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Wednesday, December 4, 2013

Suffolk County Flood Risk Areas within the Charles River Watershed

Background Information

Floods are categorized by likelihood of occurrence, representing a corresponding ratio.  100 and 500 year flood events correspond to the following ratios: 1/100 and 1/500.   Hence, a given location categorized within a given risk area has a 0.2% chance of a 500 year flood, and a 1% flood of a 100 year flood occurring.  The lower the percent chance of a flood occurring, the more severe and extensive the flooding event.  A 500 year flood will impact a greater land area than a 100 year flood.   In the map to the left, 100 year flood zones are designated in orange, while 500 year flood areas are in red.   Because 500 year floods impact greater areas, the red highlights the distance beyond 100 year flood zones the water extends. Flood areas are generally located along coastal areas in near proximity of a water body.

Data Sets
  • MassGIS Data Layers
    • Major Watersheds
    • County Boundaries
    • Landuse (2005)
    • Hydrography (1:25,000) for Charles River Watershed
    • MassDot Roads (major roads)
    • NFHL Flood Data
Methodology

All data sets were uploaded into ArcGIS 10.1 and set to the same projection.  Suffolk county and the Charles River Watersheds were selected and exported into a new shapefile from their associated datasets.  Using the Geoprocessing tool Intersect,  the area of Suffolk county that falls within the Charles River Watershed was isolated and made into a new shapefile. 

Downloaded land use data was then clipped down to the geographic extent of the Charles River - Suffolk County intersect area. To next step is to analyze 500 and 100 year flooding events have on land use types.  Because a 500 year flood is more severe, land use data is then clipped down to the spatial extent of all the flood zones.  From this new file, new areas of focus were calculated then run summary statistics on to calculate the total area at risk of a 500 year flood within each land use type. This study focuses on residential, urban, commercial, and industrial areas.

Once the land use areas were calculated, the study examined the road types affected by each type of flood.  The major roads shapefile was clipped down to the extent of the 500 year flood zones, then using Field Statistics, the length of the roads within the 500 year flood zones was calculated.  Summary Statistics were then run on the the file to calculate the total length of road types falling within the flood zones. 

To calculate the area of land use types and roads affected by 100 year flood, the same methodology was repeated, but the initial flood zones used are changed.  Because 100 year floods are less serious,  only flood zones A, AE, and VE were used.  These categories were selected and exported into a separate shapefile.  From here, the previously noted methodology was repeated to obtain the affect 100 year floods have on selected land use and road types.

Conclusions

As expected, 500 year flood risk areas have a greater area than 100 year floods.  Commercial and urban areas are projected to be highest impacted for each flood category, and industrial the least.  Due to levels of tourism, shipping ports, and desired property located along coastal areas, they are or more densely populated with businesses to sustain a denser population. Residential areas are generally more spread out and located further from the densely populated water front property so they are less at risk.

This analysis found that of the major roads, non-numbered roads were most at risk.  These roads comprise of general streets, not defined as interstates, highways or state routes.  Because larger routes usually do not extend to coastal areas found to be most at risk, the smaller roads within these areas are projected to suffer greatest impact.  In the event of a flood, non-numbered roads will require monitoring and maintenance by the Massachusetts Department of Transportation.

Map Links

ESRI Story Map Version:  http://www.arcgis.com/apps/StorytellingTextLegend/index.html?appid=1776a31e14254d11b797ea0a0777aa6b



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