FORECASTING REGIONAL CROP PRODUCTION USING SOI PHASES - AN EXAMPLE FOR THE AUSTRALIAN PEANUT INDUSTRY

Using peanuts as an example, a generic methodology is presented to for ward-estimate regional crop production and associated climatic risks b ased on phases of the Southern Oscillation Index (SOI). Yield fluctuat ions caused by a highly variable rainfall environment are of concern t o peanut processing and marketing bodies. The industry could profitabl y use forecasts of likely production to adjust their operations strate gically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simula tion model allows the derivation of yield probability distributions ba sed on historic rainfall data. This information is available shortly a fter planting a crop and at least 3-5 months prior to harvest. The stu dy shows that in years when the November-December SOI phase is positiv e there is an 80% chance of exceeding average district yields. Convers ely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average dist rict yields, but a 95% chance of below average yields. This informatio n allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.