Waterloo, AL
Waterloo, AL's wildfire risk, in USFS's own numbers
USFS scores Waterloo at the 69th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 268 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Waterloo's burn probability — fire likelihood with no building count factored in — sits at the 71st percentile nationally.
Where Waterloo's buildings actually sit
Direct exposure dominates in Waterloo: 64.6% of its 268 buildings, versus 35.1% Indirect and 0.4% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How Waterloo compares
Inside Alabama, Waterloo sits at just the 43rd percentile even though it scores 69th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Waterloo ranks 9,918 for wildfire risk (1 is highest) and 22,554 by building count (1 is largest). Within Alabama alone, it ranks 341 of 592 places by risk. See the full county-by-county picture for Alabama on its state page.
What this risk score means for insurance
Waterloo's high rating (69th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
With 64.6% of Waterloo in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Waterloo's figures come from
Every one of the two percentiles behind Waterloo's 9,918-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Waterloo's dominant direct exposure actually means, with real examples from across the dataset.