| Autor: |
Chirouze, J., Boulet, G., Jarlan, L., Fieuzal, R., Rodriguez, J. C., Ezzahar, J., Er-Raki, S., Bigeard, G., Merlin, O., Garatuza-Payan, J., Watts, C., Chehbouni, G. |
| Zdroj: |
Hydrology & Earth System Sciences Discussions; 2013, Vol. 10 Issue 1, p895-963, 69p, 1 Black and White Photograph, 1 Diagram, 9 Charts, 13 Graphs |
| Abstrakt: |
Remotely sensed surface temperature can provide a good proxy for water stress level and is therefore particularly useful to estimate spatially distributed evapotranspiration. Instantaneous stress levels or instantaneous latent heat flux are deduced from the surface energy balance equation constrained by this equilibrium temperature. Pixel av- erage surface temperature depends on two main factors: stress and vegetation fraction cover. Methods estimating stress vary according to the way they treat each factor. Two families of methods can be defined: the contextual methods, where stress levels are scaled on a given image between hot/dry and cool/wet pixels for a particular vegetation cover, and single-pixel methods which evaluate latent heat as the residual of the surface energy balance for one pixel independently from the others. Four models, two contextual (S-SEBI and a triangle method, inspired by Moran et al., 1994) and two single-pixel (TSEB, SEBS) are applied at seasonal scale over a four by four km irrigated agricultural area in semi-arid northern Mexico. Their performances, both at local and spatial standpoints, are compared relatively to energy balance data acquired at seven locations within the area, as well as a more complex soil-vegetation-atmosphere transfer model forced with true irrigation and rainfall data. Stress levels are not always well retrieved by most models, but S-SEBI as well as TSEB, although slightly biased, show good performances. Drop in model performances is observed when vegetation is senescent, mostly due to a poor partitioning both between turbulent fluxes and between the soil/plant components of the latent heat flux and the available energy. As expected, contextual methods perform well when extreme hydric and vegetation conditions are encountered in the same image (therefore, esp. in spring and early summer) while they tend to exaggerate the spread in water status in more homogeneous conditions (esp. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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