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Glacier inventories are fundamental in understanding glacier dynamics and glacier-related environmental processes. High-resolution mapping of glacier outlines is lacking, although high-resolution satellite images have become available in recent decades. Challenges in development of glacier inventories have always included accurate delineation of boundaries of debris-covered glaciers, which is particularly true for high-resolution satellite images due to their limited spectral bands. To address this issue, we introduced an automated, high-precision method in this study for mapping debris-covered glaciers based on 1 m resolution Gaofen-2 (GF-2) imagery. By integrating GF-2 reflectance, topographic features, and land surface temperature (LST), we used an attention mechanism to improve the performance of several deep learning network models (the U-Net network, a fully convolutional neural network (FCNN), and DeepLabV3+). The trained models were then applied to map the outlines of debris-covered glaciers, at 1 m resolution, in the central Karakoram regions. The results indicated that the U-Net model enhanced with the Convolutional Block Attention Module (CBAM) outperforms other deep learning models (e.g., FCNN, DeepLabV3+, and U-Net model without CBAM) in terms of precision for supraglacial debris identification. On the testing dataset, the CBAM-enhanced U-Net model achieved notable performance metrics, with its accuracy, F1 score, mean intersection over union (MIoU), and kappa coefficient reaching 0.93, 0.74, 0.79, and 0.88. When applied at the regional scale, the model even exhibits heightened precision (accuracies = 0.94, F1 = 0.94, MIoU = 0.86, kappa = 0.91) in mapping debris-covered glaciers. The experimental glacier outlines were accurately extracted, enabling the distinction of supraglacial debris, clean ice, and other features on glaciers in central Karakoram using this trained model. The results for our method revealed differences of 0.14% for bare ice and 10.36% against the manually interpreted glacier boundary for supraglacial debris. Comparison with previous glacier inventories revealed raised precisions of 8.74% and 4.78% in extracting clean ice and with supraglacial debris, respectively. Additionally, our model demonstrates exceptionally high exclusion for bare rock outside glaciers and could reduce the influence of non-glacial snow on glacier delineation, showing substantial promise in mapping debris-covered glaciers. [ABSTRACT FROM AUTHOR]

The influence of supraglacial debris cover on glacier mass balance in the Karakoram is noteworthy. However, understanding of how debris cover affects the seasonal and long-term variations in glacier mass balance through alterations in the glacier's energy budget is incomplete. The present study coupled an energy–mass balance model with heat conduction within debris layers on debris-covered Batura Glacier in Hunza Valley to demonstrate the influence of debris cover on glacial surface energy and mass exchanges during 2000–2020. The mass balance of Batura Glacier is estimated to be -0.262±0.561 m w.e. yr -1 , with debris cover accounting for a 45 % reduction in the negative mass balance. Due to the presence of debris cover, a significant portion of incoming energy is utilized for heating debris, leading to a large energy emission to the atmosphere via thermal radiation and turbulent sensible heat. This, in turn, reduces the melt latent heat energy at the glacier surface. We found that the mass balance exhibits a pronounced arch-shaped structure along the elevation gradient, which is associated with the distribution of debris thickness and the increasing impact of debris cover on the energy budget with decreasing elevation. Through a comprehensive analysis of the energy transfer within each debris layer, we have demonstrated that the primary impact of debris cover lies in its ability to modify the energy flux reaching the surface of the glacier. Thicker debris cover results in a smaller temperature gradient within debris layers, consequently reducing energy reaching the debris–ice interface. Over the past 2 decades, Batura Glacier has exhibited a trend towards less negative mass balance, likely linked to a decrease in air temperature and reduced ablation in areas with thin or sparse debris cover. [ABSTRACT FROM AUTHOR]

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 (Thematic 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 (Advanced 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 22510±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 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 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 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 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: 10.12072/ncdc.glacier.db2386.2022 (F. Xie et al., 2022). [ABSTRACT FROM AUTHOR]

Previous studies have shown that glacier changes were heterogeneous in the western Karakoram, with the coexistence of retreating, advancing, and surging glaciers. However, it remains unclear that the mechanisms driving these changes. Based on the Shuttle Radar Topography Mission (SRTM) DEM and TerraSAR-X/TanDEM-X images (2014), this study presents glacier surface height changes in the Hunza Basin of the western Karakoram, employing the method of differential synthetic aperture radar interferometry (DInSAR). A slight negative glacier mass balance was observed in the Hunza Basin during 2000–2014. Surge-type glaciers would not have an obvious effect on overall mass balance in regional assessments over long-time scales. Further, glacier surface velocities in the Hunza Basin were estimated from Landsat images for the period of 1990–2018 by utilizing published data sets and Landsat images. Compared to the annual glacier surface velocities, 22 surge events were observed in seven surge-type glaciers in the Hunza Basin. Glacier flow can be attributed to thermally and hydrologically control, and the geomorphological characteristics of different individuals. This study gives us a new insight into the situation of the "Karakoram anomaly" under the background of glacier mass loss in the high mountains of Asia (HMA). [ABSTRACT FROM AUTHOR]

