Rapid high-resolution impact-based flood early warning is possible with RIM2D: a showcase for the 2023 pluvial flood in Braunschweig

Abstract. In recent years, urban areas have been increasingly affected by more frequent and severe pluvial floods, attributed to climate change and urbanization. This trend is expected to continue in the future, underscoring the critical importance of flood warning and disaster management. However, pluvial flood forecasts on a communal level do not exist in practice, mainly due to the high computational runtimes of high-resolution flood simulation models. Here, we showcase the capability of the hydrodynamic model RIM2D (Rapid Inundation Model 2D) to deliver highly detailed and localized insights into expected flood extent and impacts in very short computational processing times, enabling operational flood warnings. We demonstrate these capabilities using the case of the June 2023 torrential rain and resulting flood event in the city of Braunschweig, located in Lower Saxony, Germany. During this event, the city experienced intense rainfall of 60 L m−2 within a short time frame, resulting in widespread inundation, significant disruption to the residents' daily life, and substantial economic costs to the city. This study serves as a clear indication that different dimensions of flood consequences can be simulated at very high resolutions in extremely short computational times and that models such as RIM2D, along with the necessary hardware for their operation, have reached a level of maturity suitable for integration into operational early warning systems and impact-based forecasting systems for such floods.

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Publication Details

Journal
Natural hazards and earth system sciences
Published
2025-05-14
DOI
https://doi.org/10.5194/nhess-25-1737-2025
Citations
2
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
2.21

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article

Rapid high-resolution impact-based flood early warning is possible with RIM2D: a showcase for the 2023 pluvial flood in Braunschweig

Max Steinhausen, Shahin Khosh Bin Ghomash, Heiko Apel, Kai Schröter
2 citations
Natural hazards and earth system sciences
Flood Risk Assessment and Management
2.21
article

Rapid high-resolution impact-based flood early warning is possible with RIM2D: a showcase for the 2023 pluvial flood in Braunschweig

Max Steinhausen, Shahin Khosh Bin Ghomash, Heiko Apel, Kai Schröter
article en
2 citations

Abstract

Abstract. In recent years, urban areas have been increasingly affected by more frequent and severe pluvial floods, attributed to climate change and urbanization. This trend is expected to continue in the future, underscoring the critical importance of flood warning and disaster management. However, pluvial flood forecasts on a communal level do not exist in practice, mainly due to the high computational runtimes of high-resolution flood simulation models. Here, we showcase the capability of the hydrodynamic model RIM2D (Rapid Inundation Model 2D) to deliver highly detailed and localized insights into expected flood extent and impacts in very short computational processing times, enabling operational flood warnings. We demonstrate these capabilities using the case of the June 2023 torrential rain and resulting flood event in the city of Braunschweig, located in Lower Saxony, Germany. During this event, the city experienced intense rainfall of 60 L m−2 within a short time frame, resulting in widespread inundation, significant disruption to the residents' daily life, and substantial economic costs to the city. This study serves as a clear indication that different dimensions of flood consequences can be simulated at very high resolutions in extremely short computational times and that models such as RIM2D, along with the necessary hardware for their operation, have reached a level of maturity suitable for integration into operational early warning systems and impact-based forecasting systems for such floods.

Natural hazards and earth system sciencesVol. 25(5)
GFZ Helmholtz Centre for Geosciences (DE), Technische Universität Braunschweig (DE)
European Commission, Brandenburger Staatsministerium für Wissenschaft, Forschung und Kultur, HORIZON EUROPE Framework Programme, Horizon 2020
Openalex Percentile: Top 14%
Flood Risk Assessment and Management
2.21
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