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@ARTICLE{Constantin:864925,
      author       = {Constantin, Julie and Raynal, Helene and Casellas, Eric and
                      Hoffmann, Holger and Bindi, Marco and Doro, Luca and
                      Eckersten, Henrik and Gaiser, Thomas and Grosz, Balász and
                      Haas, Edwin and Kersebaum, Kurt-Christian and Klatt, Steffen
                      and Kuhnert, Matthias and Lewan, Elisabet and Maharjan,
                      Ganga Ram and Moriondo, Marco and Nendel, Claas and Roggero,
                      Pier Paolo and Specka, Xenia and Trombi, Giacomo and Villa,
                      Ana and Wang, Enli and Weihermüller, Lutz and Yeluripati,
                      Jagadeesh and Zhao, Zhigan and Ewert, Frank and Bergez,
                      Jacques-Eric},
      title        = {{M}anagement and spatial resolution effects on yield and
                      water balance at regional scale in crop models},
      journal      = {Agricultural and forest meteorology},
      volume       = {275},
      issn         = {0168-1923},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2019-04528},
      pages        = {184 - 195},
      year         = {2019},
      abstract     = {Due to the more frequent use of crop models at regional and
                      national scale, the effects of spatial data input resolution
                      have gained increased attention. However, little is known
                      about the influence of variability in crop management on
                      model outputs. A constant and uniform crop management is
                      often considered over the simulated area and period. This
                      study determines the influence of crop management adapted to
                      climatic conditions and input data resolution on
                      regional-scale outputs of crop models. For this purpose,
                      winter wheat and maize were simulated over 30 years with
                      spatially and temporally uniform management or adaptive
                      management for North Rhine-Westphalia (˜34 083 km²),
                      Germany. Adaptive management to local climatic conditions
                      was used for 1) sowing date, 2) N fertilization dates, 3) N
                      amounts, and 4) crop cycle length. Therefore, the models
                      were applied with four different management sets for each
                      crop. Input data for climate, soil and management were
                      selected at five resolutions, from 1 × 1 km to
                      100 × 100 km grid size. Overall, 11 crop models were
                      used to predict regional mean crop yield, actual
                      evapotranspiration, and drainage. Adaptive management had
                      little effect $(<10\%$ difference) on the 30-year mean of
                      the three output variables for most models and did not
                      depend on soil, climate, and management resolution.
                      Nevertheless, the effect was substantial for certain models,
                      up to $31\%$ on yield, $27\%$ on evapotranspiration, and
                      $12\%$ on drainage compared to the uniform management
                      reference. In general, effects were stronger on yield than
                      on evapotranspiration and drainage, which had little
                      sensitivity to changes in management. Scaling effects were
                      generally lower than management effects on yield and
                      evapotranspiration as opposed to drainage. Despite this
                      trend, sensitivity to management and scaling varied greatly
                      among the models. At the annual scale, effects were stronger
                      in certain years, particularly the management effect on
                      yield. These results imply that depending on the model, the
                      representation of management should be carefully chosen,
                      particularly when simulating yields and for predictions on
                      annual scale.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255) / MACSUR - Modelling European Agriculture with
                      Climate Change for Food Security (2812-ERA-158)},
      pid          = {G:(DE-HGF)POF3-255 / G:(DE-BLE)2812-ERA-158},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000480376400016},
      doi          = {10.1016/j.agrformet.2019.05.013},
      url          = {https://juser.fz-juelich.de/record/864925},
}