Estimate of intense rainfall equation parameters for rainfall stations of the Paraíba State, Brazil

Abstract

Rainfall is the primary water source for hydrographic basins. Hence, the quantification and knowledge of its temporal and spatial distribution are indispensable in dimensioning hydraulic projects. This study aimed at assessing the fit of a series of rainfall data to different probability models, as well as estimating parameters of the intensity-duration-frequency (IDF) equation for rain stations of the Paraíba State, Brazil. The rainfall data of each station were obtained from the Brazilian Water Agency databanks. To estimate the maximum daily rainfall of each station and return period (5, 10, 15, 25, 50 and 100 years), the following probability distributions were used: Gumbel, Log-Normal II, Log-Normal III, Pearson III and Log-Pearson III. The estimation of rainfall in durations of 5-1,440 min was carried out by daily rainfall disaggregation. The adjustment of the IDF equation was performed via nonlinear multiple regression, using the nonlinear generalized reduced gradient interaction method. When compared to the data observed, the intense rainfall equations for most stations showed goodness of fit with coefficients of determination above 0.99, which supports the methodology applied in this study.

Intensity-Duration-Frequency equations for Rio Grande do Sul - Brazil, based on stationary rainfall series

“…The spatial variability of coefficients a and b was also evidenced by other studies in different regions of Brazil and the world, for example, Campus et al (2014) in Piauí, Campos et al (2015) in Maranhão, Souza et al (2016) in Rondônia, Campos et al (2017) in Paraíba, Braga et al (2018) in Rio de Janeiro, Silva and Oliveira (2017) in the Northeast of Brazil, among others. Besides, the range of coefficients a (Figure 4) and b (Figure 5) is similar to those found by Oliveira (2019), who adjusted IDF equations for come locations in the state of RS based on pluviometric and pluviographic data.…”

Assessing intensity-duration-frequency equations and spatialization techniques across the Grande River Basin in the state of Bahia, Brazil

“…As one may observe from Table 3 (and also in Figure 5), the parameters in the numerator of the IDF model, λ and κ , which control the decay of the upper tail of the Gumbel distribution, smoothly vary across space, with a few abrupt variations at specific locations. This is probably related to distinct climate and topographic conditions along the study region (Aragão et al, 2013;Campos et al, 2014Campos et al, , 2017, which might intensify storm bursts at short time scales. In contrast, the parameters in the denominator, η and θ , are constant for all rainfall gauging stations, which may be ascribed to the disaggregation method -in effect, all gauges are located in the same isozone defined by the Departamento de Águas e Energia Elétrica (1980).…”

Equação de chuvas intensas por desagregação de precipitação máxima diária para o estado de Santa Catarina

“…No Brasil o procedimento mais usado é a esti mati va das chuvas de menor duração por meio da desagregação da chuva diária, sendo os coefi cientes de desagregação médios muito uti lizados (CETESB, 1986;PEREIRA et al, 2007;ARAGÃO et al, 2013;CAMPOS et al, 2017), assim como também a uti lização do método das isozonas, que leva em consideração oito regiões em todo território nacional (SANTOS, 2015;BAS-SO et al, 2016). Back & Cadorin (2021) fi zeram um levantamento de equações IDF publicadas no Brasil e constataram que das 3.096 equações cadastradas, 81% foram obti das por desagregação da chuva diária.…”