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Water distribution networks (WDNs) are an important critical infrastructure, but they are increasingly at risk from contamination (WHO, 2014). The causes can be several: chlorination equipment malfunctioning, low pressure, contaminant intrusion in water tank, accidental cross-connection between drinking-water and non-drinking-water, etc... To limit potential threat to public health, it is advisable to install a network of sensors that can monitor water quality in real time and provide information about potential contamination risks. With the proliferation of IoT technologies and low-cost sensors capable of monitoring water quality parameters, it is now possible to implement a real-time monitoring network by overcoming the difficulties associated with biochemical analyses of water samples in a laboratory. Despite the modern technologies, the placement of sensors in the water network is still an open task for researchers. The main sensor placement methodologies use optimization techniques to minimize or maximize either single- or multi-objective functions (Ostfeld et al., 2008), but they require a calibrated model of the network, which is not always available because the calibration process is expensive and time-consuming.Recently, a novel approach (Santonastaso et al., 2021) based on the use of the topological centrality metric, which does not require hydraulic information and simulations, has been proposed, showing good effectiveness and easy applicability by water utilities to define locations for quality sensors, owing to its simplicity compared to optimization-based approaches.In this work, different weights such as the length of pipes, the diameter and the water demand were used to improve the performance of the adopted topological approach, as well as to evaluate the impact of the weight, used to compute centrality metrics, in relation to the most used objective functions: number of people exposed to the contaminant; number of detected contamination events; length of contaminated pipes; amount of contaminant consumed by users; detection time of contamination. ReferencesWorld Health Organization. (‎2014)‎. Water safety in distribution systems. World Health Organization. https://apps.who.int/iris/handle/10665/204422Ostfeld A, Uber JG, Salomons E, Berry JW, Hart WE, Phillips CA, Watson JP, Dorini G, Jonkergouw P, Kapelan Z, di Pierro F, Khu ST, Savic D, Eliades D, Polycarpou M, Ghimire SR, Barkdoll BD, Gueli R, Huang JJ, McBean EA, James W, Krause A, Leskovec J, Isovitsch S, Xu J, Guestrin C, VanBriesen J, Small M, Fischbeck P, Preis A, Propato M, Piller O, Trachtman GB, Wu ZY, Walski T (2008) The battle of the water sensor networks (BWSN): a design challenge for engineers and algorithms. J Water Resour Plan Manag 134:556–568. https://doi.org/10.1061/(ASCE)0733-9496(2008)134:6(556)Santonastaso, G., Di Nardo, A., Creaco, E. et al. Comparison of topological, empirical and optimization-based approaches for locating quality detection points in water distribution networks. Environ Sci Pollut Res 28, 33844–33853 (2021). https://doi.org/10.1007/s11356-020-10519-3

This paper presents the head-drop method for the modeling of pressure regulation devices in the steady-state simulation of water distribution networks (WDNs). The method is based on addition of device-associated head drops to the source term of pipe energy-balance equations. Head drops and device statuses (active, open, and closed) are updated during the iterations of WDN resolution based on the values of pipe water discharge and of head at pipe end nodes. The proposed method is easily implementable in any WDN resolution algorithm for both local and remote regulation of pressure reducing valves (PRVs) and variable speed pumps (VSPs). The application to four case studies proved the efficiency and robustness of the method, which will be implemented in the hydraulic engine of Smart Water Network Protection and Partitioning (SWANP) software.

Permanent partitioning represents one of the more effective approaches for an innovative management of water distribution networks (WDNs) because it allows simplification of the network control defining small subsystem defined as a district meter area (DMA) in which it is simpler to compute water balance, to achieve pressure management and to check water quality. The design of permanent water network partitioning (WNP) is very difficult to apply to large water networks using traditional approaches based on empirical considerations and trial and errors techniques. Recently, the authors developed the software SWANP that allows definition automatically of the number and dimension and shape of a DMA using different innovative heuristic optimization procedures. In this paper a novel release 3.5 of SWANP is presented that implements novel algorithms, based on social network theory for the clustering phase and a genetic multiobjective for the dividing phase, to automatically design DMAs of a real, large water network in Alcalá de Henares, Spain.

