Are remote sensing evapotranspiration models reliable across South American ecoregions?

Autores
Melo, D.C.D.; Anache, J.A.A.; Borges, V.P.; Miralles, D.G.; Martens, B.; Fisher, J.B.; Nobrega, R.C.B.; Moreno, A.; Cabral, O.M.R.; Rodrigues, T.R.; Bezerra, B.; Silva, C.M.S.; Meira Neto, A.A.; Moura, M.S.B.; Marques, T.V.; Campos, S.; Nogueira, J.S.; Rosolem, R.; Souza, R.; Antonino, A.C.D.; Holl, D.; Galleguillos, M.; Perez-Quezada, J.F.; Verhoef, A.; Kutzbach, L.; Lima, J.R.S.; Souza, E.S.; Gassman, M.I.; Perez, C.F.; Tonti, N.; Posse Beaulieu, Gabriela; Rains, D.; Oliveira, P.T.S.; Wendland, E.
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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). E ET was predicted satisfactorily by all four models, with correlations consistently higher (20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias ( 1010EPBIAS%). 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.MELO ET AL.© 2021. American Geophysical Union. All Rights Reserved.Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions?D. C. D. Melo1, J. A. A. Anache2, V. P. Borges1, D. G. Miralles3, B. Martens3, J. B. Fisher4, R. L. B. Nóbrega5, A. Moreno6, O. M. R. Cabral7, T. R. Rodrigues2, B. Bezerra8,9, C. M. S. Silva8,9, A. A. Meira Neto10, M. S. B. Moura11, T. V. Marques9, S. Campos9, J. S. Nogueira12, R. Rosolem13, R. M. S. Souza14, A. C. D. Antonino15, D. Holl16, M. Galleguillos17, J. F. Perez-Quezada17,18, A. Verhoef19, L. Kutzbach16, J. R. S. Lima20, E. S. Souza21, M. I. Gassman22,23, C. F. Perez22,23, N. Tonti22, G. Posse24, D. Rains3, P. T. S. Oliveira2, and E. Wendland251Federal University of Paraíba, Areia, PB, Brazil, 2Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil, 3Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium, 4Schmid College of Science and Technology, Chapman University, Orange, CA, USA, 5Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, UK, 6Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA, 7Brazilian Agricultural Research Corporation, Embrapa Meio Ambiente, Jaguariúna, SP, Brazil, 8Department of Atmospheric and Climate Sciences, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 9Climate Sciences Graduate Program, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 10Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ, USA, 11Brazilian Agricultural Research Corporation — Embrapa Tropical Semi-arid, Petrolina, PE, Brazil, 12Federal University of Mato Grosso, Cuiabá, MT, Brazil, 13University of Bristol, Bristol, UK, 14Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX, USA, 15Department of Nuclear Energy, Federal University of Pernambuco, Recife, PE, Brazil, 16Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany, 17Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile, 18Institute of Ecology and Biodiversity, Santiago, Chile, 19Department of Geography and Environmental Science, The University of Reading, Reading, UK, 20Federal University of the Agreste of Pernambuco, Garanhuns, PE, Brazil, 21Federal Rural University of Pernambuco, Serra Talhada, PE, Brazil, 22Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina, 23National Council for Scientific and Technical Research, CONICET, Buenos Aires, Argentina, 24Instituto de Clima y Agua. Instituto Nacional de Tecnología Agropecuaria (INTA), Hurlingham, Argentina, 25Department of Hydraulics and Sanitary Engineering, University of São Paulo, São Carlos, SP, BrazilKey Points:•Four remote sensing evapotranspiration (ET) models were evaluated using 25 flux towers from