Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala?
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional de Geociências - RIGEO |
Texto Completo: | https://rigeo.sgb.gov.br/handle/doc/19640 |
Resumo: | The short and medium-range flow forecasting techniques using large-scale hydrological models have several direct applications in the management of natural disasters through warning systems. The present study is a research study on this type of system, applied in the Uruguay River Basin (RS, SC, Argentina and Uruguay). The objective of this study was to investigate the predictability of critical events at points of interest in the Uruguay river basin. We aimed to evaluate how early it is possible to estimate the peak flow in some sites susceptible to flooding in the basin. For the present research we selected municipalities that will be initially served by the Geological Service of Brazil (CPRM) warning system in the Uruguay river: Garruchos, Itaqui, Porto Lucena, São Borja and Uruguaiana. In the evaluation, the Nash-Sutcliffe Efficiency coefficient (NSE) was used. After the calibration and validation of the model, the predictability analysis was performed based on 15 flood events that occurred between 1980 and 2017 in which the forecasts of daily time-step were compared to a reference simulation. It was verified that there is an increase in the predictability from one day for up to three days, increasing as further downstream the place of interest is located. Also it was evidenced that the predictability especially in Uruguaiana city is dependent on where the floods are originated (higher Uruguay basin or Ibicuí basin). These results constitute useful information that may assist managers in decision making during critical events where forecast are provided by the proposed type of modeling |
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GUIMARÃES, Guilherme MendozaFAN, Fernando MainardiMARCUZZO, Francisco Fernando NoronhaBUFFON, Franco TurcoGERMANO, Andrea de Oliveira2018-07-26T10:02:46Z2018-07-26T10:02:46Z2018-07GUIMARÃES, Guilherme Mendoza; FAN, Fernando Mainardi; MARCUZZO, Francisco Fernando Noronha; BUFFON, Franco Turco; GERMANO, Andrea de Oliveira. Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? In: ENCONTRO NACIONAL DE DESASTRES, 1., 2018, Porto Alegre. Trabalhos aprovados. Porto Alegre: ABRH, 2018.https://rigeo.sgb.gov.br/handle/doc/19640The short and medium-range flow forecasting techniques using large-scale hydrological models have several direct applications in the management of natural disasters through warning systems. The present study is a research study on this type of system, applied in the Uruguay River Basin (RS, SC, Argentina and Uruguay). The objective of this study was to investigate the predictability of critical events at points of interest in the Uruguay river basin. We aimed to evaluate how early it is possible to estimate the peak flow in some sites susceptible to flooding in the basin. For the present research we selected municipalities that will be initially served by the Geological Service of Brazil (CPRM) warning system in the Uruguay river: Garruchos, Itaqui, Porto Lucena, São Borja and Uruguaiana. In the evaluation, the Nash-Sutcliffe Efficiency coefficient (NSE) was used. After the calibration and validation of the model, the predictability analysis was performed based on 15 flood events that occurred between 1980 and 2017 in which the forecasts of daily time-step were compared to a reference simulation. It was verified that there is an increase in the predictability from one day for up to three days, increasing as further downstream the place of interest is located. Also it was evidenced that the predictability especially in Uruguaiana city is dependent on where the floods are originated (higher Uruguay basin or Ibicuí basin). These results constitute useful information that may assist managers in decision making during critical events where forecast are provided by the proposed type of modelingO estudo abrange as seguintes bacias e sub-bacias hidrográficas (entre outras): Bacia 7, Bacia hidrográfica do Rio Uruguai, Bacia Hidrográfica do Rio Quaraí, Bacia Hidrográfica do rio Ibicuí, Bacia Hidrográfica do Rio Pelotas, Bacia Hidrográfica do Rio do Peixe, Sub-Bacia 70, Sub-Bacia 71, Sub-Bacia 72, Sub-Bacia 73, Sub-Bacia 74, Sub-Bacia 75, Sub-Bacia 76, Sub-Bacia 77, Sub-Bacia 78 e Sub-Bacia 79. O estudo