[1] A combined geophysical and thermal monitoring approach for improved observation of mountain permafrost degradation is presented. Time-lapse inversion of repeated electrical resistivity tomography (ERT) measurements allows both active layer dynamics and interannual permafrost conditions to be delineated. Analysis of a comprehensive ERT monitoring data set from a 7-year study at Schilthorn, Swiss Alps, confirmed the applicability of ERT monitoring to observations of freezing and thawing processes on short-term, seasonal, and long-term scales. Long-term resistivity changes were evaluated on the basis of seasonal resistivity variations showing an annual cycle with high resistivities in frozen and low resistivities in unfrozen state. One important result is the detection of a sustained impact of the extraordinarily hot European summer of 2003 on the permafrost regime, which is more severe than previously assumed from borehole temperatures. Combined analyses of ERT monitoring and borehole temperature data revealed substantial ground ice degradation as a consequence of the 2003 summer, which did not recover in the following years despite suitable subsurface temperature conditions. Resistivity changes that are nonconforming to long-term temperature evolution are attributed to the limited availability of liquid water and/or changes in material characteristics (e.g., pore volume changes as a result of subsidence).Citation: Hilbich, C., C. Hauck, M. Hoelzle, M. Scherler, L. Schudel, I. Völksch, D. Vonder Mühll, and R. Mäusbacher (2008), Monitoring mountain permafrost evolution using electrical resistivity tomography: A 7-year study of seasonal, annual, and long-term variations at Schilthorn, Swiss Alps,

The inversion and interpretation of electrical resistivity tomography (ERT) data from coarse blocky and ice-rich permafrost sites are challenging due to strong resistivity contrasts and high contact resistances. To assess temporal changes during ERT monitoring (ERTM), corresponding inversion artefacts have to be separated from true subsurface changes. Appraisal techniques serve to analyse an ERTM data set from a rockglacier, including synthetic modelling, the depth of investigation index technique and the so-called resolution matrix approach. The application of these methods led step by step to the identification of unreliable model regions and thus to the improvement in interpretation of temporal resistivity changes. An important result is that resistivity values of model regions with strong resistivity contrasts and highly resistive features are generally of critical reliability, and resistivity changes within or below the ice core of a rockglacier should therefore not be interpreted as a permafrost signal. Conversely, long-term degradation phenomena in terms of warming of massive ground ice at the permafrost table are detectable by ERTM.

A ten‐year record (1999–2009) of annual mean ground surface temperatures (MGSTs) and mean ground temperatures (MGTs) was analysed for 16 monitoring sites in Jotunheimen and on Dovrefjell, southern Norway. Warming has occurred at sites with cold permafrost, marginal permafrost and deep seasonal frost. Ongoing permafrost degradation is suggested both by direct temperature monitoring and indirect geophysical surveys. An increase in MGT at 6.6–9.0‐m depth was observed for most sites, ranging from ~0.015 to ~ 0.095°C a‐1. The greatest rate of temperature increase was for sites having MGTs slightly above 0°C. The lowest rate of increase was for marginal permafrost sites that are affected by latent heat exchange close to 0°C. Increased snow depths and an increase in winter air temperatures appear to be the most important factors controlling warming observed over the ten‐year period. Geophysical surveys performed in 1999 to delineate the altitudinal limit of mountain permafrost were repeated in 2009 and 2010 and indicated the degradation of some permafrost over the intervening decade. Copyright © 2011 John Wiley & Sons, Ltd.

A new automated electrical resistivity tomography (A-ERT) system is described that allows continuous measurements of the electrical resistivity distribution in high-mountain or polar terrain. The advantages of continuous resistivity monitoring, as opposed to single measurements at irregular time intervals, are illustrated using the permafrost monitoring station at the Schilthorn, Swiss Alps. Data processing was adjusted to permit automated time-effective handling and quality assessment of the large number of 2D electrical resistivity profiles generated. Results from a one-year dataset show small temporal changes during periods with snow cover, and the largest changes during snowmelt in early summer and during freezing in autumn, which are in phase with changes in either near-surface soil moisture or subsurface temperature. During the snowmelt period, spatially variable infiltration processes were observed, leading to a rapid increase in soil moisture and corresponding decrease in electrical resistivity over a period of a few days. This infiltration led to the onset of active-layer thawing long before the seasonal snow cover vanished. Statistical analyses showed that both spatial and temporal variability over the course of one year are similar, indicating the significance of spatial heterogeneity regarding active-layer dynamics. As a result of its cost-effective ability to monitor freezing and thawing processes even at greater depths, the new A-ERT system can be widely applied in permafrost regions, especially in the context of long-term degradation processes.

