Terlingua, TX
Terlingua wildfire risk explained
Out of every US place USFS scores, Terlingua lands at the 56th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 169 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Terlingua at the 55th percentile, close to its 56th-percentile risk score.
Where Terlingua's buildings actually sit
Most of Terlingua's buildings (59.2%) 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.
How Terlingua compares
Terlingua ranks lower within Texas (11th percentile statewide) than its 56th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Terlingua ranks 13,755 for wildfire risk (1 is highest) and 26,086 by building count (1 is largest). Within Texas alone, it ranks 1,599 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Terlingua and the insurance market
Terlingua's elevated wildfire rating (56th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Hardening a home in Terlingua
With ember exposure the dominant pattern in Terlingua (59.2% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Terlingua's figures come from
Terlingua's 56th-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 Terlingua's dominant indirect exposure actually means, with real examples from across the dataset.