Use of special sensor microwave imager data for soil moisture estimation

The utilization of satellite data in land surface modeling is of great importance particularly if we want to move up in spatial scale for which there is a definite lack of field observations of soil moisture. The present research hopes to harness the available satellite data from various sensors in order to help in estimation of soil moisture over large areas compatible with grid sizes of climate models. This research uses the microwave brightness temperatures from the Special Sensor Microwave Imager (SSM/I) at 19 and 37 GHz in both the horizontal and vertical polarizations.; This research uses a coupled soil-canopy-atmosphere model in order to study the processes that effect the observation of the brightness temperatures by the SSM/I sensor. The land surface hydrological model is used to simulate the water and energy balance fluxes for the Kings Creek catchment for a period of 10 years from 1980 to 1989. The sensitivity of the simulated brightness temperatures to vegetation and soil is investigated using a canopy radiative transfer model for the vegetation and an atmospheric attenuation model.; The SSM/I brightness temperature observations are over large areas of the order of 900-2500 {dollar}kmsp2{dollar}. At these scales, it is important to investigate the effect of heterogeneities in land surface characteristics on the observed brightness temperatures. Simulations are carried out using the coupled soil-canopy-atmosphere model to assess the effect of vegetation distribution as well as distribution and partial coverage of rainfall on the simulated brightness temperatures.; Soil moistures and the SSM/I brightness temperatures at 19 and 37 GHz are simulated over the Red River basin area between 31.5{dollar}spcirc{dollar}N to 36{dollar}spcirc{dollar}N latitude and 94.5{dollar}spcirc{dollar}W to 104.75{dollar}spcirc{dollar}W longitude. This simulation is carried out for a time period of one year (August 1, 1987 to July 31, 1988). The soil hydrology, radiative transfer and atmospheric attenuation models utilize remotely sensed data viz-vegetation input the NDVI (Normalized Difference Vegetation Index) data derived from AVHRR observations (Advanced Very High Resolution Radiometer) and the rainfall data is obtained using Manually Digitized Radar (MDR) data.; Comparisons between the model derived and SSM/I derived soil moisture are analyzed. The monthly estimates of cumulative evapotranspiration derived using SSM/I derived soil moisture and the hydrological model are compared with estimates derived using atmospheric budget analysis. The mean monthly surface soil moistures derived using observed SSM/I data is analyzed in conjunction with rainfall and vegetation information.