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Abstract. Mountain permafrost is sensitive to climate change and is expected to gradually degrade in response to the ongoing atmospheric warming trend. Long-term monitoring of the permafrost thermal state is a key task, but problematic where temperatures are close to 0 ∘C because the energy exchange is then dominantly related to latent heat effects associated with phase change (ice–water), rather than ground warming or cooling. Consequently, it is difficult to detect significant spatio-temporal variations in ground properties (e.g. ice–water ratio) that occur during the freezing–thawing process with point scale temperature monitoring alone. Hence, electrical methods have become popular in permafrost investigations as the resistivities of ice and water differ by several orders of magnitude, theoretically allowing a clear distinction between frozen and unfrozen ground. In this study we present an assessment of mountain permafrost evolution using long-term electrical resistivity tomography monitoring (ERTM) from a network of permanent sites in the central Alps. The time series consist of more than 1000 datasets from six sites, where resistivities have been measured on a regular basis for up to 20 years. We identify systematic sources of error and apply automatic filtering procedures during data processing. In order to constrain the interpretation of the results, we analyse inversion results and long-term resistivity changes in comparison with existing borehole temperature time series. Our results show that the resistivity dataset provides valuable insights at the melting point, where temperature changes stagnate due to latent heat effects. The longest time series (19 years) demonstrates a prominent permafrost degradation trend, but degradation is also detectable in shorter time series (about a decade) at most sites. In spite of the wide range of morphological, climatological, and geological differences between the sites, the observed inter-annual resistivity changes and long-term tendencies are similar for all sites of the network.

Abstract. The ice content of the subsurface is a major factor controlling the natural hazard potential of permafrost degradation in alpine terrain. Monitoring of changes in ice content is therefore similarly important as temperature monitoring in mountain permafrost. Although electrical resistivity tomography monitoring (ERTM) proved to be a valuable tool for the observation of ice degradation, results are often ambiguous or contaminated by inversion artefacts. In theory, the sensitivity of P-wave velocity of seismic waves to phase changes between unfrozen water and ice is similar to the sensitivity of electric resistivity. Provided that the general conditions (lithology, stratigraphy, state of weathering, pore space) remain unchanged over the observation period, temporal changes in the observed travel times of repeated seismic measurements should indicate changes in the ice and water content within the pores and fractures of the subsurface material. In this paper, a time-lapse refraction seismic tomography (TLST) approach is applied as an independent method to ERTM at two test sites in the Swiss Alps. The approach was tested and validated based on a) the comparison of time-lapse seismograms and analysis of reproducibility of the seismic signal, b) the analysis of time-lapse travel time curves with respect to shifts in travel times and changes in P-wave velocities, and c) the comparison of inverted tomograms including the quantification of velocity changes. Results show a high potential of the TLST approach concerning the detection of altered subsurface conditions caused by freezing and thawing processes. For velocity changes on the order of 3000 m/s even an unambiguous identification of significant ice loss is possible.

In regions affected by seasonal and permanently frozen conditions soil moisture influences the thermal regime of the ground as well as its ice content, which is one of the main factors controlling the sensitivity of mountain permafrost to climate changes. In this study, several well established soil moisture monitoring techniques were combined with data from geophysical measurements to assess the spatial distribution and temporal evolution of soil moisture at three high elevation sites with different ground properties and thermal regimes. The observed temporal evolution of measured soil moisture is characteristic for sites with seasonal freeze/thaw cycles and consistent with the respective site-specific properties, demonstrating the general applicability of continuous monitoring of soil moisture at high elevation areas. The obtained soil moisture data were then used for the calibration and validation of two different model approaches used in permafrost research in order to characterize the lateral and vertical distribution of ice content in the ground. Calibration of the geophysically based four-phase model (4PM) with spatially distributed soil moisture data yielded satisfactory two dimensional distributions of water-, ice-, and air content. Similarly, soil moisture time series significantly improved the calibration of the one-dimensional heat and mass transfer model COUP, yielding physically consistent soil moisture and temperature data matching observations at different depths.