How to Chart Disaster Declarations Over Time by Incident Type

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Problem statement

Are there more federal disasters than there used to be? The number of major disaster declarations per year has risen fivefold since the 1950s, and charts of it are often read as a direct measure of worsening hazards. But declarations are administrative decisions, the rules for them changed, and a single pandemic produced more declarations in 2020 than any natural event. This page charts major disaster declarations by year and incident type from OpenFEMA, shows the fiscal-year trap, and separates the change in how many counties each declaration covers from the change in how many declarations there are.

Quick answer

Deduplicate to one row per disasterNumber, keep declarationType == "DR", take the calendar year from declarationDate, and group by year and a grouped incident type. Show COVID-19 (Biological) separately, and read the trend alongside the policy changes that drive it.

decl = dds.drop_duplicates("disasterNumber").copy()
decl["year"] = decl.declarationDate.dt.year
dr = decl[(decl.declarationType == "DR") & decl.year.between(1953, 2025)]
per_year = dr.groupby("year").size()
print("major disaster declarations per year, by decade (mean):", per_year.groupby(per_year.index // 10 * 10).mean().round(1).to_dict())

major disaster declarations per year, by decade (mean): {1950: 13.4, 1960: 18.4, 1970: 32.8, 1980: 23.7, 1990: 46.0, 2000: 56.0, 2010: 60.2, 2020: 70.8}

Major disaster declarations averaged 13.4 a year in the 1950s, 32.8 in the 1970s, 46.0 in the 1990s and 70.8 in the 2020s so far.

Bar chart of major disaster declarations per calendar year from 1953 to 2025, rising from around 15 to 50-100, with COVID-19 declarations stacked in red on 2020 and 2021. — Major disaster declarations per year: 104 in 2020, only 47 of them not COVID-19.

Years, incident types and designated areas

1. Calendar year, not fiscal year

fy = dr.groupby("fyDeclared").size()
print("2024 and 2025 by calendar year:", per_year.loc[2024:2025].to_dict(), "by fiscal year:", fy.loc[2024:2025].to_dict())

2024 and 2025 by calendar year: {2024: 100, 2025: 45} by fiscal year: {2024: 88, 2025: 61}

Calendar year 2024 had 100 major disasters and 2025 had 45. By fiscal year the same declarations give 88 and 61, because declarations made in October to December 2024 count in fiscal 2025. Neither is wrong, but mixing them, or comparing with a series that uses the other, moves dozens of declarations between years.

2. Group the incident types

grp = {"Severe Storm": "storms", "Tornado": "storms", "Severe Ice Storm": "winter", "Snowstorm": "winter", "Winter Storm": "winter",
       "Freezing": "winter", "Hurricane": "tropical", "Tropical Storm": "tropical", "Typhoon": "tropical", "Coastal Storm": "tropical",
       "Flood": "flood", "Fire": "fire", "Biological": "biological"}
dr = dr.assign(group=dr.incidentType.map(grp).fillna("other"))
tab = dr.groupby([dr.year // 10 * 10, "group"]).size().unstack(fill_value=0)
print(tab.loc[1960:].to_string())

group  biological  fire  flood  other  storms  tropical  winter
year                                                           
1960            0     3    115     16      25        23       2
1970            0     3    231      9      59        14      12
1980            0     8    131      7      51        33       7
1990            0     9    116     14     209        73      39
2000            0    15     23     10     410        66      36
2010            0    18    134     15     314        78      43
2020           59    22     78     14     164        59      29

The mix of incidents has shifted. Floods were the leading declared type in the 1960s to 1980s (231 in the 1970s), then severe storms took over: 410 in the 2000s against 23 floods. That is partly reclassification: since the 1990s FEMA has usually recorded combined storm-and-flood events as severe storms, with flooding listed among the designated incident types. Treat storms and floods as one family when comparing decades. The 2020s add 59 biological (COVID-19) major disasters.

Stacked decade bars of major disasters by incident type from the 1960s to the 2020s: floods dominate the 1960s to 1980s, severe storms dominate from the 1990s, with tropical, winter, fire and in the 2020s biological slices. — Major disasters per decade by incident type: floods give way to severe storms, partly a change in classification.

3. Counties per declaration

area = dds[dds.declarationType == "DR"].drop_duplicates(["disasterNumber", "fipsStateCode", "fipsCountyCode"]).groupby("disasterNumber").size()
dr = dr.assign(areas=dr.disasterNumber.map(area))
print("median designated areas per major disaster, by decade:", dr.groupby(dr.year // 10 * 10).areas.median().to_dict())

median designated areas per major disaster, by decade: {1950: 1.0, 1960: 1.0, 1970: 7.0, 1980: 5.0, 1990: 10.0, 2000: 11.0, 2010: 9.0, 2020: 9.0}

Declarations also got wider. The median major disaster designated a single area in the 1950s and 1960s, 7 in the 1970s and 9–11 since the 1990s. More declarations, each covering more counties, multiply into many more county designations. A county map of declaration counts is therefore much more sensitive to this change than a national count of declarations.

