Future precipitation extremes and urban flood risk assessment using a non-stationary and convection-permitting climate-hydrodynamic modeling framework

Urban planners and engineers rely on historical climate data to plan and design flood protection infrastructure that should withstand extreme flooding events with 1% annual exceedance probability (the 100-year flood). Here, we examine how hourly precipitation extremes are expected to change as temperatures rise and how this will affect urban flooding. The changes to short-duration rainfall extremes, often insufficiently considered in practice, are addressed utilizing a new temperature conditional extreme precipitation scaling approach and a novel regional climate convection-permitting model ensemble for +2 °C and +3 °C global warming scenarios. Based on hydrodynamic modeling, we estimate how future precipitation extremes translate into flood risks in two pre-alpine communes in Germany. Ignoring the impacts of climate change may lead to severe underestimations of flood risks. The +3 °C global warming scenario translates into an increase of 60% of affected buildings by the highest flood risk category (water level of 1 m and above). The increase in flow intensities will be greater in the commune characterized by steeper terrain. The results suggest that recently planned or implemented infrastructure projects may not be adequately equipped to cope with the anticipated effects of climate change in the coming decades. • A novel climate hydrodynamic modeling chain (CHMC) is presented. • CHMC uses radar, temperature, and CPM data to project future flash flood risks. • Flood risks are severely underestimated when climate non-stationarity is ignored. • CHMC may serve as a blueprint for other countries with similar data infrastructures.

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Publication Details

Journal
Journal of Hydrology
Published
2025-06-16
DOI
https://doi.org/10.1016/j.jhydrol.2025.133607
Citations
8
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
8.84

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article

Future precipitation extremes and urban flood risk assessment using a non-stationary and convection-permitting climate-hydrodynamic modeling framework

Harald Günter Kunstmann, Katja Trachte, Patrick Laux, Hendrik Feldmann et al.
8 citations
Journal of Hydrology
Climate variability and models
8.84
article

Future precipitation extremes and urban flood risk assessment using a non-stationary and convection-permitting climate-hydrodynamic modeling framework

Harald Günter Kunstmann, Katja Trachte, Patrick Laux, Hendrik Feldmann, Nadav Peleg, David Feldmann, Francesco Marra
article en
8 citations

Abstract

Urban planners and engineers rely on historical climate data to plan and design flood protection infrastructure that should withstand extreme flooding events with 1% annual exceedance probability (the 100-year flood). Here, we examine how hourly precipitation extremes are expected to change as temperatures rise and how this will affect urban flooding. The changes to short-duration rainfall extremes, often insufficiently considered in practice, are addressed utilizing a new temperature conditional extreme precipitation scaling approach and a novel regional climate convection-permitting model ensemble for +2 °C and +3 °C global warming scenarios. Based on hydrodynamic modeling, we estimate how future precipitation extremes translate into flood risks in two pre-alpine communes in Germany. Ignoring the impacts of climate change may lead to severe underestimations of flood risks. The +3 °C global warming scenario translates into an increase of 60% of affected buildings by the highest flood risk category (water level of 1 m and above). The increase in flow intensities will be greater in the commune characterized by steeper terrain. The results suggest that recently planned or implemented infrastructure projects may not be adequately equipped to cope with the anticipated effects of climate change in the coming decades. • A novel climate hydrodynamic modeling chain (CHMC) is presented. • CHMC uses radar, temperature, and CPM data to project future flash flood risks. • Flood risks are severely underestimated when climate non-stationarity is ignored. • CHMC may serve as a blueprint for other countries with similar data infrastructures.

Journal of HydrologyVol. 661
Karlsruhe Institute of Technology (DE), University of Padua (IT), University of Augsburg (DE), FORS – Swiss Centre of Expertise in the Social Sciences (CH), Alpenforschungsinstitut (Germany) (DE), Ingenieure für das Bauwesen (DE), Garmisch-Partenkirchen Medical Center (DE), Brandenburg University of Technology Cottbus-Senftenberg (DE), University of Lausanne (CH)
National Science Foundation, Deutsches Klimarechenzentrum, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Bundesministerium für Bildung und Forschung, Ministero dell'Università e della Ricerca
Climate action
Openalex Percentile: Top 2%
Climate variability and models
8.84
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