Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB

Bibliographic Details
Main Author: Sousa, Yesus Parvati Andrade
Publication Date: 2021
Format: Bachelor thesis
Language: por
Source: Biblioteca Digital de Teses e Dissertações da UFPB
Download full: https://repositorio.ufpb.br/jspui/handle/123456789/25443
Summary: Water is the most important asset in sustaining life and is present in practically everything around us, such as human supply, irrigation, electricity generation, among other activities. Therefore, among other needs, the monitoring of hydrological variables for the proper management of water resources must be carried out, whether at a local or regional level. In this sense, by measuring these variables, hydrological models can be developed, which seek to represent in a simplified way the physical phenomena that occur in nature. Within the mathematical hydrological models, we have the rainfall-runoff models, which aim to perform the flow calculation based on rainfall values in a given region. In addition to the mathematical hydrological models, there are models based on Artificial Neural Networks (ANN). In this sense, in the present work, the mathematical model Soil Moisture Accounting Procedure (SMAP) and an ANN-based model will be used to calculate the influent flow in the Taperoá river sub-basin and in the Piancó river sub-basin, in the State of Paraíba . The modeling of the Taperoá river sub-basin followed the temporal scope comprising the period of available data from 01/01/1970 to 12/01/2014, while the modeling of the Piancó river sub-basin comprised the period of available data from 05/01/1969 to 12/01/2014. The data were used on a monthly time scale. To fill gaps in rainfall series, the regional vector method was used. The SMAP model generated as a result Nash coefficients of 0.67 and 0.40, in the total period, for the Taperoá and Piancó river sub-basins, respectively. The ANNs generated Nash coefficients of 0.84 and 0.64, in the total period, for the Taperoá and Piancó river sub-basins, respectively. Compared to the SMAP model, the ANNs were more accurate in the rainfall-runoff modeling for the sub-basins studied.
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spelling Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PBModelos chuva-vazãoRedes Neurais ArtificiaisSMAPCNPQ::ENGENHARIAS::ENGENHARIA CIVILWater is the most important asset in sustaining life and is present in practically everything around us, such as human supply, irrigation, electricity generation, among other activities. Therefore, among other needs, the monitoring of hydrological variables for the proper management of water resources must be carried out, whether at a local or regional level. In this sense, by measuring these variables, hydrological models can be developed, which seek to represent in a simplified way the physical phenomena that occur in nature. Within the mathematical hydrological models, we have the rainfall-runoff models, which aim to perform the flow calculation based on rainfall values in a given region. In addition to the mathematical hydrological models, there are models based on Artificial Neural Networks (ANN). In this sense, in the present work, the mathematical model Soil Moisture Accounting Procedure (SMAP) and an ANN-based model will be used to calculate the influent flow in the Taperoá river sub-basin and in the Piancó river sub-basin, in the State of Paraíba . The modeling of the Taperoá river sub-basin followed the temporal scope comprising the period of available data from 01/01/1970 to 12/01/2014, while the modeling of the Piancó river sub-basin comprised the period of available data from 05/01/1969 to 12/01/2014. The data were used on a monthly time scale. To fill gaps in rainfall series, the regional vector method was used. The SMAP model generated as a result Nash coefficients of 0.67 and 0.40, in the total period, for the Taperoá and Piancó river sub-basins, respectively. The ANNs generated Nash coefficients of 0.84 and 0.64, in the total period, for the Taperoá and Piancó river sub-basins, respectively. Compared to the SMAP model, the ANNs were more accurate in the rainfall-runoff modeling for the sub-basins studied.A água é o bem mais importante na manutenção da vida e está presente em praticamente tudo à nossa volta, como por exemplo, no abastecimento humano, na irrigação, na geração de energia elétrica, entre outras atividades. Sendo assim, dentre outras necessidades, deve-se realizar, seja em nível local ou regional, o monitoramento das variáveis hidrológicas para a adequada gestão dos recursos hídricos. Neste sentido, por meio da medição destas variáveis, podem-se elaborar os modelos hidrológicos, que buscam representar de forma simplificada os fenômenos físicos que ocorrem na natureza. Dentro dos modelos hidrológicos matemáticos, temos os modelos chuva-vazão, que tem como objetivo realizar o cálculo de vazão com base nos valores de chuva de uma determinada região. Além dos modelos hidrológicos matemáticos, existem os modelos baseados em Redes Neurais Artificiais (RNA). Neste sentido, no presente trabalho será utilizado o modelo matemático Soil Moisture Accounting Procedure (SMAP) e um modelo baseado em RNA para o cálculo da vazão afluente na sub-bacia do rio Taperoá e na sub-bacia do rio Piancó, no Estado da Paraíba. A modelagem da sub-bacia do rio Taperoá seguiu o escopo temporal compreendendo o período de dados disponíveis entre 01/01/1970 à 01/12/2014, enquanto que a modelagem da sub-bacia