Automated Electrical Resistivity Tomography Testing for Early Warning in Unstable Permafrost Rock Walls Around Alpine Infrastructure
M. Keuschnig,
M. Krautblatter,
I. Hartmeyer,
C. Fuss and
L. Schrott
Permafrost and Periglacial Processes, 2017, vol. 28, issue 1, 158-171
Abstract:
Subsurface monitoring of permafrost conditions at depths up to 20–30 m is crucial to assess the safety and reliability of mountain infrastructure, because permafrost degradation critically affects rock slope stability in high mountains. Electrical resistivity tomography (ERT) provides a straightforward tool for monitoring near‐surface bedrock permafrost at monthly or longer intervals. But as rockfalls are often prepared over periods of hours or days, ERT for early warning purposes should also detect short‐term triggering events such as pressurised water flow. Here, we present the first approach to monitor steep permafrost rock walls quasi‐continuously with ERT. We measured ERT every 4 h at the up to 67° steep rock wall below the Kitzsteinhorn cable car, Austria. Wenner datasets (n = 996) were analysed from February 2013 to February 2014 in terms of data stability, raw data characteristics and measurement errors coinciding with potential disturbing factors. Strong resistivity changes coincided with rapid freezing or water inundating rock fractures. Automatically detected periods with large resistivity changes produce ERT time series with low resistivities extending from the bottom upwards during times of snowmelt. We infer that flow of pressurised water in fractures warms the surrounding rock in an upward direction, based on fracture inventories, visual observations of cleftwater and near‐surface temperature measurements. We develop a strategy for ERT monitoring suitable for potential early warning systems, where high apparent resistivity changes in 4 h intervals may precede critical hydrostatic events confined by permafrost rocks. Copyright © 2016 John Wiley & Sons, Ltd.
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:wly:perpro:v:28:y:2017:i:1:p:158-171
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