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United States Department of Agriculture

Agricultural Research Service

Title: Estimation of Spatially Distributed Evapotranspiration over Wheat Using Thermal Infrared Images and Ground-Based Radiometers

Authors
item FRENCH, ANDREW
item HUNSAKER, DOUGLAS
item Clarke, Thomas
item Fitzgerald, Glenn
item Pinter Jr, Paul

Submitted to: Proceedings of the World Water and Environmental Resources Congress
Publication Type: Proceedings
Publication Acceptance Date: April 4, 2006
Publication Date: May 26, 2006
Citation: French, A.N., Hunsaker, D.J., Clarke, T.R., 2006. Fitzgerald, G.J., Pinter Jr, P.J. Estimation of spatially distributed evapotranspiration over wheat using thermal infrared images and ground-based radiometers. Proceedings of the World Water and Environmental Resources Congress. CD-ROM unpagenated.

Interpretive Summary: Estimating daily evapotranspiration (ET) over wheat crops is important because it allows growers to decide when and where to irrigate. The only way to estimate ET over large areas is with remote sensing, which detects changes in vegetation brightness and temperature. Surface temperature observations, readily made with thermal infrared cameras, are especially useful because they can detect crop water stress. Nevertheless, accurate ET estimates using remote sensing are difficult to obtain. Temperature changes over crops such as wheat are frequently small. This investigation magnifies temperature changes by observing the crop at multiple times. The results indicate that hourly temperature changes are correlated with ET, with better correlation at field-wide scales. With further testing, the multiple surface temperature approach could help make thermal infrared remote sensing of crops a practical technique.

Technical Abstract: Spatially distributed evapotranspiration (ET) estimation is important for crop stress and assessment and irrigation scheduling. Using remotely sensed thermal infrared data in combination with visible-near infrared data, accurate instantaneous ET estimates are feasible. These estimates however need to be extended to daily time steps to have practical value at farm scales. One way to accomplish this extension is to combine hourly image observations of soil and vegetation temperatures. This approach is tested using a one-source energy balance model and data obtained from a series of morning remote sensing flights on 10 March 2005 over a wheat crop planted in Maricopa, Arizona. Aggregate remote sensing ET results from this particular day agreed well with estimates derived from soil moisture observations, but not on a plot-by-plot basis, where modeled ET variability was much less than soil moisture variability. This result is inconsistent with remotely sensed surface temperatures which do show significant spatial and temporal changes. Additional data sets will be investigated to determine how to improve ET modeling with surface temperatures.

Last Modified: 9/29/2014
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