HOW BAD IS THE DROUGHT? USING A CROPPING SYSTEMS MODEL TO ASSESS SEVERITY OF DROUGHT
B.A. Keating¹, J.P. Dimes², and R.L .McCown^2
1 QDPI/CSIRO - APSRU, 306 Carmody Road, St Lucia, Qld 4067
² QDPI/CSIRO - APSRU, PO Box 102, Toowoomba, Qld 4350

Climatic variability is a natural part of farming in Australia and current Government policy sees drought more as a normal part of the production environment, than an unpredictable disaster requiring relief. Despite this philosophy, the notion remains that drought policy should provide assistance to producers in those calamitous circumstances where government action is required as a measure of last resort (1). Government support to farmers suffering in the 1994 drought was provided because the circumstances were viewed as calamitous, although this view was not shared by all commentators (see for example the influential articles by farmer and ex Finance Minister, Peter Walsh in the Financial Review, 16-8-94). This paper examines approaches and criteria for assessing the severity of a prolonged drought.

METHODS

APSIM (Agricultural Production Systems Simulator) (2) was configured as a winter wheat - summer fallow cropping system in which temporal variability was associated only with rainfall amounts and distribution. The combination of retention of crop residues and the addition of 60 kg N ha^-1 at sowing of each crop ensured that soil fertility was non-limiting throughout the simulation. Other constraints such as pests, diseases and weeds were not considered. All other agronomic practices were assumed constant throughout the simulation period. Climate files for Dalby, Roma, Goondiwindi and Capella in Qld and Moree in north NSW were prepared using procedures outlined by Meinke et al. (3). The paper analyses the recent drought in the north-eastern cereal zone via the simulated wheat yields expressed on a four-year running mean basis.

RESULTS AND DISCUSSION

Average wheat yields estimated for sites such as Dalby and Roma over the 1991-1994 period represent some of the lowest values over the 110 year climate record, confirming the local view on the severity of this four-year drought. In contrast, while 1994 was a disastrous year in Moree, both in the model and on the ground, reasonable seasons and yields in the preceding years meant that the 4 year running mean was about on the median of expectation based on simulations over the climate record. Agricultural drought will be influenced by both the quantity and distribution of rainfall in relation to crop planting opportunities and crop developmental stage. In addition, the impact of prior-season rainfall needs to be considered in regions where fallows are important in storing water for subsequent crops. These factors are implicitly considered in the simulation approach but are difficult to quantify in climatic analyses. The poster summarises strengths and weaknesses of a simulation approach to the assessment of the severity of drought.

REFERENCES

1. Drought Policy Review Task Force. 1990. Final Report May 1990. Aust. Govt. Publ. Service, Canberra.
2. McCown, R.L., Hammer, G.L., Hargreaves, J.N.G., Holzworth, D.P. and Freebairn, D.M. 1995. Agric. Systems 48 (in press).
3. Meinke, H., Carberry, P.S., McCaskill, M.R., Hills, M.A. and McLeod, I. 1995. Agric. and Forest Meteorology 72, 295-316.
APSIM - SUGAR: A MODELLING FRAMEWORK FOR SUGARCANE PRODUCTION SYSTEMS
B.A. Keating¹, M.J. Robertson², R.C. Muchow³, and N.I. Huth^1
1 QDPI/CSIRO - APSRU, 306 Carmody Road, St Lucia, Qld 4067
² CSIRO Division of Tropical Crops and Pastures, Davies Lab., Townsville, Qld. 4810
³ CSIRO Division of Tropical Crops and Pastures, 306 Carmody Road, St. Lucia, Qld 4067

Regardless of production system, integration and generalisation are major challenges facing agricultural research. Simulation models have a role in spatial and temporal extrapolation and in the evaluation of complex interactions between climate, soil, plant and management factors. APSIM (Agricultural Production Systems Simulator (1)) provides a means by which biological (crop, weeds, pastures etc.), bio-physical (e.g. soil water, soil nitrogen, etc.), environmental and management sub-models can be combined into comprehensive simulators of agricultural systems.

METHODS

Progress on the development of a sugarcane crop module for APSIM is described. The module simulates potential growth in relation to temperature and radiation. Water and nitrogen deficits limit production below this potential. Leaf appearance and expansion, light interception and radiation conversion to dry matter are simulated and dry matter partitioned to leaf blade, cabbage, structural stem, sucrose and root carbon pools. Water use and N uptake are performed by the sugar module, via communications with other APSIM soil modules which track the status of these variables. The module simulates plant/ratoon cycles for sugarcane cultivars that have been shown to differ in a small number of key physiological / genotypic parameters.

Model performance is reported against datasets spanning the Australian sugar industry production regions, together with data from sugarcane crops grown in Hawaii and South Africa. Intended applications for such a model in research for the Australian sugar industry are outlined.

RESULTS AND DISCUSSION

The outcome of this work has been a powerful systems simulation capability for the sugar industry, through the combination of discrete work on a sugarcane module, with on-going development of soil, residue and management modules in the grains industries. Both grains and sugar industries benefit from this association. The wider testing and application of APSIM modules made possible by application to the sugar industry, returns a benefit to the grains industry in the form of new or more robust component modules.

ACKNOWLEDGMENTS

The support provided by the Sugar Research and Development Corporation (SRDC) in both experimental studies and sugarcane module development and testing is acknowledged.

REFERENCES

4. McCown, R.L., Hammer, G.L., Hargreaves, J.N.G., Holzworth, D.P. and Freebairn, D.M. 1995. Agricultural Systems 48 (in press).