Water Network Research Articles

H/D Isotope Effects in the Electrochemistry of Electrochromic Iron Hexacyanoruthenate

AbstractThe electrochemical deposition of iron hexacyanoruthenate (Fe−HCR) on gold electrodes was studied in electrolytes prepared with light and heavy water. Cyclic voltammetry of the material during preparation and after transfer to a precursor‐free solution exhibits two reductions peaks in H2O‐based electrolytes but only one reduction peak in D2O‐based electrolytes. The voltammetric behavior changes reversibly upon transfer of the material between D2O‐based and H2O‐based 1 mol L−1 KCl solutions. No clear structural differences between samples prepared in D2O and H2O were detected by means of X‐ray photoelectron spectroscopy (XPS) and polarization modulation infrared reflection absorption spectroscopy (PM IRRAS). We noted a relatively slow exchange of coordinated water and a fast exchange of zeolitic water. Using voltammetric experiments we could rule out simple effects of solution conductivity for K+, participation of H+/D+ in the charge compensation and surface effects on the observed dependence of the peak splitting on the isotopic composition of the solvent. The most likely reason for the observed behavior is the different structure of the H‐bonded water network of coordinated H2O and zeolitic H2O/D2O which is supported by the PM IRRAS data.

1H, 15N and 13C resonance assignments of the S2A and H64A double mutant of human carbonic anhydrase II.

Protein-water interactions profoundly influence protein structure and dynamics. Consequently, the function of many biomacromolecules is directly related to the presence and exchange of water molecules. While structural water molecules can be readily identified through X-ray crystallography, the dynamics within functional protein-water networks remain largely elusive. Therefore, to understand the role of biological water in protein dynamics and function, we have introduced S2A and H64A mutations in human Carbonic Anhydrase II (hCAII), a model system to study protein-water interactions. The mutations of serine to alanine at position 2 and histidine to alanine at position 64 cause an increase in hydrophobicity in the N-terminus and active site loop thereby restricting water entry and disrupting the water network in the Zn2+-binding pocket. To pave the way for a detailed investigation into the structural, functional, and mechanistic aspects of the Ser2Ala/His64Ala double mutant of hCAII, we present here almost complete sequence-specific resonance assignments for 1H, 15N, and 13C. These assignments serve as the basis for comprehensive studies on the dynamics of the protein-water network within the Zn2+-binding pocket and its role in catalysis.

Requirements for water data ecosystems: results from a business ecosystem case study

This paper studies the factors that affect the emergence of water data ecosystems using a case study as a research method. The study is based on interviews conducted with partners in a comprehensive business ecosystem focused on the development of smart water network management. Eleven representatives from six private companies, the waterworks of a city, and three organizations that provide water supply management services for municipalities were interviewed. The paper presents analysis of the interview results focusing on the interviewees’ thoughts on the state of water data systems in Finland and on the factors that affect the emergence of water data ecosystems in Finland.The interview results indicate a clear need for water data ecosystems but also obstacles preventing their emergence. Inadequate understanding on the part of customer, a lack of water data, regulations, and underdeveloped agreements were seen to hinder the development of water data solutions. In addition to ecosystem development, the emergence of water data ecosystems requires investment and the development of water data solutions, solution concepts, and demonstrations to show the value of the ecosystem. The results show that ecosystems need a clear rationale and vision, effective management of water data sharing, and mechanisms to ensure the scalability of water data ecosystems.

Cross‐administrative solutions for sustainable development: The case of the Watertown Hub

AbstractWater‐abundant regions face challenges due to urbanization and development, which pose threats to local water networks and the environment. Fragmented water network management and administrative boundaries hinder cross‐administrative collaboration and ecological conservation. This study presents a framework centered around the “Watertown Hub” concept, which focuses on integrated ecological and green development, fostering multifunctional, shared spaces for coordinated management in the Watertown region of the Yangtze River Delta, China. By leveraging landscape infrastructure and ecological sensitivity assessment, shared spaces are established beyond administrative boundaries, promoting cross‐administrative coordination, management, and resource integration. The approach effectively balances the protection of basin ecology and economic development, mitigates water system fragmentation, and addresses environmental concerns. It enhances regional communication, connectivity, and sustainability. Although the focus is on China's Jiangnan region, this research provides insights applicable to other water‐rich areas in South Asia and beyond, fostering cross‐administrative ecological coordination and sustainable development amidst urbanization pressures.

