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City-wide climate adaptation for pluvial flood mitigation requires fast and reliable simulation tools. Considering the limitations of hydrodynamic models at city-scale simulations, data driven models have high potential in the development of surrogate tools. This study explores the Google DeepMind WaveNet™ model architecture to map hydrological response of catchments onto hydraulic parameters of t
