Glacier Ice Thickness Research Articles

Ice Thickness Measurement and Volume Modeling of Muztagh Ata Glacier No.16, Eastern Pamir

As a heavily glaciated region, the Eastern Pamir plays a crucial role in regional water supply. However, considerable ambiguity surrounds the distribution of glacier ice thickness and the details of ice volume. Accurate data at the local scale are largely insufficient. In this study, ground-penetrating radar (GPR) was applied to assess the ice thickness at Muztagh Glacier No.16 (MG16) in Muztagh Ata, Eastern Pamir, for the first time, detailing findings from four distinct profiles, bridging the gap in regional measurements. We utilized a total of five different methods based on basic shear stress, surface velocity, and mass conservation, aimed at accurately delineating the ice volume and distribution for MG16. Verification was conducted using measured data, and an aggregated model outcome provided a unified view of ice distribution. The different models showed good agreement with the measurements, but there were differences in the unmeasured areas. The composite findings indicated the maximum ice thickness of MG16 stands at 115.87 ± 4.55 m, with an ice volume calculated at 0.27 ± 0.04 km3. This result is relatively low compared to the findings of other studies, which lies in the fact that the GPR measurements somewhat constrain the model. However, the model parameters remain the primary source of uncertainty. The results from this study can be used to enhance water resource assessments for future glacier change models.

Ensemble modelling of ice volume dynamics of Chhota Shigri Glacier in Himachal Pradesh from 2017 to 2022

ABSTRACT Glaciers are the source of freshwater for many perennial rivers around the world. Out of 215,000 glaciers apart from the polar ice sheets, the Himalayas constitute about 54,000 glaciers and are often referred to as the third pole on the Earth. In recent decades, the Himalayan glaciers have been experiencing increased recession as a consequence of climate change. Subsequently, understanding the dynamics of glacier ice parameters and volume becomes significant. In this study, an ensemble model of laminar-flow-based and basal-shear-stress-based models on the Chhota Shigri Glacier was investigated to understand the dynamics of glacier ice thickness over six years, from 2017 to 2022. The glacier volume was determined from the ensembled ice thickness. Our results indicate that the ensemble model yields the minimum ice thickness measurement of 102 ± 17.38 m and the maximum of 112 ± 19.04 m for the years 2017 and 2019, respectively. The estimated results show a correlation of 81% with a global ice thickness dataset. The ensemble approach provides better estimates for ice thickness accounting for more parameters affecting the glacier dynamics. From 2017 to 2022, the Chhota Shigri Glacier volume has been observed to show a slightly negative trend.

Himalayan glacier thickness mapper (HIGTHIM) tool: An automated approach to map potential glacier lakes and expansion of existing lakes

Climate warming is the driving force behind the mass change of glaciers, resulting in their thinning and retreat. These changes could result in the formation of glacial lakes across the Himalayan landscape, posing a risk of glacial lake outburst flood (GLOF) hazards, causing enormous damage to the natural environment, human property, and lives. The present study demonstrates a semi-automated tool named 'Himalayan Glacier Thickness Mapper' (HIGTHIM), a Python script based on the ArcPy module. The tool provides the glacier's ice thickness, bed topography, location of the potential lake, and lake volume. It utilizes the laminar flow equation to model ice thickness by applying the surface velocity and slope. We used HIGTHIM in the Sutlej and Beas basins for 132 glaciers covering an area of 618 km2 in the Western Himalaya for this investigation. The results indicate 118 potential lake sites covering a total area of 16 km2 and a volume of 269 × 106 m3. The information provided by the HIGTHIM tool will be useful in understanding the formation and progression of future glacial lakes caused by deglaciation. Such data is required for the scientific community to perform dynamic modelling of outburst scenarios, hydrological modelling, and risk mitigation from GLOF.

