A novel combination of borehole temperature, borehole piezometer and cross-borehole electrical resistivity tomography (ERT) data is used to investigate changing ice and/or water contents in the creeping ice-rich Schafberg rock glacier in the Eastern Swiss Alps. Instrumentation techniques and first results are presented. The rock glacier ice is close to its melting point, and the landform has locally heterogeneous stratigraphies, ice and/or water contents and temperature regimes. The measurement techniques presented continuously monitor temporal and spatial phase changes to a depth of 12 m and should provide the basis for a better understanding of accelerating rock glacier kinematics and future water availability.

Observations in the European Alps show a long-term rise in rock glacier velocities, which is often associated with increased air and ground temperatures and, more recently, water content. Long-term rock glacier acceleration is superimposed by a high interannual variability of the velocity with a particular gap in the quantitative assessment of the role of water in rock glacier kinematics and the factors leading to short-term rock glacier deceleration. To address this research gap, we drilled three vertical boreholes in the Schafberg rock glacier, Swiss Alps, in August 2020. We documented their stratigraphy and equipped one of the boreholes with temperature sensors and piezometers and the other two with cross-borehole electrodes for electrical resistivity tomography measurements. Rock glacier velocities were determined using repeated terrestrial laser scans. Using data from an additional borehole and nearby weather stations and ground surface temperature sensors, we analysed the interactions between meteorological and subsurface conditions during a rock glacier deceleration period, from January 2021 to July 2023. Our findings show that a lowering of the water content in rock glacier shear horizons is crucial for interannual rock glacier deceleration. The impact of the snowpack, both as an insulator and as a water source, is significant for rock glacier kinematics. Winters with little snow and relatively dry summers appear to be ideal for rock glacier cooling and drying, leading to deceleration. Summer heat waves have limited impact on rock glacier velocity if they are preceded by snow-poor winters. Our study uses an innovative combination of borehole data to gain insights into rock glacier temperatures and water contents, allowing us to detect relative changes in ice and/or water contents in ice-rich permafrost. The monitoring techniques used have the potential to contribute to a better understanding of the main drivers of rock glacier kinematics and water availability.

Machine learning has grown in popularity in the past few years for susceptibility and hazard mapping tasks. Necessary steps for the generation of a susceptibility or hazard map are repeatedly implemented in new studies. We present a Random Forest classifier-based landslide susceptibility and hazard mapping framework to facilitate future mapping studies using machine learning. The framework, as a piece of software, follows the FAIR paradigm, and hence is set up as a transparent, reproducible and modularly extensible workflow. It contains pre-implemented steps from conceptualisation to map generation, such as the generation of input datasets. The framework can be applied to different areas of interest using different environmental features and is also flexible in terms of the desired scale and resolution of the final map. To demonstrate the functionality and validity of the framework, and to explore the challenges and limitations of Random Forest-based susceptibility and hazard mapping, we apply the framework to a test case. This test case conveys the influence of the training dataset on the generated susceptibility maps in terms of feature combination, influence of non-landslide instances and representativeness of the training data with respect to the area of interest. A comparison of the test case results with the literature shows that the framework works reliably. Furthermore, the results obtained in this study complement the findings of previous studies that demonstrate the sensitivity of the training process to the training data, particularly in terms of its representativeness.

Seismic refraction tomography is a commonly used technique to characterise rock glaciers, as the boundary between unfrozen and ice-bearing layers represents a strong impedance contrast. In several rock glaciers, we observed a reversed polarity of the waves refracted by an extended ice-bearing layer compared to direct-wave arrivals. This phase change may be related to the presence of a thin low-velocity layer (LVL), such as fine- to coarse-grained sediments, above a thicker ice-rich layer. Our results are confirmed by the modelling and analysis of synthetic seismograms to demonstrate that the presence of a low-velocity layer can produce a polarity reversal on the seismic gather.