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@ARTICLE{Boas:891569,
      author       = {Boas, Theresa and Bogena, Heye and Grünwald, Thomas and
                      Heinesch, Bernard and Ryu, Dongryeol and Schmidt, Marius and
                      Vereecken, Harry and Western, Andrew and Hendricks-Franssen,
                      Harrie-Jan},
      title        = {{I}mproving the representation of cropland sites in the
                      {C}ommunity {L}and {M}odel ({CLM}) version 5.0},
      journal      = {Geoscientific model development},
      volume       = {14},
      number       = {1},
      issn         = {1991-9603},
      address      = {Katlenburg-Lindau},
      publisher    = {Copernicus},
      reportid     = {FZJ-2021-01594},
      pages        = {573 - 601},
      year         = {2021},
      abstract     = {The incorporation of a comprehensive crop module in land
                      surface models offers the possibility to study the effect of
                      agricultural land use and land management changes on the
                      terrestrial water, energy, and biogeochemical cycles. It may
                      help to improve the simulation of biogeophysical and
                      biogeochemical processes on regional and global scales in
                      the framework of climate and land use change. In this study,
                      the performance of the crop module of the Community Land
                      Model version 5 (CLM5) was evaluated at point scale with
                      site-specific field data focusing on the simulation of
                      seasonal and inter-annual variations in crop growth,
                      planting and harvesting cycles, and crop yields, as well as
                      water, energy, and carbon fluxes. In order to better
                      represent agricultural sites, the model was modified by (1)
                      implementing the winter wheat subroutines following Lu et
                      al. (2017) in CLM5; (2) implementing plant-specific
                      parameters for sugar beet, potatoes, and winter wheat,
                      thereby adding the two crop functional types (CFTs) for
                      sugar beet and potatoes to the list of actively managed
                      crops in CLM5; and (3) introducing a cover-cropping
                      subroutine that allows multiple crop types on the same
                      column within 1 year. The latter modification allows the
                      simulation of cropping during winter months before usual
                      cash crop planting begins in spring, which is an
                      agricultural management technique with a long history that
                      is regaining popularity as it reduces erosion and improves
                      soil health and carbon storage and is commonly used in the
                      regions evaluated in this study. We compared simulation
                      results with field data and found that both the new
                      crop-specific parameterization and the winter wheat
                      subroutines led to a significant simulation improvement in
                      terms of energy fluxes (root-mean-square error, RMSE,
                      reduction for latent and sensible heat by up to $57 \%$
                      and $59 \%,$ respectively), leaf area index (LAI), net
                      ecosystem exchange, and crop yield (up to $87 \%$
                      improvement in winter wheat yield prediction) compared with
                      default model results. The cover-cropping subroutine yielded
                      a substantial improvement in representation of field
                      conditions after harvest of the main cash crop (winter
                      season) in terms of LAI magnitudes, seasonal cycle of LAI,
                      and latent heat flux (reduction of wintertime RMSE for
                      latent heat flux by $42 \%).$ Our modifications
                      significantly improved model simulations and should
                      therefore be applied in future studies with CLM5 to improve
                      regional yield predictions and to better understand
                      large-scale impacts of agricultural management on carbon,
                      water, and energy fluxes.},
      cin          = {IBG-3 / JARA-HPC / NIC},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118 / $I:(DE-82)080012_20140620$ /
                      I:(DE-Juel1)NIC-20090406},
      pnm          = {217 - Für eine nachhaltige Bio-Ökonomie – von
                      Ressourcen zu Produkten (POF4-217) / Better predictions with
                      environmental simulation models: optimally integrating new
                      data sources $(jicg41_20190501)$ / High-resolution regional
                      reanalysis with TerrSysMP $(jibg36_20191101)$ / 2173 -
                      Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217)},
      pid          = {G:(DE-HGF)POF4-217 / $G:(DE-Juel1)jicg41_20190501$ /
                      $G:(DE-Juel1)jibg36_20191101$ / G:(DE-HGF)POF4-2173},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000614265500001},
      doi          = {10.5194/gmd-14-573-2021},
      url          = {https://juser.fz-juelich.de/record/891569},
}