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Evaluation of the water use efficiency of alternative farm practices at a range of spatial and temporal scales: A conceptual framework and a modelling approach


  • Moore, A.D.
  • Robertson, M.J.
  • Routley, R.


Water is the principal limiting resource in Australian broadacre farming, and the efficiency with which farmers use water to produce various products is a major determinant both of farm profit and of a range of natural resource management (NRM) outcomes. We propose a conceptual framework based on multiple water use efficiencies (WUEs) that can be used to gain insight into high-level comparisons of the productivity and sustainability of alternative farming practices across temporal and spatial scales. The framework is intended as a data aggregation and presentation device. It treats flows of water, biomass and money in a mixed farming system; economic inefficiencies in these flows are tracked as they are associated with a range of NRM indicators. We illustrate the use of the framework, and its place in a larger research programme, by employing it to synthesise the results from a set of modelling analyses of the effect of land use choices on long-term productivity and a range of NRM indicators (frequency of low ground cover, deep drainage, N leaching rates and rate of change in surface soil organic carbon). The analyses span scales from single paddocks and years to whole farms and have been carried out with the APSIM and GRAZPLAN biophysical simulation models and the MIDAS whole-farm economic model. In single wheat crops in one study, different land uses in preceding years affect grain yield primarily by affecting the harvest index. When the scale changes to cropping rotations, the critical factor affecting overall water use efficiency is found to be the proportion of stored soil water that is transpired by crops. When ordinated in terms of their water use efficiencies, a set of 45 modelled rotation sequences at another location are differentiated mainly by the proportion of pasture in the rotation; when rotations are ordinated using key NRM indicators, the proportion of lucerne pasture is the main distinguishing factor. Finally, we show that for whole crop-livestock farms at three different locations across southern Australia, the pattern of water use efficiencies in the most profitable farming systems changes in similar ways as cropping proportion is altered. At this scale, land use choices affect multiple water use efficiency indices simultaneously and commodity prices determine the balance of the resulting economic tradeoffs. Limitations to the use of the WUE framework arising from its relative simplicity are discussed, as are other areas of farming systems research and development to which it can be applied.

Suggested Citation

  • Moore, A.D. & Robertson, M.J. & Routley, R., 2011. "Evaluation of the water use efficiency of alternative farm practices at a range of spatial and temporal scales: A conceptual framework and a modelling approach," Agricultural Systems, Elsevier, vol. 104(2), pages 162-174, February.
  • Handle: RePEc:eee:agisys:v:104:y:2011:i:2:p:162-174

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    References listed on IDEAS

    1. Moore, A. D. & Donnelly, J. R. & Freer, M., 1997. "GRAZPLAN: Decision support systems for Australian grazing enterprises. III. Pasture growth and soil moisture submodels, and the GrassGro DSS," Agricultural Systems, Elsevier, vol. 55(4), pages 535-582, December.
    2. Pannell, David J., 2001. "Dryland salinity: economic, scientific, social and policy dimensions," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 45(4), December.
    3. Stoorvogel, J. J. & Antle, J. M. & Crissman, C. C. & Bowen, W., 2004. "The tradeoff analysis model: integrated bio-physical and economic modeling of agricultural production systems," Agricultural Systems, Elsevier, vol. 80(1), pages 43-66, April.
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    7. Moore, A.D. & Holzworth, D.P. & Herrmann, N.I. & Huth, N.I. & Robertson, M.J., 2007. "The Common Modelling Protocol: A hierarchical framework for simulation of agricultural and environmental systems," Agricultural Systems, Elsevier, vol. 95(1-3), pages 37-48, December.
    8. Freer, M. & Moore, A. D. & Donnelly, J. R., 1997. "GRAZPLAN: Decision support systems for Australian grazing enterprises--II. The animal biology model for feed intake, production and reproduction and the GrazFeed DSS," Agricultural Systems, Elsevier, vol. 54(1), pages 77-126, May.
    9. Donnelly, J. R. & Freer, M. & Salmon, L. & Moore, A. D. & Simpson, R. J. & Dove, H. & Bolger, T. P., 2002. "Evolution of the GRAZPLAN decision support tools and adoption by the grazing industry in temperate Australia," Agricultural Systems, Elsevier, vol. 74(1), pages 115-139, October.
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    12. van Calker, K. J. & Berentsen, P. B. M. & de Boer, I. M. J. & Giesen, G. W. J. & Huirne, R. B. M., 2004. "An LP-model to analyse economic and ecological sustainability on Dutch dairy farms: model presentation and application for experimental farm "de Marke"," Agricultural Systems, Elsevier, vol. 82(2), pages 139-160, November.
    13. Meyer-Aurich, Andreas, 2005. "Economic and environmental analysis of sustainable farming practices - a Bavarian case study," Agricultural Systems, Elsevier, vol. 86(2), pages 190-206, November.
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    Cited by:

    1. Sebastian Kloss & Raji Pushpalatha & Kefasi Kamoyo & Niels Schütze, 2012. "Evaluation of Crop Models for Simulating and Optimizing Deficit Irrigation Systems in Arid and Semi-arid Countries Under Climate Variability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(4), pages 997-1014, March.
    2. Tanure, Soraya & Nabinger, Carlos & Becker, João Luiz, 2013. "Bioeconomic model of decision support system for farm management. Part I: Systemic conceptual modeling," Agricultural Systems, Elsevier, vol. 115(C), pages 104-116.
    3. Ghahramani, Afshin & Moore, Andrew D., 2016. "Impact of climate changes on existing crop-livestock farming systems," Agricultural Systems, Elsevier, vol. 146(C), pages 142-155.
    4. Soraya Tanure & Carlos Nabinger & João Luiz Becker, 2015. "Bioeconomic Model of Decision Support System for Farm Management: Proposal of a Mathematical Model," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(6), pages 658-671, November.
    5. Wheeler, Sarah Ann & Zuo, Alec & Loch, Adam, 2015. "Watering the farm: Comparing organic and conventional irrigation water use in the Murray–Darling Basin, Australia," Ecological Economics, Elsevier, vol. 112(C), pages 78-85.
    6. Ghahramani, Afshin & Moore, Andrew D., 2015. "Systemic adaptations to climate change in southern Australian grasslands and livestock: Production, profitability, methane emission and ecosystem function," Agricultural Systems, Elsevier, vol. 133(C), pages 158-166.
    7. Krauß, Michael & Kraatz, Simone & Drastig, Katrin & Prochnow, Annette, 2015. "The influence of dairy management strategies on water productivity of milk production," Agricultural Water Management, Elsevier, vol. 147(C), pages 175-186.
    8. Kuehne, Geoff & Nicholson, Cam & Robertson, Michael & Llewellyn, Rick & McDonald, Cam, 2012. "Engaging project proponents in R&D evaluation using bio-economic and socio-economic tools," Agricultural Systems, Elsevier, vol. 108(C), pages 94-103.


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