across South America•Performance of all models is reduced in dry environments•Comparisons with flux tower-based ET showed that Global Land Evaporation Amsterdam Model and Priestley–Taylor Jet Propulsion Laboratory produced higher correlations whereas RMSE was similar for all modelsSupporting Information:Supporting Information may be found in the online version of this article.Correspondence to:D. C. D. Melo,melo.dcd@gmail.comCitation:Melo, D. C. D., Anache, J. A. A., Borges, V. P., Miralles, D. G., Martens, B., Fisher, J. B., et al. (2021). Are remote sensing evapotranspiration models reliable across South American ecoregions? Water Resources Research, 57, e2020WR028752. https://doi.org/10.1029/2020WR028752Received 26 APR 2021Accepted 11 OCT 202110.1029/2020WR028752RESEARCH ARTICLE1 of 23
Fil: Melo, D.C.D. Federal University of Paracaıba; Brasil
Fil: Anache, J.A.A. Federal University of Mato Grosso do Sul; Brasil
Fil: Borges, B.P. Federal University of Paracaıba; Brasil
Fil: Miralles, D.G. Ghent University. Hydro-Climate Extremes Lab (H-CEL); Bélgica
Fil: Martens, B. Ghent University. Hydro-Climate Extremes Lab (H-CEL); Bélgica
Fil: Fisher, J.B. Chapman University. Schmid College of Science and Technology; Estados Unidos
Fil: Nóbrega, R.L.B. Imperial College London. Department of Life Sciences; Reino Unido
Fil: Moreno, A. University of Montana. Numerical Terradynamic Simulation Group; Estados Unidos
Fil: Cabral, O.M.R. Embrapa Meio Ambiente. Brazilian Agricultural Research Corporation; Brasil
Fil: Rodrigues, T.R. Federal University of Mato Grosso do Sul; Brasil
Fil: Bezerra, B. Federal University of Rio Grande do Norte. Department of Atmospheric and Climate Sciences; Brasil. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil
Fil: Silva. C.M.S. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil. University of Arizona. Department of Hydrology and Atmospheric Sciences; Estados Unidos
Fil: Meira Neto, A.A. University of Arizona. Department of Hydrology and Atmospheric Sciences; Estados Unidos
Fil: Moura, M.S.B. Embrapa Tropical Semi-arid. Brazilian Agricultural Research Corporation; Brasil
Fil: Marques, T.V. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil.
Fil: Campos, S. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil.
Fil: Nogueira, J.S. Federal University of Mato Grosso do Sul; Brasil
Fil: Rosolem, R. University of Bristol; Reino Unido
Fil: Souza, R. Texas A&M University. Department of Biological and Agricultural Engineering. College Station; Estados Unidos
Fil: Antonino, A.C.D. Federal University of Pernambuco. Department of Nuclear Energy; Brasil
Fil: Holl, D. Universitat Hamburg. Center for Earth System Research and Sustainability (CEN); Alemania
Fil: Galleguillos, M. University of Chile. Department of Environmental Science and Renewable Natural Resources; Chile
Fil: Perez-Quezada, J.F. University of Chile. Department of Environmental Science and Renewable Natural Resources; Chile. Institute of Ecology and Biodiversity; Chile
Fil: Verhoef, A. University of Reading. Department of Geography and Environmental Science; Reino Unido
Fil: Kutzbach, L. Universitat Hamburg. Center for Earth System Research and Sustainability (CEN); Alemania
Fil: Lima, J.R.S. Federal University of the Agreste of Pernambuco; Brasil
Fil: Souza, E.S. Federal Rural University of Pernambuco; Brasil
Fil: Gassman, M.I. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Pérez, C.F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Tonti, N. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina.
