Abstract
The greatest water quality risks to the Great Barrier Reef are excess nutrients, fine sediments and pesticides contained in terrestrial runoff as these are a major issue affecting the health and resilience of the Great Barrier Reef. In response to a decline in water quality entering the Great Barrier Reef lagoon, the Reef Water Quality Protection Plan (Reef Plan) was developed as a joint Queensland and Australian Government initiative. Reef Plan set water quality improvement targets. Progress towards these targets are assessed through the Paddock to Reef Integrated Monitoring, Modelling and Reporting Program. To help achieve the targets, improvements in land management are being driven by a combination of the Australian Government’s reef investments, along with Queensland Government and industry-led initiatives in partnership with regional Natural Resource Management groups. Identifying farm management practices that reduce sediment, nutrient and pesticide runoff loads at a paddock scale is the first step towards improving water quality at the larger catchment scale and subsequently in the Great Barrier Reef lagoon. To model the grains industry, farm management practices for dryland cropping were defined under a water quality risk framework. Practices in the framework primarily affect soil/sediment transport, nutrient and pesticide application practices; and were grouped as Low, Moderate-Low, Moderate and High risk practices. This paper summarises the paddock scale modelling of the effectiveness of improved management practices for reducing off farm losses of sediment, nutrients and pesticides in dryland grain cropping. Paddock scale agricultural models allow explicit representation of management options available to producers. These include changes in crop rotations, tillage intensity and pesticide and nutrient application timing and rate. Importantly, the ability to simulate management practices on a daily time step means that interactions between the timing of management events and rainfall can be calculated. The results of paddock scale modelling are used in the catchment models to assess the effects of farm scale management decisions on water quality for the whole of the Great Barrier Reef catchment. Key messages from the development and application of the paddock scale modelling for dryland grain cropping in the Great Barrier Reef catchments are: • Greatest overall reductions in soil erosion can be made by coupling reduced or zero-tillage practices with well-designed controlled traffic farming (CTF) systems. • Greater than 90% reduction in soil erosion results from changing management practice from “D” management scenarios (High risk; full cultivation) to “A” management scenarios (Low risk; zero-till farming with CTF and contour banks). • Soil erosion is greater in fallows after chickpea, mungbean and sunflower crops than after sorghum and wheat crops. This is due to the small amounts and more rapid decomposition of stubble after chickpea, mungbean and sunflower crops than after sorghum and wheat crops, leaving less cover to protect the soil surface. • Atrazine runoff loads from cropping land respond directly to both application rate and to time of application relative to runoff. Tillage and traffic systems had a secondary level of effect. • There was a clear trend of decreasing atrazine runoff load as a percentage of atrazine applied, with the change from D (High risk) to A (Low risk) management scenarios. However, total atrazine loads do not follow this trend because atrazine use increases with A and B management practices. This could be viewed as an outcome of practices that achieve Low risk sediment outcomes (reduced tillage) or the Water Quality Risk Framework could be improved to reduce atrazine use for low risk scenarios.
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Owens, J. S., Silburn, D. M., & Shaw, D. M. (2017). Modelling reductions of soil erosion and pesticide loads from grain cropping due to improved management practices in the Great Barrier Reef catchments. In Proceedings - 22nd International Congress on Modelling and Simulation, MODSIM 2017 (pp. 1969–1975). Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ). https://doi.org/10.36334/modsim.2017.l22.owens
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