Avaliação da viabilidade de uso de precipitações obtidas por sensoriamento remoto em simulações hidrológicas na bacia do rio Japaratuba/SE

• Ano de defesa: 2015
• Autor(a) principal: Rocha, Leonardo Teixeira
• Orientador(a): Cruz, Marcus Aurélio Soares
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Sergipe
• Programa de Pós-Graduação: Pós-Graduação em Recursos Hídricos
• País: Brasil
• Palavras-chave em Português: Recursos hídricos; Precipitação (Meteorologia) – Previsão; Ciclo hidrológico; Satélites artificiais em sensoriamento remoto; TRMM (Satélites); Modelagem; Win_iph2; Sensoriamento remoto; Simulação hidrológica
• Palavras-chave em Inglês: Modeling; Remote sensing
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA SANITARIA
• Link de acesso: https://ri.ufs.br/handle/riufs/6181

Precipitation is considered one of the most important variables in the water cycle constantly being used for the validation of numerical models of weather and climate forecasting, water balance, radiation, among others. Understanding the spatial variability of rainfall in a given region is essential, since its interannual and seasonal pattern is crucial for agriculture and for many sectors of the economy. In this context, the reliability of estimates of rainfall becomes paramount. Brazil, with its continental dimensions, has big problems concerning the distribution of weather stations, the network of stations does not cover the whole territory satisfactorily, thus, estimated errors can significantly influence the analysis of runoff, the water deficit and the energy balance. Thus, hydrologists around the world have developed alternative techniques for obtaining the precipitation values; among these techniques, satellite photos can be highlighted. This study assessed the feasibility of applying estimated rainfall data from remote sensing by TRMM satellite in hydrologic simulation in the Japaratuba river basin, it was also analyzed the direct correlation between the precipitation values obtained through the TRMM and the values measured at the stations. The results indicate that in accumulated time scales, as ten days or monthly, estimates are better accurate than in daily scale. The rainfall-runoff simulation values obtained were 0.7 for Nash-Sutcliffe coefficient and 0.84 for Pearson Correlation, both in a monthly scale. The application in hydrological modeling should be preceded by an evaluation of data quality comparing with the pluviometric stations of the study area.