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Anyone can run a model. Building a reliable framework is the challenge

When someone says to me, “I’ve learned how to run WaveWatch III” or “I can launch cases in SWASH now” , I’m often tempted to reply: “Great… and then what?”. Because running the model is just the tip of the iceberg. Those of us working in coastal numerical modelling know that opening the software, setting up a basic input, and running a simulation can be learned in a matter of days or weeks. Even generating a nice animation of the free surface can look impressive at first glance. But that alone doesn’t make you an expert. The real challenge begins when you have to build a modelling framework that’s robust, efficient, and reusable . That’s where the amateurs and the professionals part ways. It’s Not Just the Physics – It’s What You Do With It Understanding the physics behind the models — energy transfers, dispersion, friction, nonlinearity, slope effects, infragravity generation, etc. — is fundamental. But it’s not enough. Knowing the theory without knowing how to implement it is li...

The Wee Spectrum That Grew: Tales o’ Gamma an’ the Growin’ Sea

By César Esparza Since the beginning of modern ocean and coastal engineering, one of the key questions has been: “Can we mathematically describe the state of the sea?” We know waves don’t come alone or uniformly: they arrive in groups, with varying heights, frequencies, and directions. Spectral analysis allowed us to look at the sea as a sum of sinusoidal components. But what does that spectrum actually look like? Throughout the 1950s and 60s, many researchers attempted to answer this. But it wasn’t until 1964 that Pierson and Moskowitz proposed a concrete spectral shape based on the similarity theory of Kitaigorodskii. Less than a decade later, Klaus Hasselmann and his team sharpened that curve with the now-famous JONSWAP experiment. This blog-column takes you on that journey—explaining the foundations, the derivation of the PM spectrum, the need for JONSWAP, and the intriguing role of the peak enhancement factor: the famous γ \gamma . Kitaigorodskii's Similarity Theory: Looking f...

The invisible force that waves carry: Understanding Longuet-Higgins Radiation Stress Tensor — Part 1

Why did Michael Longuet-Higgins call it radiation stress ? At first glance, the term might sound like something out of nuclear physics — but don’t worry, nothing’s glowing here. In this context, “radiation” simply refers to how waves carry or radiate momentum forward as they travel across the sea, much like light radiates energy through space. Surface waves aren’t just wiggling water up and down — they’re transporting actual momentum. And when those waves grow, shoal, or break near the coast, that momentum doesn’t vanish — it has to go somewhere. It gets transferred into the ocean itself, pushing the water around. That internal push — a force per unit area within the fluid — is what we call stress . Hence the term: radiation stress . If you’ve ever stood waist-deep in the sea and felt a swell gently nudge you shoreward — even before it breaks — then you’ve already experienced radiation stress in action. It’s subtle, but it’s there. That invisible shove is the ocean’s response to ...

How the Sea Tops Over: An Informal Journey Through De Ridder et al. (2024)

Introduction with Salt Spray There’s something mesmerising about watching the sea overflow a coastal defence. It’s not just dramatic—it’s complex. In coastal engineering, predicting how much overtopping will occur isn’t just an equation: it’s a necessity. Get it wrong, and you either waste millions or end up with a structure that behaves like a sieve. And this becomes much murkier in shallow water , where waves don’t behave like they do in textbooks. This is where De Ridder et al. (2024) really makes waves. This paper isn’t just another dataset—it’s a blend of experiments, new insights, practical formulas, and some uncomfortable truths about how little we understand the waves that matter most. Let’s dive in. The Problem with the Usual Formulas For years, we’ve relied on classic mean overtopping formulas like: q ∗ = q g H m 0 3 q^* = \frac{q}{\sqrt{g H_{m0}^3}} Followed by exponential adjustments: q ∗ = a ⋅ exp ⁡ ( − b R c / H m 0 ) q^* = a \cdot \exp(-b R_c/H_{m0}) But what h...

Stephen Salter’s Legacy: How to Build a Wave Tank That Doesn’t Lie to You

When Stephen Salter from University of Edinburgh set out to harness energy from ocean waves in the 1970s, he didn’t expect that one of his biggest challenges would come not from the sea itself, but from the tank built to simulate it. He was developing devices to capture wave power, long snake-like machines stretching across the water surface. To test them, he built scaled-down models and placed them in a wave tank. But something went wrong: every time a wave hit the model and bounced back, it returned towards the wave-maker, distorting the entire experiment. In fact, when he replaced the model with a fully reflective wall, the waves amplified rapidly. The tank was interfering with its own waves. Salter believed that a wave tank should behave like a scientific instrument, as precise as an electronic test bench. He wanted full control over wave size, frequency and direction, and he wanted to be able to repeat rare events whenever needed. He quickly realised that most existing tanks wer...

What if just one wave is enough to cause disaster? (part 3): A Review of Abdalazeez et al. (2020)

The basics... Understanding the occurrence of extreme coastal runup events — those in which individual waves reach unexpectedly high elevations on the beach — is essential for risk assessment in coastal zones. These events, often referred to as freak runups , are rare and difficult to predict using traditional statistical tools based on average wave conditions. Previous studies have been limited by short experimental records, simplified beach geometries, or assumptions of Gaussian statistics. In their 2020 paper published in Water , Abdalazeez, Didenkulova, Dutykh, and Labart address this knowledge gap by investigating the statistical characteristics of wave runup on a composite beach using long-duration numerical simulations. Their work aims to explore how wave nonlinearity , wave breaking , and spectral bandwidth affect the statistical properties of runup and the likelihood of extreme inundation events. The objective is twofold: (1) to quantify the effect of spectral properti...

Waves Over Lunch: The Theory of Waves Explained on a Napkin (part 1)

  Waves Over Lunch: The Theory of Waves Explained on a Napkin “So what are you working on these days?” “Water waves, mate. The literal ups and downs of life.” “That sounds deep.” “About \( h_0 \) metres deep, actually. Here, pass me a napkin.” Let’s start from first principles: Euler lives here We live in the world of **dimensional physics**, where the apostrophe —yes, the humble ' — reminds us that everything has units: metres, seconds, pressure in Pascals, etc. This is where water waves are born. If you want to describe how water moves, you start with the **Euler equations** (no viscosity, because we assume the water is clean, fast, and slick like a dolphin). Momentum (Euler’s equation): \[ \frac{D \tilde{\mathbf{u}}}{D \tilde{t}} = -\frac{1}{\rho} \nabla \tilde{p} + \mathbf{g} \] Incompressibility: \[ \nabla \cdot \tilde{\mathbf{u}} = 0 \] Here, \( \tilde{\mathbf{u}} = (\tilde{u}, \tilde{w}) \) is the velocity fiel...