Submitted Abstract
Flooding is the top-ranking natural disaster in terms of insured/uninsured losses. The development of reliable methods for flood simulation has greatly improved our ability to predict floods thereby reducing damages and life losses in flood-prone regions. However, there is still a lot of room for improvement. This is addressed in the proposed project SIPFLU, the goal of which it is to improve simulation/prediction of flash floods and to develop a spatial decision-making model (SDMM) for implementing flood protection measures in Luxembourg. In SIPFLU, different approaches for flood simulation and protection will be applied. The project links flood hazard modeling, remote sensing and machine learning. Combining these physical models and data driven methods will result in more reliable hybrid models that can be employed for flood prediction. Five work packages are defined to achieve the research goal: i) add more functionality to a hydrodynamic model code; ii) complement the latter with data driven methods; iii) develop a SDMM model for defining flood protection measures, iv) validate process-based and data-driven methods, and finally v) cross evaluate LIDAR topography with available local super-resolution drone data to assess the ability to incorporate local flood defences into the models.This interdisciplinary project will be carried out in Luxembourg, at RSS-Hydro’s Research and Education Department (RED) in collaboration with the University of Luxembourg, Research Unit in Engineering Sciences (RUES). To promote the scientific aspects of the SIPFLU, there will be continuous collaborations between the research team and (inter)national collaborating institutions including the Luxembourg Institute of Science and Technology (LIST) and the University of Bristol. From a practical application point of view, there will be continuous interactions between the SIPFLU team and the Luxembourg’s water management administration (AGE).The above illustrates that there is very high potential to even go beyond the main research objectives of SIPFLU