% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Li:20302,
      author       = {Li, L. and Zhou, H. and Hendricks-Franssen, H.J. and
                      Gomez-Hernandez, J.},
      title        = {{M}odeling transient groundwater flow by coupling ensemble
                      {K}alman filtering and upscaling},
      journal      = {Water resources research},
      volume       = {48},
      issn         = {0043-1397},
      address      = {Washington, DC},
      publisher    = {AGU},
      reportid     = {PreJuSER-20302},
      pages        = {W01537},
      year         = {2012},
      note         = {The authors acknowledge Wolfgang Nowak and three anonymous
                      reviewers for their comments on the previous versions of the
                      manuscript, which helped substantially to improve it. The
                      authors gratefully acknowledge the financial support by the
                      Spanish Ministry of Science and Innovation through project
                      CGL2011-23295. Extra travel grants awarded to the first and
                      second authors by the Ministry of Education (Spain) are also
                      acknowledged. The second author also acknowledges financial
                      support from the China Scholarship Council.},
      abstract     = {The ensemble Kalman filter (EnKF) is coupled with upscaling
                      to build an aquifer model at a coarser scale than the scale
                      at which the conditioning data (conductivity and piezometric
                      head) had been taken for the purpose of inverse modeling.
                      Building an aquifer model at the support scale of
                      observations is most often impractical since this would
                      imply numerical models with many millions of cells. If, in
                      addition, an uncertainty analysis is required involving some
                      kind of Monte Carlo approach, the task becomes impossible.
                      For this reason, a methodology has been developed that will
                      use the conductivity data at the scale at which they were
                      collected to build a model at a (much) coarser scale
                      suitable for the inverse modeling of groundwater flow and
                      mass transport. It proceeds as follows: (1) Generate an
                      ensemble of realizations of conductivities conditioned to
                      the conductivity data at the same scale at which
                      conductivities were collected. (2) Upscale each realization
                      onto a coarse discretization; on these coarse realizations,
                      conductivities will become tensorial in nature with
                      arbitrary orientations of their principal components. (3)
                      Apply the EnKF to the ensemble of coarse conductivity
                      upscaled realizations in order to condition the realizations
                      to the measured piezometric head data. The proposed approach
                      addresses the problem of how to deal with tensorial
                      parameters, at a coarse scale, in ensemble Kalman filtering
                      while maintaining the conditioning to the fine-scale
                      hydraulic conductivity measurements. We demonstrate our
                      approach in the framework of a synthetic worth-of-data
                      exercise, in which the relevance of conditioning to
                      conductivities, piezometric heads, or both is analyzed.},
      keywords     = {J (WoSType)},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      shelfmark    = {Environmental Sciences / Limnology / Water Resources},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000299702100001},
      doi          = {10.1029/2010WR010214},
      url          = {https://juser.fz-juelich.de/record/20302},
}