AI/ML for Computational Hydraulics Modeling
AI/ML for Computational Hydraulics Modeling From workflow automation to the promise (and limits) of AI as a hydraulics model
Water resources engineering is increasingly touched by AI and machine learning — but not always in the way people expect. This session covers two distinct roles AI/ML can play in computational hydraulics: workflow automation through agentic tool calling, and AI as a model itself through surrogate modeling and scientific machine learning (SciML).
Prof. Liu will also address a question a lot of practitioners have quietly wondered about: can AI actually replace physics-based solvers like HEC-RAS or SRH-2D — or does it play a fundamentally different role?
Speaker: Prof. Xiaofeng Liu, PhD, PE, Professor of Civil and Environmental Engineering, Penn State University
Hosted by the Digital Water Collective — a practitioner-led community for water engineers building with AI and automation.
Join the community: linkedin.com/groups/21250012