Water,
Год журнала:
2025,
Номер
17(6), С. 880 - 880
Опубликована: Март 19, 2025
Prioritizing
agricultural
land
use
is
a
significant
challenge
for
sustainable
development
in
the
rapidly
urbanizing,
semi-arid
riverine
basins
of
South
Asia,
especially
under
climate
variability
and
water
scarcity.
This
study
introduces
systematic
framework
combining
remote
sensing
geospatial
data
with
Soil
Water
Assessment
Tool
(SWAT)
model,
morphometric
analysis,
VIKOR-based
Multi-Criteria
Decision
Analysis
(MCDA)
to
effectively
identify
Agricultural
Land
Prioritization
(AgLP)
areas
Upper
Kansai
Basin,
India,
while
reducing
environmental
impact,
line
Sustainable
Development
Goals
(SDGs).
The
SWAT
model
simulation
reveals
varied
hydrological
patterns,
basin
yields
from
965.9
1012.9
mm
substantial
baseflow
(~64%
total
flow),
emphasizing
essential
groundwater–surface
interactions
agriculture.
However,
discrepancy
between
percolation
(47%
precipitation)
deep
recharge
(2%
signals
potential
long-term
groundwater
challenges.
VIKOR
analysis
offers
robust
prioritization
framework,
ranking
SW4
as
most
suitable
(Qi
=
0.003)
balanced
features,
agreement
outcomes.
SW5
display
optimal
conditions
due
stable
terrain,
effective
retention,
favorable
traits
(drainage
density
3.0–3.15
km/km2;
ruggedness
0.3–0.4).
Conversely,
SW2,
high
drainage
(5.33
km/km2)
(2.0),
shows
low
suitability,
indicating
risks
erosion
poor
retention.
integrated
AgLP
advances
supports
SDGs,
including
SDG
2
(Zero
Hunger),
6
(Clean
Water),
13
(Climate
Action),
15
(Life
on
Land).
Incorporating
dynamics,
use,
soil
properties,
variables,
this
approach
precise
assessment
suitability
address
global
sustainability
challenges
vulnerable
developing
nations.
Environmental Challenges,
Год журнала:
2021,
Номер
4, С. 100174 - 100174
Опубликована: Июнь 11, 2021
Soil
erosion
is
a
difficult
forceful
practice
by
which
useful
surface
soil
removed,
conveyed,
and
stored
at
detached
place
causing
the
exposure
of
subsurface
siltation
in
reservoirs
natural
streams.
It
also
degraded
different
agricultural
areas
rates
locations
as
well
created
gulleys,
but
these
areas,
degradation
rates,
gulley
were
not
identified
quantified.
Therefore;
core
objective
this
study
to
evaluate
rate
identify
hotspot
using
Revised
Universal
Loss
Equation
(RUSLE),
Multi-criteria
Evaluation
Analysis
Techniques,
Geographic
Information
System
(GIS).
Land
Use/Land
Cover
(LU/LC)
map,
slope
rainfall
Digital
Elevation
Model
(DEM)
necessary
inputs
used
for
study.
The
results
indicated
that
potential
annual
loss
watershed
ranged
from
0.0
706.7
tons
per
hectare
year
with
an
average
27.7
year.
From
total
area
(859.2
km2),
gully
expansion
63km2.
overall
analysis
4.8%
highly
sensitive;
54.24%
moderately
17.69%
marginally
sensitive
while,
23.28%
currently
remaining
0.06%
/constraint
erosion.
Hence,
Areas
categorized
under
classes
needed
direct
mediation
better
conservation
planning.
concluded
Gulley,
LU/LC,
Topographical
wetness
index,
types
are
factors
enable
high
low,
respectively.
recommended
concerned
bodies
should
have
take
care
further
through
creating
awareness
among
society
about
sustainable
use
resources
methods.
Journal of King Saud University - Science,
Год журнала:
2022,
Номер
34(8), С. 102332 - 102332
Опубликована: Сен. 20, 2022
This
study
focuses
on
the
application
of
multi-sensor
satellite
archived
data
products
and
ancillary
for
evaluation
drought
vulnerability.
