Journal of Water and Wastewater Science and Engineering

Journal of Water and Wastewater Science and Engineering

Leakage Detection and Localization in Water Distribution Networks Using SMA

Document Type : Original Article

Authors
1 M.Sc. Student, Water and Hydraulic Structures Engineering Department, School of Civil Engineering, University of Science and Technology, Tehran, Iran.
2 Associate Professor, Water and Environmental Engineering Department, School of Civil Engineering, Shahid Beheshti University, Tehran, Iran.
3 Professor, Water and Hydraulic Structures Engineering Department, School of Civil Engineering, University of Science and Technology, Tehran, Iran.
4 Ph.D. Student, Water and Environmental Engineering Department, School of Civil Engineering, Shahid Beheshti University, Tehran, Iran.
Abstract
The occurrence of leakage in water supply systems, in addition to water loss, increases the costs of operation as well as pollution entering the network. Therefore, finding leaks is a crucial challenge for water utilities. In most of the conventional methods, leak detection is costly and time consuming. In this paper, a calibration-optimization method is presented using a new meta-heuristic algorithm (SMA). The proposed method is based on comparing simulated and field data of pressure and flow. This method was implemented for 15 different scenarios of single leak in three water distribution networks. The amount and location of leakage in all scenarios were defined automatically. The results showed that the presented method is able to estimate the location and amount of leakage in the networks with high accuracy and independent of the dimensions and specifications of the networks and also without dependence on the amount and location of the leakage. In the studied networks, the algorithm has reached convergence in less than 90 iterations fast and the leak detection has been performed accurately. Based on the obtained results, leak location in water networks can be found with very high accuracy using the proposed powerful algorithm.
Keywords

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Volume 10, Issue 4
Winter 2026
Pages 29-40

  • Receive Date 08 April 2023
  • Revise Date 25 October 2023
  • Accept Date 28 October 2023