WildfireRiskFinder

Volga, IA

Volga wildfire risk explained

Moderate
35thpercentile nationally

Volga sits at the 35th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 200 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Volga at the 36th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.

Where Volga's buildings actually sit

200Total buildings
40%Direct exposure
60%Indirect exposure
0%Minimal exposure

200 buildings are counted in Volga, and 60% of them are Indirect exposure — ember-driven risk rather than the 40% in Direct exposure or the 0% rated Minimal.

How Volga compares

Volga's risk sits at a similar level relative to Iowa (50th percentile statewide) as it does nationally (35th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Volga ranks 20,512 for wildfire risk (1 is highest) and 24,837 by building count (1 is largest). Within Iowa alone, it ranks 514 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.

What this risk score means for insurance

At the 35th national percentile, Volga rates moderate 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

Volga's 60% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.

Where Volga's figures come from

The methodology guide shows exactly how USFS turned 200 counted buildings into the percentiles shown above for Volga. The exposure-zones guide covers what Volga's dominant indirect exposure actually means, with real examples from across the dataset.