Soil moisture plays a key role in the terrestrial water cycle and is responsible for the partitioning of precipitation between runoff and infiltration. Moreover, surface soil moisture controls the redistribution of the incoming solar radiation on land surface into sensible and latent heat fluxes. Recent developments have been made to improve soil moisture dynamics predictions with hydrologic land surface models (LSMs) that compute water and energy balances between the land surface and the low atmosphere. However, most of the time soil moisture is confined to an internal numerical model variable mainly due to its intrinsic space and time variability and to the well known difficulties in assessing its value from remote sensing as from in situ measurements. In order to exploit the synergy between hydrological distributed models and thermal remote sensed data, FEST-EWB, a land surface model that solves the energy balance equation, was developed. In this hydrological model, the energy budget is solved looking for the representative thermodynamic equilibrium temperature (RET) defined as the land surface temperature that closes the energy balance equation. So using this approach, soil moisture is linked to the latent heat flux and then to LST. In this work the relationship between land surface temperature and soil moisture is analysed using LST from AHS (airborne hyperspectral scanner), with a spatial resolution of 2-4 m, LST from MODIS, with a spatial resolution of 1000 m, and thermal infrared radiometric ground measurements that are compared with the thermodynamic equilibrium temperature from the energy water balance model. Moreover soil moisture measurements were carried out during the airborne overpasses and then compared with SM from the hydrological model. An improvement of this well known inverse relationship between soil moisture and land surface temperature is obtained when the thermodynamic approach is used. The analysis of the scale effects of the different variables retrieved from satellite data at different spatial resolutions is performed to better understand the scale laws of land surface temperature, latent heat flux and soil moisture. The study site is the agricultural area of Barrax (Spain) that is a heterogeneous area with an alternation of irrigated and non irrigated vegetated field and bare soil. The used data set was collected during two field campaigns in July 2005 in the framework of the SEN2FLEX project and in June 2009 in the SEN3EXP project.
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