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    Karst Aquifer Recharge and Conduit Flow Dynamics From High-Resolution Monitoring and Transport Modeling in Central Pennsylvania Springs

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    Genre
    Thesis/Dissertation
    Date
    2019
    Author
    Berglund, James Lundstrom
    Advisor
    Toran, Laura E.
    Committee member
    Muto, Atsuhiro
    Grandstaff, David E.
    Herman, Ellen K.
    Schreiber, Madeline
    Department
    Geoscience
    Subject
    Hydrologic Sciences
    Geology
    Environmental Science
    Conduit Flow
    Geochemistry
    Groundwater Modeling
    Karst
    Rare Earth Element
    Storm Recharge
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/2596
    
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    DOI
    http://dx.doi.org/10.34944/dspace/2578
    Abstract
    Karst aquifers are dynamic hydrologic systems which are sensitive to short-term recharge events (storms) and heterogeneous recharge characteristics (point recharge at sinks, irregular soil thicknesses). These aquifers are highly productive yet also vulnerable to contamination, in large part because the conduit network is a significant unknown for predicting karst flow paths. To address these uncertainties, two adjacent karst springs, Tippery Spring and Near Tippery Spring, were monitored to better understand flow and source mixing characteristics. The two springs in central Pennsylvania’s Nittany Valley have similar discharges and are only 65 meters apart, yet they show unique behaviors in terms of water chemistry and discharge response to storms. First examined for flow characterization in 1971 by Shuster and White, the springs were analyzed in this study using high-resolution logging and new tracers such as rare earth element (REEs) and Ca/Zr ratios. This research contributes to the field of karst hydrology through innovative water sampling and monitoring techniques to investigate karst recharge and flow behavior along with conduit flow models incorporating multiple calibration target datasets such as water temperature and dye tracing. Stable isotope signatures (δD & δ18O) of storm water samples at the two springs varied based on storm intensity, but also due to their unique recharge behaviors. Increased spring discharge preceded the arrival of storm water as conduits were purged of pre-storm water, indicated by no change in isotopic composition on the rising limb. The isotopic signature then became progressively more enriched at both springs, indicating storm water recharge. At Tippery, this enrichment began around peak flow, sooner than at Near Tippery where enrichment began during the descending limb. Thus, isotopes indicated a stronger surface connection at Tippery Spring. Storm intensity also affected the relative contribution of recharging water reaching both springs, with a larger storm producing a larger recharge signature compared to a smaller storm. At Tippery Spring, for a short time the majority of emerging water was storm water, which may indicate a reversal in water exchange between the conduits and the surrounding matrix, an important consideration in karst contaminant transport. Two natural tracers were applied in new ways for this study: Ca/Zr ratios and REE patterns. Both tracers provided additional information about flow paths and recharge sources as they varied during the storm hydrograph. Ca/Zr ratios changed in timing and intensity with storm intensity, and both springs exhibited a decline in Ca/Zr ratios as calcium-rich carbonate matrix water was displaced by zirconium-rich storm recharge water from sinking streams off the clastic upland ridges. Being a storm water arrival indicator in clastic-ridge-fed Valley and Ridge springs, this relationship made Ca/Zr ratios a useful substitute for stable water isotopes while also providing information on source area. In response to storm water recharge, REE concentrations increased with the arrival of storm water. The timing and magnitude of concentration increases were influenced both by the degree of surface connectivity intrinsic to each spring and the intensity of the recharge event. Elevated REE concentrations persisted after other parameters recovered to pre-storm levels, suggesting water which has interacted with either the local carbonate matrix or the upland siliciclastics. These slower flow paths recharging the two springs were not apparent from other geochemical parameters. This study illustrated the relationships among multiple tracers to understand source waters in different periods of storm hydrographs. A flow and transport model using the Finite Element Subsurface Flow Model (FEFLOW) was calibrated using quantitative dye trace and high resolution temperature data to simulate the connection between a sinking stream and Tippery Spring. Dye was injected at the sink and monitored at the spring while temperature data was collected using loggers at both the sink and the spring. FEFLOW was used to simulate the connection between sink and spring through varying conduit geometries, sink and spring discharges, conduit conductivity, conduit cross-sectional area, matrix transmissivity, matrix porosity, and dispersivity. Single conduit models reproduced larger peak and recession concentrations than observed. A forked conduit model diverted flow from the main conduit, reducing the concentration of dye reaching the spring, provided a better match. Latin Hypercube sensitivity analysis indicated that dye concentration breakthrough curves were most sensitive to conduit conductivity and less sensitive to other model parameters. Temperature data from high-resolution loggers at the sink and spring were then incorporated into the model scenarios to reproduce seasonal spring temperature using the conduit configuration fit to the dye trace. Simulated temperature signals at the spring were sensitive to parameters in addition to conduit conductivity, most notably matrix transmissivity and inflow rates at the sink. The dual approach to karst model calibration using a temperature model set up from an initial dye trace results in greater model confidence due to a limited possible range in conduit conductivity. This study improved conceptual and numerical models for karst by examining how data from storm events and tracers can be used to better understand recharge and flow paths.
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