The reliability of water distribution networks (WDN) can be defined as the ability of the system to meet water demands under both normal and abnormal conditions (Bao and Mays, 1990). The measure of reliability is influenced by many factors: possible failure of one or more components, unusual high demand, connectivity of the network, poor water quality, etc. Although reliability of WDN was originally defined by Goulter (1987) and Walters (1988), measuring reliability is an open challenge for researchers. Consequently, there is no established measure of WDN reliability.In recent years, many studies have attempted to mathematically define the reliability of water distribution networks and several synthetic indices are provided as proxy of reliability measures. The objective of this paper is to investigate the suitability of two of these metrics: one based on surplus of power head and other on Shannon’s informational entropy for the assessment of reliability of partitioned water distribution networks (WDNs). The creation of permanent DMAs involves permanently an alteration of the WDN by closing multiple lines at the same time, and, therefore, it is a more severe test than those commonly used in the scientific literature where a little or no disruption occurs to the operation of the WDN (e.g., segment isolation or demand amplification). In addition, the two metrics were compared with other known indicators of hydraulic performance to determine which of them is better suited to evaluate the reliability of water network partitioning. For this purpose, a medium-sized water distribution network in South of Italy was used as case study and the hydraulic simulations were performed with a pressure-driven approach using EPANET2.2 software. ReferencesBao, Y., Mays, L.W. (1990). "Model for water distribution system reliability", J. Hydrual. Eng., 116, 1119-1137Greco, R., Di Nardo, A., Santonastaso, G.F (2012). "Resilience and entropy as indices of robustness of water distribution networks", J. Hydroinformatics, 14 (3), 761–771.Gouher, I.C. (1987). "Current and future use of system analysis in water distribution network design", Civ. Engrg. Sys., 4(4), 175-184.Walters, G. (1988). "Optimal design of pipe networks: a review." Proc.,1st Int. Conf. on Compo and Water Resour., Vol. 2, Computational Mechanics Publications, Southampton, U.K., 21-31.

This paper presents a novel algorithm with improved convergence and robustness for the pressure-driven modeling of water distribution networks (WDNs), to be implemented as hydraulic engine in the fourth release of the SWANP version 4.0 software. The innovative approach is based on increasing the order of convergence, which is quadratic for algorithms obtained from the Newton Raphson linearization of the equations for WDN resolution. As an example, the cubic order of convergence is obtained by evaluating system matrices at the generic iteration in a more refined way to account for the curvature of the hyperplane associated with the system in the direction of the Newton Raphson step. To show the benefits of the methodology, a third-order algorithm is constructed and compared with a traditional second-order. Both algorithms are based on the direct pressure-driven formulation expressing outflows as a function of service pressure and are equipped with the dampening of the Newton Raphson step. Applications on two case studies of different size, in which challenging pressure-driven conditions are created through demand amplification and segment isolation scenarios, prove that the methodology always reduces the total number of iterations required for convergence and the application of the step dampening. Overall, the results also show that the more stable convergence behavior is accompanied by an appreciable reduction in computation times. Further analyses proved that the third-order algorithm has similar convergence properties to algorithms based on the inverse pressure-driven formulation recently proposed in the scientific literature and can therefore be considered as a valid alternative to these algorithms.

Water distribution systems (WDSs) today are expected to continuously provide clean water while meeting users demand, and pressure requirements. To accomplish these targets is not an easy task due to extreme weather events, operative accidents and intentional attacks; as well as the progressive deterioration of the WDS assets. Therefore, water utilities should be ready to deal with a range of disruption scenarios such as abrupt variations on the water demand e.g. caused by pipe bursts or topological changes in the water network. This paper presents a novel methodology to automatically split a WDS into self-adapting district metered areas (DMAs) of different size in response to such scenarios. Complex Networks Theory is proposed for creating novel multiscale network layouts for a WDS. This makes it possible to automatically define the dynamic partitioning of WDSs to support further DMA aggregation / disaggregation operations. A real, already partitioned, water utility network shows the usefulness of an adaptive partitioning when the network is affected by an abnormal increase of the peak demand of up to 15%. The dynamic DMA reuses the assets of the static partitioning and, in this case, up to the 82% of resilience is restored using 94% of the assets already installed. The results also show that the overall computational and economic management costs are reduced compared to the static DMA partition while the hydraulic performance of the WDS is simultaneously preserved.

