Articles | Volume 21, issue 9
https://doi.org/10.5194/hess-21-4861-2017
https://doi.org/10.5194/hess-21-4861-2017
Research article
 | 
28 Sep 2017
Research article |  | 28 Sep 2017

Parameter optimisation for a better representation of drought by LSMs: inverse modelling vs. sequential data assimilation

Hélène Dewaele, Simon Munier, Clément Albergel, Carole Planque, Nabil Laanaia, Dominique Carrer, and Jean-Christophe Calvet

Data sets

LAI GEOV1 Copernicus http://land.copernicus.eu/global/

WFDEI atmospheric variables IIASA ftp://rfdata:forceDATA@ftp.iiasa.ac.at

annual statistical surveys over France Agreste http://agreste.agriculture.gouv.fr/

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Short summary
Soil maximum available water content (MaxAWC) is a key parameter in land surface models. Being difficult to measure, this parameter is usually unavailable. A 15-year time series of satellite-derived observations of leaf area index (LAI) is used to retrieve MaxAWC for rainfed straw cereals over France. Disaggregated LAI is sequentially assimilated into the ISBA LSM. MaxAWC is estimated minimising LAI analyses increments. Annual maximum LAI observations correlate with the MaxAWC estimates.