Hydrological Processes,
Год журнала:
2025,
Номер
39(1)
Опубликована: Янв. 1, 2025
ABSTRACT
The
contemporary
era
is
marked
by
the
faster
exploitation
of
groundwater
resources
due
to
combined
effects
burgeoning
population
and
rapid
industrialisation.
This
study
tries
delineate
potential
zones
(GWPZs)
in
a
fragile
agriculturally
dominant
watershed
North‐East
India
using
GIS‐based
multi‐criteria
decision
analysis
(MCDA)
approach
Analytical
Hierarchy
Process
(AHP)
technique.
has
undertaken
10
influencing
factors:
geomorphology,
geology,
land
use/land
cover
(LU/LC),
drainage
density,
rainfall,
soil
texture,
slope,
lineament
topographic
wetness
index
(TWI)
normalised
difference
water
(NDWI).
Suitable
weights
for
parameters
are
assigned
according
their
relative
importance
association
with
storage
based
on
pairwise
comparison
matrix
(PCM).
Four
GWPZs
respective
coverages
namely
poor
(3.39%),
moderate
(24.98%),
good
(33.36%)
excellent
(38.27%)
categories
found.
central
southern
parts
area
covering
portion
Udalguri,
Sonitpur
Darrang
districts
Assam
have
porous
geological
settings
floodplains,
indicating
high
potentiality.
In
contrast,
northern
part
hard
rugged
terrain
lacks
storage.
Incorporating
socio‐economic
aspect,
particularly
number
villages
or
without
access
suitable
groundwater,
significantly
enhances
study's
utility.
outcome
cross‐verified
well
data
obtained
from
Central
Groundwater
Board
(CGWB)
field
which
validated
receiver
operating
characteristics
(ROC)
curve
resulting
an
accuracy
72.9%.
Hence,
this
inquiry
implications
both
regional
global
significance
will
assist
stakeholders
authorities
creating
roadmap
sustainable
effective
use.
Water,
Год журнала:
2022,
Номер
14(13), С. 2138 - 2138
Опубликована: Июль 5, 2022
Groundwater
occurrence
in
semi-arid
regions
is
variable
space
and
time
due
to
climate
patterns,
terrain
features,
aquifer
properties.
Thus,
accurate
delineation
of
Potential
Zones
(GWPZs)
essential
for
sustainable
water
resources
management
these
environments.
The
present
research
aims
delineate
assess
GWPZs
a
basin
San
Luis
Potosi
(SLP),
Mexico,
through
the
integration
Remote
Sensing
(RS),
Geographic
Information
System
(GIS),
Analytic
Hierarchy
Process
(AHP).
Seven
thematic
layers
(geology,
lineament
density,
land
use
cover,
topographic
wetness
index
(TWI),
rainfall,
drainage
slope)
were
generated
raster
format.
After
AHP
procedure
rank
assignment,
integrated
using
calculator
obtain
map.
results
indicated
that
68.21%
area
classified
as
low
groundwater
potential,
whereas
26.30%
moderate.
Validation
was
done
by
assessing
residence
data
from
15
wells
distributed
study
area.
Furthermore,
Receiver
Operating
Characteristics
(ROC)
curve
obtained,
indicating
satisfactory
accuracy
prediction
(AUC
=
0.677).
This
provides
valuable
information
decision-makers
regarding
conservation
resources.
Journal of Cleaner Production,
Год журнала:
2024,
Номер
441, С. 140715 - 140715
Опубликована: Янв. 11, 2024
Water
is
the
most
valuable
natural
resource
on
earth
that
plays
a
critical
role
in
socio-economic
development
of
humans
worldwide.
used
for
various
purposes,
including,
but
not
limited
to,
drinking,
recreation,
irrigation,
and
hydropower
production.
The
expected
population
growth
at
global
scale,
coupled
with
predicted
climate
change-induced
impacts,
warrants
need
proactive
effective
management
water
resources.
Over
recent
decades,
machine
learning
tools
have
been
widely
applied
to
resources
management-related
fields
often
shown
promising
results.
Despite
publication
several
review
articles
applications
water-related
fields,
this
paper
presents
first
time
comprehensive
techniques
management,
focusing
achievements.
study
examines
potential
advanced
improve
decision
support
systems
sectors
within
realm
which
includes
groundwater
streamflow
forecasting,
distribution
systems,
quality
wastewater
treatment,
demand
consumption,
marine
energy,
drainage
flood
defence.
