Data/hora: 22/06/2024 07:07:18

Biblioteca(s): | Embrapa Meio Ambiente; Embrapa Semiárido.
Data corrente: | 04/07/2022
Data da última atualização: | 04/07/2022
Autoria: | 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. de; MARQUES, T. V.; CAMPOS, S.; NOGUEIRA, J. S.; ROSOLEM, R.; SOUZA, R. M. S.; 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, G.; RAINS, D.; OLIVEIRA, P. T. S.; WENDLAND, E.
Afiliação: | D. C. D. MELO, UFPB; J. A. A. ANACHE, UFMS; V. P. BORGES, UFPB; D. G. MIRALLES, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; B. MARTENS, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; J. B. FISHER, Schmid College of Science and Technology, Chapman University, Orange, CA; R. L. B. NÓBREGA, Department of Life Sciences, Imperial College London; A. MORENO, Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT; OSVALDO MACHADO RODRIGUES CABRAL, CNPMA; T. R. RODRIGUES, UFMS; B. BEZERRA, UFRN; C. M. S. SILVA, UFRN; A. A. MEIRA NETO, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ; MAGNA SOELMA BESERRA DE MOURA, CPATSA; T. V. MARQUES, UFRN; S. CAMPOS, UFRN; J. S. NOGUEIRA, UFMT; R. ROSOLEM, University of Bristol, Bristol, UK; R. M. S. SOUZA, Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX; A. C. D. ANTONINO, UFPE; D. HOLL, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany; M. GALLEGUILLOS, Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile; J. F. PEREZ-QUEZADA, Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile; A. VERHOEF, Department of Geography and Environmental Science, The University of Reading, Reading, UK; L. KUTZBACH, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany; J. R. S. LIMA, Federal University of the Agreste of Pernambuco, Garanhuns, PE; E. S. SOUZA, UFRPE, Garanhuns, PE; M. I. GASSMAN, Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina; C. F. PEREZ, Department of Atmospheric and Ocean Sciences, FCEN ? UBA, Buenos Aires, Argentina; N. TONTI, Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina; G. POSSE, INTA; D. RAINS, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; P. T. S. OLIVEIRA, UFMS; E. WENDLAND, Department of Hydraulics and Sanitary Engineering, University of São Paulo, São Carlos, SP.
Título: | Are remote sensing evapotranspiration models reliable across South American ecoregions?
Ano de publicação: | 2021
Fonte/Imprenta: | Water Resources Research, v. 57, n. 11, e2020WR028752, 2021.
DOI: | https://doi.org/10.1029/2020WR028752
Idioma: | Inglês
Conteúdo: | 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.
Palavras-Chave: | MODIS; Penman-Monteith; Priestley-Taylor.
Thesagro: | Evapotranspiração; Sensoriamento Remoto; Vegetação.
Thesaurus Nal: | Remote sensing.
Categoria do assunto: | P Recursos Naturais, Ciências Ambientais e da Terra
Registro original: | Embrapa Meio Ambiente (CNPMA)

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