Ground penetrating radar in temperate ice: englacial water inclusions as limiting factor for data interpretation

Abstract Ground penetrating radar (GPR) has been extensively used in glaciology to infer glacier's ice thickness, liquid water content, water drainage pathways, and other properties. The interpretation of such GPR data is not always straightforward and for temperate glaciers, the signal is often affected by strong scattering and attenuation. It has often been suggested that such effects originate from englacial water inclusions, since water and ice have a large contrast in their di-electric permittivity. To investigate such effects quantitatively, we perform an extensive numerical modeling study of GPR signals. By exploring how different liquid water contents (LWC) and water-inclusions size affect the GPR signal, we show that their effects are much larger than the potential presence of a wet snowpack or a heterogeneous distribution of ice permittivity. In particularly, we show that the presence of such water inclusions is a necessary and sufficient condition for reproducing the typical characteristics of GPR data acquired in the field. Further, we find that for 25 MHz GPR antennas, a bulk LWC $\gtrsim$ 0.2%, associated with decimeters-scale water inclusions already limits bedrock detectability for ice thicknesses $\gtrsim 100$ m. Since these values are typical for Alpine glaciers, they clarify why the quality of GPR data is often poor in such environments.

Duration and ice thickness of a Late Holocene outlet glacier advance near Narsarsuaq, southern Greenland

Abstract. Greenland Ice Sheet (GrIS) outlet glaciers are currently losing mass, leading to sea level rise. Reconstructions of past outlet glacier behavior through the Holocene help us better understand how they respond to climate change. Kiattuut Sermiat, a southern Greenland outlet glacier near Narsarsuaq, is known to have experienced an unusually large Late Holocene advance that culminated at ∼1600 cal yr BP and exceeded the glacier's Little Ice Age extent. We report sedimentary records from two lakes at slightly different elevations in an upland valley adjacent to Kiattuut Sermiat. These reveal when the outlet glacier's surface elevation was higher than during the Little Ice Age and constrain the associated outlet glacier surface elevation. We use bulk sediment geochemistry, magnetic susceptibility, color, texture, and the presence of aquatic plant macrofossils to distinguish between till, glaciolacustrine sediments, and organic lake sediments. Our 14C results above basal till recording regional deglaciation skew slightly old due to a reservoir effect but are generally consistent with regional deglaciation occurring ∼ 11 000 cal yr BP. Neoglacial advance of Kiattuut Sermiat is recorded by deposition of glaciolacustrine sediments in the lower-elevation lake, which we infer was subsumed by an ice-dammed lake that formed along the glacier's margin just after ∼ 3900 cal yr BP. This timing is consistent with several other glacial records in Greenland showing neoglacial cooling driving advance between ∼ 4500–3000 cal yr BP. Given that glaciolacustrine sediments were deposited only in the lower-elevation lake, combined with glacial geomorphological evidence in the valley containing these lakes, we estimate the former ice margin's elevation to have been ∼ 670 m a.s.l., compared with ∼ 420 m a.s.l. today. The ice-dammed lake persisted until the glacier surface fell below this elevation at ∼ 1600 cal yr BP. The retreat timing contrasts with overall evidence for cooling and glacier advance in the region at that time, so we infer that Kiattuut Sermiat's retreat may have resulted from reduced snowfall amounts and/or local glaciological complexity. High sensitivity to precipitation changes could also explain the relatively limited Little Ice Age advance of Kiattuut Sermiat compared with the earlier neoglacial advance.

Dynamic Monitoring of Debris-Covered Glacier Surface Velocity and Ice Thickness of Mt.Tomur, Tian Shan, China

The Mt.Tomur glaciers, in the Tian Shan mountains of Western China, are usually debris-covered, and due to climate change, glacial hazards are becoming more frequent in this region. However, no changes in the long-time series of glacier surface velocities have been observed in this region. Conducting field measurements in high-altitude mountains is relatively difficult, and consequently, the dynamics and driving factors are less studied. Here, image-correlation offset tracking using Landsat images was exploited to estimate the glacier surface velocity of glaciers in the Mt.Tomur region from 2000 to 2020 and to assess glacier ice thickness. The results show that the glacier surface velocity in the Mt.Tomur region showed a significant slowdown during 2000–2020, from 6.71 ± 0.66 m a−1 to 3.95 ± 0.66 m a−1, an overall decrease of 41.13%. The maximum glacier ice thickness in the Mt.Tomur region was estimated based on the ice flow principle being 171.27 ± 17.10 m, and the glacier average thickness is 50.00 ± 5.0 m. Glacier thickness at first increases with increasing altitude, showing more than 100 ± 10 m ice thickness between 3400 m and 4300 m, and then decreases with further increases in altitude. The reliability of the surface velocity and ice thickness obtained from remote sensing was proved using the measured surface velocity and ice thickness of Qingbingtan glacier No. 72 stall (the correlation coefficient R2 > 0.85). The debris cover has an overall mitigating effect on the ablation and movement rate of Qingbingtan Glacier No. 72; however, it has an accelerating effect on the ablation and movement rate of glacier No. 74.

