Wathena, KS
Wathena, KS's wildfire risk, in USFS's own numbers
USFS scores Wathena at the 59th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 914 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Wathena's burn probability — fire likelihood with no building count factored in — sits at the 58th percentile nationally.
Wathena's building exposure, zone by zone
Most of Wathena's buildings (74.3%) 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.
Wathena against the rest of the country
Wathena's risk sits at a similar level relative to Kansas (50th percentile statewide) as it does nationally (59th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Wathena ranks 13,080 for wildfire risk (1 is highest) and 12,603 by building count (1 is largest). Within Kansas alone, it ranks 362 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
Shopping for coverage in Wathena
Wathena's elevated wildfire rating (59th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
Because 74.3% of Wathena'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 Wathena's figures come from
The methodology guide shows exactly how USFS turned 914 counted buildings into the percentiles shown above for Wathena. The exposure-zones guide covers what Wathena's dominant indirect exposure actually means, with real examples from across the dataset.