Articles | Volume 16, issue 6
https://doi.org/10.5194/bg-16-1111-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-16-1111-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Mar 2019
Research article |
| 19 Mar 2019
| 19 Mar 2019
Source partitioning of H2O and CO2 fluxes based on high-frequency eddy covariance data: a comparison between study sites
Anne Klosterhalfen
CORRESPONDING AUTHOR
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
Alexander Graf
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
Nicolas Brüggemann
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
Clemens Drüe
Department of Environmental Meteorology, University of Trier, 54296
Trier, Germany
Odilia Esser
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
María P. González-Dugo
IFAPA – Consejería de Agricultura, Pesca y Desarrollo Rural,
Centro Alameda del Obispo, 14080 Córdoba, Spain
Günther Heinemann
Department of Environmental Meteorology, University of Trier, 54296
Trier, Germany
Cor M. J. Jacobs
Wageningen Environmental Research, Wageningen University and Research,
6708 PB Wageningen, the Netherlands
Matthias Mauder
Institute of Meteorology and Climate Research, IMK-IFU, Karlsruhe
Institute of Technology (KIT), 82467 Garmisch-Partenkirchen, Germany
Arnold F. Moene
Meteorology and Air Quality Group, Wageningen University and Research,
6708 PB Wageningen, the Netherlands
Patrizia Ney
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
Thomas Pütz
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
Corinna Rebmann
Department Computational Hydrosystems, Helmholtz Centre for
Environmental Research (UFZ), 04318 Leipzig, Germany
Mario Ramos Rodríguez
IFAPA – Consejería de Agricultura, Pesca y Desarrollo Rural,
Centro Alameda del Obispo, 14080 Córdoba, Spain
Todd M. Scanlon
Department of Environmental Sciences, University of Virginia,
Charlottesville, VA 22904, USA
Marius Schmidt
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
Rainer Steinbrecher
Institute of Meteorology and Climate Research, IMK-IFU, Karlsruhe
Institute of Technology (KIT), 82467 Garmisch-Partenkirchen, Germany
Christoph K. Thomas
Micrometeorology Group, University of Bayreuth, 95447 Bayreuth,
Germany
Veronika Valler
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
Matthias J. Zeeman
Institute of Meteorology and Climate Research, IMK-IFU, Karlsruhe
Institute of Technology (KIT), 82467 Garmisch-Partenkirchen, Germany
Harry Vereecken
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH,
52425 Jülich, Germany
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Cited
15 citations as recorded by crossref.
- Assessment of Different Water Use Efficiency Calculations for Dominant Forage Crops in the Great Lakes Basin K. De Haan et al. 10.3390/agriculture11080739
- Partitioning gross primary production of a boreal forest among species and strata: A multi-method approach A. Vernay et al. 10.1016/j.agrformet.2023.109857
- Correlation-based flux partitioning of water vapor and carbon dioxide fluxes: Method simplification and estimation of canopy water use efficiency T. Scanlon et al. 10.1016/j.agrformet.2019.107732
- Annual variations of T/ET in a semi-arid region: Implications of plant water use strategies R. Yuan et al. 10.1016/j.jhydrol.2021.126884
- Water vapor flux in tropical lowland rice D. Chatterjee et al. 10.1007/s10661-019-7709-4
- Use of thermal signal for the investigation of near-surface turbulence M. Zeeman 10.5194/amt-14-7475-2021
- Direct partitioning of eddy-covariance water and carbon dioxide fluxes into ground and plant components E. Zahn et al. 10.1016/j.agrformet.2021.108790
- A framework for constructing machine learning models with feature set optimisation for evapotranspiration partitioning A. Stapleton et al. 10.1016/j.acags.2022.100105
- Flux variance similarity-based partitioning of evapotranspiration over a rainfed alfalfa field using high frequency eddy covariance data P. Wagle et al. 10.1016/j.agrformet.2020.107907
- Seasonal dynamics of carbon dioxide and water fluxes in a rice-wheat rotation system in the Yangtze-Huaihe region of China C. Li et al. 10.1016/j.agwat.2022.107992
- Combining flux variance similarity partitioning with artificial neural networks to gap-fill measurements of net ecosystem production of a Pacific Northwest Douglas-fir stand S. Lee et al. 10.1016/j.agrformet.2021.108382
- Suitability of fibre-optic distributed temperature sensing for revealing mixing processes and higher-order moments at the forest–air interface O. Peltola et al. 10.5194/amt-14-2409-2021
- Surface-Energy-Balance Closure over Land: A Review M. Mauder et al. 10.1007/s10546-020-00529-6
- Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities P. Stoy et al. 10.5194/bg-16-3747-2019
- Forest floor fluxes drive differences in the carbon balance of contrasting boreal forest stands J. Chi et al. 10.1016/j.agrformet.2021.108454
15 citations as recorded by crossref.
