Coasts – Page 2 – Coastally Curious

Casa en la Playa

This morning as I was finishing my first coffee, one of my Deltares colleagues shared a video of a house on the beach in El Salvador. It was a surreal, post-apocalyptic, Planet of the Apes scene, made all the more mysterious by the accompanying news text (translated from Dutch): “Abandoned villa washes up entirely on the beach in El Salvador. The ruins of a villa have recently washed up on the beach of La Puntilla in El Salvador. It is a great mystery how the entire house ended up on the beach. Hurricane Elsa may have blown the building away.“

Beach house at La Puntilla, on the Pacific coast of El Salvador [Source: La Presna Grafica]

Having spent a fair bit of time professionally contemplating the destructive power of storm-generated waves on tropical coastlines, I was immediately skeptical about this hypothesis. How could a massive concrete structure like that survive such a pummeling and then just “wash up” on a beach?

Being a bunch of sediment transport nerds, my colleagues made all kinds of jokes about building a house-transport module into XBeach or SedTRAILS, or estimating the critical shear threshold and porosity of this giant “particle”. However my curiosity was irrevocably piqued- how did the damn thing get there? It must have been there the whole time, with the coast eroding around that, but how or why?

The Dutch news site was not particularly helpful, so I snooped around on the internet until I found a promising lead in the El Salvadorian news. Apparently the house is located near the village of La Puntilla, on the Pacific coast of El Salvador. Apparently it was a former hotel built (unwisely) right next to the beach. Suffering significant damage during Hurricane Mitch in 1998, it later became a church. Numerous people died in the former hotel and more recently among the ruins, so the building is even spookier than it first seemed. Indeed, after looking in Google Earth, it became apparent that the hotel has been there the entire time:

Before-and-after satellite photos of the abandoned hotel in La Puntilla, showing about 150 m of beach erosion between 2003 and 2021. The dashed line indicates the approximate position of the 2003 shoreline, based on some quick-and-dirty georeferencing and not accounting for potential variations in shoreline position due to the stage of the tidal cycle at the time each photo was taken. The tidal range on 50 km up the coast is about 2 m, so if the beach is very flat, the 2003 shoreline may actually be much closer at high tide.

So the hotel didn’t just “wash up on the beach” one day. But why exactly did it erode so much? Was there a particularly devastating storm? Is climate change or some nefarious human meddling in the coastline to blame? By zooming out a little bit, we can put this coastal erosion into a larger context.

Google Earth is nearly always my first go-to tool for investigating a new site as a coastal engineer — you can learn so much by carefully observing how a given beach or estuary has changed through time, and by looking for evidence of the physical processes shaping the landscape. For instance, white foam usually indicates breaking waves, and by watching how sand piles up in certain places, we can estimate in which direction the sand is mostly moving. What can we learn about this site?

Tidal inlet at La Puntilla, El Salvador. The inlet channel connects the Pacific Ocean to a tidal lagoon, and is fronted by an underwater ebb-tidal delta. Large swell waves travel thousands of kilometers from the stormy south Pacific and break on the ebb-tidal delta (see the white foam), which greatly reduces their size. In this way, the ebb-tidal delta acts like a massive, sandy breakwater. Waves generate currents that push the sand from right to left along the coast, but the sand needs to cross the inlet. It makes this journey in regular spurts that lead to periodic accumulation and erosion of sand along the nearby coasts. This is the fate that befell our poor abandoned hotel.

It seems that the hotel was built on a type of coastal feature that is notorious for massive erosion world-wide: the beach adjacent to a tidal inlet. Tidal inlets connect lagoons with the ocean, the water rushing in and out of them several times a day. The water moves very fast and is stirred up by waves, so it can carry lots of sand and mud to and from the nearby coast. This means that this tidal inlets and the coastlines next to them have the potential to change shape dramatically over time. The inlet channel and smaller channels connected to it have a tendency to migrate back and forth across the underwater ebb-tidal delta like an out-of-control fire hose. If one of these channels is pushed up against the coast, it can cause massive erosion. This seems to be what happened to the abandoned hotel.

