Title

Updated numerical model with uncertainty assessment of 1950-56 drought conditions on brackish-water movement within the Edwards aquifer, San Antonio, Texas

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Publication Date

January 2015

Abstract

In 2010, the U.S. Geological Survey, in cooperation with the San Antonio Water System, began a study to assess the brackish-water movement within the Edwards aquifer (more specifically the potential for brackish-water encroachment into wells near the interface between the freshwater and brackish-water transition zones, referred to in this report as the transition-zone interface) and effects on spring discharge at Comal and San Marcos Springs under drought conditions using a numerical model. The quantitative targets of this study are to predict the effects of higher-than-average groundwater withdrawals from wells and drought-of-record rainfall conditions of 1950–56 on (1) dissolved-solids concentration changes at production wells near the transition-zone interface, (2) total spring discharge at Comal and San Marcos Springs, and (3) the groundwater head (head) at Bexar County index well J-17. The predictions of interest, and the parameters implemented into the model, were evaluated to quantify their uncertainty so the results of the predictions could be presented in terms of a 95-percent credible interval. The model area covers the San Antonio and Barton Springs segments of the Edwards aquifer; the history-matching effort was focused on the San Antonio segment. A previously developed diffuse-flow model of the Edwards aquifer, which forms the basis for the model in this assessment, is primarily based on a conceptualization in which flow in the aquifer is predominately through a network of numerous small fractures and openings. Primary updates to this model include an extension of the active area downdip, a conversion to an 8-layer SEAWAT variable-density flow and transport model to simulate dissolved-solids concentration effects on water density, history matching to 1999–2009 conditions, and parameter estimation in a highly parameterized context using automated methods in PEST (a model-independent Parameter ESTimation code). In addition to the best-fit parameter values derived from history matching, the uncertainty

Notes

USGS, Vol. 2,015, no. 5081 (2015).

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serial

Identifier

SFS0072700_00001

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