Bulletin of the American Meteorological Society,
Journal Year:
2021,
Volume and Issue:
102(11), P. E2086 - E2105
Published: July 8, 2021
Abstract
Better
understanding
and
quantification
of
river
floods
for
very
local
“flashy”
events
calls
modeling
capability
at
fine
spatial
temporal
scales.
However,
long-term
discharge
records
with
a
global
coverage
suitable
extreme
analysis
are
still
lacking.
Here,
grounded
on
recent
breakthroughs
in
runoff
hydrology,
modeling,
high-resolution
hydrography,
climate
reanalysis,
we
developed
3-hourly
record
globally
2.94
million
reaches
during
the
40-yr
period
1980–2019.
The
underlying
chain
consists
VIC
land
surface
model
(0.05°,
3-hourly)
that
is
well
calibrated
bias
corrected
RAPID
routing
(2.94
catchment
vectors),
precipitation
input
from
MSWEP
other
meteorological
fields
downscaled
ERA5.
Flood
(above
2-yr
return)
their
characteristics
(number,
distribution,
seasonality)
were
extracted
studied.
Validations
against
flow
6,000+
gauges
CONUS
daily
14,000+
show
good
performance
across
all
ranges,
skills
reconstructing
flood
(high
extremes),
benefit
(and
need
for)
subdaily
modeling.
This
data
record,
referred
as
Global
Reach-Level
Reanalysis
(GRFR),
publicly
available
https://www.reachhydro.org/home/records/grfr
.
Annals of the New York Academy of Sciences,
Journal Year:
2020,
Volume and Issue:
1472(1), P. 49 - 75
Published: April 4, 2020
Abstract
Globally,
thermodynamics
explains
an
increase
in
atmospheric
water
vapor
with
warming
of
around
7%/°C
near
to
the
surface.
In
contrast,
global
precipitation
and
evaporation
are
constrained
by
Earth's
energy
balance
at
∼2–3%/°C.
However,
this
rate
is
suppressed
rapid
adjustments
response
greenhouse
gases
absorbing
aerosols
that
directly
alter
budget.
Rapid
forcings,
cooling
effects
from
scattering
aerosol,
observational
uncertainty
can
explain
why
observed
responses
currently
difficult
detect
but
expected
emerge
accelerate
as
increases
aerosol
forcing
diminishes.
Precipitation
be
smaller
over
land
than
ocean
due
limitations
on
moisture
convergence,
exacerbated
feedbacks
affected
adjustments.
Thermodynamic
fluxes
amplify
wet
dry
events,
driving
intensification
extremes.
The
deviate
a
simple
thermodynamic
in‐storm
larger‐scale
feedback
processes,
while
changes
large‐scale
dynamics
catchment
characteristics
further
modulate
frequency
flooding
increases.
Changes
circulation
radiative
evolving
surface
temperature
patterns
capable
dominating
cycle
some
regions.
Moreover,
direct
impact
human
activities
through
abstraction,
irrigation,
use
change
already
significant
component
regional
importance
demand
grows
population.
Abstract
Compound
flooding
arises
from
storms
causing
concurrent
extreme
meteorological
tides
(that
is
the
superposition
of
storm
surge
and
waves)
precipitation.
This
can
severely
affect
densely
populated
low-lying
coastal
areas.
Here,
combining
output
climate
ocean
models,
we
analyse
concurrence
probability
conditions
driving
compound
flooding.
We
show
that,
under
a
high
emissions
scenario,
would
increase
globally
by
more
than
25%
2100
compared
to
present.
In
latitudes
above
40
o
north,
could
become
2.5
times
as
frequent,
in
contrast
parts
subtropics
where
it
weaken.
Changes
precipitation
account
for
most
(77%
20%,
respectively)
projected
change
probability.
The
evolution
dependence
between
tide
dominates
uncertainty
projections.
Our
results
indicate
that
not
accounting
these
effects
adaptation
planning
leave
communities
insufficiently
protected
against
Hydrology and earth system sciences,
Journal Year:
2021,
Volume and Issue:
25(7), P. 3897 - 3935
Published: July 7, 2021
Abstract.
Hydroclimatic
extremes
such
as
intense
rainfall,
floods,
droughts,
heatwaves,
and
wind
or
storms
have
devastating
effects
each
year.
