Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Master of Engineering Science

Program

Civil and Environmental Engineering

Supervisor

Simonovic, Slobodan P.

Abstract

Flooding events are among the costliest and most frequent natural hazards occurring in Canada. Floodplain mapping is a non-structural flood management strategy that involves the formulation of hydrologic and hydraulic models to produce maps which predict extent and depth of floods. Practices and availability of floodplain mapping vary across Canada. The current state of floodplain mapping across Canada has been identified and reviewed. Vast areas of flood prone regions across Canada have been identified as not having floodplain maps or lacking updated ones. Large region floodplain maps have been recently introduced and can cover national and global regions. Limitations of spatial resolution exist in large region mapping efforts, which hinder their implementation for local scale floodplain management practices. A recent study at Western University produced a national floodplain map with a spatial resolution of 1 km x 1 km. This national floodplain map is highly accurate; however, spatial resolution needs to be improved to be implemented within local scale floodplain studies. The study presented in this thesis developed a downscaling methodology to further improve spatial resolution of the floodplain map. The downscaling methodology was implemented to produce floodplain maps at spatial resolutions of 20m, 40m, 60m, 80m, 100m, 200m, 300m, and 400m for two case study river basins: Bow and Elbow River Basin and St John River Basin. Analysis of the floodplain maps was completed, followed by volume conservation and computational time studies to assess the accuracy of the proposed downscaling methodology and to compare the sensitivity of the downscaling methodology.

Summary for Lay Audience

Flooding is a regularly occurring event that accounts for large economic losses and insurance claims every year. Floodplain maps are a floodplain management tool designed to derive the extent of historic and projected flooding events. The floodplain maps are used to limit development within flood prone regions and to identify population, property, and infrastructure exposure, in the event of future flooding events. Provincial and territorial governments in Canada are responsible for the production of floodplain maps within their respective jurisdictions. Floodplain mapping practices vary across Canada, depending on the standards used to derive the extent of flooding and the availability of floodplain maps. The current state of floodplain mapping practices across Canada is reviewed here, as also the present issues with the availability and maintenance of maps for flood prone regions. Recently developed large region maps reflect floodplains at national, continental, and global regions and these can be created within a reasonable time period. A study conducted at Western University presented a framework for the production of a national floodplain map for Canada that was then used to identify population exposure across the country. However, the spatial resolution of many floodplain maps that cover large regions, including the national floodplain map produced by Western University, is approximately 1 km only due to computational limitations. This resolution is impractical for local scale studies and further improvement in resolution is required through downscaling. Common floodplain mapping downscaling methods were compared in this study and a methodology produced to improve the resolution of national floodplain maps. The downscaling methodology was performed to produce floodplain maps at resolutions of 20m, 40m, 60m, 80m, 100m, 200m, 300m, and 400m for two case study areas: Bow and Elbow River Basin and St John River Basin. The methodology depends on the practical utility of the map for local scale studies, the percentage volume of water conserved in downscaling, and overall computational time. The downscaled 100 m floodplain map is able to effectively predict property and infrastructure exposure and can be produced within an optimal computational time, thus reflecting its feasibility within local floodplain management strategies.

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