The potential of a quasi-2D model for rapid flood modelling as a planning tool for nature-based solutions

Flooding causes increasing social, economic, and environmental losses, driving demand for flood risk assessment tools that can handle catchment-scale modelling with limited computational resources, a key requirement for evaluating nature-based solutions (NBS) across multiple scenarios. This paper examines the potential of the PHysiographic drainage-inundation (PHD) model, a quasi-2D flood model using physically-based flow formulas (Manning's equation and weir flow) with irregular computational cells, as a practical planning tool for catchment-scale flood modelling and large-scale NBS assessment. The PHD model is benchmarked against the 1D–2D hydrodynamic model MIKE FLOOD on the Sint Maarten case study using 100-year and 20-year design rainfall events, comparing flood extent, water depth, discharge hydrographs, flood risk, and computational time. The PHD model produces results comparable to MIKE FLOOD, a critical success index of 77% and root mean square error in water depth of 0.12 m, while requiring approximately three times less computational time. These findings confirm the PHD model's strong potential as a rapid, accurate planning tool suitable for NBS assessment and real-time operations.