Preprints
https://doi.org/10.5194/tc-2022-60
https://doi.org/10.5194/tc-2022-60
 
20 Apr 2022
20 Apr 2022
Status: a revised version of this preprint was accepted for the journal TC and is expected to appear here in due course.

Exploring the capabilities of electrical resistivity tomography to study subsea permafrost

Mauricio Arboleda-Zapata1, Michael Angelopoulos2, Pier Paul Overduin2, Guido Grosse2, Benjamin Jones3, and Jens Tronicke1 Mauricio Arboleda-Zapata et al.
  • 1University of Potsdam, Institute of Geosciences, Potsdam, Germany
  • 2Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
  • 3University of Alaska Fairbanks, Institute of Northern Engineering, Fairbanks, AK, United States of America

Abstract. Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warmer and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.

Mauricio Arboleda-Zapata et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-60', Anonymous Referee #1, 13 Jun 2022
    • AC1: 'Reply on RC1', Mauricio Arboleda-Zapata, 22 Jul 2022
  • RC2: 'Comment on tc-2022-60', Anonymous Referee #2, 23 Jun 2022
    • AC2: 'Reply on RC2', Mauricio Arboleda-Zapata, 22 Jul 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-60', Anonymous Referee #1, 13 Jun 2022
    • AC1: 'Reply on RC1', Mauricio Arboleda-Zapata, 22 Jul 2022
  • RC2: 'Comment on tc-2022-60', Anonymous Referee #2, 23 Jun 2022
    • AC2: 'Reply on RC2', Mauricio Arboleda-Zapata, 22 Jul 2022

Mauricio Arboleda-Zapata et al.

Mauricio Arboleda-Zapata et al.

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Short summary
We demonstrate how we can reliably estimate the thawed-frozen permafrost interface with its associated uncertainties in subsea permafrost environments using data from 2D electrical resistivity tomography (ERT). In addition, we show how further analyses considering 1D inversion and sensitivity assessments can help quantify and better understand 2D ERT inversion results. Our results illustrate the capabilities of the ERT method to get insights into the development of the subsea permafrost.