Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/58327
Title: Intensity-duration-frequency equations for Rio Grande do Sul - Brazil, based on stationary rainfall series
Other Titles: Equações intensidade-duração-frequência para o estado do Rio Grande do Sul – Brasil, baseadas em séries estacionárias de chuva
Keywords: Goodness of fit test
Kappa probabilistic distribution
Trends test
Distribuição probabilística Kappa
Teste de aderência
Teste de tendência
Issue Date: 2023
Publisher: Instituto de Pesquisas Ambientais em Bacias Hidrográficas
Citation: RODRIGUES, A. A. et al. Intensity-duration-frequency equations for Rio Grande do Sul - Brazil, based on stationary rainfall series. Revista Ambiente e Água, Taubaté, v. 18, 2023.
Abstract: Heavy rainfall information is essential for environmental studies and water engineering. This study therefore aimed to adjust Intensity-Duration-Frequency (IDF) equations for 247 locations in the Rio Grande do Sul (RS) using stationary rainfall series. Mann-Kendall’s test was applied to identify the temporal trends in the Annual Maximum Daily Rainfall (AMDR) series of 271 rain gauges in RS. The Kappa, Generalized Extreme Value (GEV), Gumbel, two-parameters Log-Normal and three-parameters Log-Normal probabilistic distributions were adjusted to the AMDR series without significant temporal trend. The best distribution fit was given by Anderson-Darling’s test, so the AMDR was discretized up to 5 minutes. IDF equations coefficients were adjusted in RStudio, using Nash-Sutcliffe’s Coefficient and the Root-Mean-Square Error to evaluate them. In conclusion: the most suitable distributions for the AMDR were the multiparametric Kappa and GEV; the IDF equations coefficients adjustment was classified as “excellent”; coefficients a and b varied across the RS and are correlated with the AMDR and geographical positions; and the c and d coefficients were practically constant.
URI: http://repositorio.ufla.br/jspui/handle/1/58327
Appears in Collections:DEG - Artigos publicados em periódicos



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