ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe
The response of crops to changing climate and atmospheric CO<sub>2</sub> concentration ([CO<sub>2</sub>]) could have large effects on food production, and impact carbon, water, and energy fluxes, causing feedbacks to the climate. To simulate the response of temperate crops to...
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Copernicus Publications
2016-03-01
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Series: | Geoscientific Model Development |
Online Access: | http://www.geosci-model-dev.net/9/857/2016/gmd-9-857-2016.pdf |
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language |
English |
format |
Article |
sources |
DOAJ |
author |
X. Wu N. Vuichard P. Ciais N. Viovy N. de Noblet-Ducoudré X. Wang V. Magliulo M. Wattenbach L. Vitale P. Di Tommasi E. J. Moors W. Jans J. Elbers E. Ceschia T. Tallec C. Bernhofer T. Grünwald C. Moureaux T. Manise A. Ligne P. Cellier B. Loubet E. Larmanou D. Ripoche |
spellingShingle |
X. Wu N. Vuichard P. Ciais N. Viovy N. de Noblet-Ducoudré X. Wang V. Magliulo M. Wattenbach L. Vitale P. Di Tommasi E. J. Moors W. Jans J. Elbers E. Ceschia T. Tallec C. Bernhofer T. Grünwald C. Moureaux T. Manise A. Ligne P. Cellier B. Loubet E. Larmanou D. Ripoche ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe Geoscientific Model Development |
author_facet |
X. Wu N. Vuichard P. Ciais N. Viovy N. de Noblet-Ducoudré X. Wang V. Magliulo M. Wattenbach L. Vitale P. Di Tommasi E. J. Moors W. Jans J. Elbers E. Ceschia T. Tallec C. Bernhofer T. Grünwald C. Moureaux T. Manise A. Ligne P. Cellier B. Loubet E. Larmanou D. Ripoche |
author_sort |
X. Wu |
title |
ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe |
title_short |
ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe |
title_full |
ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe |
title_fullStr |
ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe |
title_full_unstemmed |
ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe |
title_sort |
orchidee-crop (v0), a new process-based agro-land surface model: model description and evaluation over europe |
publisher |
Copernicus Publications |
series |
Geoscientific Model Development |
issn |
1991-959X 1991-9603 |
publishDate |
2016-03-01 |
description |
The response of crops to changing climate and atmospheric CO<sub>2</sub>
concentration ([CO<sub>2</sub>]) could have large effects on food production, and
impact carbon, water, and energy fluxes, causing feedbacks to the climate. To
simulate the response of temperate crops to changing climate and [CO<sub>2</sub>],
which accounts for the specific phenology of crops mediated by management
practice, we describe 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 is tested here using 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 seven winter wheat and
maize sites in Europe. The specific ecosystem variables used in the
evaluation are CO<sub>2</sub> fluxes (net ecosystem exchange, NEE), latent heat,
and sensible heat fluxes. Additional measurements of leaf area index (LAI)
and
aboveground biomass and yield are used as well. Evaluation results revealed
that ORCHIDEE-CROP (v0) reproduced the observed timing of crop development
stages and the amplitude of the LAI changes. This is in contrast to
ORCHIDEEv196 where, by default, crops have the same phenology as grass. A
halving of the root mean square error for LAI from 2.38 ± 0.77 to
1.08 ± 0.34 m<sup>2</sup> m<sup>−2</sup> was obtained when ORCHIDEEv196 and
ORCHIDEE-CROP (v0) were compared across the seven study sites. Improved crop
phenology and carbon allocation led to a good match between modeled and
observed aboveground biomass (with a normalized root mean squared error
(NRMSE) of 11.0–54.2 %), crop yield, daily carbon and energy fluxes
(with a NRMSE of ∼ 9.0–20.1 and ∼ 9.4–22.3 % for NEE), and
sensible and latent heat fluxes. The simulated yields for winter wheat and
maize from ORCHIDEE-CROP (v0) showed a good match with the simulated results
from STICS for three sites with available crop yield observations, where the
average NRMSE was ∼ 8.8 %. The model data misfit for energy fluxes
were within the uncertainties of the measurements, which themselves showed an
incomplete energy balance closure within the range 80.6–86.3 %. The
remaining discrepancies between the modeled and observed LAI and other
variables at specific sites were partly attributable to unrealistic
representations of management events by the model. ORCHIDEE-CROP (v0) has the
ability to capture the spatial gradients of carbon and energy-related
variables, such as gross primary productivity, NEE, and sensible and latent
heat fluxes across the sites in Europe, which is an important requirement for
future spatially explicit simulations. Further improvement of the model, with
an explicit parameterization of nutritional dynamics and management, is
expected to improve its predictive ability to simulate croplands in an Earth system model. |
url |
http://www.geosci-model-dev.net/9/857/2016/gmd-9-857-2016.pdf |
work_keys_str_mv |
