XBeach Modeling with Python: Automating Input Preparation

In this video, we introduce a Python script for automating the preparation of input files for XBeach hydrodynamic models, enabling smoother and more reproducible simulations. 📍 Designed for use in Google Colaboratory – no installation required. ⸻ 🔍 What this video covers: • Setting up your working directory and project structure. • Creating spatial layers for non-erodible zones and Manning's roughness coefficients from GeoJSON data. • Transforming wave time series data (Waves.csv) into XBeach-ready jonswap.txt format. • Configuring params.txt with wave model settings (wavemodel, dtheta/dtheta_s), simulation timeframe (tstart, tstop), and desired output variables (nglobalvar, nmeanvar). • Visualizing the XBeach grid and bathymetry, and exporting the grid as GeoJSON for GIS integration. • Applying sea-level rise scenarios by adjusting water levels in tide.txt. ⸻ 📁 Access the full script here: 📦 GitHub repository: 👉 https://github.com/Alerovere/CoastalH... ⸻ 💬 Subtitles & Accessibility This video includes automatically generated subtitles (English), created and refined with the help of AI tools. ⸻ 👨‍🏫 For educators and students This tutorial is part of the CoastalHydrodynamics project — a collection of tools designed for teaching and research in coastal hydrodynamics and climate adaptation. It was developed by Alessio Rovere at Ca' Foscari University of Venice, with support from ChatGPT by OpenAI, as part of the WARMCOASTS project (funded by the European Research Council - grant agreement n. 802414).📍 Designed for use in Google Colaboratory – no installation required.