Data/hora: 11/06/2024 07:07:55

Provedor de dados: | 64
País: | Brazil
Título: | Performance of the probability distribution models applied to heavy rainfall daily events
Autores: | Marques,Rosângela Francisca de Paula Vitor; Mello,Carlos Rogério de; Silva,Antônio Marciano da; Franco,Camila Silva; Oliveira,Alisson Souza de.
Data: | 2014-08-01
Ano: | 2014
Palavras-chave: | Probability distribution models; Intense rainfall; Statistical inference; Non-parametric statistical tests.
Resumo: | Probabilistic studies of hydrological variables, such as heavy rainfall daily events, constitute an important tool to support the planning and management of water resources, especially for the design of hydraulic structures and erosive rainfall potential. In this context, we aimed to analyze the performance of three probability distribution models (GEV, Gumbel and Gamma two parameter), whose parameters were adjusted by the Moments Method (MM), Maximum Likelihood (ML) and L - Moments (LM). These models were adjusted to the frequencies from long-term of maximum daily rainfall of 8 rain gauges located in Minas Gerais state. To indicate and discuss the performance of the probability distribution models, it was applied, firstly, the non-parametric Filliben test, and in addition, when differences were unidentified, Anderson-Darlling and Chi-Squared tests were also applied. The Gumbel probability distribution model showed a better adjustment for 87.5% of the cases. Among the assessed probability distribution models, GEV fitted by LM method has been adequate for all studied rain gauges and can be recommended. Considering the number of adequate cases, MM and LM methods had better performance than ML method, presenting, respectively, 83% and 79.2% of adequate cases.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542014000400003
Editor: | Editora da Universidade Federal de Lavras
Relação: | 10.1590/S1413-70542014000400003
Formato: | text/html
Fonte: | Ciência e Agrotecnologia  v.38 n.4 2014
Fonte: | info:eu-repo/semantics/openAccess