SFINCS-LSG dataset, model files, python environment and scripts

Scripts supporting the manuscript Eilander, D., de Goede, R., Leijnse, T., & Fraehr, N. (n.d.). Stress-testing a physics-guided surrogate model for compound flood dynamics across hydrodynamic regimes. This study evaluates a hybrid physics guided SFINCS–LSG surrogate model, which combines low resolution SFINCS simulations with Empirical Orthogonal Function (EOF) decomposition and Sparse Gaussian Process learning to emulate high resolution flood dynamics. Two contrasting case studies, Charleston, South Carolina, USA, and Brisbane, Australia, are used to assess model performance under diverse compound flood conditions. See readme.md file for a detailed description, folder stucture and getting started.