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Rock avalanches onto glaciers are rare in Norway. Here, we examine a rock avalanche that spread onto the regenerated Brenndalsbreen, an outlet glacier from Jostedalsbreen ice cap. The rock avalanche is intriguing in that limited information exists with respect to the exact time of failure, location of detachment area, and preparatory and triggering processes. Based on an analysis of ice stratigraphy and photographic documentation, we assess that the event happened between mid-March and June 4, 2010. A potential triggering factor could have been heavy snow and rainfall combined with above freezing air temperatures on March 18–19, 2010. We use digital terrain models to determine that the detachment area is at an almost vertical rock slope in a narrow gorge above Lower Brenndalsbreen. The deposit volume is estimated to 0.130 ± 0.065 Mm3, and the H/L ratio and fahrböschung are 0.45 and 24°, respectively. We apply a Voellmy flow model to confirm the detachment location and volume estimate by producing realistic runout lengths. Although glacial debuttressing may have been a likely preparatory process, the detachment area was exposed for 45–70 years before the rock avalanche occurred. The supraglacial rock avalanche debris was separated into two branches with a distinct melt-out line across the glacier. The debris reached the glacier front in 2019 and 2020, where it started being deposited proglacially while Lower Brenndalsbreen kept receding. The 2010 Brenndalsbreen rock avalanche may not be a unique event, as deposits constituting evidence of an old rock avalanche are currently melting out at the glacier front. [ABSTRACT FROM AUTHOR]

The steep and unstable terrain found on debris-covered glaciers, rock glaciers, talus slopes, moraines and other proglacial features often make terrestrial ground-penetrating radar (GPR) surveys unsafe or cost-prohibitive. To address these challenges, this research introduces a novel approach for studying buried ice using multi-low-frequency drone-based GPR. Monostatic antennas of 50, 100, and 200 MHz were flown along a transect spanning a debris-covered glacier and an ice–debris complex at Shár Shaw Tagà (Grizzly Creek) in southwest Yukon, Canada. The drone-based results were compared to manual GPR at two locations along the transect. The two manual segments were conducted using the same radar system in a bi-static mode and included common mid-point (CMP) surveys. Overall, the drone-based radar successfully identified buried ice and enabled estimation of ice body thickness. Notably, CMP results confirmed layer characteristics and enabled depths to be measured across the entire drone-based transect. Discrimination of detail across a range of depths was made possible by comparing the three low frequencies, highlighting the possibility of using this method for future investigations of debris thickness in addition to quantifying buried ice. This study confirms the effectiveness of drone-based GPR combined with manual CMP for surveying ice beneath previously inaccessible terrain. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

Debris-free and debris-covered glaciers are both extensively present in the southeastern Tibetan Plateau. High-precision and rigorous comparative observational studies on different types of glaciers help us to accurately understand the overall state of water resource variability and the underlying mechanisms. In this study, we used multi-temporal simultaneous UAV surveys to systematically explore the surface elevation change, surface velocity, and surface mass balance of two representative glaciers. Our findings indicate that the thinning rate in the debris-free Parlung No. 4 glacier UAV survey area was consistently higher than that in the debris-covered 24K glacier in 2020–2021 (−1.16 ± 0.03 cm/d vs. −0.36 ± 0.02 cm/d) and 2021–2022 (−0.69 ± 0.03 cm/d vs. −0.26 ± 0.03 cm/d). Moreover, the surface velocity of the Parlung No. 4 glacier was also consistently higher than that of the 24K glacier across the survey period, suggesting a more dynamic glacial state. The surface mass balance of the Parlung No. 4 glacier (2020–2021: −1.82 ± 0.09 cm/d; 2021–2022: −1.30 ± 0.09 cm/d) likewise outpaced that of the 24K glacier (2020–2021: −0.81 ± 0.07 cm/d; 2021–2022: −0.70 ± 0.07 cm/d) throughout the observation period, which indicates that the debris cover slowed the glacier's melting. Additionally, we extracted the melt contribution of the ice cliff area in the 24K glacier and found that the melt ratio of this 'hotspot' area ranged from 10.4% to 11.6% from 2020 to 2022. This comparative analysis of two representative glaciers provides evidence to support the critical role of debris cover in controlling surface elevation changes, glacier dynamics, and surface mass balance. [ABSTRACT FROM AUTHOR]

Debris-covered glaciers in High Mountain Asia are important indicators of climatic variability. The present study proposed an improved glacier mapping technique based on a TIRS/(RED/SWIR) band ratio that integrates thermal infrared (TIR), visible red, and shortwave infrared (SWIR) reflectance information with slope parameter to map debris-covered areas. The object-based machine learning technique comprising a hybrid feature selection model and a decision tree classifier was adopted to classify the glacierized region. The mapping results stated that the proposed band ratio combined with the slope parameter has better differentiated supraglacial debris from other glacier surfaces in comparison with the existing debris-covered glacier mapping approaches. The resulted debris-covered glacier boundaries were also validated with reference glacier inventories. The supraglacial debris-covered area was mapped with a high user's accuracy of ≈98%. In addition, a high overall classification accuracy in the range of 99.59–99.84% was achieved with the proposed technique that overcomes the challenges of the previous noteworthy studies, confirming that this technique is effective in detecting debris-covered glaciers. [ABSTRACT FROM AUTHOR]

The steep and unstable terrain found on debris-covered glaciers, rock glaciers, talus slopes, moraines and other proglacial features often make terrestrial ground-penetrating radar (GPR) surveys unsafe or cost-prohibitive. To address these challenges, this research introduces a novel approach for studying buried ice using multi-low-frequency drone-based GPR. Monostatic antennas of 50, 100, and 200 MHz were flown along a transect spanning a debris-covered glacier and an ice–debris complex at Shár Shaw Tagà (Grizzly Creek) in southwest Yukon, Canada. The drone-based results were compared to manual GPR at two locations along the transect. The two manual segments were conducted using the same radar system in a bi-static mode and included common mid-point (CMP) surveys. Overall, the drone-based radar successfully identified buried ice and enabled estimation of ice body thickness. Notably, CMP results confirmed layer characteristics and enabled depths to be measured across the entire drone-based transect. Discrimination of detail across a range of depths was made possible by comparing the three low frequencies, highlighting the possibility of using this method for future investigations of debris thickness in addition to quantifying buried ice. This study confirms the effectiveness of drone-based GPR combined with manual CMP for surveying ice beneath previously inaccessible terrain.

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.

