2005 Salt Lake City Annual Meeting (October 16–19, 2005)

Paper No. 14
Presentation Time: 8:00 AM-12:00 PM

TRANSPORT OF ANTHROPOGENIC AND NATURAL COMPOUNDS IN THE EDWARDS AQUIFER, SOUTH-CENTRAL TEXAS


FAHLQUIST, Lynne, U.S. Geological Survey, 8027 Exchange Drive, Austin, TX 78754-4733 and LINDGREN, Richard J., U.S. Geological Survey, 5563 DeZavala Road, Suite 290, San Antonio, TX 78249, lfahlqst@usgs.gov

An investigation of transport of natural and anthropogenic contaminants to public supply wells in the Edwards aquifer in the San Antonio area is underway as part of the U.S. Geological Survey National Water-Quality Assessment Program. The prolific fractured karstic Edwards aquifer supplies approximately 450,000 acre-feet per year for municipal and other uses. This study is being conducted at two spatial scales, one regional (5340 square miles) and one local (a few square miles). The regional-scale study includes analysis of water-quality data and ground-water-flow modeling to identify zones of contribution to public supply wells. The local-scale area is defined by a modeled contributing area to a selected public supply well. The data are being used to evaluate natural and anthropogenic variables that influence the occurrence of contaminants in public supply wells.

A regional ground-water-flow model, calibrated for both steady-state (1939–46) and transient (1947–2000) conditions is being used to simulate areas contributing recharge to selected metropolitan San Antonio public supply wells. Three-dimensional hydrogeologic information is needed to more accurately simulate flow, and subsequently transport, in the local-scale study. The local-scale model uses hydrostratigraphic, (borehole, surface, and airborne) geophysical, environmental tracer, and structural mapping data. Deterministic and probabilistic modeling approaches also are being used. Probabilistic methods include parameter estimation, Monte Carlo simulations, and statistically-based fracture simulations. Results from these approaches are being combined to identify contributing areas for the local-scale area.