Water Network Research Articles

Hotspot analysis for integrated multi-infrastructure asset management.

Urban infrastructure, important for societal functioning, faces challenges from aging assets and increasing service demands. Traditional asset management practices, often conducted in silos, fail to address the interconnected nature of these systems, leading to inefficiencies and heightened system failure risks. This article combines the spatial and temporal aspects of sewer, water, and road networks to facilitate integrated interventions and enable informed decision-making among diverse stakeholders. The outcome of this research is the creation of interactive hotspot maps on a unified platform, highlighting potential areas for integrated intervention across different infrastructures. To enhance the potential for collaboration in integrated interventions, flexibility in intervention planning was incorporated. With increased flexibility in intervention decisions, the potential for collaboration also increased. For the case study, introducing a 5-year intervention flexibility increased the number of collaborative projects between sewer, water, and roads from 0 to 18. The maps can also indicate areas where the application of trenchless technologies are justifiable. Other important information on asset characteristics for the decision-makers, including age, inspection, deterioration, and other relevant spatial and temporal details can also be obtained from the maps. The presented methodology and findings provide practical solution for utilities to manage urban infrastructure networks more efficiently.

A Stable High-Performance Zn-Ion Batteries Enabled by Highly Compatible Polar Co-Solvent.

Uncontrollable growth of Zn dendrites, irreversible dissolution of cathode material and solidification of aqueous electrolyte at low temperatures severely restrict the development of aqueous Zn-ion batteries. In this work, 2,2,2-trifluoroethanol (TFEA) with a volume fraction of 50% as a highly compatible polar-solvent is introduced to 1.3M Zn(CF3SO3)2 aqueous electrolyte, achieving stable high-performance Zn-ion batteries. Massive theoretical calculations and characterization analysis demonstrate that TFEA weakens the tip effect of Zn anode and restrains the growth of Zn dendrites due to electrostatic adsorption and coordinate with H2O to disrupt the hydrogen bonding network in water. Furthermore, TFEA increases the wettability of the cathode and alleviates the dissolution of V2O5, thus improving the capacity of the full battery. Based on those positive effects of TFEA on Zn anode, V2O5 cathode, and aqueous electrolyte, the Zn//Zn symmetric cell delivers a long cycle-life of 782h at 5mAcm-2 and 2mAhcm-2. The full battery still declares an initial capacity of 116.78mAhg-1, and persists 87.73% capacity in 2000 cycles at -25 °C. This work presents an effective strategy for fully compatible co-solvent to promote the stability of Zn anode, V2O5 cathode and aqueous electrolyte for high-performance Zn-ion batteries.

The Water Hammer Characteristics of Long-Distance Water Pipelines under Different Water Supply Modes

The pressure characteristics of long-distance water pipelines during hydraulic transient processes are crucial for ensuring the safe, stable, and long-term operation of water transfer projects. This paper establishes a one-dimensional mathematical model based on sections of the Yinjiangjihuai long-distance water diversion project in China. The water supply requirements of the pipelines are categorized into two replenishment modes as follows: gravity supply and pump-pressurized water supply. The opening and closing strategies of the water pipelines under different flow conditions are simulated and analyzed to explore the hydraulic transient processes under various water supply modes. The transient variations of key hydraulic parameters during valve closure are clarified. Simulation results indicate that the water pipeline design is reasonable, meeting the water supply demands at relatively low Manning values and that it has the capability for long-term supply. Due to the excessive head provided by the pumps, pump-pressurized water supply and gravity supply modes cannot operate simultaneously. Under gravity supply mode, the minimum pressure in the downstream pipeline is relatively higher overall, while the maximum pressure in the upstream pipeline is relatively lower overall. In the pump-pressurized water supply mode, the safety and stability of the water supply can be ensured by adjusting the closing time of individual pumps and the interval time between adjacent pumps. The research findings provide technical guidance and scientific basis for the construction of national water networks and water transfer projects.

