A Bayesian assessment of an approximate model for unconfined water flow in sloping layered porous media
Chiachío, Juan and Chiachío, Manuel and Sankararaman, Shankar and Prescott, Darren (2018) A Bayesian assessment of an approximate model for unconfined water flow in sloping layered porous media. Transport in Porous Media. ISSN 0169-3913 (https://doi.org/10.1007/s11242-018-1094-2)
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Abstract
The prediction of water table height in unconfined layered porous media is a difficult modelling problem that typically requires numerical simulation. This paper proposes an analytical model to approximate the exact solution based on a steady-state Dupuit–Forchheimer analysis. The key contribution in relation to a similar model in the literature relies in the ability of the proposed model to consider more than two layers with different thicknesses and slopes, so that the existing model becomes a special case of the proposed model herein. In addition, a model assessment methodology based on the Bayesian inverse problem is proposed to efficiently identify the values of the physical parameters for which the proposed model is accurate when compared against a reference model given by MODFLOW-NWT, the open-source finite-difference code by the U.S. Geological Survey. Based on numerical results for a representative case study, the ratio of vertical recharge rate to hydraulic conductivity emerges as a key parameter in terms of model accuracy so that, when appropriately bounded, both the proposed model and MODFLOW-NWT provide almost identical results.
ORCID iDs
Chiachío, Juan ORCID: https://orcid.org/0000-0003-1243-8694, Chiachío, Manuel, Sankararaman, Shankar and Prescott, Darren;-
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Item type: Article ID code: 65361 Dates: DateEvent9 June 2018Published9 June 2018Published Online24 May 2018AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) Department: Faculty of Engineering > Naval Architecture, Ocean & Marine Engineering Depositing user: Pure Administrator Date deposited: 05 Sep 2018 10:47 Last modified: 11 Nov 2024 12:05 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/65361