Stochastic simulation in reservoir sedimentation estimation: application in a PCH

Detalhes bibliográficos
Autor(a) principal: TEIXEIRA,EMMANUEL K.C.
Data de Publicação: 2022
Outros Autores: COELHO,MÁRCIA MARIA L.P., PINTO,EBER JOSÉ A., RINCO,ALBERTO V., SALIBA,ALOYSIO P.M.
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=S0001-37652022000701707
Resumo: Abstract In reservoir projects it is important to estimate when the accumulated sediments will start to interfere with their functions. However, predicting silting is difficult because the processes involved have some uncertainties. Thus, the study is not only deterministic, as currently performed, but also stochastic. Thus, the objective of this paper was to develop a stochastic method and evaluate its performance in estimating silting in reservoirs. The method has as originalities the fact of having coupled a deterministic model widely used in the area of Hydraulics to a stochastic one. Another originality was to validate the stochastic method developed from silting data obtained in the reduced model of a Small Hydroelectric Power Plant (SHP). Thus, it was observed that the real silting was always between the 1st and 3rd quartile of probability of the stochastic result. Thus, the main advantage of the stochastic model developed was to allow obtaining the probabilities of silted heights in the stretches of interest. In addition, the variability of the results in the simulations indicated the sections that may suffer greater silting. In this way, hydraulic structures can be better positioned. Preventive and corrective measures can also be better planned and executed.
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spelling Stochastic simulation in reservoir sedimentation estimation: application in a PCHHEC-RASnumerical modelingphysical modelingAR(1) modelAbstract In reservoir projects it is important to estimate when the accumulated sediments will start to interfere with their functions. However, predicting silting is difficult because the processes involved have some uncertainties. Thus, the study is not only deterministic, as currently performed, but also stochastic. Thus, the objective of this paper was to develop a stochastic method and evaluate its performance in estimating silting in reservoirs. The method has as originalities the fact of having coupled a deterministic model widely used in the area of Hydraulics to a stochastic one. Another originality was to validate the stochastic method developed from silting data obtained in the reduced model of a Small Hydroelectric Power Plant (SHP). Thus, it was observed that the real silting was always between the 1st and 3rd quartile of probability of the stochastic result. Thus, the main advantage of the stochastic model developed was to allow obtaining the probabilities of silted heights in the stretches of interest. In addition, the variability of the results in the simulations indicated the sections that may suffer greater silting. In this way, hydraulic structures can be better positioned. Preventive and corrective measures can also be better planned and executed.Academia Brasileira de Ciências2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707Anais da Academia Brasileira de Ciências v.94 suppl.3 2022reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202220211573info:eu-repo/semantics/openAccessTEIXEIRA,EMMANUEL K.C.COELHO,MÁRCIA MARIA L.P.PINTO,EBER JOSÉ A.RINCO,ALBERTO V.SALIBA,ALOYSIO P.M.eng2022-12-02T00:00:00Zoai:scielo:S0001-37652022000701707Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2022-12-02T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Stochastic simulation in reservoir sedimentation estimation: application in a PCH
title Stochastic simulation in reservoir sedimentation estimation: application in a PCH
spellingShingle Stochastic simulation in reservoir sedimentation estimation: application in a PCH
TEIXEIRA,EMMANUEL K.C.
HEC-RAS
numerical modeling
physical modeling
AR(1) model
title_short Stochastic simulation in reservoir sedimentation estimation: application in a PCH
title_full Stochastic simulation in reservoir sedimentation estimation: application in a PCH
title_fullStr Stochastic simulation in reservoir sedimentation estimation: application in a PCH
title_full_unstemmed Stochastic simulation in reservoir sedimentation estimation: application in a PCH
title_sort Stochastic simulation in reservoir sedimentation estimation: application in a PCH
author TEIXEIRA,EMMANUEL K.C.
author_facet TEIXEIRA,EMMANUEL K.C.
COELHO,MÁRCIA MARIA L.P.
PINTO,EBER JOSÉ A.
RINCO,ALBERTO V.
SALIBA,ALOYSIO P.M.
author_role author
author2 COELHO,MÁRCIA MARIA L.P.
PINTO,EBER JOSÉ A.
RINCO,ALBERTO V.
SALIBA,ALOYSIO P.M.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv TEIXEIRA,EMMANUEL K.C.
COELHO,MÁRCIA MARIA L.P.
PINTO,EBER JOSÉ A.
RINCO,ALBERTO V.
SALIBA,ALOYSIO P.M.
dc.subject.por.fl_str_mv HEC-RAS
numerical modeling
physical modeling
AR(1) model
topic HEC-RAS
numerical modeling
physical modeling
AR(1) model
description Abstract In reservoir projects it is important to estimate when the accumulated sediments will start to interfere with their functions. However, predicting silting is difficult because the processes involved have some uncertainties. Thus, the study is not only deterministic, as currently performed, but also stochastic. Thus, the objective of this paper was to develop a stochastic method and evaluate its performance in estimating silting in reservoirs. The method has as originalities the fact of having coupled a deterministic model widely used in the area of Hydraulics to a stochastic one. Another originality was to validate the stochastic method developed from silting data obtained in the reduced model of a Small Hydroelectric Power Plant (SHP). Thus, it was observed that the real silting was always between the 1st and 3rd quartile of probability of the stochastic result. Thus, the main advantage of the stochastic model developed was to allow obtaining the probabilities of silted heights in the stretches of interest. In addition, the variability of the results in the simulations indicated the sections that may suffer greater silting. In this way, hydraulic structures can be better positioned. Preventive and corrective measures can also be better planned and executed.
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
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765202220211573
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 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 suppl.3 2022
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
instacron:ABC
instname_str Academia Brasileira de Ciências (ABC)
instacron_str ABC
institution ABC
reponame_str Anais da Academia Brasileira de Ciências (Online)
collection Anais da Academia Brasileira de Ciências (Online)
repository.name.fl_str_mv Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)
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