Solvang, CA
Solvang, CA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Solvang at the 90th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 2,371 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Solvang's burn probability — fire likelihood with no building count factored in — sits at the 90th percentile nationally.
Solvang's building exposure, zone by zone
73.8% of Solvang's 2,371 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 26.2% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Where Solvang ranks
Solvang's 90th national percentile looks worse in isolation than its 61st ranking inside California does — this place is on the milder end for its own state, by 29 points. Among the 31,521 US communities USFS scores, Solvang ranks 3,207 for wildfire risk (1 is highest) and 6,567 by building count (1 is largest). Within California alone, it ranks 613 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
What this risk score means for insurance
Solvang sits in California, one of two states that legally require a wildfire-risk disclosure at sale. California's FAIR Plan, the state's insurer of last resort, ended 2025 with 668,609 residential policies after adding 21,859 in Q4 alone — the kind of market shift a 90th-percentile score like Solvang's can end up mattering for. More on the disclosure law.
Hardening a home in Solvang
With ember exposure the dominant pattern in Solvang (73.8% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Solvang's figures come from
The methodology guide shows exactly how USFS turned 2,371 counted buildings into the percentiles shown above for Solvang. The exposure-zones guide covers what Solvang's dominant indirect exposure actually means, with real examples from across the dataset.