Spatial Variability in Patterns of Glacier Change across the Manaslu Range, Central Himalaya

Robson, Benjamin Aubrey; Nuth, Christopher; Nielsen, Pål Ringkjøb; Girod, Luc; Hendrickx, Marijn; Dahl, Svein Olaf

doi:10.3389/feart.2018.00012

Cited by 36 publications

(60 citation statements)

References 78 publications

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“…Glacial lakes that are rapidly deepening and expanding, such as Lower Barun and Imja lakes in the Everest region of Nepal, could be expected to produce larger icebergs due to greater calving activity. By contrast, our observations at Thulagi Lake likely capture smaller icebergs associated with slower rates of lake expansion (ICIMOD, 2011;Rounce et al, 2016;Haritashya et al, 2018;Robson et al, 2018).…”

Section: Glacier Calving and Iceberg Productionmentioning

confidence: 64%

“…The glacier is grounded in water < 60 m deep and future lake expansion was expected to be limited (e.g. Robson et al, 2018). However, Thulagi Glacier retreated 200 m (2008-2018) ( Table 1) and modelled ice thickness suggests that subsequent glacier retreat would continue to allow lake expansion for another ∼1 km up-valley ( Figures 6A, 9).…”

Section: Lake Thermal Regime and Glacier Dynamicsmentioning

confidence: 99%

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Mass Loss From Calving in Himalayan Proglacial Lakes

et al. 2020

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The formation and expansion of Himalayan glacial lakes has implications for glacier dynamics, mass balance and glacial lake outburst floods (GLOFs). Subaerial and subaqueous calving is an important component of glacier mass loss but they have been difficult to track due to spatiotemporal resolution limitations in remote sensing data and few field observations. In this study, we used near-daily 3 m resolution PlanetScope imagery in conjunction with an uncrewed aerial vehicle (UAV) survey to quantify calving events and derive an empirical area-volume relationship to estimate calved glacier volume from planimetric iceberg areas. A calving event at Thulagi Glacier in 2017 was observed by satellite from before and during the event to nearly complete melting of the icebergs, and was observed in situ midway through the melting period, thus giving insights into the melting processes. In situ measurements of Thulagi Lake's surface and water column indicate that daytime sunlight absorption heats mainly just the top metre of water, but this heat is efficiently mixed downwards through the top tens of metres due to forced convection by wind-blown icebergs; this heat then is retained by the lake and is available to melt the icebergs. Using satellite data, we assess seasonal glacier velocities, lake thermal regime and glacier surface elevation change for Thulagi, Lower Barun and Lhotse Shar glaciers and their associated lakes. The data reveal widely varying trends, likely signifying divergent future evolution. Glacier velocities derived from 1960/70s declassified Corona satellite imagery revealed evidence of glacier deceleration for Thulagi and Lhotse Shar glaciers, but acceleration at Lower Barun Glacier following lake development. We used published modelled ice thickness data to show that upon reaching their maximum extents, Imja, Lower Barun and Thulagi lakes will contain, respectively, about 90 × 10 6 , 62 × 10 6 and 5 × 10 6 m 3 of additional water compared to their 2018 volumes. Understanding lake-glacier interactions is essential to predict future glacier mass loss, lake formation and associated hazards.

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Section: Glacier Calving and Iceberg Productionmentioning

confidence: 64%

Section: Lake Thermal Regime and Glacier Dynamicsmentioning

confidence: 99%

Mass Loss From Calving in Himalayan Proglacial Lakes

et al. 2020

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“…Glacier mass change estimates are usually based on time series of glaciological measurements, digital elevation models (DEMs) differencing, and numerical mass balance estimations (e.g., Paul et al, 2009). In recent years, the geodetic method for estimating changes in the surface elevation and volume of glaciers has been widely used Brun et al, 2017;Azam et al, 2018;Robson et al, 2018). The data were used not only to estimate decadal mass changes but also to correct and reanalyse long-term glaciological mass balance measurements (Zemp et al, 2013;Sold et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Volume Changes of Elbrus Glaciers From 1997 to 2017