Debris-free and debris-covered glaciers are both extensively present in the southeastern Tibetan Plateau. High-precision and rigorous comparative observational studies on different types of glaciers help us to accurately understand the overall state of water resource variability and the underlying mechanisms. In this study, we used multi-temporal simultaneous UAV surveys to systematically explore the surface elevation change, surface velocity, and surface mass balance of two representative glaciers. Our findings indicate that the thinning rate in the debris-free Parlung No. 4 glacier UAV survey area was consistently higher than that in the debris-covered 24K glacier in 2020–2021 (−1.16 ± 0.03 cm/d vs. −0.36 ± 0.02 cm/d) and 2021–2022 (−0.69 ± 0.03 cm/d vs. −0.26 ± 0.03 cm/d). Moreover, the surface velocity of the Parlung No. 4 glacier was also consistently higher than that of the 24K glacier across the survey period, suggesting a more dynamic glacial state. The surface mass balance of the Parlung No. 4 glacier (2020–2021: −1.82 ± 0.09 cm/d; 2021–2022: −1.30 ± 0.09 cm/d) likewise outpaced that of the 24K glacier (2020–2021: −0.81 ± 0.07 cm/d; 2021–2022: −0.70 ± 0.07 cm/d) throughout the observation period, which indicates that the debris cover slowed the glacier’s melting. Additionally, we extracted the melt contribution of the ice cliff area in the 24K glacier and found that the melt ratio of this ‘hotspot’ area ranged from 10.4% to 11.6% from 2020 to 2022. This comparative analysis of two representative glaciers provides evidence to support the critical role of debris cover in controlling surface elevation changes, glacier dynamics, and surface mass balance.

Debris‐covered glacier mapping for monitoring glacier fluctuations is necessary to prevent geohazards caused by glaciers. Recently, deep learning‐based methods have been widely utilized for the identification of debris‐covered glaciers. Compared with conventional geospatial methods, deep learning‐based approaches have the advantage of large‐scale coverage and outstanding accuracies in identifying glaciers. However, there are two main difficulties when using deep learning‐based approaches: (1) object misclassification, which causes the misclassifications of the surrounding bedrock, snow, and mountain‐shadowed areas as glaciers; and (2) the inaccurate segmentation of boundaries. In addition, the sample sets for training deep learning models are generally insufficient, which leads to unsatisfactory results. To address the above problems, a deep learning‐based approach is proposed for accurate and automatic mapping of the complex debris‐covered glacier from remote sensing imagery for glacial hazard prevention. First, high‐quality remote sensing imagery is acquired and pre‐processed. Second, we adopt a weight‐optimized glacier semantic segmentation model to our approach. Then, the post‐processing procedures can be used to obtain the glacier outline. Finally, an accurate and automatic mapping of complex debris‐covered glaciers can be achieved. To demonstrate the effectiveness, our approach is applied to observe spatiotemporal changes in the glacier outline in the Nyenchen Tanglha region. Results show that most evaluation metrics of our model are higher than 90%, which demonstrates that it is reasonable for the glacier boundary extraction. We also verify that the proposed approach can be used to observe the changes in glaciers to prevent and control glacial hazards in high‐mountain regions. [ABSTRACT FROM AUTHOR]

As a particular type of alpine glacier, debris-covered glaciers are essential for local water resources and glacial disaster warnings. The Eastern Tomur Peak Region (EPTR) is the most concentrated glacier in Tien Shan Mountain, China, where the glaciers have not been studied in detail. This paper evaluates the delineation accuracy of Landsat8 OLI, Sentinel-1A, and GF images for debris-covered glaciers in the EPTR. Each image uses the most advanced delineation method for itself to minimize the error of inherent resolutions. The results show that the accuracy of these images for delineating debris-covered glaciers is very high, and the F1 scores are expressed as 96.73%, 93.55%, and 95.81%, respectively. Therefore, Landsat images were selected to analyze the area change of EPTR from 2000 to 2022 over a 5-year time scale. The results indicate that glaciers of the EPTR decreased by 19.05 km2 from 2000 to 2020, accounting for 1.9% (0.08% a−1), and debris increased by 10.8%, which validates the opinion that the presence of debris inhibits glacier melting. The most varied time was 2010–2022, but it was much less than other Tien Shan regions. The lower glacier ablation rate in this area results from the combined effect of decreased bare ice and increased debris. The main reason for the change in debris-covered glaciers is the increase in temperature. [ABSTRACT FROM AUTHOR]

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.

In recent years, deep learning (DL) methods have proven their efficiency for various computer vision (CV) tasks such as image classification, natural language processing, and object detection. However, training a DL model is expensive in terms of both complexities of the network structure and the amount of labeled data needed. In addition, the imbalance among available labeled data for different classes of interest may also adversely affect the model accuracy. This paper addresses these issues using a new convolutional neural network (CNN) based architecture. The proposed network incorporates both spatial and spectral information that combines two sub-networks: spatial-CNN and spectral-CNN. The spectral-CNN extracts spectral information, while spatial-CNN captures spatial information. Moreover, to make the features more robust, a multiscale spatial CNN architecture is introduced using different kernels. The final feature vector is formed by concatenating the outputs obtained from both spatial-CNN and spectral-CNN. To address the data imbalance problem, a generative adversarial network (GAN) was used to generate data for the underrepresented class. Finally, relatively a shallower network architecture was used to reduce the number of parameters in the network and improve the processing speed. The proposed model was trained and tested on Senitel-2 images for the classification of the debris-covered glacier. The results showed that the proposed method is well-suited for mapping and monitoring debris-covered glaciers at a large scale with high classification accuracy. In addition, we compared the proposed method with conventional machine learning approaches, support vector machine (SVM), random forest (RF) and multilayer perceptron (MLP). [ABSTRACT FROM AUTHOR]

