Paper No. 5
Presentation Time: 9:00 AM-6:00 PM


COVINGTON, Matthew D., Department of Geosciences, University of Arkansas, 216 Ozark Hall, Fayetteville, AR 72701 and GULLEY, Jason, University of Texas Institute for Geophysics, Austin, TX 78751,

Temporal variability in solute-discharge relationships in rivers and springs in karst aquifers is often analyzed to obtain information about the behavior of karst systems because such relationships should vary as a function of aquifer structure, recharge mode, and climatic factors. Previous work has suggested that discharge hydrographs from eogenetic and telogenetic karst springs display different characteristic behaviors, with eogenetic springs producing more muted and broad responses, and telogenetic springs producing sharper, more peaked responses. These different hydrograph responses reflect key differences in residence time of recharge in aquifers. Because solute-discharge relationships also depend upon residence time of recharge in aquifers, eogenetic and telogenetic systems should also have characteristic differences in solute discharge-relationships. To quantify these differences, we use statistical analysis of temperature, conductivity, total hardness, and SI variations at a variety of springs and rivers in eogenetic and telogenetic karst aquifer systems. Additionally, we characterize relationships between SICAL and discharge found in each setting and discuss potential implications of these relationships for incision processes in the two settings. Data collected by collaborators in this project is supplemented by legacy data available through the USGS National Water Information System. As a part of this project, we have developed a tool kit, written in Python, that allows rapid analysis of large data sets of solute-discharge relationships in springs and rivers. This toolkit includes modules for automated downloading of data from the National Water Information System (NWIS) Water-Quality Web Services, speciation calculations using PHREEQC, and further functionality for statistical analysis of the data. This toolkit will be made available online.
  • Covington_GSA_poster_2012.pdf (1.7 MB)