Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil

Detalhes bibliográficos
Autor(a) principal: de Paula,Rodrigo Sérgio
Data de Publicação: 2020
Outros Autores: Velásquez,Leila Nunes Menegasse
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Geology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2317-48892020000400304
Resumo: Abstract Data acquisition by automatic monitoring allows obtaining a large number of data, supporting a better understanding of the monitored region. The use of automated discharge measurement enables a better understanding of floods, the relationship between surface and groundwater flow rate values, and aquifer recharge. However, automatic instruments processing and storage may fail, leading to missing values in some intervals of the recorded time series. These missing values may be replaced by estimates from the regional flow rate or other statistical approximations. For evolved karst systems, however, those techniques may not be adequate due to their rapid discharge responses to rainfall. The aim of this paper is to develop a method able to estimate fluviometric monitoring missing values, based on time series correlation for correlated data. These estimates were obtained from automated monitoring through pressure transducers in 6 streams in a region of approximately 505 km2, predominantly covered by the carbonate and metapellitic Neoproterozoic rocks of the Bambuí Group. The proposed method is composed of four sequential steps: computing the streamflow-data autocorrelation and the cross-correlation of pluviometry with the flow rate; calculating the precipitation fraction that directly contributes to the discharge; fitting of a linear relationship between pluviometry and the monitored daily discharge, to calculate discharge values on days when automatic measurements failed; and approximation of the calculated and monitored discharge values, using a number of statistical criteria. The results show the maturity of the karst aquifer system, with fast ground-water flow and low storage, well-calibrated stage-discharge rating curves for the 2016/2017 hydrological year and that the values estimated by proposed methodology present a deviation of less than 9% over the monitored data.
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spelling Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazilkarst-fissural aquifercross-correlationflow rate autocorrelationfluvial discharge monitoringhydrological data completionAbstract Data acquisition by automatic monitoring allows obtaining a large number of data, supporting a better understanding of the monitored region. The use of automated discharge measurement enables a better understanding of floods, the relationship between surface and groundwater flow rate values, and aquifer recharge. However, automatic instruments processing and storage may fail, leading to missing values in some intervals of the recorded time series. These missing values may be replaced by estimates from the regional flow rate or other statistical approximations. For evolved karst systems, however, those techniques may not be adequate due to their rapid discharge responses to rainfall. The aim of this paper is to develop a method able to estimate fluviometric monitoring missing values, based on time series correlation for correlated data. These estimates were obtained from automated monitoring through pressure transducers in 6 streams in a region of approximately 505 km2, predominantly covered by the carbonate and metapellitic Neoproterozoic rocks of the Bambuí Group. The proposed method is composed of four sequential steps: computing the streamflow-data autocorrelation and the cross-correlation of pluviometry with the flow rate; calculating the precipitation fraction that directly contributes to the discharge; fitting of a linear relationship between pluviometry and the monitored daily discharge, to calculate discharge values on days when automatic measurements failed; and approximation of the calculated and monitored discharge values, using a number of statistical criteria. The results show the maturity of the karst aquifer system, with fast ground-water flow and low storage, well-calibrated stage-discharge rating curves for the 2016/2017 hydrological year and that the values estimated by proposed methodology present a deviation of less than 9% over the monitored data.Sociedade Brasileira de Geologia2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2317-48892020000400304Brazilian Journal of Geology v.50 n.4 2020reponame:Brazilian Journal of Geologyinstname:Sociedade Brasileira de Geologia (SBGEO)instacron:SBGEO10.1590/2317-4889202020190031info:eu-repo/semantics/openAccessde Paula,Rodrigo SérgioVelásquez,Leila Nunes Menegasseeng2020-11-03T00:00:00Zoai:scielo:S2317-48892020000400304Revistahttp://bjg.siteoficial.ws/index.htmhttps://old.scielo.br/oai/scielo-oai.phpsbgsede@sbgeo.org.br||claudio.riccomini@gmail.com2317-46922317-4692opendoar:2020-11-03T00:00Brazilian Journal of Geology - Sociedade Brasileira de Geologia (SBGEO)false
dc.title.none.fl_str_mv Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil
title Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil
spellingShingle Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil
de Paula,Rodrigo Sérgio
karst-fissural aquifer
cross-correlation
flow rate autocorrelation
fluvial discharge monitoring
hydrological data completion
title_short Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil
title_full Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil
title_fullStr Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil
title_full_unstemmed Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil
title_sort Method to complete flow rate data in automatic fluviometric stations in the karst system of Lagoa Santa area, MG, Brazil
author de Paula,Rodrigo Sérgio
author_facet de Paula,Rodrigo Sérgio
Velásquez,Leila Nunes Menegasse
author_role author
author2 Velásquez,Leila Nunes Menegasse
author2_role author
dc.contributor.author.fl_str_mv de Paula,Rodrigo Sérgio
Velásquez,Leila Nunes Menegasse
dc.subject.por.fl_str_mv karst-fissural aquifer
cross-correlation
flow rate autocorrelation
fluvial discharge monitoring
hydrological data completion
topic karst-fissural aquifer
cross-correlation
flow rate autocorrelation
fluvial discharge monitoring
hydrological data completion
description Abstract Data acquisition by automatic monitoring allows obtaining a large number of data, supporting a better understanding of the monitored region. The use of automated discharge measurement enables a better understanding of floods, the relationship between surface and groundwater flow rate values, and aquifer recharge. However, automatic instruments processing and storage may fail, leading to missing values in some intervals of the recorded time series. These missing values may be replaced by estimates from the regional flow rate or other statistical approximations. For evolved karst systems, however, those techniques may not be adequate due to their rapid discharge responses to rainfall. The aim of this paper is to develop a method able to estimate fluviometric monitoring missing values, based on time series correlation for correlated data. These estimates were obtained from automated monitoring through pressure transducers in 6 streams in a region of approximately 505 km2, predominantly covered by the carbonate and metapellitic Neoproterozoic rocks of the Bambuí Group. The proposed method is composed of four sequential steps: computing the streamflow-data autocorrelation and the cross-correlation of pluviometry with the flow rate; calculating the precipitation fraction that directly contributes to the discharge; fitting of a linear relationship between pluviometry and the monitored daily discharge, to calculate discharge values on days when automatic measurements failed; and approximation of the calculated and monitored discharge values, using a number of statistical criteria. The results show the maturity of the karst aquifer system, with fast ground-water flow and low storage, well-calibrated stage-discharge rating curves for the 2016/2017 hydrological year and that the values estimated by proposed methodology present a deviation of less than 9% over the monitored data.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
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=S2317-48892020000400304
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2317-48892020000400304
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2317-4889202020190031
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 Sociedade Brasileira de Geologia
publisher.none.fl_str_mv Sociedade Brasileira de Geologia
dc.source.none.fl_str_mv Brazilian Journal of Geology v.50 n.4 2020
reponame:Brazilian Journal of Geology
instname:Sociedade Brasileira de Geologia (SBGEO)
instacron:SBGEO
instname_str Sociedade Brasileira de Geologia (SBGEO)
instacron_str SBGEO
institution SBGEO
reponame_str Brazilian Journal of Geology
collection Brazilian Journal of Geology
repository.name.fl_str_mv Brazilian Journal of Geology - Sociedade Brasileira de Geologia (SBGEO)
repository.mail.fl_str_mv sbgsede@sbgeo.org.br||claudio.riccomini@gmail.com
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