Ice thickness distribution of Himalayan glaciers inferred from DInSAR-based glacier surface velocity.

Retrieval of glacier ice thickness is extremely important for monitoring water resources and predicting glacier dynamics and changes. The inter-annual glacier ice thickness observations (more than 5years) exploit the glacier mass changes. Ice thickness is one of the important parameters to predict the future sea-level rise. Without adequate knowledge and precise information of glacier ice thickness distribution, future sea-level changes cannot be accurately assessed. In this study, we use an existing flow model to estimate the ice thickness of the High Mountain Asia (HMA) glaciers, using remote sensing techniques. The glacier ice velocity is one of the significant parameters in the Laminar flow model to retrieve the ice thickness. The glacier ice velocity is derived by utilizing the Differential SAR Interferometry (DInSAR) technique. The most optimum DInSAR data (ALOS-2/PALSAR-2) is used for estimating the ice velocity of the HMA glaciers. The ice thickness is mainly estimated for five different states in the HMA region, namely Himachal Pradesh, Uttarakhand, Sikkim, Bhutan, and Arunachal Pradesh. Most of the states are observed with a mean ice thickness of 100m. Five benchmark glaciers (Samudra Tapu, Bara Shigri, Chhota Shigri, Sakchum, and Gangotri glaciers) are also selected for validating our results with the existing thickness information. The issues related to velocity-based ice thickness inversion are also emphasized in this study. The high-velocity rate due to the influx of melting water from adjacent glaciers causes an increment in the flow rate. This abnormal velocity derives erroneous ice thickness measurements. This is one of the major problems to be considered in the velocity-based thickness-derived procedures. Finally, the investigation suggests the inclusion of the velocity influencing parameters in the physical-based models for an accurate ice thickness inversion.

Modelled sensitivity of Monte San Lorenzo ice cap, Patagonian Andes, to past and present climate

Sparse measurements of glacier mass balance, velocity and ice thickness in Patagonia challenge our ability to understand glacier sensitivity to climate change and relate past glacier fluctuations to palaeoclimate change. Small ice caps, such as Monte San Lorenzo, have short response times and high climate sensitivity, making well-dated moraines in their glacier foregrounds an important tool for exploring glacier response to rapid changes in palaeoclimate. Here, the Parallel Ice Sheet Model (PISM) is used to model ice flow across a domain centred on the Monte San Lorenzo ice cap. Ice-flow parameters are calibrated to match present-day ice extent, velocity and thickness. Our aim is, firstly, to quantify present-day physical glacier properties, and ice cap dynamics and sensitivities, and secondarily, to evaluate the controls on the deglaciation of the ice cap within the context of the Southern Hemisphere palaeoclimate system during the Last Glacial-Interglacial Transition (LGIT). The simulated present-day ice cap shows high surface mass flux, with ablation at outlet glacier tongues up to 18 m w. e. a−1, accumulation at the highest elevations of up to 5.5 m w. e. a−1 and a simulated Equilibrium Line Altitude (ELA) of 1750–2000 m asl. The ice cap is more sensitive to changes in precipitation relative to changes in temperature. We provide envelopes with likely ranges of palaeotemperature and palaeoprecipitation for glacial advances to moraines formed during the Last Glacial-Interglacial Transition and Holocene. Our numerical model predicts that cooling and an increase in precipitation is required to force glacial advance to mapped moraine limits at 12.1 ka (2°C cooler, 50% more precipitation), 5.6 ka (0°C cooler, 50% more precipitation) and 0.2 ka (1°C cooler, 25% more precipitation). Our modelling results thus provide insights into the present-day mass balance, thermal regime and velocity of the ice cap, explores the sensitivities of this ice cap to various model and climatic parameters, and provide palaeoclimatic envelopes for readvances during the LGIT and Holocene in Patagonia.

