PlainHazard

Original research, PlainHazard editorial

Top 10 US Counties by FEMA Disaster Frequency

PlainHazard ranks US counties by the total number of FEMA disaster declarations affecting their territory. Rendered server-side from a live SELECT against the counties aggregate table.

Research period:

Reviewed by PlainHazard Editorial on 2026-05-17

Research question

Which US counties show the highest cumulative FEMA disaster declaration counts, and how does county-level exposure track with regional climate, coastal location, and recurring hazard types like hurricanes, severe storms, and wildfires?

Methodology

We queried the PlainHazard counties table at server render time and pulled the columns county_name, state_name, total_disasters, major_disasters, top_incident_type. The query ranks records by total_disasters DESC and returns the top 10. Every numeric value rendered on this page derives from a live SELECT against the production counties table — no figure is hardcoded, and the table refreshes whenever the underlying Federal Emergency Management Agency dataset is reingested.

County declaration counts behave differently from state counts. When the President issues a major disaster declaration, FEMA names every county eligible for assistance, so a single large event can add one declaration to dozens of counties at once. A county that sits in the recurring path of a hazard — Gulf and Atlantic coastal counties for hurricanes, Plains counties for tornadoes and flooding, Western counties for wildfire — accumulates declarations across many separate events over the years and rises to the top of this ranking.

Two caveats shape how to read the list. First, county boundaries and populations vary enormously, so a high raw count does not by itself mean a county is the most dangerous place to live; a populous, large-area county is simply exposed to more events. Second, the "major" share matters — a county with many Major Disaster (DR) declarations has faced events severe enough to need the full slate of federal individual and public assistance, a stronger signal than a long tail of smaller Emergency declarations. For a normalized view of risk, pair this with each county's FEMA National Risk Index rating, which factors in expected annual loss, social vulnerability, and community resilience.

See the methodology page for the complete ETL pipeline, source vintage, and column lineage.

Top 10 US Counties by FEMA Disaster Frequency

Live data — rendered from a SELECT against the portal database at request time

records
Source Federal Emergency Management Agency

The ranked top 10

Every row below is rendered from a live SELECT against the 10-row result returned by the query in the frontmatter above. Refresh the page after an ETL run to see the latest values.

# County State Total declarations Major disasters Top incident type
1 Los Angeles California 25 6 Fire
2 Chelan Washington 23 2 Fire
3 Yupiit Regional Educational Attendance Area Alaska 19 19 Flood
4 Washoe Nevada 19 0 Fire
5 Okanogan Washington 18 6 Fire
6 Levy Florida 15 6 Hurricane
7 Dixie Florida 15 6 Hurricane
8 Citrus Florida 15 6 Hurricane
9 Gilchrist Florida 15 6 Hurricane
10 Manatee Florida 15 6 Hurricane

Source: Federal Emergency Management Agency — OpenFEMA Disaster Declarations Summaries V2 (county designations). Values are queried live from the PlainHazard SQLite snapshot at request time; the snapshot is refreshed by the portal ETL pipeline. Federal Emergency Management Agency — OpenFEMA Disaster Declarations Summaries V2 (county designations). Values are queried live from the PlainHazard SQLite snapshot at request time; the snapshot is refreshed by the portal ETL pipeline.

Findings

Top entity in the ranking

The top-ranked record in this dataset is Los Angeles, with a value of 25 on the Total declarations column. The full top-10 set is rendered in the table above. Every value derives from the underlying counties table; no number is hardcoded into this page. When the Federal Emergency Management Agency publishes a revision and our ETL pipeline reingests, the ranking and the prose around it update on the next page load.

Distribution shape

The gap between the top-ranked record (25) and the 10th-ranked record (15) characterizes how concentrated the top of the distribution is. Where the top value is many multiples of the median value of the visible set, the population is highly concentrated — a small number of entities accumulate the bulk of the measured quantity. Where the top and bottom of the visible set are close together, the distribution is relatively flat across the top end. The full distribution beyond this top-10 cut is summarized in the aggregate context section below and explored in the linked entity profiles.

Aggregate context

Across the full counties population, the aggregate query returns the following summary statistics. These anchors situate the top-10 ranking against the underlying population: how many records exist in total, what the sum of the ranking column is across all qualifying rows, and what the mean per-record value looks like. The methodology page documents the exact filter applied by the aggregate query (records with null or zero values on the ranking column are excluded). The aggregate row is computed by the same database engine that renders the ranking above, against the same snapshot.

Source provenance

The records in this ranking originate from Federal Emergency Management Agency, specifically the OpenFEMA Disaster Declarations Summaries V2 (county designations). PlainHazard ingests the source vintage published by the agency, transforms it into a normalized SQLite schema, and serves it from a read-only snapshot. Every render of this page is a fresh SELECT against that snapshot — there is no static export carrying stale numbers, and the edge cache lifetime is bounded by the portal middleware so that a reingested dataset propagates within hours. The methodology page documents the source URL, the vintage date, and the transformation steps applied during ETL.

Why this ranking matters

Rankings like this one let a reader scan a population quickly and identify outliers, concentrations, and patterns that warrant deeper investigation. The detail pages linked from each entity in the table above give the full per-entity context: time-series history where available, related metrics from adjacent tables, and links onward to the underlying source records. The methodology page explains how an entity earns inclusion in the dataset and how the ranking column is computed at the source.

What this analysis cannot tell us

County-level disaster counts in OpenFEMA reflect the designated areas listed in each declaration. A single statewide declaration may flag all counties in a state, inflating per-county counts in states where governors frequently request statewide assistance, while counties in states that limit declarations to specifically-affected areas show lower counts even at comparable hazard exposure. Independent cities, parishes, and Census-designated areas vary in how they map to county-level FIPS codes; the OpenFEMA dataset uses FEMA's own area designations, which may not exactly match Census county boundaries. Counties spanning multiple FEMA regions or with significant tribal lands within their boundaries may show counts that differ from a strict per-FIPS aggregation.

Sources