Fil: Posse Beaulieu, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Rains, D. Ghent University. Hydro-Climate Extremes Lab (H-CEL); Bélgica
Fil: Oliveira, P.T.S. Federal University of Mato Grosso do Sul; Brasil
Fil: Wendland, E. University of Sao Paulo. Department of Hydraulics and Sanitary Engineering; Brasil
Fuente
Water Resources Research 57 (11) : e2020WR028752. (November 2021)
Materia
Remote Sensing
Evapotranspiration
Yields
Remote Sensors
Teledetección
Evapotranspiración
Rendimiento
Equipo de Teledetección
Torres de Flujo
Flux Towers
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
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spelling Are remote sensing evapotranspiration models reliable across South American ecoregions?Melo, D.C.D.Anache, J.A.A.Borges, V.P.Miralles, D.G.Martens, B.Fisher, J.B.Nobrega, R.C.B.Moreno, A.Cabral, O.M.R.Rodrigues, T.R.Bezerra, B.Silva, C.M.S.Meira Neto, A.A.Moura, M.S.B.Marques, T.V.Campos, S.Nogueira, J.S.Rosolem, R.Souza, R.Antonino, A.C.D.Holl, D.Galleguillos, M.Perez-Quezada, J.F.Verhoef, A.Kutzbach, L.Lima, J.R.S.Souza, E.S.Gassman, M.I.Perez, C.F.Tonti, N.Posse Beaulieu, GabrielaRains, D.Oliveira, P.T.S.Wendland, E.Remote SensingEvapotranspirationYieldsRemote SensorsTeledetecciónEvapotranspiraciónRendimientoEquipo de TeledetecciónTorres de FlujoFlux TowersMany 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). E ET was predicted satisfactorily by all four models, with correlations consistently higher (20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias ( 1010EPBIAS%). 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.MELO ET AL.© 2021. American Geophysical Union. All Rights Reserved.Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions?D. C. D. Melo1, J. A. A. Anache2, V. P. Borges1, D. G. Miralles3, B. Martens3, J. B. Fisher4, R. L. B. Nóbrega5, A. Moreno6, O. M. R. Cabral7, T. R. Rodrigues2, B. Bezerra8,9, C. M. S. Silva8,9, A. A. Meira Neto10, M. S. B. Moura11, T. V. Marques9, S. Campos9, J. S. Nogueira12, R. Rosolem13, R. M. S. Souza14, A. C. D. Antonino15, D. Holl16, M. Galleguillos17, J. F. Perez-Quezada17,18, A. Verhoef19, L. Kutzbach16, J. R. S. Lima20, E. S. Souza21, M. I. Gassman22,23, C. F. Perez22,23, N. Tonti22, G. Posse24, D. Rains3, P. T. S. Oliveira2, and E. Wendland251Federal University of Paraíba, Areia, PB, Brazil, 2Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil, 3Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium, 4Schmid College of Science and Technology, Chapman University, Orange, CA, USA, 5Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, UK, 6Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA, 7Brazilian Agricultural Research Corporation, Embrapa Meio Ambiente, Jaguariúna, SP, Brazil, 8Department of Atmospheric and Climate Sciences, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 9Climate Sciences Graduate Program, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 10Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ, USA, 11Brazilian Agricultural Research Corporation — Embrapa Tropical Semi-arid, Petrolina, PE, Brazil, 12Federal University of Mato Grosso, Cuiabá, MT, Brazil, 13University of Bristol, Bristol, UK, 14Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX, USA, 15Department of Nuclear Energy, Federal University of Pernambuco, Recife, PE, Brazil, 16Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany, 17Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile, 18Institute of Ecology and Biodiversity, Santiago, Chile, 19Department of Geography and Environmental Science, The University of Reading, Reading, UK, 20Federal University of the Agreste of Pernambuco, Garanhuns, PE, Brazil, 21Federal Rural University of Pernambuco, Serra Talhada, PE, Brazil, 22Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina, 23National Council for Scientific and Technical Research, CONICET, Buenos Aires, Argentina, 24Instituto de Clima y Agua. Instituto Nacional de Tecnología Agropecuaria (INTA), Hurlingham, Argentina, 25Department of Hydraulics and Sanitary Engineering, University of São Paulo, São Carlos, SP, BrazilKey Points:•Four remote sensing evapotranspiration (ET) models were evaluated using 25 flux towers from across South America•Performance