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Glacier changes in the main tributaries of the Tarim river basin in the past 40 years; note that we only include glaciers with absolute length changes >90 m
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The Tarim river basin, a river system formed by the convergence of nine tributaries, is the most heavily glacierized watershed in arid northwest China. In the basin, there are 11 665 glaciers with a total area of 19 878 km2 and a volume of 2313 km3. Glaciers in the basin play a significant role in the water resource system. It is estimated that the...
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Context 1
... acquired data for 3081 glaciers with a total area of around 1 Â 10 4 km 2 , accounting for 50.3% of the total glacial area and 26.4% of the total number of glaciers in the Tarim river basin (Table 1). Considering the total glacier area, our sample reflects the general status of glacier variations in the basin. ...Context 2
... empirical equation was derived from ice-penetrating radar thickness measure- ments of six valley glaciers, five cirque glaciers, one hanging glacier, one ice cap and three cirque-hanging glaciers (area 0.46-165 km 2 ) in the Tien Shan and seven glaciers (area 0.1-7 km 2 ) in the Qilian Shan, as well as measurements in the Qinghai-Tibetan Plateau. On the basis of the area of shrinkage of the glaciers in the basin (Table 1), the estimated total ice volume of the monitored 3081 glaciers generally decreased by 35.5 km 3 , or 319.3 Â 10 8 m 3 w.e. (assuming an ice density of 900 kg m -3 ). ...Similar publications
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... The Aksu River flows from glaciers in the central Tianshan Mountains, and groundwater generally discharges from the far north into low-lying rivers and lakes in the south, eventually entering the Tarim River through drainage networks [36]. Glaciers are present at an altitude of 3800-4800 m (the remains of glacial sediment are visible at approximately 2700 m), and its meltwater is the main water source of the Aksu River, accounting for more than 50% of the river's runoff [37]. Some watersheds have developed one-or two-foothill areas in front of the mountains that are controlled by the geological structure. ...
Thoroughly investigating the evolution of groundwater circulation and its controlling mechanism in the Aksu River Basin, where human activities are intensifying and the groundwater environment is increasingly deteriorating, is highly urgent and important for promoting the theory, development and implementation of groundwater flow systems (GFSs) and protecting groundwater resources. Based on a detailed analysis of the sediment grain size distribution, chronology, electrofacies, glacial sedimentary sequence, palaeoclimate indicators and existing groundwater age, this paper systematically reconstructs the palaeosedimentary environment of the basin-scale aquifer system in the study area and scientifically reveals the evolutionary pattern and formation mechanism of the GFS. The results showed that the later period of the late Pleistocene experienced a rapid downcutting erosional event caused by tectonic uplift, and the sedimentary environment transitioned from a dry–cold deep downcutting environment in the Last Glacial Maximum (LGM) to a coarse-grained fast-filling fluvial facies sedimentary environment in the Last Glacial Deglaciation (LDP) as the temperature rose; then, it shifted to an environment of fine-grained stable alternating accumulation of fluvial facies and lacustrine facies that was dominated by the warm and arid conditions of the Holocene megathermal period (HMP); this process changed the previous river base level via erosion, glacier elongation or shortening and river level, thus resulting in a complex coupling relationship between the palaeosedimentary environment, palaeoclimate and basin GFS. Furthermore, the existing GFS pattern in the basin exhibits a vertically unconformable groundwater age distribution, which indicates that it is the outcome of the complex superposition of groundwater flow controlled by the palaeosedimentary environment in different periods. Therefore, neotectonic movement and climate fluctuation have jointly acted on the variation in the river level, resulting in the “seesaw” effect, thereby fundamentally controlling the strength of the driving force of groundwater and resulting in the gradual evolution of the GFS from the fully developed regional GFS pattern during the LGM to the current multihierarchy nested GFS pattern.
... Warm air is likely to form precipitation in the high-altitude glacial areas of the QMs. At the same precipitation is an important factor affecting the change in the mass balance of gla Some studies have shown that warming and increased precipitation will lead to g retreat [61,62]. So, in the context of the climate warming, by the middle and late 21s tury, the glaciers of the QMs will undergo significant changes [50]. ...
... At the same time, precipitation is an important factor affecting the change in the mass balance of glaciers. Some studies have shown that warming and increased precipitation will lead to glacier retreat [61,62]. So, in the context of the climate warming, by the middle and late 21st century, the glaciers of the QMs will undergo significant changes [50]. ...
