Evaluation of remote sensing-based evapotranspiration products at low-latitude eddy covariance sites

• Published in: Journal of hydrology (Amsterdam) 2022-07, Vol.610, p.127786, Article 127786
• Main Authors: Salazar-Martínez, Diego, Holwerda, Friso, Holmes, Thomas R.H., Yépez, Enrico A., Hain, Christopher R., Alvarado-Barrientos, Susana, Ángeles-Pérez, Gregorio, Arredondo-Moreno, Tulio, Delgado-Balbuena, Josué, Figueroa-Espinoza, Bernardo, Garatuza-Payán, Jaime, González del Castillo, Eugenia, Rodríguez, Julio C., Rojas-Robles, Nidia E., Uuh-Sonda, Jorge M., Vivoni, Enrique R.
• Format: Article
• Language: English
• Subjects: ALEXI; Earth Resources And Remote Sensing; GLEAM; MOD16; Subtropics; Tropics
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2022.127786

•Remote sensing ET products were evaluated at low-latitude eddy covariance sites.•GLEAM outperformed MOD16 and ALEXI when using unadjusted ET fluxes.•No clear ranking of products when using energy balance closure-corrected fluxes.•No relationship between product performance and vegetation-match pixel and site.•Latitudinal differences in evaluation results for forests, but not for non-forests. Remote sensing-based evapotranspiration (ET) products have been evaluated primarily using data from northern middle latitudes; therefore, little is known about their performance at low latitudes. To address this bias, an evaluation dataset was compiled using eddy covariance data from 40 sites between latitudes 30° S and 30° N. The flux data were obtained from the emerging network in Mexico (MexFlux) and from openly available databases of FLUXNET, AsiaFlux, and OzFlux. This unique reference dataset was then used to evaluate remote sensing-based ET products in environments that have been underrepresented in earlier studies. The evaluated products were: MODIS ET (MOD16, both the discontinued collection 5 (C5) and the latest collection (C6)), Global Land Evaporation Amsterdam Model (GLEAM) ET, and Atmosphere-Land Exchange Inverse (ALEXI) ET. Products were compared with unadjusted fluxes (ETorig) and with fluxes corrected for the lack of energy balance closure (ETebc). Three common statistical metrics were used: coefficient of determination (R2), root mean square error (RMSE), and percent bias (PBIAS). The effect of a vegetation mismatch between pixel and site on product evaluation results was investigated by examining the relationship between the statistical metrics and product-specific vegetation match indexes. Evaluation results of this study and those published in the literature were used to examine the performance of the products across latitudes. Differences between the MOD16 collection 5 and 6 datasets were generally smaller than differences with the other products. Performance and ranking of the evaluated products depended on whether ETorig or ETebc was used. When using ETorig, GLEAM generally had the highest R2, smallest PBIAS, and best RMSE values across the studied land cover types and climate zones. Neither MOD16 nor ALEXI performed consistently better than the other. When using ETebc, none of the products stood out in terms of both low bias and strong correlations. The use of ETebc instead of ETorig affected the biases more than the correlations. The product e