Chaparrito, TX
Chaparrito, TX's wildfire risk, in USFS's own numbers
USFS scores Chaparrito at the 86th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 53 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Chaparrito at the 86th percentile, close to its 86th-percentile risk score.
Chaparrito's building exposure, zone by zone
Most of Chaparrito's buildings (96.2%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
How Chaparrito compares
Chaparrito's risk sits at a similar level relative to Texas (76th percentile statewide) as it does nationally (86th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Chaparrito ranks 4,332 for wildfire risk (1 is highest) and 30,860 by building count (1 is largest). Within Texas alone, it ranks 424 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
What this risk score means for insurance
Chaparrito's very high rating (86th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Hardening a home in Chaparrito
With ember exposure the dominant pattern in Chaparrito (96.2% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Chaparrito's figures come from
Chaparrito's 86th-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 Chaparrito's dominant indirect exposure actually means, with real examples from across the dataset.