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The aim of this study was to investigate the effect of static magnetic field (SMF) synergized with low temperature (4 °C) on the properties of shrimp gels and to reveal the underlying mechanisms through the biochemical properties, microstructural and rheological properties as well as the water distribution in the shrimp sols and gels. The experimental results showed that exposing shrimp sols to SMF for 16 h followed by heat treatment significantly improved the strength and hardness of the gels. This improvement was attributed to the fact that SMF treatment altered the water distribution in the sol, leading to a decrease in the T2 relaxation time of the gel and the conversion of immobilized water to bound water. Furthermore, FTIR results indicated that the α-helix structure in the secondary structure of the proteins was transformed into β-sheet and random coiling under the influence of SMF. The gels treated with SMF for 16 h were observed to have the densest structure by microstructural measurements. However, continuous extension of the SMF treatment time negatively affected the gel quality. This study provides valuable insights for optimizing the preparation process of shrimp gels and may facilitate further application of magnetic field treatment techniques in food science. [ABSTRACT FROM AUTHOR]

This paper presents a spatiotemporal vegetation-water system characterized by nonlocal interactions. Nonlocal interactions result in a spatially nonuniform distribution of water, which affects both the growth and distribution patterns of plants. We first investigate the stability of equilibrium points in ordinary differential systems and the Turing instability in local reaction-diffusion systems. Next, we analyze the characteristic equation of the system along with the corresponding stability conditions, confirming that Hopf bifurcation and Turing–Hopf bifurcation phenomena may occur under varying parameter conditions. Finally, for nonlocal system, we approximate the original system by truncating the Taylor expansion of the integral terms. This approach allows us to derive the conditions necessary for the emergence of spatial patterns resulting from nonlocal interactions. Numerical simulations and theoretical analyses indicate that, within a broader range of nonlocal interactions, the system may exhibit vegetation patterns. [ABSTRACT FROM AUTHOR]

The phylum Bacillota comprises metabolically diverse bacteria with potential relevance in several fields. Although some genera, such as Bacillus and others, have been extensively studied, the distribution of Bacillota in the environment is still poorly understood. This study aimed to analyze the distribution of Bacillota present in water and sediment samples from different environments. For this purpose, water (W) and sediment (S) samples were collected from different marine environments (Dois Rios Beach - DR, Abraão Beach - AB, Massambaba Beach – MB, and Guanabara Bay - GB), freshwater lagoons (Jacarepiá Lagoon- JL) and hypersaline lagoons (Vermelha Lagoon - VL), all of which are located in Rio de Janeiro, Brazil. The microbial communities present in each sample were determined by sequencing 16S rRNA-encoding genes. The distribution and diversity of Bacillota were analyzed via QIIME2. The results revealed that Bacillota represented an average of 1% of the microbial community of aquatic microbiomes and were unevenly distributed in aquatic water and sediment. The highest abundances of Bacillota were detected in JL_S and VL_S, and the lowest abundances were observed in MB_W and AB_W. Only sequences related to the Bacilli and Clostridia classes were identified. The main Bacillota genera identified were Bacillus and an unidentified Clostridiales order genus. The VL_S and JL_S samples had the highest numbers of exclusive Bacillota genera. On the other hand, 15 Bacillota genera, which are generally observed in the human and animal guts, were found only in anthropogenically impacted GB_W and AB_W. The obtained results revealed how Bacillota are distributed in different aquatic environments. [ABSTRACT FROM AUTHOR]

