Rio Grande, NJ
Rio Grande wildfire risk explained
Rio Grande's 1,800 buildings earn a 68th-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 Rio Grande at the 63rd national percentile — 5 points below its risk-to-structures score, a gap driven by how much is actually built there.
Rio Grande's building exposure, zone by zone
78.9% of Rio Grande's 1,800 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 21.1% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Where Rio Grande ranks
Rio Grande scores 68th nationally and 78th within New Jersey — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Rio Grande ranks 10,121 for wildfire risk (1 is highest) and 8,060 by building count (1 is largest). Within New Jersey alone, it ranks 154 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
Rio Grande and the insurance market
Rio Grande's 68th-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.
What would actually reduce this score
With ember exposure the dominant pattern in Rio Grande (78.9% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Rio Grande's figures come from
The methodology guide shows exactly how USFS turned 1,800 counted buildings into the percentiles shown above for Rio Grande. The exposure-zones guide covers what Rio Grande's dominant indirect exposure actually means, with real examples from across the dataset.