Factor analysis is useful for interpreting commonly collected ground‐water quality data and relating those data to specific hydrogeologic processes. One hundred nine ground‐water quality samples from wells completed in the upper Floridan Aquifer near Live Oak, Florida were analyzed for major dissolved constituents. R‐mode factor analysis was used to separate those chemical variables that reflect areally‐significant recharge processes from those related strictly to the dissolution of aquifer materials. Areas impacted by direct, rapid, artificial recharge through drainage wells and sinkholes, as well as by slow, natural recharge into the Floridan Aquifer, were delineated. Four factors which represent different chemical processes were identified and their relative areal impact determined. These processes are: (1) regional dissolution of the aquifer limestone, (2) dissolution and ion exchange in the discontinuous, semipermeable layer that overlies portions of the aquifer, (3) and (4) recharge from local, urban and agricultural runoff.

Hydrochemical facies interpretations are useful tools for determining the flow patterns, origins, and chemical histories of ground‐water masses. Factor analysis is advantageous for hydrochemical interpretations because it is independent of the number or type of variables used. Factor analysis also allows avoidance of problems of closed‐number systems inherent in more traditional techniques, such as trilinear diagrams. This paper applies factor analysis to the interpretation of mixing between sulfate and bicarbonate ground‐water masses. Whereas trilinear diagrams show one mixing trend (bicarbonate with sulfate waters), factor analysis allows interpretation of multiple mixing trends. These trends include the bicarbonate‐sulfate trend; a sodium‐, silica‐, fluoride‐, and temperature‐mixing system that is interpreted as resulting from recharge; and a chloride‐sodium system that appears to represent mixing with residual, connate water. The latter trends are identified as small‐scale, chemical variations that result in dispersion of the data points about the dominant mixing trend on the trilinear diagram. Thus, factor analysis provides greater precision in identifying hydrochemical facies and interpreting their origins.

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