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\title{Beyond The Floodplain:~ Integrating Probabilities and Storylines to
Explore Regional Uncertain Direct~ and Cascading Climate Risks in
Multi-sectoral Systems~~~~~~~~~~~~}



\author[1,2]{Franciscus Eduard Buskop}%
\author[2]{Frederiek Sperna Weiland}%
\author[3]{Stefan Hochrainer-Stigler}%
\author[3]{Robert Šakić Trogrlić}%
\author[1,2]{Bart van den Hurk}%
\affil[1]{Vrije Universiteit Amsterdam}%
\affil[2]{Deltares}%
\affil[3]{IIASA-International Institute for Applied System Analysis}%


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  \date{April 24, 2026}


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\begin{abstract}
Anticipating and managing future regional climate risks in
interconnected multi-sectoral systems is complicated by uncertainties in
risk drivers within both human and natural systems. Comprehensive yet
comprehensible targeted climate risk information exploring these
uncertainties is essential for tasks like the strategic allocation of
limited resources to vulnerable areas and sectors in the region. To
address these complexities, this study introduces an interdisciplinary
methodology combining meteorological, hydrological, and socio-economic
perspectives, tested within 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 based on their relevance for local impacts, allowing the
assessment of conditional changes in high-impact probabilistic
discharges. In addition, we sampled plausible socio-economic storylines
to asses future urban area and economic sectoral development. This
information allows us to project the impact potential in the region and
its cascading socio-economic effects. By integrating both socio-economic
and climate scenario storylines, our approach comprehensively maps
complex direct and cascading flood risks. Application to the Lielupe
basin highlights sub-catchments and sectors consistently vulnerable
across the diverse, relevant, and credible set of future storylines. Our
integrated approach equips regional risk managers with targeted and
robust risk information, providing a strong knowledge base for
prioritising adaptation planning.%
\end{abstract}%



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