The cryosphere plays an important role in the global carbon cycle, but few studies have examined carbon fluxes specifically on debris-covered glaciers. To improve understanding of the magnitude and variability of the atmospheric carbon flux in supraglacial debris, and its environmental controls, near-surface CO2 fluxes and meteorological variables were monitored over thick (0.23 m) and thin (0.04 m) debris at Miage Glacier, European Alps, over two ablation seasons, using an eddy covariance system. The CO2 flux alternates between downward and upward orientation in the day and night, respectively, and is dominated by uptake of CO2 in thick debris (mean flux = 1.58 g CO2 m−2 d−1), whereas flux magnitude is smaller and near net zero on thin debris (mean flux = −0.06 g CO2 m−2 d−1). These values infer a potential drawdown of >150 t CO2 km−2 over an ablation season, and >500 t CO2 (0.5 Gg CO2) for the whole debris-covered zone. The strong correlation of daytime CO2 flux magnitude with debris surface temperature suggests that atmospheric CO2 is consumed in hydrolysis and carbonation reactions at sediment-water interfaces in debris. Incoming shortwave radiation is key in heating debris, generating dilute meltwater, and providing energy for chemical reactions. CO2 drawdown on thin debris increases by an order of magnitude on days following frost events, implying that frost shattering generates fresh reactive sediment, which is rapidly chemically weathered with the onset of ice melting. Net CO2 release in the night, and in the daytime when debris surface temperature is below 7°C, is likely due to respiration by debris microorganisms. The combination of dilute meltwater, high temperature, and reactive mineral surfaces open to the atmosphere, makes supraglacial debris an ideal environment for rock chemical weathering. Debris-covered glaciers could be important to local and regional carbon cycling, and measurement of CO2 fluxes and controlling processes at other sites is warranted.

Rock glaciers are the most abundant (peri) glacial landform in the semiarid Andes (SA, 29–34°S), covering about three times the area of mountain glaciers. Recent studies suggest they may play an important hydrological role, including generating, storing and routing water. However, processes governing these roles are still poorly known especially for glacier complex units, i.e., where there is a juxtaposition or continuity of different (peri) glacial landforms, which are common in semiarid Andean and Himalayan areas. This study aims to understand how the internal structure of an ice-debris landform assemblage controls hydrological routing. To address this aim, we used a combination of three geophysical techniques to qualitatively determine the internal structure and favourable water routing and storage zones at the Tapado glacier complex (30°S), Chile. The Tapado glacier complex consists of an assemblage of a debris-free glacier, a debris-covered glacier and two rock glaciers. For the purpose of this study, we focused on the debris-covered and active rock glacier connection. At this site, the debris-covered glacier has a relatively thin debris-cover that increases thickness downglacier. This debris cover connects to the active rock glacier and forms the active layer. The rock glacier contains a heterogenous internal structure consisting of debris with water or segregated ice filling the voids, which likely derives from the massive ice of the debris-covered glacier. The superficial debris layer of the ice-debris landforms may act as a transmissive medium by routing water downstream above the massive ice of the debris-covered glacier, but also into deeper areas, as intra-permafrost flow, in the rock glacier. The rock glacier likely has a higher capacity to transmit vertical and horizontal flows, thereby enhancing infiltration processes. This study reinforces the value of geophysical methods to determine the internal structure of ice-debris landforms, particularly in the transition between landforms, and highlights how a warming climate and consequent paraglacial processes will impact the hydrological system not only in terms of water storage, but also water transfer.

Debris-covered glaciers have contrasting melting mechanisms and climate response patterns if compared with debris-free glaciers and thus show a unique influence on the hydrological process. Based on high-resolution satellite images and unpiloted aerial vehicle surveys, this study investigated the dynamic changes of Zhuxi Glacier, a thick debris-covered glacier in the southeastern Tibetan Plateau. Our result shows that the whole glacier can be divided into the active regime and stagnant regime along the elevation of 3400 m a.s.l. The mean surface velocity of the active regime was 13.1 m yr−1, which was five times higher than that of the stagnant regime. The surface-lowing rate of this debris-covered glacier reaches more than 1 m yr−1 and displays an accelerating trend. The majority of ice loss concentrates around ice cliffs and supraglacial ponds, the ablation hotspots. These hotspots can be roughly classified into three types, including persistent, expanding, and shrinking patterns, at different dynamic regimes on the Zhuxi Glacier. With the evolution of these hotpots and glacier dynamic changes, the supraglacial ponds showed significant change, with the total number fluctuating from 15 to 38 and the total area increasing from 1128 m2 to 95790 m2 during the past decade. The recent exponential expansion of the proglacial lake and the significant downwasting of stagnant ice inside the dammed terminus moraine possibly trigger the glacial lake outburst flood and thus threaten the security of livelihoods and infrastructure downstream. [ABSTRACT FROM AUTHOR]

Glacier changes on the Tibetan Plateau are of great importance for regional climate and hydrology and even global ecological changes. It is urgent to understand the effect of climate warming on both clean and debris-covered glaciers on the Tibetan Plateau. This study used the double RF method and Landsat series images to extract clean glaciers and debris-covered glaciers on the Tibetan Plateau from 1985 to 2020 and analyzed their temporal and spatial changes under the background of climate change. The total area of glaciers on the Tibetan Plateau showed a retreating trend from 1985 to 2020, with an average retreat rate of −0.5 % yr−1. The area of clean glaciers showed a significant retreating trend, with a retreat rate of −0.55 % yr−1. The area of debris-covered glaciers showed an expanding trend, with an expanding rate of 0.62 % yr−1. The clean glaciers retreated faster in the southeast and slower in the northwest, while the debris-covered glaciers expanded in most basins. The debris-covered glaciers were generally located at lower elevation areas than those of the clean glaciers. The slopes of clean glaciers were mainly in the range of 0–50°, while the slopes of debris-covered glaciers were mainly in the range of 0–30°. Climate warming was a main driver of glacier change. The clean glacier area was correlated negatively with average temperature in summer and positively with average precipitation in winter, while the debris-covered glacier area was correlated positively with both. The results of the study may provide a basis for scientific management of glaciers on the Tibetan Plateau in the context of climate warming. [ABSTRACT FROM AUTHOR]

The ablation zones of debris-covered glaciers in Himalaya exhibit heterogeneous processes and melt patterns. Although sub-debris melt is measured at ablation stakes, the high variability of debris thickness necessitates distributed melt measurements at the glacier scale. Focusing on Annapurna III Glacier, we used uncrewed aerial system (UAS) photogrammetry to estimate total volume loss and slope-perpendicular glacier melt between May and November 2019 using flow-corrected point clouds. Results indicated the average elevation change was −1.10 ± 0.19 m, while the mean melt was −0.87 m w.e., equating to a mean melt rate of −0.47 cm w.e. d−1. However, the spatial pattern was highly variable due to complex local processes necessitating future study over short intervals. The evaluation of specific areas showed the interplay of debris thickness variability, subseasonal debris redistribution, supraglacial channel reconfiguration and the imprint of relict ice cliffs in leading to contemporary melt rates. Ice cliffs had higher melt distances (mean −3.9 ± 0.19 m) compared to non-cliff areas (mean −0.75 ± 0.19 m) and were the predominant control on the spatial patterns of seasonal melt rates. Crucially, the definition of ice cliff areas from thinning data has a profound impact on derived melt rates and melt enhancement. Our study demonstrates the possibility and utility of deriving fully-distributed slope-perpendicular melt measurements.

