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<p>Understanding water availability and its response to climate change and water extraction is crucial for sustainable water management in Australia’s Murray–Darling Basin. This study introduces a space-based method that quantifies the natural and human-induced impact on changes in terrestrial water storage. It reveals an impact of 17% due to water extraction for irrigation over the past two decades, with 84% of this extraction coming from surface water and 16% from groundwater. The human-induced impact varies spatially with higher values in the southern Murray (up to 5.6%) and smaller values in the northern Darling (down to 0.2%). Data-model fusion of the satellite-based water storage changes into a hydrological model, which does not simulate water extraction, man-made reservoirs and wetlands, improved the representation of water storage variability and intensified trends in drying and wetting periods. This study adds valuable findings to better understand natural and human-induced impacts on the regional water resources under changing climate and to better represent these impacts (80% and 20% respectively) within hydrological models after data-model fusion.</p>

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Space-based natural and human-induced water storage change quantification

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月27日

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  • Maike Schumacher,
  • Albert I. J. M. van Dijk,
  • Leire Retegui-Schiettekatte,
  • Fan Yang,
  • Ehsan Forootan

摘要

Understanding water availability and its response to climate change and water extraction is crucial for sustainable water management in Australia’s Murray–Darling Basin. This study introduces a space-based method that quantifies the natural and human-induced impact on changes in terrestrial water storage. It reveals an impact of 17% due to water extraction for irrigation over the past two decades, with 84% of this extraction coming from surface water and 16% from groundwater. The human-induced impact varies spatially with higher values in the southern Murray (up to 5.6%) and smaller values in the northern Darling (down to 0.2%). Data-model fusion of the satellite-based water storage changes into a hydrological model, which does not simulate water extraction, man-made reservoirs and wetlands, improved the representation of water storage variability and intensified trends in drying and wetting periods. This study adds valuable findings to better understand natural and human-induced impacts on the regional water resources under changing climate and to better represent these impacts (80% and 20% respectively) within hydrological models after data-model fusion.