As urbanization trends and aging infrastructure take hold worldwide, water utilities face mounting challenges meeting the growing demand for water. This study outlines an innovative approach to assess water supply and demand, physicochemical water quality analysis, improving leakage management using data analytics and hydraulic simulation in Halaba Kulito town of Central Ethiopia Regional State. The Water Geospatial Engineering Modeling System (WaterGEMS v8i) model was used for the hydraulic analysis of the distribution network by means of the data on the water distribution network and the master plan map of the Town. Water losses were determined by indicators including Non-Revenue Water (NRW), Losses per Service Connection (LSC), Losses per Main Pipe Length (LMPL), Current and Unavoidable Annual real Losses, CARL and UARL respectively and infrastructure leakage index (ILI). To achieve this, data was collected from the field, including geographical coordinates, altitude, water level in tanks and physical parameters of the water sampled. Besides, water production, consumption, distribution network, and population data were also collected. The nodal area, city contour and study area were drawn using ArcGIS. Google Earth Pro helped locate points in the water distribution system. Hydraulic simulations of an existing network system were carried out to ensure reliable parameters, such as pressure, head loss and water flow. The analysis showed that the current maximum daily demand of the town is 5,030 m3/day, the water supply coverage is 52% and the average water consumption per capital is 22 l/c/day. The town's NRW was identified as 27% of the total water production. The town's overall hydraulic performance was poor, reflected in low water connection, high losses and low coverage. The model simulation results showed that 70% of the pipes were in either sedimentation or stagnation, causing peak and off-peak velocities respectively and 25% of the nodes also had pressures below recommended standards at peak hours. Furthermore, the physicochemical quality of the water showed that out of 19 parameters, 16 were within the acceptable limits recommended by the World Health Organization (WHO), but the remaining parameters failed to meet the WHO standard. This requires improving the capacity and quality of water distribution networks and reducing water losses, drilling additional wells and increasing coverage. To ensure safe drinking water supplies, proper maintenance, monitoring and management are essential. [ABSTRACT FROM AUTHOR]

Concerns regarding disinfection byproducts (DBPs) in drinking water persist, with measurements in water treatment plants (WTPs) being relatively easier than those in water distribution systems (WDSs) due to accessibility challenges, especially during adverse weather conditions. Machine learning (ML) models offer improved predictions of DBPs in WDSs. This study developed multiple ML models to predict Trihalomethanes (THMs), Haloacetic Acids (HAAs), Dichloroacetonitrile (DCAN), and N-nitrosodimethylamine (NDMA) in WDSs using data collected over 13 years (2008–2020) from 113 water supply systems (WSS) in Ontario. Data were collected tri-monthly (four times/year) following Ontario's regulatory requirements. Four common ML models—linear regressor (LR), random forest regressor (RFR), support vector regressor (SVR), and artificial neural networks with multiple folds cross-validation (ANN-MV) and single fold validation (ANN-SV)—were trained and tested using different datasets. R2 values for training datasets of THMs, HAAs, DCAN, and NDMA models ranged from 0.533 to 0.976, 0.560 to 0.980, 0.602 to 0.993, and 0.449 to 0.858, respectively. For testing datasets, R2 ranged from 0.517 to 0.939, 0.437 to 0.945, 0.565 to 0.973, and 0.517 to 0.718, respectively. Among THMs, HAAs, and DCAN, ANN-SV models were identified as the best, followed by the RFR model, whereas for NDMA, SVR was the superior model, followed by the LR model. Some models reliably predicted DBPs, suggesting they could replace costly sampling and experimental analysis for DBPs in the WDSs, thereby enhancing DBPs control in WDSs and reducing human exposure and associated risks. [ABSTRACT FROM AUTHOR]

This study describes a monthly Atlas for the Northeast Asian Seas 2023 (ANAS23) with a 1/10° horizontal resolution and 73 vertical levels. For ANAS23, over 1.6 million hydrographic profiles were analyzed, utilizing a simple kriging interpolation technique, which considers data density and their covariance at each grid point, along with a profile stabilizing method to minimize damage to water-mass structures. Comparison of ANAS23 with previously published atlases, repeated sectional observations, and satellite-based geostrophic current fields reveals that the ANAS23 provides reliable descriptions of the spatial distribution of water masses, currents, thermohaline fronts, and mesoscale eddies while avoiding spike-shape noises, vertical instabilities, and artificial waters, particularly over large-topographic features. The ANAS23 could be utilized as a baseline to assess the dynamic state of climatological mean fields and their changes under evolving climates. The fact that uncertainty among atlases is still apparent, particularly in a region of scarce observations, calls for a collaborative international effort to collect qualified hydrographic observations for a better-performing regional atlas, thus improving predictive skills for future climate. [ABSTRACT FROM AUTHOR]

