AI-Augmented Immersive Digital Twin and Visual Analytics Framework for Hydrology

This project aims to develop a collaborative digital twin cyber framework (web + mixed reality) to dynamically simulate watershed and hydrological systems in 3D, enhanced with visual analytics and AI-powered intelligent tools. The framework will be designed to generate realistic simulations and visualizations of hydrological systems entailing terrain and elevation data, water resources (i.e., stage, streamflow) and hazards (i.e., NWC flood forecast and map products), infrastructure (e.g., buildings, dams, bridges), and analytical layers (e.g., disaster impact, damage and mitigation assessment, demographics, traffic, weather). The simulations will serve as a digital twin representation of relevant system-level data to aid the public, scientists, officials, decision-makers, and students in acquiring a bird’s-eye view of the current, historical, or forecasted hydrological conditions of a watershed community, as well as to experiment with potential what-if scenarios and event dynamics.