Bakhtiari, Vahid, Piadeh, Farzad ORCID: https://orcid.org/0000-0002-4958-6968, Behzadian, Kourosh ORCID: https://orcid.org/0000-0002-1459-8408 and Kapelan, Zoran (2023) A critical review for the application of Cutting-edge Digital Visualisation Technologies for Effective Urban Flood Risk Management. Sustainable Cities and Society, 99. pp. 1-14. ISSN 2210-6707

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Abstract

Cutting-edge digital visualisation tools (CDVT) are playing an increasingly important role in improving urban flood risk management. However, there is a paucity of comprehensive research examining their role across all stages of urban flood risk management. To address, this study conducts an integrated critical review to identify the application of CDVT and assess their contribution to the prevention, mitigation, preparation, response, and recovery stages of flood risk management. The results show that virtual reality, augmented reality, and digital twin technologies are the primary CDVT used in urban flood visualisation, with virtual reality being the most frequently used. The focus of urban flood visualisation studies has been primarily on preparation and mitigation stages. However, there is a need to investigate the application of these technologies in the entire urban water cycle. Furthermore, there is potential for greater adoption of digital twin, especially in simulating urban flood inundation and flood evacuation routes. Integrating real-time data, data-driven modeling, and CDVT can significantly improve real-time flood forecasting. This benefits stakeholders and the public by enhancing early warning systems, preparedness, and flood resilience, leading to more effective flood risk management and reduced impacts on communities.

Item Type:	Article
Identifier:	doi.org/10.1016/j.scs.2023.104958
Additional Information:	Gold OA - Read and Publish
Keywords:	Augmented reality; Digital twin; Digital visualisation; Flood risk management; Systematic review; Virtual reality
Subjects:	Computing Construction and engineering
Depositing User:	Kourosh Behzadian
Date Deposited:	27 Sep 2023 14:00
Last Modified:	04 Nov 2024 11:26
URI:	https://repository.uwl.ac.uk/id/eprint/10398

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