This
provides
an
overview
state-of-the-art
approaches
industry
how
they
can
be
ensure
supply
sustainability,
quality,
drought
mitigation.
covers
related
studies
provide
snapshot
industry.
Overall,
LSTM
networks
proven
exhibit
reliable
performance,
outperforming
ANN
models,
traditional
established
physics-based
models.
Hybrid
ML
exhibited
great
forecasting
accuracy
across
all
showing
superior
computational
power
over
ANNs
architectures.
In
addition
purely
data-driven
physical-based
hybrid
models
also
developed
prediction
performance.
These
efforts
further
demonstrate
Machine
powerful
practical
tool
management.
It
insights,
predictions,
optimisation
capabilities
help
enhance
sustainable
use
development,
healthy
ecosystems
human
existence.
Groundwater for Sustainable Development,
Год журнала:
2023,
Номер
23, С. 101049 - 101049
Опубликована: Ноя. 1, 2023
Groundwater
plays
a
pivotal
role
as
global
source
of
drinking
water.
To
meet
sustainable
development
goals,
it
is
crucial
to
consistently
monitor
and
manage
groundwater
quality.
Despite
its
significance,
there
are
currently
no
specific
tools
available
for
assessing
trace/heavy
metal
contamination
in
groundwater.
Addressing
this
gap,
our
research
introduces
an
innovative
approach:
the
Quality
Index
(GWQI)
model,
developed
tested
Savar
sub-district
Bangladesh.
The
GWQI
model
integrates
ten
water
quality
indicators,
including
six
heavy
metals,
collected
from
38
sampling
sites
study
area.
enhance
precision
assessment,
employed
established
machine
learning
(ML)
techniques,
evaluating
model's
performance
based
on
factors
such
uncertainty,
sensitivity,
reliability.
A
major
advancement
incorporation
metals
into
framework
index
model.
best
authors
knowledge,
marks
first
initiative
develop
encompassing
heavy/trace
elements.
Findings
assessment
revealed
that
area
ranged
'good'
'fair,'
indicating
most
indicators
met
standard
limits
set
by
Bangladesh
government
World
Health
Organization.
In
predicting
scores,
artificial
neural
networks
(ANN)
outperformed
other
ML
models.
Performance
metrics,
root
mean
square
error
(RMSE),
(MSE),
absolute
(MAE)
training
(RMSE
=
0.361;
MSE
0.131;
MAE
0.262),
testing
0.001;
0.00;
0.001),
prediction
evaluation
statistics
(PBIAS
0.000),
demonstrated
superior
effectiveness
ANN.
Moreover,
exhibited
high
sensitivity
(R2
1.0)
low
uncertainty
(less
than
2%)
rating
These
results
affirm
reliability
novel
monitoring
management,
especially
regarding
metals.
Quaternary Science Advances,
Год журнала:
2023,
Номер
10, С. 100082 - 100082
Опубликована: Март 22, 2023
Geomorphological
map
plays
a
key
role
to
illustrate
landscape
evolutionary
history
along
with
the
guidelines
of
sustainable
landuse
planning.
The
Chota
Nagpur
Plateau
is
situated
in
eastern
part
Indian
subcontinent
and
it
storehouse
valuable
rocks
minerals
Precambrian
origin.
Classification
geomorphological
units
highly
required
for
planning
natural
hazards
management.
So,
principal
objective
this
scientific
study
classify
region
into
micro
by
applying
automated
semi-automated
methods.
Digital
elevation
model
(DEM)
data
satellite
imageries
(from
United
States
Geological
Survey)
have
been
used
improve
precision
map.
mapping
techniques
such
as
terrain
attributes
classification,
Topographical
Position
Index
(TPI)
Slope
(SPI)
applied
extract
major
or
features.
TPI
values
show
that
maximum
area
comes
under
valley
bottom
stream
(35.26%)
followed
high
ridge
(24.55%)
whereas
minimum
coverage
found
open
slope
zone
(0.02%).
Local
ridges
mid-slope
lie
8.77%
4.94%
respectively.
result
has
verified
through
field
verification
help
GPS
data.
