Journal of Water and Wastewater Science and Engineering

Journal of Water and Wastewater Science and Engineering

Leak Localization in Water Supply Networks through a Calibration Approach Using the Grasshopper Optimization Algorithm and K-means Clustering Integrat

Document Type : Original Article

Authors
1 Ph.D. Graduate, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.
2 M.Sc. Graduate, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.
3 Associate Professor, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.
Abstract
This paper presents a model-based methodology for leak localization in water distribution networks using the Grasshopper Optimization Algorithm (GOA). The approach calibrates a hydraulic model by minimizing the discrepancy between simulated and field pressure measurements. Two distinct methodologies are proposed: The first method accurately locates leaks by assuming a predetermined number of simultaneous leaks. The second method, designed for scenarios where the number of leaks is unknown, integrates the K-means clustering technique with a Genetic Algorithm (GA) to partition the network into zones. A novel strategy is introduced to determine the optimal number of these zones, with the primary goal of identifying the zone most susceptible to leakage. The proposed methodology was tested on the Poulakis and Balerma benchmark networks under 2000 leakage scenarios. Results indicate that the success rate of the first method decreases as the number of simultaneous leaks increases. Overall, the second method outperforms the first, demonstrating the potential to achieve 99% accuracy in leak localization. The framework outlined in this study shows significant promise for effective leakage management in water supply systems.
Keywords

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Volume 10, Issue 3
Autumn 2025
Pages 29-46

  • Receive Date 14 January 2024
  • Revise Date 28 May 2024
  • Accept Date 14 July 2024