ORCHIDEE-STICS, a process-based model of sugarcane biomass production: calibration of model parameters governing phenology
Identifieur interne : 004040 ( Main/Exploration ); précédent : 004039; suivant : 004041ORCHIDEE-STICS, a process-based model of sugarcane biomass production: calibration of model parameters governing phenology
Auteurs : Aude Valade [France] ; Nicolas Vuichard [France] ; Philippe Ciais [France] ; Françoise Ruget [France] ; Nicolas Viovy [France] ; Benoît Gabrielle [France] ; Neil Huth [Australie] ; Jean-François Martine [Réunion]Source :
- Global change biology. Bioenergy [ 1757-1693 ] ; 2014.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Biomasse, Bioénergie, Canne à sucre.
English descriptors
- KwdEn :
Abstract
Agro-Land Surface Models (agro-LSM) combine detailed crop models and large-scale vegetation models (DGVMs) to model the spatial and temporal distribution of energy, water, and carbon fluxes within the soil-vegetation-atmosphere continuum worldwide. In this study, we identify and optimize parameters controlling leaf area index (LAI) in the agro-LSM ORCHIDEE-STICS developed for sugarcane. Using the Morris method to identify the key parameters impacting LAI, at eight different sugarcane field trial sites, in Australia and La Reunion island, we determined that the three most important parameters for simulating LAI are (i) the maximum predefined rate of LAI increase during the early crop development phase, a parameter that defines a plant density threshold below which individual plants do not compete for growing their LAI, and a parameter defining a threshold for nitrogen stress on LAI. A multisite calibration of these three parameters is performed using three different scoring functions. The impact of the choice of a particular scoring function on the optimized parameter values is investigated by testing scoring functions defined from the model-data RMSE, the figure of merit and a Bayesian quadratic model-data misfit function. The robustness of the calibration is evaluated for each of the three scoring functions with a systematic cross-validation method to find the most satisfactory one. Our results show that the figure of merit scoring function is the most robust metric for establishing the best parameter values controlling the LAI. The multisite average figure of merit scoring function is improved from 67% of agreement to 79%. The residual error in LAI simulation after the calibration is discussed.
Affiliations:
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type="wicri:Area/Main/Exploration">004040</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">ORCHIDEE-STICS, a process-based model of sugarcane biomass production: calibration of model parameters governing phenology</title><author><name sortKey="Valade, Aude" sort="Valade, Aude" uniqKey="Valade A" first="Aude" last="Valade">Aude Valade</name><affiliation wicri:level="3"><inist:fA14 i1="01"><s1>Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS</s1><s2>Gif-sur-Yvette, 91191</s2><s3>FRA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Vuichard, Nicolas" sort="Vuichard, Nicolas" uniqKey="Vuichard N" first="Nicolas" last="Vuichard">Nicolas Vuichard</name><affiliation wicri:level="3"><inist:fA14 i1="01"><s1>Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS</s1><s2>Gif-sur-Yvette, 91191</s2><s3>FRA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Ciais, Philippe" sort="Ciais, Philippe" uniqKey="Ciais P" first="Philippe" last="Ciais">Philippe Ciais</name><affiliation wicri:level="3"><inist:fA14 i1="01"><s1>Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS</s1><s2>Gif-sur-Yvette, 91191</s2><s3>FRA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Ruget, Francoise" sort="Ruget, Francoise" uniqKey="Ruget F" first="Françoise" last="Ruget">Françoise Ruget</name><affiliation wicri:level="3"><inist:fA14 i1="02"><s1>Modelling agricultural and hydrological systems in the Mediterranean environment Research Unit, INRA</s1><s2>Avignon, 84914</s2><s3>FRA</s3><sZ>4 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region" nuts="2">Provence-Alpes-Côte d'Azur</region></placeName></affiliation></author><author><name sortKey="Viovy, Nicolas" sort="Viovy, Nicolas" uniqKey="Viovy N" first="Nicolas" last="Viovy">Nicolas Viovy</name><affiliation wicri:level="3"><inist:fA14 i1="01"><s1>Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS</s1><s2>Gif-sur-Yvette, 91191</s2><s3>FRA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Gabrielle, Benoit" sort="Gabrielle, Benoit" uniqKey="Gabrielle B" first="Benoît" last="Gabrielle">Benoît Gabrielle</name><affiliation wicri:level="3"><inist:fA14 i1="03"><s1>AgroParisTech, INRA, Environment and Arable Crops Research Unit</s1><s2>Thiverval-Grignon, 78850</s2><s3>FRA</s3><sZ>6 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region" nuts="2">Île-de-France</region></placeName></affiliation></author><author><name sortKey="Huth, Neil" sort="Huth, Neil" uniqKey="Huth N" first="Neil" last="Huth">Neil Huth</name><affiliation wicri:level="1"><inist:fA14 i1="04"><s1>CSIRO Ecosystem Sciences, PO Box 102</s1><s2>Toowoomba, Qld, 4350</s2><s3>AUS</s3><sZ>7 aut.