Monte Carlo-based sensitivity analysis of the RIM2D hydrodynamic model for the 2021 flood event in western Germany

Abstract. Hydrodynamic models are crucial for flood forecasts and early warnings, particularly in response to events such as the devastating floods in Germany's Ahr region in July 2021. However, several uncertainties can be present in these models stemming from various sources, such as model structure, parameters, and boundary conditions. In this study, we aim to address these uncertainties and enhance the existing hydrodynamic model set up using RIM2D (Rapid Inundation Model 2D), introduced by Apel et al. (2022) for the Ahr region. The goal is to fortify its robustness and reliability for inundation simulations in the area. For this, we employ a large number of Monte Carlo simulations, assessing the effects of various model elements such as floodplain and channel roughness coefficients, as well as terrain resolution, on river dynamics and inundation. Our findings emphasize the critical role of proper parameter assignment in attaining optimal simulation results. The results show that sensitivity to input factors varies depending on the performance metrics used and the output predicted. We demonstrate that to simulate flow formation and water level in the river channel, the roughness parameter of the river channel and the model's resolution are paramount. On the other hand, to simulate flood extent and the distribution of water depth across the domain, even coarser resolutions prove adequate and, due to their reduced computation time, might be better suited for early-warning systems. Furthermore, our findings suggest that the differences observed between finer- and coarser-resolution models may stem from the varying representations of the river channel and buildings within the model. Ultimately, this work provides a guideline for the parameterization of RIM2D and similar physically based fluvial models tailored to the Ahr region, offering valuable insights for future hydrodynamic modeling endeavors in the area.