WildfireRiskFinder

Putnam Lake, NY

Putnam Lake wildfire risk explained

Elevated
44thpercentile nationally

Putnam Lake's 1,613 buildings earn a 44th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Putnam Lake at the 42nd percentile, close to its 44th-percentile risk score.

Where Putnam Lake's buildings actually sit

1,613Total buildings
51.2%Direct exposure
48.1%Indirect exposure
0.7%Minimal exposure

1,613 buildings are counted in Putnam Lake, and 51.2% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0.7% rated Minimal.

Where Putnam Lake ranks

Compare Putnam Lake's two percentiles: 89th within New York, only 44th nationally — a gap of 45 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Putnam Lake ranks 17,619 for wildfire risk (1 is highest) and 8,720 by building count (1 is largest). Within New York alone, it ranks 141 of 1,289 places by risk. See the full county-by-county picture for New York on its state page.

What this risk score means for insurance

Putnam Lake's elevated rating (44th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Hardening a home in Putnam Lake

Putnam Lake's 51.2% 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 Putnam Lake's figures come from

Putnam Lake's 44th-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 Putnam Lake's dominant direct exposure actually means, with real examples from across the dataset.