Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Ambiente & Água |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100312 |
Resumo: | Abstract In the design of hydraulic engineering works, the estimation of project precipitation is fundamental. Rain forecasting depends on several factors, which makes estimating it simpler with stochastic processes. In this sense, the distributions of Gumbel (GUM), Log-Normal two-parameter (LN2P), Generalized Extreme Value (GEV), Fréchet with two and three parameters (FRE2P and FRE3P), Weibull with two and three parameters (W2P and W3P), Gamma (GAM2P), and Pareto with two and three parameters (PAR2P and PAR3P) were evaluated to the annual maximum daily precipitation (AMDP) adjustment in the city of Caruaru (Pernambuco´s Agreste). A series of AMDP was used, based on data obtained from the National Water Agency (Agência Nacional de Águas - ANA). Anderson Darling (AD), Kolmogorov-Smirnov (KS) and Pearson Chi-square (χ2) adherence tests, and the determination coefficient (R²) were used to assess the adherence quality of the distributions. The Likelihood Method presented a better fit quality than the Moment Method. The GEV distribution obtained the best results for the AD test in both methods to estimate the parameters. Among the adherence tests used, the AD test was considered the most restrictive. To verify the quality parameters’ fitness to the IDF relations, the Willmott performance coefficient was used. For all distributions employed in this study, Willmott performance coefficients presented values above 0.99, giving a perfect fit of IDF relations with determination coefficients close to 1.0. |
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Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PElikelihood methodmethod of momentsstatistical hydrologyAbstract In the design of hydraulic engineering works, the estimation of project precipitation is fundamental. Rain forecasting depends on several factors, which makes estimating it simpler with stochastic processes. In this sense, the distributions of Gumbel (GUM), Log-Normal two-parameter (LN2P), Generalized Extreme Value (GEV), Fréchet with two and three parameters (FRE2P and FRE3P), Weibull with two and three parameters (W2P and W3P), Gamma (GAM2P), and Pareto with two and three parameters (PAR2P and PAR3P) were evaluated to the annual maximum daily precipitation (AMDP) adjustment in the city of Caruaru (Pernambuco´s Agreste). A series of AMDP was used, based on data obtained from the National Water Agency (Agência Nacional de Águas - ANA). Anderson Darling (AD), Kolmogorov-Smirnov (KS) and Pearson Chi-square (χ2) adherence tests, and the determination coefficient (R²) were used to assess the adherence quality of the distributions. The Likelihood Method presented a better fit quality than the Moment Method. The GEV distribution obtained the best results for the AD test in both methods to estimate the parameters. Among the adherence tests used, the AD test was considered the most restrictive. To verify the quality parameters’ fitness to the IDF relations, the Willmott performance coefficient was used. For all distributions employed in this study, Willmott performance coefficients presented values above 0.99, giving a perfect fit of IDF relations with determination coefficients close to 1.0.Instituto de Pesquisas Ambientais em Bacias Hidrográficas2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100312Revista Ambiente & Água v.16 n.1 2021reponame:Revista Ambiente & Águainstname:Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)instacron:IPABHI10.4136/ambi-agua.2555info:eu-repo/semantics/openAccessMendes,Kevin Matheus CorreiaOliveira,Aline Lima deAlcântara,Lucas Ravellys Pyrrho deAlves,Adriana Thays AraújoSantos Neto,Severino Martins dosCoutinho,Artur PaivaMontenegro,Suzana Maria Gico LimaSoares,José MouraAntonino,Antonio Celso Dantaseng2021-02-19T00:00:00Zoai:scielo:S1980-993X2021000100312Revistahttp://www.ambi-agua.net/PUBhttps://old.scielo.br/oai/scielo-oai.php||ambi.agua@gmail.com1980-993X1980-993Xopendoar:2021-02-19T00:00Revista Ambiente & Água - Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI)false |
dc.title.none.fl_str_mv |
Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE |
