A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade

Detalhes bibliográficos
Autor(a) principal: Rotta, Luiz [UNESP]
Data de Publicação: 2021
Outros Autores: Alcântara, Enner [UNESP], Park, Edward, Bernardo, Nariane [UNESP], Watanabe, Fernanda [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.ecolind.2020.106913
http://hdl.handle.net/11449/206507
Resumo: Previous studies have shown the challenges in using a single model to estimate chlorophyll-a concentration (Chl-a) in water bodies with widely differing characteristics. A single model based on remote sensing to map the Chl-a distribution across the entire Tietê River Cascade System (TRCS) serves as a cost and time-efficient alternative to the conventional monitoring by providing trophic status over space and time. The Tietê River contains one of the largest cascade reservoir systems in the world, which sustains important ecological and socio-economic activities in the São Paulo State, Brazil. Surplus nutrients in water draining its surrounding catchments have been the main cause of eutrophication in the reservoirs of the TRCS. To assess the trophic state of the reservoirs, Chl-a has been regularly monitored by sampling points. However, they are limited by operational costs and dependent on weather conditions. Moreover, the current sampling method only produces point-based measurements. In this paper, we calibrate remote sensing images based on the absorption coefficient to map the spatial distribution patterns of Chl-a levels in the reservoirs. Mapping is done by estimating the Chl-a concentration. The absorption coefficients were retrieved from OLI/Landsat images using the Quasi-Analytical Algorithm (QAA). The total absorption (at) in 482 nm and 655 nm retrieved by QAA presented NRMSE of 17% and 18.5%, respectively. Both at (482 and 655 nm) were used in the model calibration and presented a satisfactory result covering all data ranges, with R2 of 0.646 and NRMSE of 15.3%. The proposed model in this study to retrieve Chl-a maps with relatively high accuracy can be incorporated into the operational monitoring system of the TRCS at a low cost that can provide timely information for reservoir managers to carry out necessary actions. This may include mitigating environmental impacts caused by sudden algae blooms.
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spelling A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascadeAbsorption coefficientOLI/Landsat-8Quasi-Analytical AlgorithmTietê River Cascade SystemTrophic statePrevious studies have shown the challenges in using a single model to estimate chlorophyll-a concentration (Chl-a) in water bodies with widely differing characteristics. A single model based on remote sensing to map the Chl-a distribution across the entire Tietê River Cascade System (TRCS) serves as a cost and time-efficient alternative to the conventional monitoring by providing trophic status over space and time. The Tietê River contains one of the largest cascade reservoir systems in the world, which sustains important ecological and socio-economic activities in the São Paulo State, Brazil. Surplus nutrients in water draining its surrounding catchments have been the main cause of eutrophication in the reservoirs of the TRCS. To assess the trophic state of the reservoirs, Chl-a has been regularly monitored by sampling points. However, they are limited by operational costs and dependent on weather conditions. Moreover, the current sampling method only produces point-based measurements. In this paper, we calibrate remote sensing images based on the absorption coefficient to map the spatial distribution patterns of Chl-a levels in the reservoirs. Mapping is done by estimating the Chl-a concentration. The absorption coefficients were retrieved from OLI/Landsat images using the Quasi-Analytical Algorithm (QAA). The total absorption (at) in 482 nm and 655 nm retrieved by QAA presented NRMSE of 17% and 18.5%, respectively. Both at (482 and 655 nm) were used in the model calibration and presented a satisfactory result covering all data ranges, with R2 of 0.646 and NRMSE of 15.3%. The proposed model in this study to retrieve Chl-a maps with relatively high accuracy can be incorporated into the operational monitoring system of the TRCS at a low cost that can provide timely information for reservoir managers to carry out necessary actions. This may include mitigating environmental impacts caused by sudden algae blooms.São Paulo State University – Unesp Department of CartographySão Paulo State University – Unesp Department of Environmental EngineeringNational Institute of Education and Asian School of the Environment Nanyang Technological UniversitySão Paulo State University – Unesp Department of