Orchard, TX
Orchard wildfire risk explained
USFS's Wildfire Risk to Communities model puts Orchard at the 75th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 229 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Orchard at the 77th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Orchard's building exposure, zone by zone
68.6% of Orchard's 229 buildings sit in USFS's Direct exposure zone, roughly 157 structures close enough to burnable vegetation for flame contact, not just embers — 31.4% fall in the Indirect, ember-only zone and 0% are Minimal.
How Orchard compares
Inside Texas, Orchard sits at just the 45th percentile even though it scores 75th 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, Orchard ranks 8,018 for wildfire risk (1 is highest) and 23,838 by building count (1 is largest). Within Texas alone, it ranks 984 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Orchard and the insurance market
Orchard's 75th-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.
Hardening a home in Orchard
Orchard's 68.6% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Orchard's figures come from
The methodology guide shows exactly how USFS turned 229 counted buildings into the percentiles shown above for Orchard. The exposure-zones guide covers what Orchard's dominant direct exposure actually means, with real examples from across the dataset.