In my research on glacier hydrology and hydropower, several collaborations have been established with hydrologists, who use our simulated future glacier evolutions as an input for modelling the future runoff in Alpine regions. This includes partnerships with scientists from WSL Birmensdorf, University of Bern, the École Polytechnique Fédérale de Lausanne (Switzerland), the TU Delft (Netherlands) and the University of Bourgogne (France). I have also participated in a study that estimated the global hydropower and water storage potential that will arise from deglaciating basins during the 21st century.
The aim of my first two postdoctoral projects (2017-2019 @ ETH Zürich-WSL Birmensdorf and 2019-2021 @ TU Delft) was to extend the GLObal Glacier Evolution Model (GloGEM) of Huss & Hock (2015, Frontiers in Earth Science) by incorporating a dynamic ice flow component. The newly developed model, GloGEMflow, was applied to the European Alps in order to project the future evolution of all glaciers under the EURO-CORDEX RCM ensemble. GloGEMflow was also used to produce results for the second phase of GlacierMIP, formed the starting point to create a response time inventory of all glaciers in the European Alps, and was used to model the future evolution of all glaciers in Iceland and Scandinavia.
From December 2012 to February 2013, I had the unique chance to join a Belgian-Japanese meteorite search expedition on the Nansen ice field on the Antarctic plateau (ca. 2900 m elevation), 120 km south of the Belgian Antarctic Station (Princes Elisabeth). During this expedition hundreds of blue ice samples surface samples were collected and these revealed clear climatic signals at the surface. To constrain the age of the ice, the terrestrial age of selected meteorites (i.e. the time since they entered the atmosphere) was determined. By combining this with satellite derived surface velocities and other sources of information, we tried to better constrain the mechanism behind the Nansen blue ice trap. As of October 2020, we are now combining many different datasets in a machine learning algorithm in order to predict where to find meteorites on the Antarctic ice sheet (a kind of “Antarctic meteorite treasure map”). This work is led by Veronica Tollenaar, funded through a PhD fellowship of the Fonds de Recherche Scientifique – FNRS.
Role: Postdoctoral Scientist
Field of Research: Glaciology
Areas of Expertise: Alpine glaciology, Arctic ice caps, numerical ice flow modeling, palaeoglaciology, regional glacier evolution modelling, stable isotope geochemistry of ice, surface mass balance modelling and statistical techniques, visualisation techniques