Nitrogen Sufficiency Index (NSI) is an important nitrogen (N) stress indicator for precision N management. It is usually calculated using variables such as leaf chlorophyll meter readings (SPAD) and vegetation indices (VIs). However, no consensus has been reached on the most preferred variable. Additionally, conventional NSI (NSIuni) calculation assumes N being the sole yield-limiting factor, neglecting other factors such as soil water variability. To tackle these issues, this study compared various variables for NSI calculation and evaluated two new N stress indicators in minimizing the impact of confounding water treatment. The following ground- and aerial-derived variables were compared for NSIuni calculation: SPAD, sampled leaf and canopy N content (LNC, CNC), LNC and CNC estimated using hyperspectral images acquired by an Unmanned Aerial Vehicle, and three VIs (Normalized Difference Vegetation Index (NDVI), Normalized Red Edge Index (NDRE), and Chlorophyll Index) from the hyperspectral images. Results demonstrated that ground-measured variables outperformed aerial-based variables in deriving N-responsive NSI. Especially, LNC derived NSIuni responded to N treatment significantly in ten out of thirteen site-date datasets. For the second objective, a modified NSI (NSIw) and the NDRE/NDVI ratio were compared to NSIuni. NSIw reduced water treatment effects in over 80% of the datasets where NSIuni showed evident impacts. NDRE/NDVI performed similarly to NSIw, with the notable advantage of not requiring prior knowledge of soil water spatial distribution. This research pioneers the optimization of N stress indicators by identifying the best variables for NSI and mitigating the effects of soil water variability. These advancements significantly contribute to precision N management in complex field conditions. [ABSTRACT FROM AUTHOR]

Hydraulic permeability and water content are usually measured on-site in wells or laboratory tests and are commonly supplemented with geohydrological inferences from geoelectrical data. Current approaches take advantage of the similarities between the physical processes behind electrical and hydraulic flows and the water distribution in a fully or partially saturated medium, leaving aside the complete transition from saturated to unsaturated media commonly observed in geoelectrical exploration. We hypothesize that the natural spatiotemporal variations in water content influence both electrical and hydraulic data in partially saturated media, and in turn, the hydraulic pressure-driven saturation can be used to unify and increase the sensitivity of both data types to hydraulic permeability. This paper introduces a theoretical framework for integrated hydraulic and electrical data modeling coupled with a pressure-dependent effective saturation curve. Following the adjoint state formalism, we develop the expression of the coupled sensitivity of electrical and hydraulic data to hydraulic permeability. We tested this methodology on three synthetic scenarios of unconfined aquifers to determine how the electrical data can increase the sensitivity of piezometer data to hydraulic permeability in a homogeneous and heterogeneous medium. From these experiments, we found that the electrical data are particularly sensitive to hydraulic permeability in the vadose zone, thus overcoming the lack of sensitivity of typical piezometer data for this zone. We also found that this sensitivity is maximum in the immediacies of the water table, which acts as a natural permeability scanner when accumulated measurements for different hydric stresses are made over time. [ABSTRACT FROM AUTHOR]

During the development of gas reservoirs with water, water invades the reservoir along preferential pathways, trapping a large amount of residual gas in the reservoir. Research on the distribution of residual gas after water invasion is crucial for further exploitation of the gas reservoir. Based on 50 core samples from the loose sandstone reservoir of the Sebei gas field, single-core water flooding gas experiments (20 samples) and parallel-core water flooding gas experiments (15 groups) were conducted under reservoir conditions (15 MPa, 40 °C) to study the effect of permeability difference on the distribution of residual gas. The results showed that: (1) The higher the permeability, the lower the residual gas saturation. When the permeability is less than 4mD, the residual gas saturation is greater than 40%, indicating a focus area of water trapping gas. When the permeability is greater than 15mD, the change in permeability has a minor effect on the residual gas saturation, which is less than 30%. (2) The influence of the permeability ratio on the distribution of residual gas can be categorized into key water seal area (permeability ratio > 15), water trapping zone (6 < permeability ratio < 23) and no influence zone (permeability ratio < 6). (3) After water invasion, the residual gas mainly distributes in the region with permeability less than 4mD and permeability ratio greater than 15. The experimental results can provide technical support for the study of the distribution of residual gas in similar reservoirs and the optimal selection of potential gas reservoir areas. [ABSTRACT FROM AUTHOR]

