Caracterização do comportamento de falhas nas séries de precipitação do Rio Grande do Sul

• Ano de defesa: 2021
• Autor(a) principal: Faria, Elaine Silva de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• dARK ID: ark:/26339/001300000f648
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia Ambiental; UFSM; Programa de Pós-Graduação em Engenharia Ambiental; Centro de Tecnologia
• Palavras-chave em Português: Precipitações pluviométricas; Observações incompletas; Dados horários; Dados diários; Estações meteorológicas automáticas; Pluviometric precipitation; Incomplete observations; Hourly data; Daily data; Automatic weather stations; CNPQ::ENGENHARIAS
• Link de acesso: http://repositorio.ufsm.br/handle/1/24882

The automatic weather stations provide hourly information over pluviometric precipitation, and it is recurrent the occurrence of missing data in these data series. This situation compromise the data analysis, since it makes the data series inconsistent and smaller, what creates considerable uncertainty towards the estimation of precipitation quantity. Considering that, this paper has as goal to characterize the behavior of missing data in pluviometric precipitation series obtained in automatic weather stations, located in the state of Rio Grande do Sul, during the period of january 1, 2015 to december 31, 2019. With the hourly data of pluviometric precipitation, to the 38 automatic weather stations, from the Nacional Institute of Meteorology (INMET), it was created maps to visualize the spacial behavior of the average hourly faults in each weather station and in each month of the year. The next step was to assess the efect of the different months of the year in the mean number of hourly missing diary data, it was applied a non-parametric analysis of variance for repeted measures. To assess the efect of the quantity of hours with effective information in the composition of a valid diary data in the precipitation series, it was proposed four definitions of a valid diary data. Based on yhe values of mean pluviometric precipitation and valid hourly numbers in each definition, it was calculated deviations from mean precipitation values. To model the mean diary precipitation desviations it was used the Gama regression model with adjustment in zero. It was observed that most of the automatic weather stations with higher mean values of hourly faults were located in the state borders of Rio Grande do Sul, with spotlight to the west/south border of the state of RS. Most of the automatic weather stations presented a lower mean numbers of hourly faults in the month of december. And the higher mean quantities of hourly faults happened in june and july. It was possible to define the minimal number of 19 hours with measurement values of pluviometric precipitation to be considered a valid day of pluviometric precipitation.