Water Science & Technology Water Supply,
Год журнала:
2023,
Номер
23(8), С. 3359 - 3376
Опубликована: Июль 31, 2023
Abstract
Highly
accurate
rainfall
prediction
can
provide
a
reliable
scientific
basis
for
human
production
and
life.
For
the
characteristics
of
occasional
sudden
changes
in
coastal
hilly
areas,
this
article
chooses
four
cities
eastern
Zhejiang
province
as
object
study
establishes
model
based
on
variational
mode
decomposition
(VMD),
reptile
search
algorithm
(RSA),
differentiable
neural
computer
(DNC).
The
VMD
reduces
complexity
sequence
data;
RSA
is
used
to
find
best-fit
function;
DNC
combines
advantages
recurrent
network
computational
processing
improve
problem
memory
forgetting
long
short-term
memory.
To
verify
accuracy
model,
results
are
compared
with
other
three
models,
show
that
VMD–RSA–DNC
has
best
maximum
minimum
relative
errors
9.62
0.17%,
respectively,
average
root-mean-square
error
5.43,
mean
absolute
percentage
3.59%,
Nash–Sutcliffe
efficiency
0.95
predicting
area.
This
provides
new
reference
method
construction
models.
Heliyon,
Год журнала:
2024,
Номер
10(20), С. e37965 - e37965
Опубликована: Сен. 30, 2024
Accurate
prediction
of
daily
river
flow
(Q
t
)
remains
a
challenging
yet
essential
task
in
hydrological
modeling,
particularly
crucial
for
flood
mitigation
and
water
resource
management.
This
study
introduces
an
advanced
M5
Prime
(M5P)
predictive
model
designed
to
estimate
Q
as
well
one-
two-day-ahead
forecasts
(i.e.
t+1
t+2
).
The
performance
M5P
ensembles
incorporating
Bootstrap
Aggregation
(BA),
Disjoint
Aggregating
(DA),
Additive
Regression
(AR),
Vote
(V),
Iterative
classifier
optimizer
(ICO),
Random
Subspace
(RS),
Rotation
Forest
(ROF)
were
comprehensively
evaluated.
proposed
models
applied
case
data
Tuolumne
County,
US,
using
dataset
comprising
measured
precipitation
(P
),
evaporation
(E
t),
.
A
wide
range
input
scenarios
explored
predicting
,
t+1,
t+2.
Results
indicate
that
P
significantly
influence
accuracy.
Notably,
relying
solely
on
the
most
correlated
variable
(e.g.,
t-1)
does
not
guarantee
robust
However,
extending
forecast
horizon
mitigates
low-correlation
variables
Performance
metrics
DA-M5P
achieves
superior
results,
with
Nash-Sutcliff
Efficiency
0.916
root
mean
square
error
23
m3/s,
followed
by
ROF-M5P,
BA-M5P,
AR-M5P,
RS-M5P,
V-M5P,
ICO-M5P,
standalone
model.
ensemble
modeling
framework
enhanced
capability
stand-alone
algorithm
1.2
%-22.6
%,
underscoring
its
efficacy
potential
advancing
forecasting.
Climate Dynamics,
Год журнала:
2023,
Номер
61(11-12), С. 5035 - 5048
Опубликована: Июнь 4, 2023
Abstract
The
present
study
investigates
the
influence
of
different
atmospheric
teleconnections
on
annual
precipitation
variability
in
Northeast
Brazil
(NEB)
based
data
from
Global
Precipitation
Climatology
Center
(GPCC)
1901
to
2013.
objective
this
is
analyze
total
NEB
for
1901–2013
period,
considering
physical
characteristics
four
subregions,
i.e.,
Mid-north,
Backwoods,
Agreste,
and
Forest
zone.
To
teleconnections,
GPCC
were
used,
behavior
was
assessed
using
Pearson
correlation
coefficient,
Rainfall
Anomaly
Index
(RAI),
cross-wavelet
analysis.
used
studied
region.
RAI
calculate
frequency
patterns
drought
episodes.
analysis
applied
identify
similarity
signals
between
series
teleconnections.
results
according
Student's
t
test
showed
that
Atlantic
Multidecadal
Oscillation
(AMO)
exerts
a
more
significant
Backwoods
region
at
an
interannual
scale.
In
contrast,
Pacific
Decadal
(PDO)
greater
control
over
modulation
climatic
NEB.
are
insightful
reveal
differential
impacts
such
as
AMO,
PDO,
MEI,
NAO
sub-regions
circulation
strongly
interdecadal
Mid-north
regions,
possibly
associated
with
Intertropical
Convergence
Zone
(ITCZ)
position.
Finally,
contributes
understanding
internal
planning
water
resources
agricultural
activities
Graphic
abstract
