Tropical storms and cyclones have already affected hundreds of millions of people in coastal areas worldwide. Extreme weather can have a devastating impact on coastal communities. To improve readiness, detailed information about all the factors that cause flooding, such as storm surges, rainfall and waves, is essential. These factors often interact in complex ways. New research by Tim Leijnse of Deltares and VU Amsterdam, who will receive his PhD today, offers a solution to this challenge.
New advanced computer model
Tim and his fellow researchers developed a new open-source model for flooding - - in recent years. It can be used to model different types of efficiently. Unlike traditional, computationally heavy models, SFINCS uses a simplified complexity but it can still accurately model essential coastal, river and rainfall processes.
It also includes the effects of dynamic waves, making the model powerful in terms of understanding the interaction between different types of flooding in coastal zones. The newly developed model can deliver levels of accuracy similar to traditional, more complex models, but much faster and with less computing power.
This means that coastal managers have faster access to crucial information in order to warn local people about potential 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."
Tim Leijnse, Deltares coastal expert
Better forecasts for tropical cyclones
The research, '', has also led to a new way of providing better forecasts of the effects of tropical cyclones, as in the Bay of Bengal. New technologies mean that researchers can now make much more reliable estimates of storm surges and high waves than with older, traditional methods.
Predicting waves more accurately
In addition, the model includes a new wave simulator that allows for a better understanding of how waves affect flooding. The simulator can even cover large areas and predict how waves move over long distances to the coast, making flood forecasts even more accurate.
Hurricane Florence in 2018: an example
The new model was tested using Hurricane Florence from 2018, showing that it can forecast complex flooding in a limited time for 1,000 km of coast. This means the model is much faster than traditional models, which can only predict small areas in detail. The results show how important waves are as a factor in the overall water level and how essential it is to include them in flood forecasts.
Improved readiness
With this new method, governments and coastal managers throughout the world may be able to respond faster and better to impending . That opens up the prospect of better warnings, more targeted measures and ultimately better protection for millions of people in coastal areas.