If you examine a timelapse in Google Earth (here), the incredibly dynamic nature of this system is apparent:

https://earthengine.google.com/timelapse/#v=13.28245,-88.90064,11.273,latLng&t=2.44&ps=50&bt=19840101&et=20201231&startDwell=0&endDwell=0

By a remarkable coincidence, this is the same process that I am investigating in my PhD: how does sediment move around at tidal inlets like this? It is not only the El Salvadorians who need to worry about this process — the topic is also a vital matter of investigation for Dutch coastal management authorities trying to protect their coast. Lesson learned: don’t mess with ebb-tidal deltas!

Sediment Pathway Detective Work

Ebb-tidal deltas are gigantic piles of sand that form at the seaward mouth of tidal inlets. They are constantly on the move, shifting shape and size in response to the waves and tides. Where exactly is that sand going? This is a question I have been struggling with for the past 5 years during my PhD, and we have recently made great strides in part due to the efforts of Paula Lambregts.

Yesterday, Paula Lambregts successfully defended her master’s thesis, “Sediment bypassing at Ameland inlet“. I had the great honour of co-supervising Paula’s research throughout the last ten or so months, and I am enormously proud of her. Her project encompassed a range of approaches, including bathymetric analysis and numerical modelling, to solve the mystery of the sediment pathways.

First, Paula’s detective work led her to examine detailed measurements of the seabed bathymetry at Ameland Inlet in the Netherlands, taken over the past fifteen years. These measurements give snapshots of the underwater delta landscape. By comparing the bathymetry from different months or years, we can track the delta’s evolution. In the image below, we see four snapshots of the ebb-tidal delta before and after the construction of a sand nourishment (i.e., the large pile of sand that appears in panel B). This nourishment was a large-scale pilot test to determine if creating sand deposits like this is a viable strategy for strengthening the coast of nearby islands.

Bathymetric maps showing Ameland Ebb-Tidal Delta before (A) and after (B,C,D) the construction of a massive sand nourishment. Paula’s analysis tracked how this nourishment evolved over time, smoothed and smeared out to the east and south east by the combined effects of waves and tides.

After describing how the delta has evolved in the past, Paula developed hypotheses about the physics underlying this behaviour- how do waves and tides move the sand around to create the patterns we observe? To answer this question, she used a combination of computer models to estimate sand transport pathways. This allows us to “connect the dots” and explain how the sand moved from one place to another. The first component was a D-Flow FM model, which is used to simulate the hydrodynamics (waves and tides) and sediment transport (where and how much sand moves). The second component of her modelling approach was to apply SedTRAILS, a brand-new tool developed by my colleagues and I at Deltares for visualizing predicting sediment transport pathways. Using SedTRAILS, she was able to create some really cool maps that indicate where the sand goes.

Sediment transport pathways on Ameland ebb-tidal delta in 2020, as visualized using SedTRAILS. The small white circles indicate the source locations of sediment, and thin black lines show the sediment pathways originating from those sources. The yellow lines highlight major transport pathways, and the red lines indicate convergent zones where multiple pathways meet. The white dashed lines indicate divergence zones, where the transport pathways veer away from and (on average) do not cross.

Drawing on her prior expertise in geology, Paula combined those two lines of evidence (the measurements of the seabed and the modelled sediment pathways), to come up with a series of fantastic conceptual diagrams. These diagrams distill the mysterious piles of sand and complex spaghetti of the images above into a more easily understandable picture:

Paula’s conceptual model summarizing all of the different processes shaping Ameland ebb-tidal delta in 2020. Check out her thesis to see the complete evolution over the past 15 years!

The work that she did is extremely valuable for coastal management, since it gives more insight into where (and where not!) to construct sand nourishments. It also brings new insights to science about how these complex systems work. Last of all, it is enormously helpful for the research that we are continuing to do at TU Delft and Deltares. In September I will continue on with the work on sediment transport pathways at tidal inlets begun during my PhD, and build on the work that Paula has carried out in her thesis project. I am extremely proud of her and hope that we can continue to collaborate in the future!

Lighthouse Fever

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!

