Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate.

Instantaneous evapotranspiration rates and surface water stress levels can be deduced from remotely sensed surface temperature data through the surface energy bud- get. Two families of methods can be defined: the contex- tual methods, where stress levels are scaled on a given im- age between hot/dry and cool/wet pixels for a particular veg- etation cover, and single-pixel methods, which evaluate la- tent heat as the residual of the surface energy balance for one pixel independently from the others. Four models, two contextual (S-SEBI and a modified triangle method, named VIT) and two single-pixel (TSEB, SEBS) are applied over one growing season (December-May) for a 4 km◊ 4 km ir- rigated agricultural area in the semi-arid northern Mexico. Their performance, both at local and spatial standpoints, are compared relatively to energy balance data acquired at seven locations within the area, as well as an uncalibrated soil- vegetation-atmosphere transfer (SVAT) model forced with local in situ data including observed irrigation and rainfall amounts. Stress levels are not always well retrieved by most models, but S-SEBI as well as TSEB, although slightly bi- ased, show good performance. The drop in model perfor- mance is observed for all models when vegetation is senes- cent, mostly due to a poor partitioning both between tur- bulent fluxes and between the soil/plant components of the latent heat flux and the available energy. As expected, con- textual methods perform well when contrasted soil moisture