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Quantification of water losses (WL) in water distribution networks (WDNs) is a crucial task towards the development of proper strategies to reduce them. Currently, WL estimation methods rely on semi-empirical assumptions and different implementation strategies that increase the uncertainty of the obtained estimates. In this work, we compare the effectiveness and robustness of two widely applied WL estimation approaches found in the international literature: (a) the water balance, or top-down, approach introduced by the International Water Association (IWA), and (b) the bottom-up or minimum night flow (MNF) approach, based on a recently proposed probabilistic MNF estimation method. In doing so, we use users’ consumption and flow-pressure data from the 4 largest pressure management areas (PMAs) of the WDN of the city of Patras (the third largest city in Greece), which consist of more than 200 km of pipeline, cover the entire city center of Patras, and serve approximately 58,000 consumers. The obtained results show that: (a) when MNF estimation is done in a rigorous statistical setting from high resolution flow-pressure timeseries, and (b) there is sufficient understanding of the consumption types and patterns during day and night hours, the two approaches effectively converge, allowing for more reliable estimation of the individual WL components. In addition, when high resolution flow-pressure timeseries are available at the inlets of PMAs, the suggested version of the bottom-up approach with probabilistic estimation of MNF should be preferred as less sensitive, while allowing for confidence interval estimation of the individual components of water losses and development of proper strategies to reduce them.

<p><strong>Abstract</strong></p><p>Quantification of the leakage volume in pressure management areas (PMAs) is a vital task for water agencies’ financial viability. However, currently, there is no rigorous approach for their parametric modeling on the basis of networks’ specific characteristics and inlet/operating pressures. To bridge this gap, the current work focuses on the development of a probabilistic framework for minimum night flow (MNF) estimation in water distribution networks that: 1) parametrizes the MNF as a function of the network’s specific characteristics, and 2) parametrically describes water losses in individual PMAs as a function of the inlet/operating pressures. MNF estimates are obtained using the robust, non-parametric, probabilistic minimum night flow (MNF) estimation methodology developed and validated by Serafeim et al. (2021 and 2022), which allows for confidence interval estimation of the observed MNFs. The effectiveness of the developed model is tested in a large-scale real world application to the water distribution network of the city of Patras in western Greece, which serves approximately 200,000 consumers with more than 700 km of pipeline. The developed framework is validated through flow-pressure tests conducted by the Municipal Enterprise of Water Supply and Sewerage of the City of Patras to 78 PMAs of the network, indicating that the developed framework can be effectively used to improve water loss estimation and flow-pressure management in a morphologically and operationally diverse set of PMAs.</p><p><strong>Acknowledgements</strong></p><p>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).</p><p> </p><p><strong>References</strong></p><p>Serafeim, A.V., Kokosalakis, G., Deidda, R., Karathanasi I. and Langousis A (2021) Probabilistic estimation of minimum night flow in water distribution networks: large-scale application to the city of Patras in western Greece, <em>Stoch. Environ. Res. Risk. Assess.</em>, https://doi.org/10.1007/s00477-021-02042-9</p><p>Serafeim, A.V.; Kokosalakis, G.; Deidda, R.; Karathanasi, I.; Langousis, A. (2022) Probabilistic Minimum Night Flow Estimation in Water Distribution Networks and Comparison with the Water Balance Approach: Large-Scale Application to the City Center of Patras in Western Greece, <em>Water</em>, <em><strong>14</strong></em>, 98, https://doi.org/10.3390/w14010098</p>

<p>Quantification of the Water Losses (WL) components in Water Distribution Networks (WDNs) is a vital task towards their reduction. However, current WL estimation methods rely on semi-empirical approaches with high uncertainty levels, which usually lead to inaccurate estimates of the lost volume. Here, we compare the probabilistic Minimum Night Flow (MNF) estimation method introduced by Serafeim et al. (2021) to the Water Balance components analysis, introduced by the International Water Association (IWA). The strong point of the Serafeim et al. (2021) approach is that it uses statistical metrics to filter out noise effects in the flow timeseries used for MNF estimation, leading to more accurate estimation of the low flows during night hours. The effectiveness of the applied methods is tested via a large-scale, real world application to the 4 largest Pressure Management Areas (PMAs) of the WDN of the city of Patras, the third largest city in Greece (see Serafeim at al., 2022). Although methodologically different, the two approaches lead to very similar results, substantiating the robustness of the Serafeim at al. (2021) approach which allows for reliable confidence interval estimation of the observed Minimum Night Flows, making it particularly suited for engineering applications.</p><p><strong>Acknowledgements</strong></p><p>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).</p><p><strong>References</strong></p><p>Serafeim, A.V., Kokosalakis, G., Deidda, R., Karathanasi I. and Langousis A (2021) Probabilistic estimation of minimum night flow in water distribution networks: large-scale application to the city of Patras in western Greece, <em>Stoch. Environ. Res. Risk. Assess.</em>, https://doi.org/10.1007/s00477-021-02042-9</p><p>Serafeim, A.V.; Kokosalakis, G.; Deidda, R.; Karathanasi, I.; Langousis, A. (2022) Probabilistic Minimum Night Flow Estimation in Water Distribution Networks and Comparison with the Water Balance Approach: Large-Scale Application to the City Center of Patras in Western Greece, <em>Water</em>, <em><strong>14</strong></em>, 98, https://doi.org/10.3390/w14010098</p>