</sZ></inist:fA14><country>Australie</country><wicri:noRegion>Toowoomba, Qld, 4350</wicri:noRegion></affiliation></author><author><name sortKey="Martine, Jean Francois" sort="Martine, Jean Francois" uniqKey="Martine J" first="Jean-François" last="Martine">Jean-François Martine</name><affiliation wicri:level="1"><inist:fA14 i1="05"><s1>CIRAD, UR SCA</s1><s2>Saint-Denis, 97408</s2><s3>REU</s3><sZ>8 aut.</sZ></inist:fA14><country>Réunion</country><wicri:noRegion>Saint-Denis, 97408</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">Global change biology. Bioenergy</title><title level="j" type="abbreviated">Glob. chang. biol., Bioenerg.</title><idno type="ISSN">1757-1693</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Global change biology. Bioenergy</title><title level="j" type="abbreviated">Glob. chang. biol., Bioenerg.</title><idno type="ISSN">1757-1693</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Bioenergy</term><term>Biomass</term><term>Calibration</term><term>Cross validation</term><term>Leaf area index</term><term>Modeling</term><term>Phenology</term><term>Process-oriented model</term><term>Saccharum</term><term>Sensitivity analysis</term><term>Sugar cane</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Biomasse</term><term>Etalonnage</term><term>Modélisation</term><term>Phénologie</term><term>Validation croisée</term><term>Indice foliaire</term><term>Analyse sensibilité</term><term>Bioénergie</term><term>Saccharum</term><term>Canne à sucre</term><term>Modèle orienté processus</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Biomasse</term><term>Bioénergie</term><term>Canne à sucre</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Agro-Land Surface Models (agro-LSM) combine detailed crop models and large-scale vegetation models (DGVMs) to model the spatial and temporal distribution of energy, water, and carbon fluxes within the soil-vegetation-atmosphere continuum worldwide. In this study, we identify and optimize parameters controlling leaf area index (LAI) in the agro-LSM ORCHIDEE-STICS developed for sugarcane. Using the Morris method to identify the key parameters impacting LAI, at eight different sugarcane field trial sites, in Australia and La Reunion island, we determined that the three most important parameters for simulating LAI are (i) the maximum predefined rate of LAI increase during the early crop development phase, a parameter that defines a plant density threshold below which individual plants do not compete for growing their LAI, and a parameter defining a threshold for nitrogen stress on LAI. A multisite calibration of these three parameters is performed using three different scoring functions. The impact of the choice of a particular scoring function on the optimized parameter values is investigated by testing scoring functions defined from the model-data RMSE, the figure of merit and a Bayesian quadratic model-data misfit function. The robustness of the calibration is evaluated for each of the three scoring functions with a systematic cross-validation method to find the most satisfactory one. Our results show that the figure of merit scoring function is the most robust metric for establishing the best parameter values controlling the LAI. The multisite average figure of merit scoring function is improved from 67% of agreement to 79%. The residual error in LAI simulation after the calibration is discussed.</div></front></TEI><affiliations><list><country><li>Australie</li><li>France</li><li>Réunion</li></country><region><li>Provence-Alpes-Côte d'Azur</li><li>Île-de-France</li></region></list><tree><country name="France"><region name="Île-de-France"><name sortKey="Valade, Aude" sort="Valade, Aude" uniqKey="Valade A" first="Aude" last="Valade">Aude Valade</name></region><name sortKey="Ciais, Philippe" sort="Ciais, Philippe" uniqKey="Ciais P" first="Philippe" last="Ciais">Philippe Ciais</name><name sortKey="Gabrielle, Benoit" sort="Gabrielle, Benoit" uniqKey="Gabrielle B" first="Benoît" last="Gabrielle">Benoît Gabrielle</name><name sortKey="Ruget, Francoise" sort="Ruget, Francoise" uniqKey="Ruget F" first="Françoise" last="Ruget">Françoise Ruget</name><name sortKey="Viovy, Nicolas" sort="Viovy, Nicolas" uniqKey="Viovy N" first="Nicolas" last="Viovy">Nicolas Viovy</name><name sortKey="Vuichard, Nicolas" sort="Vuichard, Nicolas" uniqKey="Vuichard N" first="Nicolas" last="Vuichard">Nicolas Vuichard</name></country><country name="Australie"><noRegion><name sortKey="Huth, Neil" sort="Huth, Neil" uniqKey="Huth N" first="Neil" last="Huth">Neil Huth</name></noRegion></country><country name="Réunion"><noRegion><name sortKey="Martine, Jean Francois" sort="Martine, Jean Francois" uniqKey="Martine J" first="Jean-François" last="Martine">Jean-François Martine</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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