Detecting interannual and seasonal variability in rock glacier movement using a feature tracking approach

Abstract

Permafrost degradation induces changes in water availability and runoff as well as slope instabilities in alpine regions. A thorough quantification of the degradational processes is therefore important for society in the immediate region and beyond, as it helps deepening our understanding and ultimately allows anticipating future trajectories of the alpine cryosphere. However, permafrost being an underground phenomenon makes quantification and temporal differentiation of the degradation processes inherently difficult. Active rock glaciers have become a prime research object as internal permafrost degradation induces changes in their kinematic behaviour. In our study, we investigate the surface kinematics of the Kaiserberg rock glacier in the Austrian Kaunertal on different timescales. To derive interannual surface displacement rates, we rely on UAV-derived digital topography from 2019-2022. In addition, we installed a time-lapse camera that records daily images of the rock glacier in July 2022 to resolve rock glacier movement at a higher temporal resolution. For both data sets, we use a feature-tracking approach as implemented in the environmental motion tracking software EMT. Preliminary results show differentiated velocity fields on the rock glacier surface with the southern lobe moving significantly faster than the larger northern lobe. Mean movement rates (2019- 2022) are around 0.58 m yr-1 for the southern lobe where maximum movement rates range up to 1.80 m yr-1. In contrast, mean movement rates for the northern lobe are only 0.1 m yr-1 with maximum rates of 0.36 m yr-1. Similar to earlier studies, we find a general increase in surface velocities over the past years that points to ongoing permafrost degradation. The pending analysis of the daily time lapse photos will provide an insight into how much of the annual movement occurs in summer and how the kinematics vary within a single season. As the timing of data acquisition varied each year, this knowledge can then also be used to refine the interpretation of interannual movement rates.