Skip to main content
Log in

Probabilistic leak detectability assessment via state estimation in water transport networks

  • Original Paper
  • Published:
Stochastic Environmental Research and Risk Assessment Aims and scope Submit manuscript

Abstract

Leak detectability or leakage awareness refers to the capability of sensing losses from a water supply system. Several methods exist in the technical literature to tackle this problem, but only few address it with a state estimation approach. The aim of this paper is to present a new methodology that enables probabilistic assessment of the extent to which water loss could be detected using state estimation by only analysing a single hydraulic state, i.e. one time period. Significant leaks are sensed by identifying unusually high normalised state estimation residuals, which can be identified based on the largest normalised residual test. More specifically, the probability of detecting leaks is computed here by working with the multivariate distribution among measurements and estimates to take into account the noisy nature of measurements with an analytical approach rather than with sampling experiments, which are time-consuming. The methodology set out herein also provides a procedure to systematically assess the minimum leak that could be detected in different parts of the network for a specific measurement setting and operating condition. The method has been applied to a water transport network case study to show its potential and to highlight the usefulness of such a tool for practitioners. The limitations of such a methodology are also discussed, including its possible use for on-line leak detection strategies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Andersen JH, Powell RS, Marsh JF (2001) Constrained state estimation with applications in water distribution network monitoring. Int J Syst Sci 32(6):807–816

    Article  Google Scholar 

  • Bargiela A (1984) On-line monitoring of water distribution networks. Ph.D. thesis, University of Durham, UK

  • Bargiela A, Hainsworth GD (1989) Pressure and flow uncertainty in water systems. J Water Resour Plan Manag 115(2):212–229

    Article  Google Scholar 

  • Burden RL, Faires JD (1985) Numerical analysis, 3rd edn. PWS Publishers, Boston

    Google Scholar 

  • Cabrera E, Almandoz J, Arregui F, García-Serra J (1999) Auditoría de redes de distribución de agua. Ingeniería del Agua 6(4):387–399

    Article  Google Scholar 

  • Caro E, Conejo AJ, Mínguez R (2011) A sensitivity analysis method to compute the residual covariance matrix. Electr Power Syst Res 81(5):1071–1078

    Article  Google Scholar 

  • Caro E, Conejo AJ, Mínguez R, Zima M, Andersson G (2011) Multiple bad data identification considering measurement dependencies. IEEE Trans Power Syst 26(4):1953–1961

    Article  Google Scholar 

  • Carpentier P, Cohen G (1991) State estimation and leak detection in water distribution networks. Civ Eng Syst 8(4):247–257

    Article  Google Scholar 

  • Coulbeck B (1977) Optimisation and modelling techniques in dynamic control of water distribution systems. Ph.D. thesis, University of Sheffield, UK

  • Diao K, Zhou Y, Rauch W (2013) Automated creation of district metered area boundaries in water distribution systems. J Water Resour Plan Manag 139(2):184–190

    Article  Google Scholar 

  • Díaz S, González J, Mínguez R (2016) Observability analysis in water transport networks: algebraic approach. J Water Resour Plan Manag 142(4):04015,071. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000621

    Article  Google Scholar 

  • Díaz S, González J, Mínguez R (2016) Uncertainty evaluation for constrained state estimation in water distribution systems. J Water Resour Plan Manag 142(12):06016,004. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000718

    Article  Google Scholar 

  • Díaz S, Mínguez R, González J (2016) Stochastic approach to observability analysis in water networks. Ingeniería del Agua 20(3):139–152. https://doi.org/10.4995/Ia.2016.4625

    Article  Google Scholar 

  • Díaz S, Mínguez R, González J (2017) Calibration via multi-period state estimation in water distribution systems. Water Resour Manag 31(5):4801–4819. https://doi.org/10.1007/s11269-017-1779-2

    Article  Google Scholar 

  • Díaz S, Mínguez R, González J (2017) Topological observability analysis in water distribution systems. J Water Resour Plan Manag. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000762

    Article  Google Scholar 

  • Fujiwara O, Khang DB (1990) A two-phase decomposition method for optimal design of looped water distribution networks. Water Resour Res 26(4):539–549

    Article  Google Scholar 

  • Giustolisi O (2010) Considering actual pipe connections in water distribution network analysis. J Hydraul Eng 136(11):889–900

    Article  Google Scholar 

  • Goulter I (1995) Analytical and simulation models for reliability analysis in water distribution systems. In: Cabrera E, Vela AF (eds) Improving efficiency and reliability in water distribution systems. Kluwer Academics, London, pp 235–266

