WildfireRiskFinder

Nathrop, CO

How exposed is Nathrop to wildfire?

High
70thpercentile nationally

USFS's Wildfire Risk to Communities model puts Nathrop at the 70th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 252 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Nathrop's burn probability — fire likelihood with no building count factored in — sits at the 63rd percentile nationally.

Where Nathrop's buildings actually sit

252Total buildings
29%Direct exposure
71%Indirect exposure
0%Minimal exposure

Indirect exposure is dominant in Nathrop (71% of 252 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 29% sit in the Direct zone.

How Nathrop compares

Nathrop's 70th national percentile looks worse in isolation than its 37th ranking inside Colorado does — this place is on the milder end for its own state, by 33 points. Among the 31,521 US communities USFS scores, Nathrop ranks 9,539 for wildfire risk (1 is highest) and 23,068 by building count (1 is largest). Within Colorado alone, it ranks 299 of 472 places by risk. See the full county-by-county picture for Colorado on its state page.

Nathrop and the insurance market

Nathrop's high rating (70th 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

Because 71% of Nathrop'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 Nathrop's figures come from

Nathrop's 70th-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 Nathrop's dominant indirect exposure actually means, with real examples from across the dataset.