ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe

ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe. Wu, X., Vuichard, N., Ciais, P., Viovy, N., de Noblet-Ducoudré, N., Wang, X., Magliulo, V., Wattenbach, M., Vitale, L., Di Tommasi, P., Moors, E., J., Jans, W., Elbers, J., Ceschia, E., Tallec, T., Bernhofer, C., Grünwald, T., Moureaux, C., Manise, T., Ligne, A., Cellier, P., Loubet, B., Larmanou, E., & Ripoche, D. Geoscientific Model Development, 8(6):4653-4696, 2016.

Website doi abstract bibtex

The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.

@article{
 title = {ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe},
 type = {article},
 year = {2016},
 pages = {4653-4696},
 volume = {8},
 websites = {http://www.geosci-model-dev-discuss.net/8/4653/2015/},
 id = {7869d4ec-06cb-32ba-95c8-fab1b0367aea},
 created = {2016-06-23T09:38:45.000Z},
 file_attached = {false},
 profile_id = {5c1040db-25e3-36ea-a919-0994a44709e7},
 group_id = {c4af41cc-7e3c-3fd3-9982-bdb923596eee},
 last_modified = {2021-02-05T10:33:17.539Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wu2015},
 private_publication = {false},
 abstract = {The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.},
 bibtype = {article},
 author = {Wu, X. and Vuichard, N. and Ciais, P. and Viovy, N. and de Noblet-Ducoudré, N. and Wang, X. and Magliulo, V. and Wattenbach, M. and Vitale, L. and Di Tommasi, P. and Moors, E. J. and Jans, W. and Elbers, J. and Ceschia, Eric and Tallec, T. and Bernhofer, C. and Grünwald, T. and Moureaux, C. and Manise, T. and Ligne, A. and Cellier, P. and Loubet, Benjamin and Larmanou, E. and Ripoche, D.},
 doi = {10.5194/gmdd-8-4653-2015},
 journal = {Geoscientific Model Development},
 number = {6},
 keywords = {FR_AUR,FR_GRI,FR_LAM}
}

