SVAT modeling over the Alpilles-ReSeDA experiment: comparing SVAT models over wheat fields

Abstract

Remote sensing is an interesting tool for monitoring crop production, energy exchanges and mass exchanges between the soil, the biosphere and the atmosphere. The aim of the Alpilles-ReSeDA program was the development of such techniques combining remote sensing data, and soil and vegetation process models. This article focuses on SVAT models (Soil-Vegetation-Atmosphere Transfer models) which may be used for monitoring energy and mass exchanges by using assimilation of remote sensing data procedures. As a first step, we decided to implement a model comparison experiment with the aim of analyzing the relationships between the models' complexity, validity and potential for assimilating remote sensing data. This experiment involved the definition of three comparison scenarios with different objectives: (i) test the models' capacity to accurately describe processes using input parameters as measured in the field; (ii) test the portability of the models by using a priori information on input parameters (such as pedotransfer functions), and (iii) test the robustness of the models by a calibration/validation procedure. These 3 scenarios took advantage of the experimental network that was implemented during the Alpilles experiment and which combined measurements on different fields that may be used for calibration of models and their validations on independent data sets. The results showed that the models' performances were close whatever their complexity. The simpler models were less sensitive to the specification of input parameters. Significant improvements in the models' results were achieved when calibrating the models in comparison with the first scenario. remote sensing / modeling /experiment / surface energy fluxes / comparison Résumé-Modélisation du transfert Sol-Végétation-Atmosphère sur l'expérimentation Alpilles-ReSeDA : comparaison des modèles TSVA sur champs de blé. Le programme Alpilles-ReSeDA a été mis en place pour développer des méthodes d'utilisation des données de télédétection en combinaison avec des modèles de fonctionnement du sol ou de la végétation, dans le but d'estimer ou de suivre la production des cultures ou leurs échanges de masse et d'énergie avec le sol et l'atmosphère. Parmi ces modèles, cet article se focalise sur les modèles de transfert Sol-Végétation-Atmosphère qui peuvent être utilisés pour suivre les échanges d'énergie et de masse au moyen de procédures d'assimilation des données de télédétection. Dans une première étape, nous avons mis en place une expérience de comparaison de plusieurs modèles, avec l'objectif d'analyser les relations entre la complexité des modèles, leur validité et leur utilisation potentielle pour assimiler des données de télédétection. Nous avons défini trois scénarios qui répondent à des objectifs différents : (i) tester la capacité des modèles à décrire les processus en utilisant les paramètres d'entrée des modèles tels qu'ils ont été mesurés dans les champs ; (ii) tester la portabilité des modèles en utilisant des informations a priori en entrée (comme des f...

Evaluation of land surface model simulations of evapotranspiration over a 12-year crop succession: impact of soil hydraulic and vegetation properties

“…However, the performances of such detailed models rely on accurate parametrization of root profile and soil vertical heterogeneity which may not be available at a large scale and could trigger larger uncertainties in ET than the parameters of the force-restore model (Olioso et al, 2002). Other sources of uncertainties in the model structure include inaccurate ET partitioning between the soil and the vegetation at low LAI which may require a double-source energy balance (Olioso et al, 2002), inaccurate representation of the resistance of a drying soil to water vapour diffusion which depends on both soil structure and texture (Kondo et al, 1990;Merlin et al, 2011) and shortcomings in the parametrization of water stress functions (Verhoef and Egea, 2014). Finally, this work highlights the prevailing role of the soil parameters in the simulation of ET dynamics over a multiyear crop succession.…”

“…For w fc two definitions were used. We estimated θ fc at h = −3.3 m, which corresponds to the agronomic definition (Olioso et al, 2002) and for a hydraulic conductivity of K = 0.1 mm day −1 which can be found in hydrological applications (Wetzel and Chang, 1987;Bonne et al, 1999). θ wp and θ fc estimates were averaged over the 0-1.2 m soil profile and their values are reported in Table 2. 2.…”

“…Z root-zone was approximated by the depth at which the soil moisture change in time vanished (Table 3). We assumed that at a given depth, the time variations in soil moisture due to the vertical diffusion and gravitational drainage were smaller than those generated by the plant water uptake (Olioso et al, 2002). This is a reasonable hypothesis for low hydraulic conductivity soil as the one under study.…”

“…Local site studies demonstrated that ISBA (Noilhan and Mahfouf, 1996) and ISBA-A-gs are able to correctly simulate the diurnal and seasonal time courses of energy fluxes and soil water content, over contrasted soil and vegetation types. More variable performances were obtained by Olioso et al (2002) over wheat fields with possible underestimation of ET.…”

“…Since LSMs were originally designed to be coupled with atmospheric or hydrological models over large areas, their parametrization is generally parsimonious and their spatial integration is generally based on coarse-resolution (∼ 1-10 km) maps of parameters. Surface parameters drive a large part of LSM uncertainties and explain most discrepancies between models (Chen et al, 1997;Gupta et al, 1999;Olioso et al, 2002;Boone et al, 2004). The representation of cropland and their temporal dynamics over a long period of time need to be improved in LSMs (Lafont et al, 2011;Bonan and Santanello, 2013).…”