Uso de base de dados hidrológicos espacializada em alta resolução para estudo de indicadores climáticos em Sergipe

• Ano de defesa: 2023
• Autor(a) principal: Souza, Thiers Pereira de
• 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: Engenharia civil; Variáveis climáticas; Análise estatística; Aplicativo
• Palavras-chave em Inglês: Climate variables; Statistical analysis; Application
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA CIVIL
• Link de acesso: https://ri.ufs.br/jspui/handle/riufs/18395

The main objective of this work was to evaluate the behavior of the hydrometeorological variables of evolution (P) and evapotranspiration (ETo) in Sergipe, using data from the BRDWGD base with high spatial (0.1ºx0.1º) and temporal (1961-2020) resolution. ). ), produced by Xavier et al. (2022). The selected data were organized by river basin and grouped to evaluate the annual series, the driest quarters (TMS) and the wettest quarters (TMU). In addition, the Aridity Index (AI) was calculated to classify the climate over the years and verify the susceptibility to desertification in the State. To help understand the behavior of these series over the years, statistical analyzes were performed, including parking tests such as Spearman and Mann-Kendall, and the Pettitt test for detection of change points. In these analyses, no trends were discovered in rainfall or AI when evaluating all time groupings (annual, TMS and TMU) and watersheds. Regarding ETo, an increasing behavior was observed in 5 of the 8 basins of the State in the annual and TMS series. However, in the ETo TMU series, it was not possible to identify such behavior, but it was verified that it had little representation in an annual context. Spatial analyzes were performed to evaluate the long-term means (MLT) of P, ETo and AI using annual groupings, TMS and TMU, and two-time frames (1961-1990 and 1991-2020). These analyzes identified changes in the dynamics of all these variations. With the AI, it was even possible to identify 3 types of climates: humid subhumid, dry subhumid and semi-arid, and it was possible to identify the regions susceptible to desertification, mainly in the northwest and west of the state. Specific maps and files will be shared with society through Google Drive. In order to expand society's access to the information in this work, an application for Android called PR-ET mobile was created, which allows obtaining information on the occurrence (P), evapotranspiration (ETo) and the aridity index (IA) for all hydrographic basins of Sergipe. Finally, a new plan was suggested to compose the delimitation of the semi-arid region, based on the monthly difference between P and ETo, which proved to be feasible in view of the results presented.