The Qilian Mountains (QMs) act as the “water tower” of the Hexi Corridors, playing an important role in the regional ecosystem security and economic development. Therefore, it is of great significance to understand the spatiotemporal characteristics of precipitation in the QMs. This study evaluated the performance of 21 models of phase 6 of the Coupled Model Intercomparison Project (CMIP6) from 1959 to 1988 based on ERA5 and in situ datasets. In addition, the precipitation changing trend from 2015 to 2100 was projected according to four shared socioeconomic pathways (SSPs): namely, SSP126, SSP245, SSP370, and SSP585. The results have shown the following: (1) all CMIP6 models could reflect the same precipitation changing trend, based on the observed datasets (−2.01 mm·10a−1), which was slightly lower than that of ERA5 (2.82 mm·10a−1). Multi-mode ensemble averaging (MME) showed that the projected precipitation-change trend of the four scenarios was 5.73, 9.15, 12.23, and 16.14 mm·10a−1, respectively. (2) The MME and ERA5 showed the same precipitation spatial pattern. Also, during the period 1959–1988, the MME in spring, summer, autumn and winter was 130.07, 224.62, 95.96, and 29.07 mm, respectively, and that of ERA5 was 98.57, 280.77, 96.85, and 22.64 mm, respectively. The largest precipitation difference in summer was because of strong convection and variable circulation. (3) From 2015 to 2100, the snow-to-rain ratio was between 0.1 and 1.1, and the snow-to-rain ratio climate tendency rate was concentrated in the range of −10~0.1 mm·10a−1. Both of these passed the significance test (p < 0.05). The projected rainfall of all four SSPs all showed an increasing trend with values of 6.20, 11.31, 5.64, and 20.41 mm·10a−1, respectively. The snowfall of the four SSPs all showed a decreasing trend with values of 0.42, 2.18, 3.34, and 4.17 mm·10a−1, respectively.
... The four basins in the northern part of the Kunlun Mountains are part of the Tarim River basin, so we refer to previous studies on the area and variation of glaciers in the Tarim River basin. Liu et al. [48] showed that the glacier area in the Tarim River basin decreased by 1307.2 km 2 (6.6%) from 1963 to 1999. Shangguan et al. [49] studied the changes of 7665 glaciers among 11665 glaciers in seven basins in the Tarim River by comparing the inventory of glaciers in China in the 1960s with Landsat images taken around ...
... The four basins in the northern part of the Kunlun Mountains are part of the Tarim River basin, so we refer to previous studies on the area and variation of glaciers in the Tarim River basin. Liu et al. [48] showed that the glacier area in the Tarim River basin decreased by 1307.2 km 2 (6.6%) from 1963 to 1999. Shangguan et al. [49] studied the changes of 7665 glaciers among 11665 glaciers in seven basins in the Tarim River by comparing the inventory of glaciers in China in the 1960s with Landsat images taken around the year 2000 and found that the glacier area decreased by 3.3%. ...
The glaciers in northwest China are mainly distributed in the northern part of the Himalayas, the Kunlun Mountains, and the Tianshan Mountains. Glaciers are an important freshwater resource in the northern part of the Kunlun Mountains, and the melting of glaciers and snow provides an assured source of water for rivers on the southern edge of the Tarim Basin. Based on the first glacier inventory dataset on China (1968), the second glacier inventory dataset on China (2009), and the glacier inventory dataset on Western China in 2018, this study used DEM data, Landsat remote sensing images, and ERA5 atmospheric reanalysis data to investigate glacier change and its influencing factors with respect to the northern part of the Kunlun Mountains. The results showed that there were 9273 glaciers in the northern part of the Kunlun Mountains in 2018, with an area of about 11,762.72 km2, an ice inventory of about 1168.53 km3, and an average length per glacier of about 1.68 km. The glaciers were mainly distributed at altitudes of 5300–6100 m (7574.66 km2). From 1968 to 2018, the number of glaciers in the northern stretch of the Kunlun Mountains increased by 343, while the glacier area decreased by 2452.80 km2 (−0.14%/a). From 2009 to 2018, the glacier area at the altitude of 4900 m to 6100 m decreased in the northern section of the Kunlun Mountains, and the glacier area at the remaining altitude increased slightly (10.67 km2). From 1968 to 2018, the glacier area and glacier length in all river basins decreased. The relative rate of glacier area change in the Qarqan River basin from 2009 to 2018 was five times that of 1968–2009, and this needs significant attention. From 1968 to 2018, both temperature and precipitation increased to varying degrees, and the increase in precipitation was beneficial to the accumulation of glaciers. Therefore, the increase in temperature was the main cause of glacier change in the northern section of the Kunlun Mountains.
