corrections of unmapped regions (e.g. ice in cast shadow or under debris cover). The quality of such corrections improve towards higher spatial resolution sensors, but such data were so far only seldom available for direct digitizing in a GIS. With the increasing availability of web map services (wms) such as the ESRI image service or national services the situation has strongly changed and first studies already analysed the potential of such services in geoscience.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The ESRI wms can be embedded into the professional mapping environment of ArcMap or QGIS. It provides mostly cloud and snow free mosaics of very high-resolution (0.31 - 0.5 m) GeoEye and Worldview images up to a scale of 1:5000. The images can be shown in the background as an information layer, but not further processed. The user has no control over the images provided (e.g. their acquisition date) or how they are mosaiced and orthorectified, locally resulting in snow covered or shifted images. The acquisition date and sensor used for each image part can be extracted using the information tool. Due to its recent availability, the ESRI wms has not yet been widely used and its huge potential especially for geomorphological and paleoglaciological mapping has still to be explored.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this study, which is performed in the framework of the EU Horizon 2020 project PROTECT (protect-slr.eu) we present (1) a workflow for mapping Little Ice Age (LIA) glacier extents using the ESRI wms, (2) a detailed uncertainty analysis and (3) first results of glacier area changes since the LIA for selected regions in Alaska, Baffin Island, Novaya Zemlya and the tropics. Additionally to the ESRI wms, we used Sentinel-2 images, the ArcticDEM and modern glacier outlines from the Randolph Glacier Inventory (RGI). Geomorphological indicators (trim lines, moraines, vegetation free zones) and glaciological considerations were considered to guide the digitizing. Geolocation uncertainties were determined against independent data sources and the interpretation and reproduction uncertainties were quantified by multiple digitising experiments. The possible timing of the former LIA maximum extents was obtained to the extent possible from the literature, but here large uncertainties remain.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In total, outlines for 371 LIA glaciers were created and compared to today relative area changes of -20%, -15%, -26% and -58% were found for Alaska, Baffin Island, Novaya Zemlya and the tropics, respectively. Reproduction uncertainties were calculated for a sample of 18 glaciers to be on average 1.4 &amp;amp;#177;1.3%, interpretation uncertainties for a sample of 17 glaciers 1.9 &amp;amp;#177;10%. The digitization of LIA glacier extents with 10 m Sentinel-2 images is only rarely possible due to the difficulties identifying small scale moraines and resulted in much higher . We conclude that wms such as the ESRI World imagery layer provide, despite their shortcomings, an excellent opportunity to precisely map LIA maximum extents of glaciers around the world.&amp;lt;/p&amp;gt;

The continuous increase in the emission of greenhouse gases has resulted in global warming, and substantial changes in the global climate are expected by the end of the current century. The reductions in mass, volume, area and length of glaciers on the global scale are considered as clear signals of a warmer climate. The increased rate of melting under a warmer climate has resulted in the retreating of glaciers. On the long-term scale, greater melting of glaciers during the coming years could lead to the depletion of available water resources and influence water flows in rivers. It is also very likely that such changes have occurred in Himalayan glaciers, but might have gone unnoticed or not studied in detail. The water resources of the Himalayan region may also be highly vulnerable to such climate changes, because more than 50% of the water resources of India are located in the various tributaries of the Ganges, Indus and the Brahmaputra river system, which are highly dependent on snow and glacier runoff. In the present study, the snowmelt model SNOWMOD has been used to simulate the melt runoff from a highly glacierized small basin for the summer season. The model simulated the distribution and volume of runoff with reasonably good accuracy. Based on a 2-year simulation, it is found that, on average, the contributions of glacier melt and rainfall in the total runoff are 87% and 13% respectively. The impact of climate change on the monthly distribution of runoff and total summer runoff has been studied with respect to plausible scenarios of temperature and rainfall, both individually and in combined scenarios. The analysis included six temperature scenarios ranging between 0·5 and 3 °C, and four rainfall scenarios (−10%, −5%, 5%, 10%). The combined scenarios were generated using temperature and rainfall scenarios. The combined scenarios represented a combination of warmer and drier and a combination of warmer and wetter conditions in the study area. The results indicate that, for the study basin, runoff increased linearly with increase in temperature and rainfall. For a temperature rise of 2 °C, the increase in summer streamflow is computed to be about 28%. Changes in rainfall by ±10% resulted in corresponding changes in streamflow by ±3·5%. For the range of climatic scenarios considered, the changes in runoff are more sensitive to changes in temperature, compared with rainfall, which is likely due to the major contribution of melt water in runoff. Such studies are needed for proper assessment of available water resources under a changing climate in the Himalayan region. Copyright © 2005 John Wiley & Sons, Ltd.

