Foul sewer model development using geotagged information and smart water meter data

Yueyi Jia, Feifei Zheng, Qingzhou Zhang, Huan Feng Duan, Dragan Savic, Zoran Kapelan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


Hydraulic modeling of a foul sewer system (FSS) enables a better understanding of the behavior of the system and its effective management. However, there is generally a lack of sufficient field measurement data for FSS model development due to the low number of in-situ sensors for data collection. To this end, this study proposes a new method to develop FSS models based on geotagged information and water consumption data from smart water meters that are readily available. Within the proposed method, each sewer manhole is firstly associated with a particular population whose size is estimated from geotagged data. Subsequently, a two-stage optimization framework is developed to identify daily time-series inflows for each manhole based on physical connections between manholes and population as well as sewer sensor observations. Finally, a new uncertainty analysis method is developed by mapping the probability distributions of water consumption captured by smart meters to the stochastic variations of wastewater discharges. Two real-world FSSs are used to demonstrate the effectiveness of the proposed method. Results show that the proposed method can significantly outperform the traditional FSS model development approach in accurately simulating the values and uncertainty ranges of FSS hydraulic variables (manhole water depths and sewer flows). The proposed method is promising due to the easy availability of geotagged information as well as water consumption data from smart water meters in near future.

Original languageEnglish
Article number117594
JournalWater Research
Publication statusPublished - 1 Oct 2021


  • Foul sewer system (FSS)
  • Geotagged data
  • Hydraulic models
  • Smart water meter
  • Uncertainty

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Ecological Modelling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution


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