Ecological Informatics,
Год журнала:
2024,
Номер
80, С. 102512 - 102512
Опубликована: Фев. 4, 2024
Meteorological
drought
serves
as
the
precursor
to
hydrological
drought.
Clarifying
propagation
characteristics
from
meteorological
is
crucial
for
predicting
and
mitigating
this
severe
natural
disaster.
In
study,
we
proposed
an
assessment
framework
that
integrates
both
linear
nonlinear
methods
characterize
transition
in
terms
of
response
time,
effective
transformation
rate,
threshold.
Utilizing
ERA5
land
reanalysis
data
(1951–2022)
focusing
on
Hanjiang
River
Basin
China,
analyzed
features
with
without
inter-basin
water
diversion.
Extracted
event
pairs
indicate
a
more
significant
does
not
necessarily
result
drought,
vice
versa,
which
confirms
The
times
derived
using
method
are,
average,
two
months
shorter
than
those
method.
Inter-basin
diversion
will
weaken
correlation
while
strengthening
correlation.
When
annual
exceeds
12.0
billion
m3,
time
experience
sudden
reduction.
This
research
provides
scientific
reference
basin-scale
resource
management
mitigation
practice.
Geophysical Research Letters,
Год журнала:
2024,
Номер
51(4)
Опубликована: Фев. 20, 2024
Abstract
Subseasonal
droughts
including
flash
have
occurred
frequently
in
recent
years,
which
are
accompanied
by
heatwaves
or
wildfires
that
raise
a
wide
concern
on
environmental
risk.
However,
the
changing
characteristics
of
subseasonal
drought
propagation,
and
possible
climate
drivers
remain
unknown.
This
study
quantifies
propagation
from
meteorological
to
soil
using
Copula‐based
Bayesian
framework,
shows
higher
risks
mainly
occur
more
humid
regions
with
denser
vegetation
cover.
Trends
risk
vary
regionally,
global
increase
2%/decade
(
p
<
0.01)
during
1980–2022.
Vegetation
greening
warming
key
over
>71%
vegetated
lands,
mean
contribution
rates
39.5%
36.5%
respectively.
Other
climatic
factors
vapor
pressure
deficit
precipitation
also
paly
critical
roles,
closely
correlate
temperature
vegetation.
These
findings
highlight
importance
dynamics.
Global
warming
accelerates
water
cycle,
causing
more
droughts
globally
that
challenge
monitoring
and
forecasting.
The
Standardized
Precipitation
Evapotranspiration
Index
(SPEI)
is
used
to
assess
drought
characteristics
response
time
of
natural
economic
systems
at
various
timescales.
However,
existing
SPEI
datasets
have
coarse
spatial
or
temporal
resolution
limited
extent,
restricting
their
ability
accurately
identify
the
start
end
dates
extent
global
scale.
To
narrow
these
gaps,
we
developed
a
daily
dataset
(SPEI-GD),
with
0.25°
from
1982
2021
multiple
timescales
(5,
30,
90,
180
360
days),
based
on
precipitation
European
Center
for
Medium
Weather
Forecasting
Reanalysis
V5
(ERA5)
potential
evapotranspiration
Singer's
dataset.
Compared
widely
SPEIbase
dataset,
SPEI-GD
can
improve
spatial-temporal
accuracy
in
areas
where
meteorological
sites
are
lacking.
significantly
correlates
site-based
soil
moisture.
Our
solidly
supports
sub-seasonal
daily-scale
regional
research.
