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Glaciers in High Mountain Asia generate meltwater that supports the water needs of 250 million people, but current knowledge of annual accumulation and ablation is limited to sparse field measurements biased in location and glacier size. Here, we present altitudinally-resolved specific mass balances (surface, internal, and basal combined) for 5527 glaciers in High Mountain Asia for 2000–2016, derived by correcting observed glacier thinning patterns for mass redistribution due to ice flow. We find that 41% of glaciers accumulated mass over less than 20% of their area, and only 60% ± 10% of regional annual ablation was compensated by accumulation. Even without 21 st century warming, 21% ± 1% of ice volume will be lost by 2100 due to current climatic-geometric imbalance, representing a reduction in glacier ablation into rivers of 28% ± 1%. The ablation of glaciers in the Himalayas and Tien Shan was mostly unsustainable and ice volume in these regions will reduce by at least 30% by 2100. The most important and vulnerable glacier-fed river basins (Amu Darya, Indus, Syr Darya, Tarim Interior) were supplied with >50% sustainable glacier ablation but will see long-term reductions in ice mass and glacier meltwater supply regardless of the Karakoram Anomaly. Glaciers in High Mountain Asia are a key water resource. The authors use remote sensing data and a regional implementation of the continuity equation to quantify glacier ablation and accumulation rates for 2000–2016, and establish current climatic-geometric imbalances that imply strong reductions in ice volume by 2100.

Glaciers are often located in steep mountain settings and avalanches from surrounding slopes can strongly influence snow accumulation patterns on their surface. This effect has however never been quantified for more than a few glaciers and the impact on the future evolution of glaciers is unclear. We coupled an avalanche and a glacier model to estimate the contribution of avalanches to the accumulation of all glaciers in the world and how this affects their evolution throughout the 21st century. Globally, 3% of the snow accumulation on glaciers comes from avalanches and 1% is removed by avalanches. This net contribution varies between regions and glaciers, with a maximum of 15% for New Zealand. Accounting for avalanches modifies the altitudinal pattern of glacier mass balance and the projected evolution of individual glaciers. The main effects include (1) a longer persistence of small glaciers, with for example three times more ice retained by glaciers smaller than 1 km 2 in Central Europe under a low-emission scenario, and (2) an increased sensitivity of high-elevation accumulation zones to future warming. We anticipate the relative influence of avalanches to increase in the future and advocate for a better monitoring of this process and representation in glacier models. This works presents an estimate of the contribution of avalanches to the mass balance of all glaciers in the world and its planned evolution throughout the 21st century, as well as the implications for the glacier mass balance and evolution.

Supraglacial debris strongly modulates glacier melt rates and can be decisive for ice dynamics and mountain hydrology. It is ubiquitous in High-Mountain Asia, yet because its thickness and supply rate from local topography are poorly known, our ability to forecast regional glacier change and streamflow is limited. Here we combined remote sensing and numerical modelling to resolve supraglacial debris thickness by altitude for 4689 glaciers in High-Mountain Asia, and debris-supply rate to 4141 of those glaciers. Our results reveal extensively thin supraglacial debris and high spatial variability in both debris thickness and supply rate. Debris-supply rate increases with the temperature and slope of debris-supply slopes regionally, and debris thickness increases as ice flow decreases locally. Our centennial-scale estimates of debris-supply rate are typically an order of magnitude or more lower than millennial-scale estimates of headwall-erosion rate from Beryllium-10 cosmogenic nuclides, potentially reflecting episodic debris supply to the region’s glaciers.

Ice cliff distribution plays a major role in determining the melt of debris‐covered glaciers but its controls are largely unknown. We assembled a data set of 37,537 ice cliffs and determined their characteristics across 86 debris‐covered glaciers within High Mountain Asia (HMA). We find that 38.9% of the cliffs are stream‐influenced, 19.5% pond‐influenced and 19.7% are crevasse‐originated. Surface velocity is the main predictor of cliff distribution at both local and glacier scale, indicating its dependence on the dynamic state and hence evolution stage of debris‐covered glacier tongues. Supraglacial ponds contribute to maintaining cliffs in areas of thicker debris, but this is only possible if water accumulates at the surface. Overall, total cliff density decreases exponentially with debris thickness as soon as the debris layer reaches a thickness of over 10 cm. Plain Language Summary Debris‐covered glaciers are common throughout the world's mountain ranges and are characterized by the presence of steep ice cliffs among the debris‐covered ice. It is well‐known that the cliffs are responsible for a large portion of the melt of these glaciers but the controls on their formation, development and distribution across glaciers remains poorly understood. Novel mapping approaches combined with high‐resolution satellite and drone products enabled us to disentangle some of these controls and to show that the ice cliffs are generally formed and maintained by the surface hydrology (ponds or streams) or by the opening of crevasses. As a result, they depend both at the local and glacier scale on the dynamic state of the glaciers as well as the evolution stage of their debris cover. This provides a pathway to better represent their contribution to glacier melt in predictive glacier models. Key Points We derived an unprecedented data set of 37,537 ice cliffs and their characteristics across 86 debris‐covered glaciers in High Mountain Asia We find that 38.9% of the cliffs are stream‐influenced, 19.5% pond‐influenced and 19.7% are crevasse‐originated Ice cliff distribution can be predicted by velocity, as an indicator of the dynamics and state of evolution of debris‐covered glaciers

