WildfireRiskFinder

Watha, NC

Watha wildfire risk explained

High
76thpercentile nationally

Watha's 201 buildings earn a 76th-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.)

Separately from the risk score above, Watha's burn probability — fire likelihood with no building count factored in — sits at the 74th percentile nationally.

Where Watha's buildings actually sit

201Total buildings
92.5%Direct exposure
7.5%Indirect exposure
0%Minimal exposure

Direct exposure dominates in Watha: 92.5% of its 201 buildings, versus 7.5% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.

Where Watha ranks

Watha's risk sits at a similar level relative to North Carolina (78th percentile statewide) as it does nationally (76th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Watha ranks 7,693 for wildfire risk (1 is highest) and 24,809 by building count (1 is largest). Within North Carolina alone, it ranks 172 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.

What this risk score means for insurance

Watha's 76th-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.

What would actually reduce this score

Because Direct exposure dominates in Watha (92.5%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Watha's figures come from

The methodology guide shows exactly how USFS turned 201 counted buildings into the percentiles shown above for Watha. The exposure-zones guide covers what Watha's dominant direct exposure actually means, with real examples from across the dataset.