WildfireRiskFinder

Brant Lake, SD

Brant Lake wildfire risk explained

Moderate
33rdpercentile nationally

Brant Lake's 65 buildings earn a 33rd-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Brant Lake's burn probability — fire likelihood with no building count factored in — sits at the 30th percentile nationally.

Brant Lake's building exposure, zone by zone

65Total buildings
50.8%Direct exposure
0%Indirect exposure
49.2%Minimal exposure

Of Brant Lake's 65 counted buildings, 50.8% carry Direct exposure and only 49.2% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.

How Brant Lake compares

Brant Lake ranks lower within South Dakota (6th percentile statewide) than its 33rd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Brant Lake ranks 21,253 for wildfire risk (1 is highest) and 30,481 by building count (1 is largest). Within South Dakota alone, it ranks 414 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.

Shopping for coverage in Brant Lake

At the 33rd national percentile, Brant Lake rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.

Hardening a home in Brant Lake

Because Direct exposure dominates in Brant Lake (50.8%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Brant Lake's figures come from

Every one of the two percentiles behind Brant Lake's 21,253-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Brant Lake's dominant direct exposure actually means, with real examples from across the dataset.