IOP Conference Series Earth and Environmental Science,
Год журнала:
2024,
Номер
1418(1), С. 012055 - 012055
Опубликована: Дек. 1, 2024
Abstract
The
goal
of
this
study
is
to
determine
the
classification
infiltration
for
Micro-Hydro
Power
Planning
using
Random
Forest
(RF)
machine
learning
algorithm.
Utilizing
Landsat
8
satellite
imagery,
data
provides
a
comprehensive
basis
analyzing
various
environmental
factors
relevant
infiltration.
RF
algorithm
models
and
classifies
rates,
ensuring
precise
reliable
predictions
essential
effective
micro-hydro
power
planning.
model
evaluation
results
demonstrate
excellent
performance,
with
an
Overall
Accuracy
0.97
Kappa
Coefficient
0.96,
indicating
strong
agreement
between
predicted
actual
classifications.
High
Sensitivity,
Specificity
(0.99
all
classes),
User
values
(all
above
0.95)
underscore
model’s
ability
correctly
identify
categories
maintain
consistency
in
positive
negative
predictions.
Feature
importance
analysis
highlights
that
certain
spectral
bands
significantly
enhance
predictive
capability,
Band
3
playing
crucial
role
(importance
score
100),
followed
by
Bands
7
6.
These
capture
specific
signatures
associated
different
improving
performance
reliability.
research
contributes
Sustainable
Development
Goals
(SDGs),
supporting
SDG
6
(clean
water
sanitation),
(affordable
clean
energy),
9
(industry,
innovation,
infrastructure),
13
(climate
action),
15
(life
on
land)
through
improved
resource
management
stewardship.
Journal of Environmental Engineering and Science,
Год журнала:
2025,
Номер
unknown, С. 1 - 12
Опубликована: Апрель 18, 2025
In
this
paper,
four
cities
in
India
having
different
geographical
structures,
climates,
and
hydrological
components
were
selected.
An
area
of
500
m
2
from
each
city
has
been
studied.
A
mathematical
model
with
three-dimensional
hydraulic
conductivity,
head
the
aquifer,
other
factors
was
adopted,
which
additional
artificial
recharge
added.
The
is
numerically
solved
help
C++
software,
details
provided
Appendix,
graphs
plotted
to
depict
status
groundwater
level
after
recharge.
It
found
that
during
study
period
2014
2021,
increase
Bhopal
9
m,
for
Jaipur
6
Dehradun
6.5
Bangalore
5
m.
Water Air & Soil Pollution,
Год журнала:
2025,
Номер
236(8)
Опубликована: Июнь 2, 2025
Abstract
This
study
investigates
toxic
metal
contamination
in
the
sediments
of
Değirmendere
River
Basin
(riverbed
and
estuary)
Türkiye,
with
aim
assessing
pollution
levels,
ecological
risks,
seasonal
variability
concentrations.
Sediment
samples
were
collected
from
20
stations
during
summer
winter
2022
analyzed
using
geochemical
statistical
methods.
The
metals
evaluated
include
Cu,
Pb,
Zn,
Ni,
As,
Co,
V,
La.
findings
reveal
that
Cu
(79.46
±
20.17
μg
g
-1
)
Pb
(63.83
15.11
exceeded
thresholds,
highest
concentrations
observed
winter,
particularly
estuarine
areas
affected
by
industrial
urban
activities.
Seasonal
variations
significant
for
Zn
(Mann-Whitney
U,
p
<
0.05),
higher
likely
due
to
increased
runoff
erosion.
Geoaccumulation
Index
(I
geo
Enrichment
Factor
(SEF)
indicated
moderate
As.
risk
index
(RI)
categorized
estuary
as
a
considerable
area,
RI
values
ranging
150
319.2.
These
highlight
anthropogenic
impacts
on
sediment
quality
Basin,
emphasizing
urgent
need
continuous
monitoring
targeted
mitigation
measures.
