WildfireRiskFinder

Bryant, WA

Bryant, WA's wildfire risk, in USFS's own numbers

Moderate
23rdpercentile nationally

USFS scores Bryant at the 23rd national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 1,295 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Bryant at the 23rd percentile, close to its 23rd-percentile risk score.

Where Bryant's buildings actually sit

1,295Total buildings
88%Direct exposure
12.1%Indirect exposure
0%Minimal exposure

88% of Bryant's 1,295 buildings sit in USFS's Direct exposure zone, roughly 1,139 structures close enough to burnable vegetation for flame contact, not just embers — 12.1% fall in the Indirect, ember-only zone and 0% are Minimal.

Where Bryant ranks

Bryant's risk sits at a similar level relative to Washington (37th percentile statewide) as it does nationally (23rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Bryant ranks 24,313 for wildfire risk (1 is highest) and 10,099 by building count (1 is largest). Within Washington alone, it ranks 395 of 628 places by risk. See the full county-by-county picture for Washington on its state page.

Bryant and the insurance market

Bryant's moderate rating (23rd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Hardening a home in Bryant

Because Direct exposure dominates in Bryant (88%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Bryant's figures come from

The methodology guide shows exactly how USFS turned 1,295 counted buildings into the percentiles shown above for Bryant. The exposure-zones guide covers what Bryant's dominant direct exposure actually means, with real examples from across the dataset.