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Titel |
ORCHIDEE-SRC v1.0: an extension of the land surface model ORCHIDEE for simulating short rotation coppice poplar plantations |
VerfasserIn |
T. Groote, D. Zona, L. S. Broeckx, M. S. Verlinden, S. Luyssaert, V. Bellassen, N. Vuichard, R. Ceulemans, A. Gobin, I. A. Janssens |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1991-959X
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Digitales Dokument |
URL |
Erschienen |
In: Geoscientific Model Development ; 8, no. 5 ; Nr. 8, no. 5 (2015-05-20), S.1461-1471 |
Datensatznummer |
250116344
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Publikation (Nr.) |
copernicus.org/gmd-8-1461-2015.pdf |
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Zusammenfassung |
Modelling biomass production and the environmental impact of short rotation
coppice (SRC) plantations is necessary for planning their deployment, as they
are becoming increasingly important for global energy production. This paper
describes the modification of the widely used land surface model ORCHIDEE for
stand-scale simulations of SRC plantations.
The model uses weather data, soil texture and species-specific parameters to
predict the aboveground (harvestable) biomass production, as well as carbon
and energy fluxes of an SRC plantation. Modifications to the model were made
to the management, growth, and allocation modules of ORCHIDEE.
The modifications presented in this paper were evaluated using data from two
Belgian poplar-based SRC sites, for which multiple measurements and
meteorological data were available. Biomass yield data were collected from
23 other sites across Europe and compared to 22 simulations across a
comparable geographic range. The simulations show that the model predicts
very well aboveground (harvestable) biomass production (within
measured ranges), ecosystem photosynthesis (R2 = 0.78,
NRMSE = 0.064, PCC = 0.89) and ecosystem respiration
(R2 = 0.95, NRMSE = 0.078 PCC = 0.91). Also soil temperature
and soil moisture are simulated adequately, but due to the simplicity of the
soil moisture simulation, there are some discrepancies, which also influence
the simulation of the latent heat flux.
Overall, the extended model, ORCHIDEE-SRC, proved to be a tool suitable for
predicting biomass production of SRC plantations. |
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