Large-scale application of a statistically rigorous and user unbiased algorithmic approach for reduction of leakages in the water distribution networks

Water leakage reduction in Water Distribution Networks (WDNs) is a crucial task for all water experts and engineers, as the lost water undermines the societal financial and environmental viability. The problem is significantly magnified, if one considers the effects of climate change on the spatial and temporal distribution of the available water resources. In the current work we apply a recently developed algorithmic procedure for WDN partitioning into pressure management areas (see Serafeim et al., 2022) over the highest leakage rate area of the city of Patras, which consists of more than 90 km of pipeline grid and serves approximately 15 000 consumers. The proposed algorithm seeks for minimization of water leakages while maintaining a sufficient level of hydraulic resilience in the network, using a hierarchical clustering approach enriched with topological proximity constrains. The strong points of the suggested approach are that: 1) it uses the original pipeline grid as connectivity matrix, avoiding unrealistic clustering outcomes; 2) it is statistically rigorous and user unbiased, as it is based solely on statistical metrics, and 3) it is easy and fast to implement, requiring minimal processing power. For the purposes of the current work we use flow - pressure data at 1 min temporal resolution during the 8-month high consumption period of the year; i.e. from 01 March 2019 - 30 October 2019. The obtained results are very promising, signifying a 30% reduction in leakage rates. Therefore, due to its easiness, minimal computational requirements, and objective selection criteria, the suggested approach is expected to serve as a very useful tool for water losses management and reduction in WDNs.

Acknowledgements

The research work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the "First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant" (Project Number: 1162).

References

Serafeim, A.V., Kokosalakis, G., Deidda, R., Fourniotis. N. Th. and Langousis A (2022) Combining statistical clustering with hydraulic modeling for resilient reduction of water loses in water distribution networks: Large scale application to the city of Patras in Western Greece (submitted).