Investigating Quick Clays in Norway Using CSRMT Data

Recent years have witnessed an alarming increase in quick-clay landslides in Nordic countries, such as in Alta (Norway), Gjerdrum (Norway), and Stenungsund (Sweden), resulting in substantial damages and loss of lives. This study focuses on the application of geophysical methods, particularly the Controlled-source Radio-magnetotelluric (CSRMT) technique, to understand the characteristics and model the geometry and possibly dynamics of quick clay in these regions. The CSRMT method, combines Radio-magnetotelluric (RMT) and Controlled-source Magnetotelluric (CSMT) techniques and offers an innovative approach for investigating the electrical resistivity of subterranean structures, crucial for identifying quick clay zones. The Rissa region in Norway provides a unique opportunity for this research due to its historical context and existing infrastructure for geophysical studies. The catastrophic Rissa landslide of 1978 led to an extensive national quick clay mapping initiative, forming the basis for this study. We have also collected Distributed Acoustic Sensing (DAS) data at Rissa, intending to integrate it with CSRMT data for comprehensive analysis.

Borehole analyses at the Rissa site reveal a relatively simple stratigraphy with a flat terrain and a marine clay stratum about 20 meters thick. Quick clay layers, identifiable due to their higher electrical resistivity compared to marine clays, are sandwiched in borehole samples. Our study utilizes (CS)RMT to model these layers and assess the impact of seasonal variations on their characteristics. Data collection involved a 250-meter long CSRMT profile with a 10-meter station spacing conducted in both summer and winter seasons. The EnviroMT instrument from Uppsala University was used for data acquisition. This time-lapse approach was critical to study the resistivity differences due to seasonal variation at the quick clay site.

Results from modelling the CSRMT data show a four-layer model including L1-L4. L2 appeared thicker in winter, possibly due to reduced freshwater. Conversely, in some locations, L2 appeared thicker. These findings show that CSRMT data can distinguish resistivity differences at a quick-clay site due to seasonal variations. This research offers significant insights into the modelling of seasonal variations of the resistivity related to changes in the water content which in turn might lead to development of areas with quick clays. The integration of CSRMT and DAS data presents a novel approach to studying these phenomena, potentially aiding in better understanding and predicting quick-clay landslide triggering. The findings are not only crucial for academic research but also have profound implications for infrastructure planning and disaster management in regions prone to quick-clay landslides.