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- Title
A comprehensive analysis of regional disaggregation coefficients and intensity-duration-frequency curves for the Itacaiúnas watershed in the eastern Brazilian Amazon.
- Authors
de Bodas Terassi, Paulo Miguel; Pontes, Paulo Rógenes Monteiro; Xavier, Ana Carolina Freitas; Cavalcante, Rosane Barbosa Lopes; de Oliveira Serrão, Edivaldo Afonso; Sobral, Bruno Serafini; de Oliveira-Júnior, José Francisco; de Melo, Adayana Maria Queiroz; Baratto, Jakeline
- Abstract
This study assesses the frequency and intensity of rainfall and determines the optimal methods for estimating extreme rainfall in the Itacaiúnas River watershed (IRW), situated in the eastern Brazilian Amazon. Daily rainfall data from 1988 to 2018 were acquired from the Brazilian National Water Agency (ANA) and the National Institute of Meteorology (INMET), whereas hourly data from 2016 to 2018 were obtained from the Vale Institute of Technology and INMET. To fit the annual maximum daily rainfall data, we employed 11 probability distribution functions (PDFs) and evaluated their efficacy using the Kolmogorov-Smirnov (KS) and Anderson-Darling (AD) tests, as well as the Akaike information criterion (AIC), Bayesian information criterion (BIC), and log-likelihood function (LLF). The Gumbel and gamma distributions yielded superior results, as evidenced by the AIC and BIC criteria. The LLF demonstrated that the GEV and Weibull 3 PDFs better fit the maximum annual rainfall series. We calculated rainfall disaggregation coefficients from the rainfall schedule data to estimate maximum rainfall for different duration periods. A comparison with CETESB coefficients revealed that updating these estimates is necessary for accurately representing intense rainfall events in the eastern Amazon. Our analysis estimated upper hourly maximum rainfall of up to 115 mm/h for a return period of 100 years.
- Subjects
DISTRIBUTION (Probability theory); RAINFALL frequencies; RAINFALL; AKAIKE information criterion; GAMMA distributions
- Publication
Theoretical & Applied Climatology, 2023, Vol 154, Issue 3/4, p863
- ISSN
0177-798X
- Publication type
Article
- DOI
10.1007/s00704-023-04591-1