of all models is reduced in dry environments•Comparisons with flux tower-based ET showed that Global Land Evaporation Amsterdam Model and Priestley–Taylor Jet Propulsion Laboratory produced higher correlations whereas RMSE was similar for all modelsSupporting Information:Supporting Information may be found in the online version of this article.Correspondence to:D. C. D. Melo,melo.dcd@gmail.comCitation:Melo, D. C. D., Anache, J. A. A., Borges, V. P., Miralles, D. G., Martens, B., Fisher, J. B., et al. (2021). Are remote sensing evapotranspiration models reliable across South American ecoregions? Water Resources Research, 57, e2020WR028752. https://doi.org/10.1029/2020WR028752Received 26 APR 2021Accepted 11 OCT 202110.1029/2020WR028752RESEARCH ARTICLE1 of 23Fil: Melo, D.C.D. Federal University of Paracaıba; BrasilFil: Anache, J.A.A. Federal University of Mato Grosso do Sul; BrasilFil: Borges, B.P. Federal University of Paracaıba; BrasilFil: Miralles, D.G. Ghent University. Hydro-Climate Extremes Lab (H-CEL); BélgicaFil: Martens, B. Ghent University. Hydro-Climate Extremes Lab (H-CEL); BélgicaFil: Fisher, J.B. Chapman University. Schmid College of Science and Technology; Estados UnidosFil: Nóbrega, R.L.B. Imperial College London. Department of Life Sciences; Reino UnidoFil: Moreno, A. University of Montana. Numerical Terradynamic Simulation Group; Estados UnidosFil: Cabral, O.M.R. Embrapa Meio Ambiente. Brazilian Agricultural Research Corporation; BrasilFil: Rodrigues, T.R. Federal University of Mato Grosso do Sul; BrasilFil: Bezerra, B. Federal University of Rio Grande do Norte. Department of Atmospheric and Climate Sciences; Brasil. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; BrasilFil: Silva. C.M.S. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil. University of Arizona. Department of Hydrology and Atmospheric Sciences; Estados UnidosFil: Meira Neto, A.A. University of Arizona. Department of Hydrology and Atmospheric Sciences; Estados UnidosFil: Moura, M.S.B. Embrapa Tropical Semi-arid. Brazilian Agricultural Research Corporation; BrasilFil: Marques, T.V. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil.Fil: Campos, S. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil.Fil: Nogueira, J.S. Federal University of Mato Grosso do Sul; BrasilFil: Rosolem, R. University of Bristol; Reino UnidoFil: Souza, R. Texas A&M University. Department of Biological and Agricultural Engineering. College Station; Estados UnidosFil: Antonino, A.C.D. Federal University of Pernambuco. Department of Nuclear Energy; BrasilFil: Holl, D. Universitat Hamburg. Center for Earth System Research and Sustainability (CEN); AlemaniaFil: Galleguillos, M. University of Chile. Department of Environmental Science and Renewable Natural Resources; ChileFil: Perez-Quezada, J.F. University of Chile. Department of Environmental Science and Renewable Natural Resources; Chile. Institute of Ecology and Biodiversity; ChileFil: Verhoef, A. University of Reading. Department of Geography and Environmental Science; Reino UnidoFil: Kutzbach, L. Universitat Hamburg. Center for Earth System Research and Sustainability (CEN); AlemaniaFil: Lima, J.R.S. Federal University of the Agreste of Pernambuco; BrasilFil: Souza, E.S. Federal Rural University of Pernambuco; BrasilFil: Gassman, M.I. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pérez, C.F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tonti, N. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina.Fil: Posse Beaulieu, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Rains, D. Ghent University. Hydro-Climate Extremes Lab (H-CEL); BélgicaFil: Oliveira, P.T.S. Federal University of Mato Grosso do Sul; BrasilFil: Wendland, E. University of Sao Paulo. Department of Hydraulics and Sanitary Engineering; BrasilWiley2022-04-19T10:46:01Z2022-04-19T10:46:01Z2021-11-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/11670https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020WR0287520043-1397https://doi.org/10.1029/2020WR028752Water Resources Research 57 (11) : e2020WR028752. 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dc.title.none.fl_str_mv Are remote sensing evapotranspiration models reliable across South American ecoregions?
