Abstract
Many remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM-MOD), and Penman–Monteith Nagler model (PM-VI). (Formula presented.) was predicted satisfactorily by all four models, with correlations consistently higher ((Formula presented.)) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias ((Formula presented.) %). As for PM-VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land-use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America.
| Original language | English |
|---|---|
| Article number | e2020WR028752 |
| Journal | Water Resources Research |
| Volume | 57 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - Nov 2021 |
Bibliographical note
Funding Information:Funding for AmeriFlux data resources was provided by the U.S. Department of Energy’s Office of Science. Davi de C. D. Melo was supported by the São Paulo State Research Foundation (FAPESP) (grant 2016/23546‐7) and by the Brazilian National Council for Scientific and Technological Development (CNPq) (project 409093/2018‐1). Jamil A. A. Anache was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) (project 150057/2018‐0). Edson Wendland was supported by the São Paulo State Research Foundation (FAPESP) (grant 2015/03806‐1). Paulo Tarso S. Oliveira was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) (grants 441289/2017‐7 and 306830/2017‐5) and the CAPES Print program. Rafael Rosolem would like to acknowledge the Brazilian Experimental datasets for MUlti‐Scale interactions in the critical zone under Extreme Drought (BEMUSED) project (grant number NE/R004897/1) funded by the Natural Environment Research Council (NERC). Alvaro Moreno was financially supported by the NASA Earth Observing System MODIS project (grant NNX08AG87A) and the European Research Council (ERC) funding under the ERC Consolidator Grant 2014 SEDAL (Statistical Learning for Earth Observation Data Analysis, European Union) project under Grant Agreement 647423. Diego G. Miralles, Brecht Martens, and Dominik Rains are supported by the European Research Council (ERC) DRY‐2‐DRY project (grant no. 715254) and the Belgian Science Policy Office (BELSPO) STEREO III ALBERI (grant no. SR/00/373) and ET‐SENSE (grant. no SR/02/377) projects. Thiago R. Rodrigues was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) with Bolsa de Produtividade em Pesquisa ‐ PQ (Grant Number 308844/2018‐1). Jorge Perez‐Quezada and Mauricio Galleguillos were supported by the Chilean National Agency for Research and Development, grant FONDECYT 1211652. Rodolfo Nobrega and Anne Verhoef acknowledge support by the Newton/NERC/FAPESP Nordeste project (NE/N012526/1 ICL and NE/N012488/1 UoR). Gabriela Posse acknowledges support by AERN 3632 and PNNAT 1128023 INTA Projects. J. B. Fisher was supported in part by NASA: ECOSTRESS and SUSMAP. Funding for site support: NPW tower: Brazilian National Institute for Science and Technology in Wetlands (INCT‐INAU), Federal University of Mato Grosso (UFMT ‐ PGFA and PGAT), University of Cuiabá (UNIC), and SESC‐Pantanal; SDF tower: funded by the National Commission for Scientific and Technological Research (CONICYT, Chile) through grants FONDEQUIP AIC‐37 and AFB170008 from the Associative Research Program; TF1 and TF2 towers: funded by the Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy — EXC 177 ’CliSAP — Integrated Climate System Analysis and Prediction’ — contributing to the Center for Earth System Research and Sustainability (CEN) of Universität Hamburg and by DFG project KU 1418/6‐1; MCR and BAL towers: funded by the National Council for Scientific and Technological Research (CONICET, Argentina) grants PIP‐11220100100044 and PIP‐11220130100347CO, and by the National Agency for the Scientific and Technological Promotion (ANPCyT, Argentina) grant PICT 2010‐0554; CAA, CST, and ESEC Towers: funded by National Observatory of Water and Carbon Dynamics in the Caatinga Biome (INCT‐NOWCDCB), Federal University of Pernambuco (UFPE), FACEPE (Pernambuco State Research and Technology Foundation) through the Project Caatinga‐FLUX APQ 0062‐1.07/15.
Funding Information:
Funding for AmeriFlux data resources was provided by the U.S. Department of Energy’s Office of Science. Davi de C. D. Melo was supported by the São Paulo State Research Foundation (FAPESP) (grant 2016/23546-7) and by the Brazilian National Council for Scientific and Technological Development (CNPq) (project 409093/2018-1). Jamil A. A. Anache was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) (project 150057/2018-0). Edson Wendland was supported by the São Paulo State Research Foundation (FAPESP) (grant 2015/03806-1). Paulo Tarso S. Oliveira was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) (grants 441289/2017-7 and 306830/2017-5) and the CAPES Print program. Rafael Rosolem would like to acknowledge the Brazilian Experimental datasets for MUlti-Scale interactions in the critical zone under Extreme Drought (BEMUSED) project (grant number NE/R004897/1) funded by the Natural Environment Research Council (NERC). Alvaro Moreno was financially supported by the NASA Earth Observing System MODIS project (grant NNX08AG87A) and the European Research Council (ERC) funding under the ERC Consolidator Grant 2014 SEDAL (Statistical Learning for Earth Observation Data Analysis, European Union) project under Grant Agreement 647423. Diego G. Miralles, Brecht Martens, and Dominik Rains are supported by the European Research Council (ERC) DRY-2-DRY project (grant no. 715254) and the Belgian Science Policy Office (BELSPO) STEREO III ALBERI (grant no. SR/00/373) and ET-SENSE (grant. no SR/02/377) projects. Thiago R. Rodrigues was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) with Bolsa de Produtividade em Pesquisa - PQ (Grant Number 308844/2018-1). Jorge Perez-Quezada and Mauricio Galleguillos were supported by the Chilean National Agency for Research and Development, grant FONDECYT 1211652. Rodolfo Nobrega and Anne Verhoef acknowledge support by the Newton/NERC/FAPESP Nordeste project (NE/N012526/1 ICL and NE/N012488/1 UoR). Gabriela Posse acknowledges support by AERN 3632 and PNNAT 1128023 INTA Projects. J. B. Fisher was supported in part by NASA: ECOSTRESS and SUSMAP. Funding for site support: NPW tower: Brazilian National Institute for Science and Technology in Wetlands (INCT-INAU), Federal University of Mato Grosso (UFMT - PGFA and PGAT), University of Cuiabá (UNIC), and SESC-Pantanal; SDF tower: funded by the National Commission for Scientific and Technological Research (CONICYT, Chile) through grants FONDEQUIP AIC-37 and AFB170008 from the Associative Research Program; TF1 and TF2 towers: funded by the Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy — EXC 177 ’CliSAP — Integrated Climate System Analysis and Prediction’ — contributing to the Center for Earth System Research and Sustainability (CEN) of Universität Hamburg and by DFG project KU 1418/6-1; MCR and BAL towers: funded by the National Council for Scientific and Technological Research (CONICET, Argentina) grants PIP-11220100100044 and PIP-11220130100347CO, and by the National Agency for the Scientific and Technological Promotion (ANPCyT, Argentina) grant PICT 2010-0554; CAA, CST, and ESEC Towers: funded by National Observatory of Water and Carbon Dynamics in the Caatinga Biome (INCT-NOWCDCB), Federal University of Pernambuco (UFPE), FACEPE (Pernambuco State Research and Technology Foundation) through the Project Caatinga-FLUX APQ 0062-1.07/15.
Publisher Copyright:
© 2021. American Geophysical Union. All Rights Reserved.
Research Groups and Themes
- Water and Environmental Engineering
Keywords
- MODIS
- Penman-Monteith
- Priestley-Taylor
- transpiration
