Every
Thursday morning, a colorful
map of the United States
updates online. Published by
the National Drought
Mitigation Center (NDMC)
at the University of
Nebraska–Lincoln, the U.S.
Drought Monitor (USDM)
garners intense public
interest and holds massive
real-world leverage.
The
map isn’t just
informational—it’s deeply
actionable. USDM
classifications directly
trigger billions of dollars in
federal disaster relief,
including emergency aid to
ranchers through the USDA’s
Livestock Forage Program (LFP),
and serve as a decision-making
baseline for state and local
drought plans.
How
is this weekly snapshot
actually drawn? In this post,
we’ll explore what defines a
drought, how experts construct
the map, the inherent
limitations of synthesizing
complex climate data into a
single weekly image, and how
you can lend your voice to the
process.
Defining
Drought: Unlike
some other natural hazards,
such as hurricanes and
tornadoes, there are numerous
ways to define drought.
According to the National
Integrated Drought Information
System, there are over 150
recorded definitions of
drought in the academic
literature. One of my
favorites, from Dr. Kelly
Redmond, simply defines it as
“insufficient water to meet needs.”
This principle is at the heart
of most, if not all,
reasonable definitions of
drought.
One
reason there are so many
different definitions of
drought is because there are
so many ways to measure it.
Drought can be measured
according to meteorological
indicators (such as
precipitation), hydrological
indicators (such as
streamflow), ecological
indicators (such as tree
mortality), or economic
indicators (such as crop
yields). Image 1 from the U.S.
Forest Service does a nice job
illustrating this.
Different
types of drought also occur
over different timescales. For
instance, oppressively hot and
dry conditions at an important
stage of growth for a crop
like corn may cause crippling
drought impacts to corn
growers while having little
impact on nearby lakes,
reservoirs, or even trees with
deep root systems.
The
USDM defines
drought severity by how rare a
given dryness level is
historically:
D1
(Moderate): Below
the 20th percentile (occurs
1 in 5 years)
D2
(Severe): Below
the 10th percentile (1 in 10
years)
D3
(Extreme): Below
the 5th percentile (1 in 20
years)
D4
(Exceptional):
Below the 2nd percentile (1
in 50 years)
Image
2 shows how these thresholds
align on a standard normal
distribution. Image 3 grounds
this concept using 100 years
of real precipitation data for
Fort Collins, Colorado,
overlaying the exact cutoff
thresholds for each drought
category.
Image
2: Representation of each
drought category using a
typical probability density
distribution from Lorenz et
al. 2017.
Image
3: Annual precipitation
accumulations for Fort
Collins, Colorado from
1926-2025. The thresholds
for moderate drought (tan),
severe drought (orange),
extreme drought (red), and
exceptional drought
(burgundy) have been plotted
alongside the precipitation
measurements.
Drought
thresholds depend on both
location and time of year—D4
conditions look drastically
different in Vermont in
January than in Arizona in
July. Colorado alone spans
vast climate extremes. The
high-altitude Tower weather
station in the Park Range has
never recorded less than 39.9
inches of annual precipitation
in over 45 years. By contrast,
rain-shadowed mountain
valleys, like the San Luis
Valley, average under 8 inches
per year. In fact, an average
rainfall year in Alamosa would
qualify as exceptional (D4)
drought in Fort Collins, and
would be completely off the
charts at Tower.
Creating
the US Drought Monitor Map:
How does the USDM (recent map
shown in Image 4) assess
current dryness? Do authors
use precipitation data?
Streamflow? Soil moisture?
Vegetation health? The answer
is all of the
above—and more.
USDM authors synthesize over 100
different indicators,
including:
Precipitation
and Evapotranspiration:
Meteorological fluxes
tracked across short to long
timescales.
Hydrology:
Snowpack, soil moisture,
streamflow, and groundwater
levels.
Sector
Impacts:
On-the-ground effects on
agriculture, ecology, and
outdoor recreation.
These
data streams come from weather
stations, rain and stream
gauges, satellite sensors, and
numerical models. Each
indicator acts as an “arrow in
the quiver,” helping authors
hone in on current conditions
through a convergence
of evidence
approach—setting drought
levels based on where the
overall weight of the data
points.
But
the USDM isn’t just driven by
algorithms; it relies heavily
on human expertise. Every
week, over 400 local
experts—including State
Climate Offices, University
Extension services, the
National Weather Service,
NRCS, USGS, and the Farm
Service Agency—provide
feedback to the lead author.