Analysis of crop water requirement and its influencing factors are important for optimal allocation of water resources. However, research on variations of climatic factors and their contribution to wheat water requirement in Xinjiang is insufficient. In our study, daily meteorological data during 1961‒2017 in Xinjiang was collected. Penman–Monteith formula and crop coefficient method was adopted to calculate wheat water requirement. Mann–Kendall mutation test and grey correlation degree analysis were used to investigate variation characteristics and correlation degree between climatic factors and wheat water requirement. The results showed that wheat water requirement ranged from 511 to 548 mm (average = 529.5 mm). Spatial distribution of wheat water requirement in Xinjiang presented a pattern of "southeast > Northwest, east > west". Wheat water requirement in most areas of Xinjiang showed a decreasing trend. During the whole growth period of wheat, the top five climatic factors affecting wheat water requirement in Xinjiang were ET0, Tmax, Tmean, sunshine duration, and Umean. Precipitation and relative humidity negatively impacted wheat water requirement, while reference crop evapotranspiration (ET0), mean wind speed (Umean), mean temperature (Tmean), maximum temperature (Tmax), minimum temperature, and sunshine duration had positive effects. This study provides a comprehensive basis for the decision making of efficient agricultural water use and irrigation measures in Xinjiang. [ABSTRACT FROM AUTHOR]

The Oyashio, a southern part of the western boundary current in the North Pacific subarctic gyre, carries cold and fresh seawater with abundant nutrients southward from the high-latitude, influencing regional climate in the East Asia and marine environment in the western mid-latitude North Pacific. Previously, a distribution of the Oyashio water has been evaluated by empirical temperature thresholds; for example, in spring (March–May) when the Oyashio intrudes southward into the east of Japan, the Oyashio water is defined at 100-m depth as ≤ 5 °C. However, this method is not necessarily adequate under the changing climate because upper ocean temperature may change over time due to some causes unrelated to cold water transport by the Oyashio (e.g., surface heat fluxes). In this study, we developed an objective method to evaluate the Oyashio water distribution applicable under the changing climate with a focus on a thermohaline front located at the warm- and salty-side boundary of the Oyashio water. We identified isohalines at 100-m depth best corresponding to the thermohaline front in each month and used them as the Oyashio water threshold. Using the developed method, we further investigated the springtime Oyashio water distribution east of Japan (in the North Pacific south of 43°N, 141–148°E). The area of the Oyashio water shows inter-annual variation and significant long-term decrease. It was suggested that these temporal variation and change reflect changes in a distribution of anti-cyclonic meso-scale eddies off Hokkaido, which block the southward Oyashio intrusion into the east of Japan. [ABSTRACT FROM AUTHOR]

