Wahpeton, ND
Wahpeton, ND's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Wahpeton at the 34th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 3,420 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Wahpeton at the 32nd percentile, close to its 34th-percentile risk score.
Where Wahpeton's buildings actually sit
Only 5% of Wahpeton's 3,420 buildings carry Direct exposure and 0% carry Indirect; the remaining 95% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Where Wahpeton ranks
Inside North Dakota, Wahpeton sits at just the 15th percentile even though it scores 34th 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, Wahpeton ranks 20,865 for wildfire risk (1 is highest) and 4,885 by building count (1 is largest). Within North Dakota alone, it ranks 341 of 402 places by risk. See the full county-by-county picture for North Dakota on its state page.
What this risk score means for insurance
Wahpeton's moderate rating (34th 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
With 95% of buildings rated Minimal exposure, Wahpeton gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Wahpeton's figures come from
Every one of the two percentiles behind Wahpeton's 20,865-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Wahpeton's dominant minimal exposure actually means, with real examples from across the dataset.