Tres Arroyos, NM
Tres Arroyos wildfire risk explained
USFS's Wildfire Risk to Communities model puts Tres Arroyos at the 79th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 1,099 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Tres Arroyos at the 73rd percentile, close to its 79th-percentile risk score.
Tres Arroyos's building exposure, zone by zone
Direct exposure dominates in Tres Arroyos: 90.9% of its 1,099 buildings, versus 9.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How Tres Arroyos compares
Tres Arroyos ranks lower within New Mexico (50th percentile statewide) than its 79th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Tres Arroyos ranks 6,778 for wildfire risk (1 is highest) and 11,278 by building count (1 is largest). Within New Mexico alone, it ranks 245 of 495 places by risk. See the full county-by-county picture for New Mexico on its state page.
Tres Arroyos and the insurance market
At the 79th percentile nationally, Tres Arroyos carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
Because Direct exposure dominates in Tres Arroyos (90.9%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Tres Arroyos's figures come from
The methodology guide shows exactly how USFS turned 1,099 counted buildings into the percentiles shown above for Tres Arroyos. The exposure-zones guide covers what Tres Arroyos's dominant direct exposure actually means, with real examples from across the dataset.