WildfireRiskFinder

Beverly, KS

Beverly wildfire risk explained

Elevated
44thpercentile nationally

USFS scores Beverly at the 44th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 164 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Beverly at the 40th national percentile — 4 points below its risk-to-structures score, a gap driven by how much is actually built there.

What "at risk" means for the buildings here

164Total buildings
22.6%Direct exposure
0%Indirect exposure
77.4%Minimal exposure

77.4% of Beverly's 164 buildings sit in USFS's Minimal exposure zone, with only 22.6% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.

How Beverly compares

Beverly's 44th national percentile looks worse in isolation than its 21st ranking inside Kansas does — this place is on the milder end for its own state, by 24 points. Among the 31,521 US communities USFS scores, Beverly ranks 17,514 for wildfire risk (1 is highest) and 26,249 by building count (1 is largest). Within Kansas alone, it ranks 572 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.

What this risk score means for insurance

Beverly's elevated rating (44th 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 Beverly

Beverly's 77.4% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.

Where Beverly's figures come from

Every one of the two percentiles behind Beverly's 17,514-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Beverly's dominant minimal exposure actually means, with real examples from across the dataset.