Decoupled kinematics of two neighbouring permafrost creeping landforms in the Eastern Italian Alps

Abstract

An overall acceleration of rock glacier displacement rates in the Alps has been observed in recent decades, with several cases of destabilization leading to potential geomorphological hazards. This behaviour has been attributed to the rising permafrost temperature, induced by atmospheric warming and regulated by thermo‐hydrological processes. Landforms derived from the interaction of glacier remnants and permafrost are widespread in mountain areas, but are less studied and monitored than talus rock glaciers. This work presents a comparative study of a talus rock glacier and a glacial‐permafrost composite landform (GPCL) in the Eastern Italian Alps. The two landforms are only 10 km apart, but have rather different elevation ranges and main slope aspects. The kinematics and ground thermal conditions were monitored from 2001 to 2015 along with geomorphological surveys, analyses of historical maps and remote sensing data. The dynamic behaviour of the rock glacier was similar to the majority of monitored rock glaciers in the Alps, with an acceleration after 2008 and a velocity peak in 2015. In contrast, the GPCL had a nearly unchanged displacement rate during the observation period. Statistical analyses of kinematic vs. nivo‐meteorological variables revealed a dynamic decoupling of the two landforms after 2008 that corresponds with increased winter snow accumulation. Although the kinematics of both landforms respond to ground surface temperature variations, the collected evidence suggests a different reaction of ground surface temperature to variations in the precipitation regime. This different reaction is likely due to local topo‐climatic conditions that affect snow redistribution by wind. The different reactions of the two systems to the same climatic forcing is likely a legacy of their different origins. GPCL dynamics result from interaction of permafrost and residual glacial dynamics that are associated with possible peculiarities in the internal/basal meltwater circulation, whose future response is uncertain and requires improved understanding. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.

A general theory of rock glacier creep based on in‐situ and remote sensing observations

“…Field and theoretical studies 8,17,18 show that at temporal scales from months to several years, these variations are mainly controlled by pore water pressure within the shear horizon. At longer temporal scales, changes in the structure of the shear horizon, driven by the combined influence of permafrost creep and ground temperature, are still poorly understood but are expected to play an important role in determining the long‐term evolution of rock glaciers and their dynamics 4,6,49 …”

Pluri‐decadal evolution of rock glaciers surface velocity and its impact on sediment export rates towards high alpine torrents

“…Over the last two decades, rock glaciers velocity and its evolution through time have been investigated by numerous studies (e.g., Bodin et al, 2018;Delaloye et al, 2008;Kellerer-Pirklbauer et al, 2017;Lambiel & Delaloye, 2004;PERMOS, 2019). As a result, a clear accelerating trend of rock glaciers displacement rates could be underlined for most surveyed sites as a consequence of warming air temperatures inducing higher ground temperatures and liquid water content (e.g., Cicoira et al, 2019;Ikeda et al, 2008;Kellerer-Pirklbauer & Kaufmann, 2012;PERMOS, 2019;Roer et al, 2008;Seppi et al, 2019).…”

An Unsupervised Method to Detect Rock Glacier Activity by Using Sentinel-1 SAR Interferometric Coherence: A Regional-Scale Study in the Eastern European Alps

“…An alternative hypothesis that can partly explain the observed overestimations can be due to possible switch of the rock glaciers' activity level in the period of the visual analysis conducted on Trentino (2006-2014) and the period investigated by SAR images (summer 2017). However, changes in the level of activity are not expected in such a short period, and this is supported by the direct measurements conducted on two rock glaciers [43].…”

“…Indeed, our findings showed that, among the three classification tests conducted using (i) the complete dataset of Sentinel-1 images, (ii) the images acquired only in August and (iii) those acquired only in September, the best classification performance was obtained using the complete dataset, and the number of no-moving rock glaciers was slightly overestimated using the two restricted datasets. For example, a rock glacier from the Trentino dataset surveyed with a laser total station and having an average velocity of 0.09 m y −1 [43] was classified as moving using the complete dataset, while using the images acquired only in August (maximum temporal baseline of 24 days) the displacement was not detected.…”

“…In Trentino, a set of 57 rock glaciers extracted from an inventory [15] ( Figure 1) was used to validate the method (Section 3.3. ), thanks to their activity status known from field observations [42], direct measurements [43], and visual analysis of multitemporal data. In detail, the visual analysis was conducted using high-resolution aerial orthophotos (2006 and 2014, 0.5 m and 0.2 m GSD, respectively) and LIDAR DTMs (2006 and 2013, 2 m and 0.5 m GSD, respectively).…”