Predicting and preventing algal blooms

Researchers have developed a day-ahead statistical model to predict algal bloom risk in the Caloosahatchee River and Estuary in Florida. By analyzing historical data and utilizing decision tree models, the model provides water managers with a simple and adaptable tool to anticipate bloom events, enabling proactive adjustments to reservoir releases and potentially mitigating ecological and economic impacts.

Read the full article at https://www.paperleap.com/blog/articles/predicting-and-preventing-algal-blooms-0cccuz

Episode Transcript

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Speaker 2 (00:32):
Water managers may soon check two forecasts every morning, one
for the weather and another a bloom forecast for algae
that warns you about whether the river near you is
about to turn green with algae. For communities in southwest Florida,
this isn't science fiction. It's the new reality being shaped

(00:53):
by researchers who want to give water managers a one
day head start in fighting harmful algal blooms. A team
of scientists from North Carolina State University, the University of Florida,
the University of South Florida, and the Sanabel Captiva Conservation
Foundation has developed a day ahead statistical model that predicts

(01:14):
the risk of algel blooms and the Caloosahatchie River and Estuary,
one of Florida's most troubled waterways. Their study, published in
the Journal of Environmental Management, offers a simple but powerful
forecasting tool designed for real world use, and the best
part is that it could help water managers make smarter

(01:35):
choices about when and how to release water from Lake Okeechobee,
decisions that directly influence whether the river downstream turns into
a soup of green algae. Why are Florida's waters so vulnerable?
To understand why this research matters, let's back up a little.
Florida's waterways have a long and complicated relationship with human engineering.

(01:59):
At the center of is Lake Okeechobee, the giant freshwater
lake in South Florida. A century ago, the lake naturally
overflowed into the Everglades every year, nourishing one of the
world's richest wetlands. But devastating floods in the early nineteen
hundreds led engineers to build a massive dike around the lake. Today,

(02:21):
the US Army Corps of Engineers manages the lake like
a reservoir, shuttling water east to the Saint Lucie Estuary,
west to the Calusahatchie River and south toward the Everglades.
The problem is that Lake Ogichobe is overloaded with nutrients,
especially nitrogen and phosphorus, thinks to decades of agricultural runoff

(02:43):
and urban development. These nutrients fuel explosive algo blooms, some
of which involve harmful cyanobacteria that can release toxins dangerous
to people, pets, and wildlife. When managers release water from
the lake into the calusah Hatchy River to control flooding
or maintain navigation, they can unintentionally send a surge of

(03:06):
algae and nutrients downstream, setting the stage for massive blooms
in the estuary. Local residents, fishermen, and businesses have seen
a firsthand murky green water, dead fish, and beach closures.
Alcohol blooms are tricky to predict. They depend on a
mix of factors how much water is flowing, what nutrients

(03:29):
are present, how warm the water is, and even how
long water sits still in one place. Scientists often use
process based computer models that simulate these dynamics in detail,
but those models are slow and complex, requiring heavy computing
power and specialized training that makes them ill suited for

(03:50):
day to day management decisions. Water managers need fast, simple tools,
something closer to a weather forecast than a supercomputer simulation,
and that's where Maria Minchew Maldonado and her colleagues stepped in.
Their goal wasn't to build the most intricate model, but
rather a straightforward statistical tool that could take yesterday's water

(04:13):
conditions and reliably predict tomorrow's bloomerisk. The researchers gathered more
than fourteen years of monitoring data from the US Geological
Survey and the South Florida Water Management District. They looked
at waterflow, nutrient levels, suspended solids, and chlorophyll a, a
pigment used as a proxy for algo biomass. Then they

(04:36):
built two separate decision tree models, a kind of predictive
flow chart lake dominated conditions when most water entering the
estuary comes from Lake Okeechobee, and watershed dominated conditions when
local runoff from the C forty three Canal and surrounding
land is the main contributor. By splitting the problem this way,

(04:57):
the models could better reflect the very different di ynamics
of lake water versus watershed runoff. They found that lake
driven blooms are easier to predict. The model explained about
seventy eight percent of the variation in bloom risk when
the water source was Lake Okeechobe. The key predictors levels
of suspended solids and nutrient patterns in the water released

(05:18):
from the lake instead. Watershed driven blooms are trickier when
runoff was the main driver. The model captured about forty
nine percent of the variation. Dissolved phosphorus loads and chlorophyll
a levels from the canal played the biggest roles in short.
Blooms caused by lake releases are not only more predictable,

(05:39):
but also more controllable, since water managers can adjust how
and when water leaves Lake Okeechobe. For people living near
the Calusahatchie River, this kind of forecast could be a
game changer. Imagine a tool that alerts water managers that
tomorrow's conditions are right for bloom. They could then hold
back water from Lake Okeechobe, tweak relie leased schedules, or

(06:01):
coordinate with local agencies to prepare for potential impacts. It's
not just about cleaner water. Algal blooms hurt tourism, real estate,
commercial fishing, and public health In Florida, entire summer economies
have been disrupted by guacamole thick water coating estuaries and beaches.
Having a day ahead risk map could help reduce both

(06:24):
the ecological and economic fallout. The authors emphasize that their
framework is adaptable and scalable. While they focused on the
Colusahatchie River, the same approach could be applied to other rivers, lakes,
and estuaries facing bloom problems. They also suggest that the
model could be expanded beyond algae to forecast other water

(06:46):
quality issues, like low oxygen conditions that suffocate fish or
sediment loads that cloud the water. In a world where
climate change and population growth are putting increasing pressure on
freshwater systems, tools like this are invaluable. As reservoirs and
engineered waterways become more common, so too will the need

(07:07):
for fast, actionable forecasting. Alcohol blooms may seem like sudden,
unstoppable natural disasters, but research like this shows they're often
predictable and preventable. By harnessing years of data and building simple,
decision friendly models, scientists are giving water managers a new

(07:28):
kind of forecast, one that could protect ecosystems, economies, and communities.
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