Identifying Critical Elements in Sewer Networks Using Graph-Theory

Meijer, Didrik; Bijnen, Marco van; Langeveld, Jeroen; Korving, H.; Post, Johan; Clemens, F.H.L.R.

doi:10.3390/w10020136

Cited by 36 publications

(34 citation statements)

References 24 publications

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“…The GTM was originally developed for sewer networks (Meijer et al, 2018). This study illustrates that the GTM is also applicable to WDNs.…”

Section: Discussionmentioning

confidence: 92%

“…The priority of drinking water pipes is based on 'estimating the discharged water due to transmission mains failure for certain failure modes depending on the pipe material' (Friedl et al, 2012;Fuchs-Hanusch, M€ oderl, Sitzenfrei, Friedl, & Muschalla, 2014). Meijer et al (2018) present the Graph Theory Method (GTM), a methodology to rank elements of sewer systems based on the minimum distance from every manhole to an outflow structure. Graph theory is a mathematical theory and is widely used in, for example, vehicle route problems and optimization of flow problems.…”

Section: Introductionmentioning

confidence: 99%

“…This method takes the effects of failure on the functioning of the system into account and is applicable on the whole (main and capillaries) of the network. This method is an extension of the GTM, developed to determine the criticality of elements in sewer systems (Meijer et al, 2018). In the GTM, the structure of the network is taken as a starting point instead of the results of a multitude of hydraulic calculations.…”

Section: Introductionmentioning

confidence: 99%

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Identifying critical elements in drinking water distribution networks using graph theory

Meijer

Post²,

Hoek

et al. 2020

Structure and Infrastructure Engineering

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Drinking water distribution networks (WDNs) are a crucial infrastructure for life in cities. Deterioration of this ageing, and partly hidden from view, infrastructure can result in losses due to leakage and an increased contamination risk. To counteract this, maintenance strategies are required to maintain the service level. Information on the most critical elements of a WDN, with respect to the functioning of the system as a whole, is essential for prioritising maintenance or rehabilitation activities. In this study a Graph theory based method is developed and applied for efficiently identifying the most critical elements. The main advantage of this method is that it avoids the need to perform elaborate hydrodynamic model calculations. Instead, the structure of the network is the main starting point. The results show that the structure of the network is more decisive than the hydraulics with respect to the criticality of the system's performance as a whole. Results depict that the suggested approach is applicable not only to the main (primary) network, but also to the capillaries which are normally beyond the scope of the traditional methods applied so-far because of the complexity of the networks and the required calculation time.

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“…The GTM was originally developed for sewer networks (Meijer et al, 2018). This study illustrates that the GTM is also applicable to WDNs.…”

Section: Discussionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identifying critical elements in drinking water distribution networks using graph theory

Meijer

Post²,

Hoek

et al. 2020

Structure and Infrastructure Engineering

Self Cite

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“…If the importance of an element for the total network is known, maintenance can be adjusted accordingly instead of maintaining all elements to the same quality level. Methods to determine the importance of individual elements in relation to the total network are described in Arthur et al [35], Arthur and Crow [36], Mair et al [37], Möderl et al [38], Möderl and Rauch [39], and Meijer et al [40]. When the critical elements are known, hydraulic properties of the sewer system at these locations can be monitored to safeguard performance [20].…”

Section: Discussionmentioning

confidence: 99%

Quantitative Impact Assessment of Sewer Condition on Health Risk

Bijnen

Korving

Langeveld

et al. 2018

Water

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Abstract:Due to a variety of contaminants in floodwater, exposure to urban pluvial flooding may pose a health risk to humans. In-sewer defects may cause increased pluvial flooding, possibly increasing health risks. This paper addresses the impact of in-sewer defects on urban pluvial flooding and, subsequently, on infection probabilities for humans. As such, it provides a necessary input for risk-informed sewer maintenance strategies in order to preserve the hydraulic performance of a sewer system. Critical locations in sewer networks can be safeguarded through detecting changes in hydraulic properties of the sewer system, by using monitoring equipment or alternative inspection methods. Two combined sewer systems in The Netherlands with different characteristics are studied. The catchment-wide average infection probability was calculated using Quantitative Microbial Risk Assessment (QMRA) and flooding frequencies from Monte Carlo simulations with a hydrodynamic model. For the studied catchments, it is concluded that the occurrence of flooding is significantly affected by sediment deposits and, consequently, the infection probability as well. The impact of sediment deposits on infection probabilities depends on sewer systems characteristics and varies within the catchment. The results in this paper also demonstrate that further research on the relationship between flood duration and infection probabilities is required.

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“…On the other hand, studies related to graphtheory based analysis of Urban Drainage Networks (UDNs) have focused mainly on the evolution and topological characteristics of both virtual (Ghosh et al 2006;Möderl et al 2009;Urich et al 2010) and real sewer systems (Zischg et al 2017;Krueger et al 2017), and on the application of graph-theory based methodologies for determining critical elements in the network (e.g. Meijer et al 2018). Nevertheless, advantages, limitations and insights on the UDNs' physical characteristics and dynamics that can be derived from the application of complex network analysis are still not fully understood.…”

Section: Introductionmentioning

confidence: 99%

Centrality and shortest path length measures for the functional analysis of urban drainage networks

et al. 2020

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The objective of this research is to evaluate whether complex dynamics of urban drainage networks (UDNs) can be expressed in terms of their structure, i.e. topological characteristics. The present study focuses on the application of topological measures for describing the transport and collection functions of UDNs, using eight subnetworks of the Dresden sewer network as study cases. All UDNs are considered as weighted directed graphs, where edge weights correspond to structural and hydraulic pipe characteristics which affect flow. Transport functions are evaluated in terms of travel time distributions (TTDs), under the hypothesis that frequency distributions of Single Destination Shortest Paths (SDSP) of nodes to the outlet had similar shapes than TTDs. Assessment of this hypothesis is done based on two-sample Kolmogorov-Smirnov tests and comparisons of statistical moments. Collection analysis, i.e. determination of flow paths, is done based on two approaches: (1) using Edge Betweenness Centrality (EBC), and (2) based on the number of SDSP going through an edge connecting a node to the outlet, referred as Paths. Hydrodynamic simulation results are used to validate the outcomes of graph analysis with actual flow behaviors. Results indicate that given an appropriate edge weighting factor, in this case Residence Time, SDSP has the potential to be used as an indicator for flow transport in UDNs. Moreover, both EBC and Paths values were highly correlated to average flows. The first approach, however, proved to be inadequate for estimating flows near the outlet but appropriate for identifying different paths in meshed systems, while the second approach lead to better results in branched networks. Further studies regarding the influence of UDNs layout are needed.

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Identifying Critical Elements in Sewer Networks Using Graph-Theory

Cited by 36 publications

References 24 publications

Identifying critical elements in drinking water distribution networks using graph theory

Identifying critical elements in drinking water distribution networks using graph theory

Quantitative Impact Assessment of Sewer Condition on Health Risk

Centrality and shortest path length measures for the functional analysis of urban drainage networks

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