Abstract:There is a growing requirement to generate more precise model simulations and forecasts of flows in urban drainage systems in both offline and online situations. Data assimilation tools are hence needed to make it possible to include system measurements in distributed, physically-based urban drainage models and reduce a number of unavoidable discrepancies between the model and reality. The latter can be achieved partly by inserting measured water levels from the sewer system into the model. This article describes how deterministic updating of model states in this manner affects a simulation, and then evaluates and documents the performance of this particular updating procedure for flow forecasting. A hypothetical case study and synthetic observations are used to illustrate how the Update method works and affects downstream nodes. A real case study in a 544 ha urban catchment furthermore shows that it is possible to improve the 20-min forecast of water levels in an updated node and the three-hour forecast of flow through a downstream node, compared to simulations without updating. Deterministic water level updating produces better forecasts when implemented in large networks with slow flow dynamics and with measurements from upstream basins that contribute significantly to the flow at the forecast location.

Within the last decade, the sewer system in Helsingborg, Sweden has been rehabilitated in many ways along with the reconstruction of the WWTP Oresundsverket in order to obtain a high degree of nitrogen and phosphorus removal. In that context a holistic view has been applied in order to optimise the corrective measures as seen from the effects in the receiving waters. A sewer catchment model has been used to evaluate several operation strategies and the effect of introducing RTC. Recently, a MOUSE ONLINE system was installed. In this phase the objective is to establish a stable communication with the SCADA system and to generate short-term flow forecasts.