title Are remote sensing evapotranspiration models reliable across South American ecoregions?
spellingShingle Are remote sensing evapotranspiration models reliable across South American ecoregions?
Melo, D.C.D.
Remote Sensing
Evapotranspiration
Yields
Remote Sensors
Teledetección
Evapotranspiración
Rendimiento
Equipo de Teledetección
Torres de Flujo
Flux Towers
title_short Are remote sensing evapotranspiration models reliable across South American ecoregions?
title_full Are remote sensing evapotranspiration models reliable across South American ecoregions?
title_fullStr Are remote sensing evapotranspiration models reliable across South American ecoregions?
title_full_unstemmed Are remote sensing evapotranspiration models reliable across South American ecoregions?
title_sort Are remote sensing evapotranspiration models reliable across South American ecoregions?
dc.creator.none.fl_str_mv Melo, D.C.D.
Anache, J.A.A.
Borges, V.P.
Miralles, D.G.
Martens, B.
Fisher, J.B.
Nobrega, R.C.B.
Moreno, A.
Cabral, O.M.R.
Rodrigues, T.R.
Bezerra, B.
Silva, C.M.S.
Meira Neto, A.A.
Moura, M.S.B.
Marques, T.V.
Campos, S.
Nogueira, J.S.
Rosolem, R.
Souza, R.
Antonino, A.C.D.
Holl, D.
Galleguillos, M.
Perez-Quezada, J.F.
Verhoef, A.
Kutzbach, L.
Lima, J.R.S.
Souza, E.S.
Gassman, M.I.
Perez, C.F.
Tonti, N.
Posse Beaulieu, Gabriela
Rains, D.
Oliveira, P.T.S.
Wendland, E.
author Melo, D.C.D.
author_facet Melo, D.C.D.
Anache, J.A.A.
Borges, V.P.
Miralles, D.G.
Martens, B.
Fisher, J.B.
Nobrega, R.C.B.
Moreno, A.
Cabral, O.M.R.
Rodrigues, T.R.
Bezerra, B.
Silva, C.M.S.
Meira Neto, A.A.
Moura, M.S.B.
Marques, T.V.
Campos, S.
Nogueira, J.S.
Rosolem, R.
Souza, R.
Antonino, A.C.D.
Holl, D.
Galleguillos, M.
Perez-Quezada, J.F.
Verhoef, A.
Kutzbach, L.
Lima, J.R.S.
Souza, E.S.
Gassman, M.I.
Perez, C.F.
Tonti, N.
Posse Beaulieu, Gabriela
Rains, D.
Oliveira, P.T.S.
Wendland, E.
author_role author
author2 Anache, J.A.A.
Borges, V.P.
Miralles, D.G.
Martens, B.
Fisher, J.B.
Nobrega, R.C.B.
Moreno, A.
Cabral, O.M.R.
Rodrigues, T.R.
Bezerra, B.
Silva, C.M.S.
Meira Neto, A.A.
Moura, M.S.B.
Marques, T.V.
Campos, S.
Nogueira, J.S.
Rosolem, R.
Souza, R.
Antonino, A.C.D.
Holl, D.
Galleguillos, M.
Perez-Quezada, J.F.
Verhoef, A.
Kutzbach, L.
Lima, J.R.S.
Souza, E.S.
Gassman, M.I.
Perez, C.F.
Tonti, N.
Posse Beaulieu, Gabriela
Rains, D.