Ice cliffs on debris-covered glaciers act as melt hotspots that considerably enhance glacier ablation. However, studies are typically limited in time and space; glacier-scale studies of this process of ice cliff melt are rare, and their varying seasonal energy balance remains largely unknown. In this study, we combined a process-based ice cliff backwasting model with high-resolution (1.0 m) photogrammetry-based terrain data to simulate the year-round melt of 479 ice cliffs on Trakarding Glacier, Nepal Himalaya. Ice cliff melt accounted for 26% of the mass loss of the glacier from October 2018 to October 2019, despite covering only 1.7% of the glacier surface. The annual melt rate of ice cliffs was 2.7 cm w.e. d−1, which is 8–9 times higher than the sub-debris melt rate. Ice cliff melt rates were significantly controlled by their aspects, with south-facing ice cliffs showing a melt rate 1.8 times higher than that of north facing ones. The results revealed that the aspect dependence of ice cliff melt rate was amplified in winter and decreased/disappeared toward the monsoon season. The seasonal changes in melt characteristics are considered to be related to variations in direct shortwave radiation onto the cliff surface, which are dependent on changes in solar altitude and monsoonal cloud cover.

Glacier albedo determines the net shortwave radiation absorbed at the glacier surface and plays a crucial role in glacier energy and mass balance. Remote sensing techniques are efficient means to retrieve glacier surface albedo over large and inaccessible areas and to study its variability. However, corrections of anisotropic reflectance of glacier surface have been established for specific shortwave bands only, such as Landsat 5 Thematic Mapper (L5/TM) band 2 and band 4, which is a major limitation of current retrievals of glacier broadband albedo. In this study, we calibrated and evaluated four anisotropy correction models for glacier snow and ice, applicable to visible, near-infrared and shortwave-infrared wavelengths using airborne datasets of Bidirectional Reflectance Distribution Function (BRDF). We then tested the ability of the best-performing anisotropy correction model, referred to from here on as the ‘updated model’, to retrieve albedo from L5/TM, Landsat 8 Operational Land Imager (L8/OLI) and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and evaluated these results with field measurements collected on eight glaciers around the world. Our results show that the updated model: (1) can accurately estimate anisotropic factors of reflectance for snow and ice surfaces; (2) generally performs better than prior approaches for L8/OLI albedo retrieval but is not appropriate for L5/TM; (3) generally retrieves MODIS albedo better than the MODIS standard albedo product (MCD43A3) in both absolute values and glacier albedo temporal evolution, i.e., exhibiting both fewer gaps and better agreement with field observations. As the updated model enables anisotropy correction of a maximum of 10 multispectral bands and is implemented in Google Earth Engine (GEE), it is promising for observing and analyzing glacier albedo at large spatial scales.

Central Asia hosts some of the world’s last relatively healthy mountain glaciers and is heavily dependent on snow and ice melt for downstream water supply, though the causes of this stable glacier state are not known. We combine recent in-situ observations, climate reanalysis and remote sensing data to force a land-surface model to reconstruct glacier changes over the last two decades (1999–2023) and disentangle their causes over a benchmark glacierized catchment in Tajikistan. We show that snowfall and snow depth have been substantially lower since 2018, leading to a decline in glacier health and reduced runoff generation. Remote-sensing observations confirm wider snow depletion across the Northwestern Pamirs, suggesting that a lack of snowfall might be a cause of mass losses regionally. Our results provide an explanation for the recent decline in glacier health in the region, and reinforce the need to better understand the variability of precipitation. The recent decline in glacier health and reduced runoff generation in the Northwestern Pamirs is primarily driven by substantially lower snowfall and snow depth since 2018, according to land-surface model reconstructions from 1999–2023 combining in-situ observations, climate reanalysis, and remote sensing data.

