Actual evapotranspiration in drylands derived from in-situ and satellite data: Assessing biophysical constraints

Abstract: Improving regional estimates of actual evapotranspiration (λΕ) in water-limited regions located at climatic transition zones is critical. This study assesses an λΕ model (PT-JPL model) based on downscaling potential evapotranspiration according to multiple stresses at daily time-scale in two of these regions using MSG–SEVIRI (surface temperature and albedo) and MODIS products (NDVI, LAI and fPAR ). An open woody savanna in the Sahel (Mali) and a Mediterranean grassland (Spain) were selected as test sites with Eddy Covariance data used for evaluation. The PT-JPL model was modified to run at a daily time step and the outputs from eight algorithms differing in the input variables and also in the formulation of the biophysical constraints (stresses) were compared with the λΕ from the Eddy Covariance. Model outputs were also compared with other modeling studies at similar global dryland ecosystems. The novelty of this paper is the computation of a key model parameter, the soil moisture constraint, relying on the concept of apparent thermal inertia (fSM-ATI ) computed with surface temperature and albedo observations. Our results showed that fSM-ATI from both in-situ and satellite data produced satisfactory results for λΕ at the Sahelian savanna, comparable to parameterizations using field-measured Soil Water Content (SWC) with r2 greater than 0.80. In the Mediterranean grasslands however, with much lower daily λE values, model results were not as good as in the Sahel (r2 =0.57–0.31) but still better than reported values from more complex models applied at the site such as the Two Source Model (TSM) or the Penman–Monteith Leuning model (PML). PT-JPL-daily model with a soil moisture constraint based on apparent thermal inertia, fSM-ATI offers great potential for regionalization as no field-calibrations are required and water vapor deficit estimates, required in the original version, are not necessary, being air temperature and the available energy (Rn-G) the only input variables required, apart from routinely available satellite products. [Copyright &y& Elsevier]