Research Square (Research Square),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Nov. 28, 2023
Abstract
Open
dumping
is
the
prevailing
municipal
solid
waste
(MSW)
disposal
technique
in
India.
Unsanitary
landfill
system
results
release
of
leachate,
a
substance
that
has
potential
to
contaminate
nearby
environment,
including
groundwater.
Hence,
present
study
was
carried
out
vicinity
Saduperi
open
dumpsite,
Vellore,
Tamil
Nadu,
India,
explore
key
factors
influence
groundwater
contamination.
18
sample
wells
were
identified
near
dumpsite
and
total
216
samples
collected
between
May
2021
April
2022.
These
categorized
into
four
different
seasons
such
as
summer,
southwest
monsoon
(SWM),
northeast
(NEM),
winter.
The
contamination
assessed
using
hydrogeochemical
methods
Piper
Gibbs
diagrams.
leachate
pollution
index
(LPI)
Heavy
metal
(HPI)
used
evaluate
potential.
calculated
LPI
>
35
all
indicates
poor
environmental
condition.
It
observed
about
56%
sampling
site
affected
by
heavy
concentrations
Cd,
Cr,
Ni.
HPI
value
found
be
more
than
critical
100
10
for
seasons.
Partial
least
squares-structural
equation
modelling
(PLS-SEM)
offers
novel
approach
assessing
intricate
link
several
influencing
elements
quality,
contrast
conventional
multivariate
statistical
technique.
PLS-SEM
creates
Latent
variables
“IOT
Parameters”,
“Leachate
“Heavy
Metal”
“Groundwater
Quality”
which
quantified
yield
R
2
value.
well
ahead
along
direction
flow
values
ranging
from
24.7–86.5%
located
behind
are
prone
get
due
migration
leachate.
Hence
this
shows
various
affect
quality.
Groundwater for Sustainable Development,
Journal Year:
2023,
Volume and Issue:
23, P. 101037 - 101037
Published: Nov. 1, 2023
The
study
try
to
evaluate
the
susceptibility
of
groundwater.
DRASTIC
model
was
implemented
through
GIS.
Various
input
variables,
such
as
water
table
depth,
net
recharge,
aquifer
and
soil
media,
topography,
vadose
zone
impact,
hydraulic
conductivity,
were
evaluated
within
generate
a
groundwater
vulnerability
map.
Subsequently,
machine-learning
algorithms
(SVM,
RF,
GLM)
employed
using
SDM
package
in
R
software
optimize
method.
To
assess
performance
pollution
risk
models,
training
validation
datasets
ROC
curve.
results
revealed
that
approximately
40%
area
fell
high
range,
while
around
30%
exhibited
moderate
risk.
Evaluation
machine
learning
models
indicated
their
effectiveness
development.
RF
demonstrated
highest
predictive
power,
achieving
an
AUC
0.98.
Additionally,
GLM
SVM
achieved
values
76%.
These
can
serve
efficient
techniques
for
evaluating
managing
resources.
findings
underscored
relatively
poor
quality
area,
with
excessive
exploitation
by
agricultural
sector
infiltration
urban
sewage
industrial
waste
identified
primary
causes
pollution.
implications
these
are
crucial
devising
strategies
implementing
preventive
measures
mitigate
resource
associated
health
risks
central
Iran.