i-RAT: A discussion support system to rapidly assess economic and environmental impacts resulting from different sugarcane irrigation practices
Journal Publication ResearchOnline@JCUAbstract
Water pollution and climate change are among the greatest threats to the iconic Great Barrier Reef (GBR). To improve the GBR's long-term outlook, making improvements on these fronts is required. Owing to the complex interactions between soils, climate, and farm management, a tool is needed to guide agricultural land managers about which management practice changes are more likely to deliver improved water quality and climate resilience outcomes whilst maintaining profitability. Using concepts drawn from social studies of science and technology, a ‘discussion’ support system (DSS) named Irrigation Rapid Assessment Tool (i-RAT) was developed through participatory processes designed to enhance co-learning from the development of this DSS. i-RAT is a rapid assessment-visualisation tool in an interactive web application (https://i-rat.net) to visualise the impacts of changed irrigation practices for sugarcane farmers and extension staff. Specifically, i-RAT compares these impacts regarding farm economics, water quality, productivity, carbon and nitrogen cycles, and greenhouse gas emission. The core of i-RAT is the sugarcane module from the Agricultural Production Systems sIMulator (APSIM) modelling platform. i-RAT was first developed for the Burdekin sugarcane growing region in Queensland (Australia's largest sugarcane producing region). Various soil types and management scenarios representing farming practices in the Burdekin region were used for simulations (1971–2021) to generate a datacube. In this paper, we describe how fundamental learnings about more (drought) resilient farming systems and more sustainable irrigation practices can be extracted from i-RAT. Details of the participatory approach with research and industry partners that informed the design and function of i-RAT and how APSIM was set up and parameterised are described. A ‘what-if’ analysis demonstrated the i-RAT features and application.
Journal
Computers and Electronics in Agriculture
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Volume
215
ISBN/ISSN
1872-7107
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Pages Count
13
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Publisher
Elsevier
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DOI
10.1016/j.compag.2023.108380