Abstract. Himalayan glaciers show large uncertainty regarding their present and future state due to their sensitive reaction towards change in climatic condition. Himalayan glaciers are unique as they are located in tropical, high altitude regions, predominantly valley type and many are covered with debris. The great northern plains of India sustain on the perennial melt of glaciers meeting the water requirements of agriculture, industries, domestic sector even in the months of summer when large tracts of the country go dry. Therefore, it is important to monitor and assess the state of snow and glaciers and to know the sustainability of glaciers in view of changing global scenarios of climate and water security of the nation. Any information pertaining to Himalayan glaciers is normally difficult to be obtained by conventional means due to its harsh weather and rugged terrains. Due to the ecological diversity and geographical vividness, major part of the Indian Himalaya is largely un-investigated. Considering the fact that Himalayan glaciers are situated in a harsh environment, conventional techniques of their study is challenging and difficult both in terms of logistics and finances whereas the satellite remote sensing offers a potential mode for monitoring glaciers in long term. In order to gain an updated overview of the present state of the glacier cover and its changes since the previous inventories, an attempt has been made to generate a new remotesensing- derived glacier inventory on 1:50,000 scale for Bhaga basin (N32°28'19.7'' - N33°0'9.9'' ; E76°56'16.3'' - E77°25'23.7'' ) Western Himalaya covering an area of 1695.63 km2. having 231 glaciers and occupying glacierized area of 385.17 ±3.71 km2. ranging from 0.03 km2. to 29.28 km2. Glacier inventory has been carried out using high resolution IRS P6 LISS III data of 2011, ASTER DEM and other ancillary data. Specific measurements of mapped glacier features are the inputs for generating the glacier inventory data sheet with 37 parameters as per the UNESCO/TTS format, 11 additional parameters associated with the de-glaciated valley as per the suggestions of Space Application Center Ahmadabad and 9 newly introduced parameters of present study. The data sheet provides glacier wise details for each glacier on the significant glacier parameters like morphology, dimensions, orientation, elevation, etc. for both the active glacier component as well as the associated de-glaciated valley features. Assessment of recent variation in the glacierized area between 2001 and 2011. Results indicate that 231 glaciers covering an area of 391.56 ±3.76 km2. in 2001 has been reduced to 385.17 ±3.71 km2. in 2011; a loss of 1.63 ±1.0% in glacierized area within a period of 10 years. The present paper brings out the methodology adopted and salient results of the glacier inventory carried out which will help to enrich the existing database required for water resources assessment of the country and also meet the requirements of various researches working on climate change related studies.

Glacier inventories provide the baseline data to perform climate-change impact assessment on a regional scale in a consistent and spatially representative manner. In particular, a more accurate calculation of the current and future contribution to global sea-level rise from heavily glacierized regions such as Alaska is much needed. We present a new glacier inventory for a large part of western Alaska (including Kenai Peninsula and the Tordrillo, Chigmit and Chugach mountains), derived from nine Landsat Thematic Mapper scenes acquired between 2005 and 2009 using well-established automated glacier-mapping techniques (band ratio). Because many glaciers are covered by optically thick debris or volcanic ash and partly calve into water, outlines were manually edited in these wrongly classified regions during post-processing. In total we mapped ∼8830 glaciers (>0.02 km2) with a total area of ∼16 250 km2. Large parts of the area (47%) are covered by a few (31) large (>100 km2) glaciers, while glaciers less than 1 km2 constitute only 7.5% of the total area but 86% of the total number. We found a strong dependence of mean glacier elevation on distance from the ocean and only a weak one on aspect. Glacier area changes were calculated for a subset of 347 selected glaciers by comparison with the Digital Line Graph outlines from the US Geological Survey. The overall shrinkage was ∼23% between 1948–57 and 2005–09.

