The Stochastic Hydrogeology and Risk Analysis (s-HydRA) Lab aims to develop novel task-driven, application-oriented integrated models for simulating, optimizing and predicting flow and transport in hydrogeological systems.

The research carried out in our lab focuses in capturing uncertainties and aims to create computationally efficient, theoretically sound and accurate predictions of solute transport behavior in environmental flows.

These models lead to new metrics and graphical visualization tools to evaluate sustainability of groundwater systems and the threat of contamination posed to humans and the environment (e.g. risk analysis). Achieving this goal is a challenging task since hydrogeological properties vary over multiple length scales and its full characterization is unfeasible. Therefore model predictions in hydrogeological systems are subject to uncertainty. Incorporating the heterogeneous patterns of the hydrogeological properties into models is important since variability of such properties leads to complex flow topological features which have a strong influence in solute transport and risk assessment predictions. 

Other research interests include: (1) developing computationally efficient and novel semi-analytical solutions for partial differential equations describing flow and transport in porous media and rivers and (2) improving our fundamental understanding of solute dispersion in porous materials.