These local partners help
translate dataset trends into
real-world impacts.
Citizen
scientists also play a key
role. Ground-level insights
flow in through Condition
Monitoring Observer Reports
(CMOR)
and volunteer observers in the
Community
Collaborative Rain, Hail,
and Snow (CoCoRaHS)
network, who measure rainfall
every morning and submit
qualitative field reports to
verify what datasets are
showing on the ground.
Image
4: Latest US Drought Monitor
map
When
most indicators align,
establishing a “convergence of
evidence” is more
straightforward and drawing
the map is more clear-cut.
However, balancing over 100
data streams with feedback
from hundreds of observers
often reveals conflicting
signals. For example, Image 5
shows a Condition Monitoring
Report from a CoCoRaHS
volunteer in Hayden, Colorado,
reporting wetter-than-normal
conditions right alongside
data pointing in the opposite
direction:
Image
5: Condition Monitoring
Report from weather station
near Hayden.
Would
you believe that according to
the US Drought Monitor this
person was in the midst of a
severe drought?
April and May had brought
wetter than normal conditions,
but a record warm and dry
winter brought abysmal
snowpack to the nearby
mountains. The Yampa River,
which serves as the primary
irrigation supply for the
area, was running at very low
levels (Image 6).
Image
6: 7-day average streamflows
for the Yampa River at
Steamboat Springs on May
28th, 2026. The black line
shows the current year of
data (October 2026 – May
2026). Each of the gray
lines show a previous year
of record. The brown line
shows the record low flow
year, and the blue line
shows the record high flow
year. The green lines show
the mean and median years,
and the colored lines show
flows corresponding to each
drought category listed
above.
Limitations:
The U.S. Drought Monitor has
important limitations that
users should keep in mind.
Most glaringly, it attempts to
distill a multifaceted
hazard—with over 150
definitions—into a single map.
Drought impacts vary across
sectors and space. Impacts can
even shift dramatically from
one field to the next. As
Kelly Redmond noted, “In
essence, as with rainbows,
each person experiences their
own drought.“A
single weekly map simply
cannot capture every localized
reality. In trying to be
everything to everyone, the
map can sometimes obscure the
nuanced picture on the ground.
Drought
in a changing climate:
Human-driven greenhouse gas
emissions are rapidly shifting
our baseline climate.
In regions like the American
Southwest, a long-term aridification
trend is underway that is
unlikely to reverse anytime
soon. Conditions that used to
occur only once every 20 (or
more) years are becoming far
more frequent. As a result,
the USDM’s baseline thresholds
are constantly moving.
A level of dryness that
qualified as an extreme (D3)
drought 30 years ago might
only rank as moderate (D1 or
D2) by today’s standards. For
example, if we use temperature
rather than precipitation for
our Fort Collins baseline,
rising average temperatures
shift our percentile
thresholds upward over time
(Image 7). While researchers
are actively developing more
effective frameworks
to define drought in a
warming world, solving this
moving-target problem remains
an ongoing challenge.
Image
7: Annual average
temperatures for Fort
Collins, Colorado from
1926-2025. The thresholds
for moderate drought (tan),
severe drought (orange),
extreme drought (red), and
exceptional drought
(burgundy) have been plotted
alongside the temperature
measurements.
Strengthening
the Map: The
National Drought Mitigation
Center understands the
limitations discussed here.
Perhaps the best way to
improve the USDM is active
public participation. The US
Drought Monitor authors, and
many of the people who
contribute to it (including
us) really do look at your
impact reports every week.
Bottom-up impact reporting is
essential to getting the map
right.
Two
great ways to contribute are:
Condition
Monitoring Observer
Reports (CMOR):
Submit detailed notes and
photos about localized
drought impacts directly to
the NDMC.
The
CoCoRaHS Network:
Join over 20,000 active
volunteers who log daily
backyard rainfall
measurements. Observers can
also submit weekly Condition
Monitoring Reports
(as shown in Image 8) using
helpful, step-by-step guides
to ensure field observations
deliver maximum value.
Tracking
drought across complex
landscapes is inherently
tough—but it becomes more
accurate when local observers
lend their voices to the
collective wisdom of the map.
Image
8: Photo showing dry
conditions near the Fort
Garland area in Colorado’s
San Luis Valley. This photo
was submitted by a CoCoRaHS
observer.
