Hydrodynamic models have become key tools to assess potential flood risks. Two-dimensional (2D) models based on the shallow-water equations are widely used to determine with high accuracy and resolution, the evolution of flow depths and velocities during floods. However, the high-computational requirements and long computational times have encouraged research to develop more efficient methodologies for predicting the flood propagation on real time.
Our objective is to develop new surrogate models (i.e. metamodeling) to quasi-instantaneously evaluate floods propagation in the Andes foothills. By means a small set of parameters, we define storms for a wide range of meteorological conditions. Using a 2D hydrodynamic model coupled in mass and momentum with the sediment concentration, we compute on high-fidelity the propagation of a flood set. Results are used as a database to perform sophisticated interpolation/regression, and approximate efficiently the flow depth and velocities in critical points during real storms.
This is the first application of surrogate models to evaluate flood propagation in the Andes foothills, improving the efficiency of flood hazard prediction. The model also opens new opportunities to improve early warning systems, helping decision makers to inform citizens, enhancing the reslience of cities near mountain regions.
This work has been supported by CONICYT/FONDAP grant 15110017, and by the Vice Chancellor of Research of the Pontificia Universidad Catolica de Chile, through the Research Internationalization Grant, PUC1566 funded by MINEDUC.
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