Spectral analysis in determining water quality sampling intervals
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | RBRH (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312019000100237 |
Resumo: | ABSTRACT To make water quality series more representative, real-time monitoring techniques are developed. However, these techniques have obstacles in their use, such as high costs and difficulties in equipment installation, maintenance, and calibration. One alternative is near-real time water quality monitoring (NRTWQM), with sampling done less frequently than daily. The study objective was to evaluate, through spectral analysis, the water quality sampling frequency representativity for different catchments. For this purpose, a historical series of real time water quality monitoring stations were used in Brazil, Canada, and the USA. These series were submitted to spectral analysis to identify the denser frequencies and their representativeness across the series. To obtain the sampling intervals, the Nyquist-Shannon theorem was applied. Weekly intervals accounted for 65% of cumulative frequencies for the three verified parameters, and the sampling intervals obtained by means of the characteristic frequencies were shown to be executable in the NRTWQM models for up to the 90% of cumulative frequency. For cumulative frequency above 90%, the intervals approach the daily values. |
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Spectral analysis in determining water quality sampling intervalsSampling frequencyMonitoringNear real timeABSTRACT To make water quality series more representative, real-time monitoring techniques are developed. However, these techniques have obstacles in their use, such as high costs and difficulties in equipment installation, maintenance, and calibration. One alternative is near-real time water quality monitoring (NRTWQM), with sampling done less frequently than daily. The study objective was to evaluate, through spectral analysis, the water quality sampling frequency representativity for different catchments. For this purpose, a historical series of real time water quality monitoring stations were used in Brazil, Canada, and the USA. These series were submitted to spectral analysis to identify the denser frequencies and their representativeness across the series. To obtain the sampling intervals, the Nyquist-Shannon theorem was applied. Weekly intervals accounted for 65% of cumulative frequencies for the three verified parameters, and the sampling intervals obtained by means of the characteristic frequencies were shown to be executable in the NRTWQM models for up to the 90% of cumulative frequency. For cumulative frequency above 90%, the intervals approach the daily values.Associação Brasileira de Recursos Hídricos2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312019000100237RBRH v.24 2019reponame:RBRH (Online)instname:Associação Brasileira de Recursos Hídricos (ABRH)instacron:ABRH10.1590/2318-0331.241920180077info:eu-repo/semantics/openAccessSilva,Régis Leandro Lopes daSilveira,André Luiz Lopes daSilveira,Geraldo Lopes daeng2019-10-02T00:00:00Zoai:scielo:S2318-03312019000100237Revistahttps://www.scielo.br/j/rbrh/https://old.scielo.br/oai/scielo-oai.php||rbrh@abrh.org.br2318-03311414-381Xopendoar:2019-10-02T00:00RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)false |
dc.title.none.fl_str_mv |
Spectral analysis in determining water quality sampling intervals |
title |
Spectral analysis in determining water quality sampling intervals |
spellingShingle |
Spectral analysis in determining water quality sampling intervals Silva,Régis Leandro Lopes da Sampling frequency Monitoring Near real time |
title_short |
Spectral analysis in determining water quality sampling intervals |
title_full |
Spectral analysis in determining water quality sampling intervals |
title_fullStr |
Spectral analysis in determining water quality sampling intervals |
title_full_unstemmed |
Spectral analysis in determining water quality sampling intervals |
title_sort |
Spectral analysis in determining water quality sampling intervals |
author |
Silva,Régis Leandro Lopes da |
author_facet |
Silva,Régis Leandro Lopes da Silveira,André Luiz Lopes da Silveira,Geraldo Lopes da |
author_role |
author |
author2 |
Silveira,André Luiz Lopes da Silveira,Geraldo Lopes da |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Silva,Régis Leandro Lopes da Silveira,André Luiz Lopes da Silveira,Geraldo Lopes da |
dc.subject.por.fl_str_mv |
Sampling frequency Monitoring Near real time |
topic |
Sampling frequency Monitoring Near real time |
description |
ABSTRACT To make water quality series more representative, real-time monitoring techniques are developed. However, these techniques have obstacles in their use, such as high costs and difficulties in equipment installation, maintenance, and calibration. One alternative is near-real time water quality monitoring (NRTWQM), with sampling done less frequently than daily. The study objective was to evaluate, through spectral analysis, the water quality sampling frequency representativity for different catchments. For this purpose, a historical series of real time water quality monitoring stations were used in Brazil, Canada, and the USA. These series were submitted to spectral analysis to identify the denser frequencies and their representativeness across the series. To obtain the sampling intervals, the Nyquist-Shannon theorem was applied. Weekly intervals accounted for 65% of cumulative frequencies for the three verified parameters, and the sampling intervals obtained by means of the characteristic frequencies were shown to be executable in the NRTWQM models for up to the 90% of cumulative frequency. For cumulative frequency above 90%, the intervals approach the daily values. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312019000100237 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312019000100237 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2318-0331.241920180077 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Recursos Hídricos |
publisher.none.fl_str_mv |
Associação Brasileira de Recursos Hídricos |
dc.source.none.fl_str_mv |
RBRH v.24 2019 reponame:RBRH (Online) instname:Associação Brasileira de Recursos Hídricos (ABRH) instacron:ABRH |
instname_str |
Associação Brasileira de Recursos Hídricos (ABRH) |
instacron_str |
ABRH |
institution |
ABRH |
reponame_str |
RBRH (Online) |
collection |
RBRH (Online) |
repository.name.fl_str_mv |
RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH) |
repository.mail.fl_str_mv |
||rbrh@abrh.org.br |
_version_ |
1754734701916979200 |