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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
Sprache Englisch
ISSN 1991-959X
Digitales Dokument URL
Erschienen In: Geoscientific Model Development ; 8, no. 5 ; Nr. 8, no. 5 (2015-05-20), S.1461-1471
Datensatznummer 250116344
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/gmd-8-1461-2015.pdf
 
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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