2016 NGWA Groundwater Summit

Decision Making Under Uncertainty: A New Approach to Decision Making in a Multi-Model Environment

Monday, April 25, 2016: 2:40 p.m.
Platte River Room (The Westin Denver Downtown)
Timothy Bayley , Montgomery and Associates, Tucson, AZ
Colin Kikuchi, Ph.D. , Montgomery and Associates, Tucson, AZ
Ty P.A. Ferré, Ph.D. , Hydrology and Water Resources, University of Arizona, Tucson, AZ

A primary role of hydrogeologic models is to support decision making.  However, the uncertainty inherent in these models complicates their use as decision making tools.  Increasingly, multimodel methods are used to develop more robust predictions of future system states and include measures of model associated prediction uncertainties.  Given a set of predictions from a multi-model analysis, one must undertake the process of choosing a prediction to guide decision making.  Outputs from a multi-model analysis are often reduced to single models (e.g., maximum likelihood, worst case), or averaging approaches (e.g., Bayesian model averaging, likelihood weighting) when used to make hydrologic decisions.  With the exception of the worst case method, these approaches consider the range of model predictions, but they do not consider the implications of different predictions for decision making; a consideration that is accepted as standard in formal quantitative risk analysis.  This talk presents an approach that considers the outcomes of decisions based on multi-model hydrologic predictions and demonstrates that it can lead to improved decision making and engineering design under uncertainty.   Examples will be presented from synthetic case studies that illustrate the validity of the method and from real world groundwater flow and transport studies that demonstrate the practical application of the method.

Timothy Bayley, Montgomery and Associates, Tucson, AZ
Tim Bayley is a hydrologic consultant at E.L. Montgomery and Associates and a PhD student in the Department of Hydrology and Water Resources at the University of Arizona. He has worked on a wide range of projects from estimating the decline of municipal water demand to Monte-Carlo modeling of complex subsurface groundwater flow and transport systems. His primary research interest is using multi-model methods to drive data collection and decision making under uncertainty.

Colin Kikuchi, Ph.D., Montgomery and Associates, Tucson, AZ
Colin Kikuchi is a hydrologist with Errol Montgomery & Associates in Tucson, Arizona. He completed his bachelor’s degree in Environmental Studies at Middlebury College, and his masters and doctoral work in Hydrology and Water Resources at the University of Arizona. Colin has worked in various aspects of groundwater characterization studies ranging from instrumentation and sampling to aquifer hydraulic testing analyses and groundwater flow modeling. The topic of his presentation is closely related to his doctoral research with Dr. T.P.A. Ferré, and focuses on cost effective and objective-oriented groundwater data collection through targeted groundwater sampling and monitoring network designs.

Ty P.A. Ferré, Ph.D., Hydrology and Water Resources, University of Arizona, Tucson, AZ
Ty Ferré is an Associate Professor in the Department of Hydrology and Water Resources at the University of Arizona. His research focuses on the optimization of hydrologic monitoring networks. He and his students have studied the development and use of both direct and indirect measurement methods for hydrologic monitoring and characterization including. They have also studied the use of advanced forward and inverse modeling techniques to predict the value of information of proposed monitoring networks to reduce hydrologic prediction uncertainty. Finally, they have studied the influence of the spatial distribution of measurement sensitivity on the effective recovery of hydrologic information.