Abstract ID: 28.7288 | Accepted as Poster | Poster | 2025-02-27 13:00, 2025-02-27 13:00:00 - 14:30, 2025-02-27 14:30:00 | Ágnes‐Heller‐Haus/Small Lecture Room

Glacial lake outburst floods (GLOF) pose a significant risk for settlements and infrastructure in glacierised catchments. Various studies have investigated the current distribution and past evolution of the abundance of glacial lakes and their associated flood risk. Overall, a positive trend in both the number of glacial lakes and the incidence of GLOFs seems to be identifiable as climate change leads to glacier retreat and larger lakes. As climate change is expected to lead to continued substantial glacier retreat worldwide, it is very likely new glacial lakes will continue to emerge and pose risks to downstream populations, infrastructure and ecosystems. To mitigate these risks, the analysis of present and of future glacial lake abundance is therefore crucial. This study aims to detect bedrock depressions that could allow the development of future glacial lakes. The detection is based on a new dataset of subglacial bed topographies from ice-thickness estimates derived using velocity-based inverse modelling in the Instructed Glacier Model (IGM). Using a topographical sink detection algorithm on this new bed topography dataset allows the detection of subglacial depressions worldwide. These depressions have a high potential to evolve into glacier lakes in the future. Contextualising the results of this study with present glacier lake distribution reveals the evolution of GLOF risk in the Randolph Glacier Inventory (RGI) regions with the ongoing retreat of glaciers. As part of a larger project, these first findings lay the basis for estimating the temporal evolution of GLOF hazard in glacierised catchments in a warming climate.