The Frost.ini project: A framework enabling 4D electrical resistivity investigations on a rock glacier

The Frost.ini project, Permafrost degradation and instability of high-mountain infrastructures, funded within the Interreg VI-A Italy–Austria Programme 2021–2027, aims to develop a holistic analysis of permafrost in order to monitor its degradation and integrate risk mitigation measures into territorial management policies, thereby improving the resilience of high-altitude infrastructures.

The project is structured around a series of pilot actions carried out at sites selected according to strategic and scientific criteria, including the availability of previous studies.

The Casera Razzo rock glacier is located in the northern sector of the Friulian Dolomites, in northeastern Italy, within an alpine setting of significant geomorphological and geological interest. Traditionally classified as a relict landform based solely on surface morphology, it instead shows clear evidence of frozen material within its interior. Geophysical investigations and microclimatic measurements have identified interstitial ice and small ice lenses, indicating the presence of residual permafrost even during the period of maximum seasonal thaw.

The geoelectrical method, and in particular Electrical Resistivity Tomography (ERT), is a highly effective tool for the construction of geological models and for permafrost monitoring, as it allows non-invasive subsurface investigation and the repetition of measurements over time.

An initial resistivity model based on 2D data acquired in 2015 confirmed the presence of ice. The 3D survey carried out in 2025 using the FullWaver system by IRIS Instruments, partly overlapping the previous survey area, generated a three-dimensional resistivity model that quantified the ice volumes and provided important insights into the evolution of the rock glacier.

The results demonstrate that the FullWaver system is suitable for complex electrical investigations in environmentally challenging settings. By exploiting its capabilities, it is possible to obtain key information on permafrost evolution, which is essential for the modelling of future scenarios.