Background: The analysis of changes in subcellular water distribution during mushroom fruiting is essential for elucidating the movement of water molecules within subcellular compartments. However, prior research on mushrooms has predominantly concentrated on alterations in water status during drying and postharvest processes in the food processing sector. Knowledge regarding subcellular water compartments throughout mushroom growth and fruiting remains limited. In the present study, the dynamics of subcellular water status across various growth stages of Agaricus bisporus were investigated using LF-NMR relaxometry. Results: Three components were resolved from transverse relaxation curves, assigned to cell wall, cytoplasmic and vacuolar water, in both whole mushroom and mushroom tissues (stalk and Pileus). As fruiting body developed, the proton degree of freedom of three water fractions determined by T2 measurement all increased. The T2 values of three water fractions in stalk were higher than those in pileus during the first three stages, whereas they became lower compared to those in pileus from somewhere between the two stages of 2–3 and 3–4. Apparently different patterns of change in three water contents were observed, indicating the variations in water distribution at subcellular level. Furthermore, relative humidities caused obvious changes in water status. In addition, highly significant correlations were observed between T2 and textural parameters, indicating that the dynamics of water status exert a substantial influence on the formation of mushroom quality. Conclusions: A consistent increase in the transverse proton degree of freedom of three distinct water fractions, accompanied by markedly divergent patterns in the variations of the three water contents, was observed across different growth stages of fruiting bodies. Subsequently, highly significant correlations between T2 and textural parameters were established. This study would contribute to reveal macroscopic water transport within mushroom tissues and provide theoretical insights for optimizing high-quality mushroom cultivation. [ABSTRACT FROM AUTHOR]

The enduring challenge of water distribution between India and Bangladesh persists, impacting bilateral relations significantly. This research elucidates the geopolitical intricacies of this issue and examines its adverse socioeconomic effects on Bangladesh, proposing strategic solutions. Employing qualitative methods, this study conducts a case study analysis incorporating archival research and content analysis. Data is sourced from secondary materials such as academic reports, policies, and working papers, with a theoretical framework rooted in Hydro-Politics. The study reveals Bangladesh's geographical dependency on India, particularly concerning upstream rivers where India wields hegemonic influence. Several factors contribute to the ongoing impasse, including India's internal political dynamics and unresolved issues like the Teesta dispute. Furthermore, the manipulation of water flow, such as spillway release during monsoons, presents challenges, impacting flood management and resource availability. These alterations carry significant ramifications for local communities and biodiversity. This study delves into the underexplored realm of the India-Bangladesh water distribution issue, assessing its socioeconomic impacts and proposing strategic solutions. The policy recommendations offer insights for national governments and international bodies grappling with similar challenges. [ABSTRACT FROM AUTHOR]

United Nations is standing for Sustainable Development Goal (SDG) 6 sets the agenda to address worldwide inequality in accessing safe water and improved sanitation facilities for all by 2030. However, governments in Africa seem unable to address the issue water and of sanitation facilities, since there are problems like increasing costs of sustaining existing water sources and the requirement to deliver new facilities ahead of time. Hence, this study aimed to investigate unimproved water sources and sanitation facilities geographical variation in Ethiopia using EDHS 2019 datasets. This study was community-based cross-sectional based on nationally representative data (EMDHS 2019) to identify the demographic variability of unimproved water sources and sanitation facilities in Ethiopia. STATA 14, ArcGIS 10.7, and Kuldorff's SaTScan 10.1 software were used in data analysis. Weighted by sampling weight was performed to do a trustworthy statistical analysis. Based on the dataset EMDHS 2019 Ethiopia access in both unimproved water sources was geographically clustered in Ethiopia. The finding revealed that, there were a significant spatial variation of unimproved water sources and sanitation facilities in Ethiopia. Hot and cold spot analysis revealed that there were parts of Ethiopia with higher levels of unimproved water sources and sanitation facilities coverage than other parts of the country. The SaTScan analysis of unimproved water sources indicated that the primary cluster was found southeast part of Ethiopia. The SaTScan analysis of unimproved sanitation facilities indicated that the primary cluster window was found in Benishangul Gumuz and the western part of Ethiopia. This study contribute to the understanding of the status of drinking water source and sanitation facilities based on recent EHDS data, which can inform policymakers in designing effective strategies that address specific regional challenges. This finding confirmed the previous EDHS 2016 that revealed spatial variation of unimproved water sources and sanitation facilities in the country. Findings implies that the persistence of water sources and sanitation facilities inequality continue in country. Hence, the result recommends responsible stakeholders working water source and sanitation facilities to guarantee Sustainable Development Goal 6 in Ethiopia. In addition to providing insight into Ethiopia's water and sanitation facilities situation, this study highlights important areas for development that can be applied to other nations dealing with comparable problems, especially those in Sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

