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Uncovering the dynamics of multi-sector impacts of hydrological extremes: a methods overview
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  • Mariana Madruga de Brito,
  • Jan Sodoge,
  • Alexander Fekete,
  • Michael Hagenlocher,
  • Elco Koks,
  • Christian Kuhlicke,
  • Gabriele Messori,
  • Marleen Carolijn Ruiter, de,
  • Pia-Johanna Schweizer,
  • Philip J. Ward
Mariana Madruga de Brito
Helmholtz-Centre for Environmental Research

Corresponding Author:[email protected]

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Jan Sodoge
Helmholtz-Centre for Environmental Research
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Alexander Fekete
Cologne University of Applied Sciences
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Michael Hagenlocher
United Nations University - Institute for Environment and Human Security
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Elco Koks
Vrije Universiteit Amsterdam
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Christian Kuhlicke
UFZ Helmholtz Centre for Environmental Research
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Gabriele Messori
Uppsala University
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Marleen Carolijn Ruiter, de
Vrije Universiteit Amsterdam
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Pia-Johanna Schweizer
Research Institute for Sustainability (RIFS), Helmholty Centre Potsdam
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Philip J. Ward
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam
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Hydrological extremes, such as droughts and floods, can trigger a complex web of compound and cascading impacts due to interdependencies between coupled natural and social systems. However, current decision-making processes typically only consider one impact and disaster event at a time, ignoring causal chains, feedback loops, and conditional dependencies between impacts. Analyses capturing these complex patterns across space and time are thus needed to better inform effective adaptation planning. This perspective paper aims to bridge this critical gap by presenting methods for assessing the dynamics of the multi-sector compound and cascading impacts (CCI) of hydrological extremes. We discuss existing challenges, good practices, and potential ways forward. Rather than pursuing a single methodological approach, we advocate for methodological pluralism. We see complementary roles for analyses building on quantitative (e.g. data-mining, systems modeling) and qualitative methods (e.g. mental models, qualitative storylines). We believe the data-driven and knowledge-driven methods provided here can serve as a useful starting point for understanding the dynamics of both high-frequency CCI and low-likelihood but high-impact CCI. With this perspective, we hope to foster research on CCI to improve the development of adaptation strategies for reducing the risk of hydrological extremes.
10 Jul 2023Submitted to ESS Open Archive
23 Jul 2023Published in ESS Open Archive