Global optimization for large‐scale water network synthesis based on dynamic partition and adaptive bound tightening

AbstractThe synthesis of large‐scale integrated water networks is typically formulated as nonconvex mixed‐integer quadratic constrained programming (MIQCP) or QCP problems. With the complexity arising from bilinear terms in modeling mass flows of contaminants and binary variables representing the presence of units or streams, numerous local optima exist, thus presenting a significant optimization challenge. This study introduces a deterministic global optimization algorithm based on mixed‐integer programming (MIP) to tackle such problems. The approach involves dynamically strengthening the relaxed problems to converge towards the original problems. A simultaneous partition strategy is proposed combining locally uniform division with dynamic partitioned variables choosing. Furthermore, several adaptive bound contraction schemes are introduced to efficiently manage the size of the relaxed problems, assisting in accelerating the solution process. The algorithm's effectiveness and robustness are demonstrated with a large test set, showing superior performance compared to commercial solvers specifically on MIQCP problems.

Disinfectant control in drinking water networks: Integrating advection–dispersion–reaction models and byproduct constraints

Effective disinfection is essential for maintaining water quality standards in distribution networks. Chlorination, as the most used technique, ensures safe water by maintaining sufficient chlorine residuals but also leads to the formation of disinfection byproducts (DBPs). These DBPs pose health risks, highlighting the need for chlorine injection control (CIC) by booster stations to balance safety and DBPs formation. Prior studies have followed various approaches to address this research problem. However, most of these studies overlook the changing flow conditions and their influence on the evolution of the chlorine and DBPs concentrations by integrating simplified transport-reaction models into CIC. In contrast, this paper proposes a novel CIC method that: (i) integrates multi-species dynamics, (ii) allows for a more accurate representation of the reaction dynamics of chlorine, other substances, and the resulting DBPs formation, and (iii) optimizes for the regulation of chlorine concentrations subject to EPA mandates thereby mitigating network-wide DBPs formation. The novelty of this study lies in its incorporation of time-dependent controllability analysis that captures the control coverage of each booster station. The effectiveness of the proposed CIC method is demonstrated through its application and validation via numerical case studies on different water networks with varying scales, initial conditions, and parameters.

Inclusion of water age in conjunctive optimal operation of water and power networks

ABSTRACT Water distribution systems (WDSs) are vital infrastructures designed to deliver water safely to consumers. This complex system necessitates continuous operational decisions, often optimized for efficiency. WDSs rely on power grids (PGs) to operate pumps and treatment facilities. PGs, likewise crucial, require strategic management to meet demand and environmental standards. Integrating the operation of both systems has garnered attention for its potential cost, energy, and environmental benefits. By leveraging the interconnection, trade-offs can be assessed, leading to improved solutions. Past research primarily focused on cost or carbon emissions as well as on hydraulic and voltage constraints. However, this study examines the impact of power systems on water quality, particularly water age, a key operational concern. Incorporating PGs into the optimal operation problem may alter flow directions, thereby influencing water age. Through mathematical modelling, this study evaluates these effects and applies them to simple case studies, demonstrating the influence of PG operation on water quality. Results demonstrate how tank constraints affect water age and show that a conjunctive operation approach, although beneficial for reduction of cost and energy consumption, can be damaging for water quality.

Developing resilience pathways for interdependent infrastructure networks: A simulation-based approach with consideration to risk preferences of decision-makers

In this study, we propose a methodological framework to identify and evaluate cost-effective pathways for enhancing resilience in large-scale interdependent infrastructure systems, considering decision-makers’ risk preferences. We focus on understanding how decision-makers with varying risk preferences perceive the benefits from infrastructure resilience investments and compare them with upfront costs in the context of high-impact low-probability (HILP) events. First, we compute the costs of interventions as the sum of their capital costs and maintenance costs. The benefits of the interventions include the reduction in physical damage costs and business disruption losses resulting from the improved resilience of the network. In the final stage, we develop statistical models to predict the perceived net benefits of different network resilience configurations in power, water, and transport networks. These models are employed in an optimization framework to identify optimal resilience investment pathways. By incorporating Cumulative Prospect Theory (CPT) in the optimization framework, we show that decision-makers who assign higher weights to low probability events tend to allocate more resources towards post-disaster recovery strategies leading to increased resilience against HILP events, like earthquakes. We illustrate the methodology using a case study of the interdependent infrastructure network in Shelby County, Tennessee.

