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Environmental and Engineering Geoscience; May 2005; v. 11; no. 2; p. 107-123; DOI: 10.2113/11.2.107
© 2005 Association of Engineering Geologists
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Identifying the Source of Saline Groundwater Contamination Using Geochemical Data and Modeling

MATTHEW M. ULIANA1

1 Geology Program and Aquatic Resources (Department of Biology), Texas State University-San Marcos, 601 University Drive, San Marcos, TX 78666

The source of salinization of an unconfined aquifer located in West Texas, near the Pecos River, is determined by a combination of graphical methods, comparative statistics, mass–balance mixing models, and geochemical thermodynamic equilibrium models. Water samples from the site are divided into two groups: Group 1 samples are chemically similar to groundwater samples typical of the region; Group 2 samples are chemically similar to salt-water disposal (SWD) brines injected into deeper formations for disposal and petroleum recovery enhancement. The spatial distribution of the two groups and the results of statistical analyses support the similarity between the Group 2 and the SWD samples and are consistent with the hypothesis that the Group 2 samples were contaminated by SWD brine. Bivariate plots and mixing models suggest that the Group 2 samples are a combination of brine contamination and subsequent reaction with mineral phases present in the aquifer. Three conceptual models for salinization of the Group 2 wells are tested using geochemical models: 1) evaporation of groundwater with no contamination, 2) release of brine directly into the aquifer, and 3) deep release of brine with mineral reactions in the subsurface. Results indicate that the most likely scenario is a deep release of brine, equilibration with halite in the underlying formation, and release of the modified brine into the shallow aquifer with subsequent mineral-phase reactions. The model results suggest that Br/Cl, widely accepted as a conservative ratio, can be modified by dissolution of low Br halide minerals.

Key Words: Salinization • Geochemistry • Site Investigations • Contamination • Modeling • Statistics







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