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FINAL REPORT - International Joint Commission

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The Lower St. Lawrence River<br />

In comparison to the upper portion of the study area, the waters downstream of the control dam are<br />

differentiated by the influences of river flows, ship wakes and the response of shorelines composed,<br />

for the most part, of marine clays.<br />

ANNEX 2<br />

An extensive digital data collection of bathymetry, topography, flow conditions, aerial photography and<br />

databases relating the land-use and erosion processes was compiled in a data warehouse based in the<br />

Ste-Foy, Quebec offices of Environment Canada. This dataset formed the backbone of the performance<br />

indicator analysis for the lower St. Lawrence.<br />

Application of regional-scale computer modeling to the shorelines of the lower St. Lawrence River from<br />

Cornwall, Ontario to Trois-Rivières, Quebec was developed by Pacific <strong>International</strong> Engineering to create a<br />

new and clear understanding of the relative importance of river currents, wind waves and ship-generated<br />

waves and how they interact with water levels (Pacific <strong>International</strong> Engineering, March 2004). This enabled<br />

the development of simplified predictive tools for erosion and an assessment of economic impacts.<br />

Flooding stage-damage relationships were developed for 42 municipalities on the lower St. Lawrence River<br />

from Cornwall to Trois Rivières by Environment Canada-Quebec Region based on parcel and assessment<br />

data of the affected properties and a fine-resolution digital elevation model developed for the Coastal<br />

Technical Work Group by the Common Data Needs Technical Work Group (refer to that section).<br />

Performance Indicators<br />

Lake Ontario–Upper St. Lawrence River<br />

The impacts of water level fluctuations on Lake Ontario and upper St. Lawrence River shoreline<br />

communities were categorized by three primary performance indicators, specifically: flooding, shoreline<br />

erosion of developed properties, and existing shoreline protection maintenance. The Coastal Technical<br />

Work Group also examined sediment budgets, beach access, and barrier beaches and dunes as possible<br />

performance indicators.<br />

Flooding<br />

Over 3,000 shoreline property parcels are located below elevation 76.2 m (250 ft) and could be at risk of<br />

flooding on Lake Ontario and the upper St. Lawrence River. Flood damages to these properties generally<br />

occur during periods of high lake levels and severe storms. The flooding performance indicator on Lake<br />

Ontario quantifies the impacts of flooding due to inundation of structures and the force of waves striking<br />

buildings. Economic damage calculations are made for individual property parcels at risk of flooding.<br />

The flooding performance indicator algorithm was developed, tested, calibrated and verified in the Flood<br />

and Erosion Prediction System (FEPS). The flooding performance indicator algorithm is applied to the<br />

entire parcel database for the duration of a simulation in the Shared Vision Model, commonly 101 years.<br />

However, the wave database was based on 40 years of data statistically hindcast to represent the 101-year<br />

simulation period. An analysis determined that this could significantly affect plan results as the happenstance<br />

nature of waves meant that a plan that shifted levels might avoid or enhance damage depending on the wave<br />

sequence. To address this, a number of statistically generated wave sequences were derived based on the<br />

quarter month maximum of the maximum, the average of the maximums and the 1st and 2 nd standard<br />

deviation from the maximum. The results could be tested for all of these sequences. Using this method,<br />

it was determined that the 1st standard deviation was probably the best wave-sequence representation for<br />

ensuring that the numbers were not being underestimated. The 40-year hindcast wave data was used in<br />

the 50,000 stochastic analyses since the shear number of combinations of levels and waves would dismiss<br />

any bias in the data. For more information on the flooding performance indicator refer to the report<br />

Flooding Performance Indicator: Methodology and Shared Vision Model Application (Baird, 2004a).<br />

Options for Managing Lake Ontario and St. Lawrence River Water Levels and Flows<br />

57

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