Globally, smart meters measuring the water consumption with a high temporal resolution at consumers' households are deployed at an increasing rate. In addition to their use for billing or leak detection purposes, smart meters may provide detailed knowledge of the wastewater inflow to the sewer systems in space and time and open up 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.

在全球范围内，以高时间分辨率测量消费者家庭用水量的智能电表的部署速度越来越快。除了用于计费或泄漏检测目的之外，智能电表还可以在空间和时间上提供污水流入下水道系统的详细信息，并开辟旨在关闭城市水平衡的新型系统分析。在这项研究中，我们首先根据其他独立的配水数据验证智能电表数据。随后，我们使用详细的水动力下水道系统模型将来自近 2,000 名消费者的智能仪表数据与下水道内流量观测联系起来，以模拟干旱天气流量 (DWF) 的废水成分并识别潜在的异常情况。结果表明，使用智能电表数据作为分布式城市排水模型的输入是可行的，因为模型结果的时间动态与下水道内流量观测值匹配良好。此外，该研究表明，下水道内流量观测可能会受到无法识别的不确定性的影响，这使得它们不适合对 DWF 成分进行高级调查，这强调了从独立来源收集数据的必要性。该研究还举例说明了水行业的数字系统集成可能很复杂。然而，克服这些障碍可能会改善离线和实时城市排水管理。该研究表明，下水道内流量观测可能会受到无法识别的不确定性的影响，这使得它们不适合对 DWF 成分进行高级调查，这强调了从独立来源收集数据的必要性。该研究还举例说明了水行业的数字系统集成可能很复杂。然而，克服这些障碍可能会改善离线和实时城市排水管理。该研究表明，下水道内流量观测可能会受到无法识别的不确定性的影响，这使得它们不适合对 DWF 成分进行高级调查，这强调了从独立来源收集数据的必要性。该研究还举例说明了水行业的数字系统集成可能很复杂。然而，克服这些障碍可能会改善离线和实时城市排水管理。