ABSTRACT
Ground-based measurements of hydrologic and micrometeorologic processes are now available for many parts of the world, especially for the United States and Europe, on a nearly routine basis. These measurements, however, are only representative of a very small area around the sensors, and, therefore, provide little information about regional hydrology. The variability of the land surface precludes using these measurements to make inferences about processes that occur over an area of a hectare, much less the size of an entire valley. Recent developments have demonstrated an increasing capability to estimate the spatial distribution of hydrologic surface fluxes for very large areas with remote sensing techniques. A number of studies have focused on the use of remote sensing to measure surface water and energy variables in attempts to derive latent heat flux or evapotranspiration (ET) over semiarid regions (e.g. Kustas et al. 1989a,b, 1990, 1994a,b,d, 1995; Humes et al. 1994, 1995; Moran et al. 1994; Ottlé and Vidal-madjar 1994; Tueller 1994). All of these investigations have used aircraft-based instruments and were limited to small areas. In only a few investigations has satellite-based remote sensing data been used to estimate ET. The synoptic and real-time attributes of remote sensing data from satellites offer the potential for measuring landscape, hydrometeorological, and surface energy flux characteristics that can be used in both monitoring and modeling the state and dynamics of semi-arid regions. Choudhury (1991) reviewed the current state of progress in utilizing satellite-based remote sensing data to estimate various surface energy balance parameters. Kustas et al. (1994c) used Advanced Very High Resolution Radiometer (AVHRR) data to extrapolate ET estimates from one location containing near-surface meteorological data to other areas in a semi-arid basin in Arizona. Moran et al. (1989) and Moran and Jackson (1991) used Landsat Thematic Mapper (TM) data to estimate ET over a small agricultural area. In this paper, we present a method for scaling from point to spatial estimates of instantaneous surface fluxes for a Great Basin desert valley using Landsat TM data and for characterizing the partitioning of fluxes among the different soil and landcover types found in the study area.
