The impact of El Niño Southern Oscillation on seasonal drought in the southern Australian grainbelt
P. T. Hayman A C , A. M. Whitbread B and D. L. Gobbett BA SARDI Climate Applications, Waite Research Precinct, GPO Box 397, Adelaide, SA 5001, Australia.
B CSIRO Sustainable Ecosystems, PMB 2 Glen Osmond, SA 5064, Australia.
C Corresponding author. Email: peter.hayman@sa.gov.au
Crop and Pasture Science 61(7) 528-539 https://doi.org/10.1071/CP09221
Submitted: 27 July 2009 Accepted: 13 May 2010 Published: 6 July 2010
Abstract
The cropping simulation model APSIM (Agricultural Production Systems Simulator) was used to investigate the pattern of seasonal moisture stress during the growing season for four medium- to high-rainfall regions and four low-rainfall regions in the southern Australian grains belt over the period 1906–2007. Cluster analysis of the pattern of crop water stress experienced by each simulated crop was used to devise season types for the study sites. Average crop moisture stress for two periods up to grain filling, i.e. germination to 600°C days of thermal accumulation (~Zadoks 0–32) and from 600 to 1200 days of thermal accumulation (~Zadoks 32–71), was used to devise a classification of season type: low moisture stress early and late (L-L), low early and high late (L-H), high early and low late (H-L) and high early and late (H-H). Using regional rainfall we found that El Niño events are associated with double the risk of the season being in the lowest tercile from 33 to 67% and La Niña events increase the chance of being in the top tercile to 50%. Although there was a wide range of simulated yields in El Niño and La Niña years, for most sites the average yields were lower in El Niño years and higher in La Niña years. For most sites in the study 6 or 7 of the worst 10 years were El Niño, 3 Neutral and 1 or nil cases were La Niña events. This contrasts with a pattern assuming no El Niño Southern Oscillation (ENSO) influence of 2 El Niño, 6 Neutral and 2 La Niña events. Analysis of the relationship of season types identified by the cluster analysis to ENSO showed significant results for high-rainfall sites but not for low-rainfall sites. One of the reasons for this is that in low-rainfall sites, moisture stress occurs in most seasons. We conclude that there is good reason for farmers and advisers in South Australia to pay attention to a forecast of ENSO for the coming season as one part of their risk management strategy. We conclude on the need to think clearly about drought and aridity in these low-rainfall environments and comment on how this analysis further questions canopy management as a means of dealing with drought risk.
Additional keywords: APSIM, climate risk, El Niño Southern Oscillation, seasonal drought.
Acknowledgments
Hayman’s input was partly funded by an ACIAR project on seasonal climate forecasting and a Centre for Natural Resource Management project on climate risk. The efforts of Whitbread and Gobbett were supported by the Mallee Sustainable Farming Inc. project and Training Growers to Manage Soil Water Project (GRDC Research Code CSA00011) supported by the GRDC and CSIRO Sustainable Ecosystems. Chris Dyson offered guidance on statistics, Bronya Alexander, Michael Robertson and two thoughtful referees’ reports improved earlier versions.
Asseng S, van Herwaarden AF
(2003) Analysis of the benefits to wheat yield from assimilates stored prior to grain filling in a range of environments. Plant and Soil 256, 217–229.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
(accessed 8 June 2010).
Chapman S,
Cooper M, Hammer GL
(2002) Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments. Australian Journal of Agricultural Research 53, 379–389.
| Crossref | GoogleScholarGoogle Scholar |
(accessed 8 June 2010)
Risbey JS,
Pook MJ,
McIntosh PC,
Wheeler MC, Hendon H
(2009) On the remote drivers of rainfall variability in Australia. Monthly Weather Review 137, 3233–3253.
| Crossref | GoogleScholarGoogle Scholar |
(accessed 8 June 2010).
Ummenhofer CC,
England MH,
McIntosh PC,
Meyers GA,
Pook MJ,
Risbey JS,
Gupta AS, Taschetto AS
(2009) What causes southeast Australia’s worst droughts? Geophysical Research Letters 36, L04706.
| Crossref | GoogleScholarGoogle Scholar |
(accessed March 2010).
Yunusa IAM,
Bellotti W,
Moore AD,
Probert ME,
Baldock JA, Miyan SM
(2004) An exploratory evaluation of APSIM to simulate growth and yield processes for winter cereals in rotation systems in South Australia. Australian Journal of Experimental Agriculture 44, 787–800.
| Crossref | GoogleScholarGoogle Scholar |
Zhang Q,
Guan Y, Yang H
(2008) ENSO amplitude change in observation and coupled models. Advances in Atmospheric Sciences 25, 361–366.
| Crossref | GoogleScholarGoogle Scholar |
CAS |