Abstract
Accurate estimation of spatial distributions of water (evapotranspiration) and energy fluxes is a goal sought by hydrologists, agronomists, and meteorologists but is difficult to achieve. The usual approaches to estimating these fluxes employ remote sensing observations and a surface energy flux model. However, resolution of remote sensing data, needed to observe patterns of biophysical variables, is commonly too coarse to distinguish between land cover types that constrain these fluxes. Accuracy of evapotranspiration estimates can be improved by using higher resolution (<10 m) remote sensing data since they can distinguish clusters of vegetation from bare soil fields and water bodies. A demonstration of this potential is shown using aircraft-based remote sensing observations from multiple platforms over a study site at Goermin, Germany. Four airborne surveys, conducted on the 6th and 10th of June and the 4th and 5th of July 2006, as part of the AGRISAR 2006 Experiment (AgriSAR2006), collected high resolution hyperspectral optical imagery in the visible, near infrared, and thermal infrared. Thermal infrared imagery from the Airborne Hyperspectral Scanner (AHS) of the Spanish Instituto Nacional de Tecnica Aerospacial (INTA) was employed to extract Land Surface Temperature (LST) maps, whereas imagery from the Compact Airborne Spectrographic Imager (CASI-1500) of the Canadian ITRES was used to derive horizontal (Fractional cover, Fc) and vertical (Leaf Area Index, LAI) vegetation density maps. A Bowen Ratio Energy Balance (BREB) station and a Large Aperture Scintillometer (LAS) station were installed in a winter wheat field and a single LAS was installed in a corn field during the campaign to analyze the energy balance at the surface in detail. To demonstrate the approach, data from a flight line on July the 5th was employed. Derived LST, Fc and LAI maps were combined with surface micrometeorological observations from a standard weather station in Goermin and with a dual source energy balance model to derive spatially distributed water (evapotranspiration) and energy fluxes. Results show that flux estimates with respect to the ground-based BREB and LAS observations are within observation accuracy, typically within 50 Wm-2. This means that the high spatial resolution observations can potentially produce evapotranspiration estimates similar in quality to ground-based point measurements. Furthermore, spatial patterns of evapotranspiration fluxes were confirmed by ground-based soil moisture observations. First results on how these estimates relate to spatially distributed hydrologic model output using the PROMET and TOPLATS hydrologic models are presented as well.
