Obtaining accurate and deterministic predictions of the risks associated with the presence of contaminants in aquifers is an illusive goal given the presence of heterogeneity in hydrological properties and limited site characterization data. For such reasons, a probabilistic framework is needed to quantify the risks in groundwater systems. In this work, we present a computational toolbox VisU-HydRA that aims to statistically characterize and visualize metrics that are relevant in risk analysis

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... ith the ultimate goal of supporting decision making. The VisU-HydRA computational toolbox is an open-source Python package that can be linked to a series of existing codes such as MODFLOW and PAR2, a GPU-accelerated transport simulator. To illustrate the capabilities of the computational toolbox, we simulate flow and transport in a heterogeneous aquifer within a Monte Carlo framework. The computational toolbox allows to compute the probability of a contaminant's concentration exceeding a safe threshold value as well as the uncertainty associated with the loss of resilience of the aquifer. To ensure consistency and a reproducible workflow, a step-by-step tutorial is provided and available on a GitHub repository.