Acequia, ID
How exposed is Acequia to wildfire?
Out of every US place USFS scores, Acequia lands at the 66th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 110 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Acequia at the 63rd national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Acequia's buildings actually sit
Only 18.2% of Acequia's 110 buildings carry Direct exposure and 0% carry Indirect; the remaining 81.8% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Acequia against the rest of the country
Inside Idaho, Acequia sits at just the 32nd percentile even though it scores 66th 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, Acequia ranks 10,714 for wildfire risk (1 is highest) and 28,618 by building count (1 is largest). Within Idaho alone, it ranks 158 of 232 places by risk. See the full county-by-county picture for Idaho on its state page.
Acequia and the insurance market
Acequia's high rating (66th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Lowering exposure, not just insuring around it
With 81.8% of buildings rated Minimal exposure, Acequia gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Acequia's figures come from
The methodology guide shows exactly how USFS turned 110 counted buildings into the percentiles shown above for Acequia. The exposure-zones guide covers what Acequia's dominant minimal exposure actually means, with real examples from across the dataset.