Intensity-duration-frequency of maximum rainfall in Mato Grosso State

Abstract

Intensive rainfall is an important meteorological variable that is of technical interest in hydraulic projects. This study therefore generated Intensity-Duration-Frequency equations (IDF) for 14 weather stations in Mato Grosso State, based on pluviograph analysis. Annual maximum rainfall data regarding 10-to-1440-minute long rainfall events were collected from digitized daily pluviographs. Data adherence to the generalized extreme value distribution (GEV) was checked through the Kolmogorov-Smirnov test at a 20% significance level. Next, the maximum probable rainfall for return periods such as 2, 5, 10, 20, 30, 50 and 100 years was calculated and the IDF equations were adjusted. The performance of the IDF equations was evaluated based on mean absolute error (MAE), root mean square error (RMSE), bias, Willmott's concordance index and Nash-Sutcliffe efficiency index (ENS). Adjusting the IDF equations was only possible for rainfall durations ranging from 10 to 360 min at each station due to the low frequency of longer rainfalls. High variation was present in parameters of the IDF equation and in maximum rainfall intensity between stations. The satisfactory performance of the models, as attested to by statistical indices, allows using IDF equations adjusted for rainfall durations from 10 to 360 min, and return periods from 2 to 100 years, in the regions of the Mato Grosso weather stations.

Daily Rainfall Disaggregation to Estimate the Intensity-Duration-Frequency Relationship in Minas Gerais State, Brazil

“…In their publication, Freitas and coauthors (2001) [22] tested five probability density functions (PDF) for each duration of the rainfall of the sub-daily resolution rain gauge data, and the adequacy was verified by the Kolmogorov-Smirnov (KS) test at a significance level of 20% [25,30], increasing its rigor in accepting the null hypothesis (control of type II error). The PDF tested was Gumbel (GUM), two-parameters Log-normal and three-parameter Log-Normal (LN2 and LN3, respectively), Pearson type III (P3), and Log-Pearson type III Brazilian Archives of Biology and Technology.…”

“…The estimation of the parameters was performed by three different methodologies of statistical inference such as the method of moments (MM), maximum likelihood (ML), and L-moments (LM) used in several studies about intense rainfall [32,36,37]. The KS test was used to select the PDF that presented the best performance at a significance level of 20% [22,30]. The theoretical quantiles estimated by the probabilistic distributions were calculated for the RP = 2, 5, 10, 25, 50, and 100 years [31,38].…”

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

“…In this sense, the probabilistic understanding on extreme rainfall at a given site or region is necessary for supporting decision making processes regarding the cost-risk tradeoff in such projects (Nunes et al, 2021). In general, for the sub daily time scales, the random behavior of extreme rainfall is summarized by Intensity-Duration-Frequency (IDF) models, which accommodate, in a single parametric form, the functional relationships among the maximum rainfall intensities and their durations and frequencies (or return periods) (Sabino et al, 2020).…”

Intensity-duration-frequency curves in the municipality of Belo Horizonte from the perspective of non-stationarity

“…Considering the vulnerability of urban environments to the occurrence of extreme precipitation events, often associated with increases in local temperatures (Mukherjee et al, 2018), there has been a growing interest from different stakeholders, such as municipalities, companies, and engineers, for reliable analysis of these events in order to define methodologies and procedures for the routine updating of IDF curves (Demaria et al, 2017;Petrucci et al, 2019;Sabino et al, 2020;Souza et al, 2016).…”