At-site flood frequency analysis in Brazil

Valentini, Marlon Heitor Kunst; Beskow, Samuel; Beskow, Tamara Leitzke Caldeira; de Mello, Carlos Rogério; Cassalho, Felício; da Silva, Maria Eduarda Silva

doi:10.1007/s11069-023-06231-3

Cited by 1 publication

(1 citation statement)

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“…The rcrit values for some significance levels (α) and sample sizes (N) are presented by Mello, Silva and Beskow (2020) and indicated only for the Normal, Log-Normal, Gumbel, Weibull and GEV PDFs. As the critical values are not available for all the PDFs herein evaluated, we followed the recommendations of Valentini et al (2023b). These researchers split the PDFs into four groups taking into account the PDFs with existing rcrit values as well as tail and applicability of each PDF; afterwards, they developed a regression model (5% of significance level) for each group (Table 2).…”

Section: Goodness-of-fit Of the Pdfsmentioning

confidence: 99%

Frequency analysis of annual maximum daily rainfall in Brazil with multiparameter probability density functions

Rodrigues,

Beskow,

Siqueira

et al. 2024

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For water resources engineering and management, understand the extreme rainfall events it’s essential. Using rainfall frequency analysis, one can fit many Probability Density Functions (PDFs) to the rainfall series and identify the best fit through the goodness-of-fit tests, allowing the estimate of Annual Maximum Daily Rainfall (AMDR) quantiles for different Return Periods (RP). Recommendations regarding the best PDFs for this have been made for some countries, however, in the opposite direction, Brazil has no guidelines or recommendations such as the above mentioned, and Gumbel distribution still is the most used PDF for modeling AMDR, frequently without testing others. That said, we focus in modeling thousands of AMDR series in Brazil, evaluating ten PDF candidates to find the best fit and defining the most indicated to describe AMDR in the country. The methodology consisted of: acquisition, structuration and screening process by temporal and statistical criteria; fit of the 2-, 3- and multiparameter PDFs to the AMDR series based on the L-moments method; quantile estimation; and PDFs performance assessment by Filliben test and the relative absolute error. From the almost 4 thousand AMDR series investigated, we concluded that: Gumbel and Exponential provided the poorest performance (32.1–60.2% of non-satisfactory fits); multiparametric PDFs (Wakeby and Kappa) are the most indicated for modeling AMDR in Brazil; Gumbel had the highest error values for quantile estimate, especially for high RP; novelties and advances on probabilistic modeling of AMDR in Brazil were provided, helping decision makers with accurate and essential technical information for many purposes.

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Section: Goodness-of-fit Of the Pdfsmentioning

confidence: 99%