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United States Department of Agriculture

Agricultural Research Service

Title: High Spatial Reosultion Mapping of Surface Energy Balance Components with Remotely Sensed Data

Authors
item Humes, Karen - UNIVERISTY OF OKLAHOMA
item Hardy, Ray - UNIVERSITY OKLAHOMA
item Kustas, William
item Prueger, John
item Starks, Patrick

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: September 10, 2000
Publication Date: N/A

Interpretive Summary: Remotely sensed data can provide spatially distributed information on a number of key land surface characteristics and state variables which control evapotranspiration. In this study, ground and remotely sensed data acquired over the Little Washita Experimental Watershed were used in conjunction with a relatively simple "snapshot" model to compute spatially distributed evapotranspiration at the time of a Landsat TM overpass. For the particular date studied, the satellite data were acquired shortly after a significant precipitation event moved through the area. The saturated conditions across the watershed, combined with minimal radiation loading that occurred the morning before the satellite data were acquired, had a tendency to minimize the spatial variability in some of the surface state variables which control evapotranspiration, such as surface temperature. It also gave rise to the rather unusual situation in which there was more variation in air temperature than in surface temperature. Thus, the spatial variability in evapotranspiration was rather minimal, but did show some slight spatial patterns related to meteorological conditions. Though the spatial variability in evapotranspiration for the time period studied was relatively minimal, the work presented here demonstrates the utility of this type of modeling approach, which is primarily "data driven" and does not require special calibration for application to other areas. These results also underscore the need for as much density as possible in the ground networks which provide near-surface meteorological inputs to these and other types of models.

Technical Abstract: Remotely sensed data can provide spatially distributed information on a number of key land surface characteristics and state variables which control the surface energy balance. In this study, ground and remotely sensed data acquired over the Little Washita Experimental Watershed in August 1994 were used in conjunction with a relatively simple "snapshot" model to compute spatially distributed energy fluxes at the time of a Landsat TM overpass. For the particular date studied, the satellite data were acquired shortly after a significant precipitation event moved through the area. The saturated conditions across the watershed, combined with minimal radiation loading that occurred the morning before the satellite data were acquired, had a tendency to minimize the spacial variability in some of the surface state variables which control surface fluxes, such as surface temperature. It also gave rise to the rather unusual situation in which there was more variation in near-surface air temperature than in surface temperature. Thus, the spatial variability in the surface energy balance components was rather minimal, but did show some slight spatial patterns related to near-surface meteorological conditions, precipitation totals in the hours prior to the satellite data acquisition, and land cover type. Though the spatial variability in surface fluxes for the time period studied was relatively minimal, the work presented here demonstrates the utility of this type of modeling approach, which is primarily "data driven" and does not require special calibration for application to other areas. These results also underscore the need for as much density as possible in the ground networks.

Last Modified: 11/21/2014
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