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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Manuscript title: Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

Authors
item Kustas, William
item Alfieri, Joseph
item Anderson, Martha
item Colaizzi, Paul
item Prueger, John
item Evett, Steven
item Neale, Christopher Mu -
item French, Andrew
item Hipps, Lawrence -
item Chavez, Jose -
item Copeland, Karen
item Howell, Terry

Submitted to: Advances in Water Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 6, 2012
Publication Date: November 29, 2012
Citation: Kustas, W.P., Alfieri, J.G., Anderson, M.C., Colaizzi, P.D., Prueger, J.H., Evett, S.R., Neale, C.M., French, A.N., Hipps, L.E., Chavez, J.L., Copeland, K.S., Howell, T.A. 2012. Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area. Advances in Water Resources. 50:120-133.

Interpretive Summary: For irrigated agriculture, the latent heat flux (or evapotranspiration (ET) when expressed as rate of water loss) is tied to crop water requirements, irrigation applications, and vegetation stress. Land surface temperature (LST) is a fundamental surface state that is strongly coupled to the surface energy balance and ET. For this reason, studies have evaluated the utility of LST as a key boundary condition and metric for modeling water use and availability, which is tied to plant growth and carbon assimilation. Consequently, LST provides a means for monitoring crop water use, stress and ultimately yield. Many of the LST-based ET models require local meteorological inputs of incoming solar radiation, wind speed and air temperature. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface-air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues utilizing the Two-Source Energy Balance (TSEB) model, which is a robust approach for heterogeneous landscapes, and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and ET observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains. Model output ET generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The resulting discrepancies between model and measured fluxes are found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of these remote sensing observations of the flux measurement footprint.

Technical Abstract: Application and validation of many thermal remote sensing-based energy balance models involve the use of local meteorological inputs of incoming solar radiation, wind speed and air temperature as well as accurate land surface temperature (LST), vegetation cover and surface flux measurements. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface-air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues utilizing the Two-Source Energy Balance (TSEB) model of Norman et al [1], and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and flux observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains. Model output fluxes (i.e., net radiation, soil heat flux, sensible and latent heat flux) generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The resulting discrepancies between model and measured fluxes are found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of these remote sensing observations of the flux measurement footprint.

Last Modified: 8/1/2014
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