Rapid human-induced changes, such as climate change, population growth and rapid urbanization, are putting enormous stress on water resources. An accurate estimate of available water resources is a prerequisite for sustainable water resources planning and management. For gauged basins, historical records of hydrological observations are available, but for ungauged basins, the assessment of water availability is a challenging task. Therefore, the major focus of studies in ungauged basins is the development of appropriate tools that can accurately quantify hydrologic responses under various land use and climatic conditions. The reduction of the number of unknown parameters to be estimated is a key aspect in the development of hydrological models for ungauged basins.This work is part of these issues and proposes an approach to reduce the complexity of hydrological models that include substantial uncertainties about the input data, initial and boundary conditions, model structure and parameters, owing to lack of data (i.e. for ungauged basins) and poor knowledge of hydrological response mechanisms. The case study of a basin of the District of Licola, located in the territory of the municipality of Giugliano, a city near Naples (southern Italy) is analyzed. Originally devoted to agriculture and grazing, it has been affected in the last decades by intense urbanization, which caused an increase in the impermeability of the soil cover. The increase in residential, commercial and production buildings has changed the functioning of the drainage network canals, compared to the original conditions, causing an increase in the frequency of flooding in the area. The semi-distributed hydrological model SWMM is adopted, which allows the subdivision of the basin in sub-basins according to land use and soil data.Sensitivity Analysis (SA) is an effective approach to model simplification, providing an assessment of how much each input / parameter contributes to the output uncertainty. In general, SA is an essential part of model development, reducing uncertainties that have negative effects on the accuracy and reliability of simulated results. Specifically, in this study the SA is carried out with a method based on the decomposition of the variance of the peak flow and runoff volume, to quantitatively evaluate the contributions of single uncertain inputs/parameters that characterize the surface runoff with respect to different rainfall events, for both pervious and impervious areas. To this aim, the Fourier Amplitude Sensitivity Test (FAST) is implemented. This method allows quantifying not only the “main effect” of variance, but also provides the Total Sensitivity Indices (TSI), defined as the sum of all the sensitivity indices for each parameter (including the effects of the interaction with other uncertain parameters).The research objectives aims at: (i) increased understanding of the relationships between input and output variables in a complex hydrological system; (ii) reduction of model uncertainty, through the identification of input parameters mostly contributing to output variability and should therefore be the focus of sensitivity analysis; (iii) model simplification, fixing the values of input parameters that have little effect on the output, and identifying and removing redundant parts of the model structure.

This Editorial presents the paper collection of the Special Issue (SI) on Smart Urban Water Networks [...]

Over the last three decades, the increasing development of smart water meter trials and the rise of demand management has fostered the collection of water demand data at increasingly higher spatial and temporal resolutions. Counting these new datasets and more traditional aggregate water demand data, the literature is rich with heterogeneous urban water demand datasets. They are characterized by heterogeneous spatial scales—from urban districts, to households or individual water fixtures—and temporal sampling frequencies—from seasonal/monthly up to sub-daily (minutes or seconds). Motivated by the need of tracking the existing datasets in this rapidly evolving field of investigation, this manuscript is the first comprehensive review effort of the state-of-the-art urban water demand datasets. This paper contributes a review of 92 water demand datasets and 120 related peer-review publications compiled in the last 45 years. The reviewed datasets are classified and analyzed according to the following criteria: spatial scale, temporal scale, and dataset accessibility. This research effort builds an updated catalog of the existing water demand datasets to facilitate future research efforts end encourage the publication of open-access datasets in water demand modelling and management research.