I am extremely proud to announce that Jan van Gorsel has successfully defended his MSc thesis, “Numerical analysis of broken regular wave forces on a shoal-mounted cylinder“. I was extremely privileged to sit on his graduation committee and work with him for the past 9 months.

Simulation of a wave breaking on a rocky shoal and then colliding with a lighthouse, from Jan van Gorsel’s thesis. The blue represents air and the red water. It is really hard to predict something like this, because of the complex bouncing and splashing motion of the broken wave. Simulating this process is a bit like trying to predict the exact spatial distribution of spilled beer after a drunk guy stumbles and trips in a crowded pub. Sigh. Remember crowded pubs?

Super Speedy Reef Modelling

Coral reefs and the islands that they protect from flooding are in big trouble. This is a recurring theme on this blog, 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.

I am extremely proud to announce that Vesna Bertoncelj has successfully defended her MSc thesis, “Efficient and accurate modeling of wave-driven flooding on coral reef-lined coasts: On the interpolation of parameterized boundary conditions“. I had the great privilege of sitting on her graduation committee and working with her over the past year or so.

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?

A schematic overview of Vesna’s research methodology. [Source].

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!

Restoring Coral Reefs for Flood Protection

We frequently hear in the news about dying coral reefs, and also about the threats of sea level rise and climate change. But there is a key gap: what if we can hit two birds with one stone, and restore damaged ecosystems while providing vital protection against flooding? Our latest research demonstrates how coastal managers and ecologists can join forces to achieve both goals, which may help stretch limited funding further.

I am extremely proud to share Floortje Roelvink’s first scientific paper, “Coral reef restorations can be optimized to reduce coastal flooding hazards“, published in Frontiers of Marine Science. I had the great privilege of sitting on her MSc thesis committee two years ago, and she has been our colleague at Deltares ever since.

Ebb-tidal deltas: Badass Morphological Features (BAMFs)

At TU Delft, a requirement for our PhD defense is to make ten propositions based on what we have learned during the previous years. Claims posed by my friends and colleagues deal with the nitty gritty details (“All diffusive processes can be derived from an advective one, and failing to do so yields incorrect modelling“^[1]) but also the bigger picture of how we do what we do (“The way morphological models are presented and interpreted has a lot in common with predictions of snow depth in five years on December 26th at 4pm. The knowledge in these models deserves a better presentation“^[2]).

The propositions must be both defendable and opposable, so as to stimulate an interesting debate during the defense. Some of the propositions should reflect the findings of our research, but it is also traditional to include statements that have nothing to do with it. One colleague^[3] even suggested (tongue in cheek) that the increase in the height of Dutch men over time could be explained by sea level rise. I couldn’t resist analyzing the data myself, and the results were surprisingly good:

Spurious correlation of the week! As John von Neumann said, “With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.”

These propositions are a chance to inject a bit of last-minute philosophizing into our Doctorates of Philosophy, and range from the wise (“No wind is favourable if a person does not know to what port (s)he is steering – Seneca“^[4]) to the downright cheeky (“This proposition is not opposable“^[1]).

What I Learned by Counting Sand for 5 Years

As the clock is ticking on my own PhD (259 days, 13 hours, 39 minutes, and 51 seconds, but who’s counting? *eye twitches*), I started preparing some propositions of my own (obviously in a fit of procrastination on my dissertation). After nearly five years of scrutinizing sand and contemplating connectivity, my research has led me to an inescapable conclusion:

Ebb-tidal deltas are badass morphological features (BAMFs),
(c.f. Phillips [2015]).

What, pray tell, is an ebb-tidal delta, and why is it so badass? Ebb-tidal deltas are large underwater piles of sand at the mouth of estuaries and tidal inlets, deposited by outflowing tides and reshaped by waves. I spend my days studying how waves and tides move sand around on the Ameland ebb-tidal delta in the northern part of the Netherlands (see below). We need to know this in order to plan ecologically-sustainable flood protection measures for the Dutch coast. A morphological feature is just a fancy name for some part of a landscape, like a hill or a valley or a beach.

An ebb-tidal delta is the giant pile of sand located at the mouth of a tidal inlet like this one. This may not sound glamorous, but understanding the way it moves around is extremely important for ensuring safe navigation and for predicting erosion and flooding of adjacent coasts.

