Waterloo, SC
Waterloo wildfire risk explained
USFS's Wildfire Risk to Communities model puts Waterloo at the 67th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 188 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Waterloo at the 70th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Waterloo's buildings actually sit
Of Waterloo's 188 counted buildings, 100% 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.
Where Waterloo ranks
Waterloo ranks lower within South Carolina (44th percentile statewide) than its 67th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Waterloo ranks 10,380 for wildfire risk (1 is highest) and 25,333 by building count (1 is largest). Within South Carolina alone, it ranks 265 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.
What this risk score means for insurance
At the 67th percentile nationally, Waterloo carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Waterloo (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Waterloo's figures come from
Waterloo's 67th-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 Waterloo's dominant direct exposure actually means, with real examples from across the dataset.