Seasons and record years

The data used on this page

FEMA's Disaster Declarations Summaries from OpenFEMA, saved on this site on 15 October 2026.

from pathlib import Path

import geopandas as gpd
import numpy as np
import pandas as pd
import requests

Path("data").mkdir(exist_ok=True)
# OpenFEMA, queried on 15 October 2026 and saved on this site because both datasets are revised continually:
# DisasterDeclarationsSummaries v2 (every declaration since 1953, one row per designated area) and NfipClaims v3
# (flood insurance claims with a loss in 2017 or later, 29 fields). The queries are in data/README.txt; the live API is
# https://www.fema.gov/api/open/v2/DisasterDeclarationsSummaries and https://www.fema.gov/api/open/v3/NfipClaims
FILES = ["fema-disaster-declarations-2026-10-15.zip", "nfip-claims-2017-2026-2026-10-15.zip"]
for name in FILES:
    if not Path(f"data/{name}").exists():
        Path(f"data/{name}").write_bytes(requests.get(f"https://data.spatialworkflow.io/{name}", timeout=600).content)
dds = pd.read_csv("data/fema-disaster-declarations-2026-10-15.zip", dtype={"fipsStateCode": str, "fipsCountyCode": str, "placeCode": str},
                  parse_dates=["declarationDate", "incidentBeginDate", "incidentEndDate"])
print(f"OpenFEMA: {len(dds):,} declaration rows for {dds.disasterNumber.nunique():,} declarations, "
      f"{dds.declarationDate.min():%Y}-{dds.declarationDate.max():%Y}")

OpenFEMA: 70,567 declaration rows for 5,281 declarations, 1953-2026

Example 1: seasons of declaration

inc = dr.assign(month=dr.incidentBeginDate.dt.month)
print(inc[inc.year >= 2000].pivot_table(index="month", columns="group", values="disasterNumber", aggfunc="count", fill_value=0)[["storms", "tropical", "winter", "flood", "fire"]].to_string())

group  storms  tropical  winter  flood  fire
month                                       
1          69         1      27      7     1
2          67         4      23     18     0
3          75         2       9     32     1
4         110         1       5     42     5
5         121         3       1     31     1
6         104         4       0     36     8
7          80        12       0     19    11
8          49        64       0     15    11
9          51        68       0     16     6
10         47        37       2      9     4
11         41         3       5      2     5
12         74         4      36      8     2

Since 2000, declared severe storms begin most often in April and May (110 and 121), tropical events in August and September, and winter events in December and January. Floods peak in spring with snowmelt and rain. The calendar of declarations follows the calendar of hazards, with a lag of a few weeks for the declaration itself.

Line chart of declared major disasters since 2000 by month the incident began: severe storms peaking in April and May, tropical in August and September, winter in December and January, floods in spring. — Month the incident began, by type, 2000–2025.

Example 2: years with the most

print(per_year.sort_values(ascending=False).head(6).to_dict())
print(f"2020 without COVID-19: {(dr[(dr.year == 2020)].incidentType != 'Biological').sum()}")

{2020: 104, 2024: 100, 2011: 99, 2010: 81, 2008: 75, 1996: 75}
2020 without COVID-19: 47

2020 had the most major disasters (104), but only 47 of them were not COVID-19. 2024 had 100, the highest for natural hazards alone, ahead of 2011 (99) and 2010 (81).

Why the count rose

Several things raised the count besides hazards. The Stafford Act of 1988 broadened what qualified. FEMA judges requests against a per-capita damage indicator, a dollar amount of public damage per resident that a state must exceed. It was set in 1986 and not adjusted for inflation until 1999, so for more than a decade the same real damage qualified more and more easily. Exposure grew too, with more people and property in floodplains and on coasts. Political and administrative practice also plays a part: studies find more declarations in presidential election years and in swing states.

Climate change may well be part of the trend, especially in heavy-rain floods and fire. But the declaration count cannot isolate it. For hazard trends, use physical records (Storm Events, streamflow, fire perimeters) and use declarations to study federal response.

Charting choices

One row per disasterNumber. Counting rows makes 2020 look like an order of magnitude more disasters.
Calendar or fiscal year, and say which.
Exclude emergencies and fire management unless the question is about them; their rules and history differ.
The current year is incomplete. Late-year storms are declared weeks later, so the latest year is always low.

Internal links

FEMA disaster declarations explained — what DR, EM and FM mean
How to map FEMA disaster declarations — the same data by county
Disaster counts too high — rows against declarations

FAQ

How many major disaster declarations are there per year?

In the 2020s an average of 70.8 a year, against 13.4 in the 1950s, from OpenFEMA's declarations by calendar year.

Which year had the most FEMA disaster declarations?

2020, with 104 major disasters, most of them COVID-19. Without COVID-19, 2024 had the most, 100.