The objective of this work is to conduct a detailed mapping of the Héðinsdalsjökull foreland, northern Iceland (65°39′N, 18°55′W). This cirque currently shows a variety of glacial and periglacial landforms derived from a complex deglaciation. Mapping was performed combining traditional hand-drawn and digital mapping. A hand-drawn sketch was georeferenced in ArcMap 10.7.1, supported on an aerial photograph (year 2000). Its vectorization, symbolization and final design were done in the computer-aided design (CAD) software MicroStation Connect. Complementary high-resolution Digital Surface Models were obtained from historical aerial photographs and ground-view field photographs through the application of Structure from Motion (SfM) photogrammetry. To improve the topographic expression of the geomorphological map, a photorealistic 3D view has been generated. The final map highlights the complexity of the foreland and the coexistence existence of a range of different units and landforms. The map will ease future studies on the transformation of receding glaciers.

As a particular type of alpine glacier, debris-covered glaciers are essential for local water resources and glacial disaster warnings. The Eastern Tomur Peak Region (EPTR) is the most concentrated glacier in Tien Shan Mountain, China, where the glaciers have not been studied in detail. This paper evaluates the delineation accuracy of Landsat8 OLI, Sentinel-1A, and GF images for debris-covered glaciers in the EPTR. Each image uses the most advanced delineation method for itself to minimize the error of inherent resolutions. The results show that the accuracy of these images for delineating debris-covered glaciers is very high, and the F1 scores are expressed as 96.73%, 93.55%, and 95.81%, respectively. Therefore, Landsat images were selected to analyze the area change of EPTR from 2000 to 2022 over a 5-year time scale. The results indicate that glaciers of the EPTR decreased by 19.05 km2 from 2000 to 2020, accounting for 1.9% (0.08% a−1), and debris increased by 10.8%, which validates the opinion that the presence of debris inhibits glacier melting. The most varied time was 2010–2022, but it was much less than other Tien Shan regions. The lower glacier ablation rate in this area results from the combined effect of decreased bare ice and increased debris. The main reason for the change in debris-covered glaciers is the increase in temperature.

The ablation zones of debris-covered glaciers in Himalaya exhibit heterogeneous processes and melt patterns. Although sub-debris melt is measured at ablation stakes, the high variability of debris thickness necessitates distributed melt measurements at the glacier scale. Focusing on Annapurna III Glacier, we used uncrewed aerial system (UAS) photogrammetry to estimate total volume loss and slope-perpendicular glacier melt between May and November 2019 using flow-corrected point clouds. Results indicated the average elevation change was −1.10 ± 0.19 m, while the mean melt was −0.87 m w.e., equating to a mean melt rate of −0.47 cm w.e. d−1. However, the spatial pattern was highly variable due to complex local processes necessitating future study over short intervals. The evaluation of specific areas showed the interplay of debris thickness variability, subseasonal debris redistribution, supraglacial channel reconfiguration and the imprint of relict ice cliffs in leading to contemporary melt rates. Ice cliffs had higher melt distances (mean −3.9 ± 0.19 m) compared to non-cliff areas (mean −0.75 ± 0.19 m) and were the predominant control on the spatial patterns of seasonal melt rates. Crucially, the definition of ice cliff areas from thinning data has a profound impact on derived melt rates and melt enhancement. Our study demonstrates the possibility and utility of deriving fully-distributed slope-perpendicular melt measurements. [ABSTRACT FROM AUTHOR]

Meltwater habitats are found on glacier surfaces worldwide, but much of the current understanding of these habitats comes from clean glaciers sprinkled with cryoconite. Cryoconite is windblown dust particles covered with biological material that form small meltwater holes due to difference in the albedo of cryoconite compared to clean ice. However, no information is available on the physical, chemical, and biological characteristics of supraglacial pools on debris-covered glaciers. We measured physical and chemical variables and sampled macroinvertebrates from forty-six supraglacial pools during the summers of 2018 and 2019 on the debris-covered Hailuogou Glacier in southeastern Tibet. Our physical and chemical results indicated that the sampled supraglacial pools exhibited a greater diversity of shapes, were larger, contained larger substrate sizes, and had greater substrate diversity than cryoconite holes. The sampled supraglacial pools frequently contained Chironomidae (Diptera) and Isotomidae (Collembola), which are macroinvertebrate taxa that are uncommon in cryoconite holes. Chironomidae occurrence and abundance was not correlated with any measured environmental variable. The best predictors of Isotomidae and macroinvertebrate occurrence and abundance were conductivity, ice to water surface depth, and number of supraglacial pools within 5 m. Our results highlight the uniqueness of supraglacial pools on a debris-covered glacier in southeastern Tibet.

The physical and geochemical characteristics of shallow ice cores drilled in the accumulation area (Western Cwm) of Khumbu Glacier in the Nepal Himalayas in 1980 were analyzed. The two ice cores from different elevations (cores 1 and 2 from 6,100 and 6,400 m a.s.l., respectively) showed distinct stratigraphy: Core 1 consisted of stratified firn layers with a few ice and dust layers, whereas core 2 consisted of unstratified refrozen ice with abundant debris. The mean oxygen-stable isotope was significantly lower in core 2 than in core 1, and the composition of major soluble ions also differed between the ice cores. The mineralogical characteristics of debris in core 2 were in accordance with the geology of the south face of Mt. Everest, indicating that it was supplied from above 7,000 m a.s.l. by avalanches. The distinct stratigraphy and geochemistry suggest that the snow accumulation process differed between the two drilling sites; snow was supplied by precipitation in core 1, whereas in core 2 it was supplied by avalanche with rock debris from the higher site of the south face of Mt. Everest. The two distinct snow accumulation processes are likely to characterize the mass balance and formation of debris covers of the lower ablation area of Khumbu Glacier.

