27 Sep 2022
27 Sep 2022
Status: this preprint is currently under review for the journal ESSD.

A comprehensive multidecadal glacier inventory dataset for the Chandra-Bhaga Basin, Western Himalaya, India

Sarvagya Vatsal1, Anshuman Bhardwaj2, Mohd Farooq Azam3, Arindan Mandal4, Alagappan Ramanathan1, Ishmohan Bahuguna5, N. Janardhana Raju1, and Sangita Singh Tomar6 Sarvagya Vatsal et al.
  • 1School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, 110067, India
  • 2School of Geosciences, University of Aberdeen, King’s College, Aberdeen, AB24 3FX, United Kingdom
  • 3Department of Civil Engineering, Indian Institute of Technology Indore, Simrol, 453552, India
  • 4Interdisciplinary Centre for Water Research, Indian Institute of Science, Bengaluru, 560012, India
  • 5Space Application Centre, Ahmedabad, 380015, India
  • 6Department of Geography, Norwegian University of Science and Technology, Trondheim, No-7491, Norway

Abstract. Delineation of Glaciers is a challenging task in the Himalaya due to its complex topography, cloud cover, seasonal snow cover, hillshade, debris cover. Glacio-hydrological studies including mass balance, run-off, and dynamic modelling rely on the availability of consistent and reliable glacier inventory datasets. This article on data set presents a homogenous, multidecadal inventory of glaciers in the Chandra-Bhaga Basin (CB Basin), western Himalaya, for 1993, 2000, 2010, and 2019. Landsat Thematic Mapper (TM), Enhanced Thematic mapper (ETM+), and Operational Land Imager (OLI) imageries, with minimum snow and cloud cover have been used for enhanced accuracy and consistency. Uncertainty assessment for the generated glacier inventory was performed, following various approaches such as buffer method, standard error estimation, and manual digitisation error and the maximum uncertainty has been quantified. We have identified and manually mapped a total of 251 glaciers with an area > 0.5 km2, and in order to minimise the uncertainty, field surveys were carried out on 6 glaciers in the basin. Out of these 251 glaciers, 217 are clean ice and 35 were debris-covered glaciers. The estimated total glacier area was 996 ± 62 km2 in 1993 that decreased to 973 ± 70 km2 in 2019. Apart from quantifying temporal changes in glacier area, this inventory further allows the estimation of supraglacial debris cover and glacier volume. The supraglacial debris cover area has increased by 14.1 ± 2.54 km2 (15.2 %) during 1993–2019. Accuracy of the debris cover dataset estimated using ground surveys is 82 % with a kappa coefficient of 0.87. Moreover, a glacier ice volume dataset was also generated by incorporating the inventory into Glacier Bed Topography Version 2 (GlabTop2) model and shows a total of 112.5 ± 41 km3 of ice volume stored in the CB Basin glaciers. For accuracy assessment of the DEMs generated using ASTER Stereopairs images, DGPS surveys were carried out on (28 GCPs) and off (6 GCPs) the glaciers. Glacier volume uncertainty with respect to the generated DEMs and model bias is 5.3 km3 and 35.5 km3 respectively. Overestimation of glacier volume due to over deepening is estimated to be 1.2 km3. The impact of climate change on the Himalayan glaciers is a matter of serious concern and such holistic multitemporal inventory datasets can help quantify that impact with improved certainty.

Sarvagya Vatsal et al.

Status: open (until 30 Dec 2022)

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Sarvagya Vatsal et al.

Data sets

Glacier_inventory_debris_cover_ice_thickness_dataset_Chandra_Bhaga_basin_Himalaya Sarvagya Vatsal; Anshuman Bhardwaj; Mohd Farooq Azam; Arindan Mandal; Alagappan Ramanathan; I. M. Bahuguna; N. Janardhana Raju; Sangita Singh Tomar

Sarvagya Vatsal et al.


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Short summary
Glaciers in Chandra-Bhaga Basin, western Himalaya, India have huge socio-economic importance as a large population is dependent on these glaciers for drinking and irrigation water purposes. To quantify Spatio-temporal changes in the glaciers of this basin, our study provides three major datasets. These include multidecadal glacier inventory, debris cover, and ice thickness estimates. These datasets will benefit future glacier as well as policy based studies at both local and regional scales.