Advancing a farmer decision support tool for agronomic decisions on rainfed and irrigated wheat cropping in Tasmania

Abstract

Well-designed agricultural decision support tools (DS) equip farmers with a rapid, easy way to compare multiple scenarios as well as the influence of different management strategies on crop production. One such tool, CropARM (http://www.armonline.com.au) assists users in establishing a framework of risk, with simulations incorporating climate scenarios and management actions, such as fertiliser rates, sowing time, row spacing, and irrigation regimes. When used in conjunction with soil and climate characteristics, biophysical model-based DS tools provide information that complements farmer experience and helps establish a framework for risk management given local climate characteristics. In this study, we used the APSIM model to provide the simulation data necessary to expand CropARM for new management conditions and environments in southern Australia. Prior to this work being undertaken, no CropARM data was available for Tasmania and no sites in CropARM allowed users to compare rainfed and irrigated wheat crops. This study collated data from 27 plots across ten sites in Tasmania, from the period 1981 to 2011, under both rainfed and irrigated conditions. APSIM was parameterised with these field observations and the subsequent scenario simulations were used to populate CropARM. Wheat cultivars used in the parameterisation of APSIM include Brennan, Isis, Mackeller, Revenue, Tennant (winter types) and Kellalac (spring type). The validation showed reliable model parameterisation, with an r2 value of close to 1, which is considered satisfactory. 670,680 simulations were undertaken and incorporated within the CropARM database for wheat cropping systems across Tasmania. With regularly updated climate streams, the free online framework provided by CropARM gives users the ability to assess downside risks associated with several different crop management alternatives, and by simultaneously comparing multiple scenarios, users can select management options that are likely to adhere most closely with their desired management objectives.