Modeling integrated soil fertility management for maize production in Kenya using a Bayesian calibration of the DayCent model
Biogeosciences,
Год журнала:
2024,
Номер
21(16), С. 3691 - 3716
Опубликована: Авг. 22, 2024
Abstract.
Sustainable
intensification
schemes
such
as
integrated
soil
fertility
management
(ISFM)
are
a
proposed
strategy
to
close
yield
gaps,
increase
fertility,
and
achieve
food
security
in
sub-Saharan
Africa.
Biogeochemical
models
DayCent
can
assess
their
potential
at
larger
scales,
but
these
need
be
calibrated
new
environments
rigorously
tested
for
accuracy.
Here,
we
present
Bayesian
calibration
of
DayCent,
using
data
from
four
long-term
field
experiments
Kenya
leave-one-site-out
cross-validation
approach.
The
experimental
treatments
consisted
the
addition
low-
high-quality
organic
resources,
with
without
mineral
nitrogen
fertilizer.
We
assessed
accurately
simulate
key
elements
sustainable
intensification,
including
(1)
yield,
(2)
changes
carbon
(SOC),
(3)
greenhouse
gas
(GHG)
balance
CO2
N2O
combined.
Compared
initial
parameters,
showed
improved
simulations
maize
grain
(with
Nash–Sutcliffe
model
efficiency
(EF)
increasing
0.36
0.50)
SOC
stock
EF
0.55).
those
also
by
site
site-specific
ranging
between
0.15
0.38
−0.9
0.58
changes).
cross-validation-derived
posterior
parameter
distributions
(leaving
out
one
each)
were
similar
all
parameter.
Together
performance
different
sites
cross-validation,
this
indicated
robustness
parameterization
its
reliability
conditions
Kenya.
While
poorly
reproduced
daily
emissions
−0.44
−0.03
site),
cumulative
seasonal
simulated
more
(EF
0.06
0.69
site).
yield-scaled
GHG
was
highest
control
N
(between
0.8
1.8
kg
equivalent
per
across
sites)
about
30
%
40
lower
treatment
that
combined
application
manure
rate
1.2
t
C
ha−1
yr−1.
In
conclusion,
our
results
indicate
is
well
suited
estimating
impact
ISFM
on
changes.
They
trade-off
stronger
low-fertility
preventing
losses,
while
difficult
through
external
priority
production
Язык: Английский
Multi-decadal and regional validation of the AMG model at county and grid scales unravels the role of crop residue inputs in increasing soil organic carbon stocks in the Tuojiang River Basin, China
Agriculture Ecosystems & Environment,
Год журнала:
2024,
Номер
371, С. 109092 - 109092
Опубликована: Май 21, 2024
Язык: Английский