K-Bar Ranch, TX
How exposed is K-Bar Ranch to wildfire?
K-Bar Ranch's 277 buildings earn a 78th-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks K-Bar Ranch at the 78th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
K-Bar Ranch's building exposure, zone by zone
USFS classifies 98.6% of K-Bar Ranch's buildings as Direct exposure, higher than its 1.4% Indirect share and far above its 0% Minimal share — a profile where 273 structures sit close enough to vegetation that lot clearing matters most.
How K-Bar Ranch compares
Inside Texas, K-Bar Ranch sits at just the 56th percentile even though it scores 78th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, K-Bar Ranch ranks 6,950 for wildfire risk (1 is highest) and 22,305 by building count (1 is largest). Within Texas alone, it ranks 796 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Shopping for coverage in K-Bar Ranch
K-Bar Ranch's 78th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in K-Bar Ranch (98.6%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where K-Bar Ranch's figures come from
The methodology guide shows exactly how USFS turned 277 counted buildings into the percentiles shown above for K-Bar Ranch. The exposure-zones guide covers what K-Bar Ranch's dominant direct exposure actually means, with real examples from across the dataset.