A Bayesian assessment of an approximate model for unconfined water flow in sloping layered porous media

Juan Chiachío, Manuel Chiachío, Shankar Sankararaman, Darren Prescott

Research output: Contribution to journalArticle

1 Citation (Scopus)
13 Downloads (Pure)

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.
Original languageEnglish
Number of pages21
JournalTransport in Porous Media
Early online date9 Jun 2018
DOIs
Publication statusE-pub ahead of print - 9 Jun 2018

Keywords

  • Dupuit–Forchheimer analysis
  • layered porous media
  • Bayesian hypothesis testing
  • railway track drainage

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