Glacier surges can create ice-dammed lakes when the advancing terminus blocks drainage. Such lakes are inherently unstable and can drain abruptly as glacial lake outburst floods (GLOFs), presenting a hazard to downstream populations and infrastructure in high mountain environments. We present satellite image analysis of the evolution of an ice-dammed lake formed by the 2018–20 surge of Shisper Glacier, western Karakoram. Our analysis identifies six phases of lake evolution. A large lake of up to 33.7 ± 9% million m3 formed in 2018–19, 2019–20, 2020–21 and 2021–22. In each case, the lake began to fill late in the year, reached a maximum size in May, and had completely drained between May and July, typically over 1–2 days. This analysis provides further evidence that GLOF hazards associated with lakes dammed by glacier surges can persist for several years after surge termination.

High Mountain Asia (HMA) glaciers are critical water reserves for montane regions, which are readily influenced by climate change. The glacier mass balance during 2000–2021 over HMA was estimated by comparing the elevations from ICESat-2 and the NASADEM. Radar penetration depth could be one of the intrinsic error sources in estimating glacier mass balance by using NASADEM. Therefore, we doubled elevation differences between the X-band Shuttle Radar Topography Missions (SRTMs) and NASADEM to estimate the potential error. The spatial characteristics of the altitude-dependent penetration depth can be detected in most sub-regions of HMA. Relatively deep penetrations in the Himalaya (2.3–3.7 m) and Hissar Alay (4.3 m) regions and small penetrations in the south-eastern HMA (1.0 m) were observed. The HMA region experienced a significant mass loss at a rate of −0.18 ± 0.12 m w.e. a−1, in which the Hengduan Shan exhibited the highest mass loss of −0.62 ± 0.10 m w.e. a−1, the West Kun Lun experienced a substantial mass gain of 0.23 ± 0.13 m w.e. a−1, and the Karakoram showed a more or less balance. Our results are in agreement with previous studies that assessed the mass balance of HMA glaciers from different methods.

Bedrock overdeepenings exposed by continued glacial retreat can store precipitation and meltwater, potentially leading to the formation of new proglacial lakes. These lakes may pose threats of glacial lake outburst floods (GLOFs) in high mountain areas, particularly if new lakes form in geomorphological setups prone to triggering events such as landslides or moraine collapses. We present the first complete inventory for future glacial lakes in High Mountain Asia by computing the subglacial bedrock for ~100 000 glaciers and estimating overdeepening area, volume and impact hazard for the larger potential lakes. We detect 25 285 overdeepenings larger than 104 m2 with a volume of 99.1 ± 28.6 km3 covering an area of 2683 ± 773.8 km2. For the 2700 overdeepenings larger than 105 m2, we assess the lake predisposition for mass-movement impacts that could trigger a GLOF by estimating the hazard of material detaching from surrounding slopes. Our findings indicate a shift in lake area, volume and GLOF hazard from the southwestern Himalayan region toward the Karakoram. The results of this study can be used for anticipating emerging threats and potentials connected to glacial lakes and as a basis for further studies at suspected GLOF hazard hotspots.

The response of glaciers to climate change has major implications for sea-level change and water resources around the globe. Large-scale glacier evolution models are used to project glacier runoff and mass loss, but are constrained by limited observations, which result in models being over-parameterized. Recent systematic geodetic mass-balance observations provide an opportunity to improve the calibration of glacier evolution models. In this study, we develop a calibration scheme for a glacier evolution model using a Bayesian inverse model and geodetic mass-balance observations, which enable us to quantify model parameter uncertainty. The Bayesian model is applied to each glacier in High Mountain Asia using Markov chain Monte Carlo methods. After 10,000 steps, the chains generate a sufficient number of independent samples to estimate the properties of the model parameters from the joint posterior distribution. Their spatial distribution shows a clear orographic effect indicating the resolution of climate data is too coarse to resolve temperature and precipitation at high altitudes. Given the glacier evolution model is over-parameterized, particular attention is given to identifiability and the need for future work to integrate additional observations in order to better constrain the plausible sets of model parameters.

Supraglacial ponds play a key role in absorbing atmospheric energy and directing it to the ice of debris-covered glaciers, but the spatial and temporal distribution of these features is not well documented. We analyse 172 Landsat TM/ETM+ scenes for the period 1999–2013 to identify thawed supraglacial ponds for the debris-covered tongues of five glaciers in the Langtang Valley of Nepal. We apply an advanced atmospheric correction routine (Landcor/6S) and use band ratio and image morphological techniques to identify ponds and validate our results with 2.5 m Cartosat-1 observations. We then characterize the spatial, seasonal and interannual patterns of ponds. We find high variability in pond incidence between glaciers (May–October means of 0.08–1.69% of debris area), with ponds most frequent in zones of low surface gradient and velocity. The ponds show pronounced seasonality, appearing in the pre-monsoon as snow melts, peaking at the monsoon onset at 2% of debris-covered area, then declining in the post-monsoon as ponds drain or freeze. Ponds are highly recurrent and persistent, with 40.5% of pond locations occurring for multiple years. Rather than a trend in pond cover over the study period, we find high interannual variability for each glacier after controlling for seasonality.