Morrilton, AR
Morrilton wildfire risk explained
Out of every US place USFS scores, Morrilton lands at the 71st percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 3,568 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Morrilton at the 75th national percentile — 4 points above its risk-to-structures score, a gap driven by how much is actually built there.
Morrilton's building exposure, zone by zone
3,568 buildings are counted in Morrilton, and 62.7% of them are Indirect exposure — ember-driven risk rather than the 30.8% in Direct exposure or the 6.5% rated Minimal.
Where Morrilton ranks
Morrilton scores 71st nationally and 57th within Arkansas — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Morrilton ranks 9,159 for wildfire risk (1 is highest) and 4,693 by building count (1 is largest). Within Arkansas alone, it ranks 267 of 614 places by risk. See the full county-by-county picture for Arkansas on its state page.
What this risk score means for insurance
Morrilton's 71st-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
Morrilton's 62.7% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Morrilton's figures come from
The methodology guide shows exactly how USFS turned 3,568 counted buildings into the percentiles shown above for Morrilton. The exposure-zones guide covers what Morrilton's dominant indirect exposure actually means, with real examples from across the dataset.