What makes a badass “badass”?

Phillips^[5] defines the archetypal badass as “individualistic, non-conformist, and able to produce disproportionate results”, and applies this concept to geomorphology (the study of how landscapes evolve, at the crossroads of geology and physical geography). Ebb-tidal deltas meet these three criteria, which makes them badass morphological features (BAMFs):

Ebb-tidal deltas are each unique (in shape, location, composition, and in terms of the environmental forces shaping them (like waves and tides)), and hence individualistic.
Ebb-tidal deltas are chaotic systems which defy accurate prediction using physics-based numerical models^[6], and hence are non-conformist or “naughty”^[7]. This numerical naughtiness is a serious problem for coastal engineers and scientists, since a failure to accurately predict ebb-tidal delta evolution can threaten public safety and lead to costly property or infrastructure damage. They do not “play by the rules” of our existing physics-based deterministic models.
Ebb-tidal deltas are highly nonlinear systems which can greatly amplify small instabilities^[8], and hence produce disproportionate results.

In addition to the strict definitions of Phillips^[5 ^], ebb-tidal deltas are also “belligerent or intimidating, ruthless, and tough”, other traits reflective of badassery [Oxford Engish Dictionary]. The Columbia River ebb-tidal delta alone is responsible for dozens shipwrecks in the past century, and Ameland ebb-tidal delta has also featured numerous wrecks throughout its history.

Quoting Thomas Pynchon^[9], Phillips also notes that badasses are “able to work mischief on a large scale”. Ameland ebb-tidal delta covers an area of approximately 100 square kilometers, roughly the size of The Hague. Many ebb-tidal deltas around the world are even larger!

Seriously?

Now admittedly, ebb-tidal deltas are just big piles of sand. A big pile of sand is probably not the first thing that comes to mind when you hear the word “badass”, unless you are Ralph Bagnold or a Sarlacc. This could probably also be considered gratuitous personification or anthropomorphization.

I’m sure that many of my friends and family have been scratching their heads as to why I would sacrifice the latter half of my 20s to understand them better. A critical reader might ask, “is it possible that you have only convinced yourself that ebb-tidal deltas are cool out of self-preservation?” And the answer is yes. Yes, I have. Nonetheless, I remain steadfast in my assertion that ebb-tidal deltas exhibit major symptoms of geomorphological badassery.

Although the concept of geomorphological badassery may seem silly at first, it illuminates several important truths of our (mis)understanding of these complex bathymetric features. Ebb-tidal deltas are important to study for reasons of coastal flood protection, navigational safety, and ecological value, but we are bad at predicting how they will evolve. This is because each ebb-tidal delta is unique, making it challenging to generalize their behavior. Furthermore, their chaotic, non-conformist behavior renders many of our usual deterministic prediction techniques ineffective. Lastly, the amplifying effect of highly nonlinear physical processes means that small physical changes (e.g., the development of a tiny shoal) could have disproportionately large consequences (e.g., relocation of a channel several kilometers wide). As such, badassery provides a useful conceptual framework for describing the challenges presented by ebb-tidal deltas to coastal engineers and scientists.

Badass.

References

[1] Chavarrias Borras, V. [2019]. Obtaining well-posedness in mathematical modelling of fluvial morphodynamics. PhD Thesis, Delft University of Technology.
[2] de Schipper, M.A. [2014]. Alongshore variability of nourished and natural beaches. PhD Dissertation, Delft University of Technology.
[3] Meirelles Nunes da Rocha, S. Effects of a stratified tidal flow on the morphodynamics. PhD Dissertation, Delft University of Technology.
[4] de Vet, P.L.M. [2020]. Intertidal Flats in Engineered Estuaries: On the Hydrodynamics, Morphodynamics, and Implications for Ecology and System Management. PhD Dissertation, Delft University of Technology.
[5] Phillips, J. D. (2015). Badass geomorphology. Earth Surface Processes and Landforms, 40(1), 22-33. (Yes, this is a legitimate scientific publication!)
[6] Elias, E., Teske, R., van der Spek, A., & Lazar, M. [2015]. Modelling tidal-inlet morphodynamics on medium time scales. In The Proceedings of the Coastal Sediments 2015.
[7] Kennedy, B. A. [1979]. A naughty world. Transactions of the Institute of British Geographers, 550-558.
[8] Elias, E. P., Van der Spek, A. J., Pearson, S. G., & Cleveringa, J. [2019]. Understanding sediment bypassing processes through analysis of high-frequency observations of Ameland Inlet, the Netherlands. Marine Geology, 415, 105956.
[9] Pynchon T. [1984]. Is it O.K. to be a Luddite? The New York Times Book Review (October 28): 40–41.