abrange os seguintes municípios (entre outros): Barracão, Urubici, Campos Novos, Caçador, Marcelino Ramos, Água Doce, Uruguaiana, Bagé, Quaraí, Rio dos Índios, Campo Erê, Doutor Maurício, Cardoso, Chapada, Itaqui, Tupanciretâ, Santana do Livramento, Hulha Negra, Aceguá, Alpestre, Itá, Piratuba, Maximiliano de Almeida, Anita Garibaldi e Pinhal da Serra. O estudo abrange as seguintes UHEs: Usina Hidrelétrica de Campos Novos, Usina Hidrelétrica de Barra Grande, Usina Hidrelétrica de Machadinho, Usina Hidrelétrica de Itá, Usina Hidrelétrica Foz do Chapecó e Águas de Chapecó. O estudo abrange os seguintes rios (entre outros): Rio Uruguai, Rio Canoas, Rio Pelotas, Rio do Peixe, Rio Chapecó, Rio Peperi-Guaçu, Rio camaquã, Rio Forquilha, Rio Apuaê, Rio Passo Fundo, Rio da Várzea, Rio Ijuí, Rio Ibicuí, Rio Quaraí e Rio Negro. O estudo abrange os seguintes estados e países: Rio Grande do Sul, Santa Catarina, Uruguai e Argentina.CPRMUFRGS/IPHABRHOTTOCODIFICATIONRIVER CODIFICATIONMORPHOLOGYRELIEFHIPSOMETRICDIGITAL MODEL ELEVATIONHIDROLOGYHYDROLOGICAL MODELSALERT SYSTMSHYDROLOGICAL FORECASTURUGUAY RIVERBRASILARGENTINAURUGUAIPREVISIÓN HIDROLÓGICAHIDROLOGÍAHIDROLOGIAMODELOS HIDROLÓGICOSSISTEMA DE ALERTAPREVISÃO HIDROLÓGICAPREVISIBILIDADERIO GRANDE DO SULRIO URUGUAISISTEMA DE ALERTA DE EVENTOS CRÍTICOSSACECHEIASINUNDAÇÕESMODELOS DE GRANDES BACIASMGBMODELO DIGITAL DE ELEVAÇÃOCom qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala?info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlePorto Alegreinfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional de Geociências - RIGEOinstname:Companhia de Pesquisa de Recursos Minerais (CPRM)instacron:CPRMORIGINALprevisao_uruguai.pdfprevisao_uruguai.pdfproducao cientificaapplication/pdf1181313http://rigeo.sgb.gov.br/jspui/bitstream/doc/19640/1/previsao_uruguai.pdffd8c1fe27a81bc4fc184ab5ed0eea094MD51apresentacao_END.pdfapresentacao_END.pdfapplication/pdf2797387http://rigeo.sgb.gov.br/jspui/bitstream/doc/19640/3/apresentacao_END.pdf3a1364841bdff93936ed9db3d2e1f7c7MD53localizacao_bacia_rio_uruguai.pdflocalizacao_bacia_rio_uruguai.pdfmapaapplication/pdf2949994http://rigeo.sgb.gov.br/jspui/bitstream/doc/19640/8/localizacao_bacia_rio_uruguai.pdf3cf43a6eaff977ab4c37e70add39a240MD58nash_analise_previsibilidade_inundacao.pngnash_analise_previsibilidade_inundacao.pngfiguraimage/png165459http://rigeo.sgb.gov.br/jspui/bitstream/doc/19640/9/nash_analise_previsibilidade_inundacao.png907b8b6743659175bf31bbe027fc5390MD59postos_fluviometricos.pdfpostos_fluviometricos.pdfmapaapplication/pdf3042937http://rigeo.sgb.gov.br/jspui/bitstream/doc/19640/10/postos_fluviometricos.pdf34752ecc66a7c86b8e3823fdc992e66dMD510simulacao_dados_precipitacao.pngsimulacao_dados_precipitacao.pngfiguraimage/png301999http://rigeo.sgb.gov.br/jspui/bitstream/doc/19640/11/simulacao_dados_precipitacao.pngc79b2529a08b14ff23b0e66b274da74cMD511LICENSElicense.txtlicense.txttext/plain; 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dc.title.pt_BR.fl_str_mv |
Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? |
title |
Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? |
spellingShingle |
Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? GUIMARÃES, Guilherme Mendoza HIDROLOGIA MODELOS HIDROLÓGICOS SISTEMA DE ALERTA PREVISÃO HIDROLÓGICA PREVISIBILIDADE RIO GRANDE DO SUL RIO URUGUAI SISTEMA DE ALERTA DE EVENTOS CRÍTICOS SACE CHEIAS INUNDAÇÕES MODELOS DE GRANDES BACIAS MGB MODELO DIGITAL DE ELEVAÇÃO OTTOCODIFICATION RIVER CODIFICATION MORPHOLOGY RELIEF HIPSOMETRIC DIGITAL MODEL ELEVATION HIDROLOGY HYDROLOGICAL MODELS ALERT SYSTMS HYDROLOGICAL FORECAST URUGUAY RIVER BRASIL ARGENTINA URUGUAI PREVISIÓN HIDROLÓGICA HIDROLOGÍA |
title_short |
Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? |
title_full |
Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? |
title_fullStr |
Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? |
title_full_unstemmed |
Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? |
title_sort |
Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? |
author |
GUIMARÃES, Guilherme Mendoza |
author_facet |
GUIMARÃES, Guilherme Mendoza FAN, Fernando Mainardi MARCUZZO, Francisco Fernando Noronha BUFFON, Franco Turco GERMANO, Andrea de Oliveira |
author_role |
author |
author2 |
FAN, Fernando Mainardi MARCUZZO, Francisco Fernando Noronha BUFFON, Franco Turco GERMANO, Andrea de Oliveira |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
