The potential value of seasonal climate forecasting in managing cropping systems

There is considerable interest in exploring the value of seasonal climate forecasts in assisting farmers to manage cropping systems, not only for short-term decisions on crop management but also for longer-term strategic decisions on crop rotations. This paper reviews a range of applications for climate forecasts, but focuses on cropping systems issues that would benefit from long lead-time forecasts. A specific case study is used to demonstrate the potential for using the Southern Oscillation Index in assisting the incorporation of opportunity cropping into dryland cotton production systems. In the case study, the standard dryland cropping rotation of long fallowing from sorghum (through a subsequent summer fallow) to cotton is compared to alternative fixed rotations and to a rotation influenced by an SOI forecast. The decision point is the October after sorghum harvest where the manager can choose to proceed with the standard slimmer fallow or plant sorghum or cotton in that season with the intention in all cases of planting cotton in the following summer. These three fixed rotations (fallow-cotton, sorghum-cotton, cotton-cotton) are compared to an SOI-influenced strategy using a simulation analysis over the long-term climate record for Dalby, Qld. The simulation case study demonstrated that SOI contributed some skill to improving management decisions over a two-year rotation. By changing between fallow-cotton, sorghum-cotton or cotton-cotton rotations based on the SOI phase in the August-September period preceding the next two summers, average gross margins for the two year period increased by 14% over a standard fallow-cotton rotation. At the same time, soil loss from erosion was reduced by 23% and cash flow was improved in many years because an extra crop was sown. The SOI-based strategy did however increase the risk of economic loss from 5% of years for the standard fallow-cotton rotation to 9%, but this risk was considerably less than the 15% for sorghum-cotton and 19% for cotton-cotton rotations. In conclusion, there are many decisions in the management of dryland cropping systems that would greatly benefit from climate forecasts with persistence in skill out to two years in duration. The case study used in this paper demonstrated some skill in using the SOI in choosing a cropping rotation of two-year duration. Such applications are the obvious next frontier both for the development of enhanced forecasting schemes and for their application within the cropping systems of northern Australia and possibly elsewhere.