Cuantificación de la evapotranspiración real mediante teledetección en cuencas hidrográficas: modelos, desempeño y limitaciones
DOI:
https://doi.org/10.5281/zenodo.23318228Palabras clave:
Balance de energía, Balance hídrico, Gestión del agua, Imágenes de satélite, Superficie terrestreResumen
La evapotranspiración real representa la mayor salida de agua de las cuencas continentales, pero su medición directa es costosa, puntual y poco disponible. Se objetivó analizar, en la literatura científica reciente, los modelos de teledetección empleados en la cuantificación de la evapotranspiración real en cuencas hidrográficas, así como el desempeño alcanzado y las limitaciones reportadas. Se trata de una revisión integradora de la literatura, realizada en las bases Scopus, Web of Science, ScienceDirect, Portal de Periódicos Capes y SciELO, con recorte temporal de 2021 a 2026 y reporte orientado por la recomendación PRISMA 2020. Tras las etapas de identificación, cribado y elegibilidad, 18 estudios compusieron la muestra final. Los resultados evidenciaron cuatro grupos de enfoques: modelos de balance de energía en superficie de fuente única, modelos de dos fuentes, métodos apoyados en índices de vegetación y algoritmos de aprendizaje automático. Los errores cuadráticos medios reportados en escala diaria se situaron predominantemente entre 0,26 y 0,97 milímetros por día, con coeficientes de determinación entre 0,79 y 0,95, mientras que las evaluaciones en escala mensual registraron un error absoluto medio cercano al 17 por ciento del valor observado. Las limitaciones más recurrentes fueron la cobertura de nubes, la necesidad de calibración local, la heterogeneidad del píxel y la escasez de mediciones de campo para validación. Se concluye que ningún modelo es universalmente superior y que la elección debe considerar el bioma, la escala y la disponibilidad de datos auxiliares.
Referencias
ABBASI, N. et al. Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area. Remote Sensing, v. 13, n. 24, art. 5167, 2021. Disponível em: https://doi.org/10.3390/rs13245167. Acesso em: 16 ago. 2026.
AGÊNCIA NACIONAL DE ÁGUAS E SANEAMENTO BÁSICO (Brasil). Conjuntura dos recursos hídricos no Brasil 2025. Brasília, DF: ANA, 2025. Disponível em: https://www.snirh.gov.br/portal/centrais-de-conteudos/conjuntura-dos-recursos-hidricos. Acesso em: 12 ago. 2026.
ALMEIDA, C. B. de; ALVES, M. S.; FLORES, F. F.; MUSSI, R. F. de F. Revisão integrativa: da realização da pesquisa ao desenho da publicação acadêmica. Cenas Educacionais, v. 7, e20891, 2024. Disponível em: https://revistas.uneb.br/cenaseducacionais/article/view/20891. Acesso em: 14 ago. 2026.
BEHURA, K. B. et al. Comprehensive analysis of methods for estimating actual paddy evapotranspiration: a review. Frontiers in Water, v. 7, art. 1553732, 2025. Disponível em: https://doi.org/10.3389/frwa.2025.1553732. Acesso em: 28 ago. 2026.
BEHURA, K. B. et al. Evaluation of actual evapotranspiration from rice fields of Odisha using remote sensing based surface energy balance approach. Journal of the Indian Society of Remote Sensing, v. 54, n. 3, p. 1031-1045, 2026. Disponível em: https://doi.org/10.1007/s12524-025-02345-2. Acesso em: 29 ago. 2026.
CASTAGNA, D. et al. Evapotranspiration assessment by remote sensing in Brazil with focus on Amazon biome: scientometric analysis and perspectives for applications in agro-environmental studies. Hydrology, v. 11, n. 3, art. 39, 2024. Disponível em: https://doi.org/10.3390/hydrology11030039. Acesso em: 21 ago. 2026.
CHEN, X. et al. Estimating the actual evapotranspiration using remote sensing and SEBAL model in an arid environment of northwest China. Water, v. 15, n. 8, art. 1555, 2023. Disponível em: https://doi.org/10.3390/w15081555. Acesso em: 17 ago. 2026.
DERARDJA, B. et al. Advancements in remote sensing for evapotranspiration estimation: a comprehensive review of temperature-based models. Remote Sensing, v. 16, n. 11, art. 1927, 2024. Disponível em: https://doi.org/10.3390/rs16111927. Acesso em: 22 ago. 2026.
