Author: Tomas Opazo Gonzalez
Opazo Gonzalez, Tomas, 2025 The Prior and the Likelihood: Accommodating Uncertain Priors and Model Defects in Groundwater Modelling for Decision Support, Flinders University, College of Science and Engineering
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Quantifying uncertainty in groundwater models is essential for reliable predictions and effective decision-making. This research addresses the risks posed by misspecified prior uncertainties and structural model errors, which can lead to biased predictions and underestimated uncertainty. It develops novel methodologies to: (1) update prior uncertainties via empirical Bayesian inference, (2) represent nonstationary priors through hierarchical parameterization, and (3) incorporate structural errors into history matching and prediction. These methods are tested on synthetic models and shown to reduce predictive bias and yield more conservative uncertainty estimates. Results demonstrate improved robustness and reliability in model-based decision support, advancing uncertainty quantification in groundwater modelling.
Keywords: Groundwater modelling, uncertainty quantification, history matching, nonstationary priors, model error
Subject: Earth Sciences thesis
Thesis type: Doctor of Philosophy
Completed: 2025
School: College of Science and Engineering
Supervisor: Ilka Wallis