ARS | Publication request: Overview of the Bushland Evapotranspiration and Agricultural Remote sensing experiment 2008 (BearEX08): A field experiment evaluating methods for quantifying ET at multiple scales

Submitted to: Advances in Water Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 17, 2012
Publication Date: November 29, 2012
Citation: Evett, S.R., Kustas, W.P., Gowda, P., Anderson, M.C., Prueger, J.H., Howell, T.A. 2012. Overview of the Bushland Evapotranspiration and Agricultural Remote sensing experiment 2008 (BearEX08): A field experiment evaluating methods for quantifying ET at multiple scales. Advances in Water Resources. 50:4-19. http://dx.doi.org/10.1016/j.advwatres.2012.03.010

Interpretive Summary: Accurate knowledge of crop and natural vegetation water use is critical for more effective management of the nation's watersheds and water resources. Watersheds and aquifers supply water for agriculture, which is increasingly short of adequate supplies. Irrigated agriculture places heavy demands on water but returns large yields while using water more efficiently than rain fed or dryland agriculture. That is why irrigated agriculture is the backbone of agricultural production in the nation. Determining water use over large areas of land is a difficult problem that is approachable using satellite and aerial remote sensing to provide data for computer simulations of water use that are checked (ground truthed) using ground-based water use sensing systems. Both the simulations and ground-based systems must be checked for accuracy and calibrated. Scientists from four USDA-ARS laboratories and three universities collaborated in an ARS led field campaign to check accuracy and calibrate equipment and simulation programs. The campaign occurred at and was led by the USDA-ARS Conservation & Production Research Laboratory at Bushland, Texas. Improved knowledge of water use from the Ogallala Aquifer for irrigation was the driving factor.

Technical Abstract: In 2008, scientists from seven federal and state institutions worked together to investigate temporal and spatial variations of the surface energy balance and evapotranspiration (ET) in a semi-arid irrigated and dryland agricultural region of the Southern High Plains in the Texas Panhandle. Micrometeorological fluxes (surface energy balance) were determined in four weighing lysimeter fields (each 4.7 ha) containing irrigated and dryland cotton and in nearby bare soil, wheat stubble and rangeland fields using nine eddy covariance stations, three large aperture scintillometers, and three Bowen ratio systems. Flux and remote sensing aircraft flew transects over the surrounding fields and region encompassing an area contributing fluxes from 10-30 kilometers upwind of the USDA-ARS lysimeter site. Tethered balloon soundings were conducted over the irrigated fields to investigate the effect of advection on local boundary layer development. Local ET was measured using four large weighing lysimeters, while field scale estimates were made by soil water balance with a network of neutron probe profile water sites and from the stationary flux systems. Aircraft and satellite imagery were obtained at different spatial and temporal resolutions. Plot-scale experiments dealt with row orientation and crop height effects on spatial and temporal patterns of soil surface temperature, soil water content, soil heat flux, evaporation from soil in the interrow, plant transpiration, and canopy and soil radiation fluxes. BEAREX08 is perhaps the only large-scale field study to date that has measurements of ET at scales ranging from local to regional scale; and that compares direct and indirect methods at local scale, with remote sensing based methods and models using aircraft and satellite imagery at local to regional scales. Here we present an overview of the experiment and a summary of preliminary findings presented in this special issue of Advances in Water Resources (AWR). Our understanding of the role of advection in the measurement and modeling of ET is advanced by these papers integrating measurements and model estima