... Additional details on the SWAT-Glacier model can be found in [35,36]. It is important to note that due to the large number of glaciers and their complex movement [39,40], the SWAT-Glacier model does not consider glacier movement such as surges. ...
Analyzing the future changes in runoff is crucial for efficient water resources management and planning in arid regions with large river systems. This paper investigates the future runoffs of the headwaters of the Tarim River Basin under different emission scenarios by forcing the hydrological model SWAT-Glacier using six regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) project. Results indicate that compared to the period of 1976~2005, temperatures are projected to increase by 1.22 ± 0.72 °C during 2036~2065 under RCP8.5 scenarios, with a larger increment in the south Tianshan mountains and a lower increment in the north Kunlun Mountains. Precipitation is expected to increase by 3.81 ± 14.72 mm and 20.53 ± 27.65 mm during 2036–2065 and 2066–2095, respectively, under the RCP8.5 scenario. The mountainous runoffs of the four headwaters that directly recharge the mainstream of the Tarim River demonstrate an overall increasing trend in the 21st century. Under the RCP4.5 and RCP8.5 scenarios, the runoff is projected to increase by 3.2% and 3.9% (amounting to 7.84 × 108 m3 and 9.56 × 108 m3) in 2006–2035. Among them, the runoff of the Kaidu River, which is dominated by rainfall and snowmelt, is projected to present slightly decreasing trends of 3~8% under RCP4.5 and RCP8.5 scenarios. For catchments located in the north Kunlun Mountains (e.g., the Yarkant and Hotan Rivers which are mix-recharged by glacier melt, snowmelt, and rainfall), the runoff will increase significantly, especially in summer due to increased glacier melt and precipitation. Seasonally, the Kaidu River shows a forward shift in peak flow. The summer streamflow in the Yarkant and Hotan rivers is expected to increase significantly, which poses challenges in flood risk management.
... At the same time, precipitation is an important factor affecting the change of glacier mass balance. Some studies show that climate warming and increased precipitation will lead to glacier retreat [50,51]. Therefore, under the background of climate warming, the glaciers in the Qilian Mountains will have significant changes by the middle and end of the 21st century. ...
The Qilian Mountains are a climate-sensitive area in northwest China, and extreme precipitation events have an important impact on its ecological environment. Therefore, considering the global warming scenario, it is highly important to project the extreme precipitation indices over the Qilian Mountains in the future. This study is based on three CMIP6 models (CESM2, EC-Earth3, and KACE-1-0-G). A bias correction algorithm (QDM) was used to correct the precipitation outputs of the models. The eight extreme precipitation indices over the Qilian Mountains during the historical period and in the future were calculated using meteorological software (ClimPACT2), and the performance of the CMIP6 models to simulate the extreme precipitation indices of the Qilian Mountains in the historical period was evaluated. Results revealed that: (1) The corrected CMIP6 models could simulate the changes in extreme precipitation indices over the Qilian Mountains in the historical period relatively well, and the corrected CESM2 displayed better simulation as compared to the other two CMIP6 models. The CMIP6 models performed well while simulating R10mm (CC is higher than 0.71) and PRCPTOT (CC is higher than 0.84). (2) The changes in the eight extreme precipitation indices were greater with the enhancement of the SSP scenario. The growth rate of precipitation in the Qilian Mountains during the 21st century under SSP585 is significantly higher than the other two SSP scenarios. The increment of precipitation in the Qilian Mountains mainly comes from the increase in heavy precipitation. (3) The Qilian Mountains will become wetter in the 21st century, especially in the central and eastern regions. The largest increase in precipitation intensity will be observed in the western Qilian Mountains. Additionally, total precipitation will also increase in the middle and end of the 21st century under SSP585. Furthermore, the precipitation increment of the Qilian Mountains will increase with the altitude in the middle and end of the 21st century. This study aims to provide a reference for the changes in extreme precipitation events, glacier mass balance, and water resources in the Qilian Mountains during the 21st century.
