An assimilation algorithm of satellite-derived LST observations for the operational production of soil moisture maps

The knowledge of the soil moisture state in a region plays an important role in hydrology, with particular reference to the flood events prediction. A valid tool for the evaluation of the saturation state at watershed scale is given by remote sensing imagery. In this work temporal sequences of LST images from satellite platform (MSG-SEVIRI and Terra-MODIS) have been used in an assimilation procedure, ACHAB, in order to retrieve estimations of the land surface energy balance components and daily maps of soil moisture saturation index (SMSI). The simulation has been performed over the Italian territory for seven years (2005-2011) with about 5 km of spatial resolution. A climatology of the SMSI maps has been computed and reliability index maps have been provided. This study was realized in the framework of “OPERA - Protezione Civile dalle Alluvioni” ([1]), a project of the Italian Civil Protection aimed to the operational use of satellite data for floods prediction and management.