2009 Portland GSA Annual Meeting (18-21 October 2009)

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

PREDICTING LONG-TERM CONTAMINANT FLUXES IN THE UNSATURATED ZONE TO EVALUATE THE EFFECTIVENESS OF SOIL DESICCATION


FREEDMAN, Vicky, Energy & Environment, Battelle Pacific Northwest Division, PO Box 999, MSIN K9-36, Richland, WA 99352, WARD, Andy, Pacific Northwest National Laboratory, PO Box 999, MSIN K9-36, Richland, WA 99352 and TRUEX, Mike J., Pacific Northwest National Laboratory, P.O. Box 999 MS K6-96, Richland, WA 99352, vicky.freedman@pnnl.gov

Estimates of contaminant fluxes from deep vadose zone sources are important to assess the long-term sustainability and viability of soil desiccation. Soil desiccation is a promising technology under consideration at the Hanford Site to protect groundwater from recalcitrant contaminants residing in the deep vadose zone. In this technology, groundwater risk mitigation is derived from reduction of vadose zone sediment pore water associated with the contamination, which is the driving force for contaminant transport to the groundwater table. Soil desiccation is not expected to remove contamination, but leave it relatively immobilized in the vadose zone. It is therefore necessary to rely on numerical simulations to predict to what extent contaminant transport is slowed and its eventual impact on contaminant fluxes to the groundwater. To evaluate the effectiveness of this technology at a potential site, moisture content and grain-size analyses were characterized at the cm-scale using in-situ measurements, and statistical correlation was used to estimate the hydraulic properties. Simulations were then performed at cm spatial resolution to identify the extent of desiccation necessary to achieve the desired contaminant flux reduction to groundwater. Given that high-resolution simulations are computationally expensive, upscaling of hydraulic properties was performed to assess model predictions of contaminant fluxes to groundwater when characterizing heterogeneities at different spatial scales.