Erosividade mensal e anual da chuva no Estado de Minas Gerais

Mello, Carlos Rogério de; Sá, Marcos Aurélio Carolino de; Curi, Nilton; Mello, José Márcio de; Viola, Marcelo Ribeiro; Silva, Antônio Marciano da

doi:10.1590/s0100-204x2007000400012

Cited by 93 publications

(100 citation statements)

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“…A long-term series of maximum daily rainfall, obtained from the National Water Agency (ANA/ HIDROWEB, 2012), from eight rain gauges located in medium to high heavy rainfall zones (Mello et al, 2007), in Minas Gerais state: Barbacena, Carmo da Mata, Desterro Mello, Divinópolis, Estiva, Ibituruna, Itapecirica and Ouro Preto were used. All the long-term series had at least 34 years of complete and recent data sets, being the period between 1977 and 2007 common to all them (Table 1 and figure 1).…”

Section: Methodsmentioning

confidence: 99%

“…Ciênc. Agrotec., Lavras, v.38, n.4, p.335-342, jul./ago., 2014 Three Probability Density Functions (PDF) designed for extreme values, were used: Generalized Extreme Value -GEV (Equation 1), Gamma two-parameter (Equation 2), and Gumbel (Equation 3), whose parameters were estimated by the zmethods of Moments (MM), Maximum Likelihood (ML) and L-Moments (LM) ( Naghettini; Pinto, 2007).…”

Section: Methodsmentioning

confidence: 99%

“…The Moments Method (MM), according to Naghettini and Pinto (2007), is the simplest and normally, less efficient. The Maximum Likelihood method (ML) is considered as the method that maximizes the plausibility of a given distribution to be represented by the estimated parameters.…”

Section: Introductionmentioning

confidence: 99%

“…However, for some cases, small-sized samples can produce estimators comparable or even inferior to other methods. The L-Moments method (LM) produces parameters comparable in quality to those produced by the ML method, however, for small samples, LM method can be more accurate, and thus, better performance (Naghettini; Pinto, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…The Anderson -Darling test is an alternative at to the ChiSquare and Kolmogorov-Smirnov tests, as it gives more weight to the tails of the frequency distribution, being more recommended for asymptotic distributions (Naghettini; Pinto, 2007).…”

Section: Introductionmentioning

confidence: 99%

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Performance of the probability distribution models applied to heavy rainfall daily events

et al. 2014

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Probabilistic studies of hydrological variables, such as heavy rainfall daily events, constitute an important tool to support the planning and management of water resources, especially for the design of hydraulic structures and erosive rainfall potential. In this context, we aimed to analyze the performance of three probability distribution models (GEV, Gumbel and Gamma two parameter), whose parameters were adjusted by the Moments Method (MM), Maximum Likelihood (ML) and L -Moments (LM). These models were adjusted to the frequencies from long-term of maximum daily rainfall of 8 rain gauges located in Minas Gerais state. To indicate and discuss the performance of the probability distribution models, it was applied, firstly, the non-parametric Filliben test, and in addition, when differences were unidentified, Anderson-Darlling and Chi-Squared tests were also applied. The Gumbel probability distribution model showed a better adjustment for 87.5% of the cases. Among the assessed probability distribution models, GEV fitted by LM method has been adequate for all studied rain gauges and can be recommended. Considering the number of adequate cases, MM and LM methods had better performance than ML method, presenting, respectively, 83% and 79.2% of adequate cases.Index terms: Probability distribution models, intense rainfall, statistical inference, non-parametric statistical tests. RESUMOEstudos probabilísticos de variáveis hidrológicas, como a precipitação pluvial diária máxima, constituem-se um importante instrumento de apoio para o planejamento e gestão de recursos hídricos, principalmente quando associados ao dimensionamento de estruturas hidráulicas e potencial erosivo. Neste contexto, objetivou-se analisar o desempenho de três distribuições de probabilidades (GEV, Gumbel e Gama a dois parâmetros), cujos parâmetros foram ajustados pelos métodos dos Momentos (MM), da Máxima Verossimilhança (ML) e dos Momentos-L (ML), aplicados às séries históricas de precipitação diária máxima de 8 estações pluviométricas, localizadas no centro oeste de Minas Gerais. Para a verificação da melhor combinação distribuição de probabilidade e método de estimativa dos parâmetros das distribuições, aplicou-se o teste de aderência de Filliben, e, complementarmente, quando não identificadas diferenças, utilizou-se dos testes de Anderson Darlling e Qui-quadrado. A Distribuição de Probabilidades de Gumbel apresentou melhor desempenho, ajuste em 87,5% dos casos. Entre as distribuições de probabilidades avaliadas, a GEV ajustada por ML, apresentou aderência para todas as estações pluviométricas, podendo ser indicada. Considerando o numero de ajustes verificados, os métodos de estimação dos parâmetros MM e ML apresentaram melhor desempenho do que o método ML, apresentando, respectivamente, 83% 79.2% de casos adequados.Termos para indexação: Distribuição de probabilidades, chuvas intensas, inferência estatística, testes estatísticos não paramétricos.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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