Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters

Detalhes bibliográficos
Autor(a) principal: Watanabe, Fernanda [UNESP]
Data de Publicação: 2018
Outros Autores: Alcântara, Enner [UNESP], Imai, Nilton [UNESP], Rodrigues, Thanan, Bernardo, Nariane [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3390/rs10020227
http://hdl.handle.net/11449/175936
Resumo: The high nutrient concentrations coming from non-point and point pollution have been linked to algae blooms, especially in hydroelectric plant reservoirs, due to higher residence time compared to rivers. The monitoring of algae is important to prevent risk of contamination by toxins in reservoirs used for drinking water supply. In this context, a physical model-based approach was adopted to retrieve chlorophyll-a (chl a) concentration, a photosynthetic pigment found in all phytoplankton species. We assumed that a semi-analytical algorithm parameterized to a eutrophic reservoir could also be applied to other eutrophic reservoirs, at least the specific inherent optical properties (SIOPs) are not similar. The parameterization was carried out based on Ocean and Land Color Instrument (OLCI) bands aboard Sentinel-3 spacecraft. In our study, the semi-analytical approach showed good performance in retrieving chl a content, with a normalized root mean square error (NRMSE) of 18.7%. The findings encourage the use of a unique semi-analytical algorithm in a reservoir cascade, where the impoundments present similar bio-optical status. The good performance of the algorithm indicates that this approach is rather useful in predicting trophic status in reservoirs.
id UNSP_0c400215f5d1d33e067e5219354a6e0b
oai_identifier_str oai:repositorio.unesp.br:11449/175936
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland watersOLCI Sentinel-3Productive inland watersSemi-analytical approachTrophic stateThe high nutrient concentrations coming from non-point and point pollution have been linked to algae blooms, especially in hydroelectric plant reservoirs, due to higher residence time compared to rivers. The monitoring of algae is important to prevent risk of contamination by toxins in reservoirs used for drinking water supply. In this context, a physical model-based approach was adopted to retrieve chlorophyll-a (chl a) concentration, a photosynthetic pigment found in all phytoplankton species. We assumed that a semi-analytical algorithm parameterized to a eutrophic reservoir could also be applied to other eutrophic reservoirs, at least the specific inherent optical properties (SIOPs) are not similar. The parameterization was carried out based on Ocean and Land Color Instrument (OLCI) bands aboard Sentinel-3 spacecraft. In our study, the semi-analytical approach showed good performance in retrieving chl a content, with a normalized root mean square error (NRMSE) of 18.7%. The findings encourage the use of a unique semi-analytical algorithm in a reservoir cascade, where the impoundments present similar bio-optical status. The good performance of the algorithm indicates that this approach is rather useful in predicting trophic status in reservoirs.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Department of Cartography Faculty of Sciences and Technology São Paulo State University (UNESP), Rua Roberto Simonsen 305Department of Environmental Engineering Institute of Science and Technology São Paulo State University (UNESP), Rodovia Presidente Dutra Km 137.8Federal Institute of Education Science and Technology from Pará, Rodovia BR 316, km 61Department of Cartography Faculty of Sciences and Technology São Paulo State University (UNESP), Rua Roberto Simonsen 305Department of Environmental Engineering Institute of Science and Technology São Paulo State University (UNESP), Rodovia Presidente Dutra Km 137.8Universidade Estadual Paulista (Unesp)Science and Technology from ParáWatanabe, Fernanda [UNESP]Alcântara, Enner [UNESP]Imai, Nilton [UNESP]Rodrigues, ThananBernardo, Nariane [UNESP]2018-12-11T17:18:13Z2018-12-11T17:18:13Z2018-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://dx.doi.org/10.3390/rs10020227Remote Sensing, v. 10, n. 2, 2018.2072-4292http://hdl.handle.net/11449/17593610.3390/rs100202272-s2.0-850425254662-s2.0-85042525466.pdf66913103944104900000-0002-8077-2865Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensing1,386info:eu-repo/semantics/openAccess2024-06-18T15:01:12Zoai:repositorio.unesp.br:11449/175936Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:06:08.632115Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters
title Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters
spellingShingle Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters
Watanabe, Fernanda [UNESP]
OLCI Sentinel-3
Productive inland waters
Semi-analytical approach
Trophic state
title_short Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters
title_full Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters
title_fullStr Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters
title_full_unstemmed Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters
title_sort Estimation of chlorophyll-a concentration from optimizing a semi-analytical algorithm in productive inland waters
author Watanabe, Fernanda [UNESP]
author_facet Watanabe, Fernanda [UNESP]
Alcântara, Enner [UNESP]
Imai, Nilton [UNESP]
Rodrigues, Thanan
Bernardo, Nariane [UNESP]
author_role author
author2 Alcântara, Enner [UNESP]
Imai, Nilton [UNESP]
Rodrigues, Thanan
Bernardo, Nariane [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Science and Technology from Pará
dc.contributor.author.fl_str_mv Watanabe, Fernanda [UNESP]
Alcântara, Enner [UNESP]
Imai, Nilton [UNESP]
Rodrigues, Thanan
Bernardo, Nariane [UNESP]
dc.subject.por.fl_str_mv OLCI Sentinel-3
Productive inland waters
Semi-analytical approach
Trophic state
topic OLCI Sentinel-3
Productive inland waters
Semi-analytical approach
Trophic state
description The high nutrient concentrations coming from non-point and point pollution have been linked to algae blooms, especially in hydroelectric plant reservoirs, due to higher residence time compared to rivers. The monitoring of algae is important to prevent risk of contamination by toxins in reservoirs used for drinking water supply. In this context, a physical model-based approach was adopted to retrieve chlorophyll-a (chl a) concentration, a photosynthetic pigment found in all phytoplankton species. We assumed that a semi-analytical algorithm parameterized to a eutrophic reservoir could also be applied to other eutrophic reservoirs, at least the specific inherent optical properties (SIOPs) are not similar. The parameterization was carried out based on Ocean and Land Color Instrument (OLCI) bands aboard Sentinel-3 spacecraft. In our study, the semi-analytical approach showed good performance in retrieving chl a content, with a normalized root mean square error (NRMSE) of 18.7%. The findings encourage the use of a unique semi-analytical algorithm in a reservoir cascade, where the impoundments present similar bio-optical status. The good performance of the algorithm indicates that this approach is rather useful in predicting trophic status in reservoirs.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-11T17:18:13Z
2018-12-11T17:18:13Z
2018-02-01
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/10.3390/rs10020227
Remote Sensing, v. 10, n. 2, 2018.
2072-4292
http://hdl.handle.net/11449/175936
10.3390/rs10020227
2-s2.0-85042525466
2-s2.0-85042525466.pdf
6691310394410490
0000-0002-8077-2865
url http://dx.doi.org/10.3390/rs10020227
http://hdl.handle.net/11449/175936
identifier_str_mv Remote Sensing, v. 10, n. 2, 2018.
2072-4292
10.3390/rs10020227
2-s2.0-85042525466
2-s2.0-85042525466.pdf
6691310394410490
0000-0002-8077-2865
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Remote Sensing
1,386
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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)
repository.mail.fl_str_mv
_version_ 1808128608165691392