CartographySão Paulo State University – Unesp Department of Environmental EngineeringUniversidade Estadual Paulista (Unesp)Nanyang Technological UniversityRotta, Luiz [UNESP]Alcântara, Enner [UNESP]Park, EdwardBernardo, Nariane [UNESP]Watanabe, Fernanda [UNESP]2021-06-25T10:33:26Z2021-06-25T10:33:26Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.ecolind.2020.106913Ecological Indicators, v. 120.1470-160Xhttp://hdl.handle.net/11449/20650710.1016/j.ecolind.2020.1069132-s2.0-85090356620Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEcological Indicatorsinfo:eu-repo/semantics/openAccess2024-06-18T15:01:07Zoai:repositorio.unesp.br:11449/206507Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:06:31.930244Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade
title A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade
spellingShingle A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade
Rotta, Luiz [UNESP]
Absorption coefficient
OLI/Landsat-8
Quasi-Analytical Algorithm
Tietê River Cascade System
Trophic state
title_short A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade
title_full A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade
title_fullStr A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade
title_full_unstemmed A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade
title_sort A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade
author Rotta, Luiz [UNESP]
author_facet Rotta, Luiz [UNESP]
Alcântara, Enner [UNESP]
Park, Edward
Bernardo, Nariane [UNESP]
Watanabe, Fernanda [UNESP]
author_role author
author2 Alcântara, Enner [UNESP]
Park, Edward
Bernardo, Nariane [UNESP]
Watanabe, Fernanda [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Nanyang Technological University
dc.contributor.author.fl_str_mv Rotta, Luiz [UNESP]
Alcântara, Enner [UNESP]
Park, Edward
Bernardo, Nariane [UNESP]
Watanabe, Fernanda [UNESP]
dc.subject.por.fl_str_mv Absorption coefficient
OLI/Landsat-8
Quasi-Analytical Algorithm
Tietê River Cascade System
Trophic state
topic Absorption coefficient
OLI/Landsat-8
Quasi-Analytical Algorithm
Tietê River Cascade System
Trophic state
description Previous studies have shown the challenges in using a single model to estimate chlorophyll-a concentration (Chl-a) in water bodies with widely differing characteristics. A single model based on remote sensing to map the Chl-a distribution across the entire Tietê River Cascade System (TRCS) serves as a cost and time-efficient alternative to the conventional monitoring by providing trophic status over space and time. The Tietê River contains one of the largest cascade reservoir systems in the world, which sustains important ecological and socio-economic activities in the São Paulo State, Brazil. Surplus nutrients in water draining its surrounding catchments have been the main cause of eutrophication in the reservoirs of the TRCS. To assess the trophic state of the reservoirs, Chl-a has been regularly monitored by sampling points. However, they are limited by operational costs and dependent on weather conditions. Moreover, the current sampling method only produces point-based measurements. In this paper, we calibrate remote sensing images based on the absorption coefficient to map the spatial distribution patterns of Chl-a levels in the reservoirs. Mapping is done by estimating the Chl-a concentration. The absorption coefficients were retrieved from OLI/Landsat images using the Quasi-Analytical Algorithm (QAA). The total absorption (at) in 482 nm and 655 nm retrieved by QAA presented NRMSE of 17% and 18.5%, respectively. Both at (482 and 655 nm) were used in the model calibration and presented a satisfactory result covering all data ranges, with R2 of 0.646 and NRMSE of 15.3%. The proposed model in this study to retrieve Chl-a maps with relatively high accuracy can be incorporated into the operational monitoring system of the TRCS at a low cost that can provide timely information for reservoir managers to carry out necessary actions. This may include mitigating environmental impacts caused by sudden algae blooms.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-25T10:33:26Z
2021-06-25T10:33:26Z
2021-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.ecolind.2020.106913
Ecological Indicators, v. 120.
1470-160X
http://hdl.handle.net/11449/206507
10.1016/j.ecolind.2020.106913
2-s2.0-85090356620
url http://dx.doi.org/10.1016/j.ecolind.2020.106913
http://hdl.handle.net/11449/206507
identifier_str_mv Ecological Indicators, v. 120.
1470-160X
10.1016/j.ecolind.2020.106913
2-s2.0-85090356620
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Ecological Indicators
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
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