Alkassem M. auteur aut IRD Buis S. auteur aut IRD Coulouma G. auteur aut IRD Jacob Frédéric auteur aut IRD Lagacherie P. auteur aut IRD Prevot L. auteur aut IRD text journalArticle eng text/pdf born digital access Soil available water capacity (SAWC) is a key factor to be considered when assessing soil capability to provide ecosystem services. The current study deepens the use of remotely sensed data for mapping SAWC and its components from crop model inversion. The inversion was conducted using the STICS (Simulateur mulTI-discplinaire pour les Cultures Standard) crop model along with the GLUE (Generalized Likelihood Uncertainty Estimation) algorithm on a panel of 14 sites within a rainfed vineyard catchment located in Southern France. Several constraint variables derived from Landsat 7 ETM + satellite imagery (leaf area index -LAI -and evapotranspiration -ET) or in-situ measurements (surface soil moisture -SSM), were used in the inversion process alone or in combination. Three main outcomes could be reported when comparing retrievals of both SAWC and its components against field estimates. First, retrievals were significantly correlated with ground estimates for some SAWC components and some scenarios of constraint variables, although overall retrieving performances were quite poor. Second, poor retrieving performances for two scenarios of constraint variables were related to few sites for which specific processes were disregarded by the modelling framework, namely allochthonous water supply and waterlogging during wet autumn and summer. Third, we could identify some promising combinations of constraint variables, after the removal of the aforementioned sites with specific processes. These promising combinations were (LAI, ET) and even more (LAI, ET, SSM) for estimating SAWC and root zone thickness, as well as SSM for estimating soil moistures at field capacity and wilting point of the topsoil layer. Provided we can avoid site-specific processes, our approach may further provide spatial sampling of SAWC and related components, to be used as surrogate input data for DSM models. specialized Digital soil mapping Remote sensing Crop model Inverse modelling Vineyard Soil available water capacity FRANCE ZONE MEDITERRANEENNE OCCITANIE 068 072 126 020 425 116081 [13 p.] 2022 0016-7061 https://www.documentation.ird.fr/hor/fdi:010086096 10.1016/j.geoderma.2022.116081 0016-7061 [F B010086096] https://www.documentation.ird.fr/hor/fdi:010086096 https://www.documentation.ird.fr/intranet/publi/2022-11/010086096.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2022-11-09 2025-02-24 fdi:010086096 fre