Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(19), P. 9123 - 9123
Published: Oct. 9, 2024
Various
hydrogeological
problems
like
groundwater
inflow,
water
table
drawdown,
and
pressure
redistribution
may
be
encountered
in
the
construction
of
hydraulic
projects.
How
to
accurately
predict
occurrence
inflow
assess
drainage
effect
during
are
still
challenging
for
engineering
designers.
Taking
Jinzhai
pumped
storage
power
station
(JPSPS)
China
as
an
example,
this
paper
aims
use
different
methods
calculate
rates
underground
powerhouse
evaluate
caused
by
tunnel
construction.
The
consist
analytical
formulas,
site
rating
(SGR)
method,
Signorini
type
variational
inequality
formulation.
results
show
that
considering
stable
overestimate
caverns
drained
conditions,
whereas
SGR
method
with
available
hydro-geological
parameters
obtains
a
qualitative
hazard
assessment
preliminary
phase.
numerical
solutions
provide
more
precise
reliable
values
complex
geological
structures
seepage
control
measures.
Moreover,
effects,
including
seepage-free
surface,
pore
redistribution,
gradient,
have
been
evaluated
using
various
synthetic
cases.
Specifically,
faults
intersecting
on
significantly
change
flow
regime
around
caverns.
This
comparative
study
can
not
only
exactly
identify
capabilities
cavern
but
also
comprehensively
Agronomy,
Journal Year:
2024,
Volume and Issue:
14(12), P. 3001 - 3001
Published: Dec. 17, 2024
Crop
diseases
pose
a
significant
threat
to
global
food
security,
with
both
economic
and
environmental
consequences.
Early
accurate
detection
is
essential
for
timely
intervention
sustainable
farming.
This
paper
presents
review
of
machine
learning
(ML)
deep
(DL)
techniques
crop
disease
diagnosis,
focusing
on
Support
Vector
Machines
(SVMs),
Random
Forest
(RF),
k-Nearest
Neighbors
(KNNs),
models
like
VGG16,
ResNet50,
DenseNet121.
The
method
includes
an
in-depth
analysis
algorithm
performance
using
key
metrics
such
as
accuracy,
precision,
recall,
F1
score
across
various
datasets.
We
also
highlight
the
data
imbalances
in
commonly
used
datasets,
particularly
PlantVillage,
discuss
challenges
posed
by
these
imbalances.
research
highlights
critical
insights
regarding
ML
DL
detection.
A
primary
challenge
identified
imbalance
PlantVillage
dataset,
high
number
healthy
images
strong
bias
toward
certain
categories
fungi,
leaving
other
mites
molds
underrepresented.
complicates
model
generalization,
indicating
need
preprocessing
steps
enhance
performance.
study
shows
that
combining
Vision
Transformers
(ViTs)
Green
Chromatic
Coordinates
hybridizing
SVM
achieves
classification
emphasizing
value
advanced
feature
extraction
improving
efficacy.
In
terms
comparative
performance,
architectures
convolutional
neural
network
demonstrated
robust
accuracy
(95–99%)
diverse
underscoring
their
effectiveness
managing
complex
image
data.
Additionally,
traditional
exhibited
varied
strengths;
instance,
performed
better
balanced
while
RF
excelled
imbalanced
Preprocessing
methods
K-means
clustering,
Fuzzy
C-Means,
PCA,
along
ensemble
approaches,
further
improved
accuracy.
Lastly,
underscores
high-quality,
well-labeled
stakeholder
involvement,
comprehensive
evaluation
precision
are
crucial
optimizing
models,
making
them
more
effective
real-world
applications
agriculture.
Hydrology,
Journal Year:
2025,
Volume and Issue:
12(2), P. 32 - 32
Published: Feb. 13, 2025
The
lakes
known
as
El
Sol
and
La
Luna
are
high
mountain
water
deposits
located
in
Mexico
within
an
inactive
volcanic
system.
These
of
ecological
importance
because
they
unique
Mexico.
However,
currently,
the
have
experienced
changes
their
shape
increase
algae
blooms,
coupled
with
degradation
basin,
which
has
alerted
government
entities
to
need
address
lakes’
problems.
To
environmental
status
Luna,
a
trophic
study
was
conducted
during
period
2021–2023,
including
analysis
influence
climatic
variables,
lake
quality,
eutrophication
conditions.
state
established
based
on
index.
Pearson
correlations
defined
interrelation
between
distinct
factors
influencing
status.
registered
higher
conditions
than
Luna.
identified
seasonal
eutrophic
transitioning
from
oligotrophic
mesotrophic,
showing
levels
chlorophyll,
total
phosphorus,
nitrogen
low
transparency.
principal
altering
were
pollution
variables
(precipitation
ambient
temperature).
Eutrophication
prime
factor
impacting
perimeter
loss
at
Sol,
whereas
it
due
decline
precipitation.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Feb. 27, 2025
The
Chi
and
Mun
River
Basins,
the
primary
tributary
of
Mekong
Basin
in
Thailand,
is
undergoing
significant
land
use
changes
that
impact
water
quality.
Understanding
relationship
between
quality
crucial
for
effective
river
basin
management,
providing
insights
applicable
to
global
systems.
While
past
studies
have
examined
Basin,
research
specifically
focusing
on
Chi-Mun
remains
limited.
This
study
analyzes
spatial
temporal
effects
from
2007
2021
using
change
estimation,
11
parameters,
redundancy
analysis
(RDA).
Water
samples
were
collected
January,
March,
May,
August
across
multiple
years.
Seasonal
variations
assessed,
with
dry
season
January
March
wet
May
August.
Key
findings
include:
(1)
pH,
Biochemical
Oxygen
Demand,
Total
Coliform
Bacteria,
Fecal
Phosphorus,
Nitrate
Nitrogen,
Ammonia-Nitrogen,
Suspended
Solids
increased
during
season,
while
(2)
Dissolved
Oxygen,
Electrical
Conductivity,
Quality
Index
higher
season.
(3)
Land
had
a
greater
driven
by
runoff
expanding
urban
agricultural
areas
declining
paddy
forest
cover.
(4)
Forests
aquatic
improved
quality,
expansion
contributed
its
deterioration.
These
underscore
need
sustainable
management
strategies
balance
regional
development
ecological
conservation
Basin.
