CoreLogic® (NYSE: CLGX), a leading global property information, analytics and data-enabled solutions provider, today released data analysis showing 339,480 homes in Louisiana are at moderate-to-extreme risk of tropical storm-driven flash flood damage from Tropical Storm Barry. Within the likely impacted metropolitan and micropolitan areas of Louisiana, 32.6% of homes are located within a Special Flood Hazard Area (SFHA). Homeowners are required to purchase flood insurance in these designated areas when their mortgages are backed by the federal government. CoreLogic hydrological analysis of flash flood risk in the likely impacted areas estimates that 26% of the homes have moderate-to-extreme flash flood risk.
In this analysis, CoreLogic data includes only single-family residential properties likely to be impacted by a lower category storm. Based on the National Oceanic and Atmospheric Administration’s (NOAA) forecast, Tropical Storm Barry is expected to make landfall sometime Saturday as a strong tropical storm or a weak Category 1 hurricane. While Tropical Storm Barry has not intensified into a hurricane yet, the focus of this analysis is centered around the rainfall and flooding component, which is expected to be the largest contributor to property loss.
The area along the Mississippi River, where concern is highest, appears to be able to withstand the amount of flooding expected. After Hurricane Katrina, $14 billion of levee and pumping capability improvements were made along the river; this event is not expected to cause catastrophic problems given these enhancements.
The table below shows the total number of properties at risk of flash flood damage—from moderate to extreme—depending on storm size, rainfall and path.
Visit the CoreLogic natural hazard risk information center, Hazard HQ™, to get access to the most up-to-date Tropical Storm Barry data and see reports from previous storms.
The CoreLogic Flash Flood Risk Score (FFRS) uses watershed hydrology and then extracts hydrologic properties from land information datasets (such as land slope, land imperviousness, soil infiltration, vegetation, land depression, and other factors), incorporating probabilistic characteristics of meteorological factors to simulate precipitation impact. All aspects of flash flooding factors are finally integrated to form an overall projection of flash flood risk. The model can pinpoint granular locations with high risk potential for flash flooding anywhere in the United States. FFRS provides flooding detail in areas where flooding resources are traditionally unavailable. More specifically, FFRS helps assess whether a flash flood component is identified, particularly in areas where flood zones are not mapped. FFRS fills in the flood risk assessment gaps where the previous focus was only on riverine and coastal flooding, and no initial flood insurance studies were ever conducted.
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