Avaliação de índices de seca aplicados a uma bacia hidrográfica localizada no sudeste brasileiro: estudo de caso da bacia hidrográfica do Rio São Mateus - ES/MG

• Ano de defesa: 2019
• Autor(a) principal: Silva, Fernando Roberto da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado Profissional em Gestão e Regulação de Recursos Hídricos; Centro Tecnológico; UFES; Programa de Pós-Graduação em Gestão Regulação Recursos Hídricos
• Palavras-chave em Português: Índice de seca; SPI; SRI; HSI; RAI; Seca; Matriz de seleção; Drought; Selection matrix; subject.br-rjbn; Ciências Ambientais
• Link de acesso: http://repositorio.ufes.br/handle/10/15668

The Ministry of National Integration (2016) defines drought as prolonged periods of low or no rainfall, where soil moisture loss is greater than replacement and defines drought as prolonged drought long enough for lack of precipitation to cause severe imbalance. hydrological. Drought anomalies are natural disasters most often affecting humans and the environment. Drought indices are useful tools to aid in the measurement, characterization and support of drought alert measures. This work aims to identify drought indices able to analyze hydrological data of the Säo Mateus River basin (ES and MG). Data from the Cörrego Boa Esperanca (ANA code 55920000) and pluviometric Barra de Säo Francisco (ANA code 01840004) river basins, in the Cricaré River sub-basin and the rainwater (stations ANA code 01841008) and Ataléia in the Cotaxé River sub-basin. With data from the prioritized stations, the standardized Precipitation Index (SPI) weather drought indexes of McKee et al. (1993), Herbst Severity Index (HSI), by Herbst et al. (1966) and Rooy's Precipitation Anomaly Index (RAI) (1965). For hydrological drought, the Standardized Runoff Index (SRI) of SHUKLA and WOOD (2007) was applied. The RAI - SECA index presented better characteristics for the warning system, the HSI was more conservative and the SPI index showed intermediate characteristics, identifying a significant number of monthly and long term drought anomalies. Regarding surface runoff, the SRI index showed a good correlation with SPI, confirming the relationship between precipitation and runoff. No reduction in runoff was identified throughout the series studied. The hydrological data and drought index selection matrices proved to be important tools in the selection of drought indices and hydrological data, prioritizing drought indices suitable for hydrological data of the territory under study. Regarding the selected indices, it was possible to identify potential use as a warning tool and confirmation of the occurrence of drought.