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@PHDTHESIS{Gting:834749,
      author       = {Güting, Nils},
      title        = {{H}igh resolution imaging and modeling of aquifer
                      structure},
      volume       = {383},
      school       = {Ruhr-Universität Bochum},
      type         = {Dr.},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2017-04645},
      isbn         = {978-3-95806-253-5},
      series       = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
                      Umwelt / Energy $\&$ Environment},
      pages        = {viii, 107 S.},
      year         = {2017},
      note         = {Ruhr-Universität Bochum, Diss., 2017},
      abstract     = {Predictive modeling of groundwater flow and solute
                      transport can help to protect groundwater resources and to
                      remediate contaminated sites. It is challenging, however,to
                      develop realistic groundwater models because it is difficult
                      to characterize and model the complex heterogeneity of
                      geologic media. In this work, we propose an approach that
                      combines high resolution geophysical imaging and
                      multiple-point statistical modeling to estimate the 3-D
                      structure of aquifers. Our study is carried out at the
                      Krauthausen site, Germany, where 15
                      cross-boreholeground-penetrating radar (GPR) data sets were
                      acquired in an all uvial sand and gravel aquifer. To analyze
                      the GPR data, we apply a recently developed full-waveform
                      inversion approach that is preferable, in terms of spatial
                      resolution, over traditional ray based inversion approaches.
                      By stitching together the inverted tomograms from adjacent
                      crosshole planes, we are able to image, with a
                      decimeter-scale resolution, the aquifer’s electrical
                      properties (dielectric permittivity and electrical
                      conductivity) along vertical cross-sections up to 50 m long
                      and 10 m deep. Comparison of the GPR results with co-located
                      direct-push profiles shows a strong correlation between the
                      porosity derived from GPR dielectric permittivity and the
                      porosity derived from direct-push neutron logs. We can show
                      that the dielectric permittivity obtained from full-wave
                      form inversion more accurately reconstructs sharp contrasts
                      and fine-scale variations in porositythan the dielectric
                      permittivity obtained from traditional ray-based inversion.
                      One problem with using GPR for hydrogeological site
                      characterization is that GPR yields electrical properties
                      which are only indirectly linked to hydraulic properties. We
                      present two approaches to estimate hydrogeological facies
                      from the GPR results. The first approach, based on k-means
                      cluster analysis, is applied to GPR data from five adjacent
                      crosshole planes. Cluster analysis of the GPR results
                      suggests three facies. Densely spaced cone penetration
                      tests, located along the GPR transect, confirm the number of
                      facies and their spatial distribution in the aquifer
                      cross-section. Grain size distributions and flowmeter data,
                      available from one of the boreholes, show that the derived
                      facies boundaries correlate with changes in grain size and
                      porosity, and to a lesser extent with changes in hydraulic
                      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},
      urn          = {urn:nbn:de:0001-2017120719},
      url          = {https://juser.fz-juelich.de/record/834749},
}