Fast urban inundation simulation with RIM2D for flood risk assessment and forecasting
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Introduction: Urban pluvial flooding is a growing concern worldwide as consequence of rising urban population and climate change induced increases in heavy rainfall. Easy-to-implement and fast simulation tools are needed to cope with this challenge. Methods: This study describes the development of the parsimonious, GPU-accelerated hydraulic model RIM2D for urban pluvial flood simulations. This is achieved by considering the built-up urban area as flow obstacles, and by introducing capacity-based approaches to consider urban drainage by infiltration on pervious surfaces and sewer drainage from roofs and sealed surfaces. The model performance was analyzed by simulating 8 heavy rainfall events in a test area in the city of Dresden, Germany. For these events detailed discharge measurements of sewer discharge are available, providing a unique dataset for evaluating the sewer drainage simulation, which is of high importance for realistic pluvial inundation simulations in urban areas. Results and discussion: We show that the model simulates the temporal dynamics of the sewer discharge and the sewer volume within acceptable ranges. Moreover, the erratic variation of the simulated to measured sewer discharge suggests that the deviations from the measurements are caused by the precipitation input rather than the model simplifications. We conclude that RIM2D is a valid tool for urban inundation simulation. Its short simulation runtimes allow probabilistic flood risk assessments and operational flood forecasts.
Details
Original language | English |
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Article number | 1310182 |
Journal | Frontiers in Water |
Volume | 6 |
Publication status | Published - 2024 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0003-4963-7523/work/171062702 |
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ORCID | /0000-0002-4782-6024/work/171065222 |
Keywords
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- flood forecasting, flood modeling, GPU acceleration, heavy precipitation, pluvial flood, RIM2D, urban flood risk, urban inundation