Downloads: 0

{"_id":"S7kN9K6j6m4BYJr23","bibbaseid":"wu-vuichard-ciais-viovy-denobletducoudr-wang-magliulo-wattenbach-etal-orchideecropv0anewprocessbasedagrolandsurfacemodelmodeldescriptionandevaluationovereurope-2016","downloads":0,"creationDate":"2016-07-05T13:20:36.311Z","title":"ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe","author_short":["Wu, X.","Vuichard, N.","Ciais, P.","Viovy, N.","de Noblet-Ducoudré, N.","Wang, X.","Magliulo, V.","Wattenbach, M.","Vitale, L.","Di Tommasi, P.","Moors, E., J.","Jans, W.","Elbers, J.","Ceschia, E.","Tallec, T.","Bernhofer, C.","Grünwald, T.","Moureaux, C.","Manise, T.","Ligne, A.","Cellier, P.","Loubet, B.","Larmanou, E.","Ripoche, D."],"year":2016,"bibtype":"article","biburl":"https://bibbase.org/service/mendeley/5c1040db-25e3-36ea-a919-0994a44709e7","bibdata":{"title":"ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe","type":"article","year":"2016","pages":"4653-4696","volume":"8","websites":"http://www.geosci-model-dev-discuss.net/8/4653/2015/","id":"7869d4ec-06cb-32ba-95c8-fab1b0367aea","created":"2016-06-23T09:38:45.000Z","file_attached":false,"profile_id":"5c1040db-25e3-36ea-a919-0994a44709e7","group_id":"c4af41cc-7e3c-3fd3-9982-bdb923596eee","last_modified":"2021-02-05T10:33:17.539Z","read":false,"starred":false,"authored":false,"confirmed":"true","hidden":false,"citation_key":"Wu2015","private_publication":false,"abstract":"The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.","bibtype":"article","author":"Wu, X. and Vuichard, N. and Ciais, P. and Viovy, N. and de Noblet-Ducoudré, N. and Wang, X. and Magliulo, V. and Wattenbach, M. and Vitale, L. and Di Tommasi, P. and Moors, E. J. and Jans, W. and Elbers, J. and Ceschia, Eric and Tallec, T. and Bernhofer, C. and Grünwald, T. and Moureaux, C. and Manise, T. and Ligne, A. and Cellier, P. and Loubet, Benjamin and Larmanou, E. and Ripoche, D.","doi":"10.5194/gmdd-8-4653-2015","journal":"Geoscientific Model Development","number":"6","keywords":"FR_AUR,FR_GRI,FR_LAM","bibtex":"@article{\n title = {ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe},\n type = {article},\n year = {2016},\n pages = {4653-4696},\n volume = {8},\n websites = {http://www.geosci-model-dev-discuss.net/8/4653/2015/},\n id = {7869d4ec-06cb-32ba-95c8-fab1b0367aea},\n created = {2016-06-23T09:38:45.000Z},\n file_attached = {false},\n profile_id = {5c1040db-25e3-36ea-a919-0994a44709e7},\n group_id = {c4af41cc-7e3c-3fd3-9982-bdb923596eee},\n last_modified = {2021-02-05T10:33:17.539Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Wu2015},\n private_publication = {false},\n abstract = {The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.},\n bibtype = {article},\n author = {Wu, X. and Vuichard, N. and Ciais, P. and Viovy, N. and de Noblet-Ducoudré, N. and Wang, X. and Magliulo, V. and Wattenbach, M. and Vitale, L. and Di Tommasi, P. and Moors, E. J. and Jans, W. and Elbers, J. and Ceschia, Eric and Tallec, T. and Bernhofer, C. and Grünwald, T. and Moureaux, C. and Manise, T. and Ligne, A. and Cellier, P. and Loubet, Benjamin and Larmanou, E. and Ripoche, D.},\n doi = {10.5194/gmdd-8-4653-2015},\n journal = {Geoscientific Model Development},\n number = {6},\n keywords = {FR_AUR,FR_GRI,FR_LAM}\n}","author_short":["Wu, X.","Vuichard, N.","Ciais, P.","Viovy, N.","de Noblet-Ducoudré, N.","Wang, X.","Magliulo, V.","Wattenbach, M.","Vitale, L.","Di Tommasi, P.","Moors, E., J.","Jans, W.","Elbers, J.","Ceschia, E.","Tallec, T.","Bernhofer, C.","Grünwald, T.","Moureaux, C.","Manise, T.","Ligne, A.","Cellier, P.","Loubet, B.","Larmanou, E.","Ripoche, D."],"urls":{"Website":"http://www.geosci-model-dev-discuss.net/8/4653/2015/"},"biburl":"https://bibbase.org/service/mendeley/5c1040db-25e3-36ea-a919-0994a44709e7","bibbaseid":"wu-vuichard-ciais-viovy-denobletducoudr-wang-magliulo-wattenbach-etal-orchideecropv0anewprocessbasedagrolandsurfacemodelmodeldescriptionandevaluationovereurope-2016","role":"author","keyword":["FR_AUR","FR_GRI","FR_LAM"],"metadata":{"authorlinks":{}},"downloads":0},"search_terms":["orchidee","crop","new","process","based","agro","land","surface","model","model","description","evaluation","over","europe","wu","vuichard","ciais","viovy","de noblet-ducoudré","wang","magliulo","wattenbach","vitale","di tommasi","moors","jans","elbers","ceschia","tallec","bernhofer","grünwald","moureaux","manise","ligne","cellier","loubet","larmanou","ripoche"],"keywords":["fr_aur","fr_gri","fr_lam"],"authorIDs":[],"dataSources":["LRSiZxnRXfxznxXRS","ya2CyA73rpZseyrZ8","2252seNhipfTmjEBQ"]}