Water distribution system monitoring is currently carried out using advanced real-time control technologies to achieve a higher operational efficiency. Data analysis techniques can be implemented for condition estimation, which are crucial tools for managing, developing, and operating water networks using the monitored flow rate and pressure data at some network pipes and nodes. This work proposes a state estimation methodology that enables one to infer the hydraulic state of the operating speed of pumping systems from these pressure and flow measurements. The presented approach suggests using graph convolutional neural network theory linked to hydraulic models for generating a digital twin of the water system. It is validated on two benchmark hydraulic networks: the Patios-Villa del Rosario, Colombia, and the C-Town networks. The results show that the proposed model effectively predicts the state estimation in the two hydraulic networks used. The results of the evaluation metrics indicate low values of mean squared error and mean absolute error and high values of the coefficient of determination, reflecting high predictive ability and that the prediction results adequately represent the real data.

The core idea behind sectorization of Water Supply Networks (WSNs) is to establish areas partially isolated from the rest of the network to improve operational control. Besides the benefits associated with sectorization, some drawbacks must be taken into consideration by water operators: the economic investment associated with both boundary valves and flowmeters and the reduction of both pressure and system resilience. The target of sectorization is to properly balance these negative and positive aspects. Sectorization methodologies addressing the economic aspects mainly consider costs of valves and flowmeters and of energy, and the benefits in terms of water saving linked to pressure reduction. However, sectorization entails other benefits, such as the reduction of domestic consumption, the reduction of burst frequency and the enhanced capacity to detect and intervene over future leakage events. We implement a development proposed by the International Water Association (IWA) to estimate the aforementioned benefits. Such a development is integrated in a novel sectorization methodology based on a social network community detection algorithm, combined with a genetic algorithm optimization method and Monte Carlo simulation. The methodology is implemented over a fraction of the WSN of Managua city, capital of Nicaragua, generating a net benefit of 25,572 $/year.

Nowadays, optimal sensor placement (OSP) for leakage detection in water distribution networks is a lively field of research, and a challenge for water utilities in terms of network control, management, and maintenance. How many sensors to install and where to install them are crucial decisions to make for those utilities to reach a trade-off between efficiency and economy. In this paper, we address the where-to-install-them part of the OSP through the following elements: nodes’ sensitivity to leakage, uncertainty of information, and redundancy through conditional entropy maximisation. We evaluate relationships among candidate sensors in a network to get a picture of the mutual influence among the nodes. This analysis is performed within a multi-criteria decision-making approach: specifically, a herein proposed variant of DEMATEL, which uses fuzzy logic and builds comparison matrices derived from information obtained through leakage simulations of the network. We apply the proposal first to a toy example to show how the approach works, and then to a real-world case study.

This paper considers the sectorization of a large water distribution network into district metered areas (DMAs) and simultaneously optimizes rehabilitation of the network with new pipes, control valves, and storage tanks. Because available water resources are much lower in the dry season, both the design and operational settings are optimized to satisfy water-demand, water-quality, and pressure constraints, as well as efficiency indices under stringent conditions. Because of the heterogeneity of the multiple decision variables and the complicated way they interact through the multiple objectives (some complimentary and some conflicting), it is not possible to fully automate the simultaneous sectorization, rehabilitation, and operational optimization. Therefore, a multistage approach is used where engineering judgment and network graph simplification and visualization tools are used to find a good feasible solution that serves as a first guess for further optimization of sectors and operational settings, to achieve feasible solutions with better cost of implementation, demand similarity among DMAs, and better pressure uniformity in operations. A multiobjective agent swarm optimization framework is used to iteratively change the sectors at the boundaries. For the final configuration, sequential linear programming is used to find optimal valve and pump settings.

Digitalization in water networks is essential for the future planning of urban development processes in cities and is one of the great challenges faced by small cities regarding water management and the advancement of their infrastructures towards sustainable systems. The main objective of this study is to propose a methodology that allows water utilities with limited budgets to start the path toward the digitalization and construction of the hydraulic model of their water distribution networks. The small city of Pamplona in Colombia was used as a case study. The work explains in detail the challenges faced and the solutions proposed during the digitalization process. The methodology is developed in six phases: an analysis of the cadastre and existing information, the creation and conceptualization of the base hydraulic model, the development of the topography using drones with a limited budget, an analysis of water demand, the development of a digital hydraulic model, and a hydraulic analysis of the system. The product generated is a tool to assess the overall performance of the network and contributes to the advancement of SDG-6, SDG-9, and SDG-11. Finally, this document can be replicated by other cities and companies with similar characteristics (e.g., limited size and budget) and offers an intermediate position on the road to digitalization and the first steps towards the implementation of a digital twin.