Current and future smart cities are moving towards the zero-net energy use concept. To this end, the built environment should also be designed for efficient energy use and play a significant role in the production of such energy. At present, this is achieved by focusing on energy demand in buildings and to the renewable trade-off related to smart power grids. However, urban water distribution systems constantly carry an excess of hydraulic energy that can potentially be recovered to produce electricity. This paper presents a comprehensive review of current strategies for energy production by reviewing the state-of-the-art of smart water systems. New technologies (such as cyber-physical systems, digital twins, blockchain) and new methodologies (network dynamics, geometric deep learning) associated with digital water are also discussed. The paper then focuses on modelling the installation of both micro-turbines and pumps as turbines, instead of/together with pressure reduction valves, to further demonstrate the energy-recovery methods which will enable water network partitioning into district metered areas. The associated benefits on leakage control, as a source of energy, and for contributing to overall network resilience are also highlighted. The paper concludes by presenting future research directions. Notably, digital water is proposed as the main research and operational direction for current and future Water Distribution Systems (WDS) and as a holistic, data-centred framework for the operation and management of water networks.

Water network partitioning (WNP) represents an efficient strategy to improve management of water distribution networks, reduce water losses and monitor water quality. It consists in physically dividing of a water distribution network (WDN) into districted metered areas (DMAs) through the placement of flow meters and isolation valves on boundary pipes between DMAs. In this paper, a novel methodology for designing DMAs is proposed that provides districts with quite similar node elevations and minimizes the number of boundary pipes in order to simplify pressure management and reduce the number of devices to place into the network.

The positioning of quality detection points as well as the frequency of sampling is a crucial aspect for the implementation of Water Safety Plans (WSPs), which have been proposed worldwide to ensure water quality and to minimize the risk from contamination in water distribution networks (WDNs). In this regard, some international legislations and best practices about quality of drinking water suggest very fine sampling frequencies, but they do not specify where the detection points should be located in a WDN. In this paper, three different approaches, based on empiricism, optimization and topology, respectively, were applied to locate detection quality points in a WDN. The comparison highlighted that empirical approach commonly adopted by water utility practitioners is unsatisfactory. The optimization-based approach, although performing significantly better, is difficult to apply, since it requires a calibrated hydraulic model. The topological approach, based on the use of the betweenness centrality and not requiring any hydraulic information and simulation, proves to be effective, and it can be easily adopted by water utilities to identify the location for quality detection points, due to its simplicity compared with the optimization-based approach.

Pump-and-treat technology is among the most used technologies for groundwater remediation. While conventional, vertical wells (VRWs) are well-known and used from long time, horizontal wells (HRWs) have been explored for remediation technologies only in last few decades. HRWs have shown to outperform vertical wells in terms of versatility, productivity and clean-up times under certain conditions. In this paper, the efficacy of an innovative pump-and-treat (P&T) configuration for groundwater remediation obtained by adopting either VRWs or HRWs technology is comparatively tested. A 3D transient finite element model of an unconfined aquifer containing a hexavalent chromium (Cr(VI)) contamination plume is considered to compare a single horizontal well configuration vs a range of spatially-optimised arrays containing vertical wells. A sensitivity analysis aimed at finding the best configuration to minimise the remediation time and the related cost is carried out by comparing different well diameters, D, pumping rates, Q, and position of wells. A comparative cost analysis demonstrates that, for the examined case-study, a single HRW achieves the clean-up goals in the same time span as for a greater number of vertical wells, but at higher price due to the excavation costs.

Disaggregation techniques are useful to separate data aggregated into single end-use categories, and they are becoming of great interest in the water sector due to the technological innovation in metering systems that has made water consumption data available. However, in order to apply disaggregation methods, high-resolution data at the end-use level are needed. To face this problem, the paper presents an Internet of Things water end-use monitoring system that is able to read real-time end-use consumption in a residential apartment equipped as a pilot site. Moreover, the paper describes preliminary consideration of the dataset and the potentiality of end-use consumption measures to apply disaggregation techniques and profile users’ behaviors.

