Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands

Detalhes bibliográficos
Autor(a) principal: Leandro, J.
Data de Publicação: 2013
Outros Autores: Leitão, J. P., Lima, J.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.lnec.pt:8080/jspui/handle/123456789/1006380
Resumo: Flash flooding is characterised by a rapid flooding phenomenon caused by intense rainfall. Despite being an extreme event with high uncertainty, the rainfall-run-off process is often regarded as deterministic (rather than stochastic). In this paper, the Soil Conservation Service (SCS) flood hydrograph uncertainty is quantified based on the Total Error Framework (TEF), and introduced into the model by applying perturbation in the input data and model parameters. The random perturbation component is stochastically modelled. A sensitivity analysis was carried out on the stochastic model parameters, using a real case study in the Azores (Portugal). The results showed that the flood hydrograph uncertainty varies over time, with its largest deviations occurring at the beginning of the flooding because of the uncertainty associated with the SCS method curve number parameter (correlation coefficient R2 of 0.86). Rainfall uncertainty was responsible for the uncertainty in the hydrograph peaks’ magnitude (R2 = 0.93) while uncertainty in the propagation velocity was responsible for the uncertainty in the peaks’ time (R2 = 0.97).
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spelling Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores IslandsFlash floodingLack of dataScs methodStochastic modelsUncertaintyFlash flooding is characterised by a rapid flooding phenomenon caused by intense rainfall. Despite being an extreme event with high uncertainty, the rainfall-run-off process is often regarded as deterministic (rather than stochastic). In this paper, the Soil Conservation Service (SCS) flood hydrograph uncertainty is quantified based on the Total Error Framework (TEF), and introduced into the model by applying perturbation in the input data and model parameters. The random perturbation component is stochastically modelled. A sensitivity analysis was carried out on the stochastic model parameters, using a real case study in the Azores (Portugal). The results showed that the flood hydrograph uncertainty varies over time, with its largest deviations occurring at the beginning of the flooding because of the uncertainty associated with the SCS method curve number parameter (correlation coefficient R2 of 0.86). Rainfall uncertainty was responsible for the uncertainty in the hydrograph peaks’ magnitude (R2 = 0.93) while uncertainty in the propagation velocity was responsible for the uncertainty in the peaks’ time (R2 = 0.97).2014-08-22T15:15:20Z2014-10-20T12:58:27Z2017-04-12T14:45:49Z2013-09-01T00:00:00Z2013-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.lnec.pt:8080/jspui/handle/123456789/1006380eng1753-318XLeandro, J.Leitão, J. P.Lima, J.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-13T03:02:15Zoai:localhost:123456789/1006380Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:38:29.783492Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands
title Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands
spellingShingle Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands
Leandro, J.
Flash flooding
Lack of data
Scs method
Stochastic models
Uncertainty
title_short Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands
title_full Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands
title_fullStr Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands
title_full_unstemmed Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands
title_sort Quantifying the uncertainty in the Soil Conservation Service flood hydropraphs: a case study in the Azores Islands
author Leandro, J.
author_facet Leandro, J.
Leitão, J. P.
Lima, J.
author_role author
author2 Leitão, J. P.
Lima, J.
author2_role author
author
dc.contributor.author.fl_str_mv Leandro, J.
Leitão, J. P.
Lima, J.
dc.subject.por.fl_str_mv Flash flooding
Lack of data
Scs method
Stochastic models
Uncertainty
topic Flash flooding
Lack of data
Scs method
Stochastic models
Uncertainty
description Flash flooding is characterised by a rapid flooding phenomenon caused by intense rainfall. Despite being an extreme event with high uncertainty, the rainfall-run-off process is often regarded as deterministic (rather than stochastic). In this paper, the Soil Conservation Service (SCS) flood hydrograph uncertainty is quantified based on the Total Error Framework (TEF), and introduced into the model by applying perturbation in the input data and model parameters. The random perturbation component is stochastically modelled. A sensitivity analysis was carried out on the stochastic model parameters, using a real case study in the Azores (Portugal). The results showed that the flood hydrograph uncertainty varies over time, with its largest deviations occurring at the beginning of the flooding because of the uncertainty associated with the SCS method curve number parameter (correlation coefficient R2 of 0.86). Rainfall uncertainty was responsible for the uncertainty in the hydrograph peaks’ magnitude (R2 = 0.93) while uncertainty in the propagation velocity was responsible for the uncertainty in the peaks’ time (R2 = 0.97).
publishDate 2013
dc.date.none.fl_str_mv 2013-09-01T00:00:00Z
2013-09
2014-08-22T15:15:20Z
2014-10-20T12:58:27Z
2017-04-12T14:45:49Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://repositorio.lnec.pt:8080/jspui/handle/123456789/1006380
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language eng
dc.relation.none.fl_str_mv 1753-318X
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