Detecting sources of water leakage in fractured limestone: Case study in Mokattam District, Egypt

ABSTRACT The paper investigates the sources of water leakage in Mokattam, Cairo, Egypt. It is considered a high-risk zone for landslides due to the presence of problematic soil, topography, and water conditions. The objective is to mitigate the negative impact of underground water on landslide disasters. The proposed methodology involves field visits, satellite image processing, Ground Penetration Radar scanning, chemical and isotope analysis of water, and evaluating the water and sanitary networks within the study area. The findings revealed that the underground water is formed because of the continuous leakage from the existing networks. Moreover, there was no evidence of any aquifers, particularly at Ain Mosa floating point. Thus, the accumulated water in the unsaturated zone is not sustainable for long-term development for its limited potential and poor quality. Consequently, immediate action plan is required to assess and upgrade the water and sanitary networks through the implementation of innovative technologies for such hydrogeologic conditions

Machine learning vs. regression models to predict the risk of Legionella contamination in a hospital water network.

The periodic monitoring of Legionella in hospital water networks allows preventive measures to be taken to avoid the risk of legionellosis to patients and healthcare workers. The aim of the study is to standardize a method for predicting the risk of Legionella contamination in the water supply of a hospital facility, by comparing Machine Learning, conventional and combined models. During the period July 2021- October 2022, water sampling for Legionella detection was performed in the rooms of an Italian hospital pavilion (89.9% of the total number of rooms). Fifty-eight parameters regarding the structural and environmental characteristics of the water network were collected. Models were built on 70% of the dataset and tested on the remaining 30% to evaluate accuracy, sensitivity, and specificity. A total of 1,053 water samples were analyzed and 57 (5.4%) were positive for Legionella. Of the Machine Learning models tested, the most efficient had an input layer (56 neurons), hidden layer (30 neurons), and output layer (two neurons). Accuracy was 93.4%, sensitivity was 43.8%, and specificity was 96%. The regression model had an accuracy of 82.9%, sensitivity of 20.3%, and specificity of 97.3%. The combination of the models achieved an accuracy of 82.3%, sensitivity of 22.4%, and specificity of 98.4%. The most important parameters that influenced the model results were the type of water network (hot/cold), the replacement of filter valves, and atmospheric temperature. Among the models tested, Machine Learning obtained the best results in terms of accuracy and sensitivity. Future studies are required to improve these predictive models by expanding the dataset using other parameters and other pavilions of the same hospital.

Optimized phased planning for dynamic rehabilitation of integrated municipal infrastructure

ABSTRACT Phased planning for municipal infrastructure is based on the time-dependent status of multiple networks, which is in contrast to the traditional approach, where one-phase construction and a single status are considered for planning system activities. This study integrates and optimizes the corridor-wise intervention planning of water, sewer, and road networks where the number of equally long phases and intervention decisions are among the decision variables showing the extent to which phase number optimization can impact the cost and coordination of the interventions in interdependent systems. Optimizing the phase number for municipal infrastructure optimization within an evolutionary algorithm is a challenging task due to the evolutionary recombination between numerous planning solutions with different decision variable lengths. A multi-phase design and construction approach is developed for the rehabilitation of the system in a real case study in Montreal, Canada. The study involves 20 corridors in which a street section is co-located with water and sewer pipes. A metaheuristic single-objective optimization engine is employed to minimize the total net present value of intervention plan costs for the whole integrated system. The results show that phased optimization could bring about a 25% cost saving for the rehabilitation master plan and coordinated multi-systems intervention activities.

Molecular, Genetic, and Biochemical Characterization of OXA-484 Carbapenemase, a Difficult-to-Detect R214G Variant of OXA-181.

