A monitoring system for spatiotemporal electrical self-potential measurements in cryospheric environments

Abstract

Climate-induced warming increasingly leads to degradation of high-alpine permafrost. In order to develop early warning systems for imminent slope destabilization, knowledge about hydrological flow processes in the subsurface is urgently needed. Due to the fast dynamics associated with slope failures, non- or minimally invasive methods are required for inexpensive and timely characterization and monitoring of potential failure sites to allow in-time responses. These requirements can potentially be met by geophysical methods usually applied in near-surface geophysical settings, such as electrical resistivity tomography (ERT), ground-penetrating radar (GPR), various seismic methods, and self-potential (SP) measurements. While ERT and GPR have their primary uses in detecting lithological subsurface structure and liquid water/ice content variations, SP measurements are sensitive to active water flow in the subsurface. Combined, these methods provide huge potential to monitor the dynamic hydrological evolution of permafrost systems. However, while conceptually simple, the technical application of the SP method in high-alpine mountain regions is challenging, especially if spatially resolved information is required. We here report on the design, construction, and testing phase of a multi-electrode SP measurement system aimed at characterizing surface runoff and meltwater flow on the Schilthorn, Bernese Alps, Switzerland. Design requirements for a year-round measurement system are discussed; the hardware and software of the constructed system, as well as test measurements are presented, including detailed quality-assessment studies. On-site noise measurements and one laboratory experiment on freezing and thawing characteristics of the SP electrodes provide supporting information. It was found that a detailed quality assessment of the measured data is important for such challenging field site operations, requiring adapted measurement schemes to allow for the extraction of robust data in light of an environment highly contaminated by anthropogenic and natural noise components. Finally, possible short- and long-term improvements to the system are discussed and recommendations for future installations are developed.