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United States Department of Agriculture

Agricultural Research Service

Title: Intercomparison of remote sensing-based evapotranspiration models using SGP and SMEX data

item Choi, Minha
item Kustas, William - Bill
item Anderson, Martha
item Allen, Richard

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 10/2/2007
Publication Date: 12/10/2007
Citation: Choi, M., Kustas, W.P., Anderson, M.C., Allen, R.G. 2007. Intercomparison of remote sensing-based evapotranspiration models using SGP and SMEX data [abstract]. EOS Transactions, American Geophysical Union, Fall Supplements. 88(52):H31D-0639.

Interpretive Summary:

Technical Abstract: Accurate characterization of evapotranspiration (ET) over a range of spatial and temporal scales is critical for many applications in hydrology, ecohydrology, meteorology, climatology, and agriculture. Over the past several years, there has been a major effort devoted to the development and refinement of remote sensing-based energy balance models that provide spatially-distributed ET maps operationally using satellite data. Validation of the product (ET maps) is typically performed using a handful of tower-based flux observations, and hence little is known about the reliability of the ET maps for the majority of the scene. Very few studies have attempted to inter-compare ET models over the same experimental site in order to quantify and gain greater insight as to the possible uncertainty in ET estimation using different modeling approaches over the same landscape/region. In this study, we compare several remote sensing-based energy balance/ET modeling schemes, which have operational capabilities using remote sensing, with imagery and ground-truth data from the 1997 Southern Great Plains (SGP) experiment and the 2002 Soil Moisture/ Atmosphere Coupling EXperiment (SMEX02/SMACEX). The models differ in the complexity of the algorithms used in computing energy flux exchange, estimating model parameters/variables, and ancillary data requirements. However, all modeling approaches require surface temperature, vegetation cover and meteorological inputs. In this initial inter-comparison we will investigate if model differences are significant and can be associated with land cover or other landscape features, procedures used in defining model inputs or other factors. We will also compare model output with flux tower observations and contrast difference statistics produced between the various models and the measurements and between the different models. This type of investigation may ultimately lead to improvements in the algorithms used by the various models and/or provide an opportunity for incorporating the strengths of the different approaches in the development of a hybrid remote sensing ET model with significantly greater utility.

Last Modified: 06/23/2017
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