OXA-244, an R214G variant of OXA-48, is silently spreading worldwide likely because of difficulties in detection using classical screening media. Here, we characterized two clinical isolates of Escherichia coli and Citrobacter youngae that displayed reduced susceptibility to carbapenems but were lacking significant carbapenemase activity as revealed by negative Carba NP test results. However, positive test results were seen for OXA-48-like enzymes by lateral flow immunoassays. WGS revealed the presence of a blaOXA-181-like gene that codes for OXA-484, an R214G variant of OXA-181. BlaOXA-484 gene was located on a 58.4-kb IncP1-like plasmid (pN-OXA-484), that upon transfer into E. coli HB4 with impaired permeability, conferred carbapenem and temocillin resistance (MICs > 32 mg/L). E. coli TOP10 (pTOPO-OXA-484) revealed reduced MICs in most substrates as compared to E. coli TOP10 (pTOPO-OXA-181), especially for imipenem (0.25 mg/L versus 0.75 mg/L) and temocillin (16 mg/L versus 1028 mg/L). Catalytic efficiencies of OXA-484 were reduced as compared to OXA-181 for most ß-lactams including imipenem and temocillin with 27.5- and 21.7-fold reduction, respectively. Molecular modeling confirmed that the salt bridges between R214, D159, and the R1 substituent's carboxylate group of temocillin were not possible with G214 in OXA-484, explaining the reduced affinity for temocillin. In addition, changes in active site's water network may explain the decrease in hydrolysis rate of carbapenems. OXA-484 has weak imipenem and temocillin hydrolytic activities, which may lead to silent spread due to underdetection using selective screening media or biochemical imipenem hydrolysis confirmatory tests.

PV-Based off Grid Valve Drive System for Leakage Protection in Water Networks

PV-Based off Grid Valve Drive System for Leakage Protection in Water Networks

Water Dimer under Electric Fields: An Ab Initio Investigation up to Quantum Accuracy.

It is well-established that strong electric fields (EFs) can align water dipoles, partially order the H-bond network of liquid water, and induce water splitting and proton transfers. To illuminate the fundamental behavior of water under external EFs, we present the first benchmark, to the best of our knowledge, of DFT calculations of the water dimer exposed to intense EFs against coupled cluster calculations. The analyses of the vibrational Stark effect and electron density provide a consistent picture of the intermolecular charge transfer effects driven along the H-bond by the increasing applied field at all theory levels. However, our findings prove that at extreme field regimes (∼1-2 V/Å) DFT calculations significantly exaggerate by ∼10-30% the field-induced strengthening of the H-bond, both within the GGA, hybrid GGA, and hybrid meta-GGA approximations. Notably, a linear correlation emerges between the vibrational Stark effect on OH stretching and H-bond strengthening: a 1 kcal mol-1 increase corresponds to an 80 cm-1 red-shift in OH stretching frequency.

Multiple Roles of Green Space in the Resilience, Sustainability and Equity of Aotearoa New Zealand’s Cities

Green space is needed in urban areas to increase resilience to climate change and other shocks, as well as for human health and wellbeing. Urban green space (UGS) is increasingly considered as green infrastructure and highly complementary to engineered urban infrastructure, such as water and transport networks. The needs for resilient, sustainable and equitable future wellbeing require strategic planning, designing and upgrading of UGS, especially in areas where it has been underprovided. We explore the implications of these needs for urban development through a detailed review of cited UGS analyses conducted on the larger cities in Aotearoa New Zealand (AoNZ). There are important differences in UGS availability (i.e., quantity), accessibility and quality within and between cities. Some of these differences stem from ad hoc patterns of development, as well as topography. They contribute to apparently growing inequities in the availability and accessibility of UGS. Broader health and wellbeing considerations, encompassing Indigenous and community values, should be at the heart of UGS design and decisionmaking. Most of AoNZ’s cities aim (at least to some extent) at densification and decarbonisation to accommodate a growing population without costly sprawl; however, to date, sprawl continues. Our findings indicate a clear need for the design and provision of high-quality, well-integrated UGS within and servicing areas of denser housing, which are typically areas in cities with a demonstrable UGS deficiency.