Supra-glacial debris cover is important for the control of surface ice melt and glacier retreat in mountain regions. Despite the progress in techniques based on various satellite imagery, the mapping of debris-covered glacier boundaries over large regions remains a challenging task. Previous studies of the debris-covered glaciers in the Greater Caucasus have only focused on limited areas. In this study, using the Sentinel 1–2 imagery (2020), DebCovG-carto toolbox, and existing glacier inventory (2020), we produced the first detailed assessment of supra-glacial debris cover for individual glaciers in the entire Greater Caucasus. Our study shows that in 2020, 10.3 ± 5.6% of the glacier surface in this mountain region was covered by debris. A comparison of sub-regions such as the Elbrus Massif and other individual glaciers from the central Greater Caucasus shows an increasing trend of supra-glacial debris cover from 2014 to 2020. The total area of supra-glacial debris cover expanded from ~4.6% to ~5.8% for Elbrus and from ~9.5% to ~13.9% for the glaciers of the central Greater Caucasus during the same period. Supra-glacial debris cover also expanded upward on these glaciers between 2014 and 2020. A recent increase in rock-ice avalanche activity in combination with increased air temperature and decreased precipitation in the Greater Caucasus may be responsible for this upward migration and expanded area of supra-glacial debris cover. This study provides valuable insights into the spatial distribution, temporal evolution, and factors influencing supra-glacial debris cover in the Greater Caucasus. The findings contribute to our understanding of glacier dynamics and highlight the importance of continuous monitoring and assessment of supra-glacial debris cover in the context of climate change and glacier retreat. We recommend using the DebCovG-carto toolbox for regional assessment of supra-glacial debris coverage in other mountain regions as well.

Abstract. Retrieving total suspended solids (TSS) concentration accurately is essential for sustainable management of estuaries and coasts, which plays a key role in the interaction between hydrosphere, pedosphere and atmosphere. Although many TSS retrieval models have been published, the general inversion method that is applicable to different field conditions is still under research. In order to obtain a TSS remote sensing model that is suitable for estimating TSS concentrations with wide range in estuaries and coasts by Landsat imagery, after reviewing a number of Landsat-based TSS retrieval models and improving a comparatively better one among them, this study developed a quadratic model using the ratio of logarithmic transformation of red band and near-infrared band and logarithmic transformation of TSS concentration (QRLTSS) based on 119 in situ samples collected in 2006–2013 from five regions of China. It was found that the QRLTSS model works well and shows a satisfactory performance. The QRLTSS model based on Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus) and OLI (Operational Land Imager) sensors explained about 72 % of the TSS concentration variation (TSS: 4.3–577.2 mg L−1, N = 84, P value &lt; 0.001) and had an acceptable validation accuracy (TSS: 4.5–474 mg L−1, root mean squared error (RMSE) ≤ 25 mg L−1, N = 35). In addition, a threshold method of red-band reflectance (OLI: 0.032, ETM+ and TM: 0.031) was proposed to solve the two-valued issue of the QRLTSS model and to retrieve TSS concentration from Landsat imagery. After a 6S model-based atmospheric correction of Landsat OLI and ETM+ imagery, the TSS concentrations of three regions (Moyangjiang River estuary, Pearl River estuary and Hanjiang River estuary) in Guangdong Province in China were mapped by the QRLTSS model. The results indicated that TSS concentrations in the three estuaries showed large variation ranging from 0.295 to 370.4 mg L−1. Meanwhile we found that TSS concentrations retrieved from Landsat imagery showed good validation accuracies with the synchronous water samples (TSS: 7–160 mg L−1, RMSE: 11.06 mg L−1, N = 22). The further validation from EO-1 Hyperion imagery also showed good performance (in situ synchronous measurement of TSS: 106–220.7 mg L−1, RMSE: 26.66 mg L−1, N = 13) of the QRLTSS model for the area of high TSS concentrations in the Lingding Bay of the Pearl River estuary. Evidently, the QRLTSS model is potentially applied to simulate high-dynamic TSS concentrations of other estuaries and coasts by Landsat imagery, improving the understanding of the spatial and temporal variation of TSS concentrations on regional and global scales. Furthermore, the QRLTSS model can be optimized to establish a regional or unified TSS retrieval model of estuaries and coasts in the world for different satellite sensors with medium- and high-resolution similar to Landsat TM, ETM+ and OLI sensors or with similar red bands and near-infrared bands, such as ALI, HJ-1 A and B, LISS, CBERS, ASTER, ALOS, RapidEye, Kanopus-V, and GF.