... The Karakoram mountains are centred on the western Tibetan Plateau (see Fig. 1a and b) and host more than 20 000 km 2 of glaciers, making this region one of the most glacierised areas outside of the polar regions. As the main source of the rivers' natural flow, meltwater from the Karakoram glaciers has a significant influence on the socioeconomic development in the upper Indus River basin and the Tarim River basin areas to the north of the mountains (Winiger et al., 2005;Liu et al., 2006Liu et al., , 2020Nie et al., 2021). Due to global warming in recent decades, changes in glacier-related resources and hazards present threats to the safety of critical infrastructure and the sustainable livelihoods of local communities living within the basin Bazai et al., 2021;Gao et al., 2021). ...
Multi-temporal glacier inventories provide key information about the glaciers, their characteristics, and changes and are inevitable for glacier modelling and investigating geodetic mass changes. However, to date, no consistent multi-temporal glacier inventory for the whole of the Karakoram exists, negatively affecting the monitoring of spatio-temporal variations in glaciers' geometric parameters and their related applications. We used a semi-automatic method combining automatic segmentation and manual correction and produced a multi-temporal Karakoram glacier inventory (KGI) compiled from Landsat TM/ETM+/OLI (The-matic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager) images for the 1990s, 2000s, 2010s, and 2020s. Our assessments using independent multiple digitisation of 37 glaciers show that the KGI is sufficiently accurate, with an overall uncertainty of ±3.68 %. We also performed uncertainty evaluation for the contiguous glacier polygons using a buffer of half a pixel, which resulted in an average mapping uncertainty of ±5.21 %. We calculated more than 20 attributes for each glacier, including coordinates, area, supraglacial debris area, date information, and topographic parameters derived from the ASTER GDEM (Ad-vanced Spaceborne Thermal Emission and Reflection Radiometer global digital elevation model). According to KGI-2020s, approximately 10 500 alpine glaciers (> 0.01 km 2 each) cover an area of 22 510 ± 828 km 2 of which 10.18 ± 0.38 % (2290 ± 84 km 2) is covered by supraglacial debris. Over the past 3 decades, the glaciers experienced a loss of clean ice and/or snow area but a gain in supraglacial debris. Supraglacial debris cover has Published by Copernicus Publications. 848 F. Xie et al.: Interdecadal glacier inventories in the Karakoram since the 1990s increased by 17.63±1.44 % (343.30±27.95 km 2), while non-debris-covered glaciers decreased by 1.56±0.24 % (319.85 ± 49.92 km 2). The total glacier area was relatively stable and showed only a slight insignificant increase of 23.45 ± 28.85 km 2 (0.10 ± 0.13 %). The glacier area has declined by 3.27 ± 0.24 % in the eastern Karako-ram, while the glacier area slightly increased in central (0.65 ± 0.10 %) and western Karakoram (1.26 ± 0.11 %). Supraglacial debris has increased over the whole of Karakoram, especially in areas above 4200 m a.s.l. (above sea level), showing an upward shift. The glacier area changes were characterised by strong spatial heterogene-ity, influenced by surging and advancing glaciers. However, due to global warming, the glaciers are on average retreating. This is in particular true for small and debris-free glaciers. The multi-temporal KGI data are available at the National Cryosphere Desert Data Center of China: https://doi.org/10.12072/ncdc.glacier.db2386.2022 (F. Xie et al., 2022).
... However, global warming and climate change phenomenon leads to increase in the global temperature by 0.85 °C since 1880, which may reach to 3.7 °C till the end of the twenty-first century (IPCC 2013). This increase in the global temperature resulted in accelerated melting of the glaciers and increase in the sea level (Liu et al. 2006;López-Moreno et al. 2014). Majority of the recent studies concluded that glaciers are retreating worldwide and therefore posing threats of climate change, increased sea level, inconsistent water supply, flooding, erosion and frequent Glacial Lake Outburst Floods (GLOF) (Arendt et al. 2002;Dyke et al. 2014;Loibl et al. 2014;López-Moreno et al. 2014;Schauwecker et al. 2014;Durán-Alarcón et al. 2015). ...