The optimal and sustainable management of water distribution systems still represent an arduous task. In many instances, especially in aging water net-works, pressure management is imperative for reducing breakages and leakages. Therefore, optimal District Metered Areas represent an effective solution to decreasing the overall energy input without performance compromise. Within this context, this paper proposes a novel adaptive management framework for water distribution systems by reconfiguring the original network layout into (dynamic) district metered areas. It utilises a multiscale clustering algorithm to schedule district aggregation/desegregation, whilst delivering energy and supply management goals. The resulting framework was tested in a water utility network for the simultaneously production of energy during the day (by means of the installation of micro-hydropower systems) and for the reduction of water leakage during the night. From computational viewpoint, this was found to significantly reduce the time and complexity during the clustering and the dividing phase. In addition, in this case, a recovered energy potential of 19 MWh per year and leakage reduction of up to 16% was found. The addition of pump-as-turbines was also found to reduce investment and maintenance costs, giving improved reliability to the monitoring stations. The financial analyses to define the optimal period in which to invest also showed the economic feasibility of the proposed solution, which assures, in the analysed case study, a positive annual net income in just five years. This study demonstrates that the combined optimisation, energy recovery and creation of optimized multiple-task district stations lead to an efficient, resilient, sustainable, and low-cost management strategy for water distribution networks.

International audience; The paper presents the results of the Battle of Postdisaster Response and Restoration (BPDRR) presented in a special session at the first International water distribution systems analysis & computing and control in the water industry (WDSA/CCWI) Joint Conference, held in Kingston, Ontario, Canada, in July 2018. The BPDRR problem focused on how to respond and restore water service after the occurrence of five earthquake scenarios that cause structural damage in a water distribution system. Participants were required to propose a prioritization schedule to fix the damages of each scenario while following restrictions on visibility/nonvisibility of damages. Each team/approach was evaluated against six performance criteria: (1)time without supply for hospital/firefighting, (2)rapidity of recovery, (3)resilience loss, (4)average time of no user service, (5)number of users without service for eight consecutive hours, and (6)water loss. Three main types of approaches were identified from the submissions: (1)general-purpose metaheuristic algorithms, (2)greedy algorithms, and (3)ranking-based prioritizations. All three approaches showed potential to solve the challenge efficiently. The results of the participants showed that for this network, the impact of a large-diameter pipe failure on the network is more significant than several smaller pipes failures. The location of isolation valves and the size of hydraulic segments influenced the resilience of the system during emergencies. On average, the interruptions to water supply (hospitals and firefighting) varied considerably among solutions and emergency scenarios, highlighting the importance of private water storage for emergencies. The effects of damages and repair work were more noticeable during the peak demand periods (morning and noontime) than during the low-flow periods; and tank storage helped to preserve functionality of the network in the first few hours after a simulated event.

[EN] Water temperature is often monitored at water sources and treatment works; however, there is limited monitoring of the water temperature in the drinking water distribution system (DWDS), despite a known impact on physical, chemical and microbial reactions which impact water quality. A key parameter influencing drinking water temperature is soil temperature, which is influenced by the urban heat island effects. This paper provides critique and comprehensive summary of the current knowledge, policies and challenges regarding drinking water temperature research and presents the findings from a survey of international stakeholders. Knowledge gaps as well as challenges and opportunities for monitoring and research are identified. The conclusion of the study is that temperature in the DWDS is an emerging concern in various countries regardless of the water source and treatment, climate conditions, or network characteristics such as topology, pipe material or diameter. More research is needed, especially to determine (i) the effect of higher temperatures, (ii) a legislative limit on temperature and (iii) measures to comply with this limit., This research was partially funded by the European project WATQUAL https://www.she ffield.ac.uk/civil/wat-qual and partly by the joint research program (BTO) of the Dutch Drinking Water Companies.

Flushing plans within a water distribution network (WDN) provide a tool for improving disinfectant residuals and removing stagnant water. The problem of low disinfectant residuals occurs in areas of a WDN such as dead-end nodes, in which low flow conditions and long residence times lead to excessive decay of the disinfectant upstream from users. Here, a methodology is presented to maintain adequate disinfectant residuals in WDNs that have numerous dead-end nodes. The slight increase in nodal outflows at these sites, which can be obtained through the opening of a blow-off at the hydrant site, can help in tackling this problem. The methodology is based on the combined use of optimization and of flow routing/water quality modelling. The concentration of disinfectant at the source(s) and the values of nodal emitter coefficients at the critical dead-end nodes are the decisional variables to be optimized. Two objective functions are considered in the optimization, namely the total volume of water delivered in the network and the total mass of disinfectant injected into the network. The effectiveness of the methodology is proven on a real WDN, yielding an insight into the economic feasibility of the solution.