title |
Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE |
spellingShingle |
Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE Mendes,Kevin Matheus Correia likelihood method method of moments statistical hydrology |
title_short |
Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE |
title_full |
Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE |
title_fullStr |
Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE |
title_full_unstemmed |
Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE |
title_sort |
Probability distribution of heavy rainfall and determination of IDF in the city of Caruaru - PE |
author |
Mendes,Kevin Matheus Correia |
author_facet |
Mendes,Kevin Matheus Correia Oliveira,Aline Lima de Alcântara,Lucas Ravellys Pyrrho de Alves,Adriana Thays Araújo Santos Neto,Severino Martins dos Coutinho,Artur Paiva Montenegro,Suzana Maria Gico Lima Soares,José Moura Antonino,Antonio Celso Dantas |
author_role |
author |
author2 |
Oliveira,Aline Lima de Alcântara,Lucas Ravellys Pyrrho de Alves,Adriana Thays Araújo Santos Neto,Severino Martins dos Coutinho,Artur Paiva Montenegro,Suzana Maria Gico Lima Soares,José Moura Antonino,Antonio Celso Dantas |
author2_role |
author author author author author author author author |
dc.contributor.author.fl_str_mv |
Mendes,Kevin Matheus Correia Oliveira,Aline Lima de Alcântara,Lucas Ravellys Pyrrho de Alves,Adriana Thays Araújo Santos Neto,Severino Martins dos Coutinho,Artur Paiva Montenegro,Suzana Maria Gico Lima Soares,José Moura Antonino,Antonio Celso Dantas |
dc.subject.por.fl_str_mv |
likelihood method method of moments statistical hydrology |
topic |
likelihood method method of moments statistical hydrology |
description |
Abstract In the design of hydraulic engineering works, the estimation of project precipitation is fundamental. Rain forecasting depends on several factors, which makes estimating it simpler with stochastic processes. In this sense, the distributions of Gumbel (GUM), Log-Normal two-parameter (LN2P), Generalized Extreme Value (GEV), Fréchet with two and three parameters (FRE2P and FRE3P), Weibull with two and three parameters (W2P and W3P), Gamma (GAM2P), and Pareto with two and three parameters (PAR2P and PAR3P) were evaluated to the annual maximum daily precipitation (AMDP) adjustment in the city of Caruaru (Pernambuco´s Agreste). A series of AMDP was used, based on data obtained from the National Water Agency (Agência Nacional de Águas - ANA). Anderson Darling (AD), Kolmogorov-Smirnov (KS) and Pearson Chi-square (χ2) adherence tests, and the determination coefficient (R²) were used to assess the adherence quality of the distributions. The Likelihood Method presented a better fit quality than the Moment Method. The GEV distribution obtained the best results for the AD test in both methods to estimate the parameters. Among the adherence tests used, the AD test was considered the most restrictive. To verify the quality parameters’ fitness to the IDF relations, the Willmott performance coefficient was used. For all distributions employed in this study, Willmott performance coefficients presented values above 0.99, giving a perfect fit of IDF relations with determination coefficients close to 1.0. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100312 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2021000100312 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.4136/ambi-agua.2555 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Instituto de Pesquisas Ambientais em Bacias Hidrográficas |
publisher.none.fl_str_mv |
Instituto de Pesquisas Ambientais em Bacias Hidrográficas |
dc.source.none.fl_str_mv |
Revista Ambiente & Água v.16 n.1 2021 reponame:Revista Ambiente & Água instname:Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI) instacron:IPABHI |
instname_str |
Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI) |
instacron_str |
IPABHI |
institution |
IPABHI |
reponame_str |
Revista Ambiente & Água |
collection |
Revista Ambiente & Água |
repository.name.fl_str_mv |
Revista Ambiente & Água - Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHI) |
repository.mail.fl_str_mv |
||ambi.agua@gmail.com |
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1752129751619731456 |