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

Abstract

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.

Combining Statistical Clustering with Hydraulic Modeling for Resilient Reduction of Water Losses in Water Distribution Networks: Large Scale Application Study in the City of Patras in Western Greece

“…In doing so, we use the EPANET solver (see [84,85]) for hydraulic modeling of water distribution and resilience estimation, and hierarchical clustering enriched with topological proximity constraints (see [75]) for the delineation of PMAs. Before proceeding with the implementation of the algorithm, it is essential to estimate the water equilibrium of the analyzed water system (see Section 2 and Table 2) using, e.g., the recently developed probabilistic minimum night flow (MNF) estimation methodology introduced by Serafeim et al [4,20]. Figure 2 presents a flow chart of the developed algorithmic steps that were applied to the four largest PMAs of the water distribution network of the city of Patras (see Figure 1), as detailed in Sections 3.1-3.4 below.…”

“…As outlined in the Introduction, in order to manage and reduce leakages in water distribution networks, one needs to first estimate their volume as a percentage of the System Input Volume (SIV). To do so, we used the results obtained by Serafeim et al [20]. The latter study compared the water loss estimates obtained by applying the water balance (or top-down) approach, and the bottom-up approach based on the MNF estimation method from Serafeim et al [4], to the aforementioned four PMAs (i.e., Boud, Kentro, Panahaiki and Prosfygika).…”

“…Water losses are the sums of apparent losses (i.e., unauthorized consumption and metering errors) and real losses (i.e., leaks and tank overflows) through the pipeline grid [8,9]. As the complete elimination of leakages Water 2022, 14, 3493 2 of 18 is not technically achievable (see [9,10]), one of the most widely used methods for their reduction is that of WDN partitioning into district metered or pressure management areas (DMAs and PMAs, respectively) followed by the decrease of the inlet pressures to the lowest permissible limit that meets the needs of the consumption/demand [10][11][12][13][14][15][16][17][18][19][20][21][22].…”

Leakages in Water Distribution Networks: Estimation Methods, Influential Factors, and Mitigation Strategies—A Comprehensive Review

“…In a recent study, Serafeim et al [72,[110][111][112][113][114][115] studied the minimum night flow (MNF) in pressure management areas (PMAs), revealing that that in PMAs with considerable leakage levels, the MNF estimates increase almost linearly with increasing inlet pressure.…”

Dynamic analysis of non-revenue water in district metered areas under varying water consumption conditions owing to COVID-19

“…There are also other methods to estimate water loss, such as modified minimum night flow (MNF) and component analysis, which include the Burst and Background Estimate (BABE) methods [ 18 , 19 ]. While Serafeim et al [ 20 ] reported that estimated water losses by the MNF and BABE methods converge when rigorous statistical analysis is performed, MNF requires intensive field work, and the estimated night consumption are rarely accurate [ 18 ].…”