Watergate, FL
Watergate, FL's wildfire risk, in USFS's own numbers
Watergate's 1,131 buildings earn a 66th-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 Watergate at the 72nd national percentile — 6 points above its risk-to-structures score, a gap driven by how much is actually built there.
Watergate's building exposure, zone by zone
Watergate rates 97.4% Minimal exposure against just 2.7% Direct and 0% Indirect — of 1,131 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Where Watergate ranks
Inside Florida, Watergate sits at just the 21st percentile even though it scores 66th 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, Watergate ranks 10,798 for wildfire risk (1 is highest) and 11,072 by building count (1 is largest). Within Florida alone, it ranks 757 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
Watergate and the insurance market
Watergate's 66th-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
Watergate's 97.4% 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 Watergate's figures come from
Every one of the two percentiles behind Watergate's 10,798-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Watergate's dominant minimal exposure actually means, with real examples from across the dataset.