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TitleExtreme river flow prediction for river water supply to oil sands mining sites, Athabasca River near Fort McMurray, Alberta,
LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorChen, G; Chen, ZORCID logo
SourceGeological Survey of Canada, Open File 6863, 2017, 147 pages, Open Access logo Open Access
PublisherNatural Resources Canada
Documentopen file
Mediaon-line; digital
RelatedThis publication is related to Support vector machine for the prediction of future trend of Athabasca River (Alberta) flow rate
File formatpdf
AreaAthabasca River; Fort McMurray
Lat/Long WENS-111.5000 -111.0000 56.7500 56.5000
Subjectshydrogeology; mathematical and computational geology; Nature and Environment; modelling; climate; climatic fluctuations; temperature; precipitation; hydrologic properties; hydrologic environment; surface waters; rivers; Climate change; Hydrology; Water supply; Water supply
Illustrationstime series; tables; plots; models
ProgramGeoscience for New Energy Supply (GNES) Program Coordination
Released2017 03 07
This report has been prepared at the request of Geological Survey of Canada (GSC). The speci
c instructions from GSC asked to develop the following deliverables: 1. Computer R source code in digital format; 2. Prediction results of extreme values of annual river ow rates (annual minimum and maximum); 3. A report that describes the methods and application to the Athabasca River near Fort McMurray;
4. The work is to be completed and submitted by January 15, 2011.This report meets and exceeds the above requirements.
Summary(Plain Language Summary, not published)
With increasing global mean temperature, extreme climate events become more evidence. Although various methods are available for predictions of river flow rate, none of the methods have the capacity to estimate the extremes of river flows (particularly the annual low) by incorporating different climate change scenarios, which is essential for sustainable water supply under a changing climate. This open file reports the results from a methodology study for prediction of future extreme river flow rates under different climate change scenarios.

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