Conventional analytical solutions for estimating the external water pressure neglect some factors associated with the waterproofing and drainage system (WDS), such as geotextile, circular drainage pipes, and waterproof membranes, which may lead to a gap between actual engineering observations and estimations. In this study, a reduced-scale model setup is designed to investigate the impact of the WDS on water pressure distributions. The model-test results indicate that the WDS dramatically reduces the water pressure on the secondary lining, while the effect on the initial lining is not apparent. An analytical solution is derived to analyze the external water pressure acting on the initial and secondary linings, and it is compared with model-test results. The results imply that the errors between the analytical solution and model test results ranged from −2.3% to 10.9%, thus verifying the proposed solution. Finally, a parametric analysis is conducted to reveal the WDS effect on water pressure. The following observations were made: (1) the external water pressure distribution acting on the initial and secondary linings is related to the distance between two adjacent circular drainage pipes, the surrounding rock mass and initial lining permeability, and the geotextile thickness. A small distance between the drainage pipes could increase water pressure reduction. (2) When the permeability coefficient of the surrounding rock mass is in the range of 1 × 10–8 to 5 × 10–6 m/s, the secondary lining water pressure prediction of the proposed solution is more than 54.1% lower than Liu's solution (Liu et al. 2013). The outcomes indicate the importance of the WDS effect on the water pressure under such conditions. This study results are helpful for the optimal design of composite lining structures and WDS. Highlights: A model test is designed to investigate the waterproofing and drainage system (WDS) effect on water pressure. An analytical water pressure solution on the initial and secondary lining is derived and validated. The components of the waterproofing and drainage systems (waterproof membranes, geotextile, and blind pipes) are considered. The changes of the water pressure acting on the secondary lining are more significant than those on the initial lining, as the distance between two adjacent circular drainage pipes increases. [ABSTRACT FROM AUTHOR]

Leakage and energy consumption in urban water distribution networks (WDNs) have been receiving increasing attention, and pressure management based on district metered areas (DMAs) can effectively control leakage and save energy. In this paper, a set of scientific and practical methods for designing DMA partition of WDNs and carrying out pressure management based on it is proposed. First, the spectral clustering algorithm and NSGA-III algorithm are combined in a clever and innovative way to establish and solve the DMA boundary optimization division model. Compared with the existing methods, more factors can be considered in the process of boundary partitioning, so as to obtain overall excellent partitioning results. Second, based on the partition results, the optimal arrangement model of valves and flow meters on the DMAs boundary pipes is established and solved. Finally, pressure reducing valves (PRVs) are installed at the inlet of the DMAs, and the joint scheduling optimization model of the PRVs and pump station in WDNs is established and solved. In the process of scheduling, the pump is innovatively limited to the efficient section operation, saving energy and extending the service life of the pump. The proposed method is applied to the SH town network. Results reveal that the method can establish DMAs considering multiple objectives. Furthermore, pressure management in DMAs can not only significantly reduce leakage and energy consumption of pumping stations but also improve the water quality of networks. Therefore, this method can provide a reference for water utilities in establishing DMAs and carrying out pressure management in WDNs in the future. [ABSTRACT FROM AUTHOR]

Boron toxicity is an increasingly serious problem leading to soil degradation and vegetation loss in arid and semi-arid environments worldwide. The soils of solonetzic complexes often display this characteristic. This study aimed to investigate the vertical distribution of hot water soluble-boron (hws-B) in the sodic and agricultural soils of Israna block in Haryana, India. The study also examined the influence of various soil variables on hws-B. The samples were collected at six depths to assess the availability of B. Additionally, an assessment was conducted to ascertain the appropriateness of the water sources for irrigation. The findings of our study revealed a notable disparity in the hws-B content between sodic soils and control agricultural soils, with the former exceeding the toxic thresholds. The levels of B available to plants were highest in the upper layers of soil and reduced as the depth increased. A number of variables influenced the water-soluble B content in sodic soils, particularly pH, calcite content, electrical conductivity (EC), organic matter (OM), and calcium-boron ratio (Ca/B). The results indicated that the boron levels in both surface and groundwater were within acceptable limits for irrigation purposes, suggesting that boron toxicity may not be directly attributed to these sources. Our study suggests that sodic soils contain high levels of boron, which can be toxic, and consequently, proper management of these soils is recommended. It is essential to have a comprehensive understanding of boron levels in surface and sub-surface soils, as well as in irrigation water, in order to effectively manage soil and improve crop productivity. [ABSTRACT FROM AUTHOR]

