Jennifer Teerlink, M.S., Bruce Gallaher, Enid J. Sullivan, Ardyth M. Simmons, David B. Rogers and Patrick Longmire, Ph.D., Los Alamos National Laboratory
In order to monitor contaminants in the groundwater beneath Los Alamos National Laboratory successfully, it is necessary to identify constituents at elevated concentrations above background. Background is defined as concentrations of analytes in groundwaters that have not been impacted by the Laboratory. The hydrogeology beneath and adjacent to the Pajarito Plateau is variable and complex, making it challenging to establish representative background values. The regional aquifer spans multiple geologic units with waters of variable age, resulting in a wide range in geochemistry. For example, water composition ranges from low total dissolved solids (TDS) near mountain recharge areas to waters discharging near the Rio Grande with high TDS and include high concentrations of boron, uranium, and arsenic among other constituents. Currently there are two specific uses for background values: statistical screening of all analytical data to identify potential contamination, and analysis of well chemistry to identify any impact from residual drilling fluids along screened intervals. Established background values must account for natural variability in order to be applied successfully to each use. Background locations were selected based on length of record, quality of well, consistency of sample location for springs, and lack of impact from Laboratory activities. Locations were grouped using a cluster analysis and principal component analysis of geochemical constituents. The result is two groupings; the first a less geochemically evolved group that is lower in TDS, the second a more geochemically evolved group that is greater in TDS. The groupings established through this statistical approach fit well with the current understanding of the groundwater flow system, which reflects groundwaters of varying ages, displaying various degrees of rock/water interaction. A suite of statistical values has been calculated according to these groupings. Monitoring samples can be screened for contamination more effectively based on their association with a particular background geochemical grouping.
The 2007 Ground Water Summit