Metamodels to Bridge the Gap Between Modeling and Decision Support

Authors

Michael N. Fienen, U.S. Geological Survey, Wisconsin Water Science Center, Middleton, WIFollow
Bernard T. Nolan, USGS National Water Quality Assessment Program, Reston, VAFollow
Daniel T. Feinstein, USGS WIWSC, Milwaukee, WIFollow
J. Jeffrey Starn, USGS NAWQA Program, East Hartford, CTFollow

Date of this Version

2015

Citation

Vol. 53, No. 4–Groundwater–July-August 2015

Abstract

Insights from process-based models are a mainstay of many groundwater investigations; however, long runtimes often preclude their use in the decision-making process. Screening-level predictions are often needed in areas lacking time or funding for rigorous process-based modeling. The U.S. Geological Survey (USGS) Groundwater Resources and National Water Quality Assessment Programs are addressing these issues by evaluating the “metamodel” to bridge these gaps. A metamodel is a statistical model founded on a computationally expensive model. Although faster, the question remains: Can a statistical model provide similar insights to a numerical model with faster results?