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.; Nóbrega, R. L. 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. M. S.; Antonino, A. C. D.; Holl, D.; Galleguillos, M.; Pérez Quezada, J. F.; Verhoef, A.; Kutzbach, L.; Lima, J. R. S.; Souza, E. S.; Gassmann, María Isabel; Perez, Claudio Fabian; Tonti, Natalia Edith; Posse, G.; 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). urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0001 was predicted satisfactorily by all four models, with correlations consistently higher (urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0002) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0003%). 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.
Fil: Melo, D. C. D.. Universidade Federal Da Paraíba; Brasil
Fil: Anache, J. A. A.. Universidade Federal do Mato Grosso do Sul; Brasil
Fil: Borges, V. P.. Universidade Federal Da Paraíba; Brasil
Fil: Miralles, D. G.. University of Ghent; Bélgica
Fil: Martens, B.. University of Ghent; Bélgica
Fil: Fisher, J. B.. Chapman University; Estados Unidos
Fil: Nóbrega, R. L. B.. Imperial College London; Reino Unido
Fil: Moreno, A.. University of Montana; Estados Unidos
Fil: Cabral, O. M. R.. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil
Fil: Rodrigues, T. R.. Universidade Federal do Mato Grosso do Sul; Brasil
Fil: Bezerra, B.. Universidade Federal do Rio Grande do Norte; Brasil
Fil: Silva, C. M. S.. Universidade Federal do Rio Grande do Norte; Brasil
Fil: Meira Neto, A. A.. University of Arizona; Estados Unidos
Fil: Moura, M. S. B.. Embrapa Tropical Semi-arid. Brazilian Agricultural Research Corporation; Brasil
Fil: Marques, T. V.. Universidade Federal do Rio Grande do Norte; Brasil
Fil: Campos, S.. Universidade Federal do Rio Grande do Norte; Brasil
Fil: Nogueira, J. S.. Universidade Federal de Mato Grosso; Brasil
Fil: Rosolem, R.. University of Bristol; Reino Unido
Fil: Souza, R. M. S.. Texas A&M University; Estados Unidos
Fil: Antonino, A. C. D.. Universidade Federal de Pernambuco; Brasil
Fil: Holl, D.. Universitat Hamburg; Alemania
Fil: Galleguillos, M.. Universidad de Chile; Chile
Fil: Pérez Quezada, J. F.. Universidad de Chile; Chile. Instituto de Ecología y Biodiversidad; Chile
Fil: Verhoef, A.. University of Reading; Reino Unido
Fil: Kutzbach, L.. Universitat Hamburg; Alemania
Fil: Lima, J. R. S.. Universidade Federal de Pernambuco; Brasil
Fil: Souza, E. S.. Universidad Federal Rural Pernambuco; Brasil
Fil: Gassmann, María Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina
Fil: Perez, Claudio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina
Fil: Tonti, Natalia Edith. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina
Fil: Posse, G.. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Fil: Rains, D.. University of Ghent; Bélgica
Fil: Oliveira, P. T. S.. Universidade Federal do Mato Grosso do Sul; Brasil
Fil: Wendland, E.. Universidade de Sao Paulo; Brasil - Materia
-
MODIS
PENMAN-MONTEITH
PRIESTLEY-TAYLOR
TRANSPIRATION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/163318
Ver los metadatos del registro completo
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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.Nóbrega, R. L. 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. M. S.Antonino, A. C. D.Holl, D.Galleguillos, M.Pérez Quezada, J. F.Verhoef, A.Kutzbach, L.Lima, J. R. S.Souza, E. S.Gassmann, María IsabelPerez, Claudio FabianTonti, Natalia EdithPosse, G.Rains, D.Oliveira, P. T. S.Wendland, E.MODISPENMAN-MONTEITHPRIESTLEY-TAYLORTRANSPIRATIONhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Many 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). urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0001 was predicted satisfactorily by all four models, with correlations consistently higher (urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0002) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0003%). 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.Fil: Melo, D. C. D.. Universidade Federal Da Paraíba; BrasilFil: Anache, J. A. A.