Skip to main content

Field characterization and data integration to define the hydraulic heterogeneity of a shallow granular aquifer at a sub-watershed scale

Providing a sound basis for aquifer management or remediation requires that hydrogeological investigations carried out to understand groundwater flow and contaminant transport be based on representative data that capture the heterogeneous spatial distribution of aquifer hydraulic
properties. This paper describes a general workflow allowing the characterization of the heterogeneity of the hydraulic properties of granular aquifers at an intermediate scale covering a few km2. The workflow involves characterization and data integration steps that were applied on a 12 km2 study
area encompassing a decommissioned landfill emitting a leachate plume and its main surface water receptors. The sediments composing the aquifer were deposited in a littoral-sublittoral environment and show evidence of small-scale transitional heterogeneities. Cone penetrometer tests (CPT) combined
with soil moisture and electrical resistivity (SMR) measurements were thus used to identify and characterize spatial heterogeneities in hydraulic properties over the study area. Site-specific statistical relationships were needed to infer hydrofacies units and to estimate hydraulic properties from
high-resolution CPT/SMR soundings distributed all over the study area. A learning machine approach was used due to the complex statistical relationships between colocated hydraulic and CPT/SMR data covering the full range of aquifer materials. Application of this workflow allowed the identification
of hydrofacies units and the estimation of horizontal hydraulic conductivity, vertical hydraulic conductivity and porosity over the study area. The paper describes and discusses data acquisition and integration methodologies that can be adapted to different field situations, while making the aquifer
characterization process more time-efficient and less labour-intensive.

In progress
Project URL
Start Date
End Date

The Great Lakes - St. Lawrence Research Inventory is an
interactive, Internet-based, searchable database created as a tool to collect and disseminate
up-to-date information about research projects in the
Great Lakes - St. Lawrence Region.