Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil

Detalhes bibliográficos
Autor(a) principal: CABALLERO,CASSIA B.
Data de Publicação: 2022
Outros Autores: GUEDES,HUGO ALEXANDRE S., ANDRADE,ALICE CÉSAR F. DE, MARTINS,VITOR S., FRAGA,ROSIMÉRI S., MENDES,KAREN G.P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anais da Academia Brasileira de Ciências (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000601703
Resumo: Abstract Mirim lagoon is the second largest lacustrine water body in Southern Brazil, providing water for local communities. However, algae growth and water quality in the lagoon and in tributaries rivers is influenced by nutrient’s increase. In this context, this study performs the empirical and semi-empirical chlorophyll-a (Chl-a) modeling using remote sensing and in situ data for water quality assessment. Water quality data were collected at 15 sample locations in the lagoon on the date of Sentinel-2 satellite overpass. Surface reflectance data were derived from the Sen2Cor atmospheric correction method and correlated with Chl-a concentration. The best model presented a Pearson’s correlation coefficient = 0.81 and Mean Absolute Error = 0.13µg.L-1. Low Chl-a concentration is observed at the Northern lagoon, possibly due to suspended solids presence. The same occurs in the left margin, being associated with the influence of land use for agriculture. High Chl-a concentrations are associated with shallower and lentic areas. The mean Chl-a concentration predicted by the model was 17.34μg.L-1, similar to the observed value in situ (16.32μg.L-1). Overall, the empirical model developed can be applied as a tool to reduce costs and efforts in fieldwork measures and to understand eutrophication in this river-lake transition ecosystem.
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spelling Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern BrazilEutrophicationInland watersPhytoplankton bloomsSentinel-2Water quality monitoringAbstract Mirim lagoon is the second largest lacustrine water body in Southern Brazil, providing water for local communities. However, algae growth and water quality in the lagoon and in tributaries rivers is influenced by nutrient’s increase. In this context, this study performs the empirical and semi-empirical chlorophyll-a (Chl-a) modeling using remote sensing and in situ data for water quality assessment. Water quality data were collected at 15 sample locations in the lagoon on the date of Sentinel-2 satellite overpass. Surface reflectance data were derived from the Sen2Cor atmospheric correction method and correlated with Chl-a concentration. The best model presented a Pearson’s correlation coefficient = 0.81 and Mean Absolute Error = 0.13µg.L-1. Low Chl-a concentration is observed at the Northern lagoon, possibly due to suspended solids presence. The same occurs in the left margin, being associated with the influence of land use for agriculture. High Chl-a concentrations are associated with shallower and lentic areas. The mean Chl-a concentration predicted by the model was 17.34μg.L-1, similar to the observed value in situ (16.32μg.L-1). Overall, the empirical model developed can be applied as a tool to reduce costs and efforts in fieldwork measures and to understand eutrophication in this river-lake transition ecosystem.Academia Brasileira de Ciências2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000601703Anais da Academia Brasileira de Ciências v.94 n.4 2022reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202220201891info:eu-repo/semantics/openAccessCABALLERO,CASSIA B.GUEDES,HUGO ALEXANDRE S.ANDRADE,ALICE CÉSAR F. DEMARTINS,VITOR S.FRAGA,ROSIMÉRI S.MENDES,KAREN G.P.eng2022-10-06T00:00:00Zoai:scielo:S0001-37652022000601703Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2022-10-06T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil
title Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil
spellingShingle Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil
CABALLERO,CASSIA B.
Eutrophication
Inland waters
Phytoplankton blooms
Sentinel-2
Water quality monitoring
title_short Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil
title_full Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil
title_fullStr Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil
title_full_unstemmed Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil
title_sort Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil
author CABALLERO,CASSIA B.
author_facet CABALLERO,CASSIA B.
GUEDES,HUGO ALEXANDRE S.
ANDRADE,ALICE CÉSAR F. DE
MARTINS,VITOR S.
FRAGA,ROSIMÉRI S.
MENDES,KAREN G.P.
author_role author
author2 GUEDES,HUGO ALEXANDRE S.
ANDRADE,ALICE CÉSAR F. DE
MARTINS,VITOR S.
FRAGA,ROSIMÉRI S.
MENDES,KAREN G.P.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv CABALLERO,CASSIA B.
GUEDES,HUGO ALEXANDRE S.
ANDRADE,ALICE CÉSAR F. DE
MARTINS,VITOR S.
FRAGA,ROSIMÉRI S.
MENDES,KAREN G.P.
dc.subject.por.fl_str_mv Eutrophication
Inland waters
Phytoplankton blooms
Sentinel-2
Water quality monitoring
topic Eutrophication
Inland waters
Phytoplankton blooms
Sentinel-2
Water quality monitoring
description Abstract Mirim lagoon is the second largest lacustrine water body in Southern Brazil, providing water for local communities. However, algae growth and water quality in the lagoon and in tributaries rivers is influenced by nutrient’s increase. In this context, this study performs the empirical and semi-empirical chlorophyll-a (Chl-a) modeling using remote sensing and in situ data for water quality assessment. Water quality data were collected at 15 sample locations in the lagoon on the date of Sentinel-2 satellite overpass. Surface reflectance data were derived from the Sen2Cor atmospheric correction method and correlated with Chl-a concentration. The best model presented a Pearson’s correlation coefficient = 0.81 and Mean Absolute Error = 0.13µg.L-1. Low Chl-a concentration is observed at the Northern lagoon, possibly due to suspended solids presence. The same occurs in the left margin, being associated with the influence of land use for agriculture. High Chl-a concentrations are associated with shallower and lentic areas. The mean Chl-a concentration predicted by the model was 17.34μg.L-1, similar to the observed value in situ (16.32μg.L-1). Overall, the empirical model developed can be applied as a tool to reduce costs and efforts in fieldwork measures and to understand eutrophication in this river-lake transition ecosystem.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000601703
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000601703
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765202220201891
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Academia Brasileira de Ciências
publisher.none.fl_str_mv Academia Brasileira de Ciências
dc.source.none.fl_str_mv Anais da Academia Brasileira de Ciências v.94 n.4 2022
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
instacron:ABC
instname_str Academia Brasileira de Ciências (ABC)
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institution ABC
reponame_str Anais da Academia Brasileira de Ciências (Online)
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