Riverine Flooding in Wissahickon Creek – Photo by Steven-L-Johnson on Flickr

Background

A flood is the overflowing of a large amount of water beyond its normal confines. Flooding is a pressing problem in Philadelphia with several causes; a problem that is likely worsening as the climate changes. Geographic Information System mapping can visually exhibit the risks associated with flooding in the city.

One viewpoint through which to analyze the impacts of flooding is the Flood Insurance Rate Map (FIRM) database established by the Federal Emergency Management Agency (FEMA)[1]. The database depicts flood risk information and supporting data based on the 1-percent-annual-chance flood event (i.e. a “100 year flood”), and the 0.2-percent-annual-chance flood event (i.e. a “500 year flood”)[3]. The FIRM database is a geospatial translation of the flood hazard analyses published by FEMA. The dataset includes geospatial and tabular information such as hydrographic features (surface water), regions at risk of 18-inch coastal waves (modeled based on topography and vegetation), insurance risk zones (based on 100-year flood risk), flood control structures, levees, and pertinent geographic barriers such as political jurisdiction and measurement lines. FEMA does not provide the specific definition of a “flood control structure” but describes barriers such as flood walls as being one type of flood control structure.  

Further risk data can be attained through localized analyses. The Pennsylvania Statewide Flood Study, made available by the Pennsylvania Emergency Management Agency (PEMA) estimates economic loss and housing damage due to flooding across the state[4]. The corresponding flood study generated models of five scenarios (10, 50, 100, 200 and 500-year floods) based on streams and rivers with a drainage basin area of 10 square miles or more. Flood impact predictions are divided by census block.

Economic losses data from this dataset can be displayed based on total cost, building damage, content damage, and more. Damaged homes data can be displayed based on total number damaged, substantially damaged homes, and homes by percent damage for each of the affected census blocks. “Substantially damaged homes” are defined as structures that reside within the 1-percent-annual-chance floodplain for which the total cost of repairs is 50 percent or more of the structure’s market value before the disaster occurred[5]. This designation does not include land value and does not depend on the specific cause of damage.

Other flood infrastructure can be considered in addition to the flood control structures and levees provided by the FEMA dataset. Specifically, the Philadelphia Water Department’s Green Stormwater Infrastructure (GSI) can be mapped across the city. Several datasets demonstrate these projects. The datasets I utilized were private GSI retrofits[6], public GSI projects[7], and public street projects[8]. Detailed descriptions of each type of project are available on the Philadelphia Water Department website[9].

 

Methods

Mapping flood risk using GIS helps Philadelphians visually view snapshots of otherwise unreadable but valuable information. All three of the sets of maps created are focused on Eastwick, Mayfair, Germantown, Grays Ferry, Kingsessing, and South Philadelphia as a whole. The former three regions were analyzed because they are the locations of our 2018 Climate Health and Home workshops, which focus on flooding. The latter three regions were chosen due to the large flood risk noticed in these areas upon mapping the data. 
To create maps of flood infrastructure, I mapped flood control structures from the FEMA dataset (I included levees in this ‘flood control structures’ category, although they were categorized separately in the dataset). I also added GSI sites from the Philadelphia Water Department to establish a more accurate depiction of flood control infrastructure in the region. Additionally, I included flood hazard lines from the FEMA dataset to provide context for the flood infrastructure, as well as to explore high-risk areas that are not yet protected. Where present, I included coastal wave risk in the flood hazard feature. To assist with viewer understanding, I also included Philadelphia neighborhoods[10], roads, and hydrographic features.
I created map sets of economic losses and housing damage as well. I displayed each based on total cost and total number of damaged homes, respectively. For each I chose consecutive colors to help the viewer understand the worsening flood scenarios by year. I also included neighborhoods, roads, and hydrographic features for context. Since not all economic and housing damage appears to be correlated with proximity to flood hazard lines, future maps might consider additional flood factors such as sewer overflow and runoff.

[1] http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=2365

[2] https://pubs.usgs.gov/gip/106/pdf/100-year-flood-handout-042610.pdf

[3] https://www.fema.gov/flood-zones

[4] http://www.pasda.psu.edu/uci/SearchResults.aspx?Keyword=pema+flood

[5] https://www.fema.gov/news-release/2017/09/14/fact-sheet-nfip-substantial-damage-what-does-it-mean

[6] https://www.opendataphilly.org/dataset/gsi-private-retrofit-projects

[7] https://www.opendataphilly.org/dataset/gsi-public-projects-points

[8] https://www.opendataphilly.org/dataset/gsi-public-projects-street

[9] http://philadelphiawater.org/gsi/planning-design/

[10] https://www.opendataphilly.org/dataset/philadelphia-neighborhoods

Related Posts

Part 4: Modeled Economic Losses from Riverine Flooding

Part 3: Predicting Housing Damage from Riverine Flooding

Part 2: Flood Control Infrastructure