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@PHDTHESIS{Oberdrster:11710,
      author       = {Oberdörster, Christoph},
      title        = {{H}ydrological {C}haracterization of a {F}orest {S}oil
                      {U}sing {E}lectrical {R}esistivity {T}omography},
      volume       = {76},
      issn         = {1866-1793},
      school       = {Universität Bonn},
      type         = {Dr.},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {PreJuSER-11710},
      isbn         = {978-3-89336-647-7},
      series       = {Schriften des Forschungszentrums Jülich : Energie $\&$
                      Umwelt / Energy $\&$ Environment},
      pages        = {XXI, 151 S.},
      year         = {2010},
      note         = {Record converted from VDB: 12.11.2012; Univ. Bonn, Diss.,
                      2010},
      abstract     = {An explicit knowledge of soil properties is required in
                      agronomy, nature conservation, and hydrology to characterize
                      water storage and water flow processes, even more in the
                      context of climate change. Electrical resistivity tomography
                      (ERT) has become a more frequently used method in soil
                      science and hydrogeology to obtain this information since
                      the bulk soil electrical conductivity, $\sigma_{b}$, derived
                      from ERT is directly linked to the soil water content,
                      $\theta$. In this work, a field plot (10 m x 10 m) which was
                      located in a forest on the premises of the Forschungszentrum
                      Jülich (Jülich, Germany) was equipped with 36 boreholes to
                      investigate the soil hydraulic properties of a forest stand
                      by means of ERT. First, the impact of the ERT data errors on
                      $\sigma_{b}$ was analyzed. A synthetic experiment was
                      performed to clarify whether there is a significant
                      difference between inverted ERT data sets once produced from
                      a water saturated soil profile, and once from a drier
                      profile. The related ERT data were noised in the framework
                      of a Monte Carlo approach by means of authentic error
                      distributions derived from field measurements. Different
                      error models were used within the consecutive inversion
                      process. It became obvious that data errors propagated
                      ruthlessly into the final model, leading occasionally to an
                      overlap of resulting b σ distributions related to dry and
                      wet soil conditions, respectively. The results of this study
                      suggested to evaluate data errors precisely. If possible,
                      data errors should be detected in dependence of the
                      corresponding measurement geometry. Additionally, a
                      long-term study was performed in the field to monitor
                      changes in soil water content by means of ERT. A period of
                      dewatering was chosen to calibrate the relationship between
                      $\sigma_{b}$ obtained from ERT and $\theta$ derived from
                      TDR. This petrophysical relationship was used to derive
                      water contents in an ERT image plane for a period of nine
                      months. The plausibility of the imaged spatial distributions
                      of soil water content changes could be verified by different
                      independent measurements (e.g., by TDR). The agreement with
                      those measurement techniques as well as the plausibility of
                      spatial soil water changes caused by root water uptake of
                      the trees demonstrated the additional benefit when a median
                      filter was applied to noisy time-lapse inversion results.
                      Finally, a saline tracer experiment was performed in order
                      to investigate the transport behavior of the soil. To
                      parameterize solute transport processes, the
                      convection-dispersion equation (CDE) and the mobile-immobile
                      model (MIM) were fitted to ERT and TDR data. Although
                      $\sigma_{b}$ derived from ERT was lower than TDR
                      measurements in almost all depths, estimated pore water
                      velocities of the CDE model were very similar. Early peak
                      arrival times at lower depths and long tailings of the
                      breakthrough curves (BTCs) clearly indicated preferential
                      flow phenomena which could not be described with an
                      appropriate parameterization using classical transport
                      approaches such as the CDE. Also the adaption of the MIM
                      model did not lead to more reasonable solute transport
                      parameters. However, typical features of preferential
                      transport could be detected and the spatial variability of
                      the preferential transport process could be imaged by ERT.},
      cin          = {ICG-4},
      cid          = {I:(DE-Juel1)VDB793},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      typ          = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
      url          = {https://juser.fz-juelich.de/record/11710},
}