Partitioning of evapotranspiration in remote sensing-based models
Type
ArticleAuthors
Talsma, Carl J.Good, Stephen P.
Jimenez, Carlos
Martens, Brecht
Fisher, Joshua B.
Miralles, Diego G.
McCabe, Matthew

Purdy, Adam J.
KAUST Department
Biological and Environmental Sciences and Engineering (BESE) DivisionEnvironmental Science and Engineering Program
Water Desalination and Reuse Research Center (WDRC)
Date
2018-06-14Online Publication Date
2018-06-14Print Publication Date
2018-10Permanent link to this record
http://hdl.handle.net/10754/630487
Metadata
Show full item recordAbstract
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%, r = 0.14–0.25, N = 35), interception (RMSD = 62–181%, r = 0.39–0.85, N = 13), and transpiration (RMSD = 54–114%, r = 0.33–0.55, N = 35) are relatively large compared to the combined estimates of total ET (RMSD = 35–49%, r = 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.Citation
Talsma CJ, Good SP, Jimenez C, Martens B, Fisher JB, et al. (2018) Partitioning of evapotranspiration in remote sensing-based models. Agricultural and Forest Meteorology 260-261: 131–143. Available: http://dx.doi.org/10.1016/j.agrformet.2018.05.010.Sponsors
CT and SPG acknowledge the support of the Betty Minor scholarship. JBF contributed to this research from the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged. JBF was supported in part by NASA’s SUSMAP, INCA, IDS, GRACE, and ECOSTRESS programs. MFM was supported by the King Abdullah University of Science and Technology. DGM acknowledges support from the European Research Council (ERC) under grant agreement n° 715254 (DRY–2–DRY). CJ acknowledges support from the EuropeanSpace Agency (ESA) under the project WACMOS-ET (Contract no. 4000106711/12/I-NB).Publisher
Elsevier BVAdditional Links
http://www.sciencedirect.com/science/article/pii/S016819231830162Xae974a485f413a2113503eed53cd6c53
10.1016/j.agrformet.2018.05.010