I love lighthouses, and am borderline obsessed with them. I have lucky lighthouse socks (I’m wearing them today), I own books about them, and in high school I made a papier-mâché lighthouse lamp. I have spent hours in the rain trying to photograph them during storms. Furthermore, they are most often found in places where the sea is at its most violent, and from a technical perspective, most interesting.
Naturally, when a bright master’s student from our lab asked if I was interested in joining his thesis committee to research the impact of breaking waves on lighthouses, I could not help but say yes. My research on coral reefs focuses mainly on the complex ways in which waves change as they break across the reef. In many ways, this is a similar process to what happens when waves hit the rocky shoals that many lighthouses are built on. This makes for a compelling intersection between my professional interests and private obsessions!
Coral reefs and the islands that they protect from flooding are in big trouble. This is arecurringthemeon thisblog, and now it’s time for the latest update. We are currently building towards the development of an early flood warning system for low-lying tropical islands fronted by coral reefs. Our previous work on this topic has focused on finding ways to do this accurately for a wide variety of coral reef shapes and sizes, as well as different wave and sea level conditions. However, it’s not enough to be accurate- to deliver timely early warnings, you also need to be fast.
That’s where the latest research of Vesna Bertoncelj comes in.
Vesna’s research provides us with new approaches for making highly accurate predictions of coastal flooding, at limited computational expense. The numerical models that we use to estimate flooding often take a long time to simulate, since they resolve many complex physical processes at high resolution in space and time. However, by paring down these models to only the most essential components for the task at hand, we can do this much faster. My colleagues at Deltares recently developed the SFINCS model, which has been successfully used to predict flooding in a fraction of the time that our standard models take. But how do we put all these different pieces together?
First, Vesna established a baseline for model performance by running a computationally intensive XBeach Non-Hydrostatic model (XB-NH+), and a much faster SFINCS model. These models provide an estimate for runup (R2%), which can be taken as a proxy for coastal flooding. In the second step, she used a lookup table (LUT) of pre-computed XBeach model output and to derive the input for the SFINCS model. The crucial task is doing this quickly and accurately, so she experimented with different interpolation techniques for deriving that input. She then compared her new approach with the standard models to find the fastest and most accurate combination.
Her research gives us a useful methodology that we can implement to speed up our early flood warning system, saving time and hopefully someday saving lives.
Vesna’s quality of work is excellent and she has a fantastic attitude towards research and collaboration. Her curiosity, professionalism, and diligence will undoubtedly serve her well in the years to come. I hope that we will have other opportunities to collaborate in the future. If anybody out there needs a bright young coastal researcher and/or modeller, hire her!