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@ARTICLE{Zhang:838133,
      author       = {Zhang, Hongjuan and Hendricks Franssen, Harrie-Jan and Han,
                      Xujun and Vrugt, Jasper A. and Vereecken, Harry},
      title        = {{S}tate and parameter estimation of two land surface models
                      using the ensemble {K}alman filter and the particle filter},
      journal      = {Hydrology and earth system sciences},
      volume       = {21},
      number       = {9},
      issn         = {1607-7938},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2017-06837},
      pages        = {4927 - 4958},
      year         = {2017},
      abstract     = {Land surface models (LSMs) use a large cohort of parameters
                      and state variables to simulate the water and energy balance
                      at the soil–atmosphere interface. Many of these model
                      parameters cannot be measured directly in the field, and
                      require calibration against measured fluxes of carbon
                      dioxide, sensible and/or latent heat, and/or observations of
                      the thermal and/or moisture state of the soil. Here, we
                      evaluate the usefulness and applicability of four different
                      data assimilation methods for joint parameter and state
                      estimation of the Variable Infiltration Capacity Model
                      (VIC-3L) and the Community Land Model (CLM) using a
                      5-monthcalibration (assimilation) period (March–July 2012)
                      of areal-averaged SPADE soil moisture measurements at 5, 20,
                      and 50 cm depths in the Rollesbroich experimental test site
                      in the Eifel mountain range in western Germany. We used the
                      EnKF with state augmentation or dual estimation,
                      respectively, and the residual resampling PF with a simple,
                      statistically deficient, or more sophisticated, MCMC-based
                      parameter resampling method. The performance of the
                      “calibrated” LSM models was investigated using SPADE
                      water content measurements of a 5-month evaluation period
                      (August–December 2012). As expected, all DA methods
                      enhance the ability of the VIC and CLM models to describe
                      spatiotemporal patterns of moisture storage within the
                      vadose zone of the Rollesbroich site, particularly if the
                      maximum baseflow velocity (VIC) or fractions of and, clay,
                      and organic matter of each layer (CLM) are estimated jointly
                      with the model states of each soil layer. The differences
                      between the soil moisture simulations of VIC-3L and CLM are
                      much larger than the discrepancies among the four data
                      assimilation methods. The EnKF with state augmentation or
                      dual estimation yields the best performance of VIC-3L and
                      CLM during the calibration and evaluation period, yet
                      results are in close agreementwith the PF using MCMC
                      resampling. Over-all, CLM demonstrated the best performance
                      for the Rollesbroich site. The large systematic
                      underestimation of water storage at 50 cm depth by VIC-3L
                      during the first few months of the evaluation period
                      questions, in part, the validity of its fixed water table
                      depth at the bottom of the modeled soil domain.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000412245400001},
      doi          = {10.5194/hess-21-4927-2017},
      url          = {https://juser.fz-juelich.de/record/838133},
}