Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-573-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-573-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
28 Jan 2021
Development and technical paper |
| 28 Jan 2021
| 28 Jan 2021
Improving the representation of cropland sites in the Community Land Model (CLM) version 5.0
Institute of Bio- and Geosciences,
Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial
Systems, HPSC TerrSys, Geoverbund ABC/J, 52425 Jülich, Germany
Heye Bogena
Institute of Bio- and Geosciences,
Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial
Systems, HPSC TerrSys, Geoverbund ABC/J, 52425 Jülich, Germany
Thomas Grünwald
Institute of
Hydrology and Meteorology, Technische Universität Dresden (TU Dresden), 01062 Dresden, Germany
Bernard Heinesch
Gembloux Agro-Bio Tech (GxABT), University of Liège, 5030
Gembloux, Belgium
Dongryeol Ryu
Department of Infrastructure Engineering, University of Melbourne,
Parkville, VIC 3010, Australia
Marius Schmidt
Institute of Bio- and Geosciences,
Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, Germany
Harry Vereecken
Institute of Bio- and Geosciences,
Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial
Systems, HPSC TerrSys, Geoverbund ABC/J, 52425 Jülich, Germany
Andrew Western
Department of Infrastructure Engineering, University of Melbourne,
Parkville, VIC 3010, Australia
Harrie-Jan Hendricks Franssen
Institute of Bio- and Geosciences,
Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial
Systems, HPSC TerrSys, Geoverbund ABC/J, 52425 Jülich, Germany
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Cited
22 citations as recorded by crossref.
- Effects of Extreme Weather Events on Nitrous Oxide Emissions from Rice-Wheat Rotation Croplands Y. Xia et al. 10.3390/plants13010025
- Midwest US Croplands Determine Model Divergence in North American Carbon Fluxes W. Sun et al. 10.1029/2020AV000310
- Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes A. Tai et al. 10.5194/gmd-17-3733-2024
- Integrating partitioned evapotranspiration data into hydrologic models: Vegetation parameterization and uncertainty quantification of simulated plant water use A. Schreiner‐McGraw et al. 10.1002/hyp.14580
- Incorporating dynamic crop growth processes and management practices into a terrestrial biosphere model for simulating crop production in the United States: Toward a unified modeling framework Y. You et al. 10.1016/j.agrformet.2022.109144
- Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review K. Berger et al. 10.1016/j.rse.2022.113198
- Dynamic parameterization of soil surface characteristics for hydrological models in agricultural catchments T. Grangeon et al. 10.1016/j.catena.2022.106257
- Isolating the effects of land use land cover change and inter-decadal climate variations on the water and energy cycles over India, 1981–2010 N. Ghodichore et al. 10.1016/j.jhydrol.2022.128267
- CLM5-FruitTree: a new sub-model for deciduous fruit trees in the Community Land Model (CLM5) O. Dombrowski et al. 10.5194/gmd-15-5167-2022
- Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. 10.3389/frwa.2022.981745
- Modeling Perennial Bioenergy Crops in the E3SM Land Model (ELMv2) E. Sinha et al. 10.1029/2022MS003171
- Applications of land surface model to economic and environmental-friendly optimization of nitrogen fertilization and irrigation F. Wang et al. 10.1016/j.heliyon.2024.e27549
- The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2) E. Sinha et al. 10.1029/2022JG007187
- Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach T. Boas et al. 10.5194/hess-27-3143-2023
- Probabilistic crop type mapping for ex-ante modelling and spatial disaggregation J. Baumert et al. 10.1016/j.ecoinf.2024.102836
- Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data L. Strebel et al. 10.5194/hess-28-1001-2024
- Field-scale evaluation of a satellite-based terrestrial biosphere model for estimating crop response to management practices and productivity J. Wang et al. 10.1016/j.isprsjprs.2024.11.008
- Exploring the effects of extreme weather events on methane emissions from croplands: A study combining site and global modeling Y. Xia et al. 10.1016/j.agrformet.2023.109454
- Modeling gross primary production and transpiration from sun-induced chlorophyll fluorescence using a mechanistic light-response approach Q. Beauclaire et al. 10.1016/j.rse.2024.114150
- Point-scale multi-objective calibration of the Community Land Model (version 5.0) using in situ observations of water and energy fluxes and variables T. Denager et al. 10.5194/hess-27-2827-2023
- Comparison of Data Fusion Methods in Fusing Satellite Products and Model Simulations for Estimating Soil Moisture on Semi-Arid Grasslands Y. Zhu et al. 10.3390/rs15153789
- Can a Sparse Network of Cosmic Ray Neutron Sensors Improve Soil Moisture and Evapotranspiration Estimation at the Larger Catchment Scale? F. Li et al. 10.1029/2023WR035056
22 citations as recorded by crossref.
