How Sparse and How Noisy? Systematic Benchmarking of Inverse Physics-Informed Neural Networks for Manning Friction Estimation in Shallow Water Equations

Soheil Radfar

Physics-informed neural networks (PINNs) offer a promising framework for inverse hydrodynamic modeling by combining sparse observations with governing physical constraints. However…