Qiuhua Liang

My research is focused on computational hydraulics and applications in disaster risk reduction. I have developed high-performance mathematical and numerical models to facilitate sustainable management of hydro systems interrupted by natural hazards such as floods, tsunamis, debris flows, and landslides.

Numerical methods: Godunov-type finite volume scheme, discontinuous Galerkin methods (DG methods), smooth particle hydrodynamics, particle-tracking methods, coupled hydrodynamic model and discrete element method for floating debris and mass flows, high-performance computing
Modelling the dynamic processes of extreme natural hazards to support risk assessment and damage estimation
Nature-based solutions for flood risk mitigation and resilience
Real-time flood forecasting
Crowd-sourced data acquisition, agent-based modelling and coupled human and natural systems modelling
Application of AI / deep machine learning in hydro informatics