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@ARTICLE{Laloy:186381,
      author       = {Laloy, Eric and Huisman, Johan Alexander and Jacques,
                      Diederik},
      title        = {{H}igh-resolution moisture profiles from full-waveform
                      probabilistic inversion of {TDR} signals},
      journal      = {Journal of hydrology},
      volume       = {519},
      number       = {Part B},
      issn         = {0022-1694},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2015-00457},
      pages        = {2121 - 2135},
      year         = {2014},
      abstract     = {This study presents an novel Bayesian inversion scheme for
                      high-dimensional undetermined TDR waveform inversion. The
                      methodology quantifies uncertainty in the moisture content
                      distribution, using a Gaussian Markov random field (GMRF)
                      prior as regularization operator. A spatial resolution of 1
                      cm along a 70-cm long TDR probe is considered for the
                      inferred moisture content. Numerical testing shows that the
                      proposed inversion approach works very well in case of a
                      perfect model and Gaussian measurement errors. Real-world
                      application results are generally satisfying. For a series
                      of TDR measurements made during imbibition and evaporation
                      from a laboratory soil column, the average root-mean-square
                      error (RMSE) between maximum a posteriori (MAP) moisture
                      distribution and reference TDR measurements is 0.04 cm3
                      cm-3. This RMSE value reduces to less than 0.02 cm3 cm-3 for
                      a field application in a podzol soil. The observed
                      model-data discrepancies are primarily due to model
                      inadequacy, such as our simplified modeling of the bulk soil
                      electrical conductivity profile. Among the important issues
                      that should be addressed in future work are the explicit
                      inference of the soil electrical conductivity profile along
                      with the other sampled variables, the modeling of the
                      temperature-dependence of the coaxial cable properties and
                      the definition of an appropriate statistical model of the
                      residual errors.},
      cin          = {IBG-3},
      ddc          = {690},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {246 - Modelling and Monitoring Terrestrial Systems: Methods
                      and Technologies (POF2-246) / 255 - Terrestrial Systems:
                      From Observation to Prediction (POF3-255)},
      pid          = {G:(DE-HGF)POF2-246 / G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000347018100073},
      doi          = {10.1016/j.jhydrol.2014.10.005},
      url          = {https://juser.fz-juelich.de/record/186381},
}