The Hindu Kush range of northern Pakistan has a large variety of Alpine and valley glaciers. These glaciers are subjected to volumetric changes owing to a host of factors (i.e. altitude, slope, glacier types, and aspect). The geodetic survey and field-based data are not available for assessment of glacier’s Equilibrium Line Altitude (ELA) for Hindu Kush due to rough topography and rigorous climate. However, the mass balance of the alpine and valley glaciers can be obtained through ELA and Accumulation Area Ratio (AAR). Therefore, this study deals with the estimation of ELA, the hypsometrically controlled methods based on AAR and Accumulation Area Balance Ratio (AABR). Various ratios between 0.4–0.8 with 0.05 interval for AAR and 0.67–4.4 with 0.01 for AABR are applied to obtain the ELA of valley glaciers. Moreover, the glacier contours with the interval of 50 m ± 5 m were employed for these estimations. The constant AAR and AABR ratios rather than constant glacier area adjust glacier hypsometry based on ELA variations. The results show that for AAR (0.5), 50 m ELA declined from 5409 to 5359 m and reduced (4%) the geometric area. The maximum decrease of 150 m ELA for these glaciers is reported for the AAR-AABR ratio of 0.1–4.4, showing a significant decrease. The estimated decrease in the glacier area of Hindu Kush is extremely variable specifically in Phargam, Khorabohr and Gordoghan.
... DDFs are based on a linear correlation between snow or ice melt and the sum of daily mean temperatures above the melting point. Commonly, the DDF is computed either from melt obtained by energy-balance computations (Braithwaite 1995;Zhang et al. 2006), or snow lysimeter outflow (Kustas et al. 1994) or from direct measurements using ablation stakes (Braithwaite et al. 1998;Shiyin et al. 2006). This study computed DDFs from direct measurements using ablation stakes distributed on a representative glacier. ...
The quantitative assessment of glacier changes and freshwater availability under future climate change is inevitable for sustainable water resources management and preventing natural disasters. Limiting the uncertainties in glacio-hydrological modeling and exploring spatiotemporal distributions of runoff and its components along the vertical profile are critical for such investigations. The present study quantifies glacio-hydrological changes using the Spatial Processes in HYdrology (SPHY) model forced by CMIP6 climate data (shared socioeconomic pathways: SSP126, SSP245, and SSP585) in the Upper Indus Basin (UIB) over twenty-first century. The model was calibrated based on in situ glacier changes, snow cover changes, and streamflow records to avoid the risk of equifinality. Variations in vertical distribution of runoff components and their impact on glacio-hydrology were investigated using the critical zone approach. The projected remaining glacier area is 55 ± 10%, 32 ± 17%, and 15 ± 5%, and freshwater availability is reduced by − 12 ± 5%, − 30 ± 7%, and − 36 ± 6% in 2100, compared with 2005–2014, under SSP126, SSP245, and SSP585, respectively. The average changes in snowmelt, glacier melt, baseflow, and rain-runoff contributions to total runoff under SSP245 are projected as 25 ± 15%, − 30 ± 11%, − 20 ± 16%, and 242 ± 71%, respectively. The critical zone (3500 – 5500 masl) contributes 63% of total runoff during the reference period, with a significant reduction (51–81%) in the projected period, indicating a diminishing influence of glacier runoff (with 50% reduction) in future hydrology compared with historical period. In turn, low flows (October–March) are projected to increase (9 − 58%), and high flows (April–September) will likely decrease (− 2 to − 13%). Warming temperature was identified as the dominant driver for the glacier area changes (r = − 0.85*) and total runoff (r = − 0.75*) at 0.05 level of significance. Our findings indicate a rainfall-runoff-dominant hydrological regime in future, highlighting critical freshwater availability conditions and associated socioeconomic risks in terms of agricultural applications and natural disasters. We recommend building infrastructure for water storage and conveyance in the Indus basin to prevent the adverse impacts of future climate change.
... As the main source of the rivers' natural flow, meltwater from the Karakoram glaciers has a significant influence on the socio-economic development in the upper Indus River basin and the Tarim River basin areas to the north of the mountains (Winiger et al., 2005;Liu et al., 2006;Immerzeel et al., 2020;Liu et al., 2020;Nie et al., 2021). Due to global warming in recent decades, changes in glacier-related resources and hazards present threats to the safety of critical infrastructure and the sustainable livelihoods of local 65 communities living within the basin (Immerzeel et al., 2020;Bazai et al., 2021;Gao et al., 2021). ...
