Monitoring the future behaviour of urban drainage system under climate change: a case study from north-western England

Abstract

Catchments hydrological conditions and responses are anticipated to be affected by the changes in weather patterns, increasing in climate variability and extreme rainfall. Thus, engineers have no choice but to consider climate change in their practices in order to adapt and serve the public interests. This paper is an exploration of the impacts of climate change on the hydrology that underlies the hydraulic design of urban drainage system. Future rainfall has been downscaled from the Global Climate Model (GCM) employing a hybrid Generalised Linear Model (GLM) and Artificial Neural Network (ANN) downscaling techniques under different greenhouse emission scenarios. The output from this model is applied to a combined sewer system of an urban drainage catchment in the Northwest of England during the 21st Century to monitor its future behaviour in winter and summer seasons. Potential future changes in rainfall intensity are expected to alter the level of service of the system, causing more challenges in terms of surface flooding and increase in surcharge level in sewers. The results obtained demonstrate that there is a real chance for these effects to take place and therefore would require more attention from designers and catchment managers.

Keywords

• urban drainage
• climate change
• combined sewer system
• artificial neural network
• storm water
• infoworks cs