Flood
dynamics,
and
in
particular
the
shape
of
flood
hydrographs,
are
influenced
by
a
mix
catchment
morphometric
characteristics.
To
identify
different
hydrograph
shapes
key
controls
on
them,
we
use
hydro-morphic
classification
method.
A
total
1,584
high
flow
(near
bankfull)
hydrographs
868
overbank
from
rivers
17
coastal
catchments
New
South
Wales
(NSW),
Australia
used.We
find
three
clusters
for
flows
floods.
On
average,
across
all
floods,
elongation
ration
(Er)
relief
(Rh)
dominant
shape,
followed
drainage
density
(Dd),
average
longitudinal
slope
upstream
gauge
(Sl),
position
(Gp).
Overall,
more
catchment-scale
than
where
is
confined
to
channel.Ultimately,
proposed
could
be
used
understand
fundamental,
imposed,
behaviour.
It
also
better
calibrate
hydrologic
models
assess
relative
impacts
land
climate
change
scale
hydrological
behaviour
versus
imposed
controls.
International Journal of Disaster Risk Reduction,
Journal Year:
2024,
Volume and Issue:
108, P. 104503 - 104503
Published: April 23, 2024
Floods
are
a
widespread
and
damaging
natural
phenomenon
that
causes
harm
to
human
lives,
resources,
property
has
agricultural,
eco-environmental,
economic
impacts.
Therefore,
it
is
crucial
perform
flood
susceptibility
mapping
(FSM)
identify
susceptible
zones
mitigate
reduce
damage.
This
study
assessed
the
damage
caused
by
2022
flash
in
Sindh
identified
flood-susceptible
based
on
frequency
ratio
(FR)
analytical
hierarchy
process
(AHP)
models.
Flood
inventory
maps
were
generated,
containing
150
sampling
points,
which
manually
selected
from
Landsat
imagery.
The
points
split
into
70%
for
training
30%
validating
results.
Furthermore,
fourteen
conditioning
factors
considered
analysis
developing
FSM.
final
FSM
categorized
five
zones,
representing
levels
very
low
high.
results
areas
under
high
Ghotki
(FR
4.42%
AHP
5.66%),
Dadu
21.40%
21.29%),
Sanghar
6.81%
6.78%).
Ultimately,
accuracy
was
evaluated
using
receiver
operating
characteristics
area
curve
method,
resulting
82%,
83%),
91%,
90%),
96%,
95%).
enhances
scientific
understanding
of
impacts
across
diverse
regions
emphasizes
importance
accurate
informed
decision-making.
findings
provide
valuable
insights
supportive
policymakers,
agricultural
planners,
stakeholders
engaged
risk
management
adverse
consequences
floods.
Water,
Journal Year:
2024,
Volume and Issue:
16(8), P. 1141 - 1141
Published: April 17, 2024
Mapping
spatial
data
is
essential
for
the
monitoring
of
flooded
areas,
prognosis
hazards
and
prevention
flood
risks.
The
Ganges
River
Delta,
Bangladesh,
world’s
largest
river
delta
prone
to
floods
that
impact
social–natural
systems
through
losses
lives
damage
infrastructure
landscapes.
Millions
people
living
in
this
region
are
vulnerable
repetitive
due
exposure,
high
susceptibility
low
resilience.
Cumulative
effects
monsoon
climate,
rainfall,
tropical
cyclones
hydrogeologic
setting
Delta
increase
probability
floods.
While
engineering
methods
mitigation
include
practical
solutions
(technical
construction
dams,
bridges
hydraulic
drains),
regulation
traffic
land
planning
support
systems,
geoinformation
rely
on
modelling
remote
sensing
(RS)
evaluate
dynamics
hazards.
Geoinformation
indispensable
mapping
catchments
areas
visualization
affected
regions
real-time
monitoring,
addition
implementing
developing
emergency
plans
vulnerability
assessment
warning
supported
by
RS
data.
In
regard,
study
used
monitor
southern
segment
Delta.
Multispectral
Landsat
8-9
OLI/TIRS
satellite
images
were
evaluated
(March)
post-flood
(November)
periods
analysis
extent
landscape
changes.
Deep
Learning
(DL)
algorithms
GRASS
GIS
modules
qualitative
quantitative
as
advanced
image
processing.
results
constitute
a
series
maps
based
classified
Water,
Journal Year:
2025,
Volume and Issue:
17(3), P. 345 - 345
Published: Jan. 26, 2025
This
study
focuses
on
assessing
flash
flood
risks
in
Northeastern
Thailand,
particularly
within
the
Lam
Saphung,
Phrom,
and
Chern
River
Basins,
which
are
highly
susceptible
to
floods
debris
flows.
Using
HEC-RAS
hydraulic
model
integrated
with
GIS
tools,
research
analyzes
historical
scenario-based
events
evaluate
impact
of
land
use
changes
hydrological
dynamics.
The
was
calibrated
validated
statistical
metrics
such
as
R2
values
ranging
from
0.745
0.994
NSE
between
0.653
0.893,
indicating
strong
agreement
observed
data.
also
identified
high-risk
areas,
up
5.49%
5.50%
increases
flood-prone
areas
Phrom
respectively,
2006
2019.
Key
findings
highlight
critical
role
proactive
risk
management
targeted
mitigation
strategies
enhancing
community
resilience.
integration
advanced
modeling
detailed
datasets
enables
precise
hazard
mapping,
including
depths
exceeding
1.5
m
certain
zones
covering
105.2
km2
during
severe
events.
These
results
provide
actionable
insights
for
emergency
response
planning.
significantly
contributes
assessments
by
advancing
techniques
delivering
practical
recommendations
sustainable
management.
outcomes
relevant
stakeholders,
urban
planners,
officials,
policymakers,
who
aim
strengthen
resilience
vulnerable
regions.
By
addressing
complexities
robust
quantitative
evidence,
this
not
only
enhances
understanding
dynamics,
but
lays
groundwork
developing
adaptive
mitigate
adverse
impacts
floods,
safeguarding
both
communities
infrastructure
region.
