Chaudhary et al. (2026) A Hybrid 1D/2D Dynamic Fast Urban Flood Model Using Cellular Automata

Identification

• Journal: Lecture notes in civil engineering
• Year: 2026
• Date: 2026-01-01
• Authors: Aashish Chaudhary, A Deletic, Maziar Gholami Korzani
• DOI: 10.1007/978-3-032-18708-6_21

Research Groups

• Queensland University of Technology, Brisbane, QLD, Australia

Short Summary

This study develops and validates a novel Hybrid Cellular Automata-based Dynamic Fast Flood Model (CADFFM) coupled with the 1D EPA SWMM, demonstrating improved computational efficiency and reliable accuracy for urban flood prediction by incorporating Bernoulli hydraulic head and bidirectional surface-subsurface interactions.

Objective

• To develop and validate a computationally efficient and robust hybrid 1D/2D urban flood model (Hybrid CADFFM) that accurately captures complex hydrodynamic phenomena and bidirectional interactions between surface and subsurface drainage networks for real-time urban flood prediction and management.

Study Configuration

• Spatial Scale: Urban catchment scale, including large-scale applications.
• Temporal Scale: Dynamic simulations for flood events, suitable for real-time applications.

Methodology and Data

• Models used: Cellular Automata-based Dynamic Fast Flood Model (CADFFM), Hybrid CADFFM (CADFFM coupled with 1D EPA SWMM), 1D EPA SWMM. Performance compared against MIKE FLOOD.
• Data sources: Three benchmark dam-break experiments for validation, and application to a real-world urban catchment.

Main Results

• The CADFFM effectively incorporates Bernoulli hydraulic head to account for kinetic energy, enabling it to better replicate complex hydrodynamic phenomena such as backwater effects, hydraulic jumps, and transcritical flows.
• The Hybrid CADFFM, formed by coupling CADFFM with 1D EPA SWMM, successfully enables bidirectional interactions between surface and subsurface drainage networks.
• The model demonstrates reliable accuracy in predicting flood extents (in square metres) and maximum depths (in metres) when validated against dam-break experiments and applied to a real-world urban catchment.
• Simulations using the Hybrid CADFFM perform approximately twice as fast as those conducted with MIKE FLOOD.

Contributions

• Introduction of a novel Cellular Automata-based Dynamic Fast Flood Model (CADFFM) that enhances accuracy by incorporating Bernoulli hydraulic head to capture kinetic energy and complex hydrodynamic effects.
• Development of a robust hybrid 1D/2D urban flood model (Hybrid CADFFM) through bidirectional coupling of the CA-based surface model with the 1D EPA SWMM, allowing for integrated surface and subsurface flood simulations.
• Significant improvement in computational efficiency, performing simulations approximately twice as fast as traditional models like MIKE FLOOD, while maintaining reliable accuracy.
• Provides a computationally efficient and robust tool suitable for large-scale, real-time urban flood prediction and management, addressing limitations of existing models.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{Chaudhary2026Hybrid,
  author = {Chaudhary, Aashish and Deletic, A and Korzani, Maziar Gholami},
  title = {A Hybrid 1D/2D Dynamic Fast Urban Flood Model Using Cellular Automata},
  journal = {Lecture notes in civil engineering},
  year = {2026},
  doi = {10.1007/978-3-032-18708-6_21},
  url = {https://doi.org/10.1007/978-3-032-18708-6_21}
}