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dominated regions of northern New South Wales (NSW)
and southern Queensland.
One of our Australian case studies attempts to shed
light on whether SCFs are of practical value to mixed
farming systems typical of central and southern NSW. We
use a whole farm analysis to assess the value of SCFs to
improve decisions about crop and livestock mix as well
as the choice of crop fertilizer inputs at sowing.
Approach
In order to have value, SCFs must lead to a different crop
and livestock mix or a different level of crop fertilizer
inputs. Value arises from decisions which either reduce
losses associated with expected adverse climatic
conditions or take advantage of expected good climatic
conditions.
A representative farm model for the Central West
region was used to assess the outcomes of decisions taken
with and without SCFs. The model captures some of the
whole farm interactions, resource limitations, and other
influences that may affect the value of SCFs. It uses
biological outputs from a crop simulation model to
determine the optimal area of crops and pasture to grow
and the optimal level of fertilizer to apply.
The Agricultural Production Systems Simulator
(APSIM) simulated crop yields for a period of 92 years,
under three starting levels of soil moisture and four
nitrogen application rates.
The climate forecast system assessed in this study is
referred to as the ‘SOI Phase’ system. The phases give
credence to both the absolute value of the SOI and its
rate of change. Seasons in the historical record are
categorized into one of five phases based on two
consecutive monthly values of the SOI. The five phases
are as follows:
Phase 1 - SOI consistently negative (SOI negative)
Phase 2 - SOI consistently positive (SOI positive)
Phase 3 - SOI rapidly falling (SOI falling)
Phase 4 - SOI rapidly rising (SOI rising)
Phase 5 - SOI neutral (SOI neutral)
Phases 1 and 3 identified in late autumn are
associated with below average rainfall in the following
winter and early spring period in eastern Australia while
Phases 2 and 4 are associated with above average rainfall.
Phase 5 is the neutral phase and is associated with
generally average rainfall conditions over the same period.
To estimate the value of an SCF, we rely only on the
observed influence of the SCF on rainfall probabilities and
its correlation with crop yields.
The ‘without SCF’ case (fixed management) is based
on a single farm strategy that performs best in an average
year over all climatic years. In contrast, the ‘with SCF’ case
(flexible management) implements the best farm strategy
for a given forecast type (phase) based on the subset of
years of that phase type. The overall value of SCF is found
by comparing farm profits between fixed and flexible
management over the 92-year simulation period.
Figure 1. Average farm profit with and without seasonal climate forecasts (SOI Phase)
Findings
Average returns
Farm profits with and without the SCF
under different levels of soil moisture are
shown in Figure 1. Farm profits improve as
the starting level of soil moisture increases.
The difference between the bars indicates
the gain in farm profit from forecast use.
Using the SCF at the lowest, moderate, and
maximum level of soil moisture improves
farm returns by 11.6 percent, 7.9 percent,
and 0.2 percent, respectively.
The SCF is found to be of most value
under low levels of starting soil moisture.
Low levels of starting soil moisture mean
that crop yields are more dependent on
in-season rainfall and, hence, better