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

ORCHIDEE - CROP (v0)، نموذج جديد لسطح الأراضي الزراعية قائم على العمليات: وصف النموذج وتقييمه في جميع أنحاء أوروبا
Authors: Nicolas Vuichard; Xiuchen Wu; Xiuchen Wu; Eddy Moors; P. Ciais; N. de Noblet-Ducoudré; Pierre Cellier; +18 Authors

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

Abstract

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.

Countries
France, Netherlands, France, France, France, Germany, France, France
Keywords

[ SDU.OCEAN ] Sciences of the Universe [physics]/Ocean, Atmosphere, [SDE] Environmental Sciences, Biomass (ecology), Atmospheric sciences, 550, [SDV]Life Sciences [q-bio], Climate Change and Variability Research, Plant Science, Eddy covariance, Precipitation, Crop, 551, 630, Klimaatverandering, Agricultural and Biological Sciences, Terrestrial ecosystem, Climate change, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, QE1-996.5, Global and Planetary Change, Geography, Ecology, Alterra - Klimaatverandering en adaptief land- en watermanagement, Life Sciences, Geology, [SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces, environment, [SDV] Life Sciences [q-bio], Phenology, [SDE]Environmental Sciences, Physical Sciences, Leaf area index, Global Vegetation Models, environment, Alterra - Climate change and adaptive land and water management, Climate Change and Adaptive Land and Water Management, Impacts of Elevated CO2 and Ozone on Plant Physiology, Climate Change, Climate model, Klimaatverandering en adaptief land- en watermanagement, Environmental science, Meteorology, [ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces, environment, Life Science, Crop yield, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, SDG 2 - Zero Hunger, Biology, Ecosystem, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, Global Forest Drought Response and Climate Change, FOS: Earth and related environmental sciences, Agronomy, Climate Resilience, Temperate climate, Klimaatbestendigheid, FOS: Biological sciences, Environmental Science, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, Climate Modeling

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
61
Top 10%
Top 10%
Top 10%
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