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@ARTICLE{Rings:4875,
      author       = {Rings, J. and Hauck, C. C.},
      title        = {{R}eliability of resistivity quantification for shallow
                      subsurface water processes},
      journal      = {Atmospheric measurement techniques},
      volume       = {68},
      issn         = {1867-1381},
      address      = {Katlenburg-Lindau},
      publisher    = {Copernicus},
      reportid     = {PreJuSER-4875},
      pages        = {404 - 416},
      year         = {2009},
      note         = {The authors thank M. Chouteau and one anonymous reviewer
                      for their constructive comments which largely improved the
                      manuscript. J. Rings acknowledges a grant from the Deutsche
                      Forschungsgemeinschaft in the Postgraduate Programme Natural
                      Disasters (GK 450).},
      abstract     = {The reliability of surface-based electrical resistivity
                      tomography (ERT) for quantifying resistivities for shallow
                      subsurface water processes is analysed. A method comprising
                      numerical simulations of water movement in soil and
                      forward-inverse modeling of ERT surveys for two synthetic
                      data sets is presented. Resistivity contrast, e.g. by
                      changing water content, is shown to have large influence on
                      the resistivity quantification. An ensemble and clustering
                      approach is introduced in which ensembles of 50 different
                      inversion models for one data set are created by randomly
                      varying the parameters for a regularisation based inversion
                      routine. The ensemble members are sorted into five clusters
                      of similar models and the mean model for each cluster is
                      computed. Distinguishing persisting features in the mean
                      models from singular artifacts in individual tomograms can
                      improve the interpretation of inversion results.Especially
                      in the presence of large resistivity contrasts in high
                      sensitivity areas, the quantification of resistivities can
                      be unreliable. The ensemble approach shows that this is an
                      inherent problem present for all models inverted with the
                      regularisation based routine. The results also suggest that
                      the combination of hydrological and electrical modeling
                      might lead to better results. (C) 2009 Elsevier B.V. All
                      rights reserved.},
      keywords     = {J (WoSType)},
      cin          = {ICG-4},
      ddc          = {550},
      cid          = {I:(DE-Juel1)VDB793},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      shelfmark    = {Geosciences, Multidisciplinary / Mining $\&$ Mineral
                      Processing},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000272811300010},
      doi          = {10.1016/j.jappgeo.2009.03.008},
      url          = {https://juser.fz-juelich.de/record/4875},
}