This
high-accuracy
should
be
regional
These
also
give
very
good
results
classification
well
landforms
evolution.
Environmental Sciences Europe,
Год журнала:
2024,
Номер
36(1)
Опубликована: Сен. 2, 2024
Groundwater
is
a
primary
source
of
drinking
water
for
billions
worldwide.
It
plays
crucial
role
in
irrigation,
domestic,
and
industrial
uses,
significantly
contributes
to
drought
resilience
various
regions.
However,
excessive
groundwater
discharge
has
left
many
areas
vulnerable
potable
shortages.
Therefore,
assessing
potential
zones
(GWPZ)
essential
implementing
sustainable
management
practices
ensure
the
availability
present
future
generations.
This
study
aims
delineate
with
high
Bankura
district
West
Bengal
using
four
machine
learning
methods:
Random
Forest
(RF),
Adaptive
Boosting
(AdaBoost),
Extreme
Gradient
(XGBoost),
Voting
Ensemble
(VE).
The
models
used
161
data
points,
comprising
70%
training
dataset,
identify
significant
correlations
between
presence
absence
region.
Among
methods,
(RF)
(XGBoost)
proved
be
most
effective
mapping
potential,
suggesting
their
applicability
other
regions
similar
hydrogeological
conditions.
performance
metrics
RF
are
very
good
precision
0.919,
recall
0.971,
F1-score
0.944,
accuracy
0.943.
indicates
strong
capability
accurately
predict
minimal
false
positives
negatives.
(AdaBoost)
demonstrated
comparable
across
all
(precision:
recall:
F1-score:
accuracy:
0.943),
highlighting
its
effectiveness
predicting
accurately;
whereas,
outperformed
slightly,
higher
values
metrics:
(0.944),
(0.971),
(0.958),
(0.957),
more
refined
model
performance.
(VE)
approach
also
showed
enhanced
performance,
mirroring
XGBoost's
0.958,
0.957).
that
combining
strengths
individual
leads
better
predictions.
potentiality
zoning
varied
significantly,
low
accounting
41.81%
at
24.35%.
uncertainty
predictions
ranged
from
0.0
0.75
area,
reflecting
variability
need
targeted
strategies.
In
summary,
this
highlights
critical
managing
resources
effectively
advanced
techniques.
findings
provide
foundation
practices,
ensuring
use
conservation
beyond.
Water,
Год журнала:
2022,
Номер
14(15), С. 2435 - 2435
Опубликована: Авг. 6, 2022
Groundwater
is
a
vital
water
resource
for
economic,
agricultural,
and
domestic
purposes
in
arid
regions.
To
reduce
scarcity
regions,
recently,
remote
sensing
GIS
techniques
have
been
successfully
applied
to
predict
areas
with
prospective
resources.
Thus,
this
study
attempted
spatially
reveal
groundwater
potential
zones
(GWPZs)
conduct
change
detection
on
the
desert
fringes
of
Wadi
Asyuti,
defunct
tributary
Egypt’s
Nile
basin
eastern
Sahara.
Eleven
influential
factors
generated
from
imagery,
geological,
hydrological,
climatic
conditions
were
combined
after
giving
weight
each
factor
through
GIS-based
Analytical
Hierarchy
Process
(AHP)
coupled
weighted
overlay
technique
(WOT).
The
results
revealed
six
distinctive
scores
ranging
very
low
(10.59%)
excellent
(3.03%).
Thirty-three
productive
wells,
Interferometry
Synthetic
Aperture
Radar
(InSAR)
coherence
(CCD),
land
use
map
derived
Sentinel-2,
delineated
flooding
zone
Landsat-8
data
used
validate
zones.
GWPZs
indicated
that
48%
collected
wells
can
be
classified
as
consistent
excellent.
Normalized
Difference
Vegetation
Index
(NDVI)
image
classification
multi-temporal
Landsat
series
Sentinel-2
along
InSAR
CCD
Sentinel-1
images
dramatic
changes
use/land
cover
(LU/LC)
terms
agricultural
other
anthropogenic
activities
structurally
downstream
area,
which
most
promising
area
future
developments.
Overall,
integration
radar
multispectral
has
ability
provide
valuable
information
about
resources
tested
model
technique,
such
extremely
significant
guidance
planners
decision
makers
sustainable
development.