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.

Notwithstanding recent advances in hydrological modelling, flood simulations remain challenging since many processes must be simulated with high computational efficiency. This paper presents a novel geographic information system (GIS)-oriented platform 3DNet and the associated hydrologic model, with focus on the platform and model features that are relevant for flood simulations. The platform enables hydraulic structures to be incorporated in the hydrologic model, as well as water retention. A limiting capacity can be imposed on every river reach enabling estimation of flooding volume. Runoff is simulated within irregularly shaped units that can be aggregated providing spatial flexibility, i.e. model setup can vary from lumped to semi- and fully-distributed. The model contains many parameters with a physical connotation that can be inferred from catchment characteristics, and it enables simulations with minimum data requirements. All algorithms are implemented in C++ warranting fast computations, while the spatial flexibility can provide additional speed-up. The model is used for a reconstruction of a devastating flood in the Kolubara catchment in May 2014. Despite incomplete and uncertain observations, reasonable results across the catchment are obtained with the plausible parameter estimates. The results suggest that enclosure of the presented features in flood simulation tools would improve simulation accuracy and efficiency.

To optimize the design of a water distribution network (WDN), a large number of possible solutions need to be examined; hence computation efficiency is an important issue. To accelerate the computation, one can use more powerful computers, parallel computing systems with adapted hydraulic solvers, hybrid algorithms, more efficient hydraulic methods or any combination of these techniques. This paper explores the possibility to speed up optimization using variations of the ΔQ method to solve the network hydraulics. First, the ΔQ method was used inside the evaluation function where each tested alternative was hydraulically solved and ranked. Then, the convergence criterion was relived in order to reduce the computation time. Although the accuracy of the obtained hydraulic results was reduced, these were feasible and interesting solutions. Another modification was tested, where the ΔQ method was used just once to solve the hydraulics of the initial network, and the unknown flow corrections were added to the list of other unknown variables subject to optimization. Two case networks were used for testing and were compared to the results obtained using EPANET2. The obtained results have shown that the use of the ΔQ method in hydraulic computations can significantly accelerate the optimization of WDN.

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 $\mathrm{\Delta }Q$ method) represents a viable alternative to GGA, especially when combined with suitably preprocessed network data. The main advantage of the $\mathrm{\Delta }Q$ 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 ($\mathrm{\Delta }Q$ ), is presented in this paper (TRIBAL-$\mathrm{\Delta }Q$ ). The new method aims to exploit this advantage, while overcoming key drawbacks of existing $\mathrm{\Delta }Q$ methods. The performance of the TRIBAL-$\mathrm{\Delta }Q$ -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-$\mathrm{\Delta }Q$ 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.

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.