28 Jun 2021
28 Jun 2021
Status: this preprint is currently under review for the journal TC.

Broadband Spectral Induced Polarization for the detection of Permafrost and an approach to ice content estimation – A Case study from Yakutia, Russia

Jan Mudler1, Andreas Hördt1, Dennis Kreith1, Kirill Bazhin2, Lyudmila Lebedeva2, and Tino Radić3 Jan Mudler et al.
  • 1Technische Universität Braunschweig, Institut für Geophysik und extraterrestrische Physik, Braunschweig, Germany
  • 2Melnikov Permafrost Institute, Russian Academy of Science, Yakutsk, Russia
  • 3Radic Research, Berlin, Germany

Abstract. The reliable detection of subsurface ice using non-destructive geophysical methods is an important objective in permafrost research. Furthermore, the ice content of the frozen ground is an essential parameter for further interpretation, for example in terms of risk analysis, e.g. for the description of permafrost carbon feedback by thawing processes.

The High-Frequency Induced Polarization method (HFIP) enables the measurement of the frequency dependent electrical signal of the subsurface. In contrast to the well-established Electrical Resistivity Tomography (ERT), the usage of the full spectral information provides additional physical parameters of the ground. As the electrical properties of ice exhibit a strong characteristic behaviour in the frequency range between 100 Hz and 100 kHz, HFIP is in principle suitable to estimate ice content. Here, we present methodological advancements of the HFIP method and suggest an explicit procedure for ice content estimation.

A new measuring device, the Chameleon-II (Radic Research), was used for the first time. It was designed for the application of Spectral Induced Polarization over a wide frequency range and is usable under challenging conditions, for example in field sites under periglacial influence and the presence of permafrost. Amongst other improvements, compared to a previous generation, the new system is equipped with longer cables and larger power, such that we can now achieve larger penetration depths up to 10 m. Moreover, it is equipped with technology to reduce electromagnetic coupling effects which can distort the desired subsurface signal.

The second development is a method to estimate ice content quantitatively from five Cole-Cole parameters obtained from spectral two-dimensional inversion results. The method is based on a description of the subsurface as a mixture of two components (matrix and ice) and uses a previously suggested relationship between frequency-dependent electrical permittivity and ice content.

Measurements on a permafrost site near Yakutsk, Russia, were carried out to test the entire procedure under real conditions at the field scale. We demonstrate that the spectral signal of ice can clearly be identified even in the raw data, and show that the spectral 2-D inversion algorithm is suitable to obtain the multidimensional distribution of electrical parameters. The parameter distribution and the estimated ice content agree reasonably well with previous knowledge of the field site from borehole and geophysical investigations. We conclude that the method is able to provide quantitative ice content estimates, and that relationships that have been tested in the laboratory may be applied at the field scale.

Jan Mudler et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2021-154', Anonymous Referee #1, 22 Jul 2021
  • RC2: 'Comment on tc-2021-154', Anonymous Referee #2, 05 Aug 2021

Jan Mudler et al.

Jan Mudler et al.


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Short summary
The spectral electrical signal of ice exhibits a strong characteristic behaviour in the frequency range from 100 Hz to 100 kHz, due to polarization effects. With our geophysical method, we can analyse this characteristic to detect subsurface ice. Moreover, we use a model to quantify 2-D ground ice content based on our data. The potential of our new measurement device is showed up. Data were taken on a permafrost site in Yakutia, and the results are in agreement with other existing field data.