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RESEARCH ARTICLE
Contents Vol 59(2)

Quality and potential utility of ENSO-based forecasts of spring rainfall and wheat yield in south-eastern Australia

M. R. Anwar A E , D. Rodriguez B , D. L. Liu C , S. Power D and G. J. O’Leary A
+ Author Affiliations
- Author Affiliations

A Primary Industries Research Victoria, 110 Natimuk Rd, Horsham, Vic. 3400, Australia.

B Agricultural Production Research Unit (APSRU), Queensland Department of Primary Industries & Fisheries, PO Box 102, Toowoomba, Qld 4350, Australia.

C E.H. Graham Centre for Agricultural Innovation (NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, PMB Wagga Wagga, NSW 2650, Australia.

D Bureau of Meteorology, GPO Box 1289, Melbourne, Vic. 3001, Australia.

E Corresponding author. Email: muhuddin.anwar@dpi.vic.gov.au

Australian Journal of Agricultural Research 59(2) 112-126 https://doi.org/10.1071/AR07061
Submitted: 24 April 2007  Accepted: 10 October 2007   Published: 19 February 2008

Abstract

Reliable seasonal climate forecasts are needed to aid tactical crop management decisions in south-eastern Australia (SEA). In this study we assessed the quality of two existing forecasting systems, i.e. the five phases of the Southern Oscillation Index (SOI) and a three phase Pacific Ocean sea-surface temperatures (SSTs), to predict spring rainfall (i.e. rainfall from 1 September to 31 November), and simulated wheat yield. The quality of the forecasts was evaluated by analysing four attributes of their performance: their reliability, the relative degree of shift and dispersion of the distributions, and measure of forecast consistency or skill. Available data included 117 years of spring rainfall and 104 years of grain yield simulated using the Agricultural Production Systems Simulator (APSIM) model, from four locations in SEA. Average values of spring rainfall were 102–174 mm with a coefficient of variation (CV) of 47%. Average simulated wheat yields were highest (5609 kg/ha) in Albury (New South Wales) and lowest (1668 kg/ha) in Birchip (Victoria). The average CV for simulated grain yields was 36%. Griffith (NSW) had the highest yield variability (CV = 50%). Some of this year-to-year variation was related to the El Niño Southern Oscillation (ENSO). Spring rainfall and simulated wheat yields showed a clear association with the SOI and SST phases at the end of July. Important variations in shift and dispersion in spring rainfall and simulated wheat yields were observed across the studied locations. The forecasts showed good reliability, indicating that both forecasting systems could be used with confidence to forecast spring rainfall or wheat yield as early as the end of July. The consistency of the forecast of spring rainfall and simulated wheat yield was 60–83%. We concluded that adequate forecasts of spring rainfall and grain yield could be produced at the end of July, using both the SOI and SST phase systems. These results are discussed in relation to the potential benefit of making tactical top-dress applications of nitrogen fertilisers during early August.

Additional keywords: APSIM, simulated yield, absolute median difference, dispersion, reliability, skill.


Acknowledgments

The authors thank Andries Potgieter at the Queensland Department of Primary Industries and Fisheries for his valuable comments on methodology for reliability analysis. This study was supported by PIRVic and the Grains Research and Development Corporation through grant DAV00006. We thank Drs Kim Lowell, Helen Fairweather, and an anonymous referee for helpful comments on an early version of the manuscript.


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