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Building a climate resilient farm: A risk based approach for understanding water, energy and emissions in irrigated agriculture

  • Jackson, T.M.
  • Hanjra, Munir A.
  • Khan, S.
  • Hafeez, M.M.
Registered author(s):

    The links between water application, energy consumption and emissions are complex in irrigated agriculture. There is a need to ensure that water and energy use is closely considered in future industry planning and development to provide practical options for adaptation and to build resilience at the farm level. There is currently limited data available regarding the uncertainty and sensitivity associated with water application and energy consumption in irrigated crop production in Australia. This paper examines water application and energy consumption relationships for different irrigation systems, and the ways in which the uncertainty of different parameters impacts on these relationships and associated emissions for actual farms. This analysis was undertaken by examining the current water and energy patterns of crop production at actual farms in two irrigated areas of Australia (one using surface water and the other groundwater), and then modelling the risk/uncertainty and sensitivity associated with the link between water and energy consumption at the farm scale. Results showed that conversions from gravity to pressurised irrigation methods reduced water application, but there was a simultaneous increase in energy consumption in surface irrigation areas. In groundwater irrigated areas, the opposite is true; the use of pressurised irrigation methods can reduce water application and energy consumption by enhancing water use efficiency. Risk and uncertainty analysis quantified the range of water and energy use that might be expected for a given irrigation method for each farm. Sensitivity analysis revealed the contribution of climatic (evapotranspiration and rainfall) and technical factors (irrigation system efficiency, pump efficiency, suction and discharge head) impacting the uncertainty and the model output and water-energy system performance in general. Flood irrigation systems were generally associated with greater uncertainty than pressurised systems. To enhance resilience at the farm level, the optimum situation envisaged an irrigation system that minimises water and energy consumption and greenhouse gas emissions. Where surface water is used, well designed and managed flood irrigation systems will minimise the operating energy and carbon equivalent emissions. Where groundwater is the dominant use, the optimum system is a well designed and managed pressurised system operating at the lowest discharge pressure possible that will still allow for efficient irrigation. The findings might be useful for farm level risk mitigation strategies in surface and groundwater systems, and for aiding adaptation to climate change.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X1100117X
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    Article provided by Elsevier in its journal Agricultural Systems.

    Volume (Year): 104 (2011)
    Issue (Month): 9 ()
    Pages: 729-745

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    Handle: RePEc:eee:agisys:v:104:y:2011:i:9:p:729-745
    Contact details of provider: Web page: http://www.elsevier.com/locate/agsy

