The ground water quality of the Trinity Aquifer for wells sampled between 2000 and 2009 was examined using multivariate and spatial statistical techniques. A Kruskal-Wallis test revealed that all of the water quality parameters with the exception of nitrate vary with land use. A Spearman’s rho analysis illustrates that every water quality parameter with the exception of silica correlated with well depth. Factor analysis identified four factors contributable to hydrochemical processes, electrical conductivity, alkalinity, and the dissolution of parent rock material into the ground water. The cluster analysis generated seven clusters. A chi-squared analysis shows that Clusters 1, 2, 5, and 6 are reflective of the distribution of the entire dataset when looking specifically at land use categories. The nearest neighbor analysis revealed clustered, dispersed, and random patterns depending upon the entity being examined. The spatial autocorrelation technique used on the water quality parameters for the entire dataset identified that all of the parameters are random with the exception of pH which was found to be spatially clustered. The combination of the multivariate and spatial techniques together identified influences on the Trinity Aquifer including hydrochemical processes, agricultural activities, recharge, and land use. In addition, the techniques aided in identifying areas warranting future monitoring which are located in the western and southwestern parts of the aquifer.

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Thesis (Ph. D.)--University of Texas at Austin, 2005. / Supervisors: David M. Hillis and Dean Hendrickson. Vita. Includes bibliographical references.

High concentrations of sulfate in groundwater, up to ten times the amount recommended by the EPA, in Blanco and Hays Counties, Texas, are of concern as groundwater pumping and population increase. The goals of this study are to characterize the chemistry of groundwaters in Blanco and Hays Counties within the context of Texas Groundwater Management Area-9 and to determine chemically and hydrogeologically the explanation for the spatial distribution of sulfate between the Pedernales River, the Blanco River, and Onion Creek. Insights gained by examining sulfate distribution in Blanco and Hays Counties can be applied to the other counties on the Edwards-Trinity Plateau with similarly high concentrations of sulfate in groundwater. Hydrochemical data from the Cretaceous Edwards and Trinity Groups and water level measurements were used to analyze groundwater chemistry and flow. PHREEQC was used to examine whether phase changes in aquifer minerals could explain the observed geochemical patterns. COMSOL was used to develop a simplified groundwater flow model for a cross-sectional area between the Pedernales River and Onion Creek in Hays County. Water levels indicate that groundwater generally flows southeast in the study area and most streams are gaining. The groundwater flow model indicates a zone of slow-moving groundwater beneath the topographic high between the Pedernales River, the Blanco River, and Onion Creek. Chemical analyses of well data show the presence of four groundwater chemical endmembers in Groundwater Management Area-9; a Ca-Mg-HCO3 fresh endmember, a Ca-Mg-SO4 endmember, a Ca-Mg-SO4-Na-Cl endmember, and a Na-Cl endmember. High sulfate waters generally come from the Upper and Middle Trinity aquifers while fresher waters are from the Edwards aquifer. Physical and chemical analyses indicate that the zone of high sulfate in Blanco and Hays Counties may be the result of gypsum dissolution and dedolomitization in the Upper and Middle Trinity aquifers combined with low rates of groundwater flow beneath the topographic high. Groundwater flow analyses are consistent with those for the Groundwater Availability Models published for the region. Chemical analyses, specifically SO4 distributions and Ca/Mg ratios, are consistent with those found by Nance(2010) on the Edwards Plateau, farther west of the study area. / text

The use of cross-correlation analysis on spring discharge and precipitation data in karst aquifer basins has been used for many years to develop a conceptual understanding of an aquifer and estimate aquifer properties. However, to this point, the application of these processes has relied on gaged precipitation at discrete locations. The use of spatially varying precipitation data and cross-correlation analysis provides a means of spatially characterizing recharge locations on a karst aquifer. NEXRAD provides a spatial estimate of precipitation based by combining reflectivity measurements from radar stations and traditional precipitation gages. This study combines NEXRAD precipitation data with spring discharge data to develop maps of contributing areas for two karst springs in Central Texas. By calculating the cross-correlation of each NEXRAD measurement to spring flow data for the same period of time a map showing the locations hydraulically connected to the spring can be developed. Both numerical experiments and field applications were conducted as part of the study. The numerical experiments conducted by Padilla and Pulido-Bosch are revisited using the numerical groundwater model MODFLOW. This allowed the introduction of spatially varying parameters into the model. The results show that spatially varying parameters can be inferred based on the results cross-correlation of spatially varying precipitation with respect to a single spring discharge location. Also, contributing area maps are prepared for both Barton Springs and Jacob’s Well. Barton Springs has a precise estimate of the recharge area. The current map of the recharge area and the NEXRAD derived map show good agreement with the cross-correlation results. Conversely, Jacob’s Well has not been sufficiently studied to delineate a contributing area map. This study provides an preliminary estimate of the area contributing to flow at Jacob’s Well. Finally, the development of these maps can also be applied to the construction of regional groundwater models. An application of this methodology with the groundwater availability model for the Barton Springs portion of the Edward’s aquifer is introduced. The application of spatial cross-correlation analysis to constrain recharge in the model showed a reduction in the objective function with respect to discharge at Barton Springs of 15%. / text