Title

Recalibration and Predictive Simulations of the Analytic Element Tool to Evaluate the Trinity Aquifer in Hays County, Texas

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Publication Date

January 2018

Abstract

This Technical Memorandum documents an evaluation of the Trinity Aquifer in Hays County, Texas performed by INTERA, Inc. for Barton Springs/Edwards Aquifer Conservation District (“BSEACD” or the “District”). Electro Purification, LLC (EP) is seeking a production permit from the District to produce up to 2.5 million gallons of groundwater annually from the Cow Creek layer of the Trinity Aquifer in central Hays County. As part of the process of developing desired future conditions for the Trinity Aquifer, INTERA developed an analytic element groundwater model for the aquifer in this area in 2016 for Groundwater Management Area 10. For this earlier model we used the groundwater modeling code TTIM. TTIM is useful for evaluating impacts at the well-scale, though it does contain simplifications from the level of detail that is included in a typical MODFLOW-based groundwater availability model. Since the development of the TTIM analytic element model in 2016, a series of aquifer tests were performed by EP with monitoring of many nearby wells. These provide valuable additional information on the hydrogeology of the aquifer. Since the Texas Water Development Board has not yet developed a groundwater availability model for the Trinity Aquifer that extends through this area, the modeling evaluation documented here builds on and is considered a recalibration of the TTIM model previously developed using the information derived from the additional aquifer tests. We have also run a series of predictive simulations using the recalibrated model to evaluate potential drawdown impacts in the individual units of the Trinity Aquifer, and on selected wells in the area, due to proposed pumping from the EP well field. This memorandum documents the conceptual model of the Trinity Aquifer in central Hays County, the recalibration of the TTIM analytic element model, and the predictive simulations.

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RDA

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Article

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serial

Identifier

SFS0072132_00001

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