- Effects of Extreme Weather Events on Nitrous Oxide Emissions from Rice-Wheat Rotation Croplands Y. Xia et al. 10.3390/plants13010025
- Midwest US Croplands Determine Model Divergence in North American Carbon Fluxes W. Sun et al. 10.1029/2020AV000310
- Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes A. Tai et al. 10.5194/gmd-17-3733-2024
- Integrating partitioned evapotranspiration data into hydrologic models: Vegetation parameterization and uncertainty quantification of simulated plant water use A. Schreiner‐McGraw et al. 10.1002/hyp.14580
- Incorporating dynamic crop growth processes and management practices into a terrestrial biosphere model for simulating crop production in the United States: Toward a unified modeling framework Y. You et al. 10.1016/j.agrformet.2022.109144
- Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review K. Berger et al. 10.1016/j.rse.2022.113198
- Dynamic parameterization of soil surface characteristics for hydrological models in agricultural catchments T. Grangeon et al. 10.1016/j.catena.2022.106257
- Isolating the effects of land use land cover change and inter-decadal climate variations on the water and energy cycles over India, 1981–2010 N. Ghodichore et al. 10.1016/j.jhydrol.2022.128267
- CLM5-FruitTree: a new sub-model for deciduous fruit trees in the Community Land Model (CLM5) O. Dombrowski et al. 10.5194/gmd-15-5167-2022
- Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. 10.3389/frwa.2022.981745
- Modeling Perennial Bioenergy Crops in the E3SM Land Model (ELMv2) E. Sinha et al. 10.1029/2022MS003171
- Applications of land surface model to economic and environmental-friendly optimization of nitrogen fertilization and irrigation F. Wang et al. 10.1016/j.heliyon.2024.e27549
- The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2) E. Sinha et al. 10.1029/2022JG007187
- Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach T. Boas et al. 10.5194/hess-27-3143-2023
- Probabilistic crop type mapping for ex-ante modelling and spatial disaggregation J. Baumert et al. 10.1016/j.ecoinf.2024.102836
- Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data L. Strebel et al. 10.5194/hess-28-1001-2024
- Field-scale evaluation of a satellite-based terrestrial biosphere model for estimating crop response to management practices and productivity J. Wang et al. 10.1016/j.isprsjprs.2024.11.008
- Exploring the effects of extreme weather events on methane emissions from croplands: A study combining site and global modeling Y. Xia et al. 10.1016/j.agrformet.2023.109454
- Modeling gross primary production and transpiration from sun-induced chlorophyll fluorescence using a mechanistic light-response approach Q. Beauclaire et al. 10.1016/j.rse.2024.114150
- Point-scale multi-objective calibration of the Community Land Model (version 5.0) using in situ observations of water and energy fluxes and variables T. Denager et al. 10.5194/hess-27-2827-2023
- Comparison of Data Fusion Methods in Fusing Satellite Products and Model Simulations for Estimating Soil Moisture on Semi-Arid Grasslands Y. Zhu et al. 10.3390/rs15153789
- Can a Sparse Network of Cosmic Ray Neutron Sensors Improve Soil Moisture and Evapotranspiration Estimation at the Larger Catchment Scale? F. Li et al. 10.1029/2023WR035056
Latest update: 13 Dec 2024
Short summary
In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
In this study we were able to significantly improve CLM5 model performance for European cropland...
