Groundwater Potential Assessment Using Integrated Geospatial and Analytic Hierarchy Process Techniques (AHP) in Chemoga Watershed, Upper Blue Nile Basin, Ethiopia
Air Soil and Water Research,
Год журнала:
2025,
Номер
18
Опубликована: Янв. 1, 2025
Groundwater
is
an
invaluable
natural
resource
that
sustains
human
life
and
supports
the
economic
development
of
nations.
However,
its
unsustainable
utilization
has
emerged
as
a
critical
issue,
particularly
in
developing
countries.
This
study
investigates
groundwater
potential
Chemoga
watershed
to
address
these
challenges.
Conventional
assessments
have
typically
relied
on
labor-intensive
time-consuming
field
surveys,
which
are
resource-demanding
often
fail
provide
accurate
estimates
due
inherent
complexity
systems.
In
response,
this
research
utilizes
geospatial
analytic
hierarchy
process
(AHP)
techniques
assess
Watershed,
aiming
overcome
Eight
biophysical
environmental
factors:
geology,
slope,
rainfall,
land
use/land
cover
(LULC),
soil
type,
elevation,
lineament
density,
drainage
density
were
selected
for
analysis
using
Saaty’s
AHP
methodology.
Data
was
gathered
from
satellite
imagery,
existing
thematic
maps,
local
water
offices,
national
meteorological
agencies.
The
integration
maps
performed
through
weighted
overlay
ArcGIS
10.8,
resulted
delineation
zones
(GWPZ).
model
validated
by
cross-referencing
generated
GWPZ
with
data
dug
wells
boreholes.
results
reveal
five
zones:
very
high
(0.73%),
(24.39%),
moderate
(43.38%),
poor
(31.25%),
(0.25%).
most
suitable
south,
southeast,
southwest
watershed,
near
Debre
Markos
Town.
These
high-potential
significant
81.5%
match
ground
truth
shallow
wells.
findings
crucial
insights
decision-makers,
enabling
formulation
more
effective
management
strategies.
By
identifying
cost-effective
well
sites,
contributes
ensuring
sustainable
supply
Язык: Английский
Integrated spatiotemporal data mining and DInSAR for improved understanding of subsidence related to groundwater depletion impacts
Journal of Geographical Sciences,
Год журнала:
2025,
Номер
35(3), С. 598 - 618
Опубликована: Март 1, 2025
Язык: Английский
Discrimination of potential groundwater areas using remote sensing, gravity and aeromagnetic data in Rey Bouba and environs, North Cameroon
Groundwater for Sustainable Development,
Год журнала:
2025,
Номер
unknown, С. 101455 - 101455
Опубликована: Май 1, 2025
Язык: Английский
Evaluation of potentially susceptible flooding areas leveraging geospatial technology with multicriteria decision analysis in Edo State, Nigeria
Natural Hazards Research,
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 1, 2024
Floods
have
claimed
lives
and
devastated
societal
ecological
systems.
Because
of
their
catastrophic
tendency
the
financial
fatalities
they
cause,
floods
become
more
significant
on
a
global
scale
in
recent
years.
In
Edo
State,
Nigeria,
flooding
is
frequent
threat
that
happens
annually
seriously
damages
both
property.
While
potential
cannot
entirely
be
eliminated,
geospatial-based
technologies
can
greatly
lessen
its
effects.
Nigeria's
flood-prone
study's
objectives
are
to
identify
inundated
places
provide
nuanced
mapping
flood
risk.
To
facilitate
determination
risk
index
(FRI),
fundamental
flood-predictive
features
were
determined
by
taking
into
consideration
elevation,
slope,
distance
from
river,
rainfall
intensity,
land
use/land
cover,
soil
texture,
topographic
roughness
index,
wetness
normalized
difference
vegetation
(NDVI),
runoff
coefficient,
aspect,
drainage
capacity,
flow
accumulation,
sediment
transport
stream
power
index.
The
significance
each
predictive
factor
analytic
hierarchy
procedure
(AHP)
was
gathering
expert
views
perspectives
public
entities.
A
map
created
processing
gathered
data
using
AHP
ArcGIS
10.5
framework.
multicollinearity
(MC)
estimation
applied
assess
model's
predictability.
results
FRI
showed
there
high
extremely
severe
zones
affected
roughly
26
9%
area,
respectively.
Flood
risks
been
identified
as
predominant
south
region
study
which
characterized
low
elevation
wetness,
It
resultant
vulnerability
maps
agreed
with
past
occurrences
previously
experienced
research
demonstrating
technique's
efficacy
locating
locations
plagued
flooding.
Linear
regression
(R2)
analysis
further
conducted
evaluate
scientific
reliability
utilized
methodology;
this
shows
0.816
(81.6%)
dependability.
Consequently,
long-lasting
implementation
predictions,
warning
systems,
mitigation
strategies
may
achieved.
Язык: Английский
Resolving challenges of groundwater flow modelling for improved water resources management: a narrative review
International Journal of Hydrology,
Год журнала:
2024,
Номер
8(5), С. 175 - 193
Опубликована: Янв. 1, 2024
Groundwater
flow
modelling
is
critical
for
managing
groundwater
resources,
particularly
amid
climate
change
and
rising
water
demand.
This
narrative
review
examines
the
role
of
models
in
sustainable
resource
management,
focusing
on
challenges
solutions
to
enhance
model
reliability.
A
key
challenge
data
limitation—especially
regions
like
sub-Saharan
Africa
South
Asia,
where
scarce
hydrogeological
hinders
accurate
calibration.
The
complexity
aquifer
systems,
such
as
karst
aquifers
North
America
fractured-rock
India,
further
complicates
development,
requiring
detailed
geological
complex
simulations.
Additionally,
uncertainties
arise
from
limited
knowledge
properties,
variable
boundary
conditions,
sparse
monitoring
networks,
which
can
reduce
predictability.
Despite
these
obstacles,
are
essential
simulating
behaviour
response
altered
precipitation
patterns,
increasing
extraction
rates,
extreme
events
droughts.
For
instance,
predictive
has
helped
assess
potential
depletion
risks
California’s
Central
Valley
contamination
industrial
zones
East
guiding
strategies
assessments.
To
improve
reliability,
this
emphasizes
need
enhanced
collection,
integration
advanced
technologies—such
artificial
intelligence
machine
learning
accuracy—and
adoption
multidisciplinary
approaches.
These
advancements,
improved
sensor
regional
data-sharing
initiatives
reducing
precision.
Ultimately,
improvements
will
support
adaptation
efforts
promote
management
global
benefiting
managers
policy
makers.
Язык: Английский