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@PHDTHESIS{vonHebel:828895,
      author       = {von Hebel, Christian},
      title        = {{C}alibration and large-scale inversion of
                      multi-configuration electromagnetic induction data for
                      vadose zone characterization},
      volume       = {361},
      school       = {RWTH Aachen},
      type         = {Dissertation},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2017-02746},
      isbn         = {978-3-95806-210-8},
      series       = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
                      Umwelt / Energy $\&$ Environment},
      pages        = {ix, 123 S.},
      year         = {2017},
      note         = {RWTH Aachen, Diss., 2016},
      abstract     = {Frequency-domain electromagnetic induction (EMI) devices
                      measure a secondary magnetic field superimposed by the
                      transmitted primary magnetic field in current conducting
                      media. Commercially available systems convert this magnetic
                      field ratio into an apparent electrical conductivity (ECa),
                      not concretely stated but probably with a linear
                      approximation assuming low induction numbers (LIN). In the
                      LIN-based conversion, errors were observed between the true
                      ground electrical conductivity ($\sigma(z_{i}$)) and ECa
                      such that the present thesis introduces an improved
                      non-linear exact ECa conversion (EEC) approach that can be
                      used beyond the LIN approximation. Until recently, the EMI
                      method was used for qualitative data interpretations because
                      quantitative ECa values were often not obtained. For
                      example, the operator or the field setup generated
                      additional magnetic fields being measured by the EMI device
                      that shift the recorded ECa. To eliminate the shifts, a
                      post-calibration is required. Here, a cross-correlation
                      between measured and predicted EMI-ECa values resulted in
                      calibration parameters that were applied to the EMI data
                      such that quantitative ECa values were obtained. To predict
                      the EMI device specific ECa values, a Maxwell-based
                      electromagnetic forward model (EM-FM) used $\sigma(z_{i}$)
                      obtained from inverted electrical resistivity tomography
                      (ERT) or inverted vertical electrical sounding (VES) data.
                      Analyzing several post-calibrations based on ERT,
                      coefficients of determination of R$^{2}$ > 0.75 were
                      obtained when the data range along a calibration line
                      exceeded 3 mS/m and when the ground electrical conductivity
                      was larger than 5 mS/m. Using derived calibrations of
                      different test sites, universal calibration parameters were
                      obtained that allowed postcalibrations without an ERT
                      reference line. Combining the introduced EEC with the
                      modeling using the EM-FM that assumes horizontal layers in a
                      multi-layer inversion of the post-calibrated EMI data, no
                      errors were introduced anymore such that these methods can
                      be applied also for high electrical conductive, e.g., saline
                      areas, where the LIN approximation is no longer valid.
                      Large-scale EMI measurements often reflect relevant
                      subsurface patterns, but only few researchers have attempted
                      to resolve the vertical changes in electrical conductivity
                      [...]},
      cin          = {IBG-3},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
      url          = {https://juser.fz-juelich.de/record/828895},
}