Titre:	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
Auteur(s):	Pereira, Alice Rocha Cicerelli, Rejane Ennes Almeida, Andréia de Almeida, Tati de Koide, Sergio
metadata.dc.identifier.orcid:	https://orcid.org/0000-0002-8199-5163 https://orcid.org/0000-0002-6387-8254 https://orcid.org/0000-0002-0424-5748
metadata.dc.contributor.affiliation:	Universidade de Brasília, Departamento de Engenharia Civil e Ambiental Universidade de Brasília, Instituto de Geociências Universidade de Brasília, Faculdade UnB Planaltina Universidade de Brasília, Instituto de Geociências Universidade de Brasília, Departamento de Engenharia Civil e Ambiental
Assunto::	Temperatura da superfície da água Paranoá, Lago (DF) Sensoriamento remoto
Date de publication:	31-oct-2025
Editeur:	MDPI
Référence bibliographique:	PEREIRA, 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.
Abstract:	This 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.
metadata.dc.description.unidade:	Faculdade de Tecnologia (FT) Departamento de Engenharia Civil e Ambiental (FT ENC) Instituto de Geociências (IG) Faculdade UnB Planaltina (FUP)
metadata.dc.description.ppg:	Programa de Pós-Graduação em Tecnologia Ambiental e Recursos Hídricos
Licença::	Licensee 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/).
DOI:	https://doi.org/10.3390/rs17213603
Collection(s) :	Artigos publicados em periódicos e afins

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