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@ARTICLE{Kurtz:151851,
      author       = {Kurtz, Wolfgang and Hendricks-Franssen, Harrie-Jan and
                      Kaiser, Hans-Peter and Vereecken, Harry},
      title        = {{J}oint assimilation of piezometric heads and groundwater
                      temperatures for improved modeling of river-aquifer
                      interactions},
      journal      = {Water resources research},
      volume       = {50},
      number       = {2},
      issn         = {0043-1397},
      address      = {Washington, DC},
      publisher    = {AGU},
      reportid     = {FZJ-2014-01709},
      pages        = {1665–1688},
      year         = {2014},
      abstract     = {The ensemble Kalman filter (EnKF) is increasingly used to
                      improve the real-time prediction of groundwater states and
                      the estimation of uncertain hydraulic subsurface parameters
                      through assimilation of measurement data like groundwater
                      levels and concentration data. At the interface between
                      surface water and groundwater, measured groundwater
                      temperature data can provide an additional source of
                      information for subsurface characterizations with EnKF.
                      Additionally, an improved prediction of the temperature
                      field itself is often desirable for groundwater management.
                      In this work, we investigate the worth of a joint
                      assimilation of hydraulic and thermal observation data on
                      the state and parameter estimation with EnKF for two
                      different model setups: (i) a simple synthetic model of a
                      river-aquifer system where the parameters and simulation
                      conditions were perfectly known and (ii) a model of the
                      Limmat aquifer in Zurich (Switzerland) where an exhaustive
                      set of real-world observations of groundwater levels (87)
                      and temperatures (22) was available for assimilation (year
                      2007) and verification (year 2011). Results for the
                      synthetic case suggest that a joint assimilation of
                      piezometric heads and groundwater temperatures together with
                      updating of uncertain hydraulic parameters gives the best
                      estimation of states and hydraulic properties of the model.
                      For the real-world case, the prediction of groundwater
                      temperatures could also be improved through data
                      assimilation with EnKF. For the validation period, it was
                      found that parameter fields updated with piezometric heads
                      reduced RMSE's of states significantly (heads $−49\%,$
                      temperature $−15\%),$ but an additional conditioning of
                      parameters on groundwater temperatures only influenced the
                      characterization of the temperature field.},
      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:000333563900050},
      doi          = {10.1002/2013WR014823},
      url          = {https://juser.fz-juelich.de/record/151851},
}