In the HiDALGO2 project, we need to address the pressing question of how well our models and simulations perform by openly discussing the assumptions, approximations, and limitations that impact the credibility of our simulations. For that purpose, we apply an uncertainty quantification (UQ) framework, specifically focusing on its application to environmental challenges that require computational-fluid dynamics (CFD) simulations. Here, UQ evaluates the influence of uncertainties in model inputs on computational results. However, to achieve statistically significant outcomes, UQ studies require a significant number of simulations, a challenge we aim to overcome using novel techniques such as surrogate modeling. We are exploring the integration of these UQ techniques into CFD simulations. Our ultimate goal is to enhance the overall runtime of these simulations, e.g. by optimizing surrogate modeling techniques, striving for more accurate and reliable results.