Groundwater for Sustainable Development,
Journal Year:
2023,
Volume and Issue:
23, P. 101049 - 101049
Published: Nov. 1, 2023
Groundwater
plays
a
pivotal
role
as
global
source
of
drinking
water.
To
meet
sustainable
development
goals,
it
is
crucial
to
consistently
monitor
and
manage
groundwater
quality.
Despite
its
significance,
there
are
currently
no
specific
tools
available
for
assessing
trace/heavy
metal
contamination
in
groundwater.
Addressing
this
gap,
our
research
introduces
an
innovative
approach:
the
Quality
Index
(GWQI)
model,
developed
tested
Savar
sub-district
Bangladesh.
The
GWQI
model
integrates
ten
water
quality
indicators,
including
six
heavy
metals,
collected
from
38
sampling
sites
study
area.
enhance
precision
assessment,
employed
established
machine
learning
(ML)
techniques,
evaluating
model's
performance
based
on
factors
such
uncertainty,
sensitivity,
reliability.
A
major
advancement
incorporation
metals
into
framework
index
model.
best
authors
knowledge,
marks
first
initiative
develop
encompassing
heavy/trace
elements.
Findings
assessment
revealed
that
area
ranged
'good'
'fair,'
indicating
most
indicators
met
standard
limits
set
by
Bangladesh
government
World
Health
Organization.
In
predicting
scores,
artificial
neural
networks
(ANN)
outperformed
other
ML
models.
Performance
metrics,
root
mean
square
error
(RMSE),
(MSE),
absolute
(MAE)
training
(RMSE
=
0.361;
MSE
0.131;
MAE
0.262),
testing
0.001;
0.00;
0.001),
prediction
evaluation
statistics
(PBIAS
0.000),
demonstrated
superior
effectiveness
ANN.
Moreover,
exhibited
high
sensitivity
(R2
1.0)
low
uncertainty
(less
than
2%)
rating
These
results
affirm
reliability
novel
monitoring
management,
especially
regarding
metals.
ISH Journal of Hydraulic Engineering,
Journal Year:
2024,
Volume and Issue:
30(3), P. 281 - 292
Published: Feb. 14, 2024
This
study
explores
the
potential
of
GPBoost
approach
for
groundwater
quality
assessment
in
comparison
to
three
other
gradient
boosting-based
algorithms.
Three
methods,
random
search,
grid
and
Bayesian
optimization
were
used
find
optimal
values
various
hyperparameters
with
all
four-gradient
One
hundred
two
samples
Entropy
weighted
water
index
14
input
parameters
are
assessing
quality.
The
calculated
EWQI
drinking
range
between
80.4
394.96
pre-monsoon
39.6
338.79
during
post-monsoon
period.
Moreover,
spatial
distribution
maps
displayed
that
central
portions
area
fall
under
medium
performances
models
compared
based
on
multiple
statistical
criteria,
including
Correlation
Coefficient
(CC),
root
mean
square
error
(RMSE),
absolute
(MAE).
results
reveal
CC
value
by
modeling
approaches
is
more
than
0.93,
suggesting
a
comparable
performance
methods.
Results
terms
RMSE
predicting
suggest
(random
search)
model
performed
better
models,
thus
competitive
approaches.
Relative
importance
analysis
provided
search
methods
highlights
significance
NO3−,
Mg2+,
TDS,
EC,
TH
as
important
EWQI.
Water Science & Technology,
Journal Year:
2023,
Volume and Issue:
88(3), P. 778 - 797
Published: July 20, 2023
Abstract
This
study
examined
the
groundwater
quality
in
Ha'il
according
to
World
Health
Organization
(WHO)
standards
using
entropy-weighted
water
index
(EWQI)
more
accurately.
The
investigated
several
parameters
and
found
that
than
75%
of
changes
can
be
attributed
four
main
factors
(MF1,
MF2,
MF3,
MF4).
MF1
was
have
biggest
role
controlling
33%
quality.
Due
entropy
calculations
for
each
parameter,
zinc
highest
rate
influence
on
results
EWQI
showed
number
samples
(76%)
had
Rank
2
good
Also,
it
tried
couple
with
machine-learning
techniques
improve
model
performance
survey
related
this
study.
efficiency
criteria
are
improved
noticeably.
Root-mean-square
error
decreases
by
25%,
determination
coefficient
(R2)
increases
27.94%.
Water Science & Technology Water Supply,
Journal Year:
2024,
Volume and Issue:
24(5), P. 1938 - 1957
Published: May 1, 2024
ABSTRACT
This
assessment
research
focuses
on
the
hydrochemical
characteristics
and
groundwater
suitability
in
Wadi
Righ
region,
southern
Algeria.
The
statement
of
problem
revolves
around
determining
water
quality
using
various
indices
including
Permeability
Index
(PI),
Residual
Sodium
Carbonate
(RSC),
Water
Quality
(WQI),
Percentage
(Na%),
Adsorption
Ratio
(SAR),
Canadian
Council
Ministers
Environment's
(CCME
WQI),
Magnesium
Hazard
(MH),
Irrigation
(IWQI),
Kelly
(KR).
Additionally,
statistical
methods
were
utilized
to
establish
correlations
between
these
chemical
elements.
working
method
involved
investigating
parameters
Righ's
analyzing
52
samples.
results
indicate
that
quality,
as
assessed
by
indices,
was
categorized
very
poor
unsuitable
overall,
with
lower
observed
particularly
central
regions.
However,
demonstrated
excellence
for
irrigation
purposes.
Qualitatively,
findings
suggest
there
are
significant
relationships
among
indicated
Pearson
correlation
analysis.
These
stem
from
shared
inputs
hydrogeochemical
groundwater.
analysis
reinforces
quantitative
provides
insights
into
underlying
factors
influencing
region.
