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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 2
The Cryosphere, 9, 781–794, 2015
https://doi.org/10.5194/tc-9-781-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 9, 781–794, 2015
https://doi.org/10.5194/tc-9-781-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 27 Apr 2015

Research article | 27 Apr 2015

Sensitivity of airborne geophysical data to sublacustrine and near-surface permafrost thaw

B. J. Minsley1, T. P. Wellman2, M. A. Walvoord3, and A. Revil4,5 B. J. Minsley et al.
  • 1USGS, Crustal Geophysics and Geochemistry Science Center, Denver, Colorado, USA
  • 2USGS, Colorado Water Science Center, Denver, Colorado, USA
  • 3USGS, National Research Program, Denver, Colorado, USA
  • 4Colorado School of Mines, Department of Geophysics, Golden, Colorado, USA
  • 5ISTerre, UMR CNRS 5275, Université de Savoie, Le Bourget du Lac, France

Abstract. A coupled hydrogeophysical forward and inverse modeling approach is developed to illustrate the ability of frequency-domain airborne electromagnetic (AEM) data to characterize subsurface physical properties associated with sublacustrine permafrost thaw during lake-talik formation. Numerical modeling scenarios are evaluated that consider non-isothermal hydrologic responses to variable forcing from different lake depths and for different hydrologic gradients. A novel physical property relationship connects the dynamic distribution of electrical resistivity to ice saturation and temperature outputs from the SUTRA groundwater simulator with freeze–thaw physics. The influence of lithology on electrical resistivity is controlled by a surface conduction term in the physical property relationship. Resistivity models, which reflect changes in subsurface conditions, are used as inputs to simulate AEM data in order to explore the sensitivity of geophysical observations to permafrost thaw. Simulations of sublacustrine talik formation over a 1000-year period are modeled after conditions found in the Yukon Flats, Alaska. Synthetic AEM data are analyzed with a Bayesian Markov chain Monte Carlo algorithm that quantifies geophysical parameter uncertainty and resolution. Major lithological and permafrost features are well resolved by AEM data in the examples considered. The subtle geometry of partial ice saturation beneath lakes during talik formation cannot be resolved using AEM data, but the gross characteristics of sub-lake resistivity models reflect bulk changes in ice content and can identify the presence of a talik. A final synthetic example compares AEM and ground-based electromagnetic responses for their ability to resolve shallow permafrost and thaw features in the upper 1–2 m below ground outside the lake margin.

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