Journal of Hydrology,
Journal Year:
2024,
Volume and Issue:
642, P. 131814 - 131814
Published: Aug. 12, 2024
Several
studies
have
demonstrated
that
response
times
in
natural
catchments
decrease
with
increasing
rainfall
intensity.
Consequently,
event-based
estimations
of
catchment
are
paramount
importance
applied
hydrology.
Specifically,
they
the
potential
to
address
a
major
inconsistency
use
empirical
formulas.
These
formulas
often
assume
as
constant
parameters,
regardless
whether
extreme
or
frequent
flood
events
considered,
thus
neglecting
role
flow
velocities.
In
this
paper,
built
upon
previous
approaches
developed
and/or
analyzed
by
authors,
two
different
recent
methods
for
critically
reviewed,
and
their
predictive
performances
compared.
First,
four
"physically-based"
formulas,
calibrated
using
synthetic
rainfalls
three
small
Italian
watersheds
reproduce
results
two-dimensional
hydrodynamic-based
rainfall/runoff
model
and,
consequently,
simulated
wave
celerities,
considered.
Then,
detrending
moving-average
cross-correlation
analysis
(DMCA)
has
been
assess
average
time
elapsed
between
centroids
precipitation
discharge
series.
The
soundness
these
is
initially
assessed
based
on
ability
estimated
lag
from
observations.
Their
robustness
further
evaluated
analyzing
magnitude
basin
scale
dependence
inferred
velocities
compared
observed
values,
following
approach
proposed
literature.
issues
discussed
reference
60
rainfall-runoff
occurring
across
27
Hungary
Italy,
which
possess
substantially
geomorphic
climatic
features,
highlighting
both
need
improvements.
Both
give
error
rates
around
37%
dataset.
Hydrology,
Journal Year:
2023,
Volume and Issue:
10(7), P. 141 - 141
Published: June 30, 2023
As
one
of
nature’s
most
destructive
calamities,
floods
cause
fatalities,
property
destruction,
and
infrastructure
damage,
affecting
millions
people
worldwide.
Due
to
its
ability
accurately
anticipate
successfully
mitigate
the
effects
floods,
flood
modeling
is
an
important
approach
in
control.
This
study
provides
a
thorough
summary
modeling’s
current
condition,
problems,
probable
future
directions.
The
includes
models
based
on
hydrologic,
hydraulic,
numerical,
rainfall–runoff,
remote
sensing
GIS,
artificial
intelligence
machine
learning,
multiple-criteria
decision
analysis.
Additionally,
it
covers
heuristic
metaheuristic
techniques
employed
evaluation
examines
advantages
disadvantages
various
models,
evaluates
how
well
they
are
able
predict
course
impacts
floods.
constraints
data,
unpredictable
nature
model,
complexity
model
some
difficulties
that
must
overcome.
In
study’s
conclusion,
prospects
for
development
advancement
field
discussed,
including
use
advanced
technologies
integrated
models.
To
improve
risk
management
lessen
society,
report
emphasizes
necessity
ongoing
research
modeling.
Water Resources Research,
Journal Year:
2023,
Volume and Issue:
59(10)
Published: Oct. 1, 2023
Abstract
In
our
era,
the
rapid
increase
of
parallel
programming
coupled
with
high‐performance
computing
(HPC)
facilities
allows
for
use
two‐dimensional
shallow
water
equation
(2D‐SWE)
algorithms
simulating
floods
at
“hydrological”
catchment
scale,
rather
than
just
“hydraulic”
fluvial
scale.
This
approach
paves
way
development
new
operational
systems
focused
on
impact‐based
flash‐floods
nowcasting,
wherein
hydrodynamic
simulations
directly
model
spatial
and
temporal
variability
measured
or
predicted
rainfall
impacts
even
a
street
Specifically,
main
goal
this
research
is
to
make
step
move
toward
implementation
an
effective
flash
flood
nowcasting
system
in
which
timely
accurate
impact
warnings
are
provided
by
including
weather
radar
products
HPC
2D‐SWEs
modelling
framework
able
integrate
watershed
hydrology,
flow
hydrodynamics,
river
urban
flooding
one
model.
