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@ARTICLE{Kurtz:138284,
      author       = {Kurtz, W. and Hendricks Franssen, H. -J. and Brunner, P.
                      and Vereecken, H.},
      title        = {{I}s high-resolution inverse characterization of
                      heterogeneous river bed hydraulic conductivities needed and
                      possible?},
      journal      = {Hydrology and earth system sciences},
      volume       = {17},
      number       = {10},
      issn         = {1027-5606},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2013-04441},
      pages        = {3795 - 3813},
      year         = {2013},
      abstract     = {River–aquifer exchange fluxes influence local and
                      regional water balances and affect groundwater and river
                      water quality and quantity. Unfortunately, river–aquifer
                      exchange fluxes tend to be strongly spatially variable, and
                      it is an open research question to which degree river bed
                      heterogeneity has to be represented in a model in order to
                      achieve reliable estimates of river–aquifer exchange
                      fluxes. This research question is addressed in this paper
                      with the help of synthetic simulation experiments, which
                      mimic the Limmat aquifer in Zurich (Switzerland), where
                      river–aquifer exchange fluxes and groundwater management
                      activities play an important role. The solution of the
                      unsaturated–saturated subsurface hydrological flow problem
                      including river–aquifer interaction is calculated for ten
                      different synthetic realities where the strongly
                      heterogeneous river bed hydraulic conductivities (L) are
                      perfectly known. Hydraulic head data (100 in the default
                      scenario) are sampled from the synthetic realities. In
                      subsequent data assimilation experiments, where L is unknown
                      now, the hydraulic head data are used as conditioning
                      information, with the help of the ensemble Kalman filter
                      (EnKF). For each of the ten synthetic realities, four
                      different ensembles of L are tested in the experiments with
                      EnKF; one ensemble estimates high-resolution L fields with
                      different L values for each element, and the other three
                      ensembles estimate effective L values for 5, 3 or 2 zones.
                      The calibration of higher-resolution L fields (i.e. fully
                      heterogeneous or 5 zones) gives better results than the
                      calibration of L for only 3 or 2 zones in terms of
                      reproduction of states, stream–aquifer exchange fluxes and
                      parameters. Effective L for a limited number of zones cannot
                      always reproduce the true states and fluxes well and results
                      in biased estimates of net exchange fluxes between aquifer
                      and stream. Also in case only 10 head data are used for
                      conditioning, the high-resolution characterization of L
                      fields with EnKF is still feasible. For less heterogeneous
                      river bed hydraulic conductivities, a high-resolution
                      characterization of L is less important. When uncertainties
                      in the hydraulic parameters of the aquifer are also regarded
                      in the assimilation, the errors in state and flux
                      predictions increase, but the ensemble with a high spatial
                      resolution for L still outperforms the ensembles with
                      effective L values. We conclude that for strongly
                      heterogeneous river beds the commonly applied simplified
                      representation of the streambed, with spatially homogeneous
                      parameters or constant parameters for a few zones, might
                      yield significant biases in the characterization of the
                      water balance. For strongly heterogeneous river beds, we
                      suggest adopting a stochastic field approach to model the
                      spatially heterogeneous river beds geostatistically. The
                      paper illustrates that EnKF is able to calibrate such
                      heterogeneous streambeds on the basis of hydraulic head
                      measurements, outperforming zonation approaches.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {246 - Modelling and Monitoring Terrestrial Systems: Methods
                      and Technologies (POF2-246)},
      pid          = {G:(DE-HGF)POF2-246},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000326603200008},
      doi          = {10.5194/hess-17-3795-2013},
      url          = {https://juser.fz-juelich.de/record/138284},
}