Graham, TX
Graham wildfire risk explained
Graham's 5,019 buildings earn a 94th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Graham at the 94th percentile, close to its 94th-percentile risk score.
Graham's building exposure, zone by zone
5,019 buildings are counted in Graham, and 85.8% of them are Indirect exposure — ember-driven risk rather than the 14.3% in Direct exposure or the 0% rated Minimal. At 5,019 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
Where Graham ranks
Graham's risk sits at a similar level relative to Texas (94th percentile statewide) as it does nationally (94th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Graham ranks 1,775 for wildfire risk (1 is highest) and 3,421 by building count (1 is largest). Within Texas alone, it ranks 109 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Graham and the insurance market
At the 94th percentile nationally, Graham carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
Because 85.8% of Graham's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Graham's figures come from
Every one of the two percentiles behind Graham's 1,775-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Graham's dominant indirect exposure actually means, with real examples from across the dataset.