- Assessment of Different Water Use Efficiency Calculations for Dominant Forage Crops in the Great Lakes Basin K. De Haan et al. 10.3390/agriculture11080739
- Partitioning gross primary production of a boreal forest among species and strata: A multi-method approach A. Vernay et al. 10.1016/j.agrformet.2023.109857
- Correlation-based flux partitioning of water vapor and carbon dioxide fluxes: Method simplification and estimation of canopy water use efficiency T. Scanlon et al. 10.1016/j.agrformet.2019.107732
- Annual variations of T/ET in a semi-arid region: Implications of plant water use strategies R. Yuan et al. 10.1016/j.jhydrol.2021.126884
- Water vapor flux in tropical lowland rice D. Chatterjee et al. 10.1007/s10661-019-7709-4
- Use of thermal signal for the investigation of near-surface turbulence M. Zeeman 10.5194/amt-14-7475-2021
- Direct partitioning of eddy-covariance water and carbon dioxide fluxes into ground and plant components E. Zahn et al. 10.1016/j.agrformet.2021.108790
- A framework for constructing machine learning models with feature set optimisation for evapotranspiration partitioning A. Stapleton et al. 10.1016/j.acags.2022.100105
- Flux variance similarity-based partitioning of evapotranspiration over a rainfed alfalfa field using high frequency eddy covariance data P. Wagle et al. 10.1016/j.agrformet.2020.107907
- Seasonal dynamics of carbon dioxide and water fluxes in a rice-wheat rotation system in the Yangtze-Huaihe region of China C. Li et al. 10.1016/j.agwat.2022.107992
- Combining flux variance similarity partitioning with artificial neural networks to gap-fill measurements of net ecosystem production of a Pacific Northwest Douglas-fir stand S. Lee et al. 10.1016/j.agrformet.2021.108382
- Suitability of fibre-optic distributed temperature sensing for revealing mixing processes and higher-order moments at the forest–air interface O. Peltola et al. 10.5194/amt-14-2409-2021
- Surface-Energy-Balance Closure over Land: A Review M. Mauder et al. 10.1007/s10546-020-00529-6
- Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities P. Stoy et al. 10.5194/bg-16-3747-2019
- Forest floor fluxes drive differences in the carbon balance of contrasting boreal forest stands J. Chi et al. 10.1016/j.agrformet.2021.108454
Latest update: 15 Apr 2024
Short summary
To obtain magnitudes of flux components of H2O and CO2 (e.g., transpiration, soil respiration), we applied source partitioning approaches after Scanlon and Kustas (2010) and after Thomas et al. (2008) to high-frequency eddy covariance measurements of 12 study sites covering various ecosystems (croplands, grasslands, and forests) in different climatic regions. We analyzed the interrelations among turbulence, site characteristics, and the performance of both partitioning methods.
To obtain magnitudes of flux components of H2O and CO2 (e.g., transpiration, soil respiration),...
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