From meteorological to agricultural drought: Propagation time and influencing factors over diverse underlying surfaces based on CNN-LSTM model
Ecological Informatics,
Год журнала:
2024,
Номер
82, С. 102681 - 102681
Опубликована: Июнь 17, 2024
As
global
warming
intensifies
and
extreme
weather
events
become
more
frequent,
the
severity
of
drought
conditions
in
China's
Xinjiang
region
has
escalated.
This
exacerbates
socio-economic
pressures
area
presents
increasingly
formidable
challenges
for
future.
In
response
to
these
challenges,
researching
phenomena
is
imperative.
study
employs
Bayesian
methods
copula
functions
estimate
propagation
time.
It
utilizes
a
hybrid
deep
learning
model
(CNN-LSTM)
analyze
process
its
influencing
factors
across
four
land
cover
types:
crops,
forest
land,
grassland,
unused
land.
The
findings
indicate
that
Cropland
experiences
longest
average
time
(5.27
months),
while
forests
have
shortest
duration
(4.2
months).
Unused
grassland
exhibit
similar
durations
(4.8
On
an
annual
scale,
each
type
manifests
two
phases:
from
January
May
June
December.
former
phase
shows
ranging
6
9
months,
latter
ranges
1
5
months;
both
demonstrate
increasing
trend
over
Seasonally,
all
Land
Cover
Types
pattern
shorter
times
summer
autumn
compared
with
winter
spring.
Moreover,
longer
correlates
greater
disparity
between
meteorological
resultant
agricultural
severity.
analyzing
influence
on
propagation,
soil
moisture
content
El
Niño-Southern
Oscillation(ENSO)
were
found
significantly
impact
Types,
progressively
strengthening
their
years.
Язык: Английский
Dynamic evolution of meteorological and hydrological droughts under climatic and anthropogenic pressures in water‐scarce regions
Hydrological Processes,
Год журнала:
2024,
Номер
38(10)
Опубликована: Окт. 1, 2024
Abstract
Climate
change
and
anthropogenic
influences
amplify
drought
complexity,
entangle
non‐stationarity
(NS)
further
challenge
comprehension.
This
study
aims
to
understand
the
dynamic
evolution
of
propagation
patterns
due
climatic
pressures
by
assessing
non‐stationary
linkages
between
hydrological
variables
characteristics.
It
employs
four
standardized
indicators
comprehensively
examine
spatio‐temporal
meteorological
(MD)
(HD)
Data
from
29
semi‐arid
catchments
six
river
basins
in
Peninsular
India,
are
analyzed
uncover
distinct
patterns.
utilizes
a
novel
Non‐overlapping
Block‐stratified
Random
Sampling
(NBRS)
approach
detect
NS
characteristics
variables,
shedding
light
on
underlying
drivers
this
behavior.
The
results
indicate
similarities
behavior
for
Sabarmati,
Mahi
Tapi
(SMT)
compared
with
Godavari,
Krishna
Pennar
(GKP)
basins,
shorter
(longer)
times
noted
SMT
basins.
While
HD
severity
decreases
over
time
it
intensifies
GKP
which
linked
intensive
interventions
such
as
regulation
reservoir
operations,
thus
resulting
prolonged
intensified
droughts.
Rainfall
primarily
exhibits
time‐invariance,
while
significant
is
observed
potential
evapotranspiration
(particularly
basins),
streamflow
baseflow
across
all
also
identified
three
these
highlighting
cases
where
MD
did
not
transition
HD,
instances
occurring
without
preceding
synchronous
HD.
outcomes
provide
profound
insights
into
dynamics
under
pressures,
will
aid
policymakers
stakeholders
formulating
strategies
preparedness
response.
Язык: Английский
Multi-scale characteristics of drought propagation from meteorological to hydrological phases: variability and impact in the Upper Mekong Delta, Vietnam
Natural Hazards,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 14, 2024
Язык: Английский
Probability links between meteorological drought and hydrological drought from a 3D perspective
Journal of Hydrology Regional Studies,
Год журнала:
2024,
Номер
56, С. 102001 - 102001
Опубликована: Окт. 10, 2024
Язык: Английский
Multi-index evaluation of drought conditions in Northeastern Algeria using remote sensing tool
STUDIES IN ENGINEERING AND EXACT SCIENCES,
Год журнала:
2024,
Номер
5(2), С. e11707 - e11707
Опубликована: Дек. 6, 2024
Drought
is
a
complex
natural
disaster
with
profound
impacts
on
environmental,
social,
and
economic
systems
globally.
This
research
investigates
drought
conditions
in
the
Koudiet
Mdaouar
Basin,
located
northeastern
Algeria,
through
comprehensive
analysis
of
satellite-derived
indicators
from
2019
to
2023.
Employing
advanced
remote
sensing
GIS-based
methodological
approaches,
study
systematically
evaluates
vegetation
health,
thermal
stress
patterns,
water
resource
dynamics,
particular
focus
reservoir
region.
The
reveals
significant
progressive
decline
ecological
conditions,
characterized
by
deteriorating
cover,
intensified
stress,
severe
scarcity.
These
findings
not
only
highlight
region's
environmental
vulnerability
but
also
demonstrate
intricate
interplay
between
climatic
changes
local
ecosystem
dynamics.
emphasizes
necessity
developing
adaptive
policies
underscores
potential
integrated
satellite
ground-based
observation
techniques
for
more
precise
assessments,
offering
critical
insights
management
climate
resilience
strategies.
Язык: Английский