Ai et al. (2026) A numerical modelling-supported digital twin for urban floods monitoring in typhoon or storm scenario

Identification

• Journal: Environmental Modelling & Software
• Year: 2026
• Date: 2026-01-10
• Authors: Tangyao Ai, Liang Gao, Xianfei Yin, Haoxuan Du, Q. Li, Hongcai Zhang
• DOI: 10.1016/j.envsoft.2026.106870

Research Groups

• State Key Laboratory of Internet of Things for Smart City, University of Macau, Macao SAR, China
• Department of Ocean Science and Technology, University of Macau, Macao SAR, China
• Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China
• Faculty of Science and Technology, University of Macau, Macao SAR, China
• Department of Electrical and Computer Engineering, University of Macau, Macao SAR, China

Short Summary

This study proposes a high-fidelity hydrodynamic digital twin framework that integrates a numerical urban flood model with a real-time forecasting data visualization platform via an interactive interface. The framework enables real-time urban flood prediction and dynamic scenario visualization, demonstrated successfully for the Macao Peninsula during Typhoon Hato (2017).

Objective

• To develop and test a high-fidelity hydrodynamic digital twin framework that overcomes barriers in urban flood management by integrating physics-guided numerical flood prediction with a scalable, interactive visualization platform for real-time monitoring and decision support.

Study Configuration

• Spatial Scale: Macao Peninsula
• Temporal Scale: Real-time prediction for typhoon or storm scenarios (e.g., Typhoon Hato in 2017)

Methodology and Data

• Models used: High-resolution numerical urban flood model (hydrodynamic simulations)
• Data sources: Real-time rainfall and storm data, various consolidated inputs (specific sources not detailed but implied to be observational/forecast data)

Main Results

• A three-layer digital twin framework was developed, comprising a data acquisition layer for consolidating inputs, a modeling layer for numerical simulations, and a visualization layer for web-based output interpretation.
• The framework features an interactive web interface allowing users to upload rainfall and storm data to initiate urban flooding simulations.
• It successfully enables real-time prediction of urban floods under designed storm or tropical scenarios.
• The feasibility of the framework was validated through its application to the Macao Peninsula during Typhoon Hato (2017).
• The integrated system provides an intelligent decision-support framework for real-time hydrodynamic forecasting and dynamic scenario visualization of urban floods.

Contributions

• Proposes a novel high-fidelity hydrodynamic digital twin framework that addresses the persistent barriers in integrating physics-guided urban flooding prediction with a scalable visualization platform.
• Introduces an interactive interface that allows users to upload data and initiate simulations, enhancing user participation and decision-making capabilities.
• Demonstrates the practical feasibility of a comprehensive digital twin for urban flood monitoring and real-time forecasting, bridging the gap between complex numerical models and intuitive visualization for urban water management.

Funding

• Not specified in the provided text.

Citation

@article{Ai2026numerical,
  author = {Ai, Tangyao and Gao, Liang and Yin, Xianfei and Du, Haoxuan and Li, Q. and Zhang, Hongcai},
  title = {A numerical modelling-supported digital twin for urban floods monitoring in typhoon or storm scenario},
  journal = {Environmental Modelling & Software},
  year = {2026},
  doi = {10.1016/j.envsoft.2026.106870},
  url = {https://doi.org/10.1016/j.envsoft.2026.106870}
}