Marie-Catherine Talbot Poulin’s scientific contributions

The rate of permafrost degradation in northern Quebec, Canada, has increased over the last two decades due to climate warming, which is expected to significantly modify the hydrogeologic and thermal regimes. Groundwater accessibility is also expected to increase and could become a significant source of drinking water for northern communities. In this project, an integrated surface water / groundwater flow model, HydroGeoSphere, is being applied to a 2 km2 catchment in northern Quebec to assess the effect of future climate change on thermo-hydrological conditions as well as on changes in groundwater availability for northern communities. The catchment is located in a discontinuous but widespread permafrost zone near Umiujaq (northern Quebec, Canada) where the subsurface consists of a 10-30 m-thick coarse-grained glaciofluvial layer forming a good aquifer beneath a permafrost-rich silty marine unit. A conceptual thermo-hydrological model of the catchment has been built from field data collected over 5 years, including hydraulic heads, stream flow rates, subsurface geology, as well as ground temperatures and thermal fluxes around two 10-20 m-thick permafrost mounds. The integrated 3D numerical model includes variably-saturated groundwater flow with transient recharge, as well as advective-conductive heat transport driven by transient air temperatures (varying from about -40 to +30 ºC) and a geothermal heat flux of 60 mW/m2. The model is calibrated to observed heads and temperatures by coupling PEST with HydroGeoSphere, allowing changes in hydraulic and thermal conductivities. Preliminary results are consistent with the available observed data, however non-uniqueness remains an important issue. The simulations are providing useful predictions of the permafrost thaw rate and associated changes to the hydrogeological flow system, including increased aquifer recharge following permafrost thaw.

The identification and removal of data outliers remains a major challenge for spatial analysis of piezometric data. In this context, a simple semi-automated procedure for filtering outliers of depth to static water level was developed and used as a part of a regional groundwater-mapping project in the Québec Metropolitan Community, Québec, Canada. Following a few basic steps of data control, potential outliers were detected using two simple automated steps: (1) identifying water levels that are deeper than the 99th percentile of a high-reliability dataset compiled by groundwater professionals and assumed to adequately represent depths to static water level, and (2) using moving averages within a search radius of 250 m calculated around each well. All detected potential outliers were visually examined in a geographic information system and compared to neighbouring data before being kept or discarded. To evaluate the efficiency of the procedure, exploratory statistics, histograms and semi-variograms of the initial, intermediate and filtered datasets were compared to the high-reliability dataset. Objective interpolation was then performed using ordinary kriging. A cross-validation analysis showed a less biased and more accurate interpolation after applying the proposed outlier filtering procedure. Qualitative knowledge of the hydrogeological settings is an important component of this procedure which combines advantages of both manual and automated processing, making the procedure adaptive and easy to use. The final outcome of the proposed procedure is an improved interpolation map of depth to static water level along with minimised and low squared estimation errors.