Abstract.
In
response
to
flood
risk,
design
estimation
is
a
cornerstone
of
planning,
infrastructure
design,
setting
insurance
premiums
and
emergency
planning.
Under
stationary
assumptions,
guidance
the
methods
used
in
are
firmly
established
practice
mature
their
theoretical
foundations,
but
under
climate
change,
still
its
infancy.
Human-caused
change
influencing
factors
that
contribute
risk
such
as
rainfall
extremes
soil
moisture,
there
need
for
updated
guidance.
However,
barrier
updating
translation
science
into
practical
application.
For
example,
most
focuses
on
examining
trends
annual
maximum
events,
or
application
non-stationary
frequency
analysis.
Although
this
valuable,
exceedance
probabilities
much
rarer
than
1
%
probability
event
even
rarer,
using
rainfall-based
procedures,
at
locations
where
little
no
observations
streamflow.
Here,
we
perform
systematic
review
summarise
state-of-the-art
understanding
impact
Australian
context,
while
also
drawing
international
literature.
addition,
meta-analysis,
whereby
results
from
multiple
studies
combined,
conducted
extreme
provide
quantitative
estimates
possible
future
changes.
This
information
described
context
contemporary
practice,
facilitate
inclusion
practice.
Hydrology and earth system sciences,
Journal Year:
2024,
Volume and Issue:
28(5), P. 1251 - 1285
Published: March 15, 2024
Abstract.
In
response
to
flood
risk,
design
estimation
is
a
cornerstone
of
planning,
infrastructure
design,
setting
insurance
premiums,
and
emergency
planning.
Under
stationary
assumptions,
guidance
the
methods
used
in
are
firmly
established
practice
mature
their
theoretical
foundations,
but
under
climate
change,
still
its
infancy.
Human-caused
change
influencing
factors
that
contribute
risk
such
as
rainfall
extremes
soil
moisture,
there
need
for
updated
guidance.
However,
barrier
updating
translation
science
into
practical
application.
For
example,
most
pertaining
historical
changes
focuses
on
examining
trends
annual
maximum
events
or
application
non-stationary
frequency
analysis.
Although
this
valuable,
practice,
exceedance
probabilities
much
rarer
than
events,
1
%
probability
event
even
rarer,
using
rainfall-based
procedures,
at
locations
where
few
no
observations
streamflow.
Here,
we
perform
systematic
review
summarize
state-of-the-art
understanding
impact
Australian
context,
while
also
drawing
international
literature.
addition,
meta-analysis,
whereby
results
from
multiple
studies
combined,
conducted
extreme
provide
quantitative
estimates
possible
future
changes.
This
information
described
context
contemporary
facilitate
inclusion
practice.
Journal of Geophysical Research Atmospheres,
Journal Year:
2024,
Volume and Issue:
129(4)
Published: Feb. 8, 2024
Abstract
The
unprecedented
2022
Yangtze
River
Basin
(YRB)
heatwave
is
a
threat
to
human
society
and
natural
ecology,
so
the
understanding
of
its
underlying
drivers
critical
regional
climate
adaptation
resilience.
Here
we
conducted
multi‐method
attribution
analysis
on
contribution
atmospheric
circulation
change
anthropogenic
impacts
occurrence
probability
intensity
this
extreme
heatwave.
Based
nonstationary
statistical
analysis,
YRB
1‐in‐900‐year
event
1‐in‐110‐year
with
without
considering
in
fitting,
respectively.
large‐scale
meteorological
condition
shows
that
featured
an
anomalous
high‐pressure
system
favors
hot
dry
column,
overlaid
by
subsidence
clear
skies
which
leads
warming
greater
solar
heating.
ensemble
constructed
analogue
analyses
show
anomaly
fails
explain
observed
SAT
anomalies
fully.
Specifically,
46%
(0.132
±
0.027°C
decade
−1
)
trend
during
1979–2022
(0.290
0.048°C
caused
associated
thermodynamic
feedback,
while
remaining
54%
(0.157
0.038°C
changes
circulation.
Our
findings
patterns
contributions
could
provide
valuable
information
for
mitigation
strategies
context
climate.
Journal of Flood Risk Management,
Journal Year:
2025,
Volume and Issue:
18(1)
Published: Jan. 17, 2025
ABSTRACT
Devastating
flood
events
are
recurrently
impacting
West
Africa.
To
mitigate
impacts
and
reduce
the
vulnerability
of
populations,
a
better
knowledge
on
frequency
these
is
crucial.
The
lack
reliable
hydrometric
datasets
has
hitherto
been
major
limitation
in
analysis
at
scale
Utilising
recently
developed
African
database,
we
perform
annual
maximum
flow
(AMF)
time
series,
covering
246
river
basins
Africa,
between
1975
2018.
Generalized
extreme
value
(GEV)
Gumbel
probability
distributions
were
compared
to
fit
AMF
series
with
L‐moments,
Maximum
Likelihood
(MLE)
(GMLE)
methods.
Results
indicated
that
GEV
distribution
GMLE
method
provided
best
results.
Regional
envelope
curves
entire
region
unprecedented
data
coverage
have
generated
for
first‐time
providing
insights
estimation
quantiles
ungauged
basins.
correlation
watershed
properties
shows
significant
correlations
catchment
area,
groundwater
storage,
altitude
topographic
wetness
index.
findings
from
this
study
useful
risk
assessment
design
hydraulic
infrastructures
region,
first
step
prior
development
regional
approaches
transfer
information
gauged
sites
catchments.
