WildfireRiskFinder

Beulah, ND

Beulah, ND's wildfire risk, in USFS's own numbers

Elevated
59thpercentile nationally

Beulah's 1,935 buildings earn a 59th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Beulah at the 57th percentile, close to its 59th-percentile risk score.

What "at risk" means for the buildings here

1,935Total buildings
19.1%Direct exposure
60.1%Indirect exposure
20.9%Minimal exposure

Indirect exposure is dominant in Beulah (60.1% of 1,935 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 19.1% sit in the Direct zone.

Beulah against the rest of the country

Beulah scores 59th nationally and 72nd within North Dakota — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Beulah ranks 12,898 for wildfire risk (1 is highest) and 7,664 by building count (1 is largest). Within North Dakota alone, it ranks 113 of 402 places by risk. See the full county-by-county picture for North Dakota on its state page.

Beulah and the insurance market

Beulah's elevated rating (59th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

What would actually reduce this score

Because 60.1% of Beulah'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 Beulah's figures come from

The methodology guide shows exactly how USFS turned 1,935 counted buildings into the percentiles shown above for Beulah. The exposure-zones guide covers what Beulah's dominant indirect exposure actually means, with real examples from across the dataset.