Ice thickness and morphological analysis reveal the future glacial lake distribution and formation probability in the Tibetan Plateau and its surroundings

Owing to intense glacial retreat and melting, it is anticipated that numerous glacial lakes will be formed in the next few decades. However, their development and distribution patterns in the Tibetan Plateau and its surroundings still need to be elucidated. In this study, a published glacier ice thickness distribution dataset was employed to fully detect overdeepened glacier beds as potential glacial lakes. We selected and expanded four morphological metrics to determine the formation probability of potential glacial lakes: surface slope, break in slope, lake area, and position on the glacier. The results revealed that 15,826 potential glacial lakes with areas >0.02 km 2 exist in the Tibetan Plateau and its surroundings, covering an area of 2253.95 ± 1291.29 km 2 with a water volume of 60.49 ± 28.94 km 3 that would contribute to an equivalent sea level rise of 0.16 ± 0.08 mm. The experimental comparison and uncertainty assessment for the overdeepening processing showed that the different extraction methods and basic digital elevation models used could lead to non-negligible errors in the results (at least ±30%), which were ignored in previous studies, contributing to major divergences between the several current inventories of potential glacial lakes in the plateau. Notably, approximately 90% of the total area of the potential glacial lakes is concentrated in the lower half of the individual glaciers in the Tibetan Plateau and its surroundings. >70% of the potential glacial lakes and contemporary glacial lakes in this region were found to be concentrated within the 4000–5800 m elevation range. Moreover, the study identified 5361 potential glacial lakes with high or very high exposure probabilities, and their distribution was mostly determined by regional glacier resources. However, the numbers and sizes of some potential glacial lakes that are found in the Karakoram region are considered to be exaggerated because of the presence of numerous surge-type glaciers, which have not been discussed in previous studies. These results can improve our understanding of future glacial lake formation and distribution in the Tibetan Plateau and its surroundings and have implications for further implementation of effective prevention, mitigation, and adaptation measures for glacial lake outburst floods and water security. • 15,826 PGLs with areas >0.02 km 2 exist in the Tibetan Plateau and its surroundings, covering an area of 2253.95 ± 1291.29 km 2 with a water volume of 60.49 ± 28.94 km 3 . • Approximately 90% of the total area of the Potential Glacial Lakes is concentrated in the lower half of the individual glaciers in the Tibetan Plateau and its surroundings. • The number and size of some Potential Glacial Lakes found in the Karakoram region are considered exaggerated because of the presence of numerous surge-type glaciers.

Coincident evolution of glaciers and ice-marginal proglacial lakes across the Southern Alps, New Zealand: Past, present and future

Global glacier mass loss is causing expansion of proglacial landscapes and producing meltwater that can become impounded as lakes within natural topographic depressions or ‘overdeepenings’. It is important to understand the evolution of these proglacial landscapes for water resources, natural hazards and ecosystem services. In this study we (i) overview contemporary loss of glacier ice across the Southern Alps of New Zealand, (ii) analyse ice-marginal lake development since the 1980s, (iii) utilise modelled glacier ice thickness to suggest the position and size of future lakes, and (iv) employ a large-scale glacier evolution model to suggest the timing of future lake formation and future lake expansion rate. In recent decades, hundreds of Southern Alps glaciers have been lost and those remaining have fragmented both by separation of tributaries and by detachment of ablation zones. Glaciers with ice-contact margins in proglacial lakes (n > 0.1 km2 = 20 in 2020) have experienced the greatest terminus retreat and typically twice as negative mass balance compared to similar-sized land-terminating glaciers. Our analysis indicates a positive relationship between mean glacier mass balance and rate of lake growth (R2 = 0.34) and also with length of an ice-contact lake boundary (R2 = 0.44). We project sustained and relatively homogenous glacier volume loss for east-draining basins but in contrast a heterogeneous pattern of volume loss for west-draining basins. Our model results show that ice-marginal lakes will increase in combined size by ~150% towards 2050 and then decrease to 2100 as glaciers disconnect from them. Overall, our findings should inform (i) glacier evolution models into which ice-marginal lake effects need incorporating, (ii) studies of rapid landscape evolution and especially of meltwater and sediment delivery, and (iii) considerations of future meltwater supply and water quality.

