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Evaluating the economic impact of water scarcity in a changing world

Author

Listed:
  • Flannery Dolan

    (Tufts University)

  • Jonathan Lamontagne

    (Tufts University)

  • Robert Link

    (University of Virginia School of Medicine)

  • Mohamad Hejazi

    (Joint Global Change Research Institute, Pacific Northwest National Laboratory
    King Abdullah Petroleum Studies and Research Center)

  • Patrick Reed

    (School of Civil and Environmental Engineering, Cornell University)

  • Jae Edmonds

    (Joint Global Change Research Institute, Pacific Northwest National Laboratory)

Abstract

Water scarcity is dynamic and complex, emerging from the combined influences of climate change, basin-level water resources, and managed systems’ adaptive capacities. Beyond geophysical stressors and responses, it is critical to also consider how multi-sector, multi-scale economic teleconnections mitigate or exacerbate water shortages. Here, we contribute a global-to-basin-scale exploratory analysis of potential water scarcity impacts by linking a global human-Earth system model, a global hydrologic model, and a metric for the loss of economic surplus due to resource shortages. We find that, dependent on scenario assumptions, major hydrologic basins can experience strongly positive or strongly negative economic impacts due to global trade dynamics and market adaptations to regional scarcity. In many cases, market adaptation profoundly magnifies economic uncertainty relative to hydrologic uncertainty. Our analysis finds that impactful scenarios are often combinations of standard scenarios, showcasing that planners cannot presume drivers of uncertainty in complex adaptive systems.

Suggested Citation

  • Flannery Dolan & Jonathan Lamontagne & Robert Link & Mohamad Hejazi & Patrick Reed & Jae Edmonds, 2021. "Evaluating the economic impact of water scarcity in a changing world," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22194-0
    DOI: 10.1038/s41467-021-22194-0
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    Cited by:

    1. A. L. Hamilton & P. M. Reed & R. S. Gupta & H. B. Zeff & G. W. Characklis, 2024. "Resilient water infrastructure partnerships in institutionally complex systems face challenging supply and financial risk tradeoffs," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    2. De Lange, Job & Nalley, Lawton Lanier & Shew, Aaron M. & Steur, Hans De, 2022. "CRISPR Gene Editing Drivers, Barriers and Prospects: A Comparative Study among Plant Scientists Globally," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322216, Agricultural and Applied Economics Association.
    3. Fulop Arpad-Zoltan & Fulop Kinga-Erzsebet, 2023. "Perspectives Of The Circular Economy For Water And Sewage Operators In Romania," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 125-129, December.
    4. Safa Baccour & Gerwin Goelema & Taher Kahil & Jose Albiac & Michelle T. H. Vliet & Xueqin Zhu & Maryna Strokal, 2024. "Water quality management could halve future water scarcity cost-effectively in the Pearl River Basin," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    5. Cao, Xinchun & Bao, Yutong & Li, Yueyao & Li, Jianni & Wu, Mengyang, 2023. "Unravelling the effects of crop blue, green and grey virtual water flows on regional agricultural water footprint and scarcity," Agricultural Water Management, Elsevier, vol. 278(C).
    6. Elia Moretti & Michael Benzaquen, 2024. "Mitigating Farmland Biodiversity Loss: A Bio-Economic Model of Land Consolidation and Pesticide Use," Papers 2407.19749, arXiv.org, revised Oct 2024.
    7. Piero Morseletto & Caro Eline Mooren & Stefania Munaretto, 2022. "Circular Economy of Water: Definition, Strategies and Challenges," Circular Economy and Sustainability, Springer, vol. 2(4), pages 1463-1477, December.
    8. Li, Shangge & Jian, Jinfeng & Poopal, Rama Krishnan & Chen, Xinyu & He, Yaqi & Xu, Hongbin & Yu, Huimin & Ren, Zongming, 2022. "Mathematical modeling in behavior responses: The tendency-prediction based on a persistence model on real-time data," Ecological Modelling, Elsevier, vol. 464(C).

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