    Chapter  Google Scholar 

  • Gouri RL, Srinivas VV (2017) A fuzzy approach to reliability based design of storm water drain network. Stoch Environ Res Risk Assess 31(5):1091–1106

    Article  Google Scholar 

  • Hasofer AM, Lind NC (1974) Exact and invariant second-moment code format. J Eng Mech Div 100(EM1):111–121

    Google Scholar 

  • Imschoot DPO, Furnass WR, Mounce SR, Boxall JB (2016) Flow-pressure sensor placement optimisation for pipe burst localisation in a water distribution network. In: 14th International computing and control for the water industry (CCWI) conference, Amsterdam, The Netherlands

  • Kang D, Lansey K (2010) Optimal meter placement for water distribution system state estimation. J Water Resour Plan Manag 136(3):337–347

    Article  Google Scholar 

  • Kang DS, Pasha MFK, Lansey K (2009) Approximate methods for uncertainty analysis of water distribution systems. Urban Water J 6(3):233–249

    Article  Google Scholar 

  • Kim SH, Aral MM, Eun Y, Park JJ, Park C (2017) Impact of sensor measurement error on sensor positioning in water quality monitoring networks. Stoch Environ Res Risk Assess 31(3):743–756

    Article  Google Scholar 

  • Melchers RE (1999) Structural reliability analysis and prediction. Wiley, New York

    Google Scholar 

  • Mínguez R (2003) Seguridad, fiabilidad y análisis de sensibilidad en obras de ingeniería civil mediante técnicas de optimización por descomposición. aplicaciones. Ph.D. thesis, University of Cantabria, Spain

  • Mounce SR, Boxall JB, Machell J (2010) Development and verification of an online artificial intelligence system for detection of bursts and other abnormal flows. J Water Resour Plan Manag 136(3):309–318

    Article  Google Scholar 

  • Nagar AK, Powell RS (2000) Observability analysis of water distribution systems under parametric and measurement uncertainty. In: Building partnership, pp 1–10

  • Powell RS (1992) On-line monitoring for operational control of water distribution networks. Ph.D. thesis, University of Durham, UK

  • Puust R, Kapelan Z, Savic DA, Koppel T (2010) A review of methods for leakage management in pipe networks. Urban Water J 7(1):25–45

    Article  Google Scholar 

  • Romano M, Kapelan Z, Savic DA (2014) Automated detection of pipe bursts and other events in water distribution systems. J Water Resour Plan Manag 140(4):457–467

    Article  Google Scholar 

  • Roozbahani A, Zahraie B, Tabesh M (2013) Integrated risk assessment of urban water supply systems from source to tap. Stoch Environ Res Risk Assess 27(4):923–944

    Article  Google Scholar 

  • Savic D, Ferrari G (2014) Design and performance of district metering areas in water distribution systems. Proc Eng 89:1136–1143

    Article  Google Scholar 

  • Savic DA, Kapelan ZS, Jonkergouw PMR (2009) Quo vadis water distribution model calibration? Urban Water J 6(1):3–22

    Article  Google Scholar 

  • Schweppe FC, Handschin EJ (1974) Static state estimation in electric power systems. Proc IEEE 62(7):972–982

    Article  Google Scholar 

  • Schweppe FC, Wildes J (1970) Power system static-state estimation, part I: exact model. IEEE Trans Power Appar Syst PAS–89(1):120–125

    Article  Google Scholar 

  • Vrachimis SG, Eliades DG, Polycarpou MM (2016) Real-time hydraulic interval state estimation for water transport networks: a case study. In: 14th International computing and control for the water industry (CCWI) conference, Amsterdam, The Netherlands

  • Yang T, Shi P, Yu Z, Li Z, Wang X, Zhou X (2016) Probabilistic modeling and uncertainty estimation of urban water consumption under an incompletely informational circumstance. Stoch Environ Res Risk Assess 30(2):725–736

    Article  Google Scholar 

  • Yu G, Powell RS (1994) Optimal design of meter placement in water distribution systems. Int J Syst Sci 25(12):2155–2166

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sarai Díaz.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (docx 108 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Díaz, S., Mínguez, R. & González, J. Probabilistic leak detectability assessment via state estimation in water transport networks. Stoch Environ Res Risk Assess 32, 2111–2128 (2018). https://doi.org/10.1007/s00477-018-1515-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00477-018-1515-3

Keywords

Navigation