Partitioning of evapotranspiration in remote sensing-based models

by C.J. Talsma, S. P. Good, C. Jimenez, B. Martens, J. B. Fisher, D.G. Miralles, M.F. McCabe, A. J. Purdy
Year: 2018 DOI: 10.1016/j.agrformet.2018.05.010

Extra Information

Agricultural and Forest Meteorology, volumes 260 to 261, pp. 131-143, (2018)


Satellite based retrievals of evapotranspiration (ET) are widely used for assessments of global and regional scale surface fluxes. However, the partitioning of the estimated ET between soil evaporation, transpiration, and canopy interception regularly shows strong divergence between models, and to date, remains largely unvalidated. To examine this problem, this paper considers three algorithms: the Penman-Monteith model from the Moderate Resolution Imaging Spectroradiometer (PM-MODIS), the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL), and the Global Land Evaporation Amsterdam Model (GLEAM). Surface flux estimates from these three models, obtained via the WACMOS-ET initiative, are compared against a comprehensive collection of field studies, spanning a wide range of climates and land cover types. Overall, we find errors between estimates of field and remote sensing-based soil evaporation (RMSD = 90–114%, r2 = 0.14–0.25, N = 35), interception (RMSD = 62–181%, r2 = 0.39–0.85, N = 13), and transpiration (RMSD = 54–114%, r2  = 0.33–0.55, N = 35) are relatively large compared to the combined estimates of total ET (RMSD = 35–49%, r2 = 0.61–0.75, N = 35). Errors in modeled ET components are compared between land cover types, field methods, and precipitation regimes. Modeled estimates of soil evaporation were found to have significant deviations from observed values across all three models, while the characterization of vegetation effects also influences errors in all three components. Improvements in these estimates, and other satellite based partitioning estimates are likely to lead to better understanding of the movement of water through the soil-plant-water continuum.


Evapotranspiration Partitioning modeling Remote sensing Transpiration soil evaporation