Development of Digital Twin framework for flood risk reduction and mitigation planning

Flooding is among the most frequently encountered disasters and is extravagant in terms of both economic and physical losses, among all disasters that could be triggered by climate change and other anthropogenic activities (Oulahen, 2021). The reason for flooding is not always constant in every other area and it varies depending on the local topographical and weather conditions. These can include rapid urbanisation, frequent high-intensity precipitation events, river overflows, deforestation, and blockage of water channels. The frequency of urban flooding disasters grows with the number of metropolitan regions, emphasising the necessity of understanding why and when flooding happens in urban contexts. Numerous studies have been conducted for building urban flood resilience however conventional methods have often failed to provide completely effective preventive or mitigation strategies for disasters over the years, as the interaction between disasters and physical assets is difficult to understand (Guo et al., 2021). Traditional 2D flood models provide information on flood extent and depth, but understanding the interaction of flood water with surrounding elements-at-risk is critical for flood resilience planning. Digital twin, a state-of-the-art technology for urban studies was explored for tackling the issue. A city digital twin is a dynamic digital replica of the real city that allows real-time data transfer between the two realms using Internet of Things (IoT) sensors, simulation features, and other means to facilitate improved decision-making (Digital Twin Geohub, 2023; Koeva et al., 2023). Digital twin technology offers a solution by allowing for the testing of policies or infrastructure before real-world implementation, thus saving resources and time while empowering policymakers to make data-based decisions.