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@ARTICLE{Li:21361,
      author       = {Li, L. and Zhou, H. and Hendricks-Franssen, H.J. and
                      Gomez-Hernandez, J.J.},
      title        = {{G}roundwater flow inverse modeling in
                      non-{M}ulti{G}aussian media: performance assessment of the
                      normal-score {E}nsemble {K}alman {F}ilter},
      journal      = {Hydrology and earth system sciences},
      volume       = {16},
      issn         = {1027-5606},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {PreJuSER-21361},
      pages        = {573 - 590},
      year         = {2012},
      note         = {The authors gratefully acknowledge the financial support by
                      the Spanish Ministry of Science and Innovation through
                      project CGL2011-23295. The two anonymous reviewers are
                      gratefully acknowledged for their comments which helped
                      improving the final version of the manuscript.},
      abstract     = {The normal-score ensemble Kalman filter (NS-EnKF) is tested
                      on a synthetic aquifer characterized by the presence of
                      channels with a bimodal distribution of its hydraulic
                      conductivities. This is a clear example of an aquifer that
                      cannot be characterized by a multiGaussian distribution.
                      Fourteen scenarios are analyzed which differ among them in
                      one or various of the following aspects: the prior random
                      function model, the boundary conditions of the flow problem,
                      the number of piezometers used in the assimilation process,
                      or the use of covariance localization in the implementation
                      of the Kalman filter. The performance of the NS-EnKF is
                      evaluated through the ensemble mean and variance maps, the
                      connectivity patterns of the individual conductivity
                      realizations and the degree of reproduction of the
                      piezometric heads. The results show that (i) the localized
                      NS-EnKF can characterize the non-multiGaussian underlying
                      hydraulic distribution even when an erroneous prior random
                      function model is used, (ii) localization plays an important
                      role to prevent filter inbreeding and results in a better
                      logconductivity characterization, and (iii) the NS-EnKF
                      works equally well under very different flow
                      configurations.},
      keywords     = {J (WoSType)},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      shelfmark    = {Geosciences, Multidisciplinary / Water Resources},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000300882000023},
      doi          = {10.5194/hess-16-573-2012},
      url          = {https://juser.fz-juelich.de/record/21361},
}