Lab 7 - Coastal Flooding

In this assignment, we learned to use elevation models to analyze impacts of coastal flooding. In the first part, we used a high-res LIDAR DEM for Honolulu, Hawaii to determine the impacts of two sea-level rise scenarios. We examined the population impacted by the flooding and analyzed the population distribution impacted and how it differed (or didn’t) from the overall population. In the second part, we compared the use of two elevation models for Collier County, Florida to determine the extent of flooding due to a 1 meter storm surge, and analyze the differences between the two results.

In the first part, I wanted to assess the extent of the area of impact of flooding due to a 3 foot sea level rise and a 6 foot sea level rise. I used the Lidar DEM and the desired sea level rise value as inputs to create rasters showing flooded and non-flooded areas for both scenarios. After I created the rasters showing the flooded areas, I was able to calculate the area flooded for the two scenarios. As expected, the area flooded from a 6 ft sea level rise is much greater than that flooded by a 3 ft sea level rise. Next, I wanted to investigate sea level rise vs. population density in the 6 foot sea level rise scenario. Values were calculated with the Field Calculator. The map below shows 1) the flooded area for the 6 ft scenario, 2) the flooded depth within the flooded area, and 3) the population density by census tract.

I then wanted to determine the population affected by the rise in sea level. For this I needed to convert the raster into a polygon and used the “centroid containment” analysis to include block groups whose centroids are within the flooded area. I added fields to the table and calculated the percent of various demographics that are affected by the flooding. From this, it can be seen that over 60,000 people are affected by flooding, although over 1.3 million are not flooded. As far as demographics are concerned, 35% of those affected are white, ~32% are owner occupied residences, and over 16% of those affected are 65 years of age or older. Of those not flooded, a quarter are white, over half are owner occupied residences, and ~13% are 65 years of age or older.

In the second part of the lab, I wanted to determine the impact of a uniform 1 meter storm surge on Collier County, Florida. Of course, storm surges are not usually uniform, but this is a good example of coastal flooding.  Using LIDAR and USGS elevation models, I wanted to show which cells are flooded. One catch here was that the LIDAR elevation model was in feet so I needed to convert from feet to meters. After creating rasters showing flood areas as an elevation less than 1 meter, there were a few disconnected areas; areas below 1 meter that were further inland and surrounded by higher elevation and won’t flood from a storm surge. Using the Region Group tool allowed me to eliminate those areas by only selecting regions connected to the coast, ensuring I was getting areas that will flood as they are directly connected to the incoming storm surge. I was able to determine how many buildings of which type were impacted and from that, compare the reliability of the elevation models in modeling coastal flooding due to a storm surge. When calculating the errors of omission for the LIDAR elevation model, I found that it was consistently undercounting the number of buildings by a little over 30% overall. The USGS model seemed to be a little more reliable, overcounting the number of buildings that would be flooded by about 8% overall.

I learned a lot about comparing the two elevation models and how the results can differ depending on which you choose to use. I still need some practice with calculating errors of omission and commission, but the concept makes sense. Of course, storm surges are not a uniform height. One needs to take into account the strength and speed of the storm causing the storm surge, the size of the coastline, whether there are any coastline features that help inhibit or enhance the storm surge, etc. That being said, I did enjoy this lab and learned a lot about modeling coastal flooding using GIS.