HR: 1330h
AN: H23B-01    [Abstracts]
TI: Estimating Land Surface Fluxes Using Microwave and Thermal Remote Sensing Data During SMEX02/SMACEX
AU: * Li, F
EM: fcl@hydrolab.arsusda.gov
AF: USDA-ARS Hydrology and Remote Sensing Lab, Bldg. 007, BARC-West, Beltsville, MD 20705 United States
AU: Kustas, W P
EM: bkustas@hydrolab.arsusda.gov
AF: USDA-ARS Hydrology and Remote Sensing Lab, Bldg. 007, BARC-West, Beltsville, MD 20705 United States
AU: Jackson, T J
EM: tjackson@hydrolab.arsusda.gov
AF: USDA-ARS Hydrology and Remote Sensing Lab, Bldg. 007, BARC-West, Beltsville, MD 20705 United States
AU: Bindlish, R
EM: bindlish@hydrolab.arsusda.gov
AF: USDA-ARS Hydrology and Remote Sensing Lab, Bldg. 007, BARC-West, Beltsville, MD 20705 United States
AU: Bindlish, R
EM: bindlish@hydrolab.arsusda.gov
AF: SSAI, Science Systems and Applications, 10210 Greenbelt Road, Suite 600, Lanham, MD 20706 United States
AU: Prueger, J H
AF: USDA-ARS National Soil Tilth Lab, 2150 Pammel Dr, Ames, IA 50011 United States
AB: A two-source (soil + vegetation) energy balance model using microwave-derived near-surface soil moisture (TSM_SM) as input was applied to a corn and soybean production region in central Iowa. Six days of the Polarimetric Scanning Radiometer (PSR) derived soil moisture data and Landsat derived vegetation information as well as local meteorological data were used to run the model. These data were acquired during the Soil Moisture Experiment in 2002 (SMEX02) and the Soil Moisture Atmosphere Coupling Experiment (SMACEX). The PSR derived soil moisture maps at 800 m resolution which were resampled to 30 m. At this higher resolution, a flux footprint model was applied to weight pixels within the source area of the flux tower measurements. The root mean square difference (RMSD) values between TSM_SM estimated and tower measured net radiation, Rn, and soil heat flux, G, were within 25 Wm^-2. The TSM_SM model also produced reasonable estimates of sensible heat (H) and latent heat flux (LE) with both RMSD values for H and LE being within 55 Wm^-2. The TSM_SM model output was also compared with estimates from the two-source model version using radiometric surface temperature observations (TSM_TH) from Landsat. The results from two Landsat overpasses under partial canopy cover on July 1, 2002, and near full cover on July 8 indicate that TSM_SM gave similar results (slightly better) to TSM_TH for July 1, but did not perform as well for July 8. When the two models were in good agreement, the surface temperature estimated from TSM_SM agreed closely with the Landsat radiometric temperature observations. By contrast, when TSM_SM output gave greater differences with TSM_TH flux estimates and tower measurements such as July 8, the TSM_SM model generally computed lower LE and higher H than TSM_TH and the tower measurements. This resulted in TSM_SM producing significantly higher surface temperatures than Landsat radiometric temperature observations. Both soil moisture and fractional vegetation cover/leaf area greatly affect TSM_SM output. However, it is not clear what factors caused TSM_SM to overestimate H and underestimate LE for July 8. This investigation also showed that by using the higher resolution soil moisture and vegetation cover information, the model output more closely matched tower measurements. This is most likely the result of accounting for the effects of spatial variation in the vegetation cover and application of a flux footprint model for estimating the appropriate source area from model output to compare with tower based flux measurements.
DE: 1640 Remote sensing
DE: 1655 Water cycles (1836)
DE: 1800 HYDROLOGY
DE: 1818 Evapotranspiration
DE: 1878 Water/energy interactions
SC: Hydrology [H]
MN: 2005 Joint Assembly