This study investigated the spatiotemporal variation of water cut in the AB reservoir unit of the Zubair Formation at the South Rumaila oilfield in Iraq using petrophysics, geostatistics, and machine learning techniques. The study found that the spatial distribution of petrophysical properties such as porosity, permeability, volume of shale, and unit thickness had little impact on the distribution of water cut. The most important factor was the rates of water injection and oil production. The study also found that the AB unit is homogeneous rather than heterogeneous, and this heterogeneity does not play a crucial role in the evolving water cut across the oilfield. The study of historical water cut data showed that the northern part of the oilfield had a higher water cut than the central and southern areas in 2012. However, as production and injection rates increased, the entire oilfield saw significant increases in water cut. Modeling of water cut using four machine learning algorithms (random forest, cubist, support vector machine, and linear regression) and a multi-layer perceptron deep learning technique showed that the random forest and cubist algorithms were the best in both training and testing stages. The stand-alone models of these algorithms for each well location can be used to quickly and easily predict water cut values throughout the oilfield, providing a way to efficiently manage the AB reservoir unit. [ABSTRACT FROM AUTHOR]

The advancements of the Internet of Things and Low-Power Wide-Area Network technology will accelerate in the next future the adoption of smart meters in water distribution systems, enabling the collection of a huge amount of fine-grained data. How to turn massive smart meter data into actionable knowledge will be the key point to limit water wastage and promote efficient and sustainable distribution. Although the collection of data worldwide is currently limited, the potential future impact of exploiting data-driven and machine learning methods is increasingly recognized in research and industry, as shown by many scientific works published in recent years. In particular, the interest in deep learning for smart water distribution systems is increasing, motivated by the ability to learn intricate patterns from big data. This work aims to provide an overview of the current research and identify challenges for future directions by conducting an application-oriented survey. Specifically, by analysing data characteristics and operational targets, we propose a new taxonomy that helps structure properly the macro-areas of water management into infrastructure analysis, demand analysis and water quality monitoring. Existing methods are discussed for each application under these three stages. In addition, we also discuss potential research directions, such as federated learning, incremental learning, probabilistic modeling and explainability and address broad issues like data availability and implications for privacy. [ABSTRACT FROM AUTHOR]

Mucin, proteoglycan, glyconectin, and hyaluronan intermolecular binding in the physiological hydrated state forms the native glycocalyx ultrastructure via the polyvalent interactions of their similar bottle-brush morphologies. This ultrastructure provides a variety of essential cellular recognition/adhesion and selective filtration functions. Unfortunately, for decades, the glycocalyx architecture was only examined in the non-native dehydrated/fixed state. This has resulted in the visualization of an artefactual unorganized fiber mesh, hindering understanding of structure-function relationships. We unveil a well-organized glycocalyx lamellar ultrastructure using cryo-SEM after cryo-preservation with minimal sublimation to conserve water and ion distribution and, thereby, native intermolecular interactions. The glycocalyx of human cells and the glyconectin glycocalyx of an evolutionary distant sponge displayed similar self-assembled ultrastructures comprising hierarchical micro- and nanoarrays despite compositional differences. AFM binding strength measurements and cryo-SEM results imply that evolutionarily preserved glycocalyx morphologies are formed by thermodynamically driven self-assembly of glycoconjugates with similar physicochemical properties. Cryo-SEM reveals a highly organized glycocalyx ultrastructure in human cells and sponges, with AFM measurements suggesting that evolutionarily preserved glycocalyx morphologies are formed by self-assembly of glycoconjugates. [ABSTRACT FROM AUTHOR]

