Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/15402
Título: Modelagem probabilística de eventos de precipitação extrema no estado do Rio Grande do Sul
Título(s) alternativo(s): Probabilistic modelling of extreme rainfall events in the Rio Grande do Sul state
Palavras-chave: Hidrologia – Métodos estatísticos
Distribuição de probabilidade
Indice pluviométrico – Rio Grande do Sul
Hydrology – Statistical methods
Probability distribution
Pluviometric indexes – State of Rio Grande do Sul, Brazil
Data do documento: Mar-2015
Editor: Universidade Federal de Campina Grande
Citação: CALDEIRA, T. L. et al. Modelagem probabilística de eventos de precipitação extrema no estado do Rio Grande do Sul. Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, v. 19, n. 3, p. 197-203, mar. 2015.
Resumo: Flood management in Brazilian watersheds must be discussed and prioritized, however, the current scenario indicates that there are gaps in hydrological information with respect to its spatial and temporal variability. The probabilistic modelling of extreme rainfall events, having as goal to extrapolate values for a given frequency and duration, can be used as an excellent tool for analysis and decision-making. The main objective of this study was to analyse the adjustment of different probabilistic models for series of annual maximum daily rainfall in Rio Grande do Sul. Series of 342 rain gauges were adjusted to 2-parameter Log-Normal, 3-parameter Log-Normal and Gumbel probability distributions and goodness-of-fit tests were based on the Kolmogorov-Smirnov and Chi-Square procedures. It was found that all the distributions presented adequate results, however, 3-parameter Log-Normal distribution had the best performance in accordance with the Chi-Square test. The parameters of probability distribution presented variability over the state and a pronounced relationship with the location of rain gauges. This suggests that regionalization of high-intensity rainfall can be employed in Rio Grande do Sul as an excellent management tool.
URI: http://repositorio.ufla.br/jspui/handle/1/15402
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