harbour but stop it from flowing upstream. In these cases the low-lying areas beyond
the barrier were not included. Presently there are no built in tools within the
commercial GIS and image processing systems we used in this project to automate this
type of connectivity while mapping flood risk. Therefore, a software program was
developed by M. Gould at the Applied Geomatics Research Group, Centre of
Geographic Sciences to automate the procedure. The program allows the user to enter a
water level and a starting location, and the application will use a DEM to determine all
of the areas below that water level that are connected to the starting point (a location in
the harbour was used in this case).
As mentioned earlier, the 21-22 January 2000 storm-surge flood provided an ideal
validation test. Areas flooded during that storm were compared to those generated from
the DEM model and a very good match was observed. One circumstance that the model
did not account for was the backup of seawater through the storm drain system with
water flowing up and out of street drains near the waterfront. Many of these areas were
in low-lying areas that were predicted to be flooded in the model.
Having obtained good agreement between the observed and predicted water levels
of the 21-22 January 2000 storm, we proceeded to model two additional future water
levels using a similar approach (Figure 16). The flood risk vectors show the variation of
slope within the coastal zone. Many areas have steep slopes and are not vulnerable to
flooding, although erosion may be a problem. The waterfront of Charlottetown is
vulnerable to flooding, as is the residential area to the west of the downtown core
(Figure 17).
4.3 FLOOD-DEPTH MAPS
Another set of layers from our analysis of the flood risk was the depth of the water
within the flooded areas. This was calculated by subtracting a constant value of the
flood water level from the DEM only for the areas at flood risk. This produced a grid of
flood depth values and provides more information than just the flood risk vector that
shows the area of inundation from flooding. The amount of damage will be related to
the depth of the floodwater, where more damage is expected with deeper flood depths.
This is especially true for residential areas where the floodwater must reach a high
enough point to enter the basement through windows that are low to the ground or
doorway entrances. An example of the flood depth map is shown on Figure 18 for the
21-22 January 2000 flood level. A revised economic impact assessment has not yet
been implemented using these maps. However, such maps can add significantly to the
information regarding flood risk, impact mitigation, and adaptation planning required to
minimize the effects of flooding.
4.4 FLOOD-RISK IMPACT ANALYSIS AND ADAPTATION
An additional component of the project focused on the potential economic impacts
of flooding events (Milloy and MacDonald, 2002). Much of the analysis involved the
use of GIS to summarize the areas potentially affected by flooding. This involved
compilation of the municipal GIS database, including property boundaries and building
footprints, linked to other databases such as property and building assessment
information, in relation to flood extent at various water levels (Dickie, 2001). Initially a
simple overlay of the flood-risk areas and the property boundaries was used to
determine that the flood affected more than 460 properties. By summarizing the tax
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the barrier were not included. Presently there are no built in tools within the
commercial GIS and image processing systems we used in this project to automate this
type of connectivity while mapping flood risk. Therefore, a software program was
developed by M. Gould at the Applied Geomatics Research Group, Centre of
Geographic Sciences to automate the procedure. The program allows the user to enter a
water level and a starting location, and the application will use a DEM to determine all
of the areas below that water level that are connected to the starting point (a location in
the harbour was used in this case).
As mentioned earlier, the 21-22 January 2000 storm-surge flood provided an ideal
validation test. Areas flooded during that storm were compared to those generated from
the DEM model and a very good match was observed. One circumstance that the model
did not account for was the backup of seawater through the storm drain system with
water flowing up and out of street drains near the waterfront. Many of these areas were
in low-lying areas that were predicted to be flooded in the model.
Having obtained good agreement between the observed and predicted water levels
of the 21-22 January 2000 storm, we proceeded to model two additional future water
levels using a similar approach (Figure 16). The flood risk vectors show the variation of
slope within the coastal zone. Many areas have steep slopes and are not vulnerable to
flooding, although erosion may be a problem. The waterfront of Charlottetown is
vulnerable to flooding, as is the residential area to the west of the downtown core
(Figure 17).
4.3 FLOOD-DEPTH MAPS
Another set of layers from our analysis of the flood risk was the depth of the water
within the flooded areas. This was calculated by subtracting a constant value of the
flood water level from the DEM only for the areas at flood risk. This produced a grid of
flood depth values and provides more information than just the flood risk vector that
shows the area of inundation from flooding. The amount of damage will be related to
the depth of the floodwater, where more damage is expected with deeper flood depths.
This is especially true for residential areas where the floodwater must reach a high
enough point to enter the basement through windows that are low to the ground or
doorway entrances. An example of the flood depth map is shown on Figure 18 for the
21-22 January 2000 flood level. A revised economic impact assessment has not yet
been implemented using these maps. However, such maps can add significantly to the
information regarding flood risk, impact mitigation, and adaptation planning required to
minimize the effects of flooding.
4.4 FLOOD-RISK IMPACT ANALYSIS AND ADAPTATION
An additional component of the project focused on the potential economic impacts
of flooding events (Milloy and MacDonald, 2002). Much of the analysis involved the
use of GIS to summarize the areas potentially affected by flooding. This involved
compilation of the municipal GIS database, including property boundaries and building
footprints, linked to other databases such as property and building assessment
information, in relation to flood extent at various water levels (Dickie, 2001). Initially a
simple overlay of the flood-risk areas and the property boundaries was used to
determine that the flood affected more than 460 properties. By summarizing the tax
176
Webster and Forbes