University Of Tasmania
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Near-term pasture growth rate forecasts: which method works best?

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conference contribution
posted on 2023-05-23, 10:14 authored by Richard RawnsleyRichard Rawnsley, Matthew HarrisonMatthew Harrison, Phelan, DC, Stephen Corkrey, Henry, DA
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.


Department of Agriculture


Publication title

Proceedings of the 17th Australian Agronomy Conference 2015


T Acuna, M Harrison, C Moeller, D Parsons




Tasmanian Institute of Agriculture (TIA)


Australian Society of Agronomy

Place of publication


Event title

17th Australian Agronomy Conference 2015

Event Venue

Hobart, Australia

Date of Event (Start Date)


Date of Event (End Date)


Rights statement

Copyright 2015 the author

Repository Status

  • Open

Socio-economic Objectives

Sown pastures (excl. lucerne)