Land use evaluation and capacity assessment for sustainable urban physical development: case of study Ahvaz city

Land use evaluation and capacity assessment for sustainable urban development in Ahvaz city has become crucial due to rapid urban expansion negatively impacting current and future development. Urban population growth and resource demands have led to a decline in environmental quality. Over the past decades, Ahvaz has identified potential areas for future expansion until 2030. This study assesses the city's physical expansion and spatial development patterns, aiming to identify optimistic future development scenarios. Emphasizing balanced and equitable development, the study focuses on suitable areas, environmental preservation, pollution reduction, and mitigating urban hazards . Various factors, including land use, soil type, vegetation density, landform, groundwater level, geology, and distances from railways, industries, roads, hinterland cities, water networks, faults, and the city itself, are considered. Three decision-making methods—logic, Analytical Hierarchy Process (AHP), and integrated Fuzzy-AHP—are applied to map urban physical development. Fuzzy logic, AHP models, Expert Choice, Arc GIS software, and a land fit zoning map are used for data analysis. The AHP assesses the factors' relative importance, followed by standardization based on fuzzy set theory. Criteria factors are then combined using AHP and fuzzy logic to generate a land suitability map. The study identifies five zones for Ahvaz's future development—very high, high, medium, low, and very low—based on their physical expansion potential. The third scenario, supported by maps, indicates favorable conditions for future development in the northwest and southwest zones, considering environmental characteristics, infrastructure, and land continuity.

Synthesis of heat-integrated water networks considering detailed heat exchanger design

This paper introduces a mathematical programming approach for synthesising heat-integrated water networks (HIWNs) with a detailed heat exchanger design. A common assumption of constant heat capacities of water streams is relaxed. The specific heat capacity of water is now considered as a nonlinear function of temperature to avoid errors in calculating energy balances. In addition, most previous works have assumed constant individual heat transfer coefficients for water streams and utilities when estimating heat transfer areas. This assumption can lead to significant over- or under-estimation of heat transfer areas. In this research, individual and overall heat transfer coefficients for heat exchangers are calculated based on the detailed design of plate heat exchangers for heat recovery. The objective function of the proposed mixed integer nonlinear programming (MINLP) model is to minimise the total annualised cost (TAC). The TAC includes operating costs for freshwater and utilities, pumping costs for overcoming pressure drops in heat exchangers, and investment costs for heat exchangers. Three examples are solved in this work to verify the proposed model.

Water-saving control system based on multiple intelligent algorithms

Water conservation has become a global problem as the population increases. In many densely populated cities in China, leaks from century-old pipe works have been widespread. However, entirely eradicating the issues involves replacing all water networks, which is costly and time-consuming. This paper proposed an AI-enabled water-saving control system with three control modes: time division control, flow regulation, and critical point control according to actual flow. Firstly, based on the current leaking situation of water supply networks in China and the capability level of China’s water management, a water-saving technology integrating PID control and a series of deep learning algorithms was proposed. Secondly, a multi-jet control valve was designed to control pressure and reduce water distribution network cavitation. This technology has been successfully applied in industrial settings in China and has achieved gratifying water-saving results.

Novel Leak Detector Based on DWT an Experimental Study

We always face water leakage problems in underground distribution water networks (DWNs). Existing leak detectors suffer from false alarms due to poor leak signal quality affected by external noise, often collected by acoustic or vibratory sensors. This paper introduces a novel Discrete Wavelet Transform Detector (DWTD) that leverages precise pressure signals non-influenced by environmental noise. Using a prototype of a 100m PEHD pipeline and a diameter of 40mm, Data from two pressure transmitters were collected using a dSPACE MicroLabBox unit. The main idea is to apply the Discrete Wavelet Transform (DWT) with a DONOHO threshold law to cancel noises due to water turbulence fluctuations, ensuring high-quality signals for accurate leak detection and localization. As benchmarks to assess the quality of denoising signals three parameters were calculated, Signal to Noise Ratio (SNR 26.6763 dB), Normalized Cross-Correlation (NCC≈1), and Mean Square Error (0.20573 MSE 48.4761). The denoised temporal signals are obtained from the Inverse Discrete Wavelet Transform (IDWT). A Cross-correlation is employed to these signals to determine the leak’s location. The experimental validation involves positioning the first and second transmitters at specific distances on both sides of the leak position. This allows for comparison between the actual leak position in advance known and calculated positions at various points and leak sizes. With only a few exceptions where the maximum error rate reached 5 meters from the actual leak position, the detector's effectiveness was proven across tests involving four different leak sizes.

