Winona Lake, IN
Winona Lake wildfire risk explained
USFS's Wildfire Risk to Communities model puts Winona Lake at the 8th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 1,725 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Winona Lake at the 8th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Winona Lake's buildings actually sit
70% of Winona Lake's 1,725 buildings sit in USFS's Minimal exposure zone, with only 30% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Winona Lake against the rest of the country
Compare Winona Lake's two percentiles: 49th within Indiana, only 8th nationally — a gap of 41 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Winona Lake ranks 29,055 for wildfire risk (1 is highest) and 8,318 by building count (1 is largest). Within Indiana alone, it ranks 499 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Shopping for coverage in Winona Lake
At the 8th national percentile, Winona Lake rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Even with 70% of Winona Lake outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Winona Lake's figures come from
Every one of the two percentiles behind Winona Lake's 29,055-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Winona Lake's dominant minimal exposure actually means, with real examples from across the dataset.