Spatio-temporal trends in the surface ice velocities of the central Himalayan glaciers, India

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Highlights

  • Velocities for 18 central Himalayan glaciers have been estimated between 1990 and 2015.

  • All the studied glaciers have significantly slowed-down during ~1990–2015.

  • Central Himalayan glaciers moved slowly than western and central Himalaya.

  • Entirely active glaciers have progressively been converted into entirely stagnant glaciers.

  • Glacier’ size, orientation, altitude and debris cover determine movement heterogeneity.

Abstract

The glacier surface ice velocity (SIV) is important in understanding the glacier state. This study presents results on the SIV of the 18 glaciers spread over the Indian central Himalaya (ICH). The SIV was computed by applying Co-registration of Optically Sensed Images and Correlation (COSI-Corr) technique on the Landsat time series data (1993–2017). Results show that the average SIV of all glaciers was 22.63 ± 5.8 m a−1 in 1993/94, which decreased (by ~23%) to 17.32 ± 3.1 m a−1 in 2000/01 and further declined (by ~33%) to 11.50 ± 1.7 m a−1 in 2015/16. Though a secular decline in average SIV is observed, rates of slowdown are considerably heterogeneous for the studied glaciers being largely determined by glaciers size, orientation, altitude and debris cover. Slope was found to have comparatively low influence on the glacier movement. Inter-regional comparison reveals that average SIVs of the ICH glaciers were slightly but consistently lower than that of the western and eastern Himalayan glaciers. Nonetheless, though moving slowly, ICH glaciers are more active than nearby Everest region glaciers with sufficient proportion of active glaciers (referred as Type-I; 39%). However, the point of concern is that owing to declining health, ICH-glaciers are progressively converting from Type-I to partially active (referred as Type-II), and Type-II to entirely stagnant (referred as Type-III). This observed slowdown coupled with negative mass balance and continuous debris growth (as reported in previous studies) may form favorable conditions for supraglacial lake development. We thereby recommend regular monitoring of glacier dynamics in this region for tenable assessment of climatic change impacts.

Section snippets

Introduction and background

Glaciers move downslope under the influence of gravity with varying rates depending upon various factors such as topography and climate (Benn and Evans, 2010; Zhang et al., 2010). Movement under their own weight generates stress which strains the glacial ice to deform and creep (Benn and Evans, 2010; Rivera et al., 2011). Glacier ice also melts under pressure, and meltwater at the ice-bedrock interface augments glacier sliding (Blake et al., 1994; Scherler et al., 2011). Thus, the total surface

Study area and dataset

The study area belong to the Indian part of the central Himalaya (i.e. ICH) constrained to the state boundary of Uttarakhand, India. Spatially, it extends from latitude 28.43° to 31.27° N and longitude 77.34° to 81.02° E and it is bordered by Tibet/China in the north, Himachal Pradesh in the west and Nepal in the East (Fig. 1). The relief in the study region varied from ~530 m above sea level (asl) to 7816 m asl (Nanda Devi Peak; Second highest in India after the Kangchenjunga). There are 1573

Surface ice velocity (SIV) estimation

The SIVs have been calculated using optical image correlation techniques from repeat Landsat images for three Epochs i.e. 1993/94, 2000/01 and 2015/16. These three time periods are used to label the tables and figures, however, the actual dates of SIV-pairs may vary for different glaciers (Table 3). The ‘Co-registration of Optically Sensed Images and Correlation’ (COSI-Corr), a plug-in module to ENVI software, developed by Leprince et al. (2007) and described in details by Scherler et al. (2008)

Results

Fig. 6 shows the SIVs of the selected glaciers for 1993/94, 2000/01 and 2015/16 periods. Also, the average and maximum SIV for individual glacier are summarized in Table 4. Owing to bad correlations resulted from shadow and cloud cover, out of 18 selected glaciers, the SIVs could only be computed for 16 glaciers in 1993/94 (except CG3 and CG18), and 2000/01 (except CG10 and CG18), and 17 glaciers in 2015/16 (except CG10). Results show an average SIV of 22.99 ± 5.8, 18.59 ± 3.1 and 13.08 ± 1.7 m

Understanding the glacier dynamics

This study evaluates glacier velocity variations in the ICH for 1993/94–2015/16 period. The SIV measurements are mainly restricted to the lower part of the glaciers where the visual contrast favors image matching (Fig. 6). In case of negative mass balance regimes, the ice flux is reduced over time owing to less mass to transport. Heid and Kääb (2012) highlighted that this effect eventually accumulates down the glacier so that the change in ice flux is expected to be small in upper reaches of

Concluding remarks

This study investigates the glacier velocities of the 18 selected ICH glaciers for 1993/94, 2000/01 and 2015/16. The presented analysis may provide important input for other glaciological and hydrological studies (e.g. modelling), and considering the data paucity, may form the baseline data in the region pertaining to glacier dynamics. Results reveal that as compared to the Everest region, further east to our study area, the ICH glaciers are more active with sufficient proportion of Type-I

Acknowledgements

Authors are grateful to the Director, Wadia Institute of Himalayan Geology, Dehradun, India, for providing requisite facilities to carry out this work. We thank U.S. Geological Survey for providing Landsat data free of charge for this work. P.K. Garg wishes to express his gratitude to Dr. D.P. Dobhal for his guidance throughout the study. A. Shukla thanks the Ministry of Earth Sciences, Government of India for facilitating the study.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References (49)

  • M.F. Azam et al.

    From balance to imbalance: a shift in the dynamic behaviour of Chhota Shigri glacier, western Himalaya, India

    J. Glaciol.

    (2012)
  • D. Bandyopadhyay et al.

    Spatial distribution of decadal ice-thickness change and glacier stored water loss in the Upper Ganga basin, India during 2000–2014

    Sci. Rep.

    (2019)
  • S. Basnett et al.

    The influence of debris cover and glacial lakes on the recession of glaciers in Sikkim Himalaya, India

    J. Glaciol.

    (2013)
  • D.I. Benn et al.

    Glaciers and Glaciation

    (2010)
  • R. Bhambri et al.

    Glacier changes in the Garhwal Himalaya, India, from 1968 to 2006 based on remote sensing

    J. Glaciol.

    (2011)
  • A. Bhattacharya et al.

    Overall recession and mass budget of Gangotri Glacier, Garhwal Himalayas, from 1965 to 2015 using remote sensing data

    J. Glaciol.

    (2016)
  • S. Bhushan et al.

    Quantifying changes in the Gangotri Glacier of Central Himalaya: evidence for increasing mass loss and decreasing velocity

    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

    (2017)
  • W. Blake et al.

    Instruments and methods: direct measurement of sliding at the glacier bed

    J. Glaciol.

    (1994)
  • B. Bookhagen et al.

    Toward a complete Himalayan hydrological budget: Spatiotemporal distribution of snowmelt and rainfall and their impact on river discharge

    Journal of Geophysical Research: Earth Surface

    (2010)
  • F. Brun et al.

    A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016

    Nat. Geosci.

    (2017)
  • J.G. Cogley et al.

    Tracking the source of glacier misinformation

    Science

    (2010)
  • K.M. Cuffey et al.

    The physics of glaciers

    (2010)
  • C.M. DeBEER et al.

    Topographic influences on recent changes of very small glaciers in the Monashee Mountains, British Columbia, Canada

    J. Glaciol.

    (2009)
  • A. Dehecq et al.

    Twenty-first century glacier slowdown driven by mass loss in High Mountain Asia

    Nat. Geosci.

    (2019)
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