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Probabilistic framework for the parametric modeling of leakages in water distribution networks: large scale application to the City of Patras in Western Greece

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Abstract

Although the quantification of lost water, due to leakages in pressure management areas (PMAs) is a crucial task for all water agencies’ financial viability, currently there is no rigorous approach for their parametric modeling including the effect of inlet/operating pressures. In this work we develop a probabilistic model for minimum night flow (MNF) estimation in water distribution networks that: (1) parametrizes the MNF as a function of the network’s specific characteristics (topography, length of the pipeline grid, pipe diameters, density of connections etc.), and (2) parametrically describes leakages in individual Pressure Management Areas (PMAs) as a function of the inlet/operating pressures. The effectiveness of the developed model is tested in a large-scale real-world application to 43 PMAs of the water distribution network of the city of Patras in western Greece, which cover an area of approximately 18 km2 with approximately 538 km of pipeline serving more than 150 000 consumers. The strong point of the current methodology is that it allows for confidence interval estimation of the parametrized MNFs, including inlet pressure effects, a strong indicator regarding the level of leakages in PMAs. Thus, the current parametric model can serve as a useful tool for water experts and officials, allowing effective selection of proper leakage reduction technics based on a robust probabilistic approach.

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Abbreviations

atm:

Standard atmosphere

BABE:

Bursts And Background Estimates

CV alt :

Coefficient of variation of the altimetry

CV D :

Coefficient of variation of the diameters of the pipeline

DEYAP:

Municipal Enterprise of Water Supply and Sewerage of the City of Patras

DMA:

District Metered Area

eCDF:

Empirical Cumulative Distribution Function

H :

Inlet point hydraulic head

HDPE:

High Density Polyethylene

IWA:

International Water Association

l/s:

Litters per second

L fit:

Least Squares fit

L tot :

Total length of the pipeline grid

m alt :

PMA mean elevation / altitude

m D :

Mean diameter of the pipeline grid

MLR:

Multiple Linear Regression

MNF:

Minimum Night Flow

MNF/L tot :

Ratio of the MNF to the total length of the pipeline grid

P :

Inlet pressure

PMA:

Pressure Management Area

PVC:

Polyvinyl Chloride

P s , d :

Pressure set point during day

P s , n :

Pressure set point during night

Q d :

Average flow during day

Q mean /L tot :

Mean consumption per km of pipeline grid

Q n :

Average flow during night

R 2 :

Dispersion coefficient

s :

MNF change per unit change of the inlet pressure

s alt :

Standard deviation of PMA elevation / altitude

s D :

Standard deviation of the diameters of the pipeline grid

UARL:

Unavoidable Annual Real Losses

WDN:

Water Distribution Network

z inlet :

PMA inlet point altitude / elevation

ρ con :

Density of connections

ρ nod :

Density of nodes

ρ sum :

Sum of ρcon, ρval and ρnod

ρ val :

Density of valves

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Acknowledgements

The research project was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “1st Call for H.F.R.I. Research Projects to support Faculty Members & Researchers and the procurement of high-cost research equipment grant” (Project Number: 1162). The Authors would like to acknowledge the useful comments and suggestions received by Dr. G. Pegram and one anonymous Reviewer, which significantly improved the presented work.

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Correspondence to Andreas Langousis.

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The Authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Serafeim, A.V., Kokosalakis, G., Deidda, R. et al. Probabilistic framework for the parametric modeling of leakages in water distribution networks: large scale application to the City of Patras in Western Greece. Stoch Environ Res Risk Assess 36, 3617–3637 (2022). https://doi.org/10.1007/s00477-022-02213-2

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  • DOI: https://doi.org/10.1007/s00477-022-02213-2

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