Quantifying stratigraphic uncertainty in groundwater modelling for infrastructure design

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2 Citations (Scopus)

Abstract

A methodology to quantify the stratigraphic uncertainty of the aquifer bottom is used in assessing the impact of sheet piles on the water table in the vicinity of a motorway. The method includes uncertainties on model parameters and depth of sheet piles. While parameter uncertainty dominates when simulating the existing groundwater conditions, the stratigraphic uncertainty dominates when predicting the impacts of the motorway sheet piles. The uncertainty of groundwater head predictions is a key element in risk assessments for infrastructure projects, where groundwater affects construction costs. While geological structural uncertainty often is a dominating source of uncertainty in large-scale water-resource studies, stratigraphic uncertainty (defined as the uncertainty of the location of geological boundaries between units/facies) becomes more important for small-scale infrastructure projects. The methodologies used so far for handling stratigraphic uncertainty typically use a somewhat simplistic approach basing the uncertainties of the geological surfaces on the kriging variance. The proposed methodology has two novel elements. Firstly, the uncertainties in the geological interpretation of the borehole data are explicitly included. Secondly, conditional sequential Gaussian simulation (sGs) is used to quantify the uncertainties. The advantage of sGs over standard kriging-based approaches is that sGs allows descriptions of small-scale variations that are crucial in some contexts. The methodology was tested on a case site in Denmark where a new motorway has been constructed below the water table and with sheet-pile walls designed to penetrate the aquifer down to 1 m above the aquifer bottom.

Original languageEnglish
Pages (from-to)1075-1089
Number of pages15
JournalHydrogeology Journal
Volume29
Issue number3
DOIs
Publication statusPublished - May 2021

Keywords

  • Geostatistics
  • Numerical modelling
  • Sequential Gaussian simulation
  • Sheet piling
  • Stratigraphic uncertainty

Programme Area

  • Programme Area 2: Water Resources

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