Debris-covered glaciers have contrasting melting mechanisms and climate response patterns if compared with debris-free glaciers and thus show a unique influence on the hydrological process. Based on high-resolution satellite images and unpiloted aerial vehicle surveys, this study investigated the dynamic changes of Zhuxi Glacier, a thick debris-covered glacier in the southeastern Tibetan Plateau. Our result shows that the whole glacier can be divided into the active regime and stagnant regime along the elevation of 3400 m a.s.l. The mean surface velocity of the active regime was 13.1 m yr−1, which was five times higher than that of the stagnant regime. The surface-lowing rate of this debris-covered glacier reaches more than 1 m yr−1 and displays an accelerating trend. The majority of ice loss concentrates around ice cliffs and supraglacial ponds, the ablation hotspots. These hotspots can be roughly classified into three types, including persistent, expanding, and shrinking patterns, at different dynamic regimes on the Zhuxi Glacier. With the evolution of these hotpots and glacier dynamic changes, the supraglacial ponds showed significant change, with the total number fluctuating from 15 to 38 and the total area increasing from 1128 m2 to 95790 m2 during the past decade. The recent exponential expansion of the proglacial lake and the significant downwasting of stagnant ice inside the dammed terminus moraine possibly trigger the glacial lake outburst flood and thus threaten the security of livelihoods and infrastructure downstream.

Ongoing changes in mountain glaciers affect local water resources, hazard potential and global sea level. An increasing proportion of remaining mountain glaciers are affected by the presence of a surface cover of rock debris, and the response of these debris-covered glaciers to climate forcing is different to that of glaciers without a debris cover. Here we take a back-to-basics look at the fundamental terms that control the processes of debris evolution at the glacier surface, to illustrate how the trajectory of debris cover development is partially decoupled from prevailing climate conditions, and that the development of a debris cover over time should prevent the glacier from achieving steady state. We discuss the approaches and limitations of how this has been treated in existing modeling efforts and propose that “surrogate world” numerical representations of debris-covered glaciers would facilitate the development of well-validated parameterizations of surface debris cover that can be used in regional and global glacier models. Finally, we highlight some key research targets that would need to be addressed in order to enable a full representation of debris-covered glacier system response to climate forcing.

Glacier changes on the Tibetan Plateau are of great importance for regional climate and hydrology and even global ecological changes. It is urgent to understand the effect of climate warming on both clean and debris-covered glaciers on the Tibetan Plateau. This study used the double RF method and Landsat series images to extract clean glaciers and debris-covered glaciers on the Tibetan Plateau from 1985 to 2020 and analyzed their temporal and spatial changes under the background of climate change. The total area of glaciers on the Tibetan Plateau showed a retreating trend from 1985 to 2020, with an average retreat rate of −0.5 % yr−1. The area of clean glaciers showed a significant retreating trend, with a retreat rate of −0.55 % yr−1. The area of debris-covered glaciers showed an expanding trend, with an expanding rate of 0.62 % yr−1. The clean glaciers retreated faster in the southeast and slower in the northwest, while the debris-covered glaciers expanded in most basins. The debris-covered glaciers were generally located at lower elevation areas than those of the clean glaciers. The slopes of clean glaciers were mainly in the range of 0–50°, while the slopes of debris-covered glaciers were mainly in the range of 0–30°. Climate warming was a main driver of glacier change. The clean glacier area was correlated negatively with average temperature in summer and positively with average precipitation in winter, while the debris-covered glacier area was correlated positively with both. The results of the study may provide a basis for scientific management of glaciers on the Tibetan Plateau in the context of climate warming.

Mapping patterns of supraglacial debris thickness and understanding their controls are important for quantifying the energy balance and melt of debris-covered glaciers and building process understanding into predictive models. Here, we find empirical relationships between measured debris thickness and satellite-derived surface temperature in the form of a rational curve and a linear relationship consistently outperform two different exponential relationships, for five glaciers in High Mountain Asia (HMA). Across these five glaciers, we demonstrate the covariance of velocity and elevation, and of slope and aspect using principal component analysis, and we show that the former two variables provide stronger predictors of debris thickness distribution than the latter two. Although the relationship between debris thickness and slope/aspect varies between glaciers, thicker debris occurs at lower elevations, where ice flow is slower, in the majority of cases. We also find the first empirical evidence for a statistical correlation between curvature and debris thickness, with thicker debris on concave slopes in some settings and convex slopes in others. Finally, debris thickness and surface temperature data are collated for the five glaciers, and supplemented with data from one more, to produce an empirical relationship, which we apply to all glaciers across the entire HMA region. This rational curve: 1) for the six glaciers studied has a similar accuracy to but greater precision than that of an exponential relationship widely quoted in the literature; and 2) produces qualitatively similar debris thickness distributions to those that exist in the literature for three other glaciers. Despite the encouraging results, they should be treated with caution given our relationship is extrapolated using data from only six glaciers and validated only qualitatively. More (freely available) data on debris thickness distribution of HMA glaciers are required.

Known for their important role in locally enhancing surface melt, supraglacial ponds and ice cliffs are common features on debris-covered glaciers. We use high resolution satellite imagery to describe pond-cliff systems and surface velocity on Verde debris-covered glacier, Monte Tronador, and Southern Chile. Ponds and ice cliffs represent up to 0.4 and 2.7% of the glacier debris-covered area, respectively. Through the analyzed period and the available data, we found a seasonality in the number of detected ponds, with larger number of ponds at the beginning of the ablation season and less at the end of it. Using feature tracking, we determined glacier surface velocity, finding values up to 55 m/yr on the upper part of the debris-covered area, and decreasing almost to stagnation in the terminus. We found that larger ponds develop in glacier zones of low velocity, while zones of high velocity only contain smaller features. Meanwhile, ice cliffs appeared to be less controlled by surface velocity and gradient. Persistent ice cliffs were detected between 2009 and 2019 and backwasting up to 24 m/yr was measured, highlighting significant local glacier wastage.

