Using ASTER satellite data to calculate riparian evapotranspiration in the Middle Rio Grande, New Mexico

AS Bawazir, Z Samani, M Bleiweiss… - … journal of remote …, 2009 - Taylor & Francis
AS Bawazir, Z Samani, M Bleiweiss, R Skaggs, T Schmugge
International journal of remote sensing, 2009Taylor & Francis
Riparian evapotranspiration (ET) in the Rio Grande Basin in New Mexico, USA is a major
component of the hydrological system. Over a period of several years, ET has been
measured in selected locations of dense saltcedar and cottonwood vegetation. Riparian
vegetation varies in density, species and soil moisture availability, and to obtain accurate
measurements, multiple sampling points are needed, making the process costly and
impractical. An alternative solution involves using remotely sensed data to estimate ET over …
Riparian evapotranspiration (ET) in the Rio Grande Basin in New Mexico, USA is a major component of the hydrological system. Over a period of several years, ET has been measured in selected locations of dense saltcedar and cottonwood vegetation. Riparian vegetation varies in density, species and soil moisture availability, and to obtain accurate measurements, multiple sampling points are needed, making the process costly and impractical. An alternative solution involves using remotely sensed data to estimate ET over large areas. In this study, daily ET values were measured using eddy covariance flux towers installed in areas of saltcedar and cottonwood vegetation. At these sites, remotely sensed satellite data from the National Aeronautics and Space Administration (NASA) Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to calculate the albedo, normalized difference vegetation index (NDVI) and surface temperature. A surface energy balance model was used to calculate ET values from the ASTER data, which were available for 7 days in the year. Comparison between the daily ET values of saltcedar and cottonwood measured from the flux towers and calculated from remote sensing resulted in a mean square error (MSE) of 0.16 and 0.37 mm day−1, respectively. The regional map of ET generated from the remote sensing data demonstrated considerable variation in ET, ranging from 0 to 9.8 mm day−1, with a mean of 5.5 mm day−1 and standard deviation of 1.85 mm day−1 (n = 427481 pixels) excluding open water. This was due to variations in plant variety and density, soil type and moisture availability, and the depth to water table.
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