Enhancing Urban Drainage Modelling through Deep-Learning Approach
Urban pluvial flood modelling is challenging due to the complex urban landscape and drainage
processes. Due to the quick response times of urban areas to rainfall, urban flood forecasting
requires rapid models that ideally also have some level of accuracy. This can not be achieved by our
conventional models. Therefore, the main question of this project is: How to provide timely flood
warnings in cities in response to increased flood risks due to climate change? This project will
contribute to this topic with a focus on developing high-resolution, deep learning enhanced urban
drainage models to improve flood forecasting and provide early warnings.