Production Mechanism and Emissions of CO2 in Water Networks of an Agricultural Watershed during Drainage Period

Production Mechanism and Emissions of CO₂ in Water Networks of an Agricultural Watershed during Drainage Period

Microbial drinking water monitoring now and in the future.

Over time, humanity has addressed microbial water contamination in various ways. Historically, individuals resorted to producing beer to combat the issue. Fast forward to the 19th century, and we witnessed a scientific approach by Robert Koch. His groundbreaking gelatine plating method aimed to identify and quantify bacteria, with a proposed limit of 100 colony-forming units per millilitre (CFU/mL) to avoid Cholera outbreaks. Despite considerable advancements in plating techniques through experimentation with media compositions and growth temperatures, the reliance on a century-old method for water safety remains the state-of-the-art. Even though most countries succeed in producing qualitative water at the end of the production centres, it is difficult to control, and guarantee, the same quality during distribution. Rather than focusing solely on specific sampling points, we propose a holistic examination of the entire water network to ensure comprehensive safety. Current practices leave room for uncertainties, especially given the low concentrations of pathogens. Innovative methods like flow cytometry and flow cytometric fingerprinting offer the ability to detect changes in the microbiome of drinking water. Additionally, molecular techniques and emerging sequencing technologies, such as third-generation sequencing (MinION), mark a significant leap forward, enhancing detection limits and emphasizing the identification of unwanted genes rather than the unwanted bacteria/microorganisms itself. Over the last decades, there has been the realization that the drinking water distribution networks are complex ecosystems that, beside bacteria, comprise of viruses, protozoans and even isopods. Sequencing techniques to find eukaryotic DNA are necessary to monitor the entire microbiome of the drinking water distribution network. Or will artificial intelligence, big data and machine learning prove to be the way to go for (microbial) drinking water monitoring? In essence, it is time to transcend century-old practices and embrace modern technologies to ensure the safety of our drinking water from production to consumption.

MODCEL-MHUS: a comprehensive multilayer hydrodynamic unified simulation for stormwater, sanitary sewer systems, and urban surface.

Numerous countries and regions have embraced implementing a separate sewer system, segregating sanitary and storm sewers into distinct systems. However, the functionality of these systems often needs to improve due to irregular interconnections, resulting in a mixed and malfunctioning system. Sewage collection is crucial for residential sanitation, but untreated collection significantly contributes to environmental degradation. Analyzing the simultaneous operation of both systems becomes vital for effective management. Using mathematical tools for precise and unified diagnosis and prognosis becomes imperative. However, municipal professionals and companies need more tools specifically designed to evaluate these systems in a unified way, mapping all the hydraulic connections observed in practice. This study proposes a unified simulation method for stormwater and sanitary sewer urban systems, addressing real-world scenarios and potential interferences. The primary goal is to develop a simulation method for both systems, considering system interconnections and urban layouts, involving hydrodynamic and water quality simulations. The practical application of this method, the Multilayer Hydrodynamic Simulation Method (MODCEL-MHUS), successfully identifies issues in urban water networks and suggests solutions, making it a valuable tool for urban water management and environmental engineering professionals.

Analysis of THM formation potential in drinking water networks: Effects of network age, health risks, and seasonal variations in northwest of Iran

