Predictive Modeling of Cyanobacterial Blooms and Diurnal Variation Analysis Based on GOCI
Water,
Год журнала:
2025,
Номер
17(5), С. 749 - 749
Опубликована: Март 4, 2025
Algal
bloom
is
a
major
ecological
and
environmental
problem
caused
by
abnormal
algal
reproduction
in
water,
it
poses
serious
threat
to
the
aquatic
ecosystem,
drinking
water
safety,
public
health.
Because
of
high
dynamic
spatiotemporal
heterogeneity
outbreaks,
process
often
presents
significant
changes
short
time.
Therefore,
has
important
scientific
research
value
practical
application
significance
construct
an
accurate
effective
warning
model.
This
study
constructs
integrated
model
combining
sequence
features,
attention
mechanisms,
random
forest
using
machine
learning
algorithms
for
prediction,
based
on
watercolor
geostationary
satellite
observations
meteorological
data
from
GOCI
South
Korea.
In
process,
spatial
resolution
Sentinel-2
also
utilized
sample
extraction.
With
10-m
resolution,
provides
more
precise
information
compared
500-m
GOCI,
which
significantly
enhances
accuracy
model,
especially
monitoring
local
body
changes.
The
experimental
results
demonstrate
that
exhibits
excellent
stability
prediction
blooms.
average
AUC
0.88,
F1
score
0.72,
0.79
when
identifying
change
hourly
scale.
At
same
time,
this
summarized
four
typical
diurnal
modes
effluent
bloom,
including
dispersal
mode,
persistent
outbreak
dispersal-regression
subsidence
revealing
main
characteristics
bloom.
provided
strong
technical
support
environment
quality
safety
management
showed
good
prospect.
Язык: Английский
Spatiotemporal dynamics of summer chlorophyll-a concentrations under varying drought conditions in a hierarchical Bayesian model
Chemical Engineering Journal,
Год журнала:
2025,
Номер
unknown, С. 163074 - 163074
Опубликована: Апрель 1, 2025
Язык: Английский
Light limitation during a compound drought and heat event inhibited algal blooms in a nutrient-rich shallow lake
Harmful Algae,
Год журнала:
2024,
Номер
142, С. 102796 - 102796
Опубликована: Дек. 30, 2024
Язык: Английский
Harmonized Landsat-Sentinel 2 Data Can Unveil More Subtle and Stable Changes in Lacustrine Ephemeral Algal Bloom
Опубликована: Янв. 1, 2024
Язык: Английский
Cyanobacterial Toxins: Our Line of Defense
IntechOpen eBooks,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 2, 2024
Cyanobacteria
(blue-green
algae)
are
a
diverse
group
of
photo-autotrophic
organisms
where
their
higher
dominance,
in
favorable
conditions,
represents
significant
indicator
water
quality.
Some
the
cyanobacterial
genera
toxigenic
and
can
produce
toxins—cyanotoxins,
which
influence
animals
humans’
health,
also
plants.
Commonly
known
studded
cyanotoxin
groups
include
hepatotoxins
(microcystins,
nodularins),
cytotoxins
(cylindrospermopsin),
neurotoxins
(saxitoxins,
anatoxins,
BMAA),
dermatotoxins
(lyngbyatoxin),
irritant
toxins
(lipopolysaccharide
endotoxins).
This
chapter
provides
guideline
values
for
cyanotoxins
drinking
supply
recreational
purposes.
focuses
on
critical
evaluation
efficacy
treatment
procedures
essential
control.
Such
knowledge
is
extremely
important
future
expansion
toxic
compounds
from
aquatic
ecosystems,
according
to
newest
data,
terrestrial
environments,
especially
due
climate
change
(global
warming)
anthropogenic
eutrophication.
Here
introduced
schemes
ecology
infiltration
through
biological
cycle
jeopardizing
human
tables
treatment,
along
with
proposed
therapy
limitations,
setting
strong
foundation
all
research,
outstanding
scientific
importance.
Язык: Английский