Document Type



Regional and global scale studies of land-surface-atmosphere interactions require the use of observations for calibration and validation. In situ field observations are not representative of the distributed nature of land surface characteristics, and large-scale field experiments are expensive undertakings. In light of these requirements and shortcomings, satellite observations serve our purposes adequately. The use of satellite data in land surface modeling requires developing a hydrological model with a thin upper layer to be compatible with the nature of the satellite observations and that would evaluate the soil moisture and soil temperature of a thin layer close to the surface. This paper outlines the formulation of a thin layer hydrological model for use in simulating the soil moistures and soil temperatures. This thin layer hydrological model is the first step in our attempt to use microwave brightness temperature data for regional soil moisture estimation. The hydrological model presented here has been calibrated using five years (1980–1984) of daily streamflow data for the Kings Creek catchment. The calibrated parameters are used to validate the daily streamflows for the next 5 year period (1985–1989). The comparison of surface soil moistures and surface temperatures for the period of the Intensive Field Campaigns (IFCs) during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) in 1987 is carried out and yields good results. The thin layer hydrological model is coupled with a canopy radiative transfer model and an atmospheric attenuation model to create a coupled soil-canopy-atmosphere model in order to study the effect of the vegetation and the soil characteristics on the Special Sensor Microwave Imager (SSM/I) brightness temperatures. The sensitivities of the brightness temperatures to the soil and vegetation is examined in detail. The studies show that increasing leaf area index masks the polarization difference signal originating at the soil surface.