title: A ternary age-mixing model to explain contaminant occurrence in a deep supply well.
abstract: The age distribution of water from a public-supply well in a deep alluvial aquifer was estimated and used to help explain arsenic variability in the water. The age distribution was computed using a ternary mixing model that combines three lumped parameter models of advection-dispersion transport of environmental tracers, which represent relatively recent recharge (post-1950s) containing volatile organic compounds (VOCs), old intermediate depth groundwater (about 6500 years) that was free of drinking-water contaminants, and very old, deep groundwater (more than 21,000 years) containing arsenic above the USEPA maximum contaminant level of 10 µg/L. The ternary mixing model was calibrated to tritium, chloroflorocarbon-113, and carbon-14 (14C) concentrations that were measured in water samples collected on multiple occasions. Variability in atmospheric 14C over the past 50,000 years was accounted for in the interpretation of (14) C as a tracer. Calibrated ternary models indicate the fraction of deep, very old groundwater entering the well varies substantially throughout the year and was highest following long periods of nonoperation or infrequent operation, which occured during the winter season when water demand was low. The fraction of young water entering the well was about 11% during the summer when pumping peaked to meet water demand and about 3% to 6% during the winter months. This paper demonstrates how collection of multiple tracers can be used in combination with simplified models of fluid flow to estimate the age distribution and thus fraction of contaminated groundwater reaching a supply well under different pumping conditions.
authors.affiliation: U.S. Geological Survey, 5338 Montgomery Blvd. NE, Suite 400, Albuquerque, NM 87109.
authors.forename: Bryant C
authors.initials: BC
authors.lastname: Jurgens
authors.forename: Laura M
authors.initials: LM
authors.lastname: Bexfield
authors.forename: Sandra M
authors.initials: SM
authors.lastname: Eberts
mesh_terms: D001151:Arsenic / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods*; D060587:Groundwater / Q000032:analysis*; D008962:Models, Theoretical; D009516:New Mexico; D013997:Time Factors; D014872:Water Movements; D014874:Water Pollutants, Chemical / Q000032:analysis*
chemical_list: D014874:Water Pollutants, Chemical; D001151:Arsenic