Spatial scaling of evapotranspiration as affected by heterogeneities in vegetation, topography, and soil texture

To date, simulating land surface hydrological processes over large areas at spatial resolutions higher than 1 km remains technically unfeasible, because of limitations of data availability and computational resources. Several studies have demonstrated, however, that gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of water budget components at local, regional and global scales. These biases result from the overlook of sub-pixel variability of land surface characteristics. This study suggests a simple algorithm that uses sub-pixel information on the spatial variability of vegetation and soil cover, and surface topography to correct evapotranspiration (ET) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that the ET rates as obtained from calculations made at coarse spatial resolutions are multiplied by separate simple functions that attempt to reproduce the effects of sub-pixel variability of land cover, leaf area index, soil texture, and topography on ET. Its application to a remote sensing process-based model estimates made at a 1-km resolution over a watershed located in the southern part of the Canadian boreal forest improved estimates of average ET as well as its temporal and spatial variability.