Fairchild, WI
Fairchild wildfire risk explained
Fairchild sits at the 31st percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 385 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Fairchild at the 30th percentile, close to its 31st-percentile risk score.
What "at risk" means for the buildings here
Of Fairchild's 385 counted buildings, 72% carry Direct exposure and only 25.7% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
How Fairchild compares
Within Wisconsin, Fairchild ranks higher (66th percentile) than it does nationally (31st) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Fairchild ranks 21,922 for wildfire risk (1 is highest) and 19,535 by building count (1 is largest). Within Wisconsin alone, it ranks 277 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
Fairchild and the insurance market
Fairchild's moderate wildfire rating (31st 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.
Hardening a home in Fairchild
Fairchild's 72% 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 Fairchild's figures come from
Every one of the two percentiles behind Fairchild's 21,922-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Fairchild's dominant direct exposure actually means, with real examples from across the dataset.