Stochastic simulation in reservoir sedimentation estimation: application in a PCH
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,...
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Academia Brasileira de Ciências
2022-12-01
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| Series: | Anais da Academia Brasileira de Ciências |
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| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707&tlng=en |
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| author | EMMANUEL K.C. TEIXEIRA MÁRCIA MARIA L.P. COELHO EBER JOSÉ A. PINTO ALBERTO V. RINCO ALOYSIO P.M. SALIBA |
| author_facet | EMMANUEL K.C. TEIXEIRA MÁRCIA MARIA L.P. COELHO EBER JOSÉ A. PINTO ALBERTO V. RINCO ALOYSIO P.M. SALIBA |
| author_sort | EMMANUEL K.C. TEIXEIRA |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T07:42:26Z |
| format | Article |
| id | doaj.art-025debe1b6ee4a859380dacdfc2a6166 |
| institution | Directory Open Access Journal |
| issn | 1678-2690 |
| language | English |
| last_indexed | 2024-04-11T07:42:26Z |
| publishDate | 2022-12-01 |
| publisher | Academia Brasileira de Ciências |
| record_format | Article |
| series | Anais da Academia Brasileira de Ciências |
| spelling | doaj.art-025debe1b6ee4a859380dacdfc2a61662022-12-22T04:36:28ZengAcademia Brasileira de CiênciasAnais da Academia Brasileira de Ciências1678-26902022-12-0194suppl 310.1590/0001-3765202220211573Stochastic simulation in reservoir sedimentation estimation: application in a PCHEMMANUEL K.C. TEIXEIRAhttps://orcid.org/0000-0001-7598-0240MÁRCIA MARIA L.P. COELHOhttps://orcid.org/0000-0003-2783-2467EBER JOSÉ A. PINTOhttps://orcid.org/0000-0002-4543-8829ALBERTO V. RINCOhttps://orcid.org/0000-0003-4515-5658ALOYSIO P.M. SALIBAhttps://orcid.org/0000-0002-0149-3295Abstract 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.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707&tlng=enHEC-RASnumerical modelingphysical modelingAR(1) model |
| spellingShingle | EMMANUEL K.C. TEIXEIRA MÁRCIA MARIA L.P. COELHO EBER JOSÉ A. PINTO ALBERTO V. RINCO ALOYSIO P.M. SALIBA Stochastic simulation in reservoir sedimentation estimation: application in a PCH Anais da Academia Brasileira de Ciências HEC-RAS numerical modeling physical modeling AR(1) model |
| title | 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_short | Stochastic simulation in reservoir sedimentation estimation: application in a PCH |
| title_sort | stochastic simulation in reservoir sedimentation estimation application in a pch |
| topic | HEC-RAS numerical modeling physical modeling AR(1) model |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000701707&tlng=en |
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