Tropical storms and cyclones have already impacted hundreds of millions living along the world’s coasts. As extreme weather events become more frequent and intense, understanding all the factors that contribute to flooding storm surges, rainfall, and waves is crucial. Now, new research by Tim Leijnse from Deltares and VU Amsterdam offers a powerful solution through an advanced flood model called SFINCS, enabling faster, more accurate flood risk forecasts.
New Open-Source Model: SFINCS
Over recent years, Tim Leijnse and his research team developed SFINCS (Super-Fast INundation of CoastS), a groundbreaking open-source model designed to assess different types of flood risks efficiently.
Unlike traditional flood models that require heavy computing resources, SFINCS simplifies complexity without sacrificing accuracy. It can model essential coastal, river, and rainfall processes and critically, it includes the influence of dynamic waves.
This innovation allows coastal managers to obtain vital information much faster, helping them issue early warnings and prepare communities for floods in time.
“With our newly developed methods, we acquire a better picture of flood risks in coastal areas faster, combining the knowledge of colleagues in different fields about storm surge, wave, and river effects,” said Tim Leijnse, coastal expert at Deltares.
Stronger Forecasts for Tropical Cyclone Impacts
Leijnse’s PhD research, titled “Riding the wave Enabling large-scale wave-resolving probabilistic coastal compound flood modeling”, has paved the way for much more reliable forecasting of tropical cyclone effects, particularly in vulnerable regions like the Bay of Bengal.
Thanks to new technologies, researchers can now better estimate both storm surges and high waves, improving the accuracy of forecasts significantly compared to older methods.
Accurately Predicting Wave Impacts
The SFINCS model includes a new wave simulator that enhances understanding of how waves contribute to coastal flooding.
The simulator can predict wave movements over large areas and long distances, allowing scientists to capture how incoming waves intensify flood risks. This makes forecasts much more realistic and comprehensive.
Proven Success: Testing with Hurricane Florence
To test the model’s capabilities, researchers applied SFINCS to Hurricane Florence, which struck the US East Coast in 2018.
The model successfully simulated complex flooding across 1,000 km of coastline far more territory than traditional models could handle within a similar timeframe.
The results highlighted how critical waves are to total water levels during storms and demonstrated the importance of including them in flood forecasts.
Toward Better Flood Preparedness Worldwide
With the new methods pioneered by Leijnse and his team, governments and coastal managers globally now have the tools to predict floods faster and more accurately.
This opens the door to earlier warnings, more targeted protective measures, and, ultimately, better safety for millions living in vulnerable coastal zones.
As climate change intensifies the threat of storms and flooding innovations like SFINCS could prove vital for building global resilience.