Actual Evapotranspiration (Water Use) Assessment of the Colorado River Basin at the Landsat Resolution Using the Operational Simplified Surface Energy Balance Model

Abstract

Accurately estimating consumptive water use in the Colorado River Basin (CRB) is important for assessing and managing limited water resources in the basin. Increasing water demand from various sectors may threaten long-term sustainability of the water supply in the arid southwestern United States. We have developed a first-ever basin-wide actual evapotranspiration (ET a ) map of the CRB at the Landsat scale for water use assessment at the field level. We used the operational Simplified Surface Energy Balance (SSEBop) model for estimating ET a using 328 cloud-free Landsat images acquired during 2010. Our results show that cropland had the highest ET a among all land cover classes except for water. Validation using eddy covariance measured ET a showed that the SSEBop model nicely captured the variability in annual ET a with an overall R 2 of 0.78 and a mean bias 234MODIS-based ET a was not suitable for water use assessment at the field level. In contrast, Landsat-based ET a has good potential to be used at the field level for water management. With further validation using multiple years and sites, our methodology can be applied for regular production of ET a maps of larger areas such as the conterminous United States.

Evaluation of Landsat-Based METRIC Modeling to Provide High-Spatial Resolution Evapotranspiration Estimates for Amazonian Forests

“…This eliminates the need for the selection of cold and hot pixels from each Landsat scene as required in the METRIC processing. Several of these less input-intensive models utilizing Landsat data have been tested in agriculture and other simpler land cover types [52][53][54]. Given the limited availability of meteorological data in the Amazon and challenges identifying suitable cold and hot pixels in Amazonian conditions, these alternative models, due to their simplicity, may have a use in the Amazon for applications where a potentially larger margin of error in the ET estimates can be tolerated.…”

“…For example, hourly based meteorological data is not required for SSEBop [52] which also employs a pre-defined hot and cold boundary condition for computing daily ET. This eliminates the need for the selection of cold and hot pixels from each Landsat scene as required in the METRIC processing.…”

Comparison of Four Different Energy Balance Models for Estimating Evapotranspiration in the Midwestern United States

“…We used Landsat satellite images (path 28, row 31) acquired on 4 July, 5 August, 24 October, and 11 December (Landsat 5, Thematic Mapper: TM) and four images acquired on 13 August, 29 August, 30 September, and 16 October (Landsat 7, Enhanced Thematic Mapper Plus: ETM+) during the 2001 crop growing season (Figure 1). The Landsat images were processed using Erdas Imagine software (Hexagon Geospatial Inc., Norcross, GA, USA) based on standard procedure where digital number values are first converted to radiance and then to reflectance [20]. The University of Nebraska Agricultural Research and Development Center (ARDC) near Mead, Nebraska, within the Landsat scene footprint has three eddy covariance (EC) measurements sites.…”

“…The Landsat images were processed using Erdas Imagine software (Hexagon Geospatial Inc., Norcross, GA, USA) based on standard procedure where digital number values are first converted to radiance and then to reflectance [20]. The University of Nebraska Agricultural Research and Development Center (ARDC) near Mead, Nebraska, within the Landsat scene footprint has three eddy covariance (EC) measurements sites.…”

Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region

“…Computation of annual ET from MOD-SMET involves linear interpolation, where ET values for unavailable dates (due to error in the remote sensor or cloud-contaminated images) are linearly interpolated between two image acquisition dates. This method is generally suitable when remotely sensed images are available at regular intervals and each image captures the overall pattern of variation in ET [94]. For more information regarding interpolation between clear sky days, please refer to Singh et al [94].…”