Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: September 10, 2011
Publication Date: October 3, 2011
Citation: Kustas, W.P., Anderson, M.C., Gao, F.N. 2011. Application of remote sensing for multi-scale monitoring of evapotranspiration [abstract]. Hyperspectral Infrared Imager Decadal Survey Mission Science Workshop. http://hyspiri.jpl.nasa.gov/documents/2011-workshop.
Estimating water loss from vegetation and soil or evapotranspiration (ET) at field to regional scales is critical information for many water resource and agricultural management applications as well as weather and climate forecasting and research. Water availability is strongly tied to crop productivity and yield estimation and prediction. Consequently, limited water availability due to an extended drought can lead to serious food shortages and famines particularly in third world countries facing significant growth in human population without additional water resource capabilities to produce more food. Moreover, it is becoming increasingly evident that regional weather and climate conditions, including the persistence of floods and droughts, are affected by regional ET rates from the land surface. Estimating ET from field to regional scales is a major challenge that will require the use of satellite remote sensing to provide synoptic information about the state of the land surface. Remotely sensed land surface temperature (LST) is a key boundary condition that can be used to define the energy and moisture state of the land surface. In this presentation, a modeling scheme will be described that utilizes LST to estimate ET from soil and vegetation systems and provides a means to generate both regional and field scale ET estimates when LST data is available from both coarse geostationary satellite observations and high resolution data from Landsat. It is shown that for many applications in water resource and agricultural management as well as accurately determining ET at regional scales for weather and climate modeling, it is imperative that more frequent high resolution LST observations are available, as would be with the HyspIRI satellite.