Climate warming has a significant impact on the water cycle, especially in regions where the water supply is dominated by snow and glacier meltwater. In this study, spatiotemporal changes of snowpack in the Yarkant River Basin (YRB) and the west of Upper Indus Basin (WUIB), associated with the Karakoram Mountains, were examined using Moderate-resolution Imaging Spectroradiometer (MODIS) daily cloud-free snow cover product. A sensitivity analysis was carried out to explore the climatic effects on snow cover changes. From 2002 to 2018, overall slight (but non-significant) decreasing and increasing trends in snow cover extent were observed in the basins, which occupy the northern and southern slopes of the central and western Karakoram Mountains, respectively. In both basins, the low-altitude areas experienced a slight decrease in snow cover extent, while the high-altitude areas experienced an increase. Significant elevation dependences were found for the snow cover percentage (SCP), snow covered days (SCD) and snow cover melting dates (SCMD), with an inverse elevation dependence for snow cover onset dates (SCOD). Most of the study area showed a decreasing trend in SCD, which was delayed in SCOD, and an advanced trend in SCMD by a rate of <2 d/a. An increased trend in SCD was observed at 5000–6000 m a.s.l. in the YRB and at 3000–4000 m a.s.l. in the WUIB, both attributed to delayed SCMD. Parts of the Karakoram and eastern Pamir experienced lengthened SCD, advanced SCOD, and delayed SCMD against a background of increased temperature. This was attributed to increased precipitation in the snow accumulation season, and might be related to the Karakoram Anomaly. Moreover, SCOD was found to be positively sensitive to air temperature in snow accumulation season, but negatively sensitive to precipitation. Similarly, SCMD had a positive sensitivity to precipitation, but a negative sensitivity to air temperature in both the snow accumulation season and snowmelt season. Unlabelled Image • Snow cover extent exhibited a non-significant decrease in the YRB, whereas an increase in the WUIB. • Most of the study area showed a decreasing trend in SCD, a delayed trend in SCOD, and an advanced trend in SCMD. • The lengthened SCD in parts of the Karakoram and eastern Pamir are attributed to increased precipitation in winter. • The lengthened SCD may have contributed to glacier expansion in Karakoram and might be related to the Karakoram Anomaly. [ABSTRACT FROM AUTHOR]

• Glaciers in the UIBKK experienced a slight negative mass budget from 2000 to 2019. • Mass balances in the UIBKK shifted from negative to positive from West to East. • An accelerated mass loss was found in the West UIBKK from 2000–2013 to 2013–2019. • Mass budgets in the East UIBKK shifted from negative to positive from 2000 to 2019. • Climate warming may play more important role in glacier changes in the study area. Water supply contributed by glacier and snow melt is of particular significance and play a key role for social stability in the Karakoram region of Upper Indus Basin (UIBKK). Based on the SRTM DEM, TerraSAR-X/TanDEM-X images and ZY3-02 stereo images, the spatiotemporal pattern of glacier mass budgets in the UIBKK have been estimated for the early 21st century (2000–2019) period in this study. A comparison of the total area in 2000 with that in 2019 shows that glacier area remained stable in the early 21st century, with a slight expansion of 56.3 km2 (0.4%). Glaciers in the UIBKK experienced a balanced or slight negative mass budget of −0.08 ± 0.07 m w.e. a−1 in the early 21st century. The spatial variability of mass budget in the UIBKK showed that glacier mass budgets shifted from negative to positive from West to East, respectively, along longitude. Glacier mass loss decelerated from −0.12 ± 0.16 m w.e. a−1 in 2000–2013 to −0.03 ± 0.21 m w.e. a−1 in 2013–2019. No significant differences were observed in thinning rates on debris-covered glaciers (≥19% area covered by debris) and clean-ice glaciers (<19% area covered by debris) in the early 21st century (−0.06 m a−1 vs −0.04 m a−1). The overall homogeneous mass budgets for surge and non-surge glaciers indicated that glacier surges seem not have a notable impact on glacier-wide mass budget over short time scales. The spatiotemporal variability of glacier mass budgets in the UIBKK are consistent with the tendencies of winter precipitation and summer temperature. Climate warming may play more important role in glacier changes in the UIBKK. [ABSTRACT FROM AUTHOR]