Broadband spectral induced polarization for the detection of Permafrost and an approach to ice content estimation – a case study from Yakutia, Russia

Abstract

The reliable detection of subsurface ice using non-destructive geophysical methods is an important objective in permafrost research. The ice content of the frozen ground is an essential parameter for further interpretation, for example in terms of risk analysis and 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 conductivity and permittivity of the subsurface, in a frequency range between 100 Hz and 100 kHz. As the electrical permittivity of ice exhibits a strong characteristic behaviour in this frequency range, HFIP in principle is 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. Compared to a previous generation, the new system is equipped with longer cables and higher 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. In this model, the ice relaxation is considered the dominant process in the frequency range around 10 kHz. 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.