WildfireRiskFinder

Mahtowa, MN

Mahtowa, MN's wildfire risk, in USFS's own numbers

Moderate
39thpercentile nationally

USFS's Wildfire Risk to Communities model puts Mahtowa at the 39th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 390 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Mahtowa's burn probability — fire likelihood with no building count factored in — sits at the 40th percentile nationally.

Mahtowa's building exposure, zone by zone

390Total buildings
95.1%Direct exposure
4.9%Indirect exposure
0%Minimal exposure

Of Mahtowa's 390 counted buildings, 95.1% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.

How Mahtowa compares

Mahtowa scores 39th nationally and 54th within Minnesota — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Mahtowa ranks 19,099 for wildfire risk (1 is highest) and 19,409 by building count (1 is largest). Within Minnesota alone, it ranks 426 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.

Shopping for coverage in Mahtowa

Mahtowa's moderate wildfire rating (39th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.

Lowering exposure, not just insuring around it

Because Direct exposure dominates in Mahtowa (95.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Mahtowa's figures come from

The methodology guide shows exactly how USFS turned 390 counted buildings into the percentiles shown above for Mahtowa. The exposure-zones guide covers what Mahtowa's dominant direct exposure actually means, with real examples from across the dataset.