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Borges, V. P.. Universidade Federal Da Paraíba; BrasilFil: Miralles, D. G.. University of Ghent; BélgicaFil: Martens, B.. University of Ghent; BélgicaFil: Fisher, J. B.. Chapman University; Estados UnidosFil: Nóbrega, R. L. B.. Imperial College London; Reino UnidoFil: Moreno, A.. University of Montana; Estados UnidosFil: Cabral, O. M. R.. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; BrasilFil: Rodrigues, T. R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Bezerra, B.. Universidade Federal do Rio Grande do Norte; BrasilFil: Silva, C. M. S.. Universidade Federal do Rio Grande do Norte; BrasilFil: Meira Neto, A. A.. University of Arizona; Estados UnidosFil: Moura, M. S. B.. Embrapa Tropical Semi-arid. Brazilian Agricultural Research Corporation; BrasilFil: Marques, T. V.. Universidade Federal do Rio Grande do Norte; BrasilFil: Campos, S.. Universidade Federal do Rio Grande do Norte; BrasilFil: Nogueira, J. S.. Universidade Federal de Mato Grosso; BrasilFil: Rosolem, R.. University of Bristol; Reino UnidoFil: Souza, R. M. S.. Texas A&M University; Estados UnidosFil: Antonino, A. C. D.. Universidade Federal de Pernambuco; BrasilFil: Holl, D.. Universitat Hamburg; AlemaniaFil: Galleguillos, M.. Universidad de Chile; ChileFil: Pérez Quezada, J. F.. Universidad de Chile; Chile. Instituto de Ecología y Biodiversidad; ChileFil: Verhoef, A.. University of Reading; Reino UnidoFil: Kutzbach, L.. Universitat Hamburg; AlemaniaFil: Lima, J. R. S.. Universidade Federal de Pernambuco; BrasilFil: Souza, E. S.. Universidad Federal Rural Pernambuco; BrasilFil: Gassmann, María Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; ArgentinaFil: Perez, Claudio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; ArgentinaFil: Tonti, Natalia Edith. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; ArgentinaFil: Posse, G.. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; ArgentinaFil: Rains, D.. University of Ghent; BélgicaFil: Oliveira, P. T. S.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Wendland, E.. Universidade de Sao Paulo; BrasilAmerican Geophysical Union2021-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/163318Melo, D. C. D.; Anache, J. A. A.; Borges, V. P.; Miralles, D. G.; Martens, B.; et al.; Are remote sensing evapotranspiration models reliable across South American ecoregions?; American Geophysical Union; Water Resources Research; 57; 11; 11-2021; 1-230043-1397CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020WR028752info:eu-repo/semantics/altIdentifier/doi/10.1029/2020WR028752info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:02:08Zoai:ri.conicet.gov.ar:11336/163318instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:02:08.602CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| 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. MODIS PENMAN-MONTEITH PRIESTLEY-TAYLOR TRANSPIRATION |
| 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. Nóbrega, R. L. 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. M. S. Antonino, A. C. D. Holl, D. Galleguillos, M. Pérez Quezada, J. F. Verhoef, A. Kutzbach, L. Lima, J. R. S. Souza, E. S. Gassmann, María Isabel Perez, Claudio Fabian Tonti, Natalia Edith Posse, G. 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. Nóbrega, R. L. 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. M. S. Antonino, A. C. D. Holl, D. Galleguillos, M. Pérez Quezada, J. F. Verhoef, A. Kutzbach, L. Lima, J. R. S. Souza, E. S. Gassmann, María Isabel Perez, Claudio Fabian Tonti, Natalia Edith Posse, G. 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. Nóbrega, R. L. 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. M. S. Antonino, A. C. D. Holl, D. Galleguillos, M. Pérez Quezada, J. F. Verhoef, A. Kutzbach, L. Lima, J. R. S. Souza, E. S. Gassmann, María Isabel Perez, Claudio Fabian Tonti, Natalia Edith Posse, G. 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 |
MODIS PENMAN-MONTEITH PRIESTLEY-TAYLOR TRANSPIRATION |
| topic |
MODIS PENMAN-MONTEITH PRIESTLEY-TAYLOR TRANSPIRATION |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 |
