Model-based leak localization in small water supply networks

Small leaks in water supply networks often remain undiscovered, resulting in large amounts of lost water. Moreover, small leaks can grow larger over time and may result in pipe bursts, having negative consequences for the surroundings. An automatic leak localization method is required to decrease the search area and hence localize small leaks earlier. In this research, the automatic leak localization method of Quevedo et al. (2011) is validated in DMA Leimuiden (the Netherlands). A prerequisite of the localization method is a detailed consumption distribution of the inflow for the hydraulic model. The goal of this research is to study the need for a detailed consumption distribution model in a DMA with a small MNF compared to the leak size (MNF: 4.5 m3/h, leak size: 5.2 m3/h, 7.5 m3/h and 15 m3/h). The leak localization method was applied to eight artificial leaks that lasted 15 minutes and measurements of one day of a real leak (5.2 m3/h). Leak localization results of the artificial leaks showed that there was no influence of the consumption distribution during the night. The leak localization method performs the same with both consumption models in case of low flow conditions and when leak localization results of the real leak for a whole day are combined. The performance of the leak localization method depends on the location of the leak. For some leak locations more flow in the system is required to create detectable head loss at the sensor locations. Uncertainties in the model cause larger pressure variations with higher flow conditions and a more detailed consumption distribution model must be used when there is more flow (morning peak). Too short measurement periods make the leak localization result sensitive to unexpected consumption inside the DMA. An accumulation of hourly results of a whole day makes the method more robust and gave satisfying performance irrespective of the used consumption models and with only 6 pressure sensors inside the network.