This study provides new insights into the potential use of machine learning in hydrological simulations.
Combined Sewer Overflow (CSO) infrastructure are conventionally designed based on historical climate data. Yet, variability in rainfall intensities and patterns caused by climate change have a significant impact on the performance of an urban drainage system. Although rainwater harvesting (RWH) is a potential solution to manage stormwater in urban areas, its benefits in mitigating the climate change impacts on combined sewer networks have not been assessed yet.
