Paper No. 8
Presentation Time: 3:15 PM
Public-Supply Well Vulnerability in the Edwards Aquifer, San Antonio, Texas
Public-supply well (PSW) vulnerability to contamination from common environmental compounds, often at very small (less than 1 microgram per liter) concentrations, is a national priority being addressed by the U.S. Geological Survey National Water-Quality Assessment Program. The nationwide study has several objectives with respect to PSWs: identify sources of chemicals under study; assess the importance of natural processes and anthropogenic activities on chemical occurrence; identify important factors affecting PSW vulnerability; develop simple methods for assessing vulnerability to contamination; and improve understanding of the effects of water-resource management decisions on water quality. The fractured, karstic Edwards aquifer is one of eight areas across the Nation selected for study. First, a regional-scale investigation of the Edwards aquifer will allow comparison of important chemical-transport mechanisms to those of other water-supply aquifers across the Nation and enhance understanding of common transport and transformation processes within the contributing areas of PSWs. Second, water from large-capacity PSWs generally is a mixture of waters that enter the well at different depths and thus are associated with different potential sources of chemicals. Samples are being collected from vertically nested monitoring wells and at multiple depths in a pumping PSW to assess the potential vulnerability of the well to chemicals under study. And last, resource managers need to know the area providing recharge to a PSW and the travel time between a potential chemical source and the PSW to make informed decisions. This information cannot be measured directly so resource managers must rely on estimates that are inherently uncertain. This study offers an opportunity to better understand the inherent uncertainty by comparing estimates of contributing areas and travel times on the basis of traditional and probabilistic modeling approaches with water-quality data from in and near PSWs.