Hilmar-Irwin, CA
Hilmar-Irwin, CA's wildfire risk, in USFS's own numbers
Hilmar-Irwin's 2,421 buildings earn a 61st-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 Hilmar-Irwin at the 60th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS classifies 83.8% of Hilmar-Irwin's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 16.2% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Hilmar-Irwin ranks
Hilmar-Irwin ranks lower within California (19th percentile statewide) than its 61st national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Hilmar-Irwin ranks 12,407 for wildfire risk (1 is highest) and 6,461 by building count (1 is largest). Within California alone, it ranks 1,273 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
Shopping for coverage in Hilmar-Irwin
Because Hilmar-Irwin is in California, a wildfire-hazard disclosure is legally required before a sale closes here — unusual nationally, since only these two states mandate it. The state's FAIR Plan alone carried 668,609 policies by the end of 2025. Full detail in the disclosure-law guide.
Lowering exposure, not just insuring around it
Hilmar-Irwin's 83.8% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Hilmar-Irwin's figures come from
Hilmar-Irwin's 61st-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Hilmar-Irwin's dominant minimal exposure actually means, with real examples from across the dataset.