Lake Hopatcong, NJ
How exposed is Lake Hopatcong to wildfire?
USFS's Wildfire Risk to Communities model puts Lake Hopatcong at the 40th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 4,733 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Lake Hopatcong's burn probability — fire likelihood with no building count factored in — sits at the 38th percentile nationally.
Where Lake Hopatcong's buildings actually sit
Direct exposure dominates in Lake Hopatcong: 70% of its 4,733 buildings, versus 25.7% Indirect and 4.3% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Lake Hopatcong against the rest of the country
Lake Hopatcong scores 40th nationally and 43rd 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, Lake Hopatcong ranks 18,910 for wildfire risk (1 is highest) and 3,607 by building count (1 is largest). Within New Jersey alone, it ranks 397 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
Lake Hopatcong and the insurance market
At the 40th national percentile, Lake Hopatcong rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
With 70% of Lake Hopatcong in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Lake Hopatcong's figures come from
The methodology guide shows exactly how USFS turned 4,733 counted buildings into the percentiles shown above for Lake Hopatcong. The exposure-zones guide covers what Lake Hopatcong's dominant direct exposure actually means, with real examples from across the dataset.