Dell Rapids, SD
How exposed is Dell Rapids to wildfire?
Out of every US place USFS scores, Dell Rapids lands at the 37th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 1,743 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Dell Rapids at the 36th percentile, close to its 37th-percentile risk score.
What "at risk" means for the buildings here
Dell Rapids rates 81.7% Minimal exposure against just 18.3% Direct and 0% Indirect — of 1,743 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
How Dell Rapids compares
Dell Rapids ranks lower within South Dakota (10th percentile statewide) than its 37th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Dell Rapids ranks 19,997 for wildfire risk (1 is highest) and 8,256 by building count (1 is largest). Within South Dakota alone, it ranks 396 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.
Dell Rapids and the insurance market
Dell Rapids's moderate wildfire rating (37th 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.
Hardening a home in Dell Rapids
Dell Rapids's 81.7% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Dell Rapids's figures come from
Dell Rapids's 37th-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 Dell Rapids's dominant minimal exposure actually means, with real examples from across the dataset.