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Integrating Probabilities and Storylines to Explore Uncertain Direct and Cascading Climate Risks in Multi-sectoral Systems: A Case of The Lielupe Basin
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  • Franciscus Eduard Buskop,
  • Frederiek Sperna Weiland,
  • Stefan Hochrainer-Stigler,
  • Robert Šakić Trogrlić,
  • Bart van den Hurk
Franciscus Eduard Buskop
Vrije Universiteit Amsterdam, Deltares

Corresponding Author:t.buskop@vu.nl

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Frederiek Sperna Weiland
Deltares
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Stefan Hochrainer-Stigler
IIASA-International Institute for Applied System Analysis
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Robert Šakić Trogrlić
IIASA-International Institute for Applied System Analysis
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Bart van den Hurk
Deltares, Vrije Universiteit Amsterdam
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Abstract

Anticipating and managing future climate risks in interconnected multi-sectoral systems is complicated by uncertainties in risk drivers in both human and natural systems. Comprehensive yet comprehensible targeted climate risk information exploring these uncertainties is relevant for e.g. strategic allocation of limited resources to the most vulnerable areas and sectors. To address these complexities, this study introduces an interdisciplinary methodology combining meteorological, hydrological, and socio-economic perspectives, tested in the flood-prone, transboundary Lielupe basin shared by Latvia and Lithuania. A ’plausibilistic’ risk assessment approach is applied in which plausible climate scenario storylines are sampled on their relevance for local impacts, allowing the assessment of conditional changes in high-impact probabilistic discharges. In addition, plausible yet differently structured future urban areas and economies are sampled to project direct impact potential and its cascading socio-economic effects. By integrating both climate and socio-economic scenarios, a risk mapping can be made to highlight regions where (compounding) risk drivers may occur. Application to the Lielupe basin reveals those areas and sectors most vulnerable to climate impacts across diverse climate and socio-economic scenarios. Our comprehensive approach equips regional risk managers with targeted risk information essential for prioritising adaptation planning.