Emulator-based Bayesian calibration of a subglacial drainage model Article Swipe

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Tim Hill , Gwenn E. Flowers , Derek Bingham , Matthew J. Hoffman ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.31223/x5gq68

Subglacial drainage models, often motivated by the relationship between hydrology and ice flow, sensitively depend on numerous unconstrained parameters. We explore using borehole water-pressure timeseries to calibrate the uncertain parameters of a popular subglacial drainage model, taking a Bayesian perspective to quantify the uncertainty in parameter estimates and in the calibrated model predictions. To reduce the computation time associated with Markov Chain Monte Carlo sampling, we construct a fast Gaussian process emulator to stand in for the subglacial drainage model. We first carry out a calibration experiment using synthetic observations consisting of model simulations with hidden parameter values as a demonstration of the method. Using real borehole water pressures measured in western Greenland, we find meaningful constraints on four of the eight model parameters and a factor-of-three reduction in uncertainty of the calibrated model predictions. These experiments illustrate Gaussian process-based Bayesian inference as a useful tool for calibration and uncertainty quantification of complex glaciological models using field data. However, significant differences between the calibrated model and the borehole data suggest that structural limitations of the model, rather than poorly constrained parameters or computational cost, remain the most important constraint on subglacial drainage modelling.

Related Topics

Calibration

Drainage

Computer Science

Environmental Science

Artificial Intelligence

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Calibration Bayesian probability Drainage Computer science Bayesian inference Geology Environmental science Artificial intelligence Statistics Mathematics Ecology Biology

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Type: preprint
Language: en
Landing Page: https://doi.org/10.31223/x5gq68
OA Status: gold
Cited By: 1
Related Works: 10
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DOI: https://doi.org/10.31223/x5gq68

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Title: Emulator-based Bayesian calibration of a subglacial drainage model

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Language: en

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Publication year: 2024

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Publication date: 2024-12-25

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Authors: Tim Hill, Gwenn E. Flowers, Derek Bingham, Matthew J. Hoffman

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Landing page: https://doi.org/10.31223/x5gq68

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Concepts: Calibration, Bayesian probability, Drainage, Computer science, Bayesian inference, Geology, Environmental science, Artificial intelligence, Statistics, Mathematics, Ecology, Biology

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Cited by: 1

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