- 1Amirkabir University of Technology, Civil and Environmental engineering, Iran, Islamic Republic of (vahidbakhtiari1995@gmail.com)
- 2Centre for Engineering Research, School of Physics, Engineering, Computer Science, University of Hertfordshire, AL10 9AB, Hatfield, UK
Asset-based Dynamic Flood Risk Assessment: Case Study of London Downtown
Flooding poses significant risks to urban centres, with particular challenges faced by business hubs where disruptions can have devastating consequences on national and global economies [1]. Business hubs are the lifeblood of national and global economies. During flood events, businesspeople encounter disruptions that not only obstruct daily operations but also ripple through supply chains and financial systems [2-3]. This study emphasises the importance of protecting critical assets in Downtown London, a vital business hub, to mitigate economic and social impacts during floods. Through a watershed-based approach, Downtown London, a vibrant business hub with numerous critical assets, has been selected as the case study area. The district contains key commercial buildings and infrastructure that are vital to economic and social continuity. Using Digimap and Verisk, essential commercial buildings and critical assets are pinpointed based on their usage and significance. These tools facilitate generating an accurate map of assets requiring priority attention during flood events.
The proposed decision support system (DSS) is developed to aid risk management authorities, including policy-makers, decision-makers, and technical staff. The system operates on two key bases. Real-time population density data for critical assets is obtained using Google API. This data helps evaluate the human vulnerability component during flood scenarios. A flood forecasting system is integrated to predict water levels at 15-minute intervals for the coming hours. This system provides granular and actionable insights into evolving flood conditions. For each critical asset, two risk values are computed: one based on population density and another on forecasted water levels. These values are combined to derive a dynamic risk level for each time step, enabling authorities to respond effectively. The integration of real-time data and predictive modeling in the DSS offers a comprehensive framework for flood risk assessment. By prioritising critical assets based on dynamic risk levels, authorities can implement targeted preparedness and response measures such as early warnings and evacuation plans. This approach ensures both human safety and economic resilience. The findings have demonstrated the feasibility of applying real-time data and cutting-edge modeling to enhance urban flood resilience. By combining flood risk maps, real-time population density, and a comprehensive prioritisation framework, this approach provides a promising tool for urban planners and emergency responders to protect critical business assets and ensure economic continuity during flood events.
References
[1] Bakhtiari, V., Piadeh, F., Behzadian, K. and Kapelan, Z. (2023). A critical review for the application of cutting-edge digital visualisation technologies for effective urban flood risk management. Sustainable Cities and Society, p.104958.
[2] Bakhtiari, V., Piadeh, F., Chen, A.S. and Behzadian, K. (2024). Stakeholder analysis in the application of cutting-edge digital visualisation technologies for urban flood risk management: A critical review. Expert Systems with Applications, 236, p.121426.
[3] Piadeh, F., Behzadian, K. and Alani, A.M. (2022). A critical review of real-time modelling of flood forecasting in urban drainage systems. Journal of Hydrology, 607, p.127476.
How to cite: Bakhtiari, V. and Piadeh, F.: Asset-based Dynamic Flood Risk Assessment: Case Study of London Downtown, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3504, https://doi.org/10.5194/egusphere-egu25-3504, 2025.