do rio Piancó compreendeu o período de dados disponíveis de 01/05/1969 à 01/12/2014. Trabalhou-se com dados em escala de tempo mensal. Para o preenchimento de falhas nas séries pluviométricas, foi utilizado o método do vetor regional. O modelo SMAP gerou como resultado coeficientes de Nash de 0.67 e 0.40, no período total, para as sub-bacias do rio Taperoá e Piancó, respectivamente. As RNAs geraram coeficientes de Nash de 0.84 e 0.64, no período total, para as sub-bacias do rio Taperoá e Piancó, respectivamente. Comparado ao modelo SMAP, as RNAs se mostraram mais precisas na modelagem chuva-vazão para as sub-bacias estudadas.Universidade Federal da ParaíbaBrasilEngenharia Civil e AmbientalUFPBSarmento, Francisco JacoméSousa, Yesus Parvati Andrade2022-11-16T16:04:07Z2022-11-162022-11-16T16:04:07Z2021-07-14info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bachelorThesishttps://repositorio.ufpb.br/jspui/handle/123456789/25443porinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFPBinstname:Universidade Federal da Paraíba (UFPB)instacron:UFPB2022-11-17T06:06:19Zoai:repositorio.ufpb.br:123456789/25443Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufpb.br/PUBhttp://tede.biblioteca.ufpb.br:8080/oai/requestdiretoria@ufpb.br|| bdtd@biblioteca.ufpb.bropendoar:2022-11-17T06:06:19Biblioteca Digital de Teses e Dissertações da UFPB - Universidade Federal da Paraíba (UFPB)false
dc.title.none.fl_str_mv Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB
title Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB
spellingShingle Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB
Sousa, Yesus Parvati Andrade
Modelos chuva-vazão
Redes Neurais Artificiais
SMAP
CNPQ::ENGENHARIAS::ENGENHARIA CIVIL
title_short Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB
title_full Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB
title_fullStr Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB
title_full_unstemmed Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB
title_sort Modelagem chuva-vazão a nível mensal das sub-bacias dos Rios Taperoá e Piancó – PB
author Sousa, Yesus Parvati Andrade
author_facet Sousa, Yesus Parvati Andrade
author_role author
dc.contributor.none.fl_str_mv Sarmento, Francisco Jacomé
dc.contributor.author.fl_str_mv Sousa, Yesus Parvati Andrade
dc.subject.por.fl_str_mv Modelos chuva-vazão
Redes Neurais Artificiais
SMAP
CNPQ::ENGENHARIAS::ENGENHARIA CIVIL
topic Modelos chuva-vazão
Redes Neurais Artificiais
SMAP
CNPQ::ENGENHARIAS::ENGENHARIA CIVIL
description Water is the most important asset in sustaining life and is present in practically everything around us, such as human supply, irrigation, electricity generation, among other activities. Therefore, among other needs, the monitoring of hydrological variables for the proper management of water resources must be carried out, whether at a local or regional level. In this sense, by measuring these variables, hydrological models can be developed, which seek to represent in a simplified way the physical phenomena that occur in nature. Within the mathematical hydrological models, we have the rainfall-runoff models, which aim to perform the flow calculation based on rainfall values in a given region. In addition to the mathematical hydrological models, there are models based on Artificial Neural Networks (ANN). In this sense, in the present work, the mathematical model Soil Moisture Accounting Procedure (SMAP) and an ANN-based model will be used to calculate the influent flow in the Taperoá river sub-basin and in the Piancó river sub-basin, in the State of Paraíba . The modeling of the Taperoá river sub-basin followed the temporal scope comprising the period of available data from 01/01/1970 to 12/01/2014, while the modeling of the Piancó river sub-basin comprised the period of available data from 05/01/1969 to 12/01/2014. The data were used on a monthly time scale. To fill gaps in rainfall series, the regional vector method was used. The SMAP model generated as a result Nash coefficients of 0.67 and 0.40, in the total period, for the Taperoá and Piancó river sub-basins, respectively. The ANNs generated Nash coefficients of 0.84 and 0.64, in the total period, for the Taperoá and Piancó river sub-basins, respectively. Compared to the SMAP model, the ANNs were more accurate in the rainfall-runoff modeling for the sub-basins studied.
publishDate 2021
dc.date.none.fl_str_mv 2021-07-14
2022-11-16T16:04:07Z
2022-11-16
2022-11-16T16:04:07Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/bachelorThesis
format bachelorThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://repositorio.ufpb.br/jspui/handle/123456789/25443
url https://repositorio.ufpb.br/jspui/handle/123456789/25443
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 Universidade Federal da Paraíba
Brasil
Engenharia Civil e Ambiental
UFPB
publisher.none.fl_str_mv Universidade Federal da Paraíba
Brasil
Engenharia Civil e Ambiental
UFPB
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações da UFPB
instname:Universidade Federal da Paraíba (UFPB)
instacron:UFPB
instname_str Universidade Federal da Paraíba (UFPB)
instacron_str UFPB
institution UFPB
reponame_str Biblioteca Digital de Teses e Dissertações da UFPB
collection Biblioteca Digital de Teses e Dissertações da UFPB
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações da UFPB - Universidade Federal da Paraíba (UFPB)
repository.mail.fl_str_mv diretoria@ufpb.br|| bdtd@biblioteca.ufpb.br
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