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Articles

Spatially distributed ice-thickness modelling for Chhota Shigri Glacier in western Himalayas, India

ORCID Icon, ORCID Icon &
Pages 3320-3343 | Received 18 May 2017, Accepted 06 Feb 2018, Published online: 20 Feb 2018
 

ABSTRACT

Estimation of glacier ice-thickness distribution is important for many glacio-hydrological applications such as runoff projections, glacial lake outburst flood (GLOF) predictions, future evolution of glaciers. Varieties of modelling approaches are available for estimating ice-thickness distribution depending upon the data availability. In the present study, we estimated the ice-thickness distribution and total ice volume of Chhota Shigri Glacier using an optimally parameterized Glacier Bed Topography version 2 (GlabTop2) model, a shallow ice approximation (SIA)-based spatially distributed approach. Among the model input parameters, the shape factor (f), a non-measurable factor compensating for unaccounted effects such as valley shape needs to be calibrated using field measurements of ice-thickness. However, the lack of direct measurements of ice-thickness over many glaciers worldwide restricts model calibration and effective implementation. Therefore, to overcome this limitation, in this study, a novel approach using a relationship between shape factor, glacier cross-sectional width, and ice-thickness at the centre of a cross-section has been proposed and also tested to estimate optimal shape factor of the study glacier. Additionally, a detailed analysis of the effect of Digital Elevation Model (DEM) resolution and shape factor parameterization on the modelled ice-thickness estimates indicate that improving either the DEM resolution or calibrating the shape factor individually will not lead to improved ice-thickness estimates. In fact, both are necessary for better estimation of ice-thickness distribution. The high resolution DEM used in this study is TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) DEM of 10 × 10 m grid size. Finally, a comparison of the results from a previous study where they used Shuttle Radar Topography Mission (SRTM) 90 m DEM indicates that the improved parameterisation of GlabTop2 model has led to a reduction in the error bounds of the estimated ice-thickness including the total glacier stored ice volume for the year 2013, which is estimated to be 1.74 ± 0.25 km3. Furthermore, based on the obtained results, it can be said that the GlabTop2 model combined with the proposed parameterization approach is having enormous potential to be applied over the wide range of data scarce Himalayan glaciers to quantify reliable ice-thickness estimates.

Acknowledgments

RR and AP acknowledge the support provided by the Indian Institute of Technology Bombay, Centre of Excellence in Climate Studies (IITB-CECS) project of the Department of Science and Technology (DST), New Delhi, India. We are also thankful to Dr. Holger Frey, Department of Geography, University of Zurich, Switzerland for answering our queries during the development phase of the GlabTop2 model. The authors are thankful to the DLR, Germany for providing TanDEM-X CoSSC products under TanDEM-X Science proposal XTI_GLAC7043. MFA acknowledges the research funds from DST-IFCPAR/CEFIPRA project no. 3900-W1 and the French National Research Agency for providing the DGPS devices to perform field measurements. We are also thankful for the constructive comments given by the three anonymous referees which helped to improve the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

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