Expected yearly inland flood loss
The damage flooding from rivers and heavy rain is expected to do to buildings in an average year, in dollars for every $100,000 that the buildings are worth. Flooding from the sea is not included. FEMA works it out from flood maps and the floods recorded since 1996.
Reported for3,144areas, in 51 states — none in PR
Link to density0.08not mostly about how urban a place is
Nearby places alike0.55Moran’s I: strongly, neighbouring places tend to be similar
Typerate$ per $100,000 of buildings
How it has moved
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Every state, every year
One row per state and one column per year, sorted by the latest value. It shows states, not counties: nobody can scan 3,222 rows, and the pattern only shows when it all fits on one screen.
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Where it comes from
FEMA National Risk Index · FEMA National Risk Index v1.20, NRI_Table_Counties / NRI_Table_States, IFLD_ALRB
Expected yearly damage to buildings from rivers overflowing and heavy rain. A rate over the area's building value. FEMA publishes it for counties and states; it is not rebuilt for other areas here.
Combining areas: it cannot be combined, so it is shown only where its publisher works it out.
What it goes with
The strongest links that have a page of their own. Unadjusted is the link before adjusting for anything, from −1 (opposite) to +1 (in step). Adjusted compares places with the same population density, income and education levels, so those differences can’t explain the link. This list leaves out the 1 pairs built from the same numbers or the same model as this measure, since they are bound to match.
| Measure | Unadjusted | Adjusted |
|---|---|---|
| Expected yearly inland flood loss and Land surface form (flat to mountainous)Where Expected yearly inland flood loss is higher, Land surface form (flat to mountainous) tends to be higher: a moderate link that holds when only places with similar density, income and education are compared, and inside states as well. Land surface form (flat to mountainous) by US county | +0.46 | +0.46 |
| Expected yearly inland flood loss and Drug overdose deathsWhere Expected yearly inland flood loss is higher, Drug overdose deaths tends to be higher: a weak link that holds when only places with similar density, income and education are compared, and inside states as well. Drug overdose deaths by US county | +0.35 | +0.34 |
Population makeup
How this measure varies with the racial and ethnic makeup of counties. Every group is shown, whatever its rank. These are links across counties: they describe places, not people. They say nothing about any person’s risk or behaviour based on their race. Counties with a larger share of one group also differ in much else, such as income, segregation, region and history. The adjusted figure only accounts for density, income and education.
| Share of residents | Unadjusted | Adjusted |
|---|---|---|
| Expected yearly inland flood loss and Share White, not HispanicWhere Expected yearly inland flood loss is higher, Share White, not Hispanic tends to be higher: a weak link that holds when only places with similar density, income and education are compared, and inside states as well. Share White, not Hispanic by US county | +0.19 | +0.20 |
| Expected yearly inland flood loss and Share Black, not HispanicWhere Expected yearly inland flood loss is higher, Share Black, not Hispanic tends to be lower: a weak link that holds when only places with similar density, income and education are compared, and inside states as well. Share Black, not Hispanic by US county | -0.19 | -0.23 |
| Expected yearly inland flood loss and Share Hispanic or Latino, any raceCould easily be chance once only places with similar density, income and education are compared. Share Hispanic or Latino, any race by US county | -0.05 | -0.04 |
| Expected yearly inland flood loss and Share Asian, not HispanicCould easily be chance once only places with similar density, income and education are compared. Share Asian, not Hispanic by US county | -0.02 | +0.09 |
| Expected yearly inland flood loss and Share American Indian or Alaska Native, not HispanicCould easily be chance once only places with similar density, income and education are compared. Share American Indian or Alaska Native, not Hispanic by US county | -0.04 | -0.09 |
Highest and lowest
Of 3,144 counties reporting it. These are the two ends of a national ranking. For most measures, that ranking mostly sorts places by income and how urban they are. That is why the place pages compare each place with similar places instead.
Highest
- Floyd County, KY — 651
- Wetzel County, WV — 476
- Martin County, KY — 458
- Hawaii County, HI — 444
- Wyoming County, WV — 428
The middle area reports 81.8. The middle half of counties falls between 63.2 and 108 (the 25th to 75th percentile).
US Counties With the Highest Expected Yearly Inland Flood Loss · US Counties With the Lowest Expected Yearly Inland Flood Loss
All measures · Explore its pairs · How the US county data works