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doaj-5c10762de7834b279356f27b2aa3d1ab2020-11-24T23:23:07ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032016-03-019285787310.5194/gmd-9-857-2016ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over EuropeX. Wu0N. Vuichard1P. Ciais2N. Viovy3N. de Noblet-Ducoudré4X. Wang5V. Magliulo6M. Wattenbach7L. Vitale8P. Di Tommasi9E. J. Moors10W. Jans11J. Elbers12E. Ceschia13T. Tallec14C. Bernhofer15T. Grünwald16C. Moureaux17T. Manise18A. Ligne19P. Cellier20B. Loubet21E. Larmanou22D. Ripoche23CEA-CNRS-UVSQ, UMR8212-Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Orme des Merisiers, 91191 Gif-Sur-Yvette, FranceCEA-CNRS-UVSQ, UMR8212-Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Orme des Merisiers, 91191 Gif-Sur-Yvette, FranceCEA-CNRS-UVSQ, UMR8212-Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Orme des Merisiers, 91191 Gif-Sur-Yvette, FranceCEA-CNRS-UVSQ, UMR8212-Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Orme des Merisiers, 91191 Gif-Sur-Yvette, FranceCEA-CNRS-UVSQ, UMR8212-Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Orme des Merisiers, 91191 Gif-Sur-Yvette, FranceSino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaIstituto per i Sistemi Agricoli e Forestali del Mediterraneo, CNR, Via C. Patacca 85, 80056 Ercolano (Napoli), ItalyHelmholtz Centre Potsdam GFZ German Research Centre For Geosciences, Deutsches GeoForschungsZentrum GFZ, Telegrafenberg, 14473 Potsdam, GermanyIstituto per i Sistemi Agricoli e Forestali del Mediterraneo, CNR, Via C. Patacca 85, 80056 Ercolano (Napoli), ItalyIstituto per i Sistemi Agricoli e Forestali del Mediterraneo, CNR, Via C. Patacca 85, 80056 Ercolano (Napoli), ItalyWageningen UR, Alterra, Earth System Science and Climate Change Group, P.O. Box 47, 6700 AA Wageningen, the NetherlandsWageningen UR, Alterra, Earth System Science and Climate Change Group, P.O. Box 47, 6700 AA Wageningen, the NetherlandsWageningen UR, Alterra, Earth System Science and Climate Change Group, P.O. Box 47, 6700 AA Wageningen, the NetherlandsCESBIO, UMR5126 – CNES-CNRS-UPS-IRD – 18 avenue Edouard Belin 31401 Toulouse CEDEX 9, FranceCESBIO, UMR5126 – CNES-CNRS-UPS-IRD – 18 avenue Edouard Belin 31401 Toulouse CEDEX 9, FranceTechnische Universität Dresden, Institute of Hydrology and Meteorology, Pienner Str. 23, 01737 Tharandt, GermanyTechnische Universität Dresden, Institute of Hydrology and Meteorology, Pienner Str. 23, 01737 Tharandt, GermanyUniversité de Liège – Gembloux Agro-Bio Tech, Crops Management Unit, 5030 Gembloux, BelgiumUniversité de Liège – Gembloux Agro-Bio Tech, Crops Management Unit, 5030 Gembloux, BelgiumUniversité de Liège – Gembloux Agro-Bio Tech, Crops Management Unit, 5030 Gembloux, BelgiumINRA, UMR INRA-AgroParisTech ECOSYS (Ecologie fonctionnelle et écotoxicologie des agro-écosystèmes), 78850 Thiverval-Grignon, FranceINRA, UMR INRA-AgroParisTech ECOSYS (Ecologie fonctionnelle et écotoxicologie des agro-écosystèmes), 78850 Thiverval-Grignon, FranceINRA, UMR INRA-AgroParisTech ECOSYS (Ecologie fonctionnelle et écotoxicologie des agro-écosystèmes), 78850 Thiverval-Grignon, FranceINRA, US1116 AgroClim, Avignon, FranceThe response of crops to changing climate and atmospheric CO<sub>2</sub> concentration ([CO<sub>2</sub>]) could have large effects on food production, and impact carbon, water, and energy fluxes, causing feedbacks to the climate. To simulate the response of temperate crops to changing climate and [CO<sub>2</sub>], which accounts for the specific phenology of crops mediated by management practice, we describe 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 is tested here using 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 seven winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO<sub>2</sub> fluxes (net ecosystem exchange, NEE), latent heat, and sensible heat fluxes. Additional measurements of leaf area index (LAI) and aboveground biomass and yield are used as well. Evaluation results revealed that ORCHIDEE-CROP (v0) reproduced the observed timing of crop development stages and the amplitude of the LAI changes. This is in contrast to ORCHIDEEv196 where, by default, crops have the same phenology as grass. A halving of the root mean square error for LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m<sup>2</sup> m<sup>−2</sup> was obtained when ORCHIDEEv196 and ORCHIDEE-CROP (v0) were compared across the seven study sites. Improved crop phenology and carbon allocation led to a good match between modeled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, daily carbon and energy fluxes (with a NRMSE of ∼ 9.0–20.1 and ∼ 9.4–22.3 % for NEE), and sensible and latent heat fluxes. The simulated yields for winter wheat and maize from ORCHIDEE-CROP (v0) showed a good match with the simulated results from STICS for three sites with available crop yield observations, where the average NRMSE was ∼ 8.8 %. The model data misfit for energy fluxes were within the uncertainties of the measurements, which themselves showed an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between the modeled and observed LAI and other variables at specific sites were partly attributable to unrealistic representations of management events by the model. ORCHIDEE-CROP (v0) has the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, and sensible and latent heat fluxes across the sites in Europe, which is an important requirement for future spatially explicit simulations. Further improvement of the model, with an explicit parameterization of nutritional dynamics and management, is expected to improve its predictive ability to simulate croplands in an Earth system model.http://www.geosci-model-dev.net/9/857/2016/gmd-9-857-2016.pdf |