Walnut, KS
Walnut, KS's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Walnut lands at the 52nd percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 176 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Walnut at the 52nd national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Walnut's buildings actually sit
USFS classifies 60.2% of Walnut's buildings as Direct exposure, higher than its 0% Indirect share and far above its 39.8% Minimal share — a profile where 106 structures sit close enough to vegetation that lot clearing matters most.
Where Walnut ranks
Walnut ranks lower within Kansas (35th percentile statewide) than its 52nd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Walnut ranks 15,247 for wildfire risk (1 is highest) and 25,779 by building count (1 is largest). Within Kansas alone, it ranks 469 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
What this risk score means for insurance
At the 52nd national percentile, Walnut rates elevated 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
Walnut's 60.2% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Walnut's figures come from
Every one of the two percentiles behind Walnut's 15,247-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Walnut's dominant direct exposure actually means, with real examples from across the dataset.