The
use
a
subjective
model,
namely
Analytical
Hierarchy
Process
(AHP)
integrated
with
Geographical
Information
System
(GIS)
various
influencing
parameters,
emerged
as
powerful
tool
gauged
ungauged
watershed.
Kangsabati
river
basin,
located
in
southern
part
West
Bengal
(India),
is
facing
issues
overexploitation
groundwater,
climate
variation,
unsystematic
agricultural
practices
that
are
inducing
water
crisis
vulnerability
basin
to
conditions.
In
this
study,
11
elevation,
slope,
aspect,
LULC,
population
density,
normalized
difference
vegetation
index
(NDVI),
(NDDI),
land
surface
temperature
(LST),
(NDWI),
condition
(VCI),
soil
moisture
(SMI)
were
used
delineate
catchment
River.
Findings
using
GIS
platform,
show
that,
nearly
28.5%
area
falls
under
medium
category,
followed
by
high
(21.1%),
no
(20%),
low
(19.5%),
very
(10.6%)
categories
area.
also
suggests
Nature
Based
Solution
(NBS)
Disaster
Risk
Reduction
(DRR)
strategies
such
ecosystem-based
approaches
(EBA)
blue
infrastructure
Drought
mitigation
Environmental Earth Sciences,
Год журнала:
2023,
Номер
82(3)
Опубликована: Янв. 27, 2023
Springs
are
one
of
the
vital
sources
water
in
Mizoram
district
North-Eastern
hilly
state
India.
However,
there
is
a
paucity
literature
on
spring
serviceability,
recharge
potentiality
and
watershed
management.
Therefore,
present
research
aims
to
prepare
suitable
vulnerable
map
Aizawl
using
AHP-TOPSIS
AHP-VIKOR
models.
Highest
relief,
mean
slope,
annual
rainfall,
temperature,
distribution
springs,
geomorphic
units,
geological
formations,
stream
order,
concentration
lineaments
epicentre
were
considered
as
major
suitability
inducing
factors.
Besides,
landslide,
forest
fire,
cover
area,
built-up
stone
mining
sites,
proportion
agricultural
land,
degraded
open
area
body
taken
measure
vulnerability
across
watersheds.
Relative
analysis
(0–0.60)
(0.04–1.00)
shows
that
central
part
for
water.
Study
further
reveals
hazard
intensity
anthropogenic
interventions
also
very
high
compared
other
regions
(AHP-TOPSIS—0.0–0.85
AHP-VIKOR—0.0–1.00).
Consequently,
maps
prepared
this
study
could
act
blueprint
Lastly,
ROC
curve
(0.816)
slightly
better
its
prediction
(0.743).
Journal of Water and Climate Change,
Год журнала:
2023,
Номер
14(7), С. 2055 - 2084
Опубликована: Июнь 5, 2023
Abstract
Water
resource
management
is
critical
in
the
face
of
climate
change
to
reduce
water
scarcity
and
meet
demands
an
expanding
population.
Prioritization
watersheds
has
gained
significance
natural
management,
particularly
context
watershed
management.
This
study
prioritizes
sub-watersheds
for
Peddavagu
basin
using
five
methods.
The
four
methods
mentioned
above
can
be
estimated
utilizing
remote
sensing
(RS)
geographic
information
system
(GIS)
approaches,
while
linear
discriminant
analysis
(LDA)
machine
learning
techniques.
catchment
resulted
formation
13
sub-watersheds.
quantitative
measurements
morphometric
analysis,
including
linear,
relief,
areal,
were
considered,
18
characteristics
chosen
rank
prioritize
Principal
component
(PCA)
was
used
based
on
highly
correlated
parameters.
land
use/land
cover
(LULC)
features
LDA
two
Using
hypsometric
integral
(HI)
values,
prioritization
been
done.
Sub-watersheds
prioritized.
Based
methods,
classified
as
low,
medium,
high.
Among
identified
high
priority,
immediate
priority
assigned
SW10.
Decision-makers
research
region
use
findings
plan
implement
