Abstract
Abstract 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.
Highlights
The dry weather flow (DWF) describes the flow in the sewer system during periods without rain
The current study aimed at using smart meter water consumption data to simulate the wastewater flow and to combine this information with in-sewer observations to detect system and data anomalies, such as infiltration, exfiltration and sensor errors
Smart meter data were validated with data from other independent sources, including data from the waterworks’ outflow, wastewater treatment plants (WWTPs) inflows and households’ annual water consumption audits for a period prior to the installation of the smart meters
Summary
The dry weather flow (DWF) describes the flow in the sewer system during periods without rain. Métadier & Bertrand-Krajewski ( ) analysed DWF data and recognised different flow patterns depending on the weekday and date, and found a relatively large variation within each pattern; Djebbar & Kadota ( ) estimated DWF peaks and average DWF using a neural network model based on the land use and population; and Brito et al ( ) fitted a partial least-squares model to DWF data to estimate the DWF in situations with missing data All of these methods may be used to establish DWF patterns but will not give a real-time picture of the DWF. Spatially distributed real-time DWF information is currently not realistic to obtain using only in-sewer observations
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