One
of
the
key
challenges
for
society
is
understanding
how
these
are
evolving
likely
to
unfold
beyond
their
historical
distributions
under
influence
multiple
drivers
changes
in
climate,
land
cover,
other
human
factors.
Methods
analysing
hydroclimatic
advanced
considerably
recent
decades.
Here
we
provide
a
review
drivers,
metrics,
methods
detection,
attribution,
management,
projection
nonstationary
extremes.
We
discuss
issues
uncertainty
associated
with
approaches
(e.g.
arising
from
insufficient
record
length,
spurious
nonstationarities,
incomplete
representation
sources
modelling
frameworks),
examine
empirical
simulation-based
frameworks
analysis
extremes,
identify
gaps
future
research.
Water Resources Research,
Journal Year:
2021,
Volume and Issue:
58(1)
Published: Dec. 27, 2021
Abstract
Long
short‐term
memory
(LSTM)
networks
represent
one
of
the
most
prevalent
deep
learning
(DL)
architectures
in
current
hydrological
modeling,
but
they
remain
black
boxes
from
which
process
understanding
can
hardly
be
obtained.
This
study
aims
to
demonstrate
potential
interpretive
DL
gaining
scientific
insights
using
flood
prediction
across
contiguous
United
States
(CONUS)
as
a
case
study.
Two
interpretation
methods
were
adopted
decipher
machine‐captured
patterns
and
inner
workings
LSTM
networks.
The
by
expected
gradients
method
revealed
three
distinct
input‐output
relationships
learned
LSTM‐based
runoff
models
160
individual
catchments.
These
correspond
flood‐inducing
mechanisms—snowmelt,
recent
rainfall,
historical
rainfall—that
account
for
10.1%,
60.9%,
29.0%
20,908
flow
peaks
identified
data
set,
respectively.
Single
flooding
mechanisms
dominate
70.7%
investigated
catchments
(11.9%
snowmelt‐dominated,
34.4%
rainfall‐dominated,
24.4%
rainfall‐dominated
mechanisms),
remaining
29.3%
have
mixed
mechanisms.
spatial
variability
dominant
reflects
catchments'
geographic
climatic
conditions.
Moreover,
additive
decomposition
unveils
how
network
behaves
differently
retaining
discarding
information
when
emulating
different
types
floods.
Information
inputs
within
previous
time
steps
partially
stored
predict
snowmelt‐induced
rainfall‐induced
floods,
while
only
is
retained.
Overall,
this
provides
new
perspective
processes
extremes
demonstrates
prospect
artificial
intelligence‐assisted
discovery
future.
Geophysical Research Letters,
Journal Year:
2020,
Volume and Issue:
47(7)
Published: April 1, 2020
The
magnitudes
of
river
floods
in
Europe
have
been
observed
to
change,
but
their
alignment
with
changes
the
spatial
coverage
or
extent
individual
has
not
clear.
We
analyze
flood
and
extents
for
3,872
hydrometric
stations
across
over
past
five
decades
classify
each
based
on
antecedent
weather
conditions.
find
positive
correlations
between
95%
stations.
In
central
British
Isles,
association
increasing
trends
is
due
a
magnitude-extent
correlation
precipitation
soil
moisture
along
shift
generating
processes.
highlights
importance
transnational
risk
management.
Water Resources Research,
Journal Year:
2020,
Volume and Issue:
56(3)
Published: Feb. 19, 2020
Due
to
difficulties
in
identifying
a
climate
change
signal
flood
magnitude,
it
has
been
suggested
that
shifts
timing,
is,
the
day
of
annual
streamflow
maxima,
may
be
detectable.
Here,
we
use
high-quality
streamflow,
largely
free
snowmelt,
from
221
catchments
across
Australia
investigate
influence
soil
moisture
and
rainfall
timing
on
maxima
timing.
In
tropical
areas
find
is
strongly
linked
both
maxima.
However,
southern
more
correlated
with
than
The
link
between
flood,
moisture,
confounded
by
event
severity:
For
less
extreme
events
likely
correspond
whereas
becomes
increasingly
important
as
severity
increases.
Using
circular
regression
nonstationarity,
shifting
earlier
year
tropics
later
southwest
continent,
consistent
changes
mean
due
expansion.
southeast
Australia,
there
evidence
mechanisms
controlling
seasonality
are
changing
reversal
trends
post
Millennium
Drought.
Overall,
compared
found
have
greater