Improving Applied Groundwater Model Prediction Through Parameter Estimation and Uncertainty Analysis

Monday, April 12, 2010: 11:05 a.m.-12:25 p.m.
Tabor Auditorium (Westin Tabor Center, Denver)
Prediction is the ultimate goal of applied groundwater modeling, and prediction uncertainty is vital to managers. Use of parameter estimation and uncertainty analysis to estimate prediction uncertainty has garnered significant attention in research, large-scale government projects, and the academic realm. This session focuses on integrating parameter estimation and uncertainty analysis into groundwater modeling. We present abstracts from academia, consulting, research institutes, governmental agencies, and anyone actively applying parameter estimation and uncertainty analysis to improve groundwater model predictions.
Moderators:
Eileen P. Poeter , Jason R. House and Mary C. Hill
11:05 a.m.
Improved Groundwater Modeling Using An Open and Free Environment Called Mflab
Theo N. Olsthoorn, Delft University of Technology
12:05 p.m.
Can Parameter Estimation Be Improved by Optimizing Data Use and Analysis?
Otto Strack Sr., Ph., D., University of MInnesota; Randal J. Barnes, Ph.D., University of MInnesota; Bonnie Ausk, University of MInnesota
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