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@ARTICLE{Groh:907763,
      author       = {Groh, Jannis and Diamantopoulos, Efstathios and Duan,
                      Xiaohong and Ewert, Frank and Heinlein, Florian and Herbst,
                      Michael and Holbak, Maja and Kamali, Bahareh and Kersebaum,
                      Kurt-Christian and Kuhnert, Matthias and Nendel, Claas and
                      Priesack, Eckart and Steidl, Jörg and Sommer, Michael and
                      Pütz, Thomas and Vanderborght, Jan and Vereecken, Harry and
                      Wallor, Evelyn and Weber, Tobias K. D. and Wegehenkel,
                      Martin and Weihermüller, Lutz and Gerke, Horst H.},
      title        = {{S}ame soil, different climate: {C}rop model
                      intercomparison on translocated lysimeters},
      journal      = {Vadose zone journal},
      volume       = {21},
      number       = {4},
      issn         = {1539-1663},
      address      = {Hoboken, NJ},
      publisher    = {Wiley},
      reportid     = {FZJ-2022-02196},
      pages        = {e20202},
      year         = {2022},
      abstract     = {Crop model intercomparison studies have mostly focused on
                      the assessment of predictive capabilities for crop
                      development using weather and basic soil data from the same
                      location. Still challenging is the model performance when
                      considering complex interrelations between soil and crop
                      dynamics under a changing climate. The objective of this
                      study was to test the agronomic crop and environmental
                      flux-related performance of a set of crop models. The aim
                      was to predict weighing lysimeter-based crop (i.e.,
                      agronomic) and water-related flux or state data (i.e.,
                      environmental) obtained for the same soil monoliths that
                      were taken from their original environment and translocated
                      to regions with different climatic conditions, after model
                      calibration at the original site. Eleven models were
                      deployed in the study. The lysimeter data (2014–2018) were
                      from the Dedelow (Dd), Bad Lauchstädt (BL), and Selhausen
                      (Se) sites of the TERENO (TERrestrial ENvironmental
                      Observatories) SOILCan network. Soil monoliths from Dd were
                      transferred to the drier and warmer BL site and the wetter
                      and warmer Se site, which allowed a comparison of similar
                      soil and crop under varying climatic conditions. The model
                      parameters were calibrated using an identical set of crop-
                      and soil-related data from Dd. Environmental fluxes and crop
                      growth of Dd soil were predicted for conditions at BL and Se
                      sites using the calibrated models. The comparison of
                      predicted and measured data of Dd lysimeters at BL and Se
                      revealed differences among models. At site BL, the crop
                      models predicted agronomic and environmental components
                      similarly well. Model performance values indicate that the
                      environmental components at site Se were better predicted
                      than agronomic ones. The multi-model mean was for most
                      observations the better predictor compared with those of
                      individual models. For Se site conditions, crop models
                      failed to predict site-specific crop development indicating
                      that climatic conditions (i.e., heat stress) were outside
                      the range of variation in the data sets considered for model
                      calibration. For improving predictive ability of crop models
                      (i.e., productivity and fluxes), more attention should be
                      paid to soil-related data (i.e., water fluxes and system
                      states) when simulating soil–crop–climate interrelations
                      in changing climatic conditions.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217) / DFG project 460817082 - REWET - Vorhersage,
                      Herkunft und Validierung von Tau, Raureif, Nebel und die
                      Adsorption von Wasserdampf im Boden in landwirtschaftlichen
                      Ökosystemen mithilfe eines Energiebilanzmodells, stabilen
                      Isotopen des Wassers und Lysimeterdaten},
      pid          = {G:(DE-HGF)POF4-2173 / G:(GEPRIS)460817082},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000795930100001},
      doi          = {10.1002/vzj2.20202},
      url          = {https://juser.fz-juelich.de/record/907763},
}