Bayesian inferences on groundwater flow modelling within the Great Artesian Basin
<div>Understanding groundwater flow dynamics within the Great Artesian Basin (GAB) is critical for responsible management of groundwater from an environmental, economic and cultural perspective. Numerical groundwater flow modelling involves generating a simplified representation of a groundwater system and using Darcy’s Law to simulate groundwater flow rates and the distribution of hydraulic heads throughout the system. This is a pilot study aimed at developing a workflow for groundwater flow modelling of the Great Artesian Basin using Bayesian methods. In this report, we present our initial results from building and running a steady-state groundwater flow model of the entire GAB. We demonstrate a Bayesian inference framework to generate an ensemble of groundwater flow models allowing an assessment of the uncertainty of model parameters and flow velocities. </div><div>Several models have been built to simulate groundwater flow across various areas and layers of the GAB. Most of these models aimed to predict the likely impacts on the groundwater system of some future scenario, generally climate change or groundwater extraction relating to mining activities. While these models are well-suited to their purpose, their focus on particular regions or aquifers makes them unsuitable for investigating large-scale groundwater flow throughout the GAB. In contrast, the model built as part of this study captures the entire GAB and aims to simulate large-scale flow. Although not in scope for this pilot study, the questions a model at this scale is capable of addressing include characterising 3D flow within hydrogeological layers, computing groundwater flux between aquifers and between sub-basins, inferring hydraulic properties and identifying poor quality data. As this model is steady-state and uses hydraulic head data from before the year 2000, it provides a baseline estimate of groundwater flow without considering recent anthropogenic forcing or transient system stresses. </div><div>The GAB is represented as a 14 hydrogeological layer model including basement, Permo-Carboniferous basins, Mesozoic sedimentary aquifers and aquitards and Cenozoic layers. This includes updated hydrogeological surfaces from the GAB project. The input data consisted of 8,065 hydraulic head measurements and 6,151 estimates of recharge rate while the model parameters were a single hydraulic conductivity value for each of the 14 layers. The modelling domain was discretised using 10 x 10 km cells in the horizontal plane and the mesh was deformed vertically to fit between the topography and the basement surface, with the resulting mesh having a vertical discretisation of no coarser than 50 metres. The top boundary condition was a constant head boundary that was a smoothed version of topography. The sides and bottom of the model have no flux boundary conditions and a buffer zone around the GAB was included to minimise boundary effects. </div><div>In total 2500 groundwater flow simulations were run using a Bayesian inversion framework. The inversion sampled various combinations of input parameters to find models with a relatively low misfit, which was calculated by squaring the difference between the observed and simulated values of hydraulic head and recharge. Rather than searching for a global minima, the Metropolis Hastings Markov Chain Monte Carlo sampling algorithm was used to explore a range of possible models and estimate the posterior distribution of each layer’s hydraulic conductivity. </div><div>The model performed adequately and the model parameters were generally consistent with the prior probability distributions based on previous modelling studies. However, the posterior distribution of model parameters were very broad indicating the model was not particularly informative in its current form. </div><div>Groundwater flow velocity vectors from the maximum likelihood model were used to investigate groundwater trends within the Cadna-owie-Hooray aquifer. Uncertainty of model predictions were investigated by calculating the groundwater flow velocity variance across the ensemble. This study demonstrates that it is technically feasible to use Bayesian inference to probabilistically mode groundwater flow across the entire GAB. However, for this approach to yield useful results, more work is required to understand the impacts of simplifying assumptions about layer properties, the quality of the input data and model structure on the resulting flow model. </div><div><br></div>
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Identification info
- Date (Creation)
- 2022-07-21T22:00:00
- Date (Publication)
- 2022-10-28T02:11:14
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/147027
- Citation identifier
- Digital Object Identifier/http://dx.doi.org/10.11636/Record.2022.030
- Cited responsible party
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Role Organisation / Individual Name Details Publisher Commonwealth of Australia (Geoscience Australia)
Voice Author Knight, B.
External Contact Author Mather, B.
External Contact Author Moresi, L.
External Contact Author Symington, N.
Internal Contact Author Rollet, N.
Internal Contact Author Vizy, J.
External Contact Author Ransley, T.
Internal Contact Author Wallace, L.
Internal Contact Author Sundaram, B.
Internal Contact
- Name
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GA Record
- Issue identification
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GA Record 2022/30
- Purpose
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This is a pilot study aimed at developing a workflow for groundwater flow modelling of the Great Artesian Basin using Bayesian methods. The purpose of this report is to present our initial results from building and running a steady-state groundwater flow model of the entire GAB.
- Status
- Completed
- Point of contact
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Role Organisation / Individual Name Details Resource provider Minerals, Energy and Groundwater Division
External Contact Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Rollet, N.
MEG Internal Contact
- Spatial representation type
- Topic category
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- Geoscientific information
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))
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- As needed
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Product data repository: Various Formats
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Data Store directory containing the digital product files
Data Store directory containing one or more files, possibly in a variety of formats, accessible to Geoscience Australia staff only for internal purposes
- Project
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Great Artesian Basin water balance
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- Keywords
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groundwater
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numerical modelling
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- Keywords
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bayesian
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- theme.ANZRC Fields of Research.rdf
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Groundwater hydrology
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- Keywords
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Published_External
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Resource constraints
- Title
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Creative Commons Attribution 4.0 International Licence
- Alternate title
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CC-BY
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4.0
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© Commonwealth of Australia (Geoscience Australia) 2022
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Australian Government Security Classification System
- Edition date
- 2018-11-01T00:00:00
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- Unclassified
- Classification system
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Australian Government Security Classification System
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- English
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- UTF8
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Role Organisation / Individual Name Details Distributor Commonwealth of Australia (Geoscience Australia)
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Download the Record (pdf) [15.5 MB]
Download the Record (pdf) [15.5 MB]
- Distribution format
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pdf
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Resource lineage
- Statement
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<div>This record was written based on work undertaken during the 2021-2022 financial year and was part of the Great Artesian Basin groundwater project 2019-2022. The record was reviewed and approved July 2022.</div>
Metadata constraints
- Title
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Australian Government Security Classification System
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
Metadata
- Metadata identifier
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urn:uuid/5173b53a-5897-4915-a395-cab24716d44b
- Title
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GeoNetwork UUID
- Language
- English
- Character encoding
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- Contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Rollet, N.
MEG Internal Contact
Type of resource
- Resource scope
- Document
- Name
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GA Record
Alternative metadata reference
- Title
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Geoscience Australia - short identifier for metadata record with
uuid
- Citation identifier
- eCatId/147027
- Date info (Creation)
- 2022-10-28T01:58:24
- Date info (Revision)
- 2022-10-28T01:58:24
Metadata standard
- Title
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AU/NZS ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-3
- Title
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
- Edition
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Version 2.0, September 2018
- Citation identifier
- https://pid.geoscience.gov.au/dataset/ga/122551