DU, C. et al. Machine learning-based estimation of daily cropland evapotranspiration in diverse climate zones. Remote Sensing, v. 16, n. 5, art. 730, 2024. Disponível em: https://doi.org/10.3390/rs16050730. Acesso em: 23 ago. 2026.
JIANG, Y.; LIU, Z. Evaluations of remote sensing-based global evapotranspiration datasets at catchment scale in mountain regions. Remote Sensing, v. 13, n. 24, art. 5096, 2021. Disponível em: https://doi.org/10.3390/rs13245096. Acesso em: 15 ago. 2026.
KRAGH, S. J. et al. An inter-comparison of approaches and frameworks to quantify irrigation from satellite data. Hydrology and Earth System Sciences, v. 28, n. 3, p. 441-457, 2024. Disponível em: https://doi.org/10.5194/hess-28-441-2024. Acesso em: 24 ago. 2026.
MICHAILOVSKY, C. I. et al. Investigating sources of variability in closing the terrestrial water balance with remote sensing. Hydrology and Earth System Sciences, v. 27, n. 23, p. 4335-4354, 2023. Disponível em: https://doi.org/10.5194/hess-27-4335-2023. Acesso em: 18 ago. 2026.
MOYANO, M. C. et al. Remote sensing-based assessment of evapotranspiration patterns in a UNESCO World Heritage site under increasing water competition. Remote Sensing, v. 17, n. 14, art. 2339, 2025. Disponível em: https://doi.org/10.3390/rs17142339. Acesso em: 26 ago. 2026.
NERY, L. M. et al. Estimativa da evapotranspiração com redes neurais artificiais e dados espectrais: aplicação em uma unidade de conservação. Revista Brasileira de Meteorologia, v. 40, e40250003, 2025. Disponível em: https://doi.org/10.1590/0102-778640250003. Acesso em: 27 ago. 2026.
OLIVEIRA, M. L. de et al. Evaluation of water and carbon estimation models in the Caatinga biome based on remote sensing. Forests, v. 14, n. 4, art. 828, 2023. Disponível em: https://doi.org/10.3390/f14040828. Acesso em: 19 ago. 2026.
PAGE, M. J. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, v. 372, art. n71, 2021. Disponível em: https://doi.org/10.1136/bmj.n71. Acesso em: 13 ago. 2026.
PAREETH, S.; KARIMI, P. Evapotranspiration estimation using surface energy balance model and medium resolution satellite data: an operational approach for continuous monitoring. Scientific Reports, v. 13, art. 12026, 2023. Disponível em: https://doi.org/10.1038/s41598-023-38563-2. Acesso em: 20 ago. 2026.
RATSHIEDANA, P. E. et al. Evaluation of four remote sensing algorithms in estimating actual evapotranspiration in agricultural environments. Hydrology and Earth System Sciences, v. 30, n. 13, p. 4383-4404, 2026. Disponível em: https://doi.org/10.5194/hess-30-4383-2026. Acesso em: 1 set. 2026.
UNESCO. The United Nations World Water Development Report 2024: water for prosperity and peace. Paris: Unesco, 2024. Disponível em: https://www.unwater.org/publications/un-world-water-development-report-2024. Acesso em: 14 ago. 2026.
VOLK, J. M. et al. Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications. Nature Water, v. 2, n. 2, p. 193-205, 2024. Disponível em: https://doi.org/10.1038/s44221-023-00181-7. Acesso em: 25 ago. 2026.
ZHAO, S. et al. Estimation of actual evapotranspiration and water stress in typical irrigation areas in Xinjiang, northwest China. Remote Sensing, v. 16, n. 14, art. 2676, 2024. Disponível em: https://doi.org/10.3390/rs16142676. Acesso em: 30 ago. 2026.
ZHU, P. et al. A novel framework based on data fusion and machine learning for upscaling evapotranspiration from flux towers to the regional scale. Remote Sensing, v. 17, n. 23, art. 3813, 2025. Disponível em: https://doi.org/10.3390/rs17233813. Acesso em: 2 set. 2026.
Descargas
Publicado
Número
Sección
Licencia
Derechos de autor 2026 Journal of Social Issues and Health Sciences (JSIHS)

Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
