Fast flood modelling for pluvial flood management in Innsbruck, Austria

Fast flood modelling for pluvial flood management in Innsbruck, Austria

The increasing frequency and intensity of precipitation events leads to urban flooding, often causing significant damage to infrastructure and property. This phenomenon, known as pluvial flooding, arises when heavy precipitation exceeds the capacity of urban drainage systems, leading to surface water accumulation. Climate change is expected to exacerbate this issue, emphasizing the urgent need for efficient predictive models to mitigate the associated risks and impacts.

Traditional hydrodynamic models, such as coupled 1D-2D simulations, offer highly detailed flood assessments by simulating both surface runoff and sewer network interactions. However, these models are computationally demanding, requiring significant resources and time, making them unsuitable for real-time flood forecasting and decision-making during extreme weather events.

To address these limitations, fast flood models like the dynamic CA-ffé model, based on Jamali et al. (2019) and further developed by Gholami Korzani and Deletic (2023), provide a practical alternative. These models efficiently integrate surface flow and sewer network dynamics, enabling accurate flood forecasting at a much lower computational cost. Previously validated in smaller Australian catchments, the dynamic CA-ffé model has demonstrated its ability to provide timely and accurate urban flood simulations, significantly improving flood forecasting and risk management.

To address flooding challenges in Innsbruck, a larger, mountainous catchment area (~50 km²), the dynamic CA-ffé model was adapted based on the model approach of Gholami Korzani and Deletic (2023). This model approach combines a cellular automata-based 2D simulation with a 1D sewer network model using SWMM (Stormwater Management Model). By synchronizing data exchanges between surface runoff and sewer discharge at regular intervals, the model achieves faster and more accurate flood predictions, enabling high-resolution urban flood forecasting.

Adapting the model to Innsbruck required adjustments to account for the city's complex mountainous terrain and boundary conditions. Additional case-specific modifications were implemented to ensure compatibility with the larger and more challenging catchment area. The model was tested using historical flood events and validated against fire brigade records and photo documentations, as no prior citywide flood models were available for comparison.

The model's fast computation times allow the simulation of different flood scenarios, including assessments of the effects of climate change. These simulations will help to identify flood risks and inform heavy rainfall management strategies. Initial results confirm the model's ability to simulate urban-scale flooding, while highlighting challenges in adapting the approach to larger and more topographically complex study areas, such as land-use based runoff coefficients and the use of multiple rain gauges for precipitation data.

 

Funding:

BlueGreenCities (project No. KR21KB0K00001), funded by the Austrian Climate and Energy Fund from October 2022 until September 2025

Early Stage Funding (project: FFMFF) funded by the Vice-Rectorate for Research of the University of Innsbruck from November 2023 until October 2024.

 

References:

Gholami Korzani, M., Deletic, A., 2023. Dynamic CA-ffé: a hybrid 1D/2D fast flood evaluation model for urban floods. Sydney.

Jamali, B., Bach, P.M., Cunningham, L., Deletic, A., 2019. A Cellular Automata Fast Flood Evaluation (CA-ffé) Model. Water Resources Research 55, 4936–4953. https://doi.org/10.1029/2018WR023679