In recent work, Dubayah and Lettenmaier (1997) have attempted to maximize the use of remote-sensing data as drivers for a large-scale coupled water and energy balance model. They used the V1C-3L model (Liang et al., 1994) applied to the
Arkansas-Red River basins in the Southern Great Plains in the United States. There were two objectives to this research: (1) to develop and test a land surface hydrologic model capable of using remote-sensing data and (2) to develop and test algorithms for generating data from remote-sensing measurements. Remote-sensing data were obtained from GOES (solar radiation), AVHRR (downwelling long-wave radiation, air temperature, surface humidity, and vegetation), Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI) (canopy interception, and canopy resistance).
The VIC-3L model was used to simulate the water and energy fluxes for the month of June, 1987. The model was first used with ground-based data (from 26 meteorological stations) and then with the remote-sensing-derived data. Comparison of the results yielded differences of as much as 40% in net radiation, 15% in latent heat, and 100% in sensible heat. For such studies, the results from the ground-based data are not necessarily correct; it is not known whether the remote-sensing or the ground-based data give the correct results. Thus it really could not be determined if the remote-sensing data resulted in an improvement or a degradation in the water and energy fluxes. However, the remote-sensing simulations did provide a spatial pattern that appears to provide more information about the distribution of the fluxes than do the ground-based measurements.
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