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Catastrophic Regime Shift in Water Reservoirs and São Paulo Water Supply Crisis

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  • Renato M Coutinho
  • Roberto A Kraenkel
  • Paulo I Prado

Abstract

The relation between rainfall and water accumulated in reservoirs comprises nonlinear feedbacks. Here we show that they may generate alternative equilibrium regimes, one of high water-volume, the other of low water-volume. Reservoirs can be seen as socio-environmental systems at risk of regime shifts, characteristic of tipping point transitions. We analyze data from stored water, rainfall, and water inflow and outflow in the main reservoir serving the metropolitan area of São Paulo, Brazil, by means of indicators of critical regime shifts, and find a strong signal of a transition. We furthermore build a mathematical model that gives a mechanistic view of the dynamics and demonstrates that alternative stable states are an expected property of water reservoirs. We also build a stochastic version of this model that fits well to the data. These results highlight the broader aspect that reservoir management must account for their intrinsic bistability, and should benefit from dynamical systems theory. Our case study illustrates the catastrophic consequences of failing to do so.

Suggested Citation

  • Renato M Coutinho & Roberto A Kraenkel & Paulo I Prado, 2015. "Catastrophic Regime Shift in Water Reservoirs and São Paulo Water Supply Crisis," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-14, September.
    • Handle: RePEc:plo:pone00:0138278
    DOI: 10.1371/journal.pone.0138278
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    References listed on IDEAS

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    1. Marten Scheffer & Steve Carpenter & Jonathan A. Foley & Carl Folke & Brian Walker, 2001. "Catastrophic shifts in ecosystems," Nature, Nature, vol. 413(6856), pages 591-596, October.
    2. Vasilis Dakos & Stephen R Carpenter & William A Brock & Aaron M Ellison & Vishwesha Guttal & Anthony R Ives & Sonia Kéfi & Valerie Livina & David A Seekell & Egbert H van Nes & Marten Scheffer, 2012. "Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-20, July.
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    1. Neha Deopa & Daniele Rinaldo, 2024. "Quickest Detection of Ecological Regimes for Natural Resource Management," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(5), pages 1327-1366, May.
    2. Michels-Brito, Adriane & Rodriguez, Daniel Andrés & Cruz Junior, Wellington Luís & Nildo de Souza Vianna, João, 2021. "The climate change potential effects on the run-of-river plant and the environmental and economic dimensions of sustainability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    3. Schauf, Andrew & Oh, Poong, 2021. "Adaptation strategies and collective dynamics of extraction in networked commons of bistable resources," SocArXiv wmtqk, Center for Open Science.
    4. Mohor, Guilherme Samprogna & Mendiondo, Eduardo Mario, 2017. "Economic indicators of hydrologic drought insurance under water demand and climate change scenarios in a Brazilian context," Ecological Economics, Elsevier, vol. 140(C), pages 66-78.

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