B.CCH.2114 - Co-Funding Deed AgScore project under the Managing Climate Variability (MCV) program
Did you know the Bureau of Meteorology uses one of the most widely used seasonal outlooks in Australia and was ranked highly among the top-performing models used by primary producers in Australia?
| Project start date: | 04 August 2020 |
| Project end date: | 27 February 2022 |
| Publication date: | 16 August 2024 |
| Project status: | Completed |
| Livestock species: | Grain-fed Cattle, Grass-fed Cattle, Sheep, Goat, Lamb |
| Relevant regions: | Cold wet, Dry, Mediterranean, Tropical warm season wet, Sub-tropical moist, Sub-tropical sub-humid, Temperate, Temperate sub-humid, Tropical Moist, International, Tropical wet |
Summary
This project made use of an innovative software tool providing robust comparison of seasonal climate models using agricultural relevant metrics to help primary producers assess seasonal forecasts for more profitable decision making and climate risk management.
Objectives
To model the economic value of using seasonal climate forecasts information to aid strategic on-farm decisions such as crop choice prior to sowing.
Key findings
Overall, only small differences (<5%) in gross margins between baseline scenarios were found in the case study farms that incorporated seasonal rainfall forecasts into their management choices. The limited potential of rainfall forecasts to improve profitability can be explained in part by conservative management responses to even more favourable conditions in the case study farms that were simulated.
Benefits to industry
Forecasts translated into yield or productivity-based predictions have obvious benefit to users in that they incorporate multiple climate drivers i.e. rainfall and temperature, and integrate seasonal trajectories of plant growth. However, the results indicate that the overall signal and the corresponding accuracy of the yield forecast may be similar to the rainfall forecast for the same time of year and location.
MLA action
Given the results it is unlikely that MLA will invest in further tool development in this area.
Future research
1) Investigate the potential for incorporating other sources of local farm information that might strengthen predictions of yield or productivity when generating a forecast. For example, soil water estimates, particularly early in the season, might bolster forecasts of crop yield.
2) Investigate the concept of a ‘perfect knowledge’ forecast as a means to gauge the extent to which management decisions might be optimised to the potential options available within a given enterprise.
3) Explore the role of multi-week forecasts that might address decisions that have received less attention in the past. This may include spray planning, irrigation scheduling in response to temperature fluctuations and harvest logistics.
More information
| Project manager: | Doug McNicholl |
| Contact email: | reports@mla.com.au |
| Primary researcher: | Grains Research & Development Corp |
