| Title | Directional geostatistical simulation for regional hydrostratigraphic units uncertainty characterization, Innisfil Creek sub-watershed, Ontario |
| Download | Download (whole publication) |
| |
| Licence | Please note the adoption of the Open Government Licence - Canada
supersedes any previous licences. |
| Author | Benoit, N; Marcotte, D; Boucher, A; Bajc, A F |
| Source | Regional-scale groundwater geoscience in southern Ontario: an Ontario Geological Survey, Geological Survey of Canada, and Conservation Ontario open house; by Russell, H A J ; Ford, D; Priebe, E H; Geological Survey of Canada, Open File 8212, 2017 p. 2,
https://doi.org/10.4095/299758  Open Access |
| Year | 2017 |
| Publisher | Natural Resources Canada |
| Meeting | Ontario Geological Survey and Geological Survey of Canada groundwater geoscience open house; Guelph; CA; March 1-2, 2017 |
| Document | open file |
| Lang. | English |
| Media | on-line; digital |
| Related | This publication is contained in Regional-scale groundwater
geoscience in southern Ontario: an Ontario Geological Survey, Geological Survey of Canada, and Conservation Ontario open house |
| File format | pdf |
| Province | Ontario |
| NTS | 31D/04; 31D/05 |
| Area | Innisfil Creek |
| Lat/Long WENS | -80.0000 -79.5000 44.3333 44.0000 |
| Subjects | hydrogeology; mathematical and computational geology; stratigraphy; environmental geology; groundwater; aquifers; groundwater regimes; groundwater flow; hydrostratigraphic units; geostatistics; models;
computer simulations; resource management; Innisfil Creek subwatershed |
| Program | Groundwater Geoscience Aquifer Assessment & support to mapping |
| Program | Groundwater Geoscience Aquifer Assessment & support to mapping |
| Released | 2017 02 22 |
| Abstract | The uncertainty characterization of hydrostratigraphic systems is important for risk assessment in hydrogeology. A complex system is difficult to characterize due to limited sampling. Geostatistical
simulation methods aim at representing the underlying modeling uncertainties about hydrostratigraphic units proportions, properties and spatial arrangement through an ensemble of equally probable models. These models control the connectivity and,
ultimately, the response of the system under an external stimulus. It is then critical to have geostatistical algorithms that can accurately reproduce the geological controls on the flow, such as the directional ordering of units. The latter is an
important and common feature of sedimentary environments. Recent developments in geostatistics have improved the realism of hydrostratigraphic units simulation. In that regard, we revisited the Markovian Categorical Prediction (MCP) simulation method
to allow for trends and directional ordering in simulation. The adapted MCP approach was applied to determine the uncertainty at a regional scale within the Innisfil Creek subwatershed with its 18 hydrostratigraphic units. The trend in unit
occurrences is accounted for by locally confining the geostatistical algorithm to a deterministic model, without resorting to auxiliary variables. The presented methodology allows characterization of the uncertainty of the hydrostratigraphic
model.
The outputs are a suite (ensemble) of models, which provide a variability assessment of the spatial units arrangement and are an alternative to the deterministic one that complies with known data and unit ordering and trends. The
alternative models propose a realistic variation for the thicknesses of the different units. Results suggest that the updated MCP methodology is highly flexible and efficient for closely replicating hydrostratigraphic units ordination, even for units
occurring with low frequency. These geostatistical models are then appropriate for characterizing the uncertainty of groundwater flow and transport as well as aquifer vulnerability and the delineation of wellhead protection areas. |
| Summary | (Plain Language Summary, not published)
Proceedings for Regional-Scale Groundwater Geoscience in Southern Ontario open house organized by the Ontario Geological Survey, Geological Survey of
Canada and Conservation Ontario Geoscientists. Open house is on 2017-03-01 and 02. Purpose is public engagement and dissemination of geoscience completed in Southern Ontario during the past year. |
| GEOSCAN ID | 299758 |
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