Oliveira, P.T.S.
Wendland, E.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Remote Sensing
Evapotranspiration
Yields
Remote Sensors
Teledetección
Evapotranspiración
Rendimiento
Equipo de Teledetección
Torres de Flujo
Flux Towers
topic Remote Sensing
Evapotranspiration
Yields
Remote Sensors
Teledetección
Evapotranspiración
Rendimiento
Equipo de Teledetección
Torres de Flujo
Flux Towers
dc.description.none.fl_txt_mv 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). E ET was predicted satisfactorily by all four models, with correlations consistently higher (20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias ( 1010EPBIAS%). 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.MELO ET AL.© 2021. American Geophysical Union. All Rights Reserved.Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions?D. C. D. Melo1, J. A. A. Anache2, V. P. Borges1, D. G. Miralles3, B. Martens3, J. B. Fisher4, R. L. B. Nóbrega5, A. Moreno6, O. M. R. Cabral7, T. R. Rodrigues2, B. Bezerra8,9, C. M. S. Silva8,9, A. A. Meira Neto10, M. S. B. Moura11, T. V. Marques9, S. Campos9, J. S. Nogueira12, R. Rosolem13, R. M. S. Souza14, A. C. D. Antonino15, D. Holl16, M. Galleguillos17, J. F. Perez-Quezada17,18, A. Verhoef19, L. Kutzbach16, J. R. S. Lima20, E. S. Souza21, M. I. Gassman22,23, C. F. Perez22,23, N. Tonti22, G. Posse24, D. Rains3, P. T. S. Oliveira2, and E. Wendland251Federal University of Paraíba, Areia, PB, Brazil, 2Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil, 3Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium, 4Schmid College of Science and Technology, Chapman University, Orange, CA, USA, 5Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, UK, 6Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA, 7Brazilian Agricultural Research Corporation, Embrapa Meio Ambiente, Jaguariúna, SP, Brazil, 8Department of Atmospheric and Climate Sciences, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 9Climate Sciences Graduate Program, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 10Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ, USA, 11Brazilian Agricultural Research Corporation — Embrapa Tropical Semi-arid, Petrolina, PE, Brazil, 12Federal University of Mato Grosso, Cuiabá, MT, Brazil, 13University of Bristol, Bristol, UK, 14Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX, USA, 15Department of Nuclear Energy, Federal University of Pernambuco, Recife, PE, Brazil, 16Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany, 17Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile, 18Institute of Ecology and Biodiversity, Santiago, Chile, 19Department of Geography and Environmental Science, The University of Reading, Reading, UK, 20Federal University of the Agreste of Pernambuco, Garanhuns, PE, Brazil, 21Federal Rural University of Pernambuco, Serra Talhada, PE, Brazil, 22Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina, 23National Council for Scientific and Technical Research, CONICET, Buenos Aires, Argentina, 24Instituto de Clima y Agua. Instituto Nacional de Tecnología Agropecuaria (INTA), Hurlingham, Argentina, 25Department of Hydraulics and Sanitary Engineering, University of São Paulo, São Carlos, SP, BrazilKey Points:•Four remote sensing evapotranspiration (ET) models were evaluated using 25 flux towers from across South America•Performance of all models is reduced in dry environments•Comparisons with flux tower-based ET showed that Global Land Evaporation Amsterdam