Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações do UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/24882 |
Resumo: | The automatic weather stations provide hourly information over pluviometric precipitation, and it is recurrent the occurrence of missing data in these data series. This situation compromise the data analysis, since it makes the data series inconsistent and smaller, what creates considerable uncertainty towards the estimation of precipitation quantity. Considering that, this paper has as goal to characterize the behavior of missing data in pluviometric precipitation series obtained in automatic weather stations, located in the state of Rio Grande do Sul, during the period of january 1, 2015 to december 31, 2019. With the hourly data of pluviometric precipitation, to the 38 automatic weather stations, from the Nacional Institute of Meteorology (INMET), it was created maps to visualize the spacial behavior of the average hourly faults in each weather station and in each month of the year. The next step was to assess the efect of the different months of the year in the mean number of hourly missing diary data, it was applied a non-parametric analysis of variance for repeted measures. To assess the efect of the quantity of hours with effective information in the composition of a valid diary data in the precipitation series, it was proposed four definitions of a valid diary data. Based on yhe values of mean pluviometric precipitation and valid hourly numbers in each definition, it was calculated deviations from mean precipitation values. To model the mean diary precipitation desviations it was used the Gama regression model with adjustment in zero. It was observed that most of the automatic weather stations with higher mean values of hourly faults were located in the state borders of Rio Grande do Sul, with spotlight to the west/south border of the state of RS. Most of the automatic weather stations presented a lower mean numbers of hourly faults in the month of december. And the higher mean quantities of hourly faults happened in june and july. It was possible to define the minimal number of 19 hours with measurement values of pluviometric precipitation to be considered a valid day of pluviometric precipitation. |
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2022-06-15T18:33:29Z2022-06-15T18:33:29Z2021-03-11http://repositorio.ufsm.br/handle/1/24882The automatic weather stations provide hourly information over pluviometric precipitation, and it is recurrent the occurrence of missing data in these data series. This situation compromise the data analysis, since it makes the data series inconsistent and smaller, what creates considerable uncertainty towards the estimation of precipitation quantity. Considering that, this paper has as goal to characterize the behavior of missing data in pluviometric precipitation series obtained in automatic weather stations, located in the state of Rio Grande do Sul, during the period of january 1, 2015 to december 31, 2019. With the hourly data of pluviometric precipitation, to the 38 automatic weather stations, from the Nacional Institute of Meteorology (INMET), it was created maps to visualize the spacial behavior of the average hourly faults in each weather station and in each month of the year. The next step was to assess the efect of the different months of the year in the mean number of hourly missing diary data, it was applied a non-parametric analysis of variance for repeted measures. To assess the efect of the quantity of hours with effective information in the composition of a valid diary data in the precipitation series, it was proposed four definitions of a valid diary data. Based on yhe values of mean pluviometric precipitation and valid hourly numbers in each definition, it was calculated deviations from mean precipitation values. To model the mean diary precipitation desviations it was used the Gama regression model with adjustment in zero. It was observed that most of the automatic weather stations with higher mean values of hourly faults were located in the state borders of Rio Grande do Sul, with spotlight to the west/south border of the state of RS. Most of the automatic weather stations presented a lower mean numbers of hourly faults in the month of december. And the higher mean quantities of hourly faults happened in june and july. It was possible to define the minimal number of 19 hours with measurement values of pluviometric precipitation to be considered a valid day of pluviometric precipitation.As estações meteorológicas automáticas fornecem informações horárias sobre a precipitação pluviométrica, sendo que é comum a ocorrência de dados faltantes nessas séries de dados, essa situação compromete a análise dos dados, já que os tornam inconsistentes e em tamanho reduzido, gerando estimações de quantidades de chuvas com altas incertezas associadas. Neste sentido, o presente trabalho tem como objetivo caracterizar o comportamento dos dados faltantes das séries de precipitação pluviométrica obtidas de estações meteorológicas automáticas, localizadas no estado do Rio Grande do Sul, durante o período de 01 de janeiro de 2015 a 31 de dezembro de 2019. Com os dados horários de precipitação pluviométrica, para as 38 estações meteorológicas automáticas, do Instituto Nacional de Meteorologia (INMET), foram gerados mapas para visualização do comportamento espacial das falhas horárias médias em cada estação meteorológica e em cada mês do ano. Em seguida, para avaliar o efeito dos diferentes meses do ano no número médio de horários faltantes diários, foi aplicada a análise de variância não-paramétrica para medidas repetidas. Para avaliar o efeito da quantidade de horários com informação efetiva na composição de um dado diário válido nas series de precipitação, foram propostas quatro definições de dado diário válido. Com base nos valores de precipitação pluviométrica média e número de horários válidos em cada definição, calcularamse desvios de valores médios de precipitação. Para modelar os desvios de precipitação média diária foi usado modelo de regressão Gama com ajuste de zero. Observou-se que a maioria das estações meteorológicas automáticas com maiores números médios de falhas horarias se localizam nas fronteiras do estado do Rio Grande do Sul, com destaque para a fronteira oeste/sul do estado do RS. A maioria das estações meteorológicas automáticas apresentou menores números médios de horários com falhas no mês de dezembro. Já as maiores quantidades medias de horários com falhas ocorreram em junho e julho. Foi possível definir o número mínimo de 19 horários com valores de medição de precipitação pluviométrica para se considerar um dia válido da precipitação pluviométrica.