Value of seasonal climate forecasts in reducing economic losses for grazing enterprises: Charters Towers case study
Duc-Anh An-Vo A B C , Kate Reardon-Smith
A C D , Shahbaz Mushtaq A C , David Cobon A C , Shreevatsa Kodur C and Roger Stone A C
+ Author Affiliations
- Author Affiliations
A University of Southern Queensland, Centre for Applied Climate Sciences, Darling Heights, Toowoomba, Qld 4350, Australia.
B University of Southern Queensland, Institute for Advanced Engineering and Space Sciences, Toowoomba, Qld 4350, Australia.
C University of Southern Queensland, Institute for Life Sciences and the Environment, Toowoomba, Qld 4350, Australia.
D Corresponding author. Email: kathryn.reardon-smith@usq.edu.au
The Rangeland Journal 41(3) 165-175 https://doi.org/10.1071/RJ18004
Submitted: 23 January 2018 Accepted: 29 May 2019 Published: 11 July 2019
Abstract
Seasonal climate forecasts (SCFs) have the potential to improve productivity and profitability in agricultural industries, but are often underutilised due to insufficient evidence of the economic value of forecasts and uncertainty about their reliability. In this study we developed a bio-economic model of forecast use, explicitly incorporating forecast uncertainty. Using agricultural systems (ag-systems) production simulation software calibrated with case study information, we simulated pasture growth, herd dynamics and annual economic returns under different climatic conditions. We then employed a regret and value function approach to quantify the potential economic value of using SCFs (at both current and improved accuracy levels) in decision making for a grazing enterprise in north-eastern Queensland, Australia – a region subject to significant seasonal and intra-decadal climate variability. Applying an expected utility economic modelling approach, we show that skilled SCF systems can contribute considerable value to farm level decision making. At the current SCF skill of 62% (derived by correlating the El Niño Southern Oscillation (ENSO) signal and historical climate data) at Charters Towers, an average annual forecast value of AU$4420 (4.25%) was realised for the case study average annual net profit of AU$104 000, while a perfect (no regret) forecast system could result in an increased return of AU$13 475 per annum (13% of the case study average annual net profit). Continued improvements in the skill and reliability of SCFs is likely to both increase the value of SCFs to agriculture and drive wider uptake of climate forecasts in on-farm decision making. We also anticipate that an integrated framework, such as that developed in this study, may provide a pathway for better communication with end users to support improved understanding and use of forecasts in agricultural decision making and enhanced sustainability of agricultural enterprises.
Additional keywords: economic value, grazing management, productivity, profitability, seasonal climate forecast, uncertainty.
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