Sectorization of a water distribution network (WDN) into district meter areas (DMAs) is considered a key strategy for an efficient management of WDNs. Typically, it involves a two-stage procedure: a clustering stage, in which the division of the WDN into clusters is performed, and a dividing stage, which involves the placement of valves and flow meters on the cluster’s boundary pipes to define the DMAs. While recently published methods attempt to enhance both the clustering and dividing stages, they fail to provide decision-making flexibility. They also neglect to consider the presence of existing valves in the WDN, which can significantly affect the evaluated implementation cost, often considered the primary decision-driving factor. This paper presents improvements to the previously introduced DeNSE method for sectorization of WDNs, aiming to address these deficiencies. The methodology consists of a clustering stage, based on the network uniformity index, and a dividing stage, in which the originally used heuristic procedure is replaced with Genetic Algorithm (GA) optimization, minimizing implementation cost. Consideration of existing valves in WDN and criteria for water supply security are also included in the dividing stage to offer a better estimate of implementation costs and post-sectorized operational efficiency of the WDN. Finally, GIS visualization is implemented, and a hydraulic model of the sectorized WDN (EPANET file) is generated, providing practitioners with valuable insights and decision-making flexibility. The methodology is tested on a part of the Amsterdam WDN in the Netherlands, serving as a pilot for methodology evaluation. A range of feasible sectorization solutions is generated and compared based on implementation cost and three performance indicators (PIs). The paper provides an in-depth discussion on the selection of preferable sectorization solution. The reported results demonstrate the method’s efficiency in optimizing sectorization solutions with minimum implementation cost whilst preserving the WDN operational efficiency and meeting the local design criteria.

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Sectorization of a water distribution network (WDN) into district metered areas (DMAs) is a proven solution for proactive leakage control. Traditionally, WDN sectorization is conducted by local experts using a trial-and-error approach, often resulting in the identification of arbitrary solutions. Some recently published methods try to improve WDN sectorization by automating the process, especially by using optimization. Various sectorization criteria, constraints, and limitations are introduced, which often fail to consider the issues faced by poorly managed WDNs such as limited funds and shortage of water balance data. These methods also have poor computational efficiency imposed by optimization methods used. This paper presents a new distribution network sectorization method (DeNSE), that overcomes these deficiencies. This method is based on a heuristic procedure in which WDN sectorization is driven by efficient tracking of water balance data and determining the lowest cost investment needed to maintain the same level of operational performance. The above-mentioned set of criteria is particularly well suited for initial sectorization of WDNs when major uncertainties in water balance data often lead to poor management decisions. The DeNSE method is validated and benchmarked against other sectorization methodologies in a case study of a large, real-world WDN. The results show that DeNSE can identify sound, realistic sectorization solutions that are in some respects better than corresponding solutions reported in the literature. DeNSE also enables high computational efficiency, ensuring its applicability to real-world WDNs.@en

Different methods have been developed in the past to formulate and solve steady-state hydraulics of a water distribution system (WDS). The most widely used method nowadays is probably the global gradient algorithm (GGA). The loop-flow method (also known as the ΔQ method) represents a viable alternative to GGA, especially when combined with suitably preprocessed network data. The main advantage of the ΔQ method over the GGA is in the smaller number of unknowns to solve for, which is coming from the fact that real WDSs typically have far less loops than nodes. A new loop-flow-type method, relying on the novel triangulation based loops identification algorithm (TRIBAL) that was implemented in the corresponding new hydraulic solver (ΔQ), is presented in this paper (TRIBAL-ΔQ). The new method aims to exploit this advantage, while overcoming key drawbacks of existing ΔQ methods. The performance of the TRIBAL- ΔQ-based solver is compared with the GGA-based solver on four large real networks of different complexity and topology. The results obtained demonstrate that, despite requiring an increased number of iterations to converge, the TRIBAL-ΔQ method-based solver is substantially computationally faster, has slightly better numerical stability, and is equally accurate in making predictions when compared with the GGA-based hydraulic solver.

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