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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/gmd-2020-241
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-241
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 11 Aug 2020

Submitted as: development and technical paper | 11 Aug 2020

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This preprint is currently under review for the journal GMD.

Improving the representation of cropland sites in the Community Land Model (CLM) version 5.0

Theresa Boas1,2, Heye Bogena1,2, Thomas Grünwald3, Bernard Heinesch4, Dongryeol Ryu5, Marius Schmidt1, Harry Vereecken1,2, Andrew Western5, and Harrie-Jan Hendricks-Franssen1,2 Theresa Boas et al.
  • 1Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
  • 2Centre for High-Performance Scientific Computing in Terrestrial Systems: HPSC TerrSys, Geoverbund ABC/J, 52425 Jülich, Germany
  • 3Technische Universität Dresden (TU Dresden): Institute of Hydrology and Meteorology, 01062 Dresden, Germany
  • 4University of Liège: Gembloux Agro-Bio Tech (GxABT), 5030 Gembloux, Belgium
  • 5University of Melbourne: Department of Infrastructure Engineering, Parkville VIC 3010, Australia

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 focussing 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 after Lu et al. (2017) in CLM5; (2) implementing plant specific parameters for sugar beet, potatoes and winter wheat, thereby adding these crop functional types (CFT) to the list of actively managed crops in CLM5; (3) introducing a cover cropping subroutine that allows multiple crop types on the same column within one year. The latter modification allows the simulation of cropping during winter months before usual cash crop planting begins in spring, which is a common agricultural management technique in humid and sub-humid regions. We compared simulation results with field data and found that both the parameterization of the CFTs, as well as the winter wheat subroutines, led to a significant simulation improvement in terms of energy fluxes, leaf area index (LAI), net ecosystem exchange (RMSE reduction for latent and sensible heat by up to 57 % and 59 % respectively) 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 curve and latent heat flux (reduction of winter time RMSE for latent heat flux by 42 %). We anticipate that our model modifications offer opportunities to improve yield predictions, to study the effects of large-scale cover cropping on energy fluxes, soil carbon and nitrogen pools, and soil water storage in future studies with CLM5.

Theresa Boas et al.

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Theresa Boas et al.

Model code and software

CLM_WW_CC Theresa Boas https://doi.org/10.5281/zenodo.3978092

Theresa Boas et al.

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Short summary
In this study we were able to significantly improve the CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameters for important cash crops and a cover cropping subroutine to its crop module. We anticipate that our findings and modifications can help to improve regional scale yield predictions, and offer the possibility to study the effects of large-scale cover cropping on energy fluxes, CN pools and the terrestrial water cycle.
In this study we were able to significantly improve the CLM5 model performance for European...
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