Water,
Год журнала:
2024,
Номер
16(10), С. 1422 - 1422
Опубликована: Май 16, 2024
Climate
change
profoundly
impacts
hydrological
systems,
particularly
in
regions
such
as
Croatia,
which
is
renowned
for
its
diverse
geography
and
climatic
variability.
This
study
examined
the
effect
of
climate
on
streamflow
rates
two
Croatian
rivers:
Bednja
Gornja
Dobra.
Using
seasonal
Mann–Kendall
(MK)
tests,
overall
trends
were
evaluated.
Additionally,
innovative
polygon
trend
analysis
(IPTA),
visualization
(IV-ITA),
Bayesian
changepoint
detection
time
series
decomposition
(BEAST)
algorithms
used
to
assess
trends’
magnitudes
transitions.
The
MK
identified
significant
decreasing
trends,
primarily
during
summer.
results
IPTA
IV-ITA
revealed
consistent
throughout
most
months,
with
a
notable
increase
September,
especially
at
high
flow
values.
rivers’
behavior
differed
between
first
second
halves
month.
BEAST
detected
abrupt
changes,
including
earlier
shifts
(1951–1968)
more
recent
ones
(2013–2015)
both
and,
lesser
extent,
Dobra
rivers.
comprehensive
approach
enhances
our
understanding
long-term
short-term
fluctuations
induced
by
change.
Results in Engineering,
Год журнала:
2024,
Номер
22, С. 102104 - 102104
Опубликована: Апрель 10, 2024
Forecasting
streamflows,
essential
for
flood
mitigation
and
the
efficient
management
of
water
resources
drinking,
agriculture
hydroelectric
power
generation,
presents
a
formidable
challenge
in
most
real-world
scenarios.
In
this
study,
two
models,
first
based
on
Additive
Regression
Radial
Basis
Function
Neural
Networks
(AR-RBF)
second
stacking
with
Pace
Multilayer
Perceptron
Random
Forest
(MLP-RF-PR),
were
compared
prediction
short-term
(1–3
days
ahead)
medium-term
(7
daily
streamflow
rates
three
different
rivers
Germany:
Elbe
River
at
Wittenberge,
Leine
Herrenhausen,
Saale
Hof
The
lagged
values
rate,
precipitation
temperature
considered
modeling.
Moreover,
Bayesian
Optimization
(BO)
algorithm
was
used
to
assess
optimal
number
hyperparameters.
Both
models
showed
accurate
predictions
forecasting,
R2
1-day
ahead
ranging
from
0.939
0.998
AR-RBF
0.930
0.996
MLP-RF-PR,
while
MAPE
ranged
2.02
%
8.99
2.14
9.68
when
exogeneous
variables
included.
As
forecast
horizon
increased,
reduction
forecasting
accuracy
observed.
However,
both
could
still
predict
overall
flow
pattern,
even
7-day-ahead
predictions,
0.772
0.871
0.703
0.840
10.60
20.45
10.44
19.65
MLP-RF-PR.
Overall,
outcomes
study
suggest
that
MLP-RF-PR
can
be
reliable
tools
short-
rate
prediction,
requiring
short
parameters
optimized,
making
them
easy
implement
reducing
calculation
time
required.
Water,
Год журнала:
2024,
Номер
16(10), С. 1422 - 1422
Опубликована: Май 16, 2024
Climate
change
profoundly
impacts
hydrological
systems,
particularly
in
regions
such
as
Croatia,
which
is
renowned
for
its
diverse
geography
and
climatic
variability.
This
study
examined
the
effect
of
climate
on
streamflow
rates
two
Croatian
rivers:
Bednja
Gornja
Dobra.
Using
seasonal
Mann–Kendall
(MK)
tests,
overall
trends
were
evaluated.
Additionally,
innovative
polygon
trend
analysis
(IPTA),
visualization
(IV-ITA),
Bayesian
changepoint
detection
time
series
decomposition
(BEAST)
algorithms
used
to
assess
trends’
magnitudes
transitions.
The
MK
identified
significant
decreasing
trends,
primarily
during
summer.
results
IPTA
IV-ITA
revealed
consistent
throughout
most
months,
with
a
notable
increase
September,
especially
at
high
flow
values.
rivers’
behavior
differed
between
first
second
halves
month.
BEAST
detected
abrupt
changes,
including
earlier
shifts
(1951–1968)
more
recent
ones
(2013–2015)
both
and,
lesser
extent,
Dobra
rivers.
comprehensive
approach
enhances
our
understanding
long-term
short-term
fluctuations
induced
by
change.
