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, Contribuer à l'amélioration de la gestion de l'azote des systèmes

, Deux types d'expérimentation complémentaires ont été mises en place pour tester la faisabilité et la performance d'une modélisation déterministe : 1) un réseau de parcelles agricoles AB sélectionnées par le projet Agri-Bio « de la connaissance à la performance

, Structuration et co-financement

, Ces volets sont indépendants sur le plan de l'expérimentation et complémentaires sur le plan de la modélisation, Le projet est structuré en 3 volets pilotés par AgroImpact

A. De and L. Rakotovololona, Quantification expérimentale et modélisation de la production, du bilan d'azote et des flux de nitrate en systèmes de grandes cultures biologiques

R. Partenariat-d&apos;agrotransfert, . Hauts-de-france, G. Abp, and . Co-financements,

B. De-bénédicte and A. , Quantification et modélisation des flux de C et N de systèmes de culture alternatifs, en situation expérimentale de longue durée, Collaborations : INRA Grignon, FIBL (Suisse) et Université Aarhus (Danemark), équipe STICS

. Co-financements,

C. Inra, É. Métis, and . Stics, C-Adaptation du modèle STICS aux situations AB. Calibration et test du modèle pour des espèces (ou variétés) et produits résiduaires organiques utilisés en AB. Collaborations : Arvalis, ITAB

. Co-financements, PIREN Seine et AESN. Annexes, vol.174

, Annexes méthodologiques

I. A. Annexe, Description des prélèvements réalisés au cours des différentes étapes du suivi

I. B. Annexe, Présentation du modèle de calcul LIXIM, 2006.

, D'après la notice d'utilisation du modèle LIXIM

, Le programme LIXIM simule l'évolution de l'humidité du sol et de la quantité de nitrate dans un profil de sol, dans le cas d'un sol nu. Il calcule le drainage et le lessivage sous la dernière couche de sol et l'évaporation en surface

. Le-modèle-de-transport-est-un-modèle-réservoir-multicouches-;-van-ploeg, Les couches élémentaires considérées dans le calcul ont une épaisseur fixe, à définir : elle devrait être égale à 2 fois la longueur de dispersivité, 1995.

, Compte tenu de cette résolution, le déplacement du nitrate est décrit par une loi de type chromatographique

D. Le-transfert, eau et de soluté entre couches est décrit selon l'algorithme de I, Burns, 1976.

L. Le, nitrate se déplaçant de la couche i-1 à la couche i sont supposés se mélanger d'une manière homogène dans la couche i. Si la teneur en eau de la couche i excède l'humidité à la capacité au champ (Hcc), l'eau excédentaire passe dans la couche i+1 immédiatement inférieure

, Le modèle ne prend donc pas en compte les mouvements de nitrate par diffusion, mais seulement les mouvements convectifs. Ce modèle fonctionne principalement en régime d'infiltration

, Il inclut cependant un calcul simplifié en régime d'évaporation. L'évaporation de l'eau concerne plusieurs couches, dont l'épaisseur totale z (cm) est à définir par l'utilisateur. Il peut s'agir de la couche labourée uniquement (si le sol présente une faible conductivité hydraulique) ou de tout le profil

, En fait, il effectue les calculs à partir des stocks de nitrate : le modèle calcule en réalité la vitesse de nitrification (Vn). La vitesse de minéralisation (Vm) est ensuite calculée de la façon suivante

, ?A étant la variation du stock d'azote ammoniacal de la première couche de sol sur l'intervalle de temps ?t, On peut distinguer 2 cas : Annexes, p.177

, On a alors Vm ~ Vn. Il est inutile d'entrer les mesures de quantités de NH4 + . ? les variations du pool d'azote ammoniacal sont fortes. Il faut alors entrer les stocks de NH4 + et le modèle calcule la vitesse de minéralisation d, ? les variations du pool d'azote ammoniacal sont très faibles

