Bayesian data fusion for watertable interpolation: incorporating a hydrogeological conceptual model in kriging
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Date
2010
Authors
Peeters, Luk
Fasbender, Dominique
Batelaan, Okke
Dassargues, Alain
Journal Title
Journal ISSN
Volume Title
Publisher
American Geophysical Union
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Rights Holder
Abstract
The creation of a contour map of the water table in an unconfined aquifer based on
head measurements is often the first step in any hydrogeological study. Geostatistical
interpolation methods (e.g., kriging) may provide exact interpolated groundwater levels at
the measurement locations but often fail to represent the hydrogeological flow system. A
physically based, numerical groundwater model with spatially variable parameters and
inputs is more adequate in representing a flow system. Because of the difficulty in
parameterization and solving the inverse problem, however, a considerable difference
between calculated and observed heads will often remain. In this study the water‐table
interpolation methodology presented by Fasbender et al. (2008), in which the results of a
kriging interpolation are combined with information from a drainage network and a digital
elevation model (DEM), using the Bayesian data fusion framework, is extended to
incorporate information from a tuned analytic element groundwater model. The resulting
interpolation is exact at the measurement locations whereas the shape of the head contours
is in accordance with the conceptual information incorporated in the groundwater‐flow
model. The Bayesian data fusion methodology is applied to a regional, unconfined aquifer
in central Belgium. A cross‐validation procedure shows that the predictive capability of
the interpolation at unmeasured locations benefits from the Bayesian data fusion of the
three data sources (kriging, DEM, and groundwater model), compared to the individual
data sources or any combination of two data sources.
Description
Keywords
Hydrogeology, Water tables, Conceptual modelling, Kriging
Citation
Peeters, L., Fasbender, D., Batelaan, O. and Dassargues, A., 2010. Bayesian data fusion for water table interpolation: incorporating a hydrogeological conceptual model in kriging, Water Resources Research, 46, W08532.