Hydraulic Model–Based Methods with Sequential Parameter Tuning for Localizing Leaks in Water Supply Networks

In this paper, two novel hydraulic model–based leak localization methods are presented and investigated. These are the iterative regularized inverse method (IRIM) and the tuned sensitivity matrix method (TSMM). Sequential parameter tuning techniques were developed for both methods with the goal of identifying a practically viable search area that includes the location of the leak. The null space method was implemented in calculating the sensitivity matrix for the TSMM, which enhances computational speed and addresses matrix singularity. New performance metrics were introduced to assess the effectiveness of the leak localization methods. The developed leak localization methods were benchmarked against the original regularized inverse method (RIM) and sensitivity matrix method (SMM) through a numerical case study. The results show that the proposed hydraulic model–based methods with sequential parameter tuning outperform the original methods in all performance metrics.

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Publication Details

Journal
Journal of Water Resources Planning and Management
Published
2025-03-07
DOI
https://doi.org/10.1061/jwrmd5.wreng-6570
Citations
1
Primary Topic
Water Systems and Optimization
Type
article
Field-Weighted Citation Impact
0.95
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article

Hydraulic Model–Based Methods with Sequential Parameter Tuning for Localizing Leaks in Water Supply Networks

Ivan Stoianov, Filippo Pecci, Yuanyang Liu
1 citations
Journal of Water Resources Planning and Management
Water Systems and Optimization
0.95
article

Hydraulic Model–Based Methods with Sequential Parameter Tuning for Localizing Leaks in Water Supply Networks

Ivan Stoianov, Filippo Pecci, Yuanyang Liu
article en
1 citations

Abstract

In this paper, two novel hydraulic model–based leak localization methods are presented and investigated. These are the iterative regularized inverse method (IRIM) and the tuned sensitivity matrix method (TSMM). Sequential parameter tuning techniques were developed for both methods with the goal of identifying a practically viable search area that includes the location of the leak. The null space method was implemented in calculating the sensitivity matrix for the TSMM, which enhances computational speed and addresses matrix singularity. New performance metrics were introduced to assess the effectiveness of the leak localization methods. The developed leak localization methods were benchmarked against the original regularized inverse method (RIM) and sensitivity matrix method (SMM) through a numerical case study. The results show that the proposed hydraulic model–based methods with sequential parameter tuning outperform the original methods in all performance metrics.

Journal of Water Resources Planning and ManagementVol. 151(5)
Imperial College London (GB)
Clean water and sanitation
Openalex Percentile: Top 28%
Water Systems and Optimization
0.95
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