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@ARTICLE{Montzka:14642,
      author       = {Montzka, C. and Moradkhani, H. and Weihermüller, L. and
                      Hendricks Franssen, H.-J. and Canty, M. and Vereecken, H.},
      title        = {{H}ydraulic parameter estimation by remotely-sensed top
                      soil moisture observations with the particle filter},
      journal      = {Journal of hydrology},
      volume       = {399},
      issn         = {0022-1694},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {PreJuSER-14642},
      year         = {2011},
      note         = {Record converted from VDB: 12.11.2012},
      abstract     = {In a synthetic study we explore the potential of using
                      surface soil moisture measurements obtained from different
                      satellite platforms to retrieve soil moisture profiles and
                      soil hydraulic properties using a sequential data
                      assimilation procedure and a 1D mechanistic soil water
                      model. Four different homogeneous soil types were
                      investigated including loamy sand, loam, silt, and clayey
                      soils. The forcing data including precipitation and
                      potential evapotranspiration were taken from the
                      meteorological station of Aachen (Germany). With the aid of
                      the forward model run, a synthetic data set was designed and
                      observations were generated. The virtual top soil moisture
                      observations were then assimilated to update the states and
                      hydraulic parameters of the model by means of a particle
                      filtering data assimilation method. Our analyses include the
                      effect of assimilation strategy, measurement frequency,
                      accuracy in surface soil moisture measurements, and soils
                      differing in textural and hydraulic properties.With this
                      approach we were able to assess the value of periodic
                      spaceborne observations of top soil moisture for soil
                      moisture profile estimation and identify the adequate
                      conditions (e.g. temporal resolution and measurement
                      accuracy) for remotely sensed soil moisture data
                      assimilation. Updating of both hydraulic parameters and
                      state variables allowed better predictions of top soil
                      moisture contents as compared with updating of states only.
                      An important conclusion is that the assimilation of
                      remotely-sensed top soil moisture for soil hydraulic
                      parameter estimation generates a bias depending on the soil
                      type. Results indicate that the ability of a data
                      assimilation system to correct the soil moisture state and
                      estimate hydraulic parameters is driven by the non linearity
                      between soil moisture and pressure head. (c) 2011 Elsevier
                      B.V. All tights reserved.},
      keywords     = {J (WoSType)},
      cin          = {IBG-3},
      ddc          = {690},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      shelfmark    = {Engineering, Civil / Geosciences, Multidisciplinary / Water
                      Resources},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000288828500024},
      doi          = {10.1016/j.jhydrol.2011.01.020},
      url          = {https://juser.fz-juelich.de/record/14642},
}