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Near-term pasture growth rate forecasts: which method works best?
Citation
Rawnsley, RP and Harrison, MT and Phelan, DC and Corkrey, R and Henry, DA, Near-term pasture growth rate forecasts: which method works best?, Proceedings of the 17th Australian Agronomy Conference 2015, 20-24 September 2015, Hobart, Australia, pp. 1-4. (2015) [Refereed Conference Paper]
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Copyright Statement
Copyright 2015 the author
Official URL: http://www.agronomyaustralia.org/
Abstract
Knowledge of near-term pasture growth rates helps livestock farmers with important management decisions, particularly feed budgeting. Here we contrast three approaches for generating three-month pasture growth rate forecasts using a biophysical plant model. Two methods were based on statistical growth rates simulated using either historical climate data or historical data having Southern Oscillation Indices (SOI) matching those of the current month. The third method accounted for current earth and ocean measurements using dynamic climate outlooks from the global circulation model POAMA. We used twelve months of measured pasture growth rates to calibrate the model, and then contrast each forecasting method over several three-month periods using empirical cumulative distribution functions. In general, dynamic forecasts from POAMA had the greatest skill and reliability in forecasting the near term (30 days) pasture growth rates, indicating that the use of current climate outlooks and recent weather measurements are more reliable than using methods based on historically measured data. This work is being developed into a graphical-user interface that will allow farmers to view a near -term pasture growth rates forecast using an online tool.
Item Details
| Item Type: | Refereed Conference Paper |
|---|---|
| Keywords: | forecasting, weather, pasture, growth rate, climate, pasture growth forecasting, growth rates, DairyMod, seasonal climate forecasts |
| Research Division: | Agricultural, Veterinary and Food Sciences |
| Research Group: | Agriculture, land and farm management |
| Research Field: | Agricultural production systems simulation |
| Objective Division: | Animal Production and Animal Primary Products |
| Objective Group: | Pasture, browse and fodder crops |
| Objective Field: | Sown pastures (excl. lucerne) |
| UTAS Author: | Rawnsley, RP (Dr Richard Rawnsley) |
| UTAS Author: | Harrison, MT (Associate Professor Matthew Harrison) |
| UTAS Author: | Phelan, DC (Mr David Phelan) |
| UTAS Author: | Corkrey, R (Dr Ross Corkrey) |
| ID Code: | 102159 |
| Year Published: | 2015 |
| Deposited By: | Tasmanian Institute of Agriculture |
| Deposited On: | 2015-07-31 |
| Last Modified: | 2016-05-09 |
| Downloads: | 254 View Download Statistics |
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