Estimation of glacier stored water in the Bhaga basin using laminar flow and volume-area scaling methods

Reliable estimates of glacier stored water are necessary for water resources management of Himalayan rivers. Extreme climate and rugged Himalayan terrain make it challenging to apply field methods. Therefore, the investigation used a technique based on glacier surface velocity, slope, and laminar flow law. We have estimated the stored water of 319 glaciers covering 320 ± 16 km2 area in the Bhaga basin. Glacier surface velocity and thickness of 64 glaciers are estimated using an open-source COSI-Corr and automated Himalayan Glacier Thickness Mapper (HIGTHIM) tool. The average surface velocity is calculated as 8 ± 0.06 myr−1, and the mean glacier ice thickness ranges from 28 ± 3.8 to 82 ± 11.2 m. We developed a new Volume-Area scaling relationship based on the estimates from the HIGTHIM tool in this work. The volume of the remaining 255 glaciers of the basin is estimated using this scaling relation. The total glacier stored water of Bhaga glaciers is estimated as 15 ± 2.8 Gt. The technique provides better estimates of glacier stored water, providing primary input for further hydrological investigations in the Bhaga basin.

Modelling ice thickness and storage volume of svalbard glaciers monitored through Indian Arctic Programme

In this study, glacier ice thickness distribution and storage volume has been modelled for two glaciers viz., Vestre Broggerbreen and Feiringbreen situated across the Kongsfjorden around Ny-Ålesund in Svalbard. These two high Arctic glaciers are being monitored through the ongoing efforts of the Indian Arctic Program. Here, the capability of a glacier specific shape factor parametrization approach was evaluated when paired with a parsimonoious, simple stress-driven, slope-dependent ice thickness estimation model called Glacier bed Topography2_Indian Institute of Technology Bombay version (GlabTop2_IITB). The modelled average thickness of ice for Vestre Broggerbreen and Feiringbreen Glaciers was 59 m and 92 m respectively during the study period. The obtained ice thickness estimates were found to be reliable when compared with the recent field estimates obtained through a Ground Penetrating Radar (GPR) survey. Moreover, the modelled results of both the glaciers were in good agreement with the consensus estimates of ice thickness reported in a recent study. The obtained results suggest that the modelling approach presented here can be an alternative to complex models, which requires lot of other data such as surface mass balance, surface velocity etc. Based on the modelled ice thickness distribution pertained to the year 2015, the total volume of the glacier-stored ice estimated for Vestre Broggerbreen Glacier and Freingbreen Glacier was 0.29 ± 0.04 km3and 0.65 ± 0.09 km3, respectively.

High-resolution monitoring of debris-covered glacier mass budget and flow velocity using repeated UAV photogrammetry in Iran

Iran's glaciers are commonly debris-covered. Due to climate changes, the frequency of glacial hazards such as glacial lake outbursts floods is increasing, and consequently, the mass of Iran's glaciers is decreasing. Fieldwork in high-altitude mountains is difficult, thus, the dynamics of debris–covered glaciers and their associated driving factors are poorly studied. In this study, changes in the elevation and the surface flow speed of the largest and most dynamic debris-covered glacier in Iran (Alamkouh glacier) are evaluated during 2018 to 2020 for the first time. For this purpose, images from a high-resolution unmanned aerial vehicle (UAV) are used. Additionally, the spatial distribution of glacier ice thickness is estimated based on the principles of ice-flow and glacier surface velocity data. The distribution of ice thickness is evaluated with in-situ Ground Penetration Radar (GPR) data. The acquired high-resolution images from UAV are processed into a digital elevation model (with a spatial resolution of about 15 cm) and orthoimages (with a spatial resolution of about 8 cm), and glacier ice thickness change and surface flow velocity are derived. In order to estimate glacier surface velocity, a frequency cross-correlation model was applied using the COSI-Corr module. Our results show that the mean glacier ice thinning during the study period 2018–2020 is about −0.23 ± 0.03 m yr−1 and it reaches about −5 ± 0.65 m yr−1 at the terminus and accumulation areas. The observed variations in ice thinning are best explained by the existence of debris cover (and their corresponding insulating effects), the existence of ice cliffs, and their associated supraglacial lakes. We found that ice cliffs and supraglacial lakes show mass losses that can be an order of magnitude higher than average. Moreover, the mean surface velocity of Alamkouh glacier is about 1.1 ± 0.06 m yr−1 from 2018 to 2020 with considerable spatial variation in surface velocities. The maximum surface velocity (about 4.5 ± 0.27 m yr−1) belongs to its upper regions, and lower and marginal areas are nearly stagnant. The slow movement of the glacier, along with a continuous increase in debris and ice thinning, provides a suitable condition for supraglacial pond development, which decreases glacier mass. Total volume of glacier was estimated to be ~102 × 106 m3 in 2020, corresponding to an average ice thickness of ~31.3 ± 7.5 m. Moreover, the average ice thinning rate is 0.66% yr−1 in 2018 to 2020. According to this reduction rate, it is expected that more than 51.7% of the glacier will be lost by the end of the 21st century.

Decadal terminus position changes and ice thickness measurement of Menthosa Glacier in Lahaul region of North-Western Himalaya

Glacier ice-thickness measurement and distribution is one of the essential variables to assess present status of glacier-water equivalent and its volumetric reserve as well as to model the future glacier dynamics under the climate changing scenario. Yet, substantial gaps in ice thickness information exist for the Himalayan glaciers. The present study provides a long-term assessment (1965–2016) of recessional and area change patterns, as well as the detailed field-based (2016–2017) Ground Penetrating Radar(GPR), derived ice-thickness measurement of the Menthosa Glacier, Lahaul Himalaya. Additionally, the study examines whether the modelled ice thickness from remote sensing data is consistent with the field-based GPR measurement and how can it be improved. The extensive field surveys coupled with the multi-temporal high (Corona KH-4A) to medium resolution (Landsat Enhanced Thematic Mapper+ (ETM+)/Operational Land Imager (OLI), Sentinel 2A-Multispectral Instrument (MSI)) remote sensing data and cross-sectional GPR surveyed profile measurements have been used to examine past half a century (1965–2016) glacier fluctuation and the recent ice-thickness estimations, respectively. The results show that the Menthosa Glacier receded by 301.5 ± 19.2 m during the past half a century (1965–2016) with an average annual retreat of 5.9 ± 0.4 m a−1, whereas glacier lost 0.09 km2 ice in the frontal section. Field measurement over the past one decade (2006–2017) also conforms to a continuous recessional pattern and substantial glacier degeneration particularly the extensive surface lowering and significant appearance of ice-cliffs in the ablation and lateral zones over this period. The GPR measurements (2017) show the minimum glacier ice thickness of 24 meters at 4691 m a.s.l. (in the lower part of ablation area) and maximum glacier ice thickness of 55 meters measured at 4758 m a.s.l. (in the upper left-side tributary part of ablation area). Moreover, the modelled ice thickness derived from remotely sensed data is having Root Mean Square Error (RMSE) between 38 to 72 ± 10 m as compared with GPR measured ice thickness.

Modelling and characterizing glacier-bed overdeepenings as sites for potential future lakes in the deglaciating French Alps

Glacier retreat results in major landscape changes including the formation of new lakes in Glacier-Bed Overdeepenings (GBOs) that can provoke catastrophic Glacial Lake Outburst Flood (GLOF) hazards, but could also provide economic opportunities. This study aims to identify and characterize the location of potential GBOs in the French Alps as possible sites for future lakes. We first ran GlabTop (Glacier-bed Topography) and GlabTop2 models, two GIS schemes calculating glacier ice thickness and mapping potential GBOs. Their level of confidence is estimated using morphological analysis based on slope angle, crevasse fields and lateral narrowing at bedrock thresholds. 139 GBOs (>0.01km²) were predicted among which 59 have medium to very high confidence. 20 lakes are already forming at the snout of retreating glaciers, including four lakes at predicted GBOs <0,01km². The Vanoise massif hosts 43% of the predicted GBOs but the Mont Blanc massif gathers larger, deeper and more voluminous ones. Most of the predicted GBOs are below 3,500m a.s.l. as related to the elevation of the corresponding glaciers. In the Vanoise massif, many predicted GBOs have rather low confidence because of the extent of ice-cap like glaciers for which the shear stress approach used by GlabTop becomes questionable. Furthermore, 58 potential GBOs were detected by visual analysis of glacier morphologies. The study highlights the relevance of combining various methods to determine GBOs and is a first step towards the anticipation of future risks and opportunities related to the formation of new lakes in the French Alps.