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    1. Pannell, David J., 1997. "Sensitivity analysis of normative economic models: theoretical framework and practical strategies," Agricultural Economics, Blackwell, vol. 16(2), pages 139-152, May.
    2. Isik, Murat & Khanna, Madhu & Winter-Nelson, Alex, 2001. "Sequential Investment In Site-Specific Crop Management Under Output Price Uncertainty," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 26(01), July.
    3. Molden, David & Oweis, Theib & Steduto, Pasquale & Bindraban, Prem & Hanjra, Munir A. & Kijne, Jacob, 2010. "Improving agricultural water productivity: Between optimism and caution," Agricultural Water Management, Elsevier, vol. 97(4), pages 528-535, April.
    4. Simmons, Phil, 2002. "Why do farmers have so little interest in futures markets?," Agricultural Economics, Blackwell, vol. 27(1), pages 1-6, May.
    5. Biggs, Trent W. & Gangadhara Rao, Pardhasaradhi & Bharati, Luna, 2010. "Mapping agricultural responses to water supply shocks in large irrigation systems, southern India," Agricultural Water Management, Elsevier, vol. 97(6), pages 924-932, June.
    6. Dehghanisanij, H. & Agassi, M. & Anyoji, H. & Yamamoto, T. & Inoue, M. & Eneji, A.E., 2006. "Improvement of saline water use under drip irrigation system," Agricultural Water Management, Elsevier, vol. 85(3), pages 233-242, October.
    7. Grove, Bennie & Oosthuizen, Lukas Klopper, 2010. "Stochastic efficiency analysis of deficit irrigation with standard risk aversion," Agricultural Water Management, Elsevier, vol. 97(6), pages 792-800, June.
    8. Marra, Michele & Pannell, David J. & Abadi Ghadim, Amir, 2003. "The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: where are we on the learning curve?," Agricultural Systems, Elsevier, vol. 75(2-3), pages 215-234.
    9. Khan, S. & Abbas, A. & Blackwell, J. & Gabriel, H.F. & Ahmad, A., 2007. "Hydrogeological assessment of serial biological concentration of salts to manage saline drainage," Agricultural Water Management, Elsevier, vol. 92(1-2), pages 64-72, August.
    10. Ozkan, Burhan & Akcaoz, Handan & Fert, Cemal, 2004. "Energy input–output analysis in Turkish agriculture," Renewable Energy, Elsevier, vol. 29(1), pages 39-51.
    11. Barry Smit & Mark Skinner, 2002. "Adaptation options in agriculture to climate change: a typology," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 7(1), pages 85-114, March.
    12. Li, W. & Li, Y.P. & Li, C.H. & Huang, G.H., 2010. "An inexact two-stage water management model for planning agricultural irrigation under uncertainty," Agricultural Water Management, Elsevier, vol. 97(11), pages 1905-1914, November.
    13. Lavee, Doron, 2010. "The effect of water supply uncertainty on farmers' choice of crop portfolio," Agricultural Water Management, Elsevier, vol. 97(11), pages 1847-1854, November.
    14. Khan, S. & Khan, M.A. & Hanjra, M.A. & Mu, J., 2009. "Pathways to reduce the environmental footprints of water and energy inputs in food production," Food Policy, Elsevier, vol. 34(2), pages 141-149, April.
    15. Grepperud, S., 1997. "Soil conservation as an investment in land," Journal of Development Economics, Elsevier, vol. 54(2), pages 455-467, December.
    16. Mosley, L.M. & Fleming, N., 2009. "Reductions in water use following rehabilitation of a flood-irrigated area on the Murray River in South Australia," Agricultural Water Management, Elsevier, vol. 96(11), pages 1679-1682, November.
    17. King, A.P. & Evatt, K.J. & Six, J. & Poch, R.M. & Rolston, D.E. & Hopmans, J.W., 2009. "Annual carbon and nitrogen loadings for a furrow-irrigated field," Agricultural Water Management, Elsevier, vol. 96(6), pages 925-930, June.
    18. Pannell, David J. & Malcolm, Bill & Kingwell, Ross S., 2000. "Are we risking too much? Perspectives on risk in farm modelling," Agricultural Economics, Blackwell, vol. 23(1), pages 69-78, June.
    19. Playan, Enrique & Mateos, Luciano, 2006. "Modernization and optimization of irrigation systems to increase water productivity," Agricultural Water Management, Elsevier, vol. 80(1-3), pages 100-116, February.
    20. Bergez, J. -E. & Garcia, F. & Lapasse, L., 2004. "A hierarchical partitioning method for optimizing irrigation strategies," Agricultural Systems, Elsevier, vol. 80(3), pages 235-253, June.
    21. Stephen C. Beare & Rosalyn Bell & Brian S. Fisher, 1998. "Determining the Value of Water: The Role of Risk, Infrastructure Constraints, and Ownership," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(5), pages 916-940.
    22. Ayars, J. E. & Phene, C. J. & Hutmacher, R. B. & Davis, K. R. & Schoneman, R. A. & Vail, S. S. & Mead, R. M., 1999. "Subsurface drip irrigation of row crops: a review of 15 years of research at the Water Management Research Laboratory," Agricultural Water Management, Elsevier, vol. 42(1), pages 1-27, September.
    23. Hatirli, Selim Adem & Ozkan, Burhan & Fert, Cemal, 2006. "Energy inputs and crop yield relationship in greenhouse tomato production," Renewable Energy, Elsevier, vol. 31(4), pages 427-438.
    24. Khan, Shahbaz & Rana, Tariq & Hanjra, Munir A., 2008. "A cross disciplinary framework for linking farms with regional groundwater and salinity management targets," Agricultural Water Management, Elsevier, vol. 95(1), pages 35-47, January.
    25. Khan, Shahbaz & Hanjra, Munir A., 2009. "Footprints of water and energy inputs in food production - Global perspectives," Food Policy, Elsevier, vol. 34(2), pages 130-140, April.
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