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| Pérez Figueroa, Rebeca Alejandra. |
| Las precipitaciones extremas en el estado de Tabasco, México, causan pérdidas económicas y serios estragos a los ecosistemas cada año. Esta investigación se basa en el desarrollo de un análisis de eventos de precipitación extrema en Tabasco empleando la información en la base de datos MAYA que comprende observaciones de lluvia diarias para nodos-geográficamente equidistantes. El principal objetivo es proponer un modelo de regresión espacial para datos de precipitaciones extremas con el fin de estimar períodos de retorno vía un modelo jerárquico Bayesiano, y proveer de mapas de riesgo basados en el modelo ajustado así como en la distribución predictiva de precipitación extrema. Se encontró que la localización geográfica incrementa la exactitud en la... |
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Palavras-chave: Bayesiano; Regresión espacial; Lluvia extrema; Bayesian; Spatial regression; Extreme rainfall; Estadística; Maestría. |
| Ano: 2012 |
URL: http://hdl.handle.net/10521/782 |
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| Batista,Marcelo L.; Coelho,Gilberto; Mello,Carlos R. de; Oliveira,Marcelo S. de. |
| ABSTRACT Extreme rainfall can lead to heavy damage and losses, such as landslides, floods and agricultural productivity as well as the loss of human and animal lives. To mitigate these losses, water resources management policies are needed, among other goals, to study and predict the frequency of such events in a given region to minimize their harmful effects. The present study investigated the Generalized Extreme Value (GEV) probability distribution applied to the annual maximum daily precipitation data from rainfall stations in the southeastern Brazil. A total of 1,921 rainfall stations were considered, among which the stations with at least 15 years of uninterrupted observations were selected. Subsequently, the stationarity and adherence were tested.... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Extreme rainfall; GEV; Ordinary kriging. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100097 |
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| Machado,Roriz Luciano; Ceddia,Marcos Bacis; Carvalho,Daniel Fonseca de; Cruz,Eleandro Silva da; Francelino,Marcio Rocha. |
| Knowledge of maximum daily rain and its return period in a region is an important tool to soil conservation, hydraulic engineering and preservation of road projects. The objective of this work was to evaluate the spatial variability of maximum annual daily rain considering different return periods, at the Rio de Janeiro State. The data set was composed by historical series of 119 rain gauges, for 36 years of observation. The return periods, estimated by Gumbel distribution, were 2, 5, 10, 25, 50 and 100 years. The spatial variability of the return periods was evaluated by semivariograms. All the return periods presented spatial dependence, with exponential and spherical model fitted to the experimental semivariograms. The parameters of the fitted... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Runoff; Extreme rainfall; Geostatistics; Kriging. |
| Ano: 2010 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500009 |
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