O presente trabalho discute as variações hidrogeoquímicas nas águas subterrâneas dos ambientes carbonáticos do Estado da Bahia. As Formações (Fm) em estudo são: Fm Salitre; Fm Sete Lagoas/Lagoa do Jacaré; e Fm Olhos d’água/Jacoca. Os resultados apontam que as Fm Olhos d’água/Jacoca apresentam maior concentrações de constituintes químicos, dureza, salinidade e assinatura geoquímica revelando tendências cloretadas e sódicas. A CE apresentou forte correlacão com Na+ e Cl-, componentes pluviométricos. As Fm Sete Lagoas/Lagoa do Jacaré apresentaram menor concentração de elementos químicos, dureza, salinidade e assinatura geoquímica revelando tendências bicarbonatada cálcica. A CE apresentou forte correlação com o Na+, Cl-, SO4-2 e HCO3-, indicando contribuição climática e litológicos. Já na Fm Salitre apresentou assinatura geoquímica revelando tendências bicarbonatada, cálcica e secundariamente magnesiana. A CE apresentou forte correlação com o Mg+2, indicando influência de componentes litológicos. Os três ambientes se diferenciaram em relação às médias de Mg+2 e HCO3-2. Já as Fm Sete Lagoas/Lagoa do Jacaré se diferenciam das demais devido às médias de Ca+2. Estes resultados foram associados as diferentes distribuições mineralógicas nas litofácies. As Fm Sete Lagoas/Lagoa do Jacaré também se diferenciam da Fm Salitre devido às médias de SO4-2, possivelmente associado à variação de concentração de sulfetos nas áreas.
The Marizal/São Sebastião aquifer system is the main water supply of the municipality of Alagoinhas in the state of Bahia. However, anthropic interventions contribute to soil and groundwater pollution, increasing the need for related research. Multivariate statistical analysis is a widely used tool, helping in the investigation of groundwater quality while being capable of simultaneously evaluating diverse variables of a sample set. In this study, factor analysis and multivariate cluster analysis methodologies were applied. Ten of the most influential variables for groundwater quality were selected and then grouped into two factors. The first factor included electrical conductivity, salinity, calcium, chloride, sulfate, manganese, and iron, which are indicators of water salinity. The second factor encompassed pH, bicarbonate, and phosphate, indicating anthropic interventions and alkalinity in the environment. The multivariate cluster analysis was applied to the parameters of both factors, resulting in dendrograms with four clusters. The present study showed that the multivariate statistical analysis is an efficient tool for monitoring and can contribute to the management of groundwater quality.
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