View article

Stochastic groundwater models enable the characterization of geological uncertainty. Often the major source of uncertainty is not related to aquifer heterogeneity, but to the general shape of the aquifer. This is especially the case in paleovalley-type alluvial aquifers where the bedrock surface limits the extent of easily extractable groundwater. Determining the shape of a bedrock surface is not straightforward, because it is typically non-stationary and defined by few data points that are generally far apart. This paper presents a new workflow for the stochastic reconstruction of bedrock surfaces using limited datasets that are typically available for aquifer characterization. The method is based on a lateral propagation of basement cross-sections interpreted from geophysical surveys, and conditions the reconstructed surface to existing well-log data and digital elevation model. To alleviate the typical limitations of sparse …