Considerações sobre a paisagem sociocultural e ambiental do Rio Jaú

Despite fundamental roles of rivers in the history and evolution of urban centers, city design has often disregarded water networks in the midst of accelerated urban expansion. The lack of connection between rivers and the urban landscape has over time contributed to the exacerbation of socio-environmental problems. This research aims at understanding the relationship between the Jaú River and Jaú’s cityscape through the following perspectives proposed by Jean-Marc Besse (2014): historical, sociocultural and socio-environmental landscapes. The river landscape of Jaú is characterized based on information taken from scientific and documentary sources (textual, iconographic and cartographic). The results of analysis are then presented to systematically characterize challenges to landscape planning in this case study. This research pertains to the contemporary effort aiming at understanding landscapes by analyzing historical and current perspectives allowing us to restore connections between a city and its natural environment. In conclusion, it is argued that the neglect of the Jaú River valley throughout urban expansion contributed to the disconnection between the river landscape, the city and its inhabitants’ daily lives. As an alternative, we propose a landscape planning process that integrates the river’s environmental and social dimensions.

Rational design of epoxy functionalized ionic liquids electrolyte additive for hydrogen-free and dendrite-free aqueous zinc batteries

Despite the high safety and low cost associated with aqueous Zn-ion batteries (ZIBs), uncontrolled Zn dendrite growth and parasitic reactions induced by water significantly diminish their stability. Herein, a new epoxy functionalized ionic liquid, 4-methyl-4-glycidylmorpholin bis[(trifluoromethyl)sulfonyl]imide (MGM[TFSI]), has been developed to mitigate water reactivity for stable ZIBs. It was found that the MGM+ cation disrupts the hydrogen bond network of water, hindering its adsorption on Zn anodes, thereby suppressing water decomposition and enhancing anode stability. Additionally, preferential adsorption of MGM+ cations on the Zn anode surface mitigates tip effects, suppresses dendrite growth, and promotes the formation of a ZnF2 solid electrolyte interphase layer, effectively isolating the anode from the bulk electrolyte. As a result, benefiting from the well-designed MGM+-based electrolyte, Zn//Zn cells achieve significantly enhanced cycling stability, lasting over 2000 h at 1 mA cm−2 with 1 mAh cm−2. Furthermore, Zn//MnO2 full cells deliver remarkable stability, retaining approximately 89 % of their initial capacity after 3000 cycles at 5 A/g. This work proposes that the MGM[TFSI] additive can effectively regulate the interfacial chemistry of the Zn anode, providing an opportunity to design advanced electrolytes for highly reversible ZIBs and beyond.

Sustainable development of the water-energy-Co2 nexus in the refining sector: A stochastic multi-objective optimization under emissions trading systems

Refineries consume substantial energy and water while emitting significant CO2. Solvent-based Carbon Capture (CC) offers a viable CO2 mitigation solution but increases water and energy consumption and requires considerable investments. This research aims to overcome these barriers and improve the Iranian refining sector towards Sustainable Development Goals (SDGs) 6, 7, and 13 by mitigating CO2 emissions, producing low-carbon hydrogen, and utilizing unconventional water resources for CC plants. A comprehensive nexus approach was incorporated to account for the intricate interconnections between SDGs and refineries' water, energy, and CO2 networks. We evaluate the implementation of CO2 market regulations corresponding to seven international Emissions Trading Systems (ETSs) of the EU, UK, New Zealand (NZ), Regional Greenhouse Gas Initiative (RGGI), South Korea, California, and China in the Iranian refining sector to incentivize CC integration. The problem was formulated using Stochastic Multi-Objective Mixed-Integer Linear Programming optimization, with K-means Clustering applied to account for ETS CO2 price fluctuations and uncertainties. Results showed intense competition between economic and environmental objectives without ETS regulations, but appropriate ETS implementation could transform this conflict into a cooperative compromise. Under EU and UK scenarios, 60.3% and 67% of CO2 emissions could be avoided with fully covered capture costs, potentially leading to net economic profit through surplus allowance sales. Implementation of the other five ETSs could reduce capture costs by 18–67%, with a 16.4% CO2 avoidance.

Occurrence, risk assessment and source apportionment of perfluoroalkyl acids in the river of a hill-plain intersection region: The impacts of land use and river network structure

