Pottebaum, JensEbel, MarcelGräßler, Iris2024-08-212024-08-212024https://dl.gi.de/handle/20.500.12116/44347Weather-induced emergencies are characterized by underlying weather phenomena, their evolution in time and space as well as their impact on the environment including people, nature and infrastructure. Typically, simulations are used to consider a variety of potential extreme weather scenarios in preparedness phases. Due to required computing power, duration and high efforts in parameterizing such tools are hardly used within response situations. Enhanced simulation models and surrogate models based on machine learning technologies carry potentials to overcome these challenges. An approach is presented that adopts simulation for the case of flooding events. It considers all phases from demand situation in command posts through advanced parameter space exploration to advanced visualization of simulation results in Augmented Reality. Initial evaluation results are presented, complemented by conclusions on incorporated technologies. The results contribute to future adoption of simulation even in time-critical response situations.enhttp://purl.org/eprint/accessRights/RestrictedAccessText/Workshop Paper10.18420/muc2024-mci-ws13-209