Nashua, IA
How exposed is Nashua to wildfire?
Out of every US place USFS scores, Nashua lands at the 36th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 1,073 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Nashua at the 36th percentile, close to its 36th-percentile risk score.
What "at risk" means for the buildings here
Most of Nashua's buildings (78.8%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
How Nashua compares
There's little gap between Nashua's 36th national percentile and its 51st percentile inside Iowa, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Nashua ranks 20,195 for wildfire risk (1 is highest) and 11,442 by building count (1 is largest). Within Iowa alone, it ranks 499 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Nashua
At the 36th national percentile, Nashua rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Because 78.8% of Nashua'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 Nashua's figures come from
Nashua's 36th-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 Nashua's dominant indirect exposure actually means, with real examples from across the dataset.