Agricultural drought analyses for temperate Australia using a biophysical pasture model. 2. Relationship between rainfall and the start and end of predicted droughts
G. M. Lodge A C and I. R. Johnson BA NSW Department of Primary Industries, Tamworth Agricultural Institute, 4 Marsden Park Road, Calala, NSW 2340, Australia.
B IMJ Consultants, PO Box 1590, Armidale, NSW 2350, Australia.
C Corresponding author. Email: greg.lodge@dpi.nsw.gov.au
Australian Journal of Agricultural Research 59(11) 1061-1067 https://doi.org/10.1071/AR08076
Submitted: 3 October 2007 Accepted: 11 August 2008 Published: 14 October 2008
Abstract
This paper reports relationships between predicted soil water content (SWC) on the first day of the month (SWCFOM, mm of water) and previous monthly rainfall for 100 years of daily climate data (1905–2005) at four sites (Albany, Western Australia; Hamilton, Victoria; and Wagga Wagga and Barraba, New South Wales).
Overall, predicted SWCFOM was correlated (P < 0.05) with rainfall in the previous one, two, or three months. However, the proportion of variation in SWCFOM that could be attributed to its regression on previous rainfall was variable and the relationship tended to improve when individual months were examined. At the three winter-rainfall sites (Albany, Hamilton, and Wagga Wagga), there was a reasonably good relationship between the start of a predicted drought and the end of the growing season and also between the end of a predicted drought and the occurrence of break-of-season. However, for the summer-rainfall dominant site at Barraba, rainfall occurrence was less seasonally defined and there was no clear relationship.
While analysis of historical rainfall data for the months in which predicted agricultural droughts started or ended provided some useful insights, it was concluded that it would probably be more instructive to model SWC outcomes for a range of future rainfall scenarios and then examine their likelihood of occurrence using rainfall percentiles.
Additional keywords: soil water content, monthly rainfall, percentiles, break-of-season.
Acknowledgments
Ian Johnson was partly funded by Dairy Australia, Meat and Livestock Australia, AgResearch New Zealand, and the University of Melbourne through the Whole Farm Systems Ability and Tools for the Grazing Industries project.
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