Approaches to estimating spatial distribution of actual evapotranspiration (ET) from remote sensing information have become more prominent in recent years. They are based in several different concepts and methods, with varying levels of determinism and empiricism. Two major issues remain unresolved in using these approaches to estimate actual ET. First there is a need for testing and validating the suite of approaches under a range of locations and environmental conditions, in order to document the abilities of the models to reproduce ET under various scenarios. Second, since these models only yield an instantaneous value of ET, a substantial amount of gap filling is required for the periods between images – which is most of the time
Presented here is a set of procedures planned to assess ET of urban and irrigated agriculture in the arid western USU, starting with Utah. Two main flavors of remote sensing models will be used for the first efforts. The suite of data fusion models developed by the HRSL lab of the USDA-ARS are strongly process oriented and mechanistic. The Triangle Method is the essentially the father of several other approaches (ex. Metric, ELeaf), that mix processes with limits defined by the warmest and coolest parts of an image
The first effort will be to simulate and validate urban ET, mainly resulting from as turfgrass. An eddy covariance site is running over a rather homogeneous golf course in northern Utah, to be used for both studying how turf ET responds to environmental conditions, and remote sensing model validation. The next activity will be to use four new eddy covariance sites in irrigated agriculture, one in each of the four states of the upper Colorado region. These will allow validation of the remote sensing models.
Finally, recent knowledge of coherent patters of summer temperatures in the region can be integrated with the above to simulate how ET “demand” will change in the future. Analyses indicates summers are growing hotter, albeit within the cyclical patterns that are endemic to the region. There is a pressing need to develop a new “diagnostic’ model of ET, that has just enough information about the stomatal conductance process and soil water, to allow the model to reliably denote changes in ET. This would allow another way to “check” the output of the remote sensing-based estimates. It would also allow a quantification of the changes in ET in response to changes in summer temperatures.