Model and Priestley–Taylor Jet Propulsion Laboratory produced higher correlations whereas RMSE was similar for all modelsSupporting Information:Supporting Information may be found in the online version of this article.Correspondence to:D. C. D. Melo,melo.dcd@gmail.comCitation:Melo, D. C. D., Anache, J. A. A., Borges, V. P., Miralles, D. G., Martens, B., Fisher, J. B., et al. (2021). Are remote sensing evapotranspiration models reliable across South American ecoregions? Water Resources Research, 57, e2020WR028752. https://doi.org/10.1029/2020WR028752Received 26 APR 2021Accepted 11 OCT 202110.1029/2020WR028752RESEARCH ARTICLE1 of 23
Fil: Melo, D.C.D. Federal University of Paracaıba; Brasil
Fil: Anache, J.A.A. Federal University of Mato Grosso do Sul; Brasil
Fil: Borges, B.P. Federal University of Paracaıba; Brasil
Fil: Miralles, D.G. Ghent University. Hydro-Climate Extremes Lab (H-CEL); Bélgica
Fil: Martens, B. Ghent University. Hydro-Climate Extremes Lab (H-CEL); Bélgica
Fil: Fisher, J.B. Chapman University. Schmid College of Science and Technology; Estados Unidos
Fil: Nóbrega, R.L.B. Imperial College London. Department of Life Sciences; Reino Unido
Fil: Moreno, A. University of Montana. Numerical Terradynamic Simulation Group; Estados Unidos
Fil: Cabral, O.M.R. Embrapa Meio Ambiente. Brazilian Agricultural Research Corporation; Brasil
Fil: Rodrigues, T.R. Federal University of Mato Grosso do Sul; Brasil
Fil: Bezerra, B. Federal University of Rio Grande do Norte. Department of Atmospheric and Climate Sciences; Brasil. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil
Fil: Silva. C.M.S. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil. University of Arizona. Department of Hydrology and Atmospheric Sciences; Estados Unidos
Fil: Meira Neto, A.A. University of Arizona. Department of Hydrology and Atmospheric Sciences; Estados Unidos
Fil: Moura, M.S.B. Embrapa Tropical Semi-arid. Brazilian Agricultural Research Corporation; Brasil
Fil: Marques, T.V. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil.
Fil: Campos, S. Federal University of Rio Grande do Norte. Climate Sciences Graduate Program; Brasil.
Fil: Nogueira, J.S. Federal University of Mato Grosso do Sul; Brasil
Fil: Rosolem, R. University of Bristol; Reino Unido
Fil: Souza, R. Texas A&M University. Department of Biological and Agricultural Engineering. College Station; Estados Unidos
Fil: Antonino, A.C.D. Federal University of Pernambuco. Department of Nuclear Energy; Brasil
Fil: Holl, D. Universitat Hamburg. Center for Earth System Research and Sustainability (CEN); Alemania
Fil: Galleguillos, M. University of Chile. Department of Environmental Science and Renewable Natural Resources; Chile
Fil: Perez-Quezada, J.F. University of Chile. Department of Environmental Science and Renewable Natural Resources; Chile. Institute of Ecology and Biodiversity; Chile
Fil: Verhoef, A. University of Reading. Department of Geography and Environmental Science; Reino Unido
Fil: Kutzbach, L. Universitat Hamburg. Center for Earth System Research and Sustainability (CEN); Alemania
Fil: Lima, J.R.S. Federal University of the Agreste of Pernambuco; Brasil
Fil: Souza, E.S. Federal Rural University of Pernambuco; Brasil
Fil: Gassman, M.I. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Pérez, C.F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Tonti, N. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Department of Atmospheric and Ocean Sciences; Argentina.
