A 3-dimensional geological model of the Oak Ridges Moraine area, Ontario, Canada

Abstract

The Oak Ridges Moraine area, southern Ontario, includes most of the Greater Toronto Area, which is the most populated region of Canada. The ∼11,000 km 2 region is bounded to the south by Lake Ontario and to the north where Paleozoic bedrock abuts Precambrian Canadian Shield. The area extends 160 km eastward from the Niagara Escarpment, a prominent 100 m high regional bedrock scarp. The surficial sediment is up to 200 m thick, and reveals exposures of the oldest Quaternary sediment in southern Canada. Population growth has caused land use conflicts and increased pressure on groundwater resources. Construction of a regional 3-D geological model of the glacial stratigraphy was needed to support a better understanding of aquifer distribution, scale, and resource potential and protection.Mapping of the regional glacial geomorphology and sediment succession identified a number of distinct landforms: tunnel channels, drumlins, eskers, moraines, and till and lacustrine plains. Using sequence stratigraphic concepts, strata have been grouped into four principal units that unconformably overlie Paleozoic bedrock: Lower sediment, Newmarket Till, Oak Ridges Moraine, and Halton Till.These four Quaternary units plus bedrock have been mapped in the subsurface as a succession of interpolated surfaces using an innovative stratigraphic database-GIS approach. The model-building process involved stratigraphically coding high-quality data, then integrating an extensive and diverse array of subsurface geological and archival datasets using an expert system (geological rules). Stratigraphic data subsets were then extracted and merged with DEM-controlled surface mapping and interpolated in a GIS.

Mediating stream baseflow response to climate change: The role of basin storage

“…The Oak Ridges Moraine (ORM) is an important hydrogeologic feature in Southern Ontario (Holysh & Gerber, 2014), supplying potable water to~60,000 wells (Sharpe, Russell, & Logan, 2007) and more than 250,000 people (Furberg & Ban, 2012). Studies of the linkage between climate change and stream BF response in the ORM region benefit from the numerous streams that are gauged in the region, the relatively high density of climate stations for assessing temporal trends in key hydroclimatic drivers and the detailed hydrogeologic information available for the region.…”

Comment on “Converging ice streams: a new paradigm for reconstructions of the Laurentide Ice Sheet in southern Ontario and deposition of the Oak Ridges Moraine”

“…There is also a lack of citations of much of the work on the subsurface of the ORM and where it is cited, Sookhan et al (2018) do not correctly apply the information. For example, Sookhan et al (2018) directly reference a figure of Sharpe et al (2007) that documents seismic data of incised and buried valleys beneath the ORM, yet they state throughout the article that the valleys stop at the northern flank of the ORM. Sookhan et al (2018) suggest that geomorphologic data provide unambiguous evidence that the ORM was formed between converging paleo ice streams.…”

“…As a surface expression of the landscape, valleys stop at the moraine because the ORM sediment overlies and infills the southward subsurface extension of the valleys (e.g., Barnett et al 1998). Data from seismic and drillcore are extensive and unambiguous in the documentation of valley extension beneath the ORM, in papers cited by Sookhan et al (2018) (e.g., Russell et al 2004;Brennand et al 2006;Sharpe et al 2007;Sharpe et al 2013) and in additional publications (e.g., Pugin et al 1996Pugin et al , 1999Barnett et al 1998;Sharpe et al 2002Sharpe et al , 2004Russell et al 2003aRussell et al , 2003b. Drawing upon technical groundwater reports, Sookhan et al (2018) reference Kassenaar and Wexler (2006) as supporting the absence of a regional network of tunnel valleys.…”

Performance evaluation of groundwater model hydrostratigraphy from airborne electromagnetic data and lithological borehole logs

“…Geological knowledge, which can be incorporated into cognitive geological models (Royse, 2010;Scharling et al, 2009;Sharpe et al, 2007), cannot be included in automatically generated models. Geological knowledge may identify continuity/discontinuity of geological layers, or discriminate between materials based on stratigraphy or depositional environment.…”