Over the past 30 years, marine-type glaciers in the eastern Himalayas have been significantly affected by climate change, making the region a key area for global climate change research. Based on Landsat series remote sensing imagery, this study employs visual interpretation and the band ratio threshold method to analyze the area and variation characteristics of marine-type glaciers in the eastern Himalayas from 1990 to 2015. It further investigates the influence of debris cover, glacial lakes, and climate change on glacier ablation. The results indicate that (1) From 1990 to 2015, marine-type glaciers in the eastern Himalayas showed an accelerating retreat trend, with an average annual retreat rate of 0.48%/a. (2) A significant increase in temperature was the primary climatic factor driving the accelerated retreat of glaciers during the study period. In the future, changes in precipitation may surpass temperature as the dominant climatic factor influencing glacier variation in the study area. (3) Debris cover mainly played a mitigating role in glacier retreat in the eastern Himalayas. Within the 50°–60° slope range, debris-covered glaciers gradually became dominant, resulting in a lower average annual retreat rate during 2000–2015 compared to 1990–2000. (4) The impact of climate change on glaciers in the study area was greater than that of glacial lakes. This study reveals the mechanisms by which debris cover, glacial lakes, and climate change influence glacier ablation, providing scientific support for glacier disaster early warning and water resource assessment.

Satellite remote sensing is an advanced tool used to characterize seagrass biomass and monitor changes in clear to less-turbid waters by analyzing multi-temporal satellite images. Seagrass information was extracted from the multi-temporal satellite datasets following a two-step procedure: (i) retrieval of substrate-leaving radiances; and (ii) estimation of seagrass total aboveground biomass (STAGB). Firstly, the substrate leaving radiances is determined by compensating the water column correction of the pre-processed data because of the inherent errors associated with the geometric and radiometric fidelities including atmospheric perturbations. Secondly, the seagrass leaving radiances were correlated to the corresponding in situ STAGB to predict seagrass biomass. The relationship between STAGB and cover percentage was then established for seagrass meadows occurring in Merambong, Straits of Johor, Malaysia. By applying the above-mentioned approach on Landsat Thematic Mapper (TM) acquired in 2009 and Operational Land Imager (OLI) data acquired in 2013, the resulting maps indicated that submerged STAGB in less clear water can be successfully quantified empirically from Landsat data, and can be utilized in STAGB change detection over time. Data validation showed a good agreement between in situ STAGB and Landsat TM (R2 = 0.977, p &lt; 0.001) and OLI (R2 = 0.975, p &lt; 0.001) derived water leaving radiances for the studied seagrass meadows. The STAGB was estimated as 803 ± 0.47 kg in 2009, while it was 752.3 ± 0.34 kg in 2013, suggesting a decrease of 50.7 kg within the four-year interval. This could be mainly due to land reclamation in the intertidal mudflat areas performed, with a view to increase port facilities and coastal landscape development. Statistics on dugong sightings also supports changes in STAGB.

