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Universidade de Brasília
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dc.contributor.authorPereira, Alice Rocha-
dc.contributor.authorCicerelli, Rejane Ennes-
dc.contributor.authorAlmeida, Andréia de-
dc.contributor.authorAlmeida, Tati de-
dc.contributor.authorKoide, Sergio-
dc.date.accessioned2025-12-05T13:35:43Z-
dc.date.available2025-12-05T13:35:43Z-
dc.date.issued2025-10-31-
dc.identifier.citationPEREIRA, Alice Rocha et al. Four decades of thermal monitoring in a tropical urban reservoir using remote sensing : trends, climatic and external drivers of surface water warming in Lake Paranoá, Brazil. Remote Sensing, [S. l.], v. 17, n. 21, 3603, 2025. DOI: https://doi.org/10.3390/rs17213603. Disponível em: https://www.mdpi.com/2072-4292/17/21/3603. Acesso em: 5 nov. 2025.pt_BR
dc.identifier.urihttp://repositorio.unb.br/handle/10482/53343-
dc.language.isoengpt_BR
dc.publisherMDPIpt_BR
dc.rightsAcesso Abertopt_BR
dc.titleFour decades of thermal monitoring in a tropical urban reservoir using remote sensing : trends, climatic and external drivers of surface water warming in Lake Paranoá, Brazilpt_BR
dc.typeArtigopt_BR
dc.subject.keywordTemperatura da superfície da águapt_BR
dc.subject.keywordParanoá, Lago (DF)pt_BR
dc.subject.keywordSensoriamento remotopt_BR
dc.rights.licenseLicensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).pt_BR
dc.identifier.doihttps://doi.org/10.3390/rs17213603pt_BR
dc.description.abstract1This study analyzed how external forcings, such as meteorological conditions and inflows, influence the average water surface temperature (WST) of the urban Lake Paranoá, Brasília-Brazil, using both in situ measurements and remote sensing estimates over a 40-year period. The temperature model calibrated for Lake Paranoá with no time lag (0-day delay) presented the following metrics: R2 = 0.92, RMSE = 0.59 ◦C, demonstrating the feasibility of obtaining reliable thermal estimates from remote sensing even in urban water bodies. Simple and multiple regression analyses were applied to identify the main external drivers of WST across different temporal scales. A warming trend of 0.036 ◦C/yr in lake surface temperature was observed, higher than the concurrent increase in air temperature (0.026 ◦C/yr), suggesting enhanced thermal stratification that may impact water quality. The most influential variables on WST were air temperature, relative humidity, and wind speed, with varying degrees of influence depending on the time scale considered (daily, monthly, annual or seasonal). Remote sensing proved to be essential for overcoming the limitations of traditional monitoring, such as temporal gaps and limited spatial coverage, and allowed detailed mapping of thermal patterns throughout the lake. Integrating these data into hydrodynamic models enhances their diagnostic, predictive, and decision-support capabilities in the context of climate change.pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-8199-5163pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-6387-8254pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-0424-5748pt_BR
dc.contributor.affiliationUniversidade de Brasília, Departamento de Engenharia Civil e Ambientalpt_BR
dc.contributor.affiliationUniversidade de Brasília, Instituto de Geociênciaspt_BR
dc.contributor.affiliationUniversidade de Brasília, Faculdade UnB Planaltinapt_BR
dc.contributor.affiliationUniversidade de Brasília, Instituto de Geociênciaspt_BR
dc.contributor.affiliationUniversidade de Brasília, Departamento de Engenharia Civil e Ambientalpt_BR
dc.description.unidadeFaculdade de Tecnologia (FT)pt_BR
dc.description.unidadeDepartamento de Engenharia Civil e Ambiental (FT ENC)pt_BR
dc.description.unidadeInstituto de Geociências (IG)pt_BR
dc.description.unidadeFaculdade UnB Planaltina (FUP)pt_BR
dc.description.ppgPrograma de Pós-Graduação em Tecnologia Ambiental e Recursos Hídricospt_BR
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