Various factors influence the formation of disinfection by-products (DBPs) in drinking water. Therefore, it is crucial to study the formation of DBPs and identify the associated influencing agents in water distribution networks (WDNs) to effectively prevent and control the health risks posed by DBPs. This research aimed to examine THM concentrations in the WDNs of Maragheh, Iran, focusing on seasonal variations. It also compared THM levels between new and old WDNs and assessed the health risks associated with exposure to THMs through various exposure routes. The mean concentrations of Chloroform, BDCM, DBCM, and Bromoform were 44.28 ± 18.25, 12.66 ± 5.19, 3.16 ± 0.89, and 0.302 ± 0.89 μg/L, respectively. Therefore, Chloroform was the predominant compound among the THM species, accounting for over 72 % of the total THMs (TTHMs). The average TTHMs concentration in summer (69.89 μg/L) was significantly higher than in winter (50.97 μg/L) (p < 0.05). Except for Bromoform, concentrations of other THM species in the new WDNs were considerably lower than in the old WDN (p < 0.05). The mean lifetime cancer risk (LTCR) rates for oral and dermal exposure routes to THMs were negligible and within acceptable risk levels. However, the LTCR mean values for inhalation exposure routes to THMs in winter and summer were within low (1 × 10−6 ≤ LTCR <5.1 × 10−5) and high acceptable risk levels (5.1 × 10−5 ≤ LTCR <10−4), respectively. Inhalation exposure presented the highest cancer risk among the various exposure routes. The hazard index values for oral and dermal contact with THMs were less than 1. Finally, sensitivity analysis revealed that the ingestion rate and exposure duration of THMs had the most significant positive effect on chronic daily intake (CDI) values and cancer risk. However, further comprehensive investigations are needed to develop effective solutions for reducing and controlling the precursors of DBP formation, as well as identifying suitable alternative disinfection compounds that minimize by-product formation.

Efficient simultaneous optimization approach for the synthesis of large-scale heat-integrated water networks

This study develops a generalized superstructure and a compact mixed-integer nonlinear programming (MINLP) model for achieving efficient energy and water utilization in designing integrated process water systems with large sizes. Utilizing non-isothermal mixing reduces the need for many heat exchangers for indirect heat recovery. Hence, an exchanger-centric modeling strategy for heat integration is embraced over a hot–cold streams matching-based approach. A novel two-step approach is proposed to address the nonconvex and nonlinear challenges and ensure the efficiency of getting high-quality solutions. Initially, a targeting model incorporating linear heat integration is adopted to reduce the superstructure and partially initialize the design model. Subsequently, in the synthesizing stage, a two-level global search procedure is devised, integrating adaptive exchanger adjustment with multi-start local optimization. The robustness and efficiency of the proposed approach are confirmed through the resolution of four large-scale problems within one hour, yielding improved results compared to the best-known existing solutions.

Unraveling the Impacts of River Network Connectivity on Ecological Quality Dynamics at a Basin Scale

The ecological quality of river basins is significantly influenced by the complex network of river structures and their connectivity. This study measured the temporal and spatial variability of ecological quality, as reflected by remote sensing ecological indices (RSEI), and examined their responses to river network connectivity (RNC). In total, 8 RNC indices, including river structure of river density (Dr), water surface ratio (Wr), edge-node ratio (β), and network connectivity (γ), and node importance indices of betweenness centrality (BC), PageRank (PG_R), out_degree centrality (Out_D), and in_closeness centrality (In_C), were generated at the subbasin scale. Our results highlighted the significance of RNC in influencing both the values and variability of RSEI, and the extent of this influence varied across different time periods. Specifically, three distinct clusters can be extracted from the temporal variability of RSEI, representing wet, near-normal, and dry years. The river structure index of γ significantly influenced the spatial patterns of subbasin RSEIs, particularly in wet years (R2 = 0.554), whereas β displayed a pronounced U-shape correlation with subbasin RSEIs in dry years (R2 = 0.512). Although node importance indices did not correlate directly with subbasin RSEI levels, as the river structure indices did, they significantly positively affected temporal variability of subbasin RSEIs (EI_SD_t). Higher values of PG_R, Out_D, and In_C were associated with increased subbasin RSEI variability. Based on these correlations, we developed RNC-based RSEI and EI_SD_t models with high adjusted coefficients of determination to facilitate the assessment of ecosystem quality. This study provides essential insights into ecosystem dynamics related to river connectivity within a basin and offers valuable guidance for effective watershed management and conservation efforts aimed at enhancing ecological resilience and sustainability.