Groundwater
recharge
is
the
most
important
component
in
all
water
balance
studies.
Norms
set
by
Resource
Estimation
Committee,
GEC-2015
was
used
for
estimation
of
recharge.
The
study
conducted
Bandar
canal
command
area
constituting
Krishna
Central
Delta
Andhra
Pradesh.
Following
norms
GEC-2015,
estimated
past
decade
from
2012-13
to
2021-22
and
it
found
that
rate
ranging
438135.8
ha-m
year
2015-16
1677730
2013-14.While
computing
gross
recharge,
attributed
rainfall,
seepage,
irrigation
return
flow
ponds/tanks
are
considered.
Environmental Science and Pollution Research,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 25, 2024
Abstract
Managed
aquifer
recharge
(MAR)
replenishes
groundwater
by
artificially
entering
water
into
subsurface
aquifers.
This
technology
improves
storage,
reduces
over-extraction,
and
ensures
security
in
water-scarce
or
variable
environments.
MAR
systems
are
complex,
encompassing
various
components
such
as
soil,
meteorological
factors,
management
(GWM),
receiving
bodies.
Over
the
past
decade,
utilization
of
machine
learning
(ML)
methodologies
for
modeling
prediction
has
increased
significantly.
review
evaluates
all
supervised,
semi-supervised,
unsupervised,
ensemble
ML
models
employed
to
predict
factors
parameters,
rendering
it
most
comprehensive
contemporary
on
this
subject.
study
presents
a
concise
integrated
overview
MAR’s
effective
approaches,
focusing
design,
suitability
quality
(WQ)
applications,
GWM.
The
paper
examines
performance
measures,
input
specifications,
variety
functions
GWM,
highlights
prospects.
It
also
offers
suggestions
utilizing
MAR,
addressing
issues
related
physical
aspects,
technical
advancements,
case
studies.
Additionally,
previous
research
ML-based
data-driven
soft
sensing
techniques
is
critically
evaluated.
concludes
that
integrating
holds
significant
promise
optimizing
WQ
enhancing
efficiency
replenishment
strategies.
Herald of Kazakh-British technical university,
Год журнала:
2025,
Номер
22(1), С. 330 - 345
Опубликована: Март 27, 2025
Climate
change
is
transforming
water
systems
worldwide,
bringing
more
unpredictable
weather
patterns
and
challenging
management
practices.
Prolonged
droughts,
intensified
storms,
diminishing
snowpacks,
shifting
runoff
dynamics
complicate
efforts
to
ensure
security.
In
Kazakhstan,
attempts
mitigate
flooding
through
dam
construction
have
proven
inadequate
for
managing
urban
stormwater
effectively.
This
study
explores
the
implementation
of
Agricultural
Managed
Aquifer
Recharge
(AgMAR)
in
leveraging
3D
visualizations
created
with
PyVista
library
model
soil
layers,
flow
dynamics,
MAR
principle.
The
findings
highlight
AgMAR
as
a
promising
solution
irrigation
rural
management,
offering
benefits
such
groundwater
stabilization,
aquifer
recharge
during
seasonal
precipitation,
purification
underground
sources,
increased
freshwater
availability.
Groundwater
recharge
is
the
most
important
component
in
all
water
balance
studies.
Norms
set
by
Resource
Estimation
Committee,
GEC-2015
was
used
for
estimation
of
recharge.
The
study
conducted
Bandar
canal
command
area
constituting
Krishna
Central
Delta
Andhra
Pradesh.
Following
norms
GEC-2015,
estimated
past
decade
from
2012-13
to
2021-22
and
it
found
that
rate
ranging
438135.8
ha-m
year
2015-16
1677730
2013-14.While
computing
gross
recharge,
attributed
rainfall,
seepage,
irrigation
return
flow
ponds/tanks
are
considered.
