Análise da evolução temporal da região semiárida brasileira a partir de base de dados espacializada em alta resolução

• Ano de defesa: 2025
• Autor(a) principal: Lima, Ronaldo Guilherme Santos
• Orientador(a): Mendes, Ludmilson Abritta
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Programa de Pós-Graduação: Pós-Graduação em Engenharia Civil
• Palavras-chave em Português: Índice de aridez; Análise de tendência; Variação de temperatura; Mudanças climáticas
• Palavras-chave em Inglês: Aridity index; Trend analysis; Temperature variation; Climate change
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA CIVIL
• Link de acesso: https://ri.ufs.br/jspui/handle/riufs/21346

For an effective meteorological observation that accurately represents climatic conditions, it is essential that it be conducted in a systematic, uniform, and uninterrupted manner, particularly in the context of climate change. Elevated concentrations of greenhouse gases in the atmosphere result in planetary warming, which, in turn, leads to rising temperatures and an intensification of heat waves. The increase in temperature raises Evapotranspiration (ET) levels and may cause alterations in Precipitation (P) patterns globally. In this context, the primary objective of this dissertation is to analyze the delimitation of the Brazilian semi-arid region based on the criteria of Precipitation (P < 800 mm) and Aridity Index (AI < 0.5), in order to identify the municipalities that belong to this territory. The study was applied to the nine states of the Brazilian Northeast (NEB), as well as Minas Gerais and Espírito Santo. The BR-DWGD Database was used to obtain Tmax, Tmin, ET, and P data for the period from 1961 to 2020, and the AI series was derived from the ratio between P and ET. These series enabled an analysis of the temporal evolution of these variables, as well as a comparison between the official delimitation of the semi-arid region and the results for municipalities that presented Precipitation < 800 mm and AI < 0.5. A historical series analysis and trend assessment were conducted using routines in RStudio and with the support of QGIS. The study revealed an expansion of areas with Tmax > 31°C and Tmin > 19°C, indicating regional warming associated with Atlantic warming and greenhouse gas emissions. Evapotranspiration (ET > 1800 mm) increased, particularly in agricultural areas, while regions with P < 600 mm expanded, impacting the semi-arid zone and leading to a reduction in humid areas. The AI analysis highlighted the emergence of an arid climate, particularly in Bahia, with an eastward and northward expansion of arid conditions and a growing semi-arid area, while humid regions declined over time. The delimitation of the semi-arid region based on Precipitation and AI criteria, using data from 1991 to 2020, showed a greater coincidence with the delimitation of the Caatinga biome.