The last remaining very small glaciers (&lt; 0.5 km2) of the Pyrenees are the southernmost glaciers in Europe and respond rapidly to climate variability. Most of them are also influenced by local topographic factors and geomorphological processes impacting the energy and mass balance. This paper presents the first temporal study on the changes in debris cover on Pyrenean glaciers from 2000 to 2022 at a regional scale. The data allowed for the first analysis of the lithological characteristics of each glaciarised cirque in order to identify possible factors that determine the evolution of debris input. We manually mapped the extent of supraglacial debris with corresponding glacier outlines using very high-resolution aerial imagery and the existing glacier inventories from 2000, 2011, 2020 and 2022. The results show that debris cover on Pyrenean glaciers has increased significantly in number and extent over the study period whilst glaciers continue to decline and shrink. In 2022, 14 of the 18 remaining glaciers have debris cover greater than 10% of their area, and six have debris cover greater than 40%. The observed increase in debris cover is much stronger for glaciers determined by topoclimatic factors and located on metamorphic and sedimentary cirques, which underlines the important role of paraglacial processes in their development. Meanwhile, glaciers on granitic cirques have lower debris cover and have shown a lesser increase compared to initial measurements conditions. Future work should focus on understanding debris sources and their characteristics to determine the role of debris cover in the response of Pyrenean glaciers to climate change.

The Tibetan Plateau and its surroundings contain the largest number of glaciers outside the polar regions. In the past 100 years, the glaciers on the Tibetan Plateau and its surrounding areas have been retreating slowly. Since the 1990s, however, the state of glaciers has undergone abnormal changes. Compared with the data derived from the First Chinese Glacier Inventory (CGI) (1960s−1980s), the glacier volume in China decreased by approximately 20% and the glacier area was reduced by approximately 17.7%, based on the data derived from the Second CGI. In particular, the glacier mass loss of the small glaciers was characterized by an area less than 1 km2 and was more intensive than that of lager glaciers. Abnormal changes in the glaciers on the Tibetan Plateau and the surrounding areas are mainly reflected by the spatial pattern. Through the systematic analysis of the data on glacier area, terminal position, and mass balance changes, it was found that the glacier changes in the region experienced obvious spatial heterogeneity from 1990 to 2010. The “Karakoram glacier anomaly” in the eastern Pamir, Karakoram, and western Kunlun regions has exhibited slight mass stability or even glacier advance. However, the glaciers on the southeastern Tibetan Plateau experienced the most intensive and accelerated shrinkage. On the evaluated timescale, the state of glaciers on the Tibetan Plateau and its surroundings has undergone abnormal changes regarding the loss rate of glacier volume. In the past 50 years, most of the glaciers have had a negative mass balance. Moreover, the mass loss process has intensified, especially since the 1990s. It is estimated that the loss rate of glacier volume from the Tibetan Plateau was as large as −15.6 ± 10.1 Gt/a between 2003 and 2009. In addition to the abnormal changes in spatial patterns and temporal changes, the glaciers exhibited an abnormal change within the glacial system. The most significant variability within the glacier system was the abnormal change in the structure of glacier ice. Another abnormal change within the glacier system was that the glaciers showed a sustained slowdown concomitant with ice thinning. Abnormal warming at high altitudes is an important driver of abnormal changes in glaciers on the Tibetan Plateau and its surroundings. Moreover, these contrasting glacier behaviors on the Tibetan Plateau and surroundings are related to atmospheric circulation processes, especially interactions between the westerlies and the Indian Summer Monsoon. In addition, changes in glaciers on the Tibetan Plateau and its surroundings are closely related to the enhancement of human activities. The South Asian region on the southern slope of the Himalayas acts as a main source of severe anthropogenic aerosol emissions, especially that of black carbon. The black carbon transported from South Asia to the glaciers reduces the glacier’s albedo and thus accelerates glacier melting. As global warming intensifies, the abnormal glacier status will likely lead to more hazards, such as ice collapse and glacial lake outburst floods. To reduce the potential glacial risks on the Tibetan Plateau and surroundings, it is necessary to further strengthen the abilities of glacier monitoring and disaster prevention.

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 (RAB = 0.75) and RGI (RAB = 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 data-scarce 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).