Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil

Gabriel C Blain,Marcelo B P De Camargo

doi:10.1590/s0100-69162012000300014

Gabriel C Blain, Marcelo B P De Camargo

Open Access

https://doi.org/10.1590/s0100-69162012000300014

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Journal: Engenharia Agrícola	Publication Date: Jun 1, 2012
Citations: 16	License type: cc-by

Affiliation: Instituto Agronômico do Paraná

Abstract

This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.

Highlights

Extreme rainfall events are one of the major concerns of the human society due to its potential for causing material damages and human life losses
As indicated by EL ADLOUNI et al (2007), the extreme value theory allow us to infer that the probability of occurrence associated with maximum daily rainfall amounts can be estimated by one of the three extreme value distributions
The auto-correlation function (ACF) allowed us to accept the hypothesis that the Preabs series is generated from a white noise process, since all the coefficients of this function fell within the white noise limits (Figure 1)

Summary

Introduction

Extreme rainfall events are one of the major concerns of the human society due to its potential for causing material damages and human life losses. As pointed out by VICENTE & NUNES (2004) floods (in general triggered by rainfall) may cause, among others hazards, degradation of ecosystems, soil erosion, extensive damage to properties, destruction of crops and (even) trigger slope failures. As indicated by EL ADLOUNI et al (2007), the extreme value theory allow us to infer that the probability of occurrence associated with maximum daily rainfall amounts can be estimated by one of the three extreme value distributions (type I - Gumbel; type II - Fréchet and; type III Weibull). Following WILKS (2006), EL ADLOUNI et al (2007) and, NADARAJAH & CHOI (2007), these three types can be generalized as a three parameter function called General Extreme. Recebido pelo Conselho Editorial em: 24-11-2010 Aprovado pelo Conselho Editorial em: 9-1-2012

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