Modeling glacier thickness distribution and bed topography over entire mountain ranges with GlabTop: Application of a fast and robust approach

Abstract

[1] The combination of glacier outlines with digital elevation models (DEMs) opens new dimensions for research on climate change impacts over entire mountain chains. Of particular interest is the modeling of glacier thickness distribution, where several new approaches were proposed recently. The tool applied herein, GlabTop (Glacier bed Topography) is a fast and robust approach to model thickness distribution and bed topography for large glacier samples using a Geographic Information System (GIS). The method is based on an empirical relation between average basal shear stress and elevation range of individual glaciers, calibrated with geometric information from paleoglaciers, and validated with radio echo soundings on contemporary glaciers. It represents an alternative and independent test possibility for approaches based on mass-conservation and flow. As an example for using GlabTop in entire mountain ranges, we here present the modeled ice thickness distribution and bed topography for all Swiss glaciers along with a geomorphometric analysis of glacier characteristics and the overdeepenings found in the modeled glacier bed. These overdeepenings can be seen as potential sites for future lake formation and are thus highly relevant in connection with hydropower production and natural hazards. The thickest ice of the largest glaciers rests on weakly inclined bedrock at comparably low elevations, resulting in a limited potential for a terminus retreat to higher elevations. The calculated total glacier volume for all Swiss glaciers is 75 AE 22 km 3 for 1973 and 65 AE 20 km 3 in 1999. Considering an uncertainty range of AE30%, these results are in good agreement with estimates from other approaches.Citation: Linsbauer, A., F. Paul, and W. Haeberli (2012), Modeling glacier thickness distribution and bed topography over entire mountain ranges with GlabTop: Application of a fast and robust approach,

Glacial lake outburst flood risk in Himachal Pradesh, India: an integrative and anticipatory approach considering current and future threats

“…The modelled ice thickness distribution is subtracted from a surface DEM to obtain the bed topography, i.e. a DEM without glaciers, from which overdeepenings in the glacier bed can be detected and analysed (see, Linsbauer et al 2012Linsbauer et al , 2016 (Fig. 5).…”

High uncertainty in 21st century runoff projections from glacierized basins

“…Based on different approaches, the uncertainty in glacier volume calculations without a priori knowledge on ice thickness has been estimated as about AE30% (e.g., Gabbi et al, 2012;Huss and Farinotti, 2012;Linsbauer et al, 2012). To assess the impact of this uncertainty source, the observation-based ice thickness distribution of Anderson (2000) Findelengletscher is scaled with a factor f = 0.7, mimicking a 30% ice volume underestimate (Exp.…”

Observation-Based Estimates of Global Glacier Mass Change and Its Contribution to Sea-Level Change

“…Based on detailed worldwide ice-thickness modeling, Huss and Farinotti (2012) provided a value of 0.43 ± 0.06 m sealevel equivalent for the total ice volume. Haeberli and Linsbauer (2013) used information from modeled glacier-bed topographies for still existing mountain glaciers (Linsbauer et al 2012 for the Swiss Alps; cf. also Linsbauer et al 2015 for the Himalaya-Karakoram region) to infer that ice below sea level and in overdeepenings together accounts for a few (probably 1-6) centimeters SLE, with millimeters rather than centimeters in overdeepenings and centimeters rather than millimeters below sea level.…”

“…The same technique can also be used to assess quantitative information on mass changes through time of large glacier samples and entire mountain regions . New technologies like numerical modeling of detailed glacier-bed topographies (e.g., Clarke et al 2013;Huss and Farinotti 2012;Linsbauer et al 2012) that can be used to bridge spatio-temporal gaps in the observational network and low-cost/high-precision measurements with LIDAR (Bhardwaj et al 2016a) or drones (Bhardwaj et al 2016b) are now refining observational techniques as well as the frequency and quality of obtained results.…”

“…Glacier-specific calculations can only be performed when the glacier mask is divided into entities by drainage divides. In a first step, a single glacier inventory is already highly useful as it allows selecting glaciers by size, using their mean elevation as a proxy for the balanced-budget equilibrium line altitude ELA 0 (Braithwaite and Raper 2010) and henceforth precipitation amounts (e.g., Sakai et al 2015), or calculating their ice-thickness distribution (Huss and Farinotti 2012;Linsbauer et al 2012;Frey et al 2014) or length Machguth and Huss 2014). When glacier-specific outlines are combined with elevation changes derived from DEM differencing and an appropriate assumption for density (e.g., Huss 2013), it is possible to not only determine the sea level equivalent contribution of an entire region (e.g., Rignot et al 2003;Schiefer et al 2007;Berthier et al 2010), but also Field measurements added as reference the mean changes for each individual glacier.…”