Ameland Datapalooza!

Check out our new paper here!

Three years ago, I experienced one of the highlights of my professional career so far. Alongside researchers from 3 universities, the Dutch government, and several other institutions, we carried out a 40-day field measurement campaign at Ameland Inlet in the north of the Netherlands. We deployed several frames loaded up like Christmas trees with every instrument imaginable: ADVs and ADCPs to measure waves and currents, LISSTs and OBSs to measure suspended sediment, a YSI multiprobe to measure salinity and other water quality indicators, and even a 3D sonar to track the migration of ripples along the seabed.

One of the five measurement frames that we deployed in Ameland back in Fall 2017. It was stacked full of instruments to measure the waves, currents, suspended sand and mud, salinity, ripples, and more.

Four of our five frames survived the relentless ebb and flow of the tide, and even two major storms (one of which left me stranded in Germany after the wind blew down all the overhead train power lines between Berlin and Amsterdam!). In the end, we obtained enough data to keep me busy for probably 3 PhDs, if not the rest of my career. This is just as well, since that last frame was buried in the storm, and based on our understanding of the local dynamics, it will likely re-emerge in another few decades, just in time for my retirement! I look forward to sharing my other findings with you here in the next few months!

Although it used to be the norm for scientists to squirrel away their data, there is an increasing movement towards open accessibility of research data. This improves transparency and accountability in the scientific process, and opens up new opportunities for collaboration. The data we collected is now available in its entirety here on the 4TU web portal or on Rijkswaterstaat’s interactive web viewer.

However, there is a lot of data – I mean A LOT! To help researchers interpret the contents of this database, we prepared an overview paper, which was finally published in the journal of Earth System Science Data! It is also accompanied by a more detailed report, which gets into the nitty-gritty details we didn’t have room to describe in the paper. Nobody likes to read a phonebook-sized report, but it’s nice to have the information there for the few brave souls who do want to comb through our dataset.

Sailing across the Vlie ebb-tidal delta on our way to retrieve the measurement frames at the end of the field campaign.

It was all a huge team effort, as evidenced by the 20+ co-authors. My contribution to this paper focused on the processing of the LISST and YSI multiprobe data, which tell us about the size of particles floating through the water, and how salty that water is. I also designed the maps. As a kid, I loved to read and draw maps, and I think that 7-year-old Stuart would have been tickled to know that he would still be dabbling in cartography all these years later.

As the research in the rest of my PhD (and beyond!) will continue to focus on the fruits of this measurement campaign, I am very keen to work together and collaborate with other researchers who have an interest in this dataset. Please get in touch if you are interested!

Rolling the Dice: Dealing with Uncertainty in Coastal Flood Predictions for Small Island Developing States

Small island developing states around the world are especially vulnerable to the hazards posed by sea level rise and climate change. As engineers, we have a number of tools in our toolbox for reducing the risk posed by coastal flooding and for planning adaptation measures. We often rely on predictive models which combine information about expected wave and sea level conditions, the topography of the coast, and vulnerable buildings and population to estimate potential flooding and expected damage.

However, to use these types of models, we first need to answer a lot of questions: what exactly are the expected wave and sea level conditions? What if detailed topographic measurements are unavailable? What if the population of a given coastal area increases? How are the local buildings constructed, and what are the consequences of that for estimating damage from flooding?

