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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #303330
Title: A thermal-based remote sensing modeling system for estimating crop water use, stress and drought from field to global scales

Author
item Kustas, William - Bill
item Anderson, Martha
item HAIN, C. - University Of Maryland

Submitted to: Abstract of International Horticultural Congress
Publication Type: Abstract Only
Publication Acceptance Date: 3/30/2014
Publication Date: 8/5/2014
Citation: Kustas, W.P., Anderson, M.C., Hain, C. 2014. A thermal-based remote sensing modeling system for estimating crop water use, stress and drought from field to global scales [abstract]. 29th International Horticultural Congress. 2014 CDROM

Interpretive Summary:

Technical Abstract: Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. This presentation describes a robust but relatively simple thermal-based energy balance model that parameterizes the key soil/substrate and vegetation exchange processes affecting the radiative balance and turbulent energy transport with the overlying atmosphere. The thermal-based scheme, called the Two-Source Energy Balance (TSEB) model, solves for the soil/substrate and canopy temperatures that achieves a balance in the radiation and turbulent heat flux exchange with the lower atmosphere for the soil/substrate and vegetation elements. In doing so, the TSEB modeling framework is applicable to a wide range in atmospheric and canopy cover conditions. An overview of applications of the TSEB modeling framework to a variety of landscapes will be presented. In addition, a modeling framework will be described called the Atmosphere-Land Exchange Inverse (ALEXI) that couples the TSEB scheme with an atmospheric boundary layer model in time-differencing mode to routinely map continental-scale daily ET at 5 to 10-km resolution using geostationary satellites. A related algorithm (DisALEXI) spatially disaggregates ALEXI output down to finer spatial scales using polar orbiting satellites. This modeling system along with strategies for fusing information from multiple satellite platforms and wavebands is being used to generate both ET and drought maps at global scales. How such information can be used for assessing the impacts of human activities and climate change on water resources and agricultural production, particularly in data poor regions, will be discussed.