Mountains are important suppliers of freshwater to downstream areas, affecting large populations in particular in High Mountain Asia (HMA). Yet, the propagation of water from HMA headwaters to downstream areas is not fully understood, as interactions in the mountain water cycle between the cryo-, hydro- and biosphere remain elusive. We review the definition of blue and green water fluxes as liquid water that contributes to runoff at the outlet of the selected domain (blue) and water lost to the atmosphere through vapor fluxes, that is evaporation from water, ground, and interception plus transpiration (green) and propose to add the term white water to account for the (often neglected) evaporation and sublimation from snow and ice. We provide an assessment of models that can simulate the cryo-hydro-biosphere continuum and the interactions between spheres in high mountain catchments, going beyond disciplinary separations. Land surface models are uniquely able to account for such complexity, since they solve the coupled fluxes of water, energy, and carbon between the land surface and atmosphere. Due to the mechanistic nature of such models, specific variables can be compared systematically to independent remote sensing observations - providing vital insights into model accuracy and enabling the understanding of the complex watersheds of HMA. We discuss recent developments in spaceborne earth observation products that have the potential to support catchment modeling in high mountain regions. We then present a pilot study application of the mechanistic land surface model Tethys & Chloris to a glacierized watershed in the Nepalese Himalayas and discuss the use of high-resolution earth observation data to constrain the meteorological forcing uncertainty and validate model results. We use these insights to highlight the remaining challenges and future opportunities that remote sensing data presents for land surface modeling in HMA.

This project explored the integrated use of satellite, ground observations and hydrological distributed models to support water resources assessment and monitoring in High Mountain Asia (HMA). Hydrological data products were generated taking advantage of the synergies of European and Chinese data assets and space-borne observation systems. Energy-budget-based glacier mass balance and hydrological models driven by satellite observations were developed. These models can be applied to describe glacier-melt contribution to river flow. Satellite hydrological data products were used for forcing, calibration, validation and data assimilation in distributed river basin models. A pilot study was carried out on the Red River basin. Multiple hydrological data products were generated using the data collected by Chinese satellites. A new Evapo-Transpiration (ET) dataset from 2000 to 2018 was generated, including plant transpiration, soil evaporation, rainfall interception loss, snow/ice sublimation and open water evaporation. Higher resolution data were used to characterize glaciers and their response to environmental forcing. These studies focused on the Parlung Zangbo Basin, where glacier facies were mapped with GaoFeng (GF), Sentinal-2/Multi-Spectral Imager (S2/MSI) and Landsat8/Operational Land Imager (L8/OLI) data. The geodetic mass balance was estimated between 2000 and 2017 with Zi-Yuan (ZY)-3 Stereo Images and the SRTM DEM. Surface velocity was studied with Landsat5/Thematic Mapper (L5/TM), L8/OLI and S2/MSI data over the period 2013–2019. An updated method was developed to improve the retrieval of glacier albedo by correcting glacier reflectance for anisotropy, and a new dataset on glacier albedo was generated for the period 2001–2020. A detailed glacier energy and mass balance model was developed with the support of field experiments at the Parlung No. 4 Glacier and the 24 K Glacier, both in the Tibetan Plateau. Besides meteorological measurements, the field experiments included glaciological and hydrological measurements. The energy balance model was formulated in terms of enthalpy for easier treatment of water phase transitions. The model was applied to assess the spatial variability in glacier melt. In the Parlung No. 4 Glacier, the accumulated glacier melt was between 1.5 and 2.5 m w.e. in the accumulation zone and between 4.5 and 6.0 m w.e. in the ablation zone, reaching 6.5 m w.e. at the terminus. The seasonality in the glacier mass balance was observed by combining intensive field campaigns with continuous automatic observations. The linkage of the glacier and snowpack mass balance with water resources in a river basin was analyzed in the Chiese (Italy) and Heihe (China) basins by developing and applying integrated hydrological models using satellite retrievals in multiple ways. The model FEST-WEB was calibrated using retrievals of Land Surface Temperature (LST) to map soil hydrological properties. A watershed model was developed by coupling ecohydrological and socioeconomic systems. Integrated modeling is supported by an updated and parallelized data assimilation system. The latter exploits retrievals of brightness temperature (Advanced Microwave Scanning Radiometer, AMSR), LST (Moderate Resolution Imaging Spectroradiometer, MODIS), precipitation (Tropical Rainfall Measuring Mission (TRMM) and FengYun (FY)-2D) and in-situ measurements. In the case study on the Red River Basin, a new algorithm has been applied to disaggregate the SMOS (Soil Moisture and Ocean Salinity) soil moisture retrievals by making use of the correlation between evaporative fraction and soil moisture.