Search

International audience; During the 1999/2000 agricultural seasons, an experiment was carried out on winter wheat fields in the semiarid Yaqui Valley (Northwest Mexico). This data set was used to calibrate the evolution of the leaf area index (LAI) simulated by STICS, which was found to be in excellent agreement with estimates obtained from field reflectance measurements. After calibration, STICS was able to simulate satisfactorily the seasonal levels and trends observed in net radiation, soil moisture and evapotranspiration, but the crop temperature was overestimated by about 2.5 °C. On a larger scale, STICS was run on 16 fields with contrasting management practices. The simulations indicate that yield predictability is significantly lower for later sowing dates, consistent with observations. The seasonal variations of field and satellite data (Landsat-ETM+, Terra-MODIS and VEGETATION) NDVI were very close. However, some difficulties were noted: saturation of NDVI at high LAI values and smoothed variability on a 1-km spatial scale, as well as the need for a sound methodology for processing satellite data.

The STICS simulation model was adapted for linseed. An original procedure was used. Firstly, options were selected from among the possibilities available in STICS to simulate the processes of crops. Secondly, the model was calibrated following six steps: 1. gathering of information, 2. the use of parameters from the literature or from other models, 3. the use of STICS parameters for other crops if there is an analogy with linseed, 4. the use of the experimental data to determine parameters which can be measured or calculated, 5. the use of the experimental data to determine parameters by testing a range of values, and 6. the checking of consistency between the parameters and their physical or biological meaning. After adaptation to linseed, the simulations of leaf area, biomass, water consumption, plant nitrogen content, seed number and seed yield were in good agreement with the measurements used for calibration. Thirdly, the results of calculations by STICS were compared with measurements not used for calibration. There was little difference between calculations and measurements of leaf area, biomass, plant nitrogen content and seed number, while seed yield was overestimated because of diseases and lodging, which are not taken into account by the model. However, the differences in seed yield between treatments were properly simulated. This work was a first step towards developing a model to improve linseed crop management. To this end, modifications are needed to account for all yield limitations.

International audience; The STICS crop model was recently coupled with radiative transfer (RT) models in the solar and microwave domains. This permits the simulation of the temporal variation of remotely-sensed data over wheat canopies. This paper presents the first results in assimilating remotely sensed data into STICS: comparing simulated and actual remotely-sensed data allows the recalibration of some STICS parameters so as to constrain the evolution of the simulated canopy variables. A sensitivity analysis of the coupled STICS+RT model was carried out to select the parameters of STICS with the largest influence on remotely-sensed observables and on some canopy variables (dry biomass and LAI), leading us to assess the parameters that should be recalibrated in the assimilation process, in order to adequately simulate the time course of the remotely-sensed data. In a second step, the benefits of assimilating optical data alone, radar data alone and both optical and radar data into STICS+RT were compared.; Assimilation de données de télédétection optique et radar dans le modèle STICS de culture de blé. Le modèle de culture STICS a été récemment couplé avec des modèles de transfert radiatif (RT) dans les domaines optique (du visible au moyen infrarouge) et radar. Ceci permet de simuler l'évolution temporelle de variables obtenues par télédétection au dessus d'un couvert de blé. Cet article présente les premiers résultats d'assimilation de données de télédétection dans le modèle STICS : la comparaison de données de télédétection modélisées aux données réelles permet de re-étalonner certains des paramètres de STICS, de manière à contraindre la simulation de l'évolution temporelle des variables du couvert. Une analyse de sensibilité du modèle couplé STICS+RT permet de sélectionner les paramètres de STICS ayant le plus d'effet sur les données de télédétection simulées, ainsi que sur certaines variables caractéristiques du couvert (indice foliaire et biomasse aérienne). On peut ainsi choisir les paramètres devant être ajustés dans la procédure d'assimilation, afin d'améliorer la simulation des données de télédétection. On compare ensuite les résultats obtenus en assimilant des données de télédétection optique, des données radar, et simultanément des données optiques et radar.