First Street Foundation's probabilistic Flood Model uses data from government agencies including NOAA, NASA, and USGS to determine property Flood Factors. Search your home on Risk Factor to understand your risk.
The data behind Flood Factor
The First Street Foundation Flood Model is a nationwide, probabilistic flood model that shows any location’s risk of flooding from rain, rivers, tides, and storm surge. The Flood Model is built off of decades of peer-reviewed research and forecasts how flood risks will change over time due to changes in the environment.
Flood Factors are derived entirely from the outputs of this probabilistic Flood Model. While the Flood Model includes things like recreations of historic flood events, these are not used in the determination of a Flood Factor®. Reports of past flooding are a validation source for the model, and probabilistic flow estimates are based in part on historic observations of river flows, tide levels, and rainfall. However, these records do not directly influence a property’s Flood Factor.
Types of data sources used
Flood Factor takes a variety of public data sources into consideration including hydrologic, climate, and adaptation data sources.
Hydrologic data sources
Flood Factor considers a location’s risk of flooding from high-intensity rainfall, overflowing rivers and streams, high tides, and coastal storm surges.
- USGS river gauge discharge values
- USGS river water levels
- NOAA Atlas 14 Rainfall Intensity-Duration-Frequency data
- Land cover and impervious surfaces
- NOAA tide gauge water level
- The National Elevation Dataset (NED) is managed by the United States Geological Survey (USGS)
- Individual county digital elevation model (DEM)
- USGS NHDPlus database
Climate data sources
An essential trademark of Risk Factor™ is the inclusion of environmental changes that impact flood risks, such as sea level rise and precipitation patterns, The Flood Model analyzes multiple environmental possibilities under the RCP 4.5 carbon emissions scenario with high and low uncertainty bounds, using 1980-2010 as a baseline period
- CMIP GCMIP5 Global Climate Models (GCMs) using Representative Concentration Pathway 4.5
- NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP)
Adaptation data sources
The purpose of adding flood adaptation structures to the modeling process is to increase the accuracy of the flood inundation layers giving a complete picture of what structures exist to alleviate flooding such as levees and dams.
- United States Army Corps of Engineers National Levee Database
- State, County, and Municipal level GIS databases
- Coastal Zone Management Authorities
- American Society of Adaptation Professionals (ASAP)
- News reports
- Public project plans
- Local and state officials such as floodplain managers
Other data sources available
The First Street Foundation Flood Model has developed a method to recreate historic flooding events. The model has been used to recreate riverine flooding events as well as the flooding associated with hurricanes, tropical storms, and nor’easters. To create the catalog of events, First Street relied on hydrologic models and public data sources detailing the impacts of flooding. While these sources are useful to provide a holistic picture, they do not influence a property’s Flood Factor.
Hurricane Data Sources
- NOAA International Best Track Archive for Climate Stewardship (IBTrACS) historic hurricane track database
- Synthetic hurricane tracks created by Dr. Kerry Emmanuel
- Post-hurricane LiDAR collection runs by the National Oceanic and Atmospheric Administration (NOAA)
Historic Recreation Data Sources
- NOAA Storm events database
- FEMA National Flood Insurance Program (NFIP) claims data
- FEMA Individual Assistance (IA) flood claims data
- Small Business Administration (SBA) flood claims data
- USGS High Water Mark data
- Remotely sensed data (LIDAR)
Press Coverage
Wall Street Journal: Is Your Home at Risk of Flooding? The Data Is Hard to Find
The Washington Post: Millions of homeowners face flood risks without realizing it, and climate change is making it worse