Studying the impacts of land use and river network structure on perfluoroalkyl acids (PFAAs) footprint in rivers is crucial for predicting the fate of PFAAs in aquatic environments. This study investigated the distribution, ecological risks, sources and influence factors of 17 PFAAs in water and sediments of rivers from hills to plain areas. The results showed that the detection frequencies were higher for short-chain PFAAs than long-chain PFAAs in water, whereas an opposite pattern was found in sediments. The concentration of ∑PFAAs ranged from 59.2 to 414 ng/L in water and from 1.4 to 60.1 ng/g in sediments. Perfluorohexanoic acid and perfluorooctanoic acid were identified as the main pollutants in the river. The average concentrations of PFAAs were higher in the aquaculture areas (water: 309.8 ng/L; sediments: 43.27 ng/g) than in residential areas (water: 206.03 ng/L; sediments: 11.7 ng/g) and farmland areas (water: 123.12 ng/L; sediments: 9.4 ng/g). Environmental risk assessment showed that PFAAs were mainly low risk or no risk in water, but were moderate risk and even high risk in sediments, especially for perfluorooctane sulfonate. Source apportionment found that PFAA sources were mostly from industry, wastewater discharge, and surface runoff. Dissolved oxygen, chemical oxygen demand, water system circularity, network connectivity and organic matter were significantly correlated to PFAA concentration, indicating that the physicochemical properties and river network might directly influence the environmental behavior of PFAAs. The built-up area was positively correlated with PFAAs. These findings indicated that a comprehensive understanding of the influences of land use and river network structure on PFAAs in rivers is essential for managers to formulate effective PFAA control strategies.

Transferable and data efficient metamodeling of storm water system nodal depths using auto-regressive graph neural networks

Storm water systems (SWSs) are essential infrastructure providing multiple services including environmental protection and flood prevention. Typically, utility companies rely on computer simulators to properly design, operate, and manage SWSs. However, multiple applications in SWSs are highly time-consuming. Researchers have resorted to cheaper-to-run models, i.e. metamodels, as alternatives of computationally expensive models. With the recent surge in artificial intelligence applications, machine learning has become a key approach for metamodelling urban water networks. Specifically, deep learning methods, such as feed-forward neural networks, have gained importance in this context. However, these methods require generating a sufficiently large database of examples and training their internal parameters. Both processes defeat the purpose of using a metamodel, i.e., saving time. To overcome this issue, this research focuses on the application of inductive biases and transfer learning for creating SWS metamodels which require less data and retain high performance when used elsewhere. In particular, this study proposes an auto-regressive graph neural network metamodel of the Storm Water Management Model (SWMM) from the Environmental Protection Agency (EPA) for estimating hydraulic heads. The results indicate that the proposed metamodel requires a smaller number of examples to reach high accuracy and speed-up, in comparison to fully connected neural networks. Furthermore, the metamodel shows transferability as it can be used to predict hydraulic heads with high accuracy on unseen parts of the network. This work presents a novel approach that benefits both urban drainage practitioners and water network modeling researchers. The proposed metamodel can help practitioners on the planning, operation, and maintenance of their systems by offering an efficient metamodel of SWMM for computationally intensive tasks like optimization and Monte Carlo analyses. Researchers can leverage the current metamodel’s structure for developing new surrogate model architectures tailored to their specific needs or start paving the way for more general foundation metamodels of urban drainage systems.

Effect of ion-specific water structures at metal surfaces on hydrogen production

Water structures at electrolyte/electrode interfaces play a crucial role in determining the selectivity and kinetics of electrochemical reactions. Despite extensive experimental and theoretical efforts, atomic-level details of ion-specific water structures on metal surfaces remain unclear. Here we show, using scanning tunneling microscopy and noncontact atomic force microscopy, that we can visualize water layers containing alkali metal cations on a charged Au(111) surface with atomic resolution. Our results reveal that Li+ cations are elevated from the surface, facilitating the formation of an ice-like water layer between the Li+ cations and the surface. In contrast, K+ and Cs+ cations are in direct contact with the surface. We observe that the water network structure transitions from a hexagonal arrangement with Li+ to a distorted hydrogen-bonding configuration with Cs+. These observations are consistent with surface-enhanced infrared absorption spectroscopy data and suggest that alkali metal cations significantly impact hydrogen evolution reaction kinetics and efficiency. Our findings provide insights into ion-specific water structures on metal surfaces and underscore the critical role of spectator ions in electrochemical processes.

