Moorhead, IA
Moorhead, IA's wildfire risk, in USFS's own numbers
USFS scores Moorhead at the 76th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 194 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Moorhead at the 76th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS puts 70.6% of Moorhead's 194 buildings in the Indirect exposure zone, versus 29.4% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How Moorhead compares
Within Iowa, Moorhead ranks higher (98th percentile) than it does nationally (76th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Moorhead ranks 7,689 for wildfire risk (1 is highest) and 25,071 by building count (1 is largest). Within Iowa alone, it ranks 24 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Moorhead and the insurance market
Moorhead's 76th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Because 70.6% of Moorhead'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 Moorhead's figures come from
The methodology guide shows exactly how USFS turned 194 counted buildings into the percentiles shown above for Moorhead. The exposure-zones guide covers what Moorhead's dominant indirect exposure actually means, with real examples from across the dataset.