Evaluation
of
precipitation
events
is
essential
for
predicting
severe
droughts
and
floods,
particularly
in
the
context
global
warming.
We
concluded
a
comprehensive
temporal
spatial
evaluation
concentration
index
(CI),
quantified
contribution
rates
anomalies
atmospheric
circulation
patterns
to
CI,
investigated
CI'
relationship
with
drought
flood
using
standardized
(SPI)
across
rainstorm-prone,
arid,
transition
regions.
The
findings
are
as
follows:
1)
Globally,
CI
amounts
exhibited
similar
distributions,
analysis
indicating
an
increasing
trend
extreme
precipitation.
2)
Significant
variations
were
observed
influence
factors
on
different
Antarctic
Oscillation
(AAO)
predominantly
influenced
concentration.
3)
proved
effective
assessing
frequency
intensities,
but
should
not
serve
sole
indicator
floods;
complementary
indicators
necessary
likelihood.
This
study
enhances
our
understanding
provides
novel
insights
into
water
resources
management,
ecological
conservation,
river
basin
prevention
strategies.
Water,
Journal Year:
2024,
Volume and Issue:
16(15), P. 2161 - 2161
Published: July 31, 2024
Runoff
simulation
is
essential
for
effective
water
resource
management
and
plays
a
pivotal
role
in
hydrological
forecasting.
Improving
the
quality
of
runoff
forecasting
continues
to
be
highly
relevant
research
area.
The
complexity
terrain
scarcity
long-term
observation
data
have
significantly
limited
application
Physically
Based
Models
(PBMs)
Qinghai–Tibet
Plateau
(QTP).
Recently,
Long
Short-Term
Memory
(LSTM)
network
has
been
found
learning
dynamic
characteristics
watersheds
outperforming
some
traditional
PBMs
simulation.
However,
extent
which
LSTM
works
data-scarce
alpine
regions
remains
unclear.
This
study
aims
evaluate
applicability
basins
QTP,
as
well
performance
transfer-based
(T-LSTM)
regions.
Lhasa
River
Basin
(LRB)
Nyang
(NRB)
were
areas,
model
was
compared
that
by
relying
solely
on
meteorological
inputs.
results
show
average
values
Nash–Sutcliffe
efficiency
(NSE),
Kling–Gupta
(KGE),
Relative
Bias
(RBias)
B-LSTM
0.80,
0.85,
4.21%,
respectively,
while
corresponding
G-LSTM
0.81,
0.84,
3.19%.
In
comparison
PBM-
Block-Wise
use
TOPMEDEL
(BTOP),
an
enhancement
0.23,
0.36,
−18.36%,
respectively.
both
basins,
outperforms
BTOP
model.
Furthermore,
transfer
learning-based
at
multi-watershed
scale
demonstrates
that,
when
input
are
somewhat
representative,
even
if
amount
limited,
T-LSTM
can
obtain
more
accurate
than
models
specifically
calibrated
individual
watersheds.
result
indicates
effectively
improve
applied
Agronomy,
Journal Year:
2024,
Volume and Issue:
14(9), P. 2128 - 2128
Published: Sept. 19, 2024
Global
climate
change
is
intensifying
and
extreme
weather
events
are
occurring
frequently,
with
far-reaching
impacts
on
agricultural
production.
The
Songnen
Plain,
as
an
important
maize
production
region
in
China,
faces
challenges
posed
by
change.
This
study
aims
to
explore
the
effects
of
extremes
yield
provide
a
scientific
basis
for
adaptation
agriculture
this
region.
focuses
spatial
temporal
evolution
characteristics
during
reproductive
period
from
1988
2020
Plain
their
yield.
Daily
temperature
precipitation
data
11
meteorological
stations
were
selected
combined
information
assess
trends
indices
using
statistical
methods
such
moving
average
Mann–Kendall
(M-K)
mutation
test.
Pearson
correlation
analysis
random
forest
algorithm
also
used
quantify
degree
influence
results
showed
that
(1)
heat
humidity
(TN90p,
TX90p,
CWD,
R95p,
R10,
SDII)
tended
increase,
while
cold
(TN10p,
TX10p)
drought
(CDD)
decreasing
trend,
suggesting
tends
be
warmer
more
humid.
(2)
pattern
being
higher
north
lower
south
west
east,
warm
opposite,
east
west.
(3).
Both
trend
significant
upward
trend.
Maize
fluctuating
downward
within
range
−1.64~0.79
t/hm2.
During
33
years,
there
three
climatic
abundance
two
failure
rest
years
normal
years.
(4)
index
TN10p
TN90p
CWD
significantly
correlated
yield,
which
had
highest
positive
comprehensive
analysis,
importance
was
order
TN90p,
TN10p,
CWD.
demonstrates
impact
providing
local
management
decision-making,
helping
formulate
response
strategies
mitigate
negative
climate,
ensure
food
security,
promote
sustainable
development.
