Construction of a geological model for southern Manitoba for groundwater modelling
Author(s) -
L H Thorleifson,
G L D Matile,
G. Keller,
D M Pyne
Publication year - 2002
Language(s) - English
Resource type - Reports
DOI - 10.4095/299512
Subject(s) - groundwater , geology , hydrology (agriculture) , geotechnical engineering
Most of the one million inhabitants of Manitoba, Canada, live in the 400-km x 700-km area of Phanerozoic terrane adjacent to North Dakota and Minnesota, and the majority live in the Winnipeg area, a 200 km x 230 km area in the southeastern corner of the province. The City of Winnipeg obtains water from Shoal Lake, but the 200,000 residents of surrounding areas rely on groundwater from bedrock aquifers. Fresh water in these aquifers consists of modern recharge and relict subglacial recharge, but a saline water system recharged in South Dakota and Montana discharges to the western Red River valley. Research on the long-term sustainability of the fresh groundwater resource is addressing protection of recharge, and ensuring that excessive pumping does not lead to unacceptable lateral migration of the saline waters. Groundwater modelling is a key element of this strategy. The first phase of work involved construction of a pilot model for the Winnipeg area, and the geological model for this area has now been successfully used for groundwater flow modelling by P. Kennedy, under the supervision of A. Woodbury (Kennedy, P. L. 2002: Groundwater flow and transport model of the Red River/Interlake area in southern Manitoba; University of Manitoba Ph.D. thesis, 273 pp). Having completed the pilot model, work is now underway to build a 3D geological model of the entire Phanerozoic succession of southern Manitoba, including reconciliation with the stratigraphy of Saskatchewan, North Dakota, Minnesota, and Ontario. Having found readily available digital elevation models (DEMs) to be inadequate, a new digital elevation model was constructed by the authors, largely from Provincial legal survey data*. The resulting model has a grid resolution of 100 m, absolute vertical accuracy of about +/3 m, and relative accuracy of less than a metre. The DEM has been used to position drillholes vertically, the geological model hangs from the topography, and the DEM has provided insight into previously unrecognized geological features. Large lakes occur in the area, including Lake Winnipeg, which is 25% larger than Lake Ontario. These are key features in the hydrological landscape, and lake-bottom features provide insights into geology. Soundings from 22 hydrographic charts therefore were digitized and a database containing 31,607 digitized bathymetry points was created. These were gridded with shoreline data and locations of shoals, at a grid resolution of 100 m. Offshore geology of Lake Winnipeg is being interpreted from geophysical and coring data collected during two one-month cruises. Surficial geological maps are being digitised and reconciled as a guide to 3D modelling of the uppermost strata, and efforts are underway to better utilize soil mapping. The subsurface geological model is not directly linked to the surficial map polygons, due to the greater detail of the surficial geological mapping. Key inputs to the 3D model of the sediments were cored holes logged by geologists, and geophysical surveys. These high-quality results were extrapolated laterally using water well data from 80,000 sites (Figure 1; Figure 2). The 200 km x 230 km Winnipeg pilot area was divided into 46 transects each 5 km wide, and a large colour chart was printed for each transect, showing all drillhole data, surficial geology, and surface elevation. The drillhole data were correlated lithologically (Figure 3) and the correlation was digitised as predicted stratigraphy points at a 5-km spacing, which were then gridded. A new set of 1:1 million bedrock polygons for the Phanerozoic units was constructed, linking outcrop to subcrop, to produce stacked polygons. Structure contours for each Phanerozoic unit were then gridded. Experimentation presently underway is meant to optimize methods for model construction, verification, and communication.
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