Research Square (Research Square),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Dec. 4, 2023
Abstract
The
rapid
development
of
the
city
leads
to
continuous
updating
ratio
land
use
allocation,
especially
during
flood
season,
which
will
exacerbate
significant
changes
in
spatial
and
temporal
patterns
urban
flooding,
increasing
difficulty
forecasting
early
warning.
In
this
study,
evolution
flooding
a
high-density
area
was
analyzed
based
on
Mike
Flood
model,
influence
mechanisms
different
rainfall
peak
locations
infiltration
rate
scenarios
characteristics
waterlogging
were
explored.
results
revealed
that
under
same
return
period,
larger
coefficient,
value
inundation
volume
area.
When
coefficient
is
small,
higher
period
is,
lag
time
P
=
50a,
r
0.2,
delay
for
depths
H
>
0.03
m
0.15
reached
32
min
45
min,
respectively,
At
time,
there
are
also
differences
depths.
greater
depth,
longer
volume,
more
effect
prolongation.
It
worth
noting
increase
lead
advance
area,
overall
obvious
than
volume.
times
advanced
by
4
~
8
−
2
9
m,
after
rate;
smaller
time.
capacities
obtained
study
can
help
provide
new
perspective
warning
waterlogging.
Land Degradation and Development,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 19, 2025
ABSTRACT
Crop
rotation
can
help
to
alleviate
land
use
pressure,
prevent
soil
degradation,
and
promote
sustainable
agricultural
development.
Land
in
Northeast
China
has
long
been
overused
ensure
national
food
security.
Maize–soybean
(MSR)
is
an
effective
conservation
strategy,
but
its
suitability
not
yet
determined
China.
In
this
study,
we
applied
optimized
MaxEnt
model
by
integrating
multiple
environmental
variables
systematically
predict
the
of
for
maize
soybean
cultivation,
establish
MSR
function,
define
specific
range
priority
The
obtained
significantly
improved
performance,
where
suitable
areas
covered
60.25%
56.88%,
respectively,
total
area
Suitability
was
influenced
factors,
including
climate,
topography,
soil,
hydrology,
conditions,
particularly
gravel
content
depth,
were
identified
as
main
factors.
Extensive
are
supporting
MSR,
highly
only
account
6.96%
area,
they
primarily
located
Songnen
Plain,
most
which
developed
into
cropland.
scientifically
implementing
thereby
providing
crucial
support
adjusting
planting
structure
optimizing
planning
Journal of Environmental Management,
Journal Year:
2025,
Volume and Issue:
380, P. 124972 - 124972
Published: March 23, 2025
The
Mahananda
River
basin,
located
in
Eastern
India,
faces
escalating
flood
risks
due
to
its
complex
hydrology
and
geomorphology,
threatening
socioeconomic
environmental
stability.
This
study
presents
a
novel
approach
susceptibility
(FS)
mapping
updates
the
region's
inventory.
Multitemporal
Sentinel-1
(S1)
SAR
images
(2020-2022)
were
processed
using
U-Net
transfer
learning
model
generate
water
body
frequency
map,
which
was
integrated
with
Global
Flood
Dataset
(2000-2018)
refined
through
grid-based
classification
create
an
updated
Eleven
geospatial
layers,
including
elevation,
slope,
soil
moisture,
precipitation,
type,
NDVI,
Land
Use
Cover
(LULC),
wind
speed,
drainage
density,
runoff,
used
as
conditioning
factors
(FCFs)
develop
hybrid
FS
approach.
integrates
Fuzzy
Analytic
Hierarchy
Process
(FuzzyAHP)
six
machine
(ML)
algorithms
models
FuzzyAHP-RF,
FuzzyAHP-XGB,
FuzzyAHP-GBM,
FuzzyAHP-avNNet,
FuzzyAHP-AdaBoost,
FuzzyAHP-PLS.
Future
trends
(1990-2030)
projected
CMIP6
data
under
SSP2-4.5
SSP5-8.5
scenarios
MIROC6
EC-Earth3
ensembles.
SHAP
algorithm
identified
LULC,
type
most
influential
FCFs,
contributing
over
60
%
susceptibility.
Results
show
that
31.10
of
basin
is
highly
susceptible
flooding,
western
regions
at
greatest
risk
low
elevation
high
density.
projections
indicate
30.69
area
will
remain
vulnerable,
slight
increase
SSP5-8.5.
Among
models,
FuzzyAHP-XGB
achieved
highest
accuracy
(AUC
=
0.970),
outperforming
FuzzyAHP-GBM
0.968)
FuzzyAHP-RF
0.965).
experimental
results
showed
proposed
can
provide
spatially
well-distributed
inventory
derived
from
freely
available
remote
sensing
(RS)
datasets
robust
framework
for
long-term
assessment
ML
techniques.
These
findings
offer
critical
insights
improving
management
mitigation
strategies
basin.
