Land Degradation and Development,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 10, 2025
ABSTRACT
Soil
erosion,
driven
by
climate
and
land
cover
changes,
poses
a
significant
challenge
to
watershed
sustainability.
This
study
assessed
historical
projected
soil
erosion
in
Ethiopia's
Gidabo
Watershed
using
data
from
an
ensemble
of
six
GCMs
Landsat
images
(2003,
2011,
2019),
which
were
classified
predicted
integrating
the
Random
Forest
classifier
Google
Earth
Engine,
InVEST‐SDR
model
evaluate
potential.
Historical
future
change
projections
revealed
trend
increasing
agricultural
built‐up
areas,
while
dense
vegetation
exhibited
declining
trend.
The
average
annual
precipitation
baseline
scenario
showed
insignificant
decreasing
trend,
whereas
indicated
overall
increase.
was
for
both
periods
CMIP6
(SSP2‐4.5
SSP5‐8.5)
with
maps.
results
that
mean
loss
increased
18.74
t
ha
−1
yr
during
period
22.75
2030s
24.76
2050s
under
SSP2‐4.5.
Under
SSP5‐8.5,
rates
reached
23.12
25.42
2050s.
increase
expansion,
reduced
cover,
high
rainfall
erosivity.
High
concentrated
southwestern
northeastern
sub‐watersheds,
requiring
immediate
conservation
interventions
severely
eroded
areas.
Reforestation,
terracing,
sustainable
management
are
essential
mitigate
enhance
resilience,
providing
key
insights
targeted
strategies
management.
Geomatics Natural Hazards and Risk,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: July 9, 2024
Soil
erosion
significantly
impacts
dam
functionality
by
leading
to
reservoir
siltation,
reducing
capacity,
and
heightening
flood
risks.
This
study
aims
map
soil
within
a
Geographic
Information
Systems
(GIS)
framework
estimate
the
siltation
of
K'sob
compare
these
estimates
with
bathymetric
observations.
Focused
on
one
Hodna
basin's
sub-basins,
watershed
(1477
km2),
assessment
utilizes
Revised
Universal
Loss
Equation
(RUSLE)
integrated
GIS
remote
sensing
data
predict
spatial
distribution
erosion.
Remote
were
pivotal
in
updating
land
cover
parameters
critical
for
RUSLE,
enhancing
precision
our
predictions.
Our
results
indicate
an
average
annual
rate
7.83
t/ha,
variations
ranging
from
0
224
t/ha/year.
With
typical
relative
error
about
13%
predictions,
figures
confirm
robustness
methodology.
These
insights
are
crucial
crafting
mitigation
strategies
areas
facing
high
extreme
loss
will
assist
governmental
agencies
prioritizing
actions
formulating
effective
management
policies.
Future
studies
should
explore
integration
real-time
advanced
modeling
techniques
further
refine
predictions
expand
their
applicability
similar
environmental
assessments.
In
the
Kashmir
Valley,
wetland
ecosystems
cover
an
area
of
42
663
ha
comprising
nearly
2.67%
entire
geographical
area.
These
form
indispensable
portion
natural
landscape
and
play
a
key
part
in
maintenance
environmental
quality.
wetlands
are
harbingers
pristine
biodiversity
provide
various
ecological
economic
services.
However,
recent
past,
threats
resource
exploitation,
reclamation
land
surfaces,
pollution,
hydrologic
system
changes
looming
this
region.
Although
having
wealth
about
755
only
13
(1.72%)
protected
through
legislative
conservation
measures
while
others
continue
to
be
overlooked
management
plans.
Therefore,
there
growing
loud
calls
for
effective
that
requires
scientifically
credible
knowledge
base
pertaining
use,
water
quality,
hydrology,
topography,
socioeconomic
conditions.
Strategies
include
identification
diminution
current
anthropogenic
pressures,
flow
regulation,
wide
array
other
restoration
practices.
This
chapter
therefore
tries
comprehensive
picture
region
with
regard
existing
knowledge,
distribution,
challenges
push
up
policy
intervention
wetlands.
Remote Sensing,
Journal Year:
2023,
Volume and Issue:
15(3), P. 697 - 697
Published: Jan. 24, 2023
Soil
loss
(SL)
and
its
related
sedimentation
in
mountainous
areas
affect
the
lifetime
functionality
of
dams.
Darbandikhan
Lake
is
one
example
a
dam
lake
Zagros
region
that
was
filled
late
1961.
Since
then,
has
received
considerable
amount
sediments
from
upstream
area
basin.
Interestingly,
series
dams
have
been
constructed
(13
dams),
leading
to
change
rate
arriving
at
main
reservoir.
This
motivated
us
evaluate
different
combination
equations
estimate
Revised
Universal
Loss
Equation
(RUSLE),
Sediment
Delivery
Ratio
(SDR),
Reservoir
Sedimentation
(RSed).
Sets
Digital
Elevation
Model
(DEM)
gathered
by
Shuttle
Radar
Topography
Mission
(SRTM),
Tropical
Rainfall
Measuring
(TRMM),
Harmonized
World
Database
(HWSD),
AQUA
eMODIS
NDVI
V6
data,
situ
surveys
echo-sounding
bathymetry,
other
ancillary
data
were
employed
for
this
purpose.
In
research,
RSed,
five
models
SDR
two
most
sensitive
factors
affecting
soil-loss
estimation
tested
(i.e.,
rainfall
erosivity
(R)
cover
management
factor
(C))
propose
proper
RUSLE-SDR
model
suitable
RSed
modeling
areas.
Thereafter,
using
field
measurement
bathymetric
survey
Basin
(DLB)
validated.
The
results
show
six
ninety
scenarios
errors
<20%.
best
scenario
out
Scenario
#18,
which
an
error
<1%,
0.46458
km3·yr−1.
Moreover,
study
advises
Modified
Fournier
index
(MIF)
R
factor.
Avoiding
Index
Connectivity
(IC)
calculating
land
C
obtain
better
estimates
highly
recommended.