, La minéralisation peut être décrite de 2 façons : ? la vitesse de minéralisation (Vm) est supposée constante au cours du temps ? la vitesse de minéralisation (Vm) varie au cours du temps. Elle est supposée égale à une vitesse potentielle (Vp), correspondant à une température de référence à définir et une humidité optimale pour la minéralisation, qui est égale à Hcc, multipliée par un facteur température et un facteur humidité

, La vitesse de minéralisation réelle (1er cas) ou potentielle (2ème cas) est supposée constante sur chaque intervalle de temps (entre 2 dates de mesure ou de simulation)

, Attention : Vm représente la vitesse réelle de minéralisation, alors que Vp représente la vitesse potentielle de nitrification

. Le,

, Le rapport k=ETR/ETP qui représente la fraction de l'évapotranspiration potentielle qui

, La vitesse de minéralisation réelle (Vm) ou potentielle (Vp)

, La vitesse de dénitrification (Vd) ou d'absorption (dans le cas où il y a une plante

, Chacun de ces 3 paramètres peut être soit imposé (simulation pure), soit calculé par ajustement non linéaire dans le cas où l'on dispose de mesures réalisées à différentes dates (option ajustement)

C. Dans-le, On impose alors l'absorption journalière calculée pour chaque intervalle de temps via le paramètre Vd (kg N/ha/jour). L'absorption est calculée par le modèle sur tout le profil de sol. Elle est supposée varier en fonction de la quantité d'azote disponible et décroît linéairement en fonction de la profondeur, jusqu'à la profondeur maximale atteinte par les racines, il est possible d'en tenir compte, vol.178

I. C. Annexe and . Beaudoin, Présentation du modèle sol-plante STICS, STICS : un modèle générique et robuste de réponse des agrosystèmes aux facteurs techno-pédo-climatiques, 2015.

N. Beaudoin, S. Buis, D. Ripoche, E. Justes, P. Bertuzzi et al.,

. Brisson, Il simule d'une façon fonctionnelle la production et les impacts environnementaux des systèmes de culture, intégrant une ou deux cultures associées ou plusieurs cultures successives. Il a été conçu comme opérationnel, générique et robuste pour différentes pédo-techno-climat, Les entrées sont les variables de forçage climatiques, les caractéristiques du sol, les pratiques culturales et les valeurs initiales du système (eau, 1996.

, entre lesquelles varient les valeurs de paramètres et/ou l'activation d'options de formalisme

. Coucheney, le drainage et l'évapotranspiration et les émissions de CO2, N2O, NO3 et NH3. L'état du système porte sur le développement des cultures et la température, les teneurs en eau et azote du sol. Parmi elles, les variables observées permettent de tester les prédictions du modèle. Ainsi, les performances du modèle (version 8.2) ont été évaluées sur une grande base de données couvrant 15 cultures et un large éventail de conditions en France (76 sites), représentant 1 809 unités de simulation, Les prédictions portent sur l'état des compartiments et les sorties du système sol-culture atmosphère. Les flux d'intérêt sont l'énergie solaire interceptée, la biomasse produite et le rendement (quantité, qualité), 2015.

L. and L. Diagnostic, l'étude cognitive et la synthèse des connaissances ; il est utilisé seul (interface Java) ou intégré en plate-forme de modélisation. Les résultats ci-dessus justifient l'usage en pronostic, i.e. l'étude des effets d'un changement advenant dans un écosystème donné, Le diagnostic fournit des variables d'intérêt pour une situation réelle dont les entrées de STICS Annexes, p.179

, Lors d'un diagnostic à l'échelle régionale, l'assimilation des données de télédétection sur l'état du couvert permet d'améliorer les prédictions. L'étude cognitive consiste à tester des hypothèses sur le fonctionnement d'un système dont certaines variables d'état sont connues, en jouant sur la valeur de paramètres ou la présence de formalismes. Enfin, la construction collective de STICS en fait un remarquable outil de synthèse de connaissances interdisciplinaires

, Un nouveau challenge consiste à en faire un outil d'évaluation de la durabilité et de test d'hypothèses sur le fonctionnement agro-écologique des systèmes de culture, STICS sert à relever des défis propres aux systèmes de cultures