WildfireRiskFinder

Duncombe, IA

Duncombe wildfire risk explained

Low
2ndpercentile nationally

Out of every US place USFS scores, Duncombe lands at the 2nd percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 295 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 Duncombe at the 2nd percentile, close to its 2nd-percentile risk score.

Duncombe's building exposure, zone by zone

295Total buildings
13.6%Direct exposure
0%Indirect exposure
86.4%Minimal exposure

Duncombe rates 86.4% Minimal exposure against just 13.6% Direct and 0% Indirect — of 295 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.

How Duncombe compares

Duncombe's risk sits at a similar level relative to Iowa (3rd percentile statewide) as it does nationally (2nd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Duncombe ranks 30,798 for wildfire risk (1 is highest) and 21,754 by building count (1 is largest). Within Iowa alone, it ranks 983 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.

Shopping for coverage in Duncombe

At the 2nd national percentile, Duncombe rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.

What would actually reduce this score

Duncombe's 86.4% 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 Duncombe's figures come from

Duncombe's 2nd-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 Duncombe's dominant minimal exposure actually means, with real examples from across the dataset.