Análise dos dados de precipitação máxima no noroeste paulista pela teoria dos valores extremos

Affonso, Vinicius; Faria, Gláucia Amorim; Lopes, Beatriz Garcia; Tsutsumoto, Nayra Yumi; Fonseca, Ariéli Daieny da; Felizardo, Lucas Menezes

doi:10.33448/rsd-v9i10.9396

Cited by 3 publications

(3 citation statements)

References 10 publications

(9 reference statements)

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“…Existem diversos modelos que podem ser usados para determinar a frequência hidrológica das cheias, precipitações máximas e intensidade-duração-frequência de um evento. Em geral, os modelos probabilísticos dependem do uso de dados existentes para fazer previsões cenário futuro (Affonso et al, 2020;Filho et al, 2020;Ximenes et al, 2020).…”

Section: Análise Da Frequência De Cheiasunclassified

Estudo de vazões máximas de projeto usando uma distribuição de Gumbel

Nobre

Pereira

Campos

2021

RSD

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O cálculo de cheias máximas de projeto é fundamental para o projeto e desenvolvimento de construções hidráulicas. A previsão de enchentes, por exemplo, pode ser estimada, aplicando o cálculo de uma enchente de projeto por extrapolação dos dados históricos para condições extremas. Assim, para evitar riscos de colapso em construções hidráulicas, é fundamental o uso de distribuições estatísticas especializadas para realizar cálculos de vazões de projeto de vertedouros. A distribuição de Gumbel é uma das funções de distribuição de probabilidade mais amplamente utilizadas para valores extremos em estudos hidrológicos, nos quais os parâmetros considerados na análise são a vazão e período de retorno. Neste trabalho de pesquisa, uma distribuição de Gumbel foi utilizada para analisar os dados das vazões máximas de uma série histórica da estação Tabajara, do rio Ji-Paraná, localizado no município de Machadinho d’Oeste – RO. Os dados estudados foram coletados entre os anos de 1978 e 2015.

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Section: Análise Da Frequência De Cheiasunclassified

Estudo de vazões máximas de projeto usando uma distribuição de Gumbel

Nobre

Pereira

Campos

2021

RSD

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“…Climate change risk assessment studies also benefit from the use of statistical tools. In this context, some studies have analyzed extreme daily rainfall (e.g., Rupa and Mujumdar, 2017;Medeiros et al, 2019;Affonso et al, 2020), while others have focused their analysis on flow series (Yonus and Hassan, 2019;Isensee et al, 2021). Blöschl et al (2019) point out the variability of extreme events as a prominent theme among the open problems, due to the difficulty of being precisely understood temporally and spatially, in addition to the magnitude of the impacts resulting from these events.…”

Section: Introductionmentioning

confidence: 99%

Analysis of hydrological extremes in the Guaíba hydrographic region: an application of extreme values theory

Vieira

Osório

Quevedo

2022

Rev. Bras. Ciênc. Ambient.

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Knowing the behavior of extreme hydrological phenomena is essential so that the impacts resulting from these natural events are minimized. Rio Grande do Sul has frequently been hit by extreme events such as droughts and floods, and these events are associated with several consequences, such as energy or water rationing, urban flooding and damage to hydraulic structures. In this context, the analysis of historical series extremes of hydrometeorological data through the Extreme Values Theory (EVT) is one of the ways to determine the variability due to climate change, enabling the modeling of extreme events. EVT makes it possible to know the frequency with which extreme events occur, allowing extrapolation beyond the historical series, generating occurrence probabilities of such an event. Therefore, the purpose of this work was to apply the Extreme Values Theory in hydrological the data historical series of flow and precipitation in the Guaíba hydrographic region and to carry out occurrence probabilities of intense events return, helping in the planning of the hydrographic watersheds that are in this region, as well as to verify whether the EVT has return periods similar to the climate projections of CMIP5 models. The results demonstrate that the values of flow and precipitation, in the historical series used, have already presented changes regarding the volume and frequency of extreme events occurrence and, in the future, for some stations, values can be expected both above and below the extremes already observed in the historical series.

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“…The type I extreme or Gumbel distribution and extensions have been applied to different areas of scientific knowledge such as hydrology, meteorology, climatology, insurance, finance, and geology, among many others (Nanvapisheh, 2021). The Gumbel distribution has been widely used to study maximum rainfall (Marques et al, 2014;Affonso et al, 2020).…”

Section: Evaluation Of Generalized Extreme Value and Gumbel Distributions For Estimating Maximum Daily Rainfall Introductionmentioning

confidence: 99%

Evaluation of generalized extreme value and Gumbel distributions for estimating maximum daily rainfall

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Bonfante

2021

Rev. Bras. Ciênc. Ambient.

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Extreme rain events can cause social and economic impacts in various sectors. Knowing the risk of occurrences of extreme events is fundamental for the establishment of mitigation measures and for risk management. The analysis of frequencies of historical series of observed rain through theoretical probability distributions is the most commonly used method. The generalized extreme value (GEV) and Gumbel probability distributions stand out among those applied to estimate the maximum daily rainfall. The indication of the best distribution depends on characteristics of the data series used to adjust parameters and criteria used for selection. This study compares GEV and Gumbel distributions and analyzes different criteria used to select the best distribution. We used 224 series of annual maximums of rainfall stations in Santa Catarina (Brazil), with sizes between 12 and 90 years and asymmetry coefficient ranging from -0.277 to 3.917. We used the Anderson–Darling, Kolmogorov-Smirnov (KS), and Filliben adhesion tests. For an indication of the best distribution, we used the standard error of estimate, Akaike’s criterion, and the ranking with adhesion tests. KS test proved to be less rigorous and only rejected 0.25% of distributions tested, while Anderson–Darling and Filliben tests rejected 9.06% and 8.8% of distributions, respectively. GEV distribution proved to be the most indicated for most stations. High agreement (73.7%) was only found in the indication of the best distribution between Filliben tests and the standard error of estimate.

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Análise dos dados de precipitação máxima no noroeste paulista pela teoria dos valores extremos

Cited by 3 publications

References 10 publications

Estudo de vazões máximas de projeto usando uma distribuição de Gumbel

Estudo de vazões máximas de projeto usando uma distribuição de Gumbel

Analysis of hydrological extremes in the Guaíba hydrographic region: an application of extreme values theory

Evaluation of generalized extreme value and Gumbel distributions for estimating maximum daily rainfall

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