Tracking the spatiotemporal evolution of groundwater chemistry in the Quaternary aquifer system of Debrecen area, Hungary: integration of classical and unsupervised learning methods
Environmental Science and Pollution Research,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 1, 2025
Abstract
Monitoring
changes
in
groundwater
quality
over
time
helps
identify
time-dependent
factors
influencing
water
safety
and
supports
the
development
of
effective
management
strategies.
This
study
investigates
spatiotemporal
evolution
chemistry
Debrecen
area,
Hungary,
from
2019
to
2024,
using
indexing,
machine
learning,
multivariate
statistical
techniques.
These
techniques
include
self-organizing
maps
(SOM),
hierarchical
cluster
analysis
(HCA),
principal
component
(PCA),
indexing
(GWQI).
The
hydrochemical
revealed
that
Ca-Mg-HCO₃
is
dominant
type,
with
a
temporal
shift
toward
Na-HCO₃,
reflecting
increased
salinity
driven
by
ongoing
rock-water
interactions.
SOM
showed
transition
heterogeneous
more
uniform
time,
suggesting
greater
stability
aquifer
system.
Elevated
zones
shifted
spatially
due
recharge
flow
patterns,
while
hardness
intensified
expanded,
indicating
continued
carbonate
dissolution.
HCA
highlighted
shifts
composition,
six
clusters
identified
five
gradual
homogenization
quality.
PCA
further
confirmed
this
trend,
linking
it
underlying
processes,
such
as
water–rock
interactions,
limited
contributions
anthropogenic
influences.
GWQI
indicated
general
improvement
most
regions
meeting
drinking
standards.
However,
specific
areas
exhibited
signs
localized
contamination,
requiring
targeted
management.
findings
underscore
importance
continuous
monitoring
detect
emerging
trends
guide
resource
highlights
need
for
sustainable
practices
safeguard
resources
ensure
long-term
security
area.
Language: Английский
Multi‐Objective Optimization of a Spherical Thermal Storage Tank Using a Student Psychology‐Based Approach
Energy Storage,
Journal Year:
2025,
Volume and Issue:
7(1)
Published: Feb. 1, 2025
ABSTRACT
Energy
storage
technologies
often
store
heat,
with
water
as
a
preferred
medium
due
to
its
availability
and
low
cost.
However,
maintaining
in
liquid
state
at
high
temperatures
requires
large
pressure
vessels,
posing
significant
design
challenges.
Balancing
thermal
capacity
constraints
is
essential.
This
paper
explores
the
dynamics
of
tanks,
aiming
optimize
their
using
multi‐criteria
approach.
An
equilibrium
thermodynamic
model
was
developed
evaluate
impact
geometric
structure
operating
parameters.
The
results
show
that
optimizing
single
variable
insufficient
minimize
swing,
reduce
heat
loss,
maximize
capacity.
To
address
these
trade‐offs,
multi‐objective
student
psychology‐based
optimization
(SPBO)
algorithm
employed
for
three‐objective
optimization,
outperforming
particle
swarm
(PSO)
convergence.
technique
order
preference
by
similarity
ideal
solution
(TOPSIS)
method
applied
Pareto
frontier,
yielding
solutions
both
data‐driven
manually
weighted
approaches.
Compared
initial
design,
(entropy‐weighted
coefficient
variation
methods)
optimal
designs
improved
all
objectives,
reducing
swing
12.8%
19.8%,
respectively.
A
approach
reduced
up
86.7%,
albeit
decrease
Language: Английский