A number of glaciological observations on debris-covered glaciers around the globe have shown a delayed length and mass adjustment in relation to climate variability, a behavior normally attributed to the ice insulation effect of thick debris layers. Dynamic interactions between debris cover, geometry and surface topography of debris-covered glaciers can nevertheless govern glacier velocities and mass changes over time, with many glaciers exhibiting high thinning rates in spite of thick debris cover. Such interactions are progressively being incorporated into glacier evolution research. In this paper we reconstruct changes in debris-covered area, surface velocities and surface features of three glaciers in the Patagonian Andes over the 1958–2020 period, based on satellite and aerial imagery and Digital Elevation Models. Our results show that debris cover has increased from 40 ± 0.6 to 50 ± 6.7% of the total glacier area since 1958, whilst glacier slope has slightly decreased. The gently sloping tongues have allowed surface flow velocities to remain relatively low (

Ice cliffs can act as “hot spots” for melt on debris-covered glaciers and promote local glacier mass loss. Repeat high-resolution remote-sensing data are therefore required to monitor the role of ice cliff dynamics in glacier mass loss. Here we analyze high-resolution aerial photogrammetry data acquired during the 2007, 2018, and 2019 post-monsoon seasons to delineate and monitor the morphology, distribution, and temporal changes of the ice cliffs across the debris-covered Trakarding Glacier in the eastern Nepal Himalaya. We generate an ice cliff inventory from the 2018 and 2019 precise terrain data, with ice cliffs accounting for 4.7 and 6.1% of the debris-covered area, respectively. We observe large surface lowering (>2.0 m a−1) where there is a denser distribution of ice cliffs. We also track the survival, formation, and disappearance of ice cliffs from 2018 to 2019, and find that ∼15% of the total ice cliff area is replaced by new ice cliffs. Furthermore, we observe the overall predominance of northwest-facing ice cliffs, although we do observe spatial heterogeneities in the aspect variance of the ice cliffs (ice cliffs face in similar/various directions). Many new ice cliffs formed across the stagnant middle sections of the glacier, coincident with surface water drainage and englacial conduit intake observations. This spatial relationship between ice cliffs and the glacier hydrological system suggests that these englacial and supraglacial hydrological systems play a significant role in ice cliff formation.

Debris cover on glaciers is an important component of glacial systems as it influences climate–glacier dynamics and thus the lifespan of glaciers. Increasing air temperatures, permafrost thaw and rock faces freshly exposed by glacier downwasting in accumulation zones result in increased rockfall activity and debris input. In the ablation zone, negative mass balances result in an enhanced melt‐out of englacial debris. Glacier debris cover thus represents a clear signal of climate warming in mountain areas. To assess the temporal development of debris on glaciers of the Eastern Alps, Austria, we mapped debris cover on 255 glaciers using Landsat data at three time steps. We applied a ratio‐based threshold classification technique and analysed glacier catchment characteristics to understand debris sources better. Across the Austrian Alps, debris cover increased by more than 10% between 1996 and 2015 while glaciers retreated in response to climate warming. Debris cover distribution shows significant regional variability, with some mountain ranges being characterised by mean debris cover on glaciers of up to 75%. We also observed a general rise of the mean elevation of debris cover on glaciers in Austria. The debris cover distribution and dynamics are highly variable due to topographic, lithological and structural settings that determine the amount of debris delivered to and stored in the glacier system. Despite strong variation in debris cover, all glaciers investigated melted at increasing rates. We conclude that the retarding effects of debris cover on the mass balance and melt rate of Austrian glaciers is strongly subdued compared with other mountain areas. The study indicates that, if this trend continues, many glaciers in Austria may become fully debris covered. However, since debris cover seems to have little impact on melt rates, this would not lead to prolonged existence of debris‐covered ice compared with clean ice glaciers. [ABSTRACT FROM AUTHOR]

The north and east slopes of Mount Rainier, Washington, are host to three of the largest glaciers in the contiguous United States: Carbon Glacier, Winthrop Glacier, and Emmons Glacier. Each has an extensive blanket of supraglacial debris on its terminus, but recent work indicates that each has responded to late twentieth- and early twenty-first-century climate changes in a different way. While Carbon Glacier has thinned and retreated since 1970, Winthrop Glacier has remained steady and Emmons Glacier has thickened and advanced. There are several possible climatic and dynamic factors that can account for some of these disparities, but differences in supraglacial debris properties and distribution have not been systematically evaluated. We combine field measurements and satellite remote sensing analysis from a 10-day period in the 2014 melt season to estimate both the debris thickness distribution and key debris thermal properties on Emmons Glacier. A simplified energy-balance model was then used with debris surface temperatures derived from Landsat 8 thermal infrared bands to estimate the distribution of debris across all three debris-covered termini. The results suggest that differences in summer balance among these glaciers can be partly explained by differences in the thermal resistance of their debris mantles.

This work defends and applies a new proposal for mapping debris-covered glaciers and rock glaciers. This proposal combines highly accurate traditional methods, such as manual geomorphological photointerpretation, with novel digital techniques. The new methodological strategy applies rendering and lighting tools from Computer-Aided Design platforms and uses graphic design from Desktop Publishing Programs, to improve the geovisualization of geomorphological maps. This combination was applied to the debris-covered glacier and a set of rock glaciers located on the Tröllaskagi peninsula (northern Iceland). The result is a 1:4,500 scale geomorphological map of 16 km2, which for the first time maps the features that differentiate the debris-covered glacier from rock glaciers, as well as genetically different units within each formation and a long series of landforms characteristic of different processes. This map thus becomes a very useful tool in the evolutionary study of these formations in relation to the impact of climate change.

Mountains are global biodiversity hotspots where cold environments and their associated ecological communities are threatened by climate warming. Considerable research attention has been devoted to understanding the ecological effects of alpine glacier and snowfield recession. However, much less attention has been given to identifying climate refugia in mountain ecosystems where present‐day environmental conditions will be maintained, at least in the near‐term, as other habitats change. Around the world, montane communities of microbes, animals, and plants live on, adjacent to, and downstream of rock glaciers and related cold rocky landforms (CRL). These geomorphological features have been overlooked in the ecological literature despite being extremely common in mountain ranges worldwide with a propensity to support cold and stable habitats for aquatic and terrestrial biodiversity. CRLs are less responsive to atmospheric warming than alpine glaciers and snowfields due to the insulating nature and thermal inertia of their debris cover paired with their internal ventilation patterns. Thus, CRLs are likely to remain on the landscape after adjacent glaciers and snowfields have melted, thereby providing longer‐term cold habitat for biodiversity living on and downstream of them. Here, we show that CRLs will likely act as key climate refugia for terrestrial and aquatic biodiversity in mountain ecosystems, offer guidelines for incorporating CRLs into conservation practices, and identify areas for future research. [ABSTRACT FROM AUTHOR]

