Exploring Techniques to Improve Large-Scale Drainage System Maintenance Scheduling Using a Risk Driven Model

Gully pots are part of the infrastructure of a storm drain system, designed to drain surface water from streets. Any broken or blocked gully pot represents a potential cause of flooding, for instance during periods of intense or prolonged rainfall. Regular cleaning is necessary for gully pots to function effectively. We model gully pot maintenance as a risk-driven problem, and evaluate the maintenance quality of maintenance strategies by considering the risk impact of gully pot failure and failure behaviour. The results suggest investment directions and management policies that potentially improve the efficiency of maintenance. We find that the current maintenance quality is significantly affected by untimely system status information. We propose that low-cost sensor techniques might be able to improve timeliness of status information, and use simulation results to show the behaviour and advantages that might arise in a range of real-world scenarios.