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Electromagnetic induction methods reveal wetland hydrogeological structure and properties
  • +4
  • Paul McLachlan,
  • Guillaume Blanchy,
  • Jonathan Edward Chambers,
  • James Sorensen,
  • Sebastian Uhlemann,
  • Paul Bryan Wilkinson,
  • Andrew Binley
Paul McLachlan
Bordeaux INP, Bordeaux INP

Corresponding Author:[email protected]

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Guillaume Blanchy
Lancaster University, Lancaster University
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Jonathan Edward Chambers
British Geological Survey, British Geological Survey
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James Sorensen
British Geological Survey, British Geological Survey
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Sebastian Uhlemann
Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory
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Paul Bryan Wilkinson
British Geological Survey, British Geological Survey
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Andrew Binley
Lancaster University, Lancaster University
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Abstract

Understanding sensitive wetlands often requires non-invasive methods to characterize their complex geological structure and hydrogeological parameters. Here, geoelectrical characterization is explored by employing frequency-domain electromagnetic induction (EMI) at a site previously characterized by extensive intrusive measurements and 3D electrical resistivity tomography (ERT). This work investigates the performance of several approaches to obtain structural information from EMI data and sharp and smooth inversions. Additionally, the hydrological information content of EMI data is investigated using correlation with piezometric measurements, established petrophysical relationships, and synthetic modeling. EMI measurements were dominated by peat thickness and were relatively insensitive to both topography and depth to bedrock. An iso-conductivity method for peat depth estimation had a normalized mean absolute difference (NMAD) of 23.5%, and although this performed better than the sharp inversion algorithm (NMAD = 73.5%), a multi-linear regression approach achieved a more accurate prediction with only 100 measurements (NMAD = 17.8%). In terms of hydrological information content, it was not possible to unravel correlation causation at the site, however, synthetic modeling demonstrates that the EMI measurements are predominantly controlled by the electrical conductivity of the upper peat pore-water and not the thickness of the unsaturated zone or the lower peat pore-water conductivity. Additionally, a priori information significantly improves the potential for time-lapse applications in similar environments. This study provides an objective overview and insights for future EMI applications in similar environments. It also covers areas seldom investigated in EMI studies, e.g. error quantification and the depth of investigation of ERT models used for EMI calibration.