| 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). urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0001 was predicted satisfactorily by all four models, with correlations consistently higher (urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0002) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0003%). 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. Fil: Melo, D. C. D.. Universidade Federal Da Paraíba; Brasil Fil: Anache, J. A. A.. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Borges, V. P.. Universidade Federal Da Paraíba; Brasil Fil: Miralles, D. G.. University of Ghent; Bélgica Fil: Martens, B.. University of Ghent; Bélgica Fil: Fisher, J. B.. Chapman University; Estados Unidos Fil: Nóbrega, R. L. B.. Imperial College London; Reino Unido Fil: Moreno, A.. University of Montana; Estados Unidos Fil: Cabral, O. M. R.. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Rodrigues, T. R.. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Bezerra, B.. Universidade Federal do Rio Grande do Norte; Brasil Fil: Silva, C. M. S.. Universidade Federal do Rio Grande do Norte; Brasil Fil: Meira Neto, A. A.. University of Arizona; Estados Unidos Fil: Moura, M. S. B.. Embrapa Tropical Semi-arid. Brazilian Agricultural Research Corporation; Brasil Fil: Marques, T. V.. Universidade Federal do Rio Grande do Norte; Brasil Fil: Campos, S.. Universidade Federal do Rio Grande do Norte; Brasil Fil: Nogueira, J. S.. Universidade Federal de Mato Grosso; Brasil Fil: Rosolem, R.. University of Bristol; Reino Unido Fil: Souza, R. M. S.. Texas A&M University; Estados Unidos Fil: Antonino, A. C. D.. Universidade Federal de Pernambuco; Brasil Fil: Holl, D.. Universitat Hamburg; Alemania Fil: Galleguillos, M.. Universidad de Chile; Chile Fil: Pérez Quezada, J. F.. Universidad de Chile; Chile. Instituto de Ecología y Biodiversidad; Chile Fil: Verhoef, A.. University of Reading; Reino Unido Fil: Kutzbach, L.. Universitat Hamburg; Alemania Fil: Lima, J. R. S.. Universidade Federal de Pernambuco; Brasil Fil: Souza, E. S.. Universidad Federal Rural Pernambuco; Brasil Fil: Gassmann, María Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: Perez, Claudio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: Tonti, Natalia Edith. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: Posse, G.. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina Fil: Rains, D.. University of Ghent; Bélgica Fil: Oliveira, P. T. S.. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Wendland, E.. Universidade de Sao Paulo; 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). urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0001 was predicted satisfactorily by all four models, with correlations consistently higher (urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0002) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (urn:x-wiley:00431397:media:wrcr25611:wrcr25611-math-0003%). 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. |
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2021 |
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2021-11 |
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http://hdl.handle.net/11336/163318 Melo, D. C. D.; Anache, J. A. A.; Borges, V. P.; Miralles, D. G.; Martens, B.; et al.; Are remote sensing evapotranspiration models reliable across South American ecoregions?; American Geophysical Union; Water Resources Research; 57; 11; 11-2021; 1-23 0043-1397 CONICET Digital CONICET |
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http://hdl.handle.net/11336/163318 |
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Melo, D. C. D.; Anache, J. A. A.; Borges, V. P.; Miralles, D. G.; Martens, B.; et al.; Are remote sensing evapotranspiration models reliable across South American ecoregions?; American Geophysical Union; Water Resources Research; 57; 11; 11-2021; 1-23 0043-1397 CONICET Digital CONICET |
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eng |
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American Geophysical Union |
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American Geophysical Union |
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