MONITORING TRANSIENT CHANGES IN HIGH-RESOLUTION VERTICAL GRADIENTS TO IMPROVE HYDROSTRATIGRAPHIC UNITS FOR GLACIOGENIC SEDIMENTS AT A CONTAMINATED SITE

Depth discrete and detailed profiles of hydraulic head (i.e., high resolution head profiles) provide insight into changes in vertical hydraulic conductivity (Kv) often associated with distinct hydrostratigraphic units. Subtle changes in Kv can be difficult to resolve in parts of the flow system where vertical gradients are typically small. The objective of this study is to monitor high-resolution head profiles frequently through time during recharge events and changes in pumping conditions to determine if transient increases in vertical gradients resolve changes in Kv that are not obvious in the steady state head profiles. To accomplish this objective, open tube Waterloo multilevel systems (MLS) were instrumented with fiber optic pressure sensors. These MLSs include either 14 or 15 ports monitoring a 20 m thick package of Quaternary glaciogenic sediments at a contaminated groundwater site in south central Wisconsin. The fiber optic pressure sensors were specifically designed to fit into the small diameter (0.635 cm) tubes of the MLSs. Pressures were monitored once every 10 seconds for several months capturing the response to recharge events, barometric pressure fluctuations, and changes in pumping rates associated with a nearby groundwater remediation system. Results are preliminary but do show transient changes in vertical gradients that may reflect subtle contrasts in Kv with depth that were not resolvable in static head profiles collected during steady state conditions. These data will be further processed to assess the repeatability of vertical gradients resolved during these transient events and to determine what geologic features are associated with the changes in Kv. Ultimately, the data will be used to refine the hydrostratigraphic framework for the Quaternary sediments at the site. This hydraulically-calibrated framework will greatly improve the numerical models’ ability to predict long term plume behavior and assess future remediation strategies.