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Title: ESTIMATING SURFACE SOIL MOISTURE WITH SCANNING LOW FREQUENCY MICROWAVE RADIOMETER (SLFMR) DURING THE SOUTHERN GREAT PLAINS 1997 (SGP97) HYDROLOGY EXPERIMENT

Author
item UITDEWILLIGEN, D - WAGENINGEN UNIVERSITY
item Kustas, William - Bill
item VAN OEVELEN, PETER - WAGENINGEN UNIVERSITY

Submitted to: Physics and Chemistry of the Earth
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/8/2003
Publication Date: 4/5/2003
Citation: Uitdewilligen, D., Kustas, W.P., Van Oevelen, P. 2003. Estimating surface soil moisture with scanning low frequency microwave radiometer (SLFMR) during the Southern Great Plains 1997 (SGP97) Hydrology Experiment. Physics and Chemistry of the Earth. 28:41-51.

Interpretive Summary: The Scanning Low Frequency Microwave Radiometer (SLFMR) was used to map surface soil moisture (0-5 cm depth) during the Southern Great Plains 1997 (SGP97) hydrology experiment. It was found that the soil moisture retrieval algorithm, developed for regional soil moisture mapping, required a more site specific calibration for reliable soil moisture estimation at the local scale. This research indicates that further work is required to develop more robust soil moisture retrieval algorithms for high resolution soil moisture mapping at the field scale, and will involve developing a better framework for merging different remote sensing data sources. Ultimately, this research will improve NASA, NOAA and USDA's efforts in improved monitoring of soil-plant conditions affecting local and regional climate, and for assessing the extent and severity of drought.

Technical Abstract: The Scanning Low Frequency Microwave Radiometer (SLFMR) was used to map surface soil moisture (0-5 cm depth) during the Southern Great Plains 1997 (SGP97) hydrology experiment. On June 29, July 2 and July 3, surface soil moisture maps with a pixel resolution of 200 m were obtained using a soil moisture retrieval algorithm, developed for L-band passive microwave data. In comparison with the 800 m resolution data from the Electronically Scanned Thinned Array Radiometer (ESTAR), the higher resolution SLFMR data required a more site specific calibration. After calibration root mean square difference between model and observed surface soil moisture observations were on the order of ~5%. Uncertainties in the retrieval algorithm were mainly due to the inability to distinguish land properties, for example differences in the effects of wheat stubble and bare soil fields. Furthermore at high resolution, pixels crossing field boundaries had a more significant impact on the retrieval algorithm due to difficulties in specifying the input data for pixels containing more than one land use.