The
timing,
location,
intensity
street‐level
evolution
some
key
elements
risk
(people,
vehicles,
infrastructures)
also
discussed
considering
both
calibration
issues
role
played
resolution.
All
these
analyzed
having
as
starting
point
event
hit
Mandra
town
(Athens,
Greece)
15
November
2017,
highlighting
feasibility
accuracy
overall
providing
insights
field.
Journal of Hydrology,
Journal Year:
2024,
Volume and Issue:
632, P. 130728 - 130728
Published: Jan. 24, 2024
Fluvial
landscape
analysis
represents
an
essential
component
in
geomorphology,
hydrology,
ecology
and
cartography.
It
is
traditionally
focused
on
the
transition
between
hillslopes
channel
domain,
which
network
drainage
represented
by
static
flow
lines.
However,
natural
fluctuations
of
processes
occurring
watershed
induce
lateral
longitudinal
expansions
contractions
patterns
variations
stream
surface
area.
These
can
be
better
understood
introducing
a
two-dimensional
(2D)
view
catchment
hydrography,
river
width
floodplain
are
included
analysis.
The
novelty
introduced
this
work
development
hydrodynamic
hierarchical
framework
(HHF)
to
analyse
transitions
among
geomorphic
hydrographic
features
fluvial
landscape,
distinguishing
hillslope,
unchanneled
valleys,
floodplains,
single/multithreads
channels.
HHF
based
estimation
nested
inundation
pattern
domains
(IPDs)
from
digital
elevation
models
2D
modeling.
IPDs
defined
scaling
laws
that
characterize
log–log
relations
density
unit
discharge
thresholds
extracted
direct
rainfall
method
(DRM)
approach
under
steady
state
solutions.
physical
significance
analysed
within
context
both
physiographic
rates
employed
as
input
for
modeling
approach.
Initially,
spatial
heterogeneity
initially
used
derive
metrics
function
rate.
Then,
index,
representative
IPDs'
heterogeneity,
measure
susceptibility
area
expand/contract.
Finally,
consistency
results
assessed
comparison
another
hydrodynamic-based
recently
proposed
literature.
using
challenging
mountain
low-relief
environments,
characterized
multithread
channels,
meander
cut-offs,
oxbow
lakes,
extreme
landscapes
feature
glacial
outwash,
permafrost,
peatlands.
Journal of Hydrology,
Journal Year:
2024,
Volume and Issue:
632, P. 130778 - 130778
Published: Jan. 26, 2024
Badlands
are
often
the
source
of
a
significant
fraction
sediment
reaching
river
network
due
to
exposure
bare
soil
impact
rain
drops
and
bed
shear
stress
generated
by
surface
runoff.
Hence,
correct
understanding
erosion
transport
processes
inside
badlands
can
help
better
characterisation
suspended
production
at
catchment
scale.
In
this
work
we
study
suitability
two-dimensional
(2D)
physically-based
event-scale
model
as
tool
represent
in
seasonal
The
solves
2D
shallow
water
equations,
including
infiltration
rainfall,
order
compute
generation
routing
runoff
within
badland.
Coupled
hydrodynamic
equation
with
terms
that
account
for
rainfall-
runoff-driven
deposition.
Based
on
model,
an
overall
procedure
was
developed
tested
considering,
case
study,
badland
located
El
Soto
(central
Pyrenees,
Iberian
Peninsula).
For
analysed
badland,
several
high-resolution
topography
surveys
were
available,
which
allowed
estimation
loss
spatial
distribution
patterns
periods
3-4
months
over
two
years.
These
data
sets
used
calibrate
validate
proposed
modelling
approach,
analyse
its
capabilities
limitations
assessment
Natural Hazards,
Journal Year:
2024,
Volume and Issue:
120(8), P. 7381 - 7409
Published: March 13, 2024
Abstract
This
paper
explores
the
use
of
rain-on-grid
(or
direct
rainfall)
method
for
flood
risk
assessment
at
a
basin
scale.
