A water distribution network (WDN) is an indispensable element of civil infrastructure that provides fresh water for domestic use, industrial development, and fire-fighting. However, in a large and complex network, operation and management (O&M) can be challenging. As a technical initiative to improve O&M efficiency, the paradigm of “divide and conquer” can divide an original WDN into multiple subnetworks. Each subnetwork is controlled by boundary pipes installed with gate valves or flow meters that control the water volume entering and leaving what are known as district metered areas (DMAs). Many approaches to creating DMAs are formulated as two-phase procedures, clustering and sectorizing, and are called water network partitioning (WNP) in general. To assess the benefits and drawbacks of DMAs in a WDN, we provide a comprehensive review of various state-of-the-art approaches, which can be broadly classified as: (1) Clustering algorithms, which focus on defining the optimal configuration of DMAs; and (2) sectorization procedures, which physically decompose the network by selecting pipes for installing flow meters or gate valves. We also provide an overview of emerging problems that need to be studied.
Operation and management of a water distribution network (WDN) by district metered areas (DMAs) bring many benefits for water utilities, particularly regarding water loss control and pressure management. However, the optimal design of DMAs in a WDN is a challenging task. This paper proposes an approach for the optimal design of DMAs in the multiple-criteria decision analysis (MCDA) framework based on the outcome of a coupled model comprising a self-organizing map (SOM) and a community structure algorithm (CSA). First, the clustering principle of the SOM algorithm is applied to construct initial homologous clusters in terms of pressure and elevation. CSA is then coupled to refine the SOM-based initial clusters for the automated creation of multiscale and dynamic DMA layouts. Finally, the criteria for quantifying the performance of each DMA layout solution are assessed in the MCDA framework. Verifying the model on a hypothetical network and an actual WDN proved that it could efficiently create homologous and dynamic DMA layouts capable of adapting to water demand variability.
Water distribution network (WDN) is a human-centered infrastructure that is indispensable for modern cities worldwide. In addition to optimizing the operation and management (O&M) of WDNs under the current state, water utilities should be able to manage uncertain and risk conditions for improving their O&M efficiency. Although the disintegration of large WDNs into permanent district metered areas (DMAs) is an O&M innovation based on water leakage monitoring and pressure management, its network redundancy and reliability diminish under anomalous conditions. Therefore, this study proposed a design and operation procedure to obtain optimal, self-adaptive DMA configurations for various plausible abnormal scenarios. The proposed method is based on multiscenario simulation and optimization, comprising two phases: (1) design of optimal DMA layout for each scenario using the pressure uniformity index to optimize the placement of flow meters and gate valves, and (2) dynamic transformation of the base DMA configuration into an adaptive DMA layout adapting to abnormal conditions and optimization of the locations and statuses of the control valves. Moreover, we used a real-world WDN to demonstrate the effectiveness of the proposed approach, and the obtained results revealed the efficiency and appropriate performance of the adaptive DMA layouts for sustainable adaptation of WDNs under anomalous conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.