HR: 13:55h
AN: H12G-02    [PDF]
TI: Addressing Uncertainty in Predictive Groundwater Modeling in the Context of a Major Regulatory Permitting Process
AU: * Carlson, C P
EM: christopher.carlson@dnr.state.wi.us
AF: Wisconsin Department of Natural Resources, Bureau of Waste Management P.O. Box 7921, Madison, WI 53719
AU: Feinstein, D T
EM: dtfeinst@usgs.gov
AF: U.S. Geological Survey, Water Resources Division 8505 Research Way, Middleton, WI 53562
AU: Hunt, R J
EM: rjhunt@usgs.gov
AF: U.S. Geological Survey, Water Resources Division 8505 Research Way, Middleton, WI 53562
AU: Gotkowitz, M B
EM: mbgotkow@facstaff.wisc.edu
AF: Wisconsin Geological and Natural History Survey, 3817 Mineral Point Road, Madison, WI 53705
AU: Kenoyer, G J
EM: Galen.Kenoyer@rmtinc.com
AF: RMT, Inc., P.O. Box 8923, Madison, WI 53708
AB: Regulatory assessments of the environmental impacts from proposed natural-resource development often require detailed information regarding potential project effects on water resources. Understanding these impacts is important for both disclosure to the public and determination of regulatory compliance in permitting. Many such projects involve pumping substantial quantities of groundwater to access the desired resource; in some cases, nearby surface water resources may be adversely affected by this groundwater withdrawal. In addition, some projects involve the management of waste materials that have the potential to contaminate area groundwater and surface waters. Because the regulatory assessment needs to address potential future conditions, predictive groundwater modeling has been used to help provide the necessary information. A case study of a proposed mine in northern Wisconsin is the focus of this discussion. In this project, both the applicant and the state regulatory agency review team recognized that substantial uncertainty would remain in model output even after conducting detailed analyses of sizeable project data sets to develop reasonable model inputs and completion of a rigorous calibration and an extensive sensitivity analysis. As a consequence, the modeling work and associated impact assessments submitted by the applicant addressed uncertainty by incorporating two scenarios: an expected case and a worst case. The agency review team, however, concluded that the level of uncertainty was so great in this situation, and the results of such importance to the impact assessment and permitting processes, that a more extensive approach to addressing uncertainty was necessary to ensure a technically defensible product. In response, the state's review team completed a number of detailed analyses of the project area information and the applicant's 3D MODFLOW regional flow model. These included: development of a 2D analytic-element model (GFLOW) to evaluate the submitted MODFLOW model boundary conditions and recharge rates; completion of Monte Carlo analyses to assess lake outlet flow and lakebed hydraulic conductivity; calculation of GFLOW-UCODE confidence intervals for prediction of mine pumping rates and associated reductions in stream baseflow; and the development of detailed analyses of project-site historical pump tests using both the regional and inset models. Numerous sensitivity analyses were performed after completing updates to the submitted model, allowing the review team to identify and evaluate the most sensitive parameters. This work on model uncertainty provided the review team's "reasonable" range for model inputs, which in turn provided two end-member scenarios that established high and low estimates of the reasonable range of project effects on the groundwater system for use in the regulatory process. The concept of reasonable ranges of model inputs and outputs was also subsequently used in the review team's work on the solute transport models submitted by the applicant to assess groundwater chemistry impacts from the proposed mine and waste facilities. This approach provides a means for communicating uncertainty to both the public and regulatory decision-makers. Moreover, it underscores the uncertainty inherent in simplified numerical representations of complex, real-world systems.
DE: 1800 HYDROLOGY
DE: 1803 Anthropogenic effects
DE: 1829 Groundwater hydrology
DE: 1831 Groundwater quality
DE: 1832 Groundwater transport
SC: Hydrology [H]
MN: 2003 Fall Meeting