Debris-covered glaciers from around the world offer distinct environmental, climatic, and historical conditions from which to study the effects of debris on glacier-ice evolution. A rich literature on debris-covered glaciers exists from decades of field work, laboratory studies, remote-sensing observations, and numerical modeling. In general, the base of knowledge established by studying periglacial, glacial, and paraglacial landforms on Earth has been applied to aid interpretation of ice-rich or ice-remnant landforms on Mars, but research has progressed on both planets. For Mars, the spatial distribution of lobate debris aprons and glacier-like forms, in particular, is critical to constraining past climate conditions when such features were active, reconstructing past ice extent, and estimating the total inventory of buried ice remaining in the mid-latitudes of Mars. This review spans a range of knowledge about debris-covered glaciers on Earth, in order to add context to investigations of dust and debris-covered ice on Mars and to put research on both planets in a perspective aimed at maximizing process-based understanding of glacier evolution. The state of knowledge and some gaps in knowledge on Mars are discussed in relation to possible avenues for future research in how landforms are classified, advances in comparative planetology, and new understanding from future missions. While this review is focused primarily on processes controlling active debris-covered glaciers, a key to understanding glacier change through time is to consider individual landforms in context with the full-system environment in which they are found. For Earth, this includes understanding local and regional controls on current glacier change, and how these processes relate to landform development in the past as well as what may develop in the future. For Mars, this includes evaluating how present-day landforms elucidate past ice activity and environmental conditions during epochs when orbital parameters, climate, and water ice distribution were substantially different. [ABSTRACT FROM AUTHOR]

There exists a need to advance our understanding of debris‐covered glacier surfaces over relatively short timescales due to rapid, climatically induced areal expansion of debris cover at the global scale, and the impact debris has on mass balance. We applied unpiloted aerial vehicle structure‐from‐motion (UAV‐SfM) and digital elevation model (DEM) differencing with debris thickness and debris stability modelling to unravel the evolution of a 0.15 km2 region of the debris‐covered Miage Glacier, Italy, between June 2015 and July 2018. DEM differencing revealed widespread surface lowering (mean 4.1 ± 1.0 m a‐1; maximum 13.3 m a‐1). We combined elevation change data with local meteorological data and a sub‐debris melt model, and used these relationships to produce high resolution, spatially distributed maps of debris thickness. These maps were differenced to explore patterns and mechanisms of debris redistribution. Median debris thicknesses ranged from 0.12 to 0.17 m and were spatially variable. We observed localized debris thinning across ice cliff faces, except those which were decaying, where debris thickened. We observed pervasive debris thinning across larger, backwasting slopes, including those bordered by supraglacial streams, as well as ingestion of debris by a newly exposed englacial conduit. Debris stability mapping showed that 18.2–26.4% of the survey area was theoretically subject to debris remobilization. By linking changes in stability to changes in debris thickness, we observed that slopes that remain stable, stabilize, or remain unstable between periods almost exclusively show net debris thickening (mean 0.07 m a‐1) whilst those which become newly unstable exhibit both debris thinning and thickening. We observe a systematic downslope increase in the rate at which debris cover thickens which can be described as a function of the topographic position index and slope gradient. Our data provide quantifiable insights into mechanisms of debris remobilization on glacier surfaces over sub‐decadal timescales, and open avenues for future research to explore glacier‐scale spatiotemporal patterns of debris remobilization. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd [ABSTRACT FROM AUTHOR]

Supraglacial debris covers 7% of mountain glacier area globally and generally reduces glacier surface melt. Enhanced energy absorption at ice cliffs and supraglacial ponds scattered across the debris surface leads these features to contribute disproportionately to glacier-wide ablation. However, the degree to which cliffs and ponds actually increase melt rates remains unclear, as these features have only been studied in a detailed manner for selected locations, almost exclusively in High Mountain Asia. In this study we model the surface energy balance for debris-covered ice, ice cliffs, and supraglacial ponds with a set of automatic weather station records representing the global prevalence of debris-covered glacier ice. We generate 5000 random sets of values for physical parameters using probability distributions derived from literature, which we use to investigate relative melt rates and to isolate the melt responses of debris, cliffs and ponds to the site-specific meteorological forcing. Modelled sub-debris melt rates are primarily controlled by debris thickness and thermal conductivity. At a reference thickness of 0.1 m, sub-debris melt rates vary considerably, differing by up to a factor of four between sites, mainly attributable to air temperature differences. We find that melt rates for ice cliffs are consistently 2–3× the melt rate for clean glacier ice, but this melt enhancement decays with increasing clean ice melt rates. Energy absorption at supraglacial ponds is dominated by latent heat exchange and is therefore highly sensitive to wind speed and relative humidity, but is generally less than for clean ice. Our results provide reference melt enhancement factors for melt modelling of debris-covered glacier sites, globally, while highlighting the need for direct measurement of debris-covered glacier surface characteristics, physical parameters, and local meteorological conditions at a variety of sites around the world.

Recently, Unmanned Aerial Vehicles (UAV) have opened up unparalleled opportunities for alpine glacier monitoring, as they allow for reconstructing extensive and high-resolution 3D models. In order to evaluate annual ice flow velocities and volume variations, six yearly measurements were carried out between 2015 and 2020 on the debris-covered Belvedere Glacier (Anzasca Valley, Italian Alps) with low-cost fixed-wing UAVs and quadcopters. Every year, ground control points and check points were measured with GNSS. Images acquired from UAV were processed with Structure-from-Motion and Multi-View Stereo algorithms to build photogrammetric models, orthophotos and digital surface models, with decimetric accuracy. Annual glacier velocities were derived by combining manually-tracked features on orthophotos with GNSS measurements. Velocities ranging between 17 m y−1 and 22 m y−1 were found in the central part of the glacier, whereas values between 2 m y−1 and 7 m y−1 were found in the accumulation area and at the glacier terminus. Between 2 × 106 m3 and 3.5 × 106 m3 of ice volume were lost every year. A pair of intra-year measurements (October 2017–July 2018) highlighted that winter and spring volume reduction was ∼1/4 of the average annual ice loss. The Belvedere monitoring activity proved that decimetric-accurate glacier models can be derived with low-cost UAVs and photogrammetry, limiting in-situ operations. Moreover, UAVs require minimal data acquisition costs and allow for great surveying flexibility, compared to traditional techniques. Information about annual flow velocities and ice volume variations of the Belvedere Glacier may have great value for further understanding glacier dynamics, compute mass balances, or it might be used as input for glacier flow modelling.

