Caracterização espaço-temporal da precipitação nas escalas subhorária e subdiária no Brasil

• Ano de defesa: 2022
• Autor(a) principal: Lemos, Filipe Carvalho
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Engenharia Civil e Ambiental; Programa de Pós-Graduação em Engenharia Civil e Ambiental; UFPB
• Palavras-chave em Português: Mínimo intervalo de tempo; Eventos chuvosos; Variabilidade espacial; Minimum time interval; Rainy events; Spatial variability; CNPQ::ENGENHARIAS::ENGENHARIA CIVIL
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/23139

The study of the properties of rainfall events at various spatio-temporal scales is of great importance for the understanding of environmental processes and variables, as well as socioeconomic activities. These studies on rainfall characteristics, mainly in sub-hourly resolutions, are not carried out in large areas of South America due to lack of data. The National Center for Monitoring and Alerting Natural Disasters (CEMADEN) has gradually implemented, since 2011, a sub-hourly monitoring network, composed of approximately 3,500 automated rain gauges distributed in Brazil, opening new opportunities for hydrological studies in this vast tropical country. To fill this knowledge gap, this study analyzed the dynamics and spatio-temporal correlation of rainfall and its characteristics in Brazil on sub-daily and subhourly time scales, using seven years of data (from 2014 to 2020) provided by CEMADEN. The minimum time between events (MIT) and the minimum depth (MRD = 1 mm) were used to define the rainfall events. Seven MITs (i.e., 30, 60, 120, 180, 360, 720 and 1440 min) were considered to assess the characteristics of rainfall events and their interrelationship. The Gaussian Mixture Models (GMM) clustering algorithm was applied to identify regions with similar rainfall patterns according to the considered MIT. Six groups with similar rainfall patterns were identified in Brazil, and even though some groups are close in a specific property, they are considerably different in others. The results show that the MIT has a strong influence on the properties of precipitation, with dry weather (variation of 4,812%) and the number of events (variation of 45%) being the most sensitive variables to the variation of this parameter. The Northeast coast is the region where the most precipitation events occur, with more than 200 events per year (MIT < 60 min). In contrast, the Semiarid region presented the lowest number of events in Brazil, with an average of 69 per year and reaching only 38 events with na MIT of 1440 minutes. The Central regions (mainly), Semi-arid, North and the Southeast coast have very intense rains, which can cause, with greater ease; floods, inundations and inundations. The Northeast, South and Southeast Coasts have the volume of accumulated rain as the main alert factor. In terms of the spatial correlation between stations, the smaller the measurement interval, the smaller the correlation for the same distance. In terms of spatial correlation between the data from the stations, considering the resolution of 10 minutes, on average, 2.5 km is the distance necessary to guarantee a correlation of 0.7 between the rainfall stations in Brazil. The results of this study provide a better understanding of precipitation and its characteristics in Brazil.