CALL FOR PROPOSALS:

ORGANIZERS

  • Harvey Thorleifson, Chair
    Minnesota Geological Survey
  • Carrie Jennings, Vice Chair
    Minnesota Geological Survey
  • David Bush, Technical Program Chair
    University of West Georgia
  • Jim Miller, Field Trip Chair
    University of Minnesota Duluth
  • Curtis M. Hudak, Sponsorship Chair
    Foth Infrastructure & Environment, LLC

 

Paper No. 13
Presentation Time: 9:00 AM-6:00 PM

CONNECTING STOCHASTIC AND DETERMINISTIC HYDROSTRATIGRAPHIC MODELS OF THE QUATERNARY FORT WAYNE MORAINE GLACIAL AQUIFER SYSTEM, ANN ARBOR, MICHIGAN, USA


PAPPAS, Lena K., Dept. of Geology, Wayne State University, 0224 Old Main, 4841 Cass, Detroit, MI 48202 and LEMKE, L.D., Geology, Wayne State University, Detroit, MI 48202, lkpappas@wayne.edu

The complex distribution of aquifers and aquitards in glacial sediments presents numerous challenges for groundwater flow and contaminant transport modeling. Conceptualization of heterogeneities in glacial sediments may employ a combination of deterministic and stochastic methodologies. Deterministic methods, such as hydrostratigraphic correlation of aquifers and aquitards, can be linked to the Quaternary history of an area with useful insights derived from the distribution and orientation of Quaternary geologic features. Stochastic methods employing geostatistics can then be used to estimate physical hydrogeologic parameters at a scale below the resolution of coarser deterministic hydrostratigraphic models. This study illustrates one such hybrid approach for a groundwater contamination site located on the Fort Wayne Moraine in central Washtenaw County, Michigan, USA, where more than 170 monitoring wells have been installed as part of an ongoing remediation effort.

Natural gamma radiation logs for 77 of the wells were digitized and used to interpret the locations of aquifer and aquitard subunits within each well. Gamma radiation measurements in counts per minute established a basis for stochastic modeling. Count data collected through the underlying shale bedrock were removed from the data set. 3D vertical and horizontal omnidirectional variograms were then constructed using raw gamma counts as a function of well location and depth. Vertical variograms incorporated small lag distances (30 cm or 1 ft) to account for high data density in the vertical direction. In the horizontal dimension, lag distances ranging from 6 to 300 m (20 to 1,000 feet) were examined to determine the short and long-scale correlation structure. A number of different approaches were used to explore variogram structure. The raw data were normalized to account for variation introduced by different logging and drilling equipment. Normalized gamma values were further transformed to indicator values based on pentile thresholds and deterministic classifications. Vertical variograms displayed clear structure, while horizontal variograms displayed almost pure nugget effect. Consequently, subsequent groundwater models constructed in this site will need to rely upon both the deterministic and stochastic methods employed.

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