Water availability at the global scale is affected by climate change and contamination processes. The use of probabilistic methods is necessary to provide predictions with an appropriate confidence level, but this is compromised in practice by the high computational cost associated with physically-based models of flow and transport processes in hydraulic systems. On the other hand, predictions are required in the medium-long term to be the basis for the design of proper adaptation and mitigation strategies.
The research project plans to analyze the effect of the different sources of uncertainty (e.g., parametric, design, or scenario) on transport phenomena in natural and artificial water systems by using model reduction techniques, including response surface methods and data-driven approaches. The research activity will be connected with Horizon Europe European projects.