Efficiency of artificial neural networks for glacier ice-thickness estimation: a case study in western Himalaya, India

Abstract Knowledge of glacier volume is crucial for ice flow modelling and predicting the impacts of climate change on glaciers. Rugged terrain, harsh weather conditions and logistic costs limit field-based ice thickness observations in the Himalaya. Remote-sensing applications, together with mathematical models, provide alternative techniques for glacier ice thickness and volume estimation. The objective of the present research is to assess the application of artificial neural network (ANN) modelling coupled with remote-sensing techniques to estimate ice thickness on individual glaciers with direct field measurements. We have developed two ANN models and estimated the ice thickness of Chhota Shigri Glacier (western Himalaya) on ten transverse cross sections and two longitudinal sections. The ANN model estimates agree well with ice thickness measurements from a ground-penetrating radar, available for five transverse cross sections on Chhota Shigri Glacier. The overall root mean square errors of the two ANN models are 24 and 13 m and the mean bias errors are ±13 and ±6 m, respectively, which are significantly lower than for other available models. The estimated mean ice thickness and volume for Chhota Shigri Glacier are 109 ± 17 m and 1.69 ± 0.26 km3, respectively.

Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2)

Knowing the ice thickness distribution of a glacier is of fundamental importance for a number of applications, ranging from the planning of glaciological fieldwork to the assessments of future sea-level change. Across spatial scales, however, this knowledge is limited by the paucity and discrete character of available thickness observations. To obtain a spatially coherent distribution of the glacier ice thickness, interpolation or numerical models have to be used. Whilst the first phase of the Ice Thickness Models Intercomparison eXperiment (ITMIX) focused on approaches that estimate such spatial information from characteristics of the glacier surface alone, ITMIX2 sought insights for the capability of the models to extract information from a limited number of thickness observations. The analyses were designed around 23 test cases comprising both real-world and synthetic glaciers, with each test case comprising a set of 16 different experiments mimicking possible scenarios of data availability. A total of 13 models participated in the experiments. The results show that the inter-model variability in the calculated local thickness is high, and that for unmeasured locations, deviations of 16% of the mean glacier thickness are typical (median estimate, three-quarters of the deviations within 37% of the mean glacier thickness). This notwithstanding, limited sets of ice thickness observations are shown to be effective in constraining the mean glacier thickness, demonstrating the value of even partial surveys. Whilst the results are only weakly affected by the spatial distribution of the observations, surveys that preferentially sample the lowest glacier elevations are found to cause a systematic underestimation of the thickness in several models. Conversely, a preferential sampling of the thickest glacier parts proves effective in reducing the deviations. The response to the availability of ice thickness observations is characteristic to each approach and varies across models. On average across models, the deviation between modeled and observed thickness increase by 8.5% of the mean ice thickness every time the distance to the closest observation increases by a factor of 10. No single best model emerges from the analyses, confirming the added value of using model ensembles.

Recession of Gya Glacier and the 2014 glacial lake outburst flood in the Trans-Himalayan region of Ladakh, India

This study assessed spatiotemporal changes at Gya Glacier, the associated development of a proglacial lake, and reconstructed the 2014 outburst flood that struck Gya Village in the Trans-Himalayan region of Ladakh, India. This study analyzed and for the first time modeled a Glacial Lake Outburst Flood (GLOF) event in the Trans-Himalayan region of Ladakh. Glacier and glacial lakes changes were quantified using remote sensing data supplemented with field observations. Glacier ice-thickness and glacier-bed overdeepenings were modeled using a shear-stress based model, GlabTop (Glacier-bed Topography). The reconstruction of the 2014 GLOF and the potential hazard assessment of Gya Lake were carried out using the hydrodynamic model HEC-RAS; results were validated against ground-collected data. Temporal evaluation of satellite data revealed a 45.6% loss in the total glacier area between 1969 and 2019. The earliest snow-free image available for the region shows that a proglacial lake existed as early as 1969 with an area of 3.06 ha. The lake has expanded to ~11 ha in 2019. Results from the GlabTop model suggest that the lake could grow further up to 12 ha in the future. Field-based geomorphic indicators suggest that the 2014 GLOF event resulted from a piping failure of the frontal moraine destroying numerous agricultural fields, some buildings, downstream infrastructure, and eroded natural channel embankments. The reconstruction of the event revealed that 25% of the lake waters drained out with a peak discharge of 470 m3s−1, inundating an area of ~4 km2 around Gya Village. However, a complete breaching of the terminal moraine could result in an event that would be 5.5 times larger than the 2014 GLOF. Therefore, this study could be useful not only in planning disaster-resilient infrastructure around proglacial lake environments in the cold-arid Ladakh but also in framing mitigation plans to reduce risk for vulnerable downstream communities.

