Evolution of a debris-covered glacier in the western Himalaya during the last four decades (1971–2016): A multiparametric assessment using remote sensing and field observations

Shukla, Aparna; Garg, Purushottam Kumar

doi:10.1016/j.geomorph.2019.05.009

Cited by 42 publications

(22 citation statements)

References 49 publications

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“…3 in Quincey and other (2009) depicts). Shukla and Garg (2019) defined SIV <10 m a −1 as a ‘very slow movement’. In the present study, we term a glacier part as stagnation if the SIV is <5 m a −1 .…”

Section: Introductionmentioning

confidence: 99%

Stagnation of the Pensilungpa glacier, western Himalaya, India: causes and implications

Garg

Yousuf

et al. 2021

J. Glaciol.

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This study investigates stagnation conditions of the Pensilungpa glacier, western Himalaya. Multiple glacier parameters (length, area, debris extent and thickness, snowline altitude (SLA), velocity, downwasting and ice cliffs) were studied using field measurements (2016–18), high-resolution imagery from GoogleEarth (2013–17) and spaceborne Landsat, ASTER and SRTM data (1993–2017) to comprehend the glacier's current state. Results show a moderate decrease in length (6.62 ± 2.11 m a−1) and area (0.11 ± 0.03% a−1), a marked increase in SLA (~6 m a−1) and debris cover (2.86 ± 0.29% a−1) and a slowdown of ~50% during 1993–2016. Notable thinning of −0.88 ± 0.04 m a−1 was observed between 2000 and 2017 showing a similar trend as field measurements during 2016–17 (−0.88 m) and 2017–18 (−1.54 m). Further, results reveal a stagnation of the lower ablation zone (LAZ). Less mass supply and heterogeneous debris growth (6.67 ± 0.41% a−1) over the previous decade resulted in slowdown, margin insulation and slope-inversion, leading to stagnation. Stagnation of LAZ caused bulging in the dynamic upper ablation zone and favored the development of supraglacial ponds and ice cliffs. Ice cliffs have grown significantly (48% in number; 41% in area during 2013–17) and their back-wasting now dominates the ablation process.

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Section: Introductionmentioning

confidence: 99%

Stagnation of the Pensilungpa glacier, western Himalaya, India: causes and implications

Garg

Yousuf

et al. 2021

J. Glaciol.

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“…Climate change may force geomorphological processes on high mountain slopes (Tipper et al, 2012;Cook et al, 2020) by accelerating the disintegration of rocks and increasing the accumulation of debris on glaciers and mountain slopes. As a result, the alpine glaciers widely distributed in the Pamir, Karakorum, Kunlun, Nyainqentangula, and Himalaya Mountains (Scherler et al, 2011;Khan et al, 2015;Zhang et al, 2016;Shukla and Garg, 2019) have widespread supra-glacial debris cover. Some studies have referred to glacier areas with sporadic debris cover as "dirty ice" (Robson et al, 2015;Fyffe et al, 2019a,b).…”

Section: Introductionmentioning

confidence: 99%

Upward Expansion of Supra-Glacial Debris Cover in the Hunza Valley, Karakoram, During 1990 ∼ 2019

Xie

Liu

et al. 2020

Front. Earth Sci.

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Supra-glacial debris cover is key to glacier ablation through increasing (thin debris layer) or decreasing (thick debris layer) melt rates, thereby regulating the mass balance of a glacier and its meltwater runoff. The thickening or lateral expansion of supra-glacial debris cover correlates with a reduction of glacier ablation and, consequently, runoff generation, which is also considered to be an influential factor on the rheology and dynamics of a glacierized system. Studies on supra-glacial debris cover have recently attracted wide attention especially for glaciers in the Himalayas and Karakoram, where the glaciers have heterogeneously responded to climate change. In this study, we used 32 images from the Landsat Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager archive, going back to 1990, which are available on the Google Earth Engine cloud-computing platform, to map the supra-glacial debris cover in the Hunza Valley, Karakoram, Pakistan, based on a band ratio segmentation method (normalized difference snow index [NDSI] < 0.4), Otsu thresholding, and machine learning algorithms. Compared with manual digitization, the random forest (RF) model was found to have the greatest accuracy in identifying supra-glacial debris, with a Kappa coefficient of 0.94 ± 0.01 and an overall accuracy of 95.5 ± 0.9%. Overall, the supraglacial debris cover in the study area showed an increasing trend, and the total area expanded by 8.1-21.3% for various glaciers from 1990 to 2019. The other two methods (Otsu thresholding and NDSI < 0.4) generally overestimated the supra-glacial debris covered area, by 36.3 and 18.8%, respectively, compared to that of the RF model. The supra-glacial debris cover has migrated upward on the glaciers, with intensive variation near the equilibrium-line altitude zone (4,500-5,500 m a.s.l.). The increase in ice or snow avalanche activity at high altitudes may be responsible for this upward expansion of supra-glacial debris cover in the Hunza Valley, which is attributed to the combined effect of temperature decrease and precipitation increase in the study area.

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“…The ASTER DEM products (AST14DMO) are created using only orbital ancillary data and without GCPs, therefore small outliers (peaks and sinks) are likely to be present in DEMs. These outliers were removed using the method followed by Shukla and Garg, 2019. Relative horizontal and vertical biases are often present in DEMs derived from different sensors (Nuth and Kaab, 2011). In the present study, we observed a slight shift in the DEMs from the same sensor for the two periods (2004 and 2020).…”

Section: 2glacier Thickness and Volume Estimationmentioning

confidence: 99%

Spatiotemporal quantification of key environmental changes in Stok and Kang Yatze regions of Ladakh Himalaya, India

Soheb

Ramanathan

Bhardwaj

et al. 2022

Geocarto International

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Tourism fuelled economic transformation of Ladakh region is bringing a change in demography and livelihood preferences leading to increased exploitation of scarce natural resources. In addition to the nerve centre of tourism-related activities (Leh city), rural hinterlands of Ladakh are also witnessing a stark transformation in land and resource use patterns. In this study we quantified and assessed the changes in key environmental parameters of rural Ladakh between 1969 and 2020. We observed a decrease in glacier area, glacier volume and vegetation cover by ~19%, 13% and 14%, whereas built-up and lake area increased by ~238% and 122%, respectively. Simultaneously, local population of the region doubled while tourism footprint increased by ~620 folds. The study highlights the environmental changes happening at a higher rate in rural regions around Leh city. Therefore, need of the hour is to recognise the disruptive changes being brought in the traditional way of life and to devise strategies to reorient the development paradigm towards sustainable resource use and management.

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Evolution of a debris-covered glacier in the western Himalaya during the last four decades (1971–2016): A multiparametric assessment using remote sensing and field observations

Cited by 42 publications

References 49 publications

Stagnation of the Pensilungpa glacier, western Himalaya, India: causes and implications

Stagnation of the Pensilungpa glacier, western Himalaya, India: causes and implications

Upward Expansion of Supra-Glacial Debris Cover in the Hunza Valley, Karakoram, During 1990 ∼ 2019

Spatiotemporal quantification of key environmental changes in Stok and Kang Yatze regions of Ladakh Himalaya, India

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