Abstract
There is considerable interest in using remote sensing to characterize the hydrologic behavior of the land surface on a routine basis. Information on moisture fluxes between the surface and lower atmosphere reveals linkages and land–atmosphere feedback mechanisms, aiding our understanding of energy and water balance cycles. Techniques that combine information on land and atmospheric properties with remotely sensed variables would allow improved prediction for a number of hydrological variables. Over the last few decades, there has been a focus on better determining evapotranspiration and its spatial variability, but for many regions routine prediction is not generally available at a spatial resolution appropriate to the underlying surface heterogeneity. Over agricultural regions, this is particularly critical, since the spatial extent of typical field scales is not regularly resolved within the pixel resolution of satellite sensors. Understanding the role of landscape heterogeneity and its influence on the scaling behavior of surface fluxes as observed by satellite sensors with different spatial resolutions is a critical research need. To attend this task, data from Landsat-ETM (60 m), ASTER (90 m), and MODIS (1020 m) satellite platforms are employed to independently estimate evapotranspiration. The range of the satellite sensor resolutions allows analyses that span scales from (point-scale) in-situ tower measurements to the MODIS kilometer-scale. Evapotranspiration estimates derived at these multiple resolutions were assessed against eddy covariance flux measurements collected during the 2002 Soil Moisture Atmospheric Coupling Experiment (SMACEX) over the Walnut Creek watershed in Iowa. Together, these data allow a comprehensive scale intercomparison of remotely sensed predictions, which include intercomparisons of the evapotranspiration products from the various sensors as well as a statistical analysis for the retrievals at the watershed scale. A high degree of consistency was observed between the retrievals from the higher-resolution satellite platforms (Landsat-ETM and ASTER). The MODIS-based estimates, while unable to discriminate the influence of land surface heterogeneity at the field scale, effectively reproduced the watershed average response, illustrating the utility of this sensor for regional-scale evapotranspiration estimation.