GUIMARÃES, Guilherme Mendoza FAN, Fernando Mainardi MARCUZZO, Francisco Fernando Noronha BUFFON, Franco Turco GERMANO, Andrea de Oliveira |
dc.subject.por.fl_str_mv |
HIDROLOGIA MODELOS HIDROLÓGICOS SISTEMA DE ALERTA PREVISÃO HIDROLÓGICA PREVISIBILIDADE RIO GRANDE DO SUL RIO URUGUAI SISTEMA DE ALERTA DE EVENTOS CRÍTICOS SACE CHEIAS INUNDAÇÕES MODELOS DE GRANDES BACIAS MGB MODELO DIGITAL DE ELEVAÇÃO |
topic |
HIDROLOGIA MODELOS HIDROLÓGICOS SISTEMA DE ALERTA PREVISÃO HIDROLÓGICA PREVISIBILIDADE RIO GRANDE DO SUL RIO URUGUAI SISTEMA DE ALERTA DE EVENTOS CRÍTICOS SACE CHEIAS INUNDAÇÕES MODELOS DE GRANDES BACIAS MGB MODELO DIGITAL DE ELEVAÇÃO OTTOCODIFICATION RIVER CODIFICATION MORPHOLOGY RELIEF HIPSOMETRIC DIGITAL MODEL ELEVATION HIDROLOGY HYDROLOGICAL MODELS ALERT SYSTMS HYDROLOGICAL FORECAST URUGUAY RIVER BRASIL ARGENTINA URUGUAI PREVISIÓN HIDROLÓGICA HIDROLOGÍA |
dc.subject.en.en.fl_str_mv |
OTTOCODIFICATION RIVER CODIFICATION MORPHOLOGY RELIEF HIPSOMETRIC DIGITAL MODEL ELEVATION |
dc.subject.en.pt_BR.fl_str_mv |
HIDROLOGY HYDROLOGICAL MODELS ALERT SYSTMS HYDROLOGICAL FORECAST URUGUAY RIVER BRASIL ARGENTINA URUGUAI |
dc.subject.es.es.fl_str_mv |
PREVISIÓN HIDROLÓGICA HIDROLOGÍA |
description |
The short and medium-range flow forecasting techniques using large-scale hydrological models have several direct applications in the management of natural disasters through warning systems. The present study is a research study on this type of system, applied in the Uruguay River Basin (RS, SC, Argentina and Uruguay). The objective of this study was to investigate the predictability of critical events at points of interest in the Uruguay river basin. We aimed to evaluate how early it is possible to estimate the peak flow in some sites susceptible to flooding in the basin. For the present research we selected municipalities that will be initially served by the Geological Service of Brazil (CPRM) warning system in the Uruguay river: Garruchos, Itaqui, Porto Lucena, São Borja and Uruguaiana. In the evaluation, the Nash-Sutcliffe Efficiency coefficient (NSE) was used. After the calibration and validation of the model, the predictability analysis was performed based on 15 flood events that occurred between 1980 and 2017 in which the forecasts of daily time-step were compared to a reference simulation. It was verified that there is an increase in the predictability from one day for up to three days, increasing as further downstream the place of interest is located. Also it was evidenced that the predictability especially in Uruguaiana city is dependent on where the floods are originated (higher Uruguay basin or Ibicuí basin). These results constitute useful information that may assist managers in decision making during critical events where forecast are provided by the proposed type of modeling |
publishDate |
2018 |
dc.date.accessioned.fl_str_mv |
2018-07-26T10:02:46Z |
dc.date.available.fl_str_mv |
2018-07-26T10:02:46Z |
dc.date.issued.fl_str_mv |
2018-07 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
GUIMARÃES, Guilherme Mendoza; FAN, Fernando Mainardi; MARCUZZO, Francisco Fernando Noronha; BUFFON, Franco Turco; GERMANO, Andrea de Oliveira. Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? In: ENCONTRO NACIONAL DE DESASTRES, 1., 2018, Porto Alegre. Trabalhos aprovados. Porto Alegre: ABRH, 2018. |
dc.identifier.uri.fl_str_mv |
https://rigeo.sgb.gov.br/handle/doc/19640 |
identifier_str_mv |
GUIMARÃES, Guilherme Mendoza; FAN, Fernando Mainardi; MARCUZZO, Francisco Fernando Noronha; BUFFON, Franco Turco; GERMANO, Andrea de Oliveira. Com qual antecedência conseguimos prever cheias no rio Uruguai usando um modelo hidrológico de grande escala? In: ENCONTRO NACIONAL DE DESASTRES, 1., 2018, Porto Alegre. Trabalhos aprovados. Porto Alegre: ABRH, 2018. |
url |
https://rigeo.sgb.gov.br/handle/doc/19640 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
ABRH |
publisher.none.fl_str_mv |
ABRH |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional de Geociências - RIGEO instname:Companhia de Pesquisa de Recursos Minerais (CPRM) instacron:CPRM |
instname_str |
Companhia de Pesquisa de Recursos Minerais (CPRM) |
instacron_str |
CPRM |
institution |
CPRM |
reponame_str |
Repositório Institucional de Geociências - RIGEO |
collection |
Repositório Institucional de Geociências - RIGEO |
bitstream.url.fl_str_mv |
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