Estimação de nível de retorno da precipitação máxima diária na cidade de Jataí-GO

Medeiros, Elias Silva de; Alves, Marcos Antônio; Souza, Sidnei Azevedo de

doi:10.5902/2179460x35639

Cited by 5 publications

(1 citation statement)

References 13 publications

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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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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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Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil

et al. 2020

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The rainfall monitoring allows us to understand the hydrological cycle that not only influences the ecological and environmental dynamics, but also affects the economic and social activities. These sectors are greatly affected when rainfall occurs in amounts greater than the average, called extreme event; moreover, statistical methodologies based on the mean occurrence of these events are inadequate to analyze these extreme events. The Extreme Values Theory provides adequate theoretical models for this type of event; therefore, the Generalized Pareto Distribution (Henceforth GPD) is used to analyze the extreme events that exceed a threshold. The present work has applied both the GPD and its nested version, the Exponential Distribution, in monthly rainfall data from the city of Uruguaiana, in the state of Rio Grande do Sul in Brazil, which calculates the return levels and probabilities for some events of practical interest. To support the results, the goodness of fit criteria is used, and a Monte Carlo simulation procedure is proposed to detect the true probability distribution in each month analyzed. The results show that the GPD and Exponential Distribution fits to the data in all months. Through the simulation study, we perceive that the GPD is more suitable in the months of September and November. However, in January, March, April, and August the, Exponential Distribution is more appropriate, and in the other months, we can use either one.

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Modelagem Espacial de Chuvas Intensas no Estado da Paraíba

Souza

Medeiros

Galbetti

et al. 2022

Rev. bras. meteorol.

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Resumo O Nordeste Brasileiro (NEB) apresenta, como característica marcante, a irregularidade em acumulados de precipitações, o que é decorrência de vários fatores, tais como as características ambientais e de sistemas atmosféricos. Análises estatísticas adequadas são necessárias para ter conhecimento dos níveis de retorno da precipitação em uma região e são muito importantes para auxiliar ações para prevenção de desastres naturais causados por chuvas máximas. O objetivo dessa pesquisa consistiu em apresentar os níveis de retorno da precipitação máxima diária (PMD) em todo o estado da Paraíba, o qual está localizado na NEB. O conjunto de dados foi composto por 238 estações pluviométricas, abrangendo o período de 1994 a 2020. Para a modelagem estatística foi ajustada a distribuição Gumbel, por meio do método da máxima verossimilhança. Os resultados indicaram que o Sertão Paraibano apresentou as maiores estimadas da PMD nos meses de janeiro a março, com volumes superiores a 75 mm. A Mata Paraibana apresentou as maiores estimativas da PMD nos meses de abril a junho, com valores superiores a 125 mm no mês de junho em regiões litorâneas. As informações obtidas sobre os níveis de retorno da PMD são relevantes e podem ser de grande auxílio na implementação de políticas públicas, visando a diminuição dos impactos causados pelas chuvas intensas.

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Estimação de nível de retorno da precipitação máxima diária na cidade de Jataí-GO

Cited by 5 publications

References 13 publications

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

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

Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil

Modelagem Espacial de Chuvas Intensas no Estado da Paraíba

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