Abstract:
The ability to accurately translate the current condition of the crops into yield foresight
expected at the end of the growing season helps the governments and other policymakers
around the world to make informed decisions on matters relating to food security and
economic planning
. While the Agricultural Production Systems Simulator (APSIMWheat)
is
the
widely
used
wheat-yield
simulator
in
the
world
today,
its
major
challenge
is
the
lack of adequate data for calibration and parameterization of the model in many
developing countries. This aspect inhibits the model's performance. This study utilized
earth observation data derived from sentinel-2 to calibrate APSIM-wheat (version 7.5
R3008) to compensate for the data inadequacy and improve the model's performance in
developing countries. The phenological statistics generated from sentinel2
were
integrated
into
the
model
as
part
of
the
input
parameters.
The
phenological
statistics
were
based
on
NDVI,
MSI
and
NPCRI
and were used with other crop management data
collected at the field level. When the phenological statistics from sentinel-2 were used to
calibrate APSIM-Wheat, the improved model outperformed the conventional APSIMWheat
by 18.65%
since
the
RRMSE
improved
from
25.99%
to
7.34%;
RMSE
from
1784
Kgha-
1
to 501 Kgha-
1
and R
2
from o.6 to 0.82 respectively.