Frontiers in Environmental Science,
Год журнала:
2023,
Номер
11
Опубликована: Ноя. 2, 2023
Globally,
communities
and
governments
face
growing
challenges
from
an
increase
in
natural
disasters
worsening
weather
extremes.
Precision
disaster
preparation
is
crucial
responding
to
these
issues.
The
revolutionary
influence
that
machine
learning
algorithms
have
strengthening
catastrophe
response
systems
thoroughly
explored
this
paper.
Beyond
a
basic
summary,
the
findings
of
our
study
are
striking
demonstrate
sophisticated
powers
forecasting
variety
patterns
anticipating
range
catastrophes,
including
heat
waves,
droughts,
floods,
hurricanes,
more.
We
get
practical
insights
into
complexities
applications,
which
support
enhanced
effectiveness
predictive
models
preparedness.
paper
not
only
explains
theoretical
foundations
but
also
presents
proof
significant
benefits
provide.
As
result,
results
open
door
for
governments,
businesses,
people
make
wise
decisions.
These
accurate
predictions
catastrophes
emerging
may
be
used
implement
pre-emptive
actions,
eventually
saving
lives
reducing
severity
damage.
Geocarto International,
Год журнала:
2023,
Номер
38(1)
Опубликована: Май 2, 2023
The
majority
of
people
living
on
earth
rely
groundwater
as
their
primary
supply
water
for
daily
needs.
However,
human
activities
continuously
threaten
this
natural
resource.
In
an
attempt
to
unravel
the
extent
impact
human-related
physicochemical
characteristics
in
Nnewi
and
Awka
urban
clusters
(Nigeria),
several
techniques
were
integrated
study.
Groundwater
samples
warm
acidic
nature.
Concentrations
SO42-,
NO3-,
PO43-,
Cl-,
HCO3-,
Ca2+,
Mg2+,
Na+
K+
within
set
benchmarks.
nutrient
pollution
index
(ranging
from
0.060
0.745),
nitrate
(varying
between
−0.999
−0.790)
0.057
0.630)
estimated
anthropogenic
contamination
showed
low
characteristics.
health
risks
due
ingestion
skin
absorption
nitrate-contaminated
computed
six
age
groups
(6–12
months,
5–10
years,
10–15
15–20
20–60
years
>60
years)
risk
values
that
<
1,
implying
chronic
humans.
cumulative
total
hazard
ranged
0.006
0.787
with
a
mean
value
0.167.
Chemometric
analyses
geochemical
plots
revealed
relationships
variables
sources.
Chadha's
plot
55%
Ca2+-Mg2+-Cl-
waters,
predominating
over
Na+-Cl-
Ca2+-Mg2+-HCO3-
waters.
Bivariate
multivariate
also
indicated
impact.
Furthermore,
principal
component
analysis
R-type
hierarchical
clustering
confirmed
chemistry
quality
mostly
influenced
by
geogenic
processes
than
acts.
Conclusively,
influence
is
low.
These
findings
would
be
useful
future
monitoring
both
clusters.
Frontiers in Environmental Science,
Год журнала:
2023,
Номер
11
Опубликована: Март 3, 2023
Land
degradation
has
become
one
of
the
major
threats
throughout
globe,
affecting
about
2.6
billion
people
in
more
than
100
countries.
The
highest
rate
land
is
Asia,
followed
by
Africa
and
Europe.
Climate
change
coupled
with
anthropogenic
activities
have
accelerated
developing
nations.
In
India,
affected
105.48
million
hectares.
Thus,
modeling
mapping
soil
loss,
assessing
vulnerability
threat
active
erosional
processes
a
region
are
challenges
from
water
conservation
aspects.
present
study
attempted
rigorous
to
estimate
loss
Banas
Basin
Rajasthan
state,
using
GIS-integrated
Revised
Universal
Soil
Loss
Equation
(RUSLE)
equation.
Priority
ranking
was
computed
for
different
watersheds
terms
degree
their
catchments,
so
that
appropriate
measures
can
be
implemented.
total
area
basin
(68,207.82
km
2
)
systematically
separated
into
25
ranging
113.0
7626.8
.
Rainfall
dataset
Indian
Meteorological
Department
30
years
(1990–2020),
FAO
based
map
characterization,
ALOS
PALSAR
digital
elevation
model
topographic
assessment,
Sentinal-2
use
cover
were
integrated
erosion/loss
risk
assessment.
annual
recorded
as
21,766,048.8
tons.
areas
under
very
low
(0–1
t
ha
-1
year
),
(1–5
medium
(5–10
high
(10–50
extreme
(>50
categories
24.2,
66.8,
7.3,
0.9,
0.7%,
respectively,
whereas
respective
average
values
obtained
0.8,
3.0,
6.0,
23.1,
52.0
among
range
1.1–84.9
,
being
(84.9
WS18,
WS10
(38.4
SW25
(34.7
WS23
(17.9
it
lowest
WS8
(1.1
).
WS18
highest/top
priority
rank
considered
first
planning
implementation.
quantitative
results
this
would
useful
implementation
problematic
controlling
through
erosion.
Water,
Год журнала:
2023,
Номер
15(3), С. 558 - 558
Опубликована: Янв. 31, 2023
Flood,
a
distinctive
natural
calamity,
has
occurred
more
frequently
in
the
last
few
decades
all
over
world,
which
is
often
an
unexpected
and
inevitable
hazard,
but
losses
damages
can
be
managed
controlled
by
adopting
effective
measures.
In
recent
times,
flood
hazard
susceptibility
mapping
become
prime
concern
minimizing
worst
impact
of
this
global
threat;
nonlinear
relationship
between
several
causative
factors
dynamicity
risk
levels
makes
it
complicated
confronted
with
substantial
challenges
to
reliable
assessment.
Therefore,
we
have
considered
SVM,
RF,
ANN—three
ML
algorithms
GIS
platform—to
delineate
zones
subtropical
Kangsabati
river
basin,
West
Bengal,
India;
experienced
frequent
events
because
intense
rainfall
throughout
monsoon
season.
our
study,
adopted
are
efficient
solving
non-linear
problems
assessment;
multi-collinearity
analysis
Pearson’s
correlation
coefficient
techniques
been
used
identify
collinearity
issues
among
fifteen
factors.
research,
predicted
results
evaluated
through
six
prominent
statistical
(“AUC-ROC,
specificity,
sensitivity,
PPV,
NPV,
F-score”)
one
graphical
(Taylor
diagram)
technique
shows
that
ANN
most
modeling
approach
followed
RF
SVM
models.
The
values
AUC
model
for
training
validation
datasets
0.901
0.891,
respectively.
derived
result
states
about
7.54%
10.41%
areas
accordingly
lie
under
high
extremely
danger
zones.
Thus,
study
help
decision-makers
constructing
proper
strategy
at
regional
national
mitigate
particular
region.
This
type
information
may
helpful
various
authorities
implement
outcome
spheres
decision
making.
Apart
from
this,
future
researchers
also
able
conduct
their
research
byconsidering
methodology