Fil: Posse Beaulieu, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Rains, D. Ghent University. Hydro-Climate Extremes Lab (H-CEL); Bélgica
Fil: Oliveira, P.T.S. Federal University of Mato Grosso do Sul; Brasil
Fil: Wendland, E. University of Sao Paulo. Department of Hydraulics and Sanitary Engineering; Brasil
description 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). E ET was predicted satisfactorily by all four models, with correlations consistently higher (20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias ( 1010EPBIAS%). 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.MELO ET AL.© 2021. American Geophysical Union. All Rights Reserved.Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions?D. C. D. Melo1, J. A. A. Anache2, V. P. Borges1, D. G. Miralles3, B. Martens3, J. B. Fisher4, R. L. B. Nóbrega5, A. Moreno6, O. M. R. Cabral7, T. R. Rodrigues2, B. Bezerra8,9, C. M. S. Silva8,9, A. A. Meira Neto10, M. S. B. Moura11, T. V. Marques9, S. Campos9, J. S. Nogueira12, R. Rosolem13, R. M. S. Souza14, A. C. D. Antonino15, D. Holl16, M. Galleguillos17, J. F. Perez-Quezada17,18, A. Verhoef19, L. Kutzbach16, J. R. S. Lima20, E. S. Souza21, M. I. Gassman22,23, C. F. Perez22,23, N. Tonti22, G. Posse24, D. Rains3, P. T. S. Oliveira2, and E. Wendland251Federal University of Paraíba, Areia, PB, Brazil, 2Federal University of Mato Grosso do Sul, Campo Grande, MS, Brazil, 3Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium, 4Schmid College of Science and Technology, Chapman University, Orange, CA, USA, 5Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, UK, 6Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA, 7Brazilian Agricultural Research Corporation, Embrapa Meio Ambiente, Jaguariúna, SP, Brazil, 8Department of Atmospheric and Climate Sciences, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 9Climate Sciences Graduate Program, Federal University of Rio Grande do Norte, Natal, RN, Brazil, 10Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ, USA, 11Brazilian Agricultural Research Corporation — Embrapa Tropical Semi-arid, Petrolina, PE, Brazil, 12Federal University of Mato Grosso, Cuiabá, MT, Brazil, 13University of Bristol, Bristol, UK, 14Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX, USA, 15Department of Nuclear Energy, Federal University of Pernambuco, Recife, PE, Brazil, 16Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany, 17Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile, 18Institute of Ecology and Biodiversity, Santiago, Chile, 19Department of Geography and Environmental Science, The University of Reading, Reading, UK, 20Federal University of the Agreste of Pernambuco, Garanhuns, PE, Brazil, 21Federal Rural University of Pernambuco, Serra Talhada, PE, Brazil, 22Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina, 23National Council for Scientific and Technical Research, CONICET, Buenos Aires, Argentina, 24Instituto de Clima y Agua. Instituto Nacional de Tecnología Agropecuaria (INTA), Hurlingham, Argentina, 25Department of Hydraulics and Sanitary Engineering, University of São Paulo, São Carlos, SP, BrazilKey Points:•Four remote sensing evapotranspiration (ET) models were evaluated using 25 flux towers from across South America•Performance of all models is reduced in dry environments•Comparisons with flux tower-based ET showed that Global Land Evaporation Amsterdam Model and Priestley–Taylor Jet Propulsion Laboratory produced higher correlations whereas RMSE was similar for all modelsSupporting Information:Supporting Information may be found in the online version of this article.Correspondence to:D. C. D. Melo,melo.dcd@gmail.comCitation:Melo, D. C. D., Anache, J. A. A., Borges, V. P., Miralles, D. G., Martens, B., Fisher, J. B., et al. (2021). Are remote sensing evapotranspiration models reliable across South American ecoregions? Water Resources Research, 57, e2020WR028752. https://doi.org/10.1029/2020WR028752Received 26 APR 2021Accepted 11 OCT 202110.1029/2020WR028752RESEARCH ARTICLE1 of 23
publishDate 2021
dc.date.none.fl_str_mv 2021-11-01
2022-04-19T10:46:01Z
2022-04-19T10:46:01Z
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info:ar-repo/semantics/articulo
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dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/11670
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020WR028752
0043-1397
https://doi.org/10.1029/2020WR028752
url http://hdl.handle.net/20.500.12123/11670
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020WR028752
https://doi.org/10.1029/2020WR028752
identifier_str_mv 0043-1397
dc.language.none.fl_str_mv eng
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eu_rights_str_mv restrictedAccess
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dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv Water Resources Research 57 (11) : e2020WR028752. (November 2021)
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repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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