Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 12/8/2002
Publication Date: 12/18/2002
Citation: Guha, A., Hsu, E., Jacobs, J.M., Cosh, M.H. Estar brightness temperatures for soil moisture estimating and spatial characterization of the retrieved fields-a study from SGP99. American Geophysical Union. EOS Trans. of AGU. 83:F507.
Technical Abstract: Surface soil moisture is an important variable in the modeling of hydrological and biophysical processes. Several field experiments have been carried out in the last decade in the Southern Great Plains region of the United States to evaluate sensors for soil moisture detection and retrieval algorithms. Previous studies have used the results of these experiments to study the temporal and spatial variability of soil moisture at various scales. This study focuses on extending this work to the Southern Great Plains Experiment 1999 (SGP99), which took place during the second and third weeks of July 1999 and covered an area greater than 10,000 km2. During SGP99 the Electronically Scanned Thinned Array Radiometer (ESTAR) was flown to study surface soil moisture. The ESTAR is a synthetic aperture, microwave radiometer operating at a frequency of 1.4 GHz. The brightness temperature of a vegetated surface at microwave frequencies depends on a number of land surface parameters including vegetation type, soil type, temperature, and roughness, in addition to soil moisture. Results of soil moisture retrievals from the ESTAR recorded brightness temperatures using a semi-empirical retrieval algorithm are presented. The retrieved soil moisture shows considerable agreement with ground measurements from various sites distributed over the study region. The validity of spatially interpolating the ground observations to obtain regionalized values of soil moisture over the entire watershed is also investigated. Also, this study investigates the spatial structure from the SGP99 retrieved fields by examining the transition from simple scaling to multi-scaling for various moments of soil moisture. Soil moisture scaling behavior is statistically characterized by parameters such as the scaling exponent, the order moment, and the fractal dimension. The relationship between rainfall and soil moisture is identified and its influence on scaling properties is discussed. The variations of these parameters are considered as a time series that enables us to observe climate induced variation. To improve future land surface modeling and to capture the critical forcing variables, the scaling properties of some physically derived features, such as latent heat flux, porosity, leaf area index, and topography are also evaluated. These results are compared to the previous studies using the Washita '92, Washita '94, and SGP97 soil moisture fields. Regressive parameters for previously derived best-fit relationships of soil moisture structure are examined for their robustness.