Multi-temporal glacier inventories provide key information about the glaciers, their characteristics and changes and are inevitable for glacier modelling and investigating geodetic mass changes. However, to date, no consistent multi-tempo glacier inventory for the whole of the Karakoram exists, negatively affecting the monitoring of spatiotemporal variations of glaciers’ geometric parameters and their related applications. We used a semi-automatic method combining automatic segmentation and manual correction and produced multi-temporal Karakoram glacier inventories (KGI) compiled from Landsat TM/ETM+/OLI images for the 1990s, 2000s, 2010s, and 2020s. Our assessments using independent multiple digitization of 37 glaciers show that the KGI is sufficiently accurate, with an overall uncertainty of ±3.68 %. We also performed uncertainty evaluation for the contiguous glacier polygons using a buffer of half a pixel, which resulted in an average mapping uncertainty of ±3.68 %. We calculated more than 20 attributes for each glacier, including coordinates, area, supraglacial debris area, date information, and topographic parameters derived from the ASTER GDEM. According to the KGI-2020, approximately 10500 alpine glaciers (> 0.01 km2 each) cover an area of 22510 ± 828 km2 of which 10.18 ± 0.38 % (2290 ± 84 km2) are covered by supraglacial debris. Over the past three decades, the glaciers experienced a loss of clean ice/snow area but a gain in supraglacial debris. Supraglacial debris cover has increased by 17.63 ± 1.44 % (343.30 ± 27.95 km2) while non-debris-covered glaciers decreased by 1.56 ± 0.0.24 % (319.85 ± 49.92 km2). The total glacier area was relatively stable and showed only a slight insignificant increase of 23.45 ± 28.85 km2 (0.10 ± 0.13 %). The glacier area has declined by 3.27 ± 0.24 % in the eastern Karakoram while the glacier area slightly increased in central (0.65 ± 0.10 %) and western Karakoram (1.26 ± 0.11 %). Supraglacial debris has increased over whole Karakoram, especially in areas above 4200 m a.s.l., showing an upward shift. The glacier area changes were characterized by strong spatial heterogeneity, influenced by surging and advancing glaciers. However, due to global warming, the glaciers are on average retreating. This is in particular true for small and debris-free glaciers. The multi-temporal KGI data are available at the National Cryosphere Desert Data Center of China: https://doi.org/10.12072/ncdc.glacier.db2386.2022 (Xie et al., 2022a).
... Recent studies have reported that Himalayan glaciers are retreating at an alarming rate (Azam et al., 2021;Bolch, 2019;Kääb et al., 2015;Maurer et al., 2019;Pritchard, 2019;Shean et al., 2020, among others) with glaciers of the Western Himalayas showing less shrinkage than the glaciers of the central and eastern parts (Azam et al., 2021;Shukla et al., 2020;Singh et al., 2016). Glaciers in the nearby Karakoram region display long-term irregular behaviour with frequent glacier advances/surges and minimal shrinkage, which is yet to be fully understood (Azam et al., 2021;Bhambri et al., 2013;Bolch et al., 2012;Liu et al., 2006;Minora et al., 2013;Negi et al., 2021). Glaciers of the Karakoram region experienced an increase in area post-2000, due to surge-type glaciers. ...
Multi-temporal inventories of glacierised regions provide an improved understanding of water resource availability. In this study, we present a Landsat-based multi-temporal inventory of glaciers in four Upper Indus sub-basins and three internal drainage basins in the Ladakh region for the years 1977, 1994, 2009 and 2019. The study records data on 2257 glaciers (of individual size >0.5 km2) covering an area of ∼7923±106 km2 which is equivalent to ∼30 % of the total glacier population and ∼89 % of the total glacierised area of the region. Glacier area ranged between 0.5±0.02 and 862±16 km2, while glacier length ranged between 0.4±0.02 and 73±0.54 km. Shayok Basin has the largest glacierised area and glacier population, while Tsokar has the least. Results show that the highest concentration of glaciers is found in the higher elevation zones, between 5000 and 6000 m a.s.l., with most of the glaciers facing towards the NW–NE quadrant. The error assessment shows that the uncertainty, based on the buffer-based approach, ranges between 2.6 % and 5.1 % for glacier area, and 1.5 % and 2.6 % for glacier length with a mean uncertainty of 3.2 % and 1.8 %, respectively. This multitemporal inventory is in good agreement with previous studies undertaken in parts of the Ladakh region. The new glacier database for the Ladakh region will be valuable for policy-making bodies, and future glaciological and hydrological studies. The data can be viewed and downloaded from PANGAEA, https://doi.org/10.1594/PANGAEA.940994 (Soheb et al., 2022).
