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Intensity-Duration-Frequency equations for Rio Grande do Sul - Brazil, based on stationary rainfall serie.
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- Author(s): Araujo Rodrigues, Aryane; Moreira Siqueira, Tirzah; Caldeira Beskow, Tamara Leitzke; Beskow, Samuel; Rogério de Mello, Carlos
- Source:
Revista Ambiente e Água; 2023, Vol. 18 Issue 1, p1-17, 17p- Subject Terms:
- Source:
- Additional Information
- Alternate Title: Equações Intensidade-Duração-Frequência para o estado do Rio Grande do Sul – Brasil, baseadas em séries estacionárias de chuva. (Portuguese)
- Subject Terms:
- 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, twoparameters 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-MeanSquare 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. [ABSTRACT FROM AUTHOR]
- Abstract: Informações sobre chuvas intensas são essenciais para estudos ambientais e engenharia de recursos hídricos. Assim, o estudo objetivou ajustar equações Intensidade-DuraçãoFrequências (IDF) de chuvas para 247 locais do Rio Grande do Sul (RS), utilizando séries estacionárias de chuva. Para identificar tendencias temporais significativas, o teste MannKendall foi aplicado em 271 séries de Chuva Máxima Diária Annual (CMDA) do RS. As distribuições probabilisticas Kappa, GEV, Gumbel, Log-Normal 2 parâmetros e Log-Normal 2 parãmetros foram ajustadas às séries sem tendência de CMDA. Com as distribuições melhores ajustadas à cada série de CMDA, esta foi discretizada em intervalos de até 5 minutos. O ajuste dos coeficientes das equações IDF foi realizado no RStudio, utilizando o Coeficiente de NashSutcliffe e a Raíz Quadrada do Erro Quadrático Médio para avaliá-lo. Em conclusão: as distribuições mais adequadas foram as multiparamétricas Kappa e GEV; o ajuste dos coeficientes da equação IDF foi classificado como “excelente”; os coeficientes a e b variam no RS e estão correlacionados com a magnitude da CMDA e sua localização; os coeficientes c e d foram praticamentes contantes. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Revista Ambiente e Água is the property of Revista Ambiente e Agua and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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