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Applications of Seasonal Climate Forecasting in Agricultural and Natural Ecosystems pp 329–349Cite as

Aussie Grass: Australian Grassland and Rangeland Assessment by Spatial Simulation

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Part of the Atmospheric and Oceanographic Sciences Library book series (ATSL,volume 21)

Abstract

Defining drought, categorising current droughts, and assessing grassland and rangeland sustainability in a quantitative and scientific manner are important national issues for Australian State and Commonwealth governments, landholders and agribusiness. A challenge for ecologists and modellers of Australia’s grasslands and rangelands is to integrate biological models, geographic information systems, satellite imagery, economics, climatology and visual high-performance computing into readily available products that can provide monitoring and prediction advice in near real-time.

The QDNR systems approach to the management of native grasslands recognises that drought occurs at a regional scale, and that impacts on livestock and natural resources can be forecast using simple models of soil water, plant growth and animal performance Our vision for a comprehensive Australian Grassland and Rangeland Assessment System (Aussie GRASS) is one that consists of the best combination of rainfall analyses, seasonal climate forecasts, satellite and terrestrial monitoring, and simulation models of relevant biological processes. This will provide a rational basis for large-scale management decisions by graziers, extension workers, land resource managers, bureaucrats and politicians. Aussie GRASS products are currently used within the Queensland government for drought declaration assessments and applications for Drought Exceptional Circumstances.

The Aussie GRASS national spatial modelling framework allows agricultural simulation models to be run at a continental scale on a 0.05 degree (~5 km) grid. The simulation model currently in use by the Aussie GRASS project is the GRASP pasture model developed for tropical native pastures in Queensland by QDPI and QDNR. In the latest Aussie GRASS project, other regional models are being examined for their applicability to areas such as the southern winter perennial grass zone, chenopod shrublands or the high rainfall temperate zone.

The Queensland version of the Aussie GRASS model is currently used to produce data for a monthly report — A Summary of Seasonal Conditions in Queensland. Model outputs are used in conjunction with recorded and forecast rainfall, satellite imagery, Southern Oscillation Index and current drought declarations to build a comprehensive picture of the current and future seasonal conditions impacting on primary producers. Other numerous outputs from the model can be produced and tailored as required.

Keywords

  • Soil Erosion
  • Southern Oscillation Index
  • Water Resource Research
  • Pasture Community
  • Tree Basal Area

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Authors and Affiliations

  1. Queensland Department of Natural Resources, Queensland Centre for Climate Applications, 80 Meiers Rd, Indooroopilly, QLD, 4068, Australia

    J. O. Carter, W. B. Hall, K. D. Brook, G. M. McKeon, K. A. Day & C. J. Paull

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  1. J. O. Carter
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  2. W. B. Hall
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  3. K. D. Brook
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  4. G. M. McKeon
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  5. K. A. Day
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  6. C. J. Paull
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Editor information

Editors and Affiliations

  1. Queensland Department of Primary Industries, Toowoomba, Queensland, Australia

    G. L. Hammer

  2. Bureau of Meteorology Research Centre, PO Box 1289K, 3001, Melbourne, Victoria, Australia

    N. Nicholls

  3. CSIRO Division of Atmospheric Research, Melbourne, Victoria, Australia

    C. Mitchell

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Carter, J.O., Hall, W.B., Brook, K.D., McKeon, G.M., Day, K.A., Paull, C.J. (2000). Aussie Grass: Australian Grassland and Rangeland Assessment by Spatial Simulation. In: Hammer, G.L., Nicholls, N., Mitchell, C. (eds) Applications of Seasonal Climate Forecasting in Agricultural and Natural Ecosystems. Atmospheric and Oceanographic Sciences Library, vol 21. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9351-9_20

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  • DOI: https://doi.org/10.1007/978-94-015-9351-9_20

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