Water Resources Research,
Journal Year:
2025,
Volume and Issue:
61(2)
Published: Feb. 1, 2025
Abstract
Extreme
rainfall
events
have
profound
implications
across
various
sectors,
necessitating
accurate
modeling
to
assess
risks
and
devise
effective
adaptation
strategies.
The
common
practice
of
employing
three‐parameter
probability
distributions,
such
as
the
Generalized
Value
(GEV)
Pearson
Type
III
in
frequency
analysis
often
encounters
limitations
capturing
rare,
heavy‐tailed
with
a
lack
consensus
which
distribution
is
most
applicable.
In
this
study,
we
explore
applicability
four‐parameter
Kappa
(K4D)
for
extreme
daily
rainfalls
using
annual
maxima
from
Global
Historical
Climatology
Network‐Daily
database.
Quality
checks
thresholds
were
used
remove
erroneous
poor‐quality
data,
retaining
20,500
stations
50
or
more
years
data.
variation
second
shape
parameter
()
was
examined
regime
characteristics,
geospatial
regions,
climate
regional
groupings
identify
where
K4D
best
able
model
rainfalls.
Consistent
theoretical
expectations,
converges
toward
zero
(i.e.,
limiting
GEV
distribution)
average
number
per
year
increases
(here
approximated
by
rain
days).
However,
arid
regions
limited
storm
events,
observe
values
greater
than
zero,
strong
climatic
coherence
.
Our
results
suggest
that
there
merit
heavy
tail
behavior,
particularly
small
year.
These
findings
will
contribute
advancing
statistical
techniques
rainfall,
benefiting
hydrological
risk
assessments.
Journal of Hydrology,
Journal Year:
2024,
Volume and Issue:
636, P. 131309 - 131309
Published: May 10, 2024
Flood
estimates
used
in
engineering
design
are
commonly
based
on
intensity–duration–frequency
(IDF)
curves
derived
from
historical
extreme
rainfalls.
Under
global
warming
these
rainfalls
increasing,
threatening
the
capacity
of
existing
infrastructure
to
resist
failure
as
IDF
traditionally
assume
no
change
rainfall
magnitude.
Hence,
there
is
a
need
investigate
implications
non-stationarity
derive
IDFs
across
storm
durations
and
annual
exceedance
probabilities
(AEPs).
One
way
doing
this
incorporate
covariates
into
fitted
probability
distribution.
However,
few
studies
which
examine
using
large-scale
climate
drivers
covariates,
with
little
consensus
covariate
most
appropriate.
Here
we
evaluate
different
durations,
1
2
AEP
100
AEP,
potential
including
continental
mean
temperature,
diurnal
temperature
range,
dewpoint
precipitable
water,
Indian
Ocean
Dipole,
El
Niño
Southern
Oscillation,
Annular
Mode.
These
linked
three
parameters
Generalized
Extreme
Value
distribution
identify
appropriate
form
non-stationary
model.
We
analyse
16
6
min
7
day
maxima
46
stations
Australia.
Based
Akaike
Information
Criteria,
water
superior
at
large
proportion
irrespective
duration.
when
modelled
quantile
changes
inspected,
only
able
adequately
capture
variability
both
duration
probability.
Further,
regional
average
values
were
was
improvement
model
performance
compared
continental-wide
particularly
for
short
durations.
The
results
show
that
stationary
underestimated
by
12
%
–
9
frequent
(1
5
AEP)
23
13
rare
(6
30
min)
events.
Moving
forward
our
suggests
needs
ensure
flood
planning
levels
not
under-designed.
Abstract
Extreme
precipitation
events
are
widely
held
to
become
more
intense
and
frequent
as
a
result
of
climate
change,
which
will
have
major
impacts
for
future
flooding
with
implications
the
environment,
infrastructure,
agriculture,
human
life.
We
investigated
projected
changes
daily
mean,
moderately
extreme
(99th
99.7th
percentile),
rare
(Annual
Exceedance
Probability
(AEP)
1
in
10,
50,
100)
across
Australia
its
greater
capital
cities,
where
approximately
two
thirds
Australian
population
reside.
used
dynamically
downscaled
CMIP6
simulations
from
4
modelling
groups
Australia.
This
large
ensemble
consists
19
different
host
models
using
3
distinct
regional
5
configurations,
making
an
39
simulations.
The
mean
were
quantified
at
each
grid
cell
according
rate
change
per
degree
global
warming.
largest
increases
extremes
seen
over
northern
Australia,
100
AEP
event
Darwin
increase
by
11.9%
K−
1
12.2%
averages,
respectively.
Other
cities
had
lower
but
still
substantial
(7.6%
Brisbane,
7.3%
Sydney,
3.4%
Melbourne,
4.4%
Perth).
Large
spatial
differences
noted
among
ensembles,
showing
varying
patterns
magnitudes
change.
These
results
highlight
influence
downscaling
approach
determining
show
need
consider
ensembles
ensure
uncertainties
methods
can
be
accounted
for.
findings
inform
decision
around
flood
management,
urban
planning,
water
supply
agriculture
addition
revealing
globally
relevant
scientific
insights.
