Nash, TX
Nash, TX's wildfire risk, in USFS's own numbers
Nash sits at the 65th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 1,804 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Nash's burn probability — fire likelihood with no building count factored in — sits at the 67th percentile nationally.
What "at risk" means for the buildings here
Most of Nash's buildings (55.9%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Nash ranks
Nash ranks lower within Texas (21st percentile statewide) than its 65th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Nash ranks 11,076 for wildfire risk (1 is highest) and 8,052 by building count (1 is largest). Within Texas alone, it ranks 1,419 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Shopping for coverage in Nash
At the 65th percentile nationally, Nash carries the 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.
Hardening a home in Nash
Nash's 55.9% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Nash's figures come from
Every one of the two percentiles behind Nash's 11,076-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Nash's dominant indirect exposure actually means, with real examples from across the dataset.