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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m12.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador6qtX3pFwXQZGivnJRY/KU9yN
Repositóriosid.inpe.br/mtc-m12@80/2006/04.28.18.38   (acesso restrito)
Última Atualização2006:12.19.16.21.23 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m12@80/2006/04.28.18.38.18
Última Atualização dos Metadados2018:06.05.00.40.45 (UTC) administrator
Chave SecundáriaINPE-14457-PRE/9527
ISSN0022-1694
Chave de CitaçãoPereiraFoSant:2006:MoDeUr
TítuloModeling a densely urbanized watershed with an artificial neural network, weather radar and telemetric data
Ano2006
MêsFev.
Data de Acesso10 maio 2024
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho513 KiB
2. Contextualização
Autor1 Pereira Filho, Augusto José
2 Santos, Cláudia Cristina dos
Grupo1
2 DSR-INPE-MCT-BR
Afiliação1 Universidade de São Paulo
2 Instituto Nacional de Pesquisas Espaciais
RevistaJournal of Hydrology
Volume317
Número1-2
Páginas31-48
Histórico (UTC)2006-04-28 18:38:18 :: claudia -> marciana ::
2006-05-16 12:09:09 :: marciana -> administrator ::
2006-08-02 21:31:31 :: administrator -> marciana ::
2006-08-02 22:08:49 :: marciana -> administrator ::
2006-09-03 21:43:56 :: administrator -> marciana ::
2007-04-20 14:45:15 :: marciana -> administrator ::
2009-08-12 01:08:39 :: administrator -> marciana ::
2011-05-23 01:04:43 :: marciana -> administrator ::
2018-06-05 00:40:45 :: administrator -> marciana :: 2006
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Palavras-ChaveGEOCIENCIAS
Geosciences
models
rainfall-runoff
urban hydrology
artificial neural network
weather radar
nowcasting
ResumoArtificial neural networks (ANN) are widely used in a myriad of fields of research and development, including the predictability of time series. This work is concerned with one of such applications to simulate and to forecast stage level and streamflow at the Tamanduatei river watershed, one of the main tributaries of the Alto Tiete river watershed in Sao Paulo State, Brazil. This heavily urbanized watershed is within the Metropolitan Area of Sao Paulo (MASP) where recurrent flash floods affect a population of more than 17 million inhabitants. Flash floods events between 1991 and 1995 were selected and divided up into three groups for training, verification and forecasting purposes. Weather radar rainfall estimation and telemetric stage level and streamflow data were input to a three-layer feed forward ANN trained with the Linear Least Square Simplex training algorithm (LLSSIM) by Hsu et al. [Hsu, K.L., Gupta, H.V., Sorooshian, S., 1996. A superior training strategy for three-layer feed forward artificial neural networks. Tucson, University of Arizona. (Technique report, HWR no. 96-030, Department of Hydrology and Water Resources)]. The performance of the ANN is improved by 40% when either streamflow or stage level were input together with the rainfall. The ANN simulated flood waves tend to be dominated by phase errors. The ANN showed slightly better results then a multi-parameter auto-regression model and indicates its usefulness in flash flood forecasting. (C) 2005 Elsevier B.V. All rights reserved.
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4. Condições de acesso e uso
Idiomaen
Arquivo Alvopereira filho - modeling.pdf
Grupo de Usuáriosadministrator
claudia
marciana
Visibilidadeshown
Detentor da CópiaSID/SCD
Política de Arquivamentodenypublisher denyfinaldraft24
Permissão de Leituradeny from all and allow from 150.163
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3ER446E
DivulgaçãoWEBSCI; PORTALCAPES; MGA; COMPENDEX.
Acervo Hospedeirosid.inpe.br/banon/2001/04.06.10.52
6. Notas
Campos Vaziosalternatejournal archivist callnumber copyright creatorhistory descriptionlevel documentstage doi e-mailaddress electronicmailaddress format isbn label lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url versiontype
7. Controle da descrição
e-Mail (login)marciana
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