This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.envsoft.2023.10578. This is version 1 of this Preprint.
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The current status of technological advancement does not allow to generate complete flood simulations in real-time for large geographic areas. This hinders warning-systems, interactive planning tools and detailed forecasts and as a consequence the population cannot be quickly or reliably informed of where large masses of water will flow. Our novel method computes flood hazard maps over three orders of magnitude faster than current state-of-the-art methods. It applies physically-based principles of steady-state flow to evade full dynamic aspects of flood simulations. It directly estimates the relevant information for flood hazard, such as peak flow height, velocity and flood arrival time. Performance indicators show similar or exceeding accuracy compared to traditional flow models depending on the type of event and quality of the used elevation data. In our tests, computational costs are reduced on average by a factor 1500. As a result, the developed method provides new perspective for the field of flood hazards, flood risk reduction through new types of early-warning systems, and user-interactive hazard assessment systems. As climate change is expected to aggravate flood hazard, the presented method can bring necessary efficiency to flood simulation and thereby save lives and livelihoods.
Fluid Dynamics, Hydrology
Flow networks, Algorithms, forecasting, floods, algorithms, Forecasting
Published: 2022-12-05 21:12
Last Updated: 2022-12-05 21:12
Conflict of interest statement:
Data Availability (Reason not available):