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@PHDTHESIS{Brogi:888221,
      author       = {Brogi, Cosimo},
      title        = {{G}eophysics-based soil mapping for improved modelling of
                      spatial variability in crop growth and yield},
      volume       = {518},
      school       = {Universität Stuttgart},
      type         = {Dissertation},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2020-04774},
      isbn         = {978-3-95806-510-9},
      series       = {Schriften des Forschungszentrums Jülich. Reihe Energie
                      $\&$ Umwelt / Energy $\&$ Environment},
      pages        = {xxi, 127 S.},
      year         = {2020},
      note         = {Universität Stuttgart, Diss., 2019},
      abstract     = {Water shortage is one of the predominant factors that can
                      directly or indirectly cause a reduction in crop yield and
                      thus poses a severe threat to sustainable crop production.
                      It is therefore critical to improve the sustainability of
                      current agricultural management practices and develop new
                      strategies that will allow the establishment of more
                      sustainable agricultural production systems that can meet
                      present and future food demand. The use of agro-ecosystem
                      models to simulate crop growth for given environmental
                      conditions, and the use of detailed information on soil
                      heterogeneity beyond the field scale are among the most
                      promising tools for achieving this goal. Soil properties are
                      a key control for water and nutrient availability and are
                      therefore co-responsible for yield gaps and harvest
                      failures. A detailed representation of the spatial
                      variability of soil is consequently essential for
                      establishing relevant spatially distributed agro-ecosystem
                      simulations of crop performance in response to water stress.
                      Unfortunately, a detailed soil representation is costly to
                      obtain, and generally cannot be substituted by the use of
                      existing general-purpose soil maps that lack the necessary
                      level of detail. Recently, improvements in digital soil
                      mapping have been made using non-invasive geophysical
                      methods such as electromagnetic induction (EMI) that provide
                      fast and costeffective mapping of relevant soil information.
                      It is however still challenging to derive information
                      relevant for agricultural management from large geophysical
                      datasets and their added value for agricultural applications
                      has not been fully investigated yet, especially for the
                      analysis of patterns in crop performance. This thesis aims
                      at investigating and quantifying the added value of detailed
                      soil information obtained using large-scale geophysical
                      mapping for the simulation and prediction of the spatial
                      variability of crop growth and yield obtained with
                      agro-ecosystem modelling. [...]},
      cin          = {IBG-3},
      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)3 / PUB:(DE-HGF)11},
      url          = {https://juser.fz-juelich.de/record/888221},
}