Knowles, OK
Knowles, OK's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Knowles at the 95th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 34 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Knowles's burn probability — fire likelihood with no building count factored in — sits at the 96th percentile nationally.
What "at risk" means for the buildings here
Direct exposure dominates in Knowles: 58.8% of its 34 buildings, versus 41.2% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Knowles against the rest of the country
Knowles's risk sits at a similar level relative to Oklahoma (80th percentile statewide) as it does nationally (95th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Knowles ranks 1,523 for wildfire risk (1 is highest) and 31,299 by building count (1 is largest). Within Oklahoma alone, it ranks 167 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
What this risk score means for insurance
Knowles's 95th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Knowles
Because Direct exposure dominates in Knowles (58.8%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Knowles's figures come from
Knowles's 95th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Knowles's dominant direct exposure actually means, with real examples from across the dataset.