If our information is imperfect (which it almost always is), all is not lost: we can still make educated guesses or test the sensitivity of our models to a range of values. However, these uncertainties can multiply out of control rather quickly, so we need to be able to quantify them. There is no sense in spending the time to develop a detailed hydrodynamic model if your bathymetry data is crap. Can we get a better handle on which variables are the most important to quantify properly? Can we prioritize which data is the most important to collect? This would help us make better predictions, and to make better use of scarce resources (data collection is expensive, especially on remote islands!).

Matteo Parodi investigated these questions in his master’s thesis, and just published his first paper, “Uncertainties in coastal flood risk assessments in small island developing states“. I had the great privilege and joy of co-supervising Matteo during his thesis, and I am immensely proud of him and his work!

Based on a study of the islands of São Tomé and Príncipe, off the coast of Africa, Matteo found that topographic measurements and the relationship between flood depth and damage to buildings were the biggest uncertainties for predicting present-day flood damage. This means that measuring topography of vulnerable coastal areas in high resolution, and performing better post-disaster damage surveys will provide the best “bang for your buck” right now. However, for longer time horizons (i.e. the year 2100), uncertainty in sea level rise estimates become most important.

Matteo’s work will help coastal managers on vulnerable islands to better prioritize limited financial resources, and will improve the trustworthiness of our predictive models. Great job, Matteo!

Can 3D-Printed Corals Help Us Prevent Flooding?

Coral reefs around the world are dying; that much is clear from the headlines we see in the news that grow increasingly distressed with each passing year. This is an ecological catastrophe, but are we also losing another key benefit of reefs? Coral reefs provide a form of natural protection against wave-driven flooding on tropical coastlines. This is partly because the physical form of the reef (often a big rocky shelf) serves as a sort of natural breakwater, but is also due to the frictional effects of the corals themselves.

Many species of coral have complex shapes that disrupt the flow of water across reefs, generating turbulence and dissipating energy. This has the effect of reducing the height of waves as they travel across the reef towards the shore. However, these effects are incredibly complex and poorly understood, so we usually just simplify them in our predictive models by considering a reef to be more “hydraulically rough” than a sandy beach, for example. But we need to do better: these models are used to forecast flooding and estimate the impact of future climate change on vulnerable coasts.

How can we improve this? In coastal engineering, we often conduct experiments in the laboratory to test our theories and understand the chaos of natural systems in more controlled settings. What if we could make a scale model of a coral reef and measure exactly how waves are dissipated?

I am extremely proud to announce the graduation of Paul van Wiechen, one of the Master’s students whom I have had the pleasure of supervising. Yesterday, he defended his thesis, “Wave dissipation on a complex coral reef: An experimental study“, where he built a tiny coral reef in the TU Delft wave flume (a 30-m long bathtub with a wave-making paddle at one end) using hundreds of 3D-printed coral models.

Paul’s thesis, “Wave dissipation on a complex coral reef: An experimental study“.

It was one of the coolest projects I have ever seen, and his research provides us with valuable measurements that give us a deeper understanding of the vital role that corals play in protecting our coasts.

He also did all of this in the middle of a global pandemic, and somehow managed to stay completely on schedule. We are very lucky, because Paul will be joining the Coastal Engineering department here at TU Delft to start a PhD on dune erosion this fall. We are all glad to have him on the team and eager to see what his research unveils next!

Clustering Coral Reefs for Coastal Flood Forecasting

Many of the world’s idyllic tropical coasts are facing threats on multiple fronts. Rising seas threaten the very habitability of many low-lying islands, and the coral reefs that often defend these coasts from wave attack are dying, too. Compounding this problem is the sheer number and variety of these islands: there are thousands of islands, and the coral reefs surrounding them come in all shapes and sizes. Located around the globe, these islands are each exposed to a unique wave climate and range of sea level conditions. This variability in reef characteristics and hydrodynamic forcing makes it a big challenge to forecast how waves will respond when they approach the shore, something that is quite tricky even at the best of times. Under these circumstances, how can we protect vulnerable coastal communities on coral reef coasts from wave-driven flooding?