Ecological Network Construction in High-Density Water Network Areas Based on a Three-Dimensional Perspective: The Case of Foshan City

The acceleration of urbanization has resulted in varying degrees of impact on the stability and health of high-density urban ecosystems. Building urban ecological networks is crucial for safeguarding biodiversity and sustaining ecosystem vitality. In this study, the city of Foshan was selected as the study area, which is a prime representative of a high-density water network city. Additionally, a morphological spatial pattern analysis was employed to identify the ecological source. We built an ecological resistance surface using geographic, natural, and behavioral elements, adjusting it based on the density of the water network and the building height. Following this, the circuit theoretical model was utilized to create an ecological network by identifying ecological corridors. There were three key findings. First, the ecological network consisted of 30 ecological source sites and 53 ecological corridors, and 103 ecological “pinch points” and 193 ecological barrier points were identified. Second, the ecological sources were predominantly situated in the southwestern and northern parts of Foshan City. Meanwhile, the suburbs of Foshan City contained the primary ecological barrier points, mainly stemming from new construction sites, while the key ecological “pinch points” were concentrated at river junctions. The third outcome was the recommendations to (a) boost the connectivity of the ecological network in the suburbs, (b) improve the connection of the water network in urban areas, and (c) focus on enhancing landscape connectivity. The objective was to develop approaches for optimizing urban ecological networks, leading to better connectivity and improved ecological network quality.

Investigation of Dynamic Water Cluster and Droplet Interactions in Polymer Electrolyte Fuel Cells using Operando X-ray Tomographic Microscopy

Efficient removal of the electrochemically produced water from the gas diffusion layer (GDL) in polymer electrolyte fuel cells is crucial for reducing mass transport losses and improving the efficiency at high current densities. Understanding the relationship between the water percolation through the GDL and droplet formation in the gas channel will allow the design of advanced GDL materials, which provide optimal water management. In this study, a catalyst-coated membrane with 8 individual active areas (0.06 mm2 each) is investigated using operando X-ray tomographic microscopy to study the transient development and interaction of multiple percolating water clusters in a GDL and droplet formation in the channel. The 4D imaging results at a time resolution of 1 Hz showed transient instabilities in the developed percolating water networks at various frequencies associated with break-through and spontaneous water drainage.

Conjunctive optimal design of water and power networks

Water distribution systems (WDS) and power grids (PG) are critical infrastructure systems that are vital to all human activity. As such, their quality of service is of great importance for economic, environmental, and human welfare reasons. Although traditionally being analyzed separately, the two systems are interconnected and can mutually affect one another. In order to utilize the potential benefits that the two systems can produce for each other, their design and operation should be analyzed conjunctively. In this paper, a conjunctive optimal design approach for water and power networks is presented, with the objective of finding the dimensions of the systems’ facilities that will result in minimal overall costs, for both design and operation. The model is formulated and implemented on two example applications using an off-the-shelf nonlinear solver by MATLAB and compared to the optimal design of the independent WDS. A sensitivity analysis is performed to provide validity to the obtained results. The conjunctive design is compared to the design of an independent WDS to emphasize the effect of including the PG in the optimization problem. Results show a clear link between the availability of renewable energy and sizing of WDS components. The design of the independent WDS leads to the violation of PG constraints, which are satisfied when including both systems under a single optimization model, demonstrating the importance of a holistic design approach.

Food-borne disease risk: biosurveillance in water networks.

Food-borne disease risk: biosurveillance in water networks.

A Framework for Planning Climate Change Resilience for Water and Drainage Networks (A Case Study of Alexandria)

A Framework for Planning Climate Change Resilience for Water and Drainage Networks (A Case Study of Alexandria)

Does the upstream gate control scheme threaten the safety of extra-long pressurized water diversion tunnel: Gas–liquid evolution characteristics of the filling process

With the promotion of China's “National Water Networks” strategy, extra-long pressurized water diversion tunnels are increasingly implemented in trans-regional and trans-basin water diversion projects. Existing projects commonly employ middle or downstream gate control schemes, but setting the control gate at the upstream offers a new approach to mitigate the adverse effects of flow pattern changes and hydraulic inertia caused by gate operations. However, there is no precedent for a 200 km-extra-long pressurized water diversion tunnel worldwide, it is not clear whether deviating from established norms will create new problems, and how to illustrate the hydraulic evolution characteristics under this scheme is the primary challenge. Therefore, this study takes a follow-up project for China's South-to-North Water Diversion Project as the research object: (1) Modeling: establish a mathematical model of an extra-long pressurized water diversion tunnel based on the movement of gas–liquid interface; and (2) Simulating: analyze the transient process of two arrangement schemes (single-slope and variable-slope) under various operating conditions. The study reveals the characteristics of pressure distribution, flow rates, and water level variations along the tunnel, conducting a comparative analysis of different arrangement schemes. The findings demonstrate that, even under the most unfavorable assumption, the key indicators during the water filling process remain within the acceptable range specified by engineering design. Therefore, the adoption of the upstream gate control scheme for the extra-long water diversion tunnel is considered feasible. This research provides specific theoretical basis and technical support for the construction and operation of water diversion projects.