Journal of Hydrology and Hydromechanics,
Journal Year:
2023,
Volume and Issue:
71(3), P. 271 - 282
Published: Aug. 10, 2023
Abstract
This
study
compares
the
flood
regime
of
rivers
in
Ukraine
and
Austria
over
last
decades.
We
used
data
from
mountain
lowland
watersheds,
where
floods
are
caused
by
different
processes.
In
order
to
identify
possible
shifts
day
occurrence
annual
maxima,
we
apply
kernel
density
method
time
series
two
subperiods
(1960–1987
1988–2015).
use
Mann
Kendall
test
at
a
5%
significance
level
significant
positive
or
negative
trends
maximum
discharges.
Austria,
observe
an
increasing
trend
summer
associated
with
precipitation.
areas
Ukraine,
clear
reduction
spring
is
observed,
linked
shallower
snow
packs
warming
climate.
Ukrainian
Carpathians,
on
other
hand,
occur
throughout
year,
increase
portion
liquid
precipitation
during
cold
period
year
leads
earlier
probability
flooding
winter.
Geographies,
Journal Year:
2025,
Volume and Issue:
5(2), P. 16 - 16
Published: April 1, 2025
Floods
represent
a
significant
threat
to
the
livelihoods
of
individuals
and
pose
challenges
global
development
prospects.
An
individual’s
age
is
an
essential
predictor
for
adopting
flood
preparedness
measures.
In
this
context,
present
study
aims
identify
community
resilience
based
on
age.
Two
groups
were
considered
analysis,
i.e.,
young
group
(age
less
than
24
years)
adult
over
years),
using
Flood
Resilience
Index
(FRI)
approach
through
five
dimensions
resilience,
natural,
physical,
economic,
social,
institutional.
The
data
analysis
included
200
respondents,
with
each
compromise
equaling
100
from
both
groups.
A
total
34
structured
questions
analyzed
FRI
dimensions.
survey
results
show
that
overall
in
low,
but
adults
are
relatively
more
flood-resilient
group.
Moreover,
all
differences
between
two
groups,
appearing
resilient
shows
local
authorities
protection
bodies
should
focus
community’s
youth
regarding
risks
flooding.
Natural hazards and earth system sciences,
Journal Year:
2025,
Volume and Issue:
25(4), P. 1353 - 1375
Published: April 9, 2025
Abstract.
Flooding
is
the
natural
hazard
most
likely
to
affect
individuals
and
can
be
driven
by
rainfall,
river
discharge,
storm
surge,
tides,
waves.
Compound
floods
result
from
their
co-occurrence
generate
a
larger
flood
when
compared
synthetic
generated
respective
drivers
occurring
in
isolation
one
another.
Current
state-of-the-art
stochastic
compound
risk
assessments
are
based
on
statistical,
hydrodynamic,
impact
simulations.
However,
nature
of
some
key
variables
flooding
process
often
not
accounted
for
as
adding
exponentially
increases
computational
costs
(i.e.,
curse
dimensionality).
These
simplifications
(e.g.,
constant
driver
duration
or
time
lag
between
drivers)
may
lead
mis-quantification
risk.
This
study
develops
conceptual
framework
that
allows
better
representation
while
limiting
increase
overall
time.
After
generating
events
statistical
model
fitted
selected
drivers,
proposed
applies
treed
Gaussian
(TGP).
A
TGP
uses
active
learning
explore
uncertainty
associated
with
response
damages
events.
Thereby,
it
informs
regarding
best
choice
hydrodynamic
simulations
run
reduce
damages.
Once
predicts
damage
all
within
tolerated
range,
calculated.
As
proof
concept,
was
applied
case
Charleston
County
(South
Carolina,
USA)
model,
which
used
equidistant
sampling
linear
scatter
interpolation.
The
decreased
factor
4
root
mean
square
error
8.
With
reduction
errors,
additional
such
drivers'
were
included
assessment.
Not
accounting
these
resulted
an
underestimation
11.6
%
(USD
25.47
million)
expected
annual
(EAD).
Thus,
accelerating
learning,
presented
here
more
comprehensive
loosens
constraints
imposed
dimensionality.
Hydrological Processes,
Journal Year:
2025,
Volume and Issue:
39(4)
Published: April 1, 2025
ABSTRACT
Floods
are
amplified
and
attenuated
by
features
processes
across
spatial
scales,
defined
here
as
flood
dynamics.
We
review
synthesise
these
influences
at
the
catchment,
river
network
reach
scales
a
means
of
integrating
understanding
controls
on
dynamics
identifying
key
questions
that
arise
because
differences
in
techniques
investigation
disciplinary
emphases
between
scales.
Catchment‐scale
include
catchment
area,
topography,
lithology,
land
cover,
precipitation,
antecedent
conditions
human
alterations
such
changing
cover.
Network‐scale
topology,
longitudinal
variations
geometry
successive
corridor
reaches,
lakes
wetlands
including
flow
regulation
cumulative
changes
channel‐floodplain
connectivity
multiple
reaches
network.
Reach‐scale
water
sources,
artificial
levees,
channelisation,
bank
stabilisation,
to
floodplain
cover
drainage,
dike
operation,
process‐based
restoration
urban
stormwater
management.
Our
synthesis
relevant
literature
suggest
relative
importance
varies
Hillslope
response
may
dominate
hydrograph
characteristics
smaller
catchments,
for
example,
whereas
exert
progressively
stronger
with
increasing
size.
Scale‐specific
advances
dynamics,
rainfall‐runoff
analyses
movements
from
uplands
into
channel
networks
(catchment‐scale),
along
(network‐scale)
investigations
biophysical
feedbacks
hydraulic
roughness
(reach‐scale),
have
largely
contributed
but
there
remain
important
disconnects
diverse
bodies
research
outstanding
related
effects
Journal of Hydrology and Hydromechanics,
Journal Year:
2023,
Volume and Issue:
71(3), P. 271 - 282
Published: Aug. 10, 2023
Abstract
This
study
compares
the
flood
regime
of
rivers
in
Ukraine
and
Austria
over
last
decades.
We
used
data
from
mountain
lowland
watersheds,
where
floods
are
caused
by
different
processes.
In
order
to
identify
possible
shifts
day
occurrence
annual
maxima,
we
apply
kernel
density
method
time
series
two
subperiods
(1960–1987
1988–2015).
use
Mann
Kendall
test
at
a
5%
significance
level
significant
positive
or
negative
trends
maximum
discharges.
Austria,
observe
an
increasing
trend
summer
associated
with
precipitation.
areas
Ukraine,
clear
reduction
spring
is
observed,
linked
shallower
snow
packs
warming
climate.
Ukrainian
Carpathians,
on
other
hand,
occur
throughout
year,
increase
portion
liquid
precipitation
during
cold
period
year
leads
earlier
probability
flooding
winter.