It is known that large hydraulic transients have the potential to cause significant damage to pipeline systems. In addition, the repeated application of these transient pressures has been hypothesised as a potential cause of fatigue failure in WDS. It has also been shown that transients can have impacts on water quality, either through contaminant ingress or by sloughing off biofilms. System operators and managers often ignore transient effects as they underestimate their severity and believe that the character of complex systems reduces their impact. However, literature suggests that the opposite may sometimes be true. The current state of WDS is largely unknown, due to their huge spatial extent and to the large part they are buried. This means that the task of accurately modelling their hydraulic behaviour is extremely difficult, even more so with the increased information requirements for an accurate dynamic model. Uncertainty represents such variability in data and is ubiquitous because of our incomplete knowledge of either the underlying physics or inevitable measurement errors. Hence in order to fully understand any simulation results, and to subsequently get the best representation of the true reality of the system, it is imperative to incorporate uncertainty from the beginning of the simulations, and not as an afterthought. This paper explores the development of a robust modelling methodology to probabilistically predict the propagation of hydraulic transients in a water distribution system.