Storm Surge Analysis in New Jersey and Florida

This week, we looked at elevation data for the New Jersey shoreline from pre and post Sandy datasets, and compared two DEMs in Florida to determine the impacts of a 1M storm surge and comparing how the elevation data effects the results.  

Below, you will see the final difference in elevation on a stretch of the Jersey shore from before and after Sandy. The pre-Sandy file has a more consistent coastline in terms of obvious areas of development.  There are many areas that now look almost like little inlets where housing has clearly been destroyed and beaches eroded.  There are clearly some areas that were hit much harder than others and destruction is not consistent or even.  The areas of greatest erosion appear to be along the center left of the image.  This matches up with my observations of the differences between the two las images and confirms the areas of greatest destruction.  There appear to be some data anomalies as you move farther inland in that the difference between the two layers is as if the post layer was subtracting a value of zero.  This is also right next to areas that were apparently built up during the storm.  The take home message is that destruction was not equal and that more analysis should be done to gain a greater understanding of the situation.

This exercise was very good because it helped me to think about the many variables to consider when assessing pre and post storm damage.  It also helped me to see the impact of data that does not perfectly align and the general limitations in analysis such as this.

The map below is a comparison of a USGS DEM and a LiDar DEM to assess the coastal affects of a 1M storm surge. There are a number of potential issues related to how we assumed the lack of connectedness and uniform surge could influence the areas being impacted.  In reality, it is quite likely that areas not showing a complete connection or that are in a low lying area, but surrounded by higher ground, are actually connected and vulnerable enough to be impacted by the combination of high winds, rainfall, and variability in storm surge that is not encapsulated in a study that assumes this level of uniformity.  Just because storm surge might max out at a given height on average, it does not mean this impact is felt equally across all regions and even limited connectivity and semi-protected areas should be considered as points of vulnerability.  We could adjust our analysis by applying a storm surge range that gives us a level of uncertainty with which to work.  We could also review the areas that show limited connectivity and determine what might be causing that limitation.  All limits to connectivity of elevation are not created equally and having a deeper understanding of those areas would be very beneficial in designing a study to better model real world possibilities.  Rainfall and inland flooding should also be incorporated as variables in a realistic study.

This exercise was very beneficial for understanding the impact of DEM accuracy on flood analysis.  It also helped me to understand the many assumptions we make when relying on elevation data and constant variables in complex analysis.