Halchita, UT
Halchita wildfire risk explained
USFS scores Halchita at the 49th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 116 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Halchita at the 43rd national percentile — 6 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Halchita's buildings actually sit
Of Halchita's 116 counted buildings, 100% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Halchita against the rest of the country
Inside Utah, Halchita sits at just the 8th percentile even though it scores 49th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Halchita ranks 16,184 for wildfire risk (1 is highest) and 28,390 by building count (1 is largest). Within Utah alone, it ranks 298 of 326 places by risk. See the full county-by-county picture for Utah on its state page.
Shopping for coverage in Halchita
Halchita's elevated wildfire rating (49th 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.
Lowering exposure, not just insuring around it
With 100% of Halchita in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Halchita's figures come from
The methodology guide shows exactly how USFS turned 116 counted buildings into the percentiles shown above for Halchita. The exposure-zones guide covers what Halchita's dominant direct exposure actually means, with real examples from across the dataset.