Horizon / Plein textes La base de ressources documentaires de l'IRD

IRD

Publications des scientifiques de l'IRD

Sreelash K., Buis S., Sekhar M., Ruiz Laurent, Tomer S. K., Guerif M. (2017). Estimation of available water capacity components of two-layered soils using crop model inversion : effect of crop type and water regime. Journal of Hydrology, 546, 166-178. ISSN 0022-1694

Accès réservé (Intranet IRD) Document en accès réservé (Intranet IRD)

Lien direct chez l'éditeur doi:10.1016/j.jhydrol.2016.12.049

Titre
Estimation of available water capacity components of two-layered soils using crop model inversion : effect of crop type and water regime
Année de publication2017
Type de documentArticle référencé dans le Web of Science WOS:000395607700016
AuteursSreelash K., Buis S., Sekhar M., Ruiz Laurent, Tomer S. K., Guerif M.
SourceJournal of Hydrology, 2017, 546, p. 166-178. ISSN 0022-1694
RésuméCharacterization of the soil water reservoir is critical for understanding the interactions between crops and their environment and the impacts of land use and environmental changes on the hydrology of agricultural catchments especially in tropical context. Recent studies have shown that inversion of crop models is a powerful tool for retrieving information on root zone properties. Increasing availability of remotely sensed soil and vegetation observations makes it well suited for large scale applications. The potential of this methodology has however never been properly evaluated on extensive experimental datasets and previous studies suggested that the quality of estimation of soil hydraulic properties may vary depending on agro-environmental situations. The objective of this study was to evaluate this approach on an extensive field experiment. The dataset covered four crops (sunflower, sorghum, turmeric, maize) grown on different soils and several years in South India. The components of AWC (available water capacity) namely soil water content at field capacity and wilting point, and soil depth of two layered soils were estimated by inversion of the crop model STICS with the GLUE (generalized likelihood uncertainty estimation) approach using observations of surface soil moisture (SSM; typically from 0 to 10 cm deep) and leaf area index (LAI), which are attainable from radar remote sensing in tropical regions with frequent cloudy conditions. The results showed that the quality of parameter estimation largely depends on the hydric regime and its interaction with crop type. A mean relative absolute error of 5% for field capacity of surface layer, 10% for field capacity of root zone, 15% for wilting point of surface layer and root zone, and 20% for soil depth can be obtained in favorable conditions. A few observations of SSM (during wet and dry soil moisture periods) and LAI (within water stress periods) were sufficient to significantly improve the estimation of AWC components. These results show the potential of crop model inversion for estimating the AWC components of two-layered soils and may guide the sampling of representative years and fields to use this technique for mapping soil properties that are relevant for distributed hydrological modelling.
Plan de classementPédologie [068] ; Hydrologie [062] ; Sciences fondamentales / Techniques d'analyse et de recherche [020]
Descr. géo.INDE
LocalisationFonds IRD [F B010069424]
Identifiant IRDfdi:010069424
Lien permanenthttp://www.documentation.ird.fr/hor/fdi:010069424

Export des données

Disponibilité des documents

Télechargment fichier PDF téléchargeable

Lien sur le Web lien chez l'éditeur

Accès réservé en accès réservé

HAL en libre accès sur HAL


Accès aux documents originaux :

Accès direct

Bureau du chercheur

Site de la documentation

Espace intranet IST (accès réservé)

Suivi des publications IRD (accès réservé)

Mentions légales

Services Horizon

Poser une question

Consulter l'aide en ligne

Déposer une publication (accès réservé)

S'abonner au flux RSS

Voir les tableaux chronologiques et thématiques

Centres de documentation

Bondy

Montpellier (centre IRD)

Montpellier (MSE)

Nouméa

Papeete

Niamey

Ouagadougou

Tunis

La Paz

Quito