et al. 2019

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This study describes the analysis of changes in area and volume of the Mt.Elbrus glacier system, Central Caucasus from 1997 to 2017. It is based on helicopter-borne ice thickness measurements, comparison of high-resolution imagery and two digital elevation models (DEMs) with 10 m resolution. More than 250 km of ground-penetrating radar (GPR) profiles of ice thickness with reliable reflections were obtained. The total volume of Mt. Elbrus glaciers was 5.03 ± 0.85 km 3 of ice in 2017. Our results show that 68% of the total ice volume is concentrated below 4,000 m a.s.l. where the average ice thickness was 44.6 ± 7.3 m, 18% of the volume lies within 4,000-4,500 m a.s.l. (thickness of 41.2 ± 7.3 m), and just 14% lies above 4,500 m a.s.l. (thickness of 29.7 ± 6.7 m). The glacier-covered area of Mt. Elbrus decreased from 125.76 ± 0.65 km 2 in 1997 to 112.20 ± 0.58 km 2 in 2017, a reduction of 10.8%. Over the same period the volume decreased by 22.8%. The mass balance of the Elbrus glaciers decreased by −0.55 ± 0.04 m w.e. a −1 from 1997 to 2017. Mass balance on west-oriented glaciers is less negative than on east-and south-oriented glaciers where mass balance is most negative. The mass balance of the east-oriented Djikiugankez glacier decreased at the fastest average rate (−0.97 ± 0.07 m w.e. a −1 ). This glacier contains 28% of the total Elbrus glacier system ice volume, most of which is concentrated below 4,000 m a.s.l. Only one small glacier on the western slope demonstrated mass gain. Our results match well with the long term direct mass balance measurements on the Garabashi glacier on Elbrus which lost 12.58 m w.e. and 12.92 ± 0.95 m w.e. between 1997 and 2017 estimated by glaciological and geodetic method, respectively. The rate of Elbrus glacier mass loss tripled in 1997-2017 compared with the 1957-1997 period.

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“…Hence, the assessment of glacier-climate interaction requires repeated creation of the higher resolution glacier inventories and observation of glacier parameters over the temporal and spatial scale. Corona and Declassified Hexagon aerial photograph series have proved to be a robust dataset for glaciological studies [12,13]. There are no published studies on the Changme Khangpu basin (CKB) monitoring of glaciers.…”

Section: Introductionmentioning

confidence: 99%

Glacier Dynamics in Changme Khangpu Basin, Sikkim Himalaya, India, between 1975 and 2016

2019

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This study provides a high resolution glacier database in the Changme Khangpu Basin (CKB) using LANDSAT 8 (2014) and Sentinel-2A image (2016), mapping of 81 glaciers that cover a 75.78 ± 1.54 km2 area. Composite maps of land surface temperature, slope and Normalized differential Snow Index have been successfully utilized in delineating near accurate debris cover boundary of glaciers. The cumulative controlling parameters of aspect, elevation, slope, and debris cover have been assessed to evaluate the nature of glacier distribution and dynamics. The local topographic settings seem to have significantly determined the glacier distribution in the CKB. Almost 20% area erstwhile under glacier cover has been lost since 1975 at an average rate of −0.453 ± 0.001 km2a−1. The recent decade (2001–2016) has witnessed a higher rate of area shrinkage (−0.665 ± 0.243 km2a−1), compared to a relatively lower rate of recession (−0.170 ± 0.536 km2a−1) between 1988 and 2001. The lower rates of glacial recession can most likely be induced regionally due to relatively cooler decadal late summer temperatures and peak in the monsoon spell. Glaciers with western and north-western aspects showed more vulnerability to area loss than the rest of the aspects. Lower altitude glaciers have receded faster than ones perched up on higher elevations. The rate of glacier area recession has been nearly twice that on clean glaciers as compared to debris-covered glaciers in the CKB.

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Spatial Variability in Patterns of Glacier Change across the Manaslu Range, Central Himalaya

Cited by 36 publications

References 78 publications

Mass Loss From Calving in Himalayan Proglacial Lakes

Mass Loss From Calving in Himalayan Proglacial Lakes

Volume Changes of Elbrus Glaciers From 1997 to 2017

Glacier Dynamics in Changme Khangpu Basin, Sikkim Himalaya, India, between 1975 and 2016

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