|Paul, George -|
|Prasad, P.V. Vara -|
|Staggenborg, Scott -|
|Neale, Christopher -|
Submitted to: Advances in Water Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 6, 2013
Publication Date: June 17, 2013
Citation: Paul, G., Gowda, P., Prasad, P., Howell, T.A., Staggenborg, S.A., Neale, C.M. 2013. Lysimetric evaluation of SEBAL using high resolution airborne imagery from BEAREX08. Advances in Water Resources. 59:157-168. Interpretive Summary: Evapotranspiration (ET) maps can assist irrigation and groundwater management in semiarid regions. Remote sensing based ET models are presently most suited for mapping ET at regional scales. In this study, we evaluated SEBAL model for its ability to estimate ET using high-resolution remote sensing data in the Texas High Plains. Analysis of the results suggested improvements in the model to make it viable for ET mapping.
Technical Abstract: In this study, the SEBAL was evaluated for its ability to derive aerodynamic components and surface energy fluxes from high resolution airborne remote sensing data acquired during the Bushland Evapotranspiration and Agricultural Remote Sensing Experiment 2008 in Texas, USA. Issues related to hot and cold pixel selection and the underlying assumptions of linear temperature gradient were also addressed. Estimated ET and other components of the surface energy balance were compared with measured data from four large precision weighing lysimeters and other instrumentation systems placed on two irrigated and two dryland fields. Instantaneous ET was estimated with overall mean bias error and root mean square error (RMSE) of 0.13 and 0.16 mm/h (24.2 and 29.6%) respectively, where relatively large RMSE was contributed by dryland field. Sensitivity analysis of the hot and cold pixel selection indicated that up to 20% of the variability in ET estimates can be attributed to the differences in the surface energy balance and roughness properties of the anchor pixels. Adoption of an excess resistance to heat transfer (kB-1) model into SEBAL significantly improved ET estimates.