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@ARTICLE{Herbst:50874,
      author       = {Herbst, M. and Diekkrüger, B. and Vereecken, H.},
      title        = {{G}eostatistical co-regionalization of soil hydraulic
                      properties in a micro-scale catchment using terrain
                      attributes},
      journal      = {Geoderma},
      volume       = {132},
      issn         = {0016-7061},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {PreJuSER-50874},
      pages        = {206 - 221},
      year         = {2006},
      note         = {Record converted from VDB: 12.11.2012},
      abstract     = {Any effort of distributed hydrological modeling requires
                      the spatially distributed input of soil hydraulic properties
                      and soil thickness. Most of the hydrological models are
                      sensitive concerning these soil properties, thus the use of
                      point measurements and co-variables should be optimized for
                      a most accurate spatial prediction. During this study, we
                      focus on the use of terrain attributes as co-variables. In
                      order to determine the dependencies between the soil
                      properties and topography, we derived 17 terrain attributes
                      for a small rural catchment (28.6 ha). Correlation
                      statistics between these terrain attributes and soil
                      hydraulic properties calculated from measured grain size
                      distribution and organic carbon content with pedo-transfer
                      functions were used to identify terrain attributes as
                      co-variables for the spatial prediction of the soil
                      properties. We detected in particular for the following
                      terrain attributes a high prediction potential for soil
                      properties: relative elevation, slope of the catchment area,
                      radiation angle and morphometric units such as slope
                      elements. We also compared the performance of multiple
                      regression, ordinary kriging, external drift kriging and
                      regression kriging model C to estimate the spatial
                      distribution of topsoil and subsoil hydraulic properties and
                      horizon thickness. The prediction errors for the spatial
                      structure of soil hydraulic properties according to
                      Mualem/Van Genuchten and horizon thickness were quantified
                      by a cross validation procedure. We determined the
                      regression kriging model C as the most appropriate method
                      with, on average, the smallest prediction errors and because
                      the resulting spatial structure corresponds to recent models
                      of soil properties spatial structure. Compared to ordinary
                      kriging without covariables, the spatial prediction of soil
                      properties could be improved with up to $15\%$ by using
                      terrain attributes as co-variables. (c) 2005 Elsevier B.V.
                      All rights reserved.},
      keywords     = {J (WoSType)},
      cin          = {ICG-IV / JARA-ENERGY},
      ddc          = {550},
      cid          = {I:(DE-Juel1)VDB50 / $I:(DE-82)080011_20140620$},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      shelfmark    = {Soil Science},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000236740900017},
      doi          = {10.1016/j.geoderma.2005.05.008},
      url          = {https://juser.fz-juelich.de/record/50874},
}