Globally, smart meters measuring the water consumption with a high temporal resolution at the consumers' households are deployed at an increasing rate. In addition to their use for billing or leak detection purposes, smart meters may provide a detailed knowledge of the wastewater inflow to the sewer systems in space and time and open up for new types of system analyses aimed at closing the urban water balance. In this study, we first validate the smart meter data against other, independent water distribution data. Subsequently, we use a detailed hydrodynamic sewer system model to link the smart meter data from almost 2,000 consumers with in-sewer flow observations in order to simulate the wastewater component of the dry weather flow (DWF) and to identify potential anomalies. Results show that it is feasible to use smart meter data as input to a distributed urban drainage model, as the temporal dynamics of the model results and in-sewer flow observations match well. Furthermore, the study suggests that in-sewer flow observations may be subject to unrecognised uncertainties, which make them unsuitable for advanced investigations of the DWF composition, and this underlines the necessity of collecting data from independent sources. The study also exemplifies that digital system integration in the water sector may be complicated. However, overcoming these obstacles may improve both offline and real-time urban drainage management.
Smart meter-simulated wastewater flow is a valuable step towards closing the water balance in urban drainage systems.
Coupling between independent data sources opens up for enhanced anomaly detection; here the discovery of potentially erroneous in-sewer observations.
It can be tedious to gain access to data and models as these may be stored in different silos, but the effort is worthwhile.