Flood Model
First Street Flood Model Export
The First Street Flood Model (FS-FM) is a nationwide probabilistic flood model that shows the risk of flooding at any location in the continental US, Puerto Rico, Hawaii, as well as most of Alaska due to rainfall (pluvial), riverine flooding (fluvial), and coastal surge flooding. In collaboration with more than 80 scientists, technologists, and experts, First Street has built on decades of peer-reviewed research and models from climatology, hydrology, and statistics to create an unprecedented flood model of the entire United States.
While other hydraulic and hydrologic models show refined risks of flooding in certain areas, this model provides complete coverage across the United States at 3-meter resolution. Existing flood models are built for individual municipalities and can rely on widely varying assumptions. The FS-FM provides a consistent and unified methodology across the entire country with continuous outputs. This extends into areas that have no previous flood modeling and even areas that do not have recorded hydrologic data. As a result, there is increased visibility into new regions of the entire country.
Additionally, flood models are typically only produced under existing conditions using historic environmental data as a representation for current risk. The FS-FM takes changing environmental factors into account by applying global climate model projections to forecast how flood risk will change over the next 30 years.
The FS-FM covers the contiguous United States, Hawaii, Puerto Rico and much of Alaska. The North Slope Borough was not modeled.
Version 4.2
Version 4.2 of the First Street Flood Model (FS-FM) extends the V3.0 methodological changes and use of CMIP6 climate models to Alaska, Hawaii, and Puerto Rico. This includes the recalculation of sea level rise and climate change factors in these areas based on the CMIP6 projections. Additionally, these areas have now been updated with new precipitation inputs with the expansion of the First Street Precipitation Model (FS-PM) into these states and territory. For all areas, including CONUS, the flood data also have been updated to fully capture changes to likelihoods of flooding at depth thresholds that were not updated with Version 3.1 in those locations where flood risk had changed in coastal areas.
View the methodology pages on https://firststreet.org/methodology/flood.
Data Dictionary
Properties do not appear in this table if they have no modeled exposure (Flood Factor = 1), are outside of the modeled area or have been excluded due to irregularities or artifacts.
The data table has a large number of columns with similar names. The field name is given below with a placeholder name to represent the variety of fields, refer the naming scheme for an explanation.
Location and Scores
place_id
text
0
First Street assigned unique identifier for a building or property
fsid
int
0
First Street ID (FSID) is a unique identifier assigned to each location (deprecated)
building_id
int
1
Building index, a zero-based counter for the buildings on the parcel. If null, statistics are based on the parcel centroid.
floodfactor
int
0
The property's legacy Flood Factor, a score ranging from 1-10 (where 1 = minimal and 10 = extreme) based on flooding exposure in the middle climate scenario. The score is based on the combination of depths across the range of modeled return periods in the current year and in 30 years. Flood depth is calculated at the lowest elevation of the largest building footprint or at the parcel centroid where no footprints exist.
floodfactor100_yYY
int
0
The property's Flood Factor, a score ranging from 1-100 (where 1 = minimal and 100 = extreme). Based on exposure in the current year.
flood_source
float
0
Indicator of primary source of flooding (1=pluvial, 3=fluvial, 4=fluvial and pluvial, 5=coastal, 6=coastal and pluvial, 8=coastal and fluvial, 9=coastal, fluvial and pluvial)
Depths
Depths are given in centimeters, with a minimum modeled depth of 5 cm.
For the depth columns, a value of zero should be interpreted as no modeled flooding within the model's minimum threshold, which is 5 cm. For chance columns, a value of zero should be interpreted as an annual probability less than 0.2%.
depth_rRRR_yYY
int
0
Flood mean depth at the given return period in the given year
depth_rRRR_yYY_max
int
0
Flood max depth at the given return period in the given year
Damages and Downtime
All costs are in today's dollars. The aal and repair columns will be null when the damageable column in the property export is 0 (false).
These fields are provided for return periods 2, 5, 20, 100, 200 and 500; years 0, 30 and 75, and percentiles: 10, 50 and 90. The 10th, 50th and 90th percentiles refer to ranges of internal repair costs depending on a structure's characteristics.
aal_yYY_pPP
int
1
Modeled annualized damage cost to the structure from flooding in the given year
repair_cost_rRRR_yYY_pPP
int
1
Modeled cost to repair flood damage in the given return period event and year
repair_days_rRRR_yYY_pPP
int
1
Modeled downtime to repair flood damage in the given return period event and year
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