This is the problem that our fantastic former student, Fred Scott (now at Baird & Associates in Canada), tackled in his paper, Hydro-Morphological Characterization of Coral Reefs for Wave Runup Prediction, recently published in Frontiers in Marine Science. Working in partnership with Deltares and the US Geological Survey for his master’s thesis, Fred came up with a new methodology for forecasting how waves transform in response to variations in the shape and size of coral reefs.

fredFigure1 — **(A)** This is a typical fringing coral reef cross-section, showing waves approaching from the right, with the shore on the left. **(B)** Fred came up with a number of algorithms for classifying and organizing the massive dataset of coral reef cross-sections. **(C)** The measurements used in our study are from sites around the globe. **(D)** This is what 30,000 reef cross-sections look like when you try to plot them all on top of one another- clearly we need to whittle those down a bit… [Source: Scott et al, 2020]

In our previous research on this topic, we tried to predict flooding on coral reef-lined coasts using a very simplified coral reef shape. This was fine as a first guess, but most reefs are bumpy and jagged and bear little resemblance to the unnaturally straight lines in my model. We couldn’t help it though: there just wasn’t enough data available when I started my thesis four years ago, so we did the best we could with the information we had at the time. On the bright side, using a single simple reef shape meant that we could easily run our computer simulations hundreds of thousands of times to represent a wide range of wave and relative sea level conditions.

Fast forward three years to when Fred began his own thesis. We now had access to a mind-boggling dataset of over 30,000 measured coral reef cross-sections from locations around the world! However, instead of too little data, we now had too much! If we wanted to simulate a whole range of wave and sea level conditions on each of the reefs in our dataset, it might take months or even years to run our models! Fred had the daunting task of distilling that gargantuan database down to a more manageable number of reef cross-sections.

But how do we choose which cross-sections are the most useful or important to look at? Even though every coral reef is, like a beautiful snowflake, utterly unique, surely there must be some general trends or similarities that we can identify, right? This question lies at the heart of Fred’s research, and to answer it, he turned to many of the same powerful statistical and machine-learning techniques used by the likes of Google and Facebook to harvest your life’s secrets from the internet or power self-driving cars. Maybe we can use some of this technology for good, after all!

The main approach that Fred used in this study was cluster analysis, a family of techniques that look for similarities or differences between entries in a dataset, and then group the entries accordingly into clusters. The entries within one cluster should be more similar to each other than to the entries in other clusters. In our case, this meant grouping the reefs into clusters by similar shape and size. This allowed us to increase efficiency and reduce redundancy by proceeding with 500 representative cross sections, instead of the entire database of 30,000.

zoom — These days when I’m lonely, I Zoom with 500 of my favourite coral reef profiles…

Other studies in our field have tried similar approaches (such as this Brazilian study of coral reef shape), but the innovative part of Fred’s technique was to also account for similarities in the hydrodynamic response of the waves to each reef via a second round of clustering. Wave transformation on coral reefs can be immensely complicated, so it is entirely possible that two reef profiles could look very different, but lead to the same amount of flooding in the end. Since we are mainly concerned about the flooding (rather than a classification for ecological or geological purposes about coral reef formation and evolution), this suits us just fine!

In the end, Fred was able to distill this colossal dataset into between 50-312 representative cross sections that can forecast wave runup with a mean error of only about 10%, compared to predictions made using the actual cross sections. This opens the door wide for a range of future applications, such as climate change impact assessments or coral reef restoration projects. Right now, we are working on a new project that will apply Fred’s approach to the development of a simplified global early-warning system for wave-induced flooding on coral reef-fronted coasts.

Great work, Fred, and congratulations on your first publication! I am excited to see where this road takes us!

Sources:

Scott, F., Antolinez, J.A.A., McCall, R.C., Storlazzi, C.D., Reniers, A.J.H.M., & Pearson, S.G. (2020). Hydro-morphological characterization of coral reefs for wave-runup prediction. Frontiers in Marine Science. [Link]
Scott, F. (2019). Data reduction techniques of coral reef morphology and hydrodynamics for use in wave runup prediction. [Link]. TU Delft MSc thesis in cooperation with Deltares and the US Geological Survey.
Scott, F., Antolinez, J.A., McCall, R.T., Storlazzi, C.D., Reniers, A., and Pearson, S., 2020, Coral reef profiles for wave-runup prediction: U.S. Geological Survey data release [Link].