Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation

Khorshidi, MS; Izady, A; Al-Maktoumi, A; Chen, M; Nikoo, MR; Gandomi, AH

Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation

Khorshidi, MS Izady, A Al-Maktoumi, A Chen, M Nikoo, MR Gandomi, AH

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Publisher:: SPRINGER
Publication Type:: Journal Article
Citation:: Environmental Earth Sciences, 2023, 82, (23)
Issue Date:: 2023-12-01

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Field	Value	Language
dc.contributor.author	Khorshidi, MS
dc.contributor.author	Izady, A
dc.contributor.author	Al-Maktoumi, A
dc.contributor.author	Chen, M
dc.contributor.author	Nikoo, MR
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2024-04-29T01:54:49Z
dc.date.available	2024-04-29T01:54:49Z
dc.date.issued	2023-12-01
dc.identifier.citation	Environmental Earth Sciences, 2023, 82, (23)
dc.identifier.issn	1866-6280
dc.identifier.issn	1866-6299
dc.identifier.uri	http://hdl.handle.net/10453/178439
dc.description.abstract	This paper presents a novel approach to analyzing uncertainty in complex groundwater models based on the approximate Bayesian computation (ABC) framework and information-theoretic summary statistics. Two summary statistics using the concepts of mutual information and variation of information are formulated as distance function measures of the ABC. These signatures are utilized within an ABC rejection (ABC-REJ) algorithm to measure the similarity and dissimilarity of the generated samples to the true posterior distribution of the groundwater model parameters. This method was applied to groundwater model calibration and uncertainty analysis in an arid region of Oman with a complex hydrogeological setting and a hardrock-alluvial aquifer system. MODFLOW unstructured-grid was used for modelling groundwater dynamics. A three-dimensional stratigraphic model was developed based on borehole data, and five-layer grid cells were defined according to the material and elevations of the stratigraphic model. Results show that the model reproduces the observed data behaviour very well, including peaks and abrupt declines in the head, as well as the trend of fluctuations in the observation wells. A notable match between the observed and simulated heads indicates the accuracy of the ABC-REJ algorithm based on summary statistics for calibrating and analyzing groundwater models.
dc.language	English
dc.publisher	SPRINGER
dc.relation.ispartof	Environmental Earth Sciences
dc.relation.isbasedon	10.1007/s12665-023-11264-9
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0403 Geology, 0406 Physical Geography and Environmental Geoscience, 0905 Civil Engineering
dc.subject.classification	3705 Geology
dc.subject.classification	3709 Physical geography and environmental geoscience
dc.title	Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation
dc.type	Journal Article
utslib.citation.volume	82
utslib.for	0403 Geology
utslib.for	0406 Physical Geography and Environmental Geoscience
utslib.for	0905 Civil Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	in_progress	*
dc.date.updated	2024-04-29T01:54:47Z
pubs.issue	23
pubs.publication-status	Published
pubs.volume	82
utslib.citation.issue	23

Abstract:

This paper presents a novel approach to analyzing uncertainty in complex groundwater models based on the approximate Bayesian computation (ABC) framework and information-theoretic summary statistics. Two summary statistics using the concepts of mutual information and variation of information are formulated as distance function measures of the ABC. These signatures are utilized within an ABC rejection (ABC-REJ) algorithm to measure the similarity and dissimilarity of the generated samples to the true posterior distribution of the groundwater model parameters. This method was applied to groundwater model calibration and uncertainty analysis in an arid region of Oman with a complex hydrogeological setting and a hardrock-alluvial aquifer system. MODFLOW unstructured-grid was used for modelling groundwater dynamics. A three-dimensional stratigraphic model was developed based on borehole data, and five-layer grid cells were defined according to the material and elevations of the stratigraphic model. Results show that the model reproduces the observed data behaviour very well, including peaks and abrupt declines in the head, as well as the trend of fluctuations in the observation wells. A notable match between the observed and simulated heads indicates the accuracy of the ABC-REJ algorithm based on summary statistics for calibrating and analyzing groundwater models.

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http://hdl.handle.net/10453/178439