Susan SmithSusan Smith has worked as an editor and writer in the technology industry for over 16 years. As an editor she has been responsible for the launch of a number of technology trade publications, both in print and online. Currently, Susan is the Editor of GISCafe and AECCafe, as well as those sites’ newsletters and blogs. She writes on a number of topics, including but not limited to geospatial, architecture, engineering and construction. As many technologies evolve and occasionally merge, Susan finds herself uniquely situated to be able to cover diverse topics with facility.
« Less
Susan SmithSusan Smith has worked as an editor and writer in the technology industry for over 16 years. As an editor she has been responsible for the launch of a number of technology trade publications, both in print and online. Currently, Susan is the Editor of GISCafe and AECCafe, as well as those sites’
… More »
CoreLogic’s New Analysis on Flood and Wind Losses from Hurricane Florence
October 4th, 2018 by Susan Smith
David Smith, Senior Director of Model Development at CoreLogic, spoke with GISCafe Voice about the recent analysis of loss from flooding from Hurricane Florence released by CoreLogic.
CoreLogic analysis shows Hurricane Florence is estimated to have caused between $20 billion and $30 billion in flood and wind losses.
According to this new data analysis, flood loss for residential and commercial properties in North Carolina, South Carolina and Virginia is estimated to be between $19 billion and $28.5 billion which includes both storm surge and inland flooding. Specifically, uninsured flood loss for the same area is estimated to be between $13 billion and $18.5 billion. Wind losses are estimated to be an additional $1 billion to $1.5 billion.
- What percentage of loss from flooding is characteristically covered by insurance?
- The percentage of flood losses covered by insurance, whether through the NFIP (National Flood Insurance Program) or through private insurance, is typically low in major flood events, especially on the residential side. Our modeling indicates that about 85 percent of the residential flood losses in Florence will be uninsured. This is even greater than the estimated 70 percent of uninsured residential flood losses as a result of Hurricane Harvey last year.
- Will new areas be considerate for designated Special Flood Hazard Areas after this hurricane? How does that work?
- It’s possible that new areas could be considered for designated Special Flood Hazard Areas (SFHAs) after Hurricane Florence. FEMA is continually updating its flood maps and flood elevations, and major flood events in the past have raised the priority of such updates in the affected areas.
It’s important to recognize that the SFHAs are designed to identify areas that are subject to flooding with an annual probability of 1 percent or greater – sometimes described as a 100-year return period. Areas outside the SFHAs often flood in major events, in which we often see rainfall return periods well beyond 100 years.
- How does this flooding compare historically with past events in this location?
- Eastern North Carolina is no stranger to major floods, often caused by hurricanes and tropical storms. Nevertheless, the rainfall amounts, geographic extents and especially rates were beyond what we’ve seen over, at least, the last few decades. Wilmington, NC received about 22 inches of rain in a three-day period, more than in any event since at least 1980. The closest comparable events by this measure were Hurricanes Fran, Floyd and Ophelia in 1998, 1999, and 2005 respectively, and Tropical Storm Nicole in 2010. All of these storms had three-day rainfall amounts of approximately 15 to 20 inches in Wilmington.
- Will the areas that have been flooded by Florence be subject to higher scrutiny in the future and if so, what will that look like?
- As mentioned above, a likely result of Florence, in terms of FEMA’s response, is that the organization may raise its priority to update flood maps and elevations in affected areas.
- How do you calculate the reconstruction costs?
- RCV figures represent the cost to completely rebuild a property in case of damage, including labor and materials by geographic location, assuming the worst-case scenario at 100 percent destruction.
- Is PxPoint your proprietary geocoding engine?
- Yes, PxPoint is the proprietary structure- and parcel-level geocoding engine that CoreLogic uses, providing the highest level of location accuracy. Given a street address, PxPoint provides the centroid of the structure footprint for a large and expanding fraction of properties and the parcel centroid for nearly all other properties. This is far superior than traditional street geocoders, which often provide an estimated location along the street that can be relatively far from the actual building location. Accurate location is critical in modeling flood and storm surge.
- Do you have current data on damage from specifically wind damage and storm surge (separately)?
- Flood loss for residential and commercial properties in North Carolina, South Carolina and Virginia is estimated to be between $19 billion and $28.5 billion which includes both storm surge and inland flooding. Specifically, uninsured flood loss for the same area is estimated to be between $13 billion and $18.5 billion. Wind losses are estimated to be an additional $1 billion to $1.5 billion. The portion of the flood losses coming from storm surge is likely to be significant, perhaps 20 percent or more, with an even higher percentage of NFIP claims coming from storm surge due to the higher NFIP buy rates in coastal areas. The storm surge losses are not only on the barrier islands and immediate coastal areas, but also well into the large inlets behind the Outer Banks. For example, New Bern, NC, which is well up the Neuse River, had significant flooding driven by storm surge.
Related
Tags: data, geospatial, GIS, imagery, Infrastructure, intelligence, location, mapping, maps, NASA, NOAA, situational intelligence
Categories: analytics, cloud, CoreLogic, data, geospatial, GIS, government, location intelligence, NASA, spatial data
This entry was posted
on Thursday, October 4th, 2018 at 5:06 pm.
You can follow any responses to this entry through the RSS 2.0 feed.
You can leave a response, or trackback from your own site.