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESporUniversidade Federal de Santa MariaCentro de TecnologiaPrograma de Pós-Graduação em Engenharia AmbientalUFSMBrasilEngenharia AmbientalAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessPrecipitações pluviométricasObservações incompletasDados horáriosDados diáriosEstações meteorológicas automáticasPluviometric precipitationIncomplete observationsHourly dataDaily dataAutomatic weather stationsCNPQ::ENGENHARIASCaracterização do comportamento de falhas nas séries de precipitação do Rio Grande do SulCharacterization of failure behavior in the precipitation series of Rio Grande do Sulinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisSeidel, Enio Júniorhttp://lattes.cnpq.br/7115995033005231Vieira, Afrânio Márcio CorrêaPiccilli, Daniel Gustavo Allasiahttp://lattes.cnpq.br/9014215586862485Faria, Elaine Silva de300000000009600600600600600bd3d465a-223f-468a-a744-31df8d283e10ee0f295b-b62e-4699-8d6e-b708870bf2507746bdda-c182-47d8-8dda-03b09762a83663b54ae1-c1f0-484c-b846-47ed0bf4864ereponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/24882/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/24882/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD53ORIGINALDIS_PPGEA_2021_FARIA_ELAINE.pdfDIS_PPGEA_2021_FARIA_ELAINE.pdfDissertação de mestradoapplication/pdf2367590http://repositorio.ufsm.br/bitstream/1/24882/1/DIS_PPGEA_2021_FARIA_ELAINE.pdfe25c152cd64a9d56c3c81a0af21a5ff7MD511/248822022-06-15 15:33:29.592oai:repositorio.ufsm.br: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 Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2022-06-15T18:33:29Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul |
dc.title.alternative.eng.fl_str_mv |
Characterization of failure behavior in the precipitation series of Rio Grande do Sul |
title |
Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul |
spellingShingle |
Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul Faria, Elaine Silva de Precipitações pluviométricas Observações incompletas Dados horários Dados diários Estações meteorológicas automáticas Pluviometric precipitation Incomplete observations Hourly data Daily data Automatic weather stations CNPQ::ENGENHARIAS |
title_short |
Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul |
title_full |
Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul |
title_fullStr |
Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul |
title_full_unstemmed |
Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul |
title_sort |
Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul |
author |
Faria, Elaine Silva de |
author_facet |
Faria, Elaine Silva de |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Seidel, Enio Júnior |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/7115995033005231 |
dc.contributor.referee1.fl_str_mv |
Vieira, Afrânio Márcio Corrêa |
dc.contributor.referee2.fl_str_mv |
Piccilli, Daniel Gustavo Allasia |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/9014215586862485 |
dc.contributor.author.fl_str_mv |
Faria, Elaine Silva de |
contributor_str_mv |
Seidel, Enio Júnior Vieira, Afrânio Márcio Corrêa Piccilli, Daniel Gustavo Allasia |
dc.subject.por.fl_str_mv |
Precipitações pluviométricas Observações incompletas Dados horários Dados diários Estações meteorológicas automáticas |
topic |
Precipitações pluviométricas Observações incompletas Dados horários Dados diários Estações meteorológicas automáticas Pluviometric precipitation Incomplete observations Hourly data Daily data Automatic weather stations CNPQ::ENGENHARIAS |
dc.subject.eng.fl_str_mv |
Pluviometric precipitation Incomplete observations Hourly data Daily data Automatic weather stations |
dc.subject.cnpq.fl_str_mv |
CNPQ::ENGENHARIAS |
description |
The automatic weather stations provide hourly information over pluviometric precipitation, and it is recurrent the occurrence of missing data in these data series. This situation compromise the data analysis, since it makes the data series inconsistent and smaller, what creates considerable uncertainty towards the estimation of precipitation quantity. Considering that, this paper has as goal to characterize the behavior of missing data in pluviometric precipitation series obtained in automatic weather stations, located in the state of Rio Grande do Sul, during the period of january 1, 2015 to december 31, 2019. With the hourly data of pluviometric precipitation, to the 38 automatic weather stations, from the Nacional Institute of Meteorology (INMET), it was created maps to visualize the spacial behavior of the average hourly faults in each weather station and in each month of the year. The next step was to assess the efect of the different months of the year in the mean number of hourly missing diary data, it was applied a non-parametric analysis of variance for repeted measures. To assess the efect of the quantity of hours with effective information in the composition of a valid diary data in the precipitation series, it was proposed four definitions of a valid diary data. Based on yhe values of mean pluviometric precipitation and valid hourly numbers in each definition, it was calculated deviations from mean precipitation values. To model the mean diary precipitation desviations it was used the Gama regression model with adjustment in zero. It was observed that most of the automatic weather stations with higher mean values of hourly faults were located in the state borders of Rio Grande do Sul, with spotlight to the west/south border of the state of RS. Most of the automatic weather stations presented a lower mean numbers of hourly faults in the month of december. And the higher mean quantities of hourly faults happened in june and july. It was possible to define the minimal number of 19 hours with measurement values of pluviometric precipitation to be considered a valid day of pluviometric precipitation. |
publishDate |
2021 |
dc.date.issued.fl_str_mv |
2021-03-11 |
dc.date.accessioned.fl_str_mv |
2022-06-15T18:33:29Z |
dc.date.available.fl_str_mv |
2022-06-15T18:33:29Z |
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masterThesis |
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http://repositorio.ufsm.br/handle/1/24882 |
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http://repositorio.ufsm.br/handle/1/24882 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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300000000009 |
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Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Tecnologia |
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UFSM |
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Brasil |
dc.publisher.department.fl_str_mv |
Engenharia Ambiental |
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Universidade Federal de Santa Maria Centro de Tecnologia |
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