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Small-scale land use change modelling using transient groundwater levels and salinities as driving factors – An example from a sub-catchment of Australia’s Murray-Darling Basin

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  • Penny, Jessica
  • Ordens, Carlos M.
  • Barnett, Steve
  • Djordjević, Slobodan
  • Chen, Albert S.

Abstract

Although land-use change (LUC) can have detrimental environmental impacts, very few studies have explored the idea that changes in groundwater conditions and water management directly influence LU. This study models how water management policies, groundwater quality (as salinity) and availability drive and impact LUC at a small scale. The Angas Bremer (AB) irrigation district (Murray-Darling Basin, Australia) was used as a case study because it provides a rare example of complex and transient groundwater management. The key questions raised were (i) how has LU, more specifically agricultural practices, changed groundwater quality and availability; (ii) how have groundwater conditions (salinity and levels) subsequently driven LUC and influenced policy changes; and, (iii) how have groundwater conditions improved as a consequence of LU and policy changes. Using the newly-developed Patch-generating LU Simulation (PLUS) model, LUC was simulated and driving factors analysed for the period 1949–2014. To the best of our knowledge, PLUS was able to successfully model groundwater-driven LUC at a small, local scale for the first time in the international literature. The results show that (i) LUC driving factors depend on groundwater conditions and extent of policy in place, and (ii) changes in groundwater salinity and levels led to new water management policy, which in turn dictated LU changes where more water-efficient crops were favoured. LUC likely contributed to a recovery of groundwater levels and low salinity, i.e. groundwater improved to pre-development conditions. Groundwater-related driving factors are responsible for 5–12% depending on agricultural land use and phase.

Suggested Citation

  • Penny, Jessica & Ordens, Carlos M. & Barnett, Steve & Djordjević, Slobodan & Chen, Albert S., 2023. "Small-scale land use change modelling using transient groundwater levels and salinities as driving factors – An example from a sub-catchment of Australia’s Murray-Darling Basin," Agricultural Water Management, Elsevier, vol. 278(C).
  • Handle: RePEc:eee:agiwat:v:278:y:2023:i:c:s0378377423000392
    DOI: 10.1016/j.agwat.2023.108174
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    References listed on IDEAS

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    1. Dench, William E. & Morgan, Leanne K., 2021. "Unintended consequences to groundwater from improved irrigation efficiency: Lessons from the Hinds-Rangitata Plain, New Zealand," Agricultural Water Management, Elsevier, vol. 245(C).
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    3. Yongyut Trisurat & Hiroaki Shirakawa & John M. Johnston, 2019. "Land-Use/Land-Cover Change from Socio-Economic Drivers and Their Impact on Biodiversity in Nan Province, Thailand," Sustainability, MDPI, vol. 11(3), pages 1-22, January.
    4. Robert Pontius & Wideke Boersma & Jean-Christophe Castella & Keith Clarke & Ton Nijs & Charles Dietzel & Zengqiang Duan & Eric Fotsing & Noah Goldstein & Kasper Kok & Eric Koomen & Christopher Lippitt, 2008. "Comparing the input, output, and validation maps for several models of land change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 11-37, March.
    5. Reshmidevi, T.V. & Eldho, T.I. & Jana, R., 2009. "A GIS-integrated fuzzy rule-based inference system for land suitability evaluation in agricultural watersheds," Agricultural Systems, Elsevier, vol. 101(1-2), pages 101-109, June.
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    Cited by:

    1. Ming Shi & Fei Lin & Xia Jing & Bingyu Li & Jingsha Qin & Manqi Wang & Yang Shi & Yimin Hu, 2023. "Research on the Spatio-Temporal Changes of Vegetation and Its Driving Forces in Shaanxi Province in the Past 20 Years," Sustainability, MDPI, vol. 15(23), pages 1-25, November.
    2. Penny, Jessica & Ordens, Carlos M. & Barnett, Steve & Djordjević, Slobodan & Chen, Albert S., 2023. "Vineyards, vegetables or business-as-usual? Stakeholder-informed land use change modelling to predict the future of a groundwater-dependent prime-wine region under climate change," Agricultural Water Management, Elsevier, vol. 287(C).

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