The paper presents a hardware/software platform that integrates IoT technologies for deploying a smart water network in a domestic environment. Low cost sensors and edge nodes have been deployed in a real pilot for monitoring water fixture use. A data collection platform, which can run in the Fog or in Cloud, allows for processing of raw data and monitoring. It makes available raw and intermediate data to offload the computation of complex Big Data analytic. The paper presents preliminary results according to the data available after two months of operation.

This paper proposes a combined management strategy for monitoring water distribution networks (WDNs). This strategy is based on the application of water network partitioning (WNP) for the creation of district metered areas (DMAs) and on the installation of sensors for water quality monitoring. The proposed methodology was tested on a real WDN, showing that boundary pipes, at which flowmeters are installed to monitor flow, are good candidate locations for sensor installation, when considered along with few other nodes detected through topological criteria on the partitioned WDN. The option of considering only these potential locations, instead of all WDN nodes, inside a multi-objective optimization process, helps in reducing the search space of possible solutions and, ultimately, the computational burden. The solutions obtained with the optimization are effective in reducing affected population and detection time in contamination scenarios, and in increasing detection likelihood and redundancy of the monitoring system. Last but most importantly, these solutions offer benefits in terms of management and costs. In fact, installing a sensor alongside the flowmeter present between two adjacent DMAs yields managerial advantages associated with the closeness of the two devices. Furthermore, economic benefits due to the possibility of sharing some electronical components for data acquisition, saving, and transmission are derived.

Effective landfill management and operation require an accurate evaluation of the occurrence and extent of odour emission events, which are among the main causes of resident complaints and concerns, in particular in densely urbanised areas. This paper proposes a fuzzy optimal protection system (FOPS) based on fuzzy logic to manage odour production from a municipal solid waste (MSW) landfill. The case study is a MSW landfill in an old quarry site located 6 km north-west of Naples city centre (Italy). The aim is to reduce the odour nuisance in the area surrounding the landfill where there are several sensitive receptors. FOPS is based on logical relationships between local atmospheric dynamics, number and intensity of odour pollution events detected by certain fixed receptors and odour emission rate via an optimal fuzzy approach. Such system allows to start, in real time, established mitigation actions required to further reduce the odorous emissions from the landfill itself (e.g. spraying of perfumed substances and activation of extraction wells), especially when weather conditions might not be favourable and cause by causing a higher odour perception. The fuzzy system was coupled with the air pollutant transport software CALPUFF to simulate the odour dispersion in the considered area taking into account both different odour emission rates and local weather conditions. FOPS results show that this approach can be very useful as, by measuring the odour concentrations, a significant reduction of the odour exceedances over the thresholds fixed, to minimise the olfactory harassment, was observed in the whole area studied.

Installing an efficient monitoring and control sensor system provides the possibility to carry out main tasks on Water Distribution Networks (WDNs) management and protection. Given the WDNs complexity, efficient numerical techniques are needed to support optimal monitoring system design. Generally, it is appropriate to locate sensors at highly connected places in the WDN with water flow reaching several parts of the network. This paper introduces a general method to support water utilities on the decision making process for an efficient water system monitoring. The proposal is based on graph spectral techniques that take advantage on spectrum properties of the adjacency matrix of the water distribution network graph. It is consequently created a novel tool-set of graph spectral techniques adapted to improve the water monitoring tasks and consequently simplify further sensor placement. This is approached with no need of hydraulic simulation, as data availability is often limited or not suitable to face anomaly events changing assets and distribution performance. A real water distribution network serving a town near to Naples is used to analyze the proposed graph spectral methodology. In order to test the proposed procedure, a comparison was made with a sensor layout obtained through a bi-objective optimization, through some performance indicators. The results confirm the effectiveness of the proposed spectral procedure.