SEAMLESS-WAVE is a developing “SoftwarE infrAstructure for Multi-purpose fLood modElling at variouS scaleS” based on "WAVElets" and their versatile properties. The vision behind SEAMLESS-WAVE is to produce an intelligent and holistic modelling framework, which can drastically reduce iterations in building and testing for an optimal model setting, and in controlling the propagation of model-error due to scaling effects and of uncertainty due statistical inputs.

View the Project on GitHub ci1xgk/Fellowship_Webpage

Team and partners

The team involves researchers working at the interface between mathematics, hydraulic modelling and software engineering, which includes:

with contribution from:

We are greatful to the following scientists, who serve on our steering committee meetings to provide scientific guidance:

We are also greatful to many external partners serving on our steering committee meetings to provide practical guidance, inluding: