GSA Connects 2021 in Portland, Oregon

Paper No. 134-14
Presentation Time: 11:30 AM

DEVELOPMENT OF PRELIMINARY REMEDIATION GOALS PROTECTIVE OF GROUNDWATER BASED ON AN EFFICIENT FATE AND TRANSPORT MODELING APPROACH


NELL, Ryan1, MEHTA, Sunil2 and PETERSEN, Dennis1, (1)INTERA Incorporated, Richland, WA 99354, (2)INTERA Incorporated, 3240 Richardson Rd, Suite 2, Richland, WA 99354

Preliminary remediation goals (PRGs) protective of groundwater represent the maximum quantity of a contaminant that can remain in the soil without causing an exceedance of applicable drinking water standards when reaching the groundwater. PRGs can be calculated by use of fate and transport modeling with site-specific data. Computationally efficient, one-dimensional contaminant fate and transport simulations were developed to represent 17 generalized geologic columns below the waste sites of interest. Flow-fields in the vadose zone were developed for each of the one-dimensional vadose zone column components by abstracting results from complex three-dimensional vadose zone flow and transport models developed using STOMP code. Similarly, localized steady state groundwater gradient and saturated hydraulic conductivity values were assigned to each saturated zone component by extracting predictive flow results from a complex three-dimensional MODFLOW-based model. A total of 23 chemicals and seven radionuclides, with their respective decay chains, were included in the contaminant transport simulations to evaluate peak groundwater concentrations within the compliance period of 1,000 years. One-dimensional simulations were implemented using the GoldSim software in a single model file for all representative columns. Select benchmarking comparisons were conducted between the one-dimensional representations and corresponding three-dimensional model simulations to provide confidence in abstraction process. PRG values were calculated based on the maximum of the simulated peak concentrations across all generalized geologic columns within an area of interest. This approach provides a computationally efficient framework for utilizing available information from complex process-level models for performing contaminant transport modeling to support regulatory decision-making process.