The
is
particularly
useful
rural
catchments
with
small
vertical
variations
and
complex
interactions
man-made
obstacles
structures,
which
may
be
oversimplified
by
traditional
hydrologically
based
estimations.
hydrodynamic
model
solving
mass
momentum
conservation
equations
allows
simulation
runoff
over
watershed
As
drawback,
more
detailed
spatially
distributed
data
are
needed,
computational
time
extended.
On
other
hand,
smaller
number
parameters
needed
compared
to
hydrological
model.
Roughness
rainfall
loss
coefficients
need
calibrated
only.
methodology
was
here
implemented
within
two-dimensional
HEC-RAS
low-land
rural,
ungauged,
Terdoppio
River,
Northern
Italy.
resulting
hydrographs
closing
section
were
synthetic
design
evaluated
through
pure
modelling,
showing
agreement
on
peak
discharge
values
low-probability
scenarios,
but
not
total
volumes.
results
in
terms
water
depth
flow
velocity
maps
used
create
hazard
using
Australian
Institute
Disaster
Resilience
methodology.
Index
Proportional
Risk
then
adopted
generate
basin-scale
map,
combining
maps,
damage
functions
different
building-use
classes,
value
reconstruction
content
per
unit
area.
Water,
Journal Year:
2023,
Volume and Issue:
15(22), P. 3982 - 3982
Published: Nov. 16, 2023
Climate
change
and
urbanization
have
increased
the
frequency
of
floods
worldwide,
resulting
in
substantial
casualties
property
loss.
Accurate
flood
forecasting
can
offer
governments
early
warnings
about
impending
disasters,
giving
them
a
chance
to
evacuate
save
lives.
Deep
learning
is
used
improve
timeliness
accuracy
water
level
predictions.
While
various
deep
models
similar
Long
Short-Term
Memory
(LSTM)
achieved
notable
results,
they
complex
structures
with
low
computational
efficiency,
often
lack
generalizability
stability.
This
study
applies
spatiotemporal
Attention
Gated
Recurrent
Unit
(STA-GRU)
model
for
prediction
increase
models’
computing
efficiency.
Another
salient
feature
our
methodology
incorporation
lag
time
during
data
preprocessing
before
training
model.
Notably,
12-h
forecasting,
STA-GRU
model’s
R-squared
(R2)
value
from
0.8125
0.9215.
Concurrently,
manifested
reduced
root
mean
squared
error
(RMSE)
absolute
(MAE)
metrics.
For
more
extended
24-h
R2
improved
0.6181
0.7283,
accompanied
by
diminishing
RMSE
MAE
values.
Seven
typical
models—the
LSTM,
Convolutional
Neural
Networks
LSTM
(CNNLSTM),
(ConvLSTM),
(STA-LSTM),
GRU,
GRU
(CNNGRU),
STA-GRU—are
compared
prediction.
Comparative
analysis
delineated
that
use
application
pre-processing
method
significantly
reliability
forecasting.
Water,
Journal Year:
2022,
Volume and Issue:
14(7), P. 997 - 997
Published: March 22, 2022
Topographic
depressions
in
Digital
Elevation
Models
(DEMs)
have
been
traditionally
seen
as
a
feature
to
be
removed
no
outward
flow
direction
is
available
route
and
accumulate
flows.
Therefore,
simplify
hydrologic
analysis
for
practical
purposes,
the
common
approach
treated
all
DEMs
artefacts
completely
them
DEMs’
data
preprocessing
prior
modelling.
However,
effects
of
depression
filling
on
both
geomorphic
structure
river
network
surface
runoff
still
not
clear.
The
use
two-dimensional
(2D)
hydrodynamic
modeling
track
inundation
patterns
has
potential
provide
novel
point
views
this
issue.
Specifically,
there
need
remove
topographic
from
DEM,
performed
traditional
methods
automatic
extraction
networks,
so
that
their
can
directly
taken
into
account
simulated
drainage
associated
response.
novelty
introduced
work
evaluation
DEM
net-points
characterizing
networks
response
watersheds
simplified
rainfall
scenarios.
results
highlight
how
important
these
might
applications,
providing
new
insights
field
watershed-scale
modeling.