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

Abstract

ABSTRACTEstimation 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.