For carrying out glacier change analysis in Chandra basin, Western Himalaya, India during 1971–2016, glacier inventory is generated for year 2002 using Landsat Enhanced Thematic Mapper+ (ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM V2) data. Total 395 glaciers are mapped covering 703.3 ± 20.4 km2 area with minimum glacier size being >0.02 km2. Out of these, 59 glaciers have debris-covered ice covering an area of 67.2 ± 1.9 km2. In this study, a subset of 169 glaciers is used for glacier area change analysis using Corona KH-4B (1971), Landsat ETM+ (2002) and Sentinel-2 (2016) images due to the availability of cloud free data sources. In 1971, 639.4 ± 5.8 km2 glacier area is estimated which decreased to 620.2 ± 18.0 km2 (–3.0 ± 3.0%) in 2002 and 608.1 ± 10.3 km2 (–4.9 ± 1.9%) in 2016. The change in glacier length of Samudra Tapu and Gepang Gath glaciers is showing increasing trend since last two decades as compared to Hamtah, Chhota Shigri and Bara Shigri glaciers due to presence of pro-glacial lake at their snout. Clean-ice glaciers, glaciers with low mean elevation, glaciers having steep surface, glaciers with west to south and east to south orientation, small size glaciers and glaciers having pro-glacial lake at the snout are responsible to higher loss in glacier area. Statistical trend analysis using Mann-Kendall test and Sen's slope estimator test show that Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) based annual mean temperature have rising trend at a rate of 0.02°C per year during 1961–2015, and can be ascribed as one of the factors for glacier shrinking. [ABSTRACT FROM AUTHOR]

Meltwater habitats are found on glacier surfaces worldwide, but much of the current understanding of these habitats comes from clean glaciers sprinkled with cryoconite. Cryoconite is windblown dust particles covered with biological material that form small meltwater holes due to difference in the albedo of cryoconite compared to clean ice. However, no information is available on the physical, chemical, and biological characteristics of supraglacial pools on debris-covered glaciers. We measured physical and chemical variables and sampled macroinvertebrates from forty-six supraglacial pools during the summers of 2018 and 2019 on the debris-covered Hailuogou Glacier in southeastern Tibet. Our physical and chemical results indicated that the sampled supraglacial pools exhibited a greater diversity of shapes, were larger, contained larger substrate sizes, and had greater substrate diversity than cryoconite holes. The sampled supraglacial pools frequently contained Chironomidae (Diptera) and Isotomidae (Collembola), which are macroinvertebrate taxa that are uncommon in cryoconite holes. Chironomidae occurrence and abundance was not correlated with any measured environmental variable. The best predictors of Isotomidae and macroinvertebrate occurrence and abundance were conductivity, ice to water surface depth, and number of supraglacial pools within 5 m. Our results highlight the uniqueness of supraglacial pools on a debris-covered glacier in southeastern Tibet. [ABSTRACT FROM AUTHOR]

The presence of supraglacial debris on glaciers in the Himalaya-Karakoram affects the ablation rate of these glaciers and their response to climatic change. To understand how supraglacial debris distribution and associated surface features vary spatially and temporally, geomorphological mapping was undertaken on Baltoro Glacier, Karakoram, for three time-separated images between 2001–2012. Debris is supplied to the glacier system through frequent but small landslides at the glacier margin that form lateral and medial moraines and less frequent but higher volume rockfall events which are more lobate and often discontinuous in form. Debris on the glacier surface is identified as a series of distinct lithological units which merge downglacier of the convergence area between the Godwin-Austen and Baltoro South tributary glaciers. Debris distribution varies as a result of complex interaction between tributary glaciers and the main glacier tongue, complicated further by surge events on some tributary glaciers. Glacier flow dynamics mainly controls the evolution of a supraglacial debris layer. Identifying such spatial variability in debris rock type and temporal variability in debris distribution has implications for glacier ablation rate, affecting glacier surface energy balance. Accordingly, spatial and temporal variation in supraglacial debris should be considered when determining mass balance for these glaciers through time.

Debris-covered glaciers are common in many regions of the world, and accurately modelling their melt is of increasing importance for water resources planning, and biological and ecological research. In this study, we investigate meteorological and glaciological conditions and estimate the melt of Amola Glacier (a small debris-covered glacier in the Adamello-Presanella Massif, Italian Alps) using an empirical approach, based on shortwave radiation, surface temperature, debris thickness and thermal resistance. Meteorological conditions are determined from a supraglacial automatic weather station, while the model is calibrated using i) field data acquired during the ablation season 2020, including a network of ablation stakes and thermistors, ii) modelled solar radiation and iii) thermal imagery from Landsat 8 TIRS. The analysis of glacier meteorological conditions shows a high prevalence of cloud-covered (50.60% of daytime observations) and humid conditions, with a high daily air temperature range (22.24 °C). Analysis of thermistor data suggests that a linear thermal gradient of the debris layer can be assumed when the model is run at daily resolution. Modelled debris thickness, surface temperatures and melt capture patterns observed on the field, including the decrease in debris thickness and increasing melt with elevation and their variability across the glacier surface. The root mean square error between measured and observed melt is 0.16 m, corresponding to 22% of the average observed melt, in line with the performance of empirical models for debris-free and debris-covered ice. The model could thus be used to provide a first estimate of debris-covered ice melt for glaciers in the Adamello region. Improvements to the model would require measuring all energy fluxes on the glacier from a weather station and investigating their spatial distribution on the glacier surface. • We set up an automatic weather station on an Alpine debris-covered glacier. • We used field, meteorological and satellite data to estimate buried ice melt. • Cloud-covered and humid conditions prevail on the glacier in summer 2020. • Modelled melt and debris thickness capture patterns observed on the field. • RMSE between modelled and measured buried ice melt is 0.16 m. [ABSTRACT FROM AUTHOR]

Glaciers in High Mountain Asia (HMA) have a significant impact on human activity. Thus, a detailed and up-to-date inventory of glaciers is crucial, along with monitoring them regularly. The identification of debris-covered glaciers is a fundamental and yet challenging component of research into glacier change and water resources, but it is limited by spectral similarities with surrounding bedrock, snow-affected areas, and mountain-shadowed areas, along with issues related to manual discrimination. Therefore, to use fewer human, material, and financial resources, it is necessary to develop better methods to determine the boundaries of debris-covered glaciers. This study focused on debris-covered glacier mapping using a combination of related technologies such as random forest (RF) and convolutional neural network (CNN) models. The models were tested on Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) data and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), selecting Eastern Pamir and Nyainqentanglha as typical glacier areas on the Tibetan Plateau to construct a glacier classification system. The performances of different classifiers were compared, the different classifier construction strategies were optimized, and multiple single-classifier outputs were obtained with slight differences. Using the relationship between the surface area covered by debris and the machine learning model parameters, it was found that the debris coverage directly determined the performance of the machine learning model and mitigated the issues affecting the detection of active and inactive debris-covered glaciers. Various classification models were integrated to ascertain the best model for the classification of glaciers.