Ice thickness distribution and volume estimation of Burqin Glacier No. 18 in the Chinese Altay Mountains

Information on the thickness distribution and volume of glacier ice is highly important for glaciological applications; however, detailed measurements of the ice thickness of many glaciers in the Chinese Altay Mountains remain lacking. Burqin Glacier No. 18 is a northeast-orientated cirque glacier located on the southern side of the Altay Mountains. This study used PulseEKKO® PRO 100A enhancement ground-penetrating radar (GPR) to survey the ice thickness and volume of Burqin Glacier No. 18 in summer 2018. Together with GPR surveying, spatial distributed profiles of the GPR measurements were concurrently surveyed using the real-time kinematic (RTK) global navigation satellite system (GNSS, Unistrong E650). Besides, we used QuickBird, WorldView-2, and Landsat TM to delineate accurate boundary of the glacier for undertaking estimation of glacier ice volume. GPR measurements revealed that the basal topography of profile B1–B2 was flat, the basal topography of profile C1–C2 presented a V-type form, and the basal topography of profile D1–D2 had a typical U-type topographic feature because the bedrock near the central elevation of the glacier was relatively flat. The longitudinal profile A1–A2 showed a ladder-like distribution. Glacier ice was thin at the terminus and its thickness increased gradually from the elevation of approximately 2620 m a.s.l. along the main axis of the glacier tongue with an average value of 80 (±1) m. The average ice thickness of the glacier was determined as 27 (±2) m and its total ice volume was estimated at 0.031 (±0.002) km3. Interpretation of remote sensing images indicated that during 1989–2016, the glacier area reduced from 1.30 to 1.17 km2 (reduction of 0.37%/a) and the glacier terminus retreated at the rate of 8.48 m/a. The mean ice thickness of Burqin Glacier No. 18 was less than that of the majority of other observed glaciers in China, especially those in the Qilian Mountains and Central Chinese Tianshan Mountains; this is probably attributable to differences in glacier type and climatic setting.

Glacier Ice Thickness Estimation and Future Lake Formation in Swiss Southwestern Alps—The Upper Rhône Catchment: A VOLTA Application

Glacial lake formations are currently being observed in the majority of glacierized mountains in the world. Given the ongoing climate change and population increase, studying glacier ice thickness and bed topography is a necessity for understanding the erosive power of glacier activity in the past and lake formation in the future. This study uses the available information to predict potential sites for future lake formation in the Upper Rhône catchment located in the Southwestern Swiss Alps. The study integrates the latest available glacier outlines and high-quality digital elevation models (DEMs) into the Volume and Topography Automation (VOLTA) model to estimate ice thickness within the extent of the glaciers. Unlike the previous ice thickness models, VOLTA calculates ice thickness distribution based on automatically-derived centerlines, while optimizing the model by including the valley side drag parameter in the force equation. In this study, a total ice volume of 37.17 ± 12.26 km3 (1σ) was estimated for the Upper Rhône catchment. The comparison of VOLTA performance indicates a stronger relationship between measured and predicted bedrock, confirming the less variability in VOLTA’s results (r2 ≈ 0.92) than Glacier Bed Topography (GlabTop) (r2 ≈ 0.82). Overall, the mean percentage of ice thickness error for all measured profiles in the Upper Rhône catchment is around ±22%, of which 28 out of 42 glaciers are underestimated. By incorporating the vertical accuracy of free-ice DEM, we could identify 171 overdeepenings. Among them, 100 sites have a high potential for future lake formation based on four morphological criteria. The visual evaluation of deglaciated areas also supports the robustness of the presented methodology, as 11 water bodies were already formed within the predicted overdeepenings. In the wake of changing global climate, such results highlight the importance of combined datasets and parameters for projecting the future glacial landscapes. The timely information on future glacial lake formation can equip planners with essential knowledge, not only for managing water resources and hazards, but also for understanding glacier dynamics, catchment ecology, and landscape evolution of high-mountain regions.