Residual chlorine has a bactericidal effect, but it may react with natural organic matter in water to produce harmful substances. In this work, we report an efficient residual chlorine removal filter with activated carbon fiber (ACF) as adsorption carrier and CuO as residual chlorine degradation catalyst. Experimental results show that CuO has high catalytic efficiency and no attenuation of catalytic performance in 2924 h. The CuO is loaded on the surface of ACF by dipping-calcinating method. When the loading rate is 1.5%, the CuO distribution is uniform without defects and agglomeration. Continuous-flow experiment result shows that 1.5%-CuO/ACF filter can treat water amount 2.2 times as long as that for single ACF filter (residual chlorine concentration < 0.1 mg/L). Weak acidity and rising temperature can improve the reaction activity and increase the degradation amount of residual chlorine. The composite filter has excellent adsorption performance for Cu2+, showing the Cu2+ concentration in the produced water is less than 0.1 mg/L after filter treatment, which is in line with the National Drinking Water Standards, and in agreement with the Standard for Safety Assessment of Water Transmission and Distribution Equipment and Protective Materials for Drinking Water (GB/T17219-1998) of Immersion Experiment, indicating that 1.5%-CuO/ACF filter has good stability and safety. [ABSTRACT FROM AUTHOR]

In the context of limited resources and a growing demand for food due to an increase in the worldwide population, irrigation plays a vital role, and the efficient use of water is a major objective. In pressurized irrigation systems, water management is linked to high energy requirements, which is especially relevant in sprinkler irrigation. Therefore, decision support models are important for optimizing the design and management of irrigation systems. In this study, a holistic model for solid set irrigation systems (SORA 2024) was developed. This new model integrates hydraulic models at the subunit and plot levels to evaluate the distribution of pressure (EPANET, Rossman in The EPANET programmer's toolkit for analysis of water distribution systems, Tempe, Arizona, 1999), the discharge and water distribution for each emitter (SIRIAS, Carrion et al. in , Irrig Sci 20(2):73–84, 2001) and the distribution of water applied by all the emitters of the subunit (SORA, Carrión et al. in Irrig Sci 20(2): 73–84, 2001). The integrated model also includes crop simulation (AQUACROP, Steduto et al. in Agron J 101(3), 426–437, 2009). to assess the effect of water distribution on crop production. The objective of this holistic model is to assist in decision-making processes for designing, sizing, upgrading, and managing solid set irrigation systems at the sprinkler level. The new integrated model (SORA 2024) was applied to a 2.84 ha commercial plot with 2 irrigation sectors that grow onion crops (Allium cepa L.). It was used to analyse each irrigation event from a real irrigation season, considering the conditions (pressure, irrigation time/periods, environmental conditions, and so on). The analysis is based on the sprinkler–nozzle combination, working pressure and wind direction and intensity during each irrigation event. The model also accounts for the cumulative effect/impact of all irrigation events on the plot. The model was validated through field trials using the "crop as a sensor" approach (Sarig et al. in , Agron 11(3):2021). To demonstrate the effectiveness of the model, the choice of nozzles in each sprinkler of the subunit was optimized. This is a quick and cost-effective way for farmers to improve their irrigation systems. By using this method, farmers can achieve better uniformity of water application and a slight increase in crop yield while maintaining the same irrigation schedule and amount of water used. Furthermore, the model enables farmers to work at the emitter level while integrating the results for the entire plot. This allows for precise irrigation of variable dosages by using different sprinkler–nozzle combinations in the same subunit. Farmers can do this based on the prior zoning of the plot, which is determined by its productive potential. This justifies the use of different irrigation dosages in each zone. [ABSTRACT FROM AUTHOR]

The ectoparasitic salmon louse (Lepeophtheirus salmonis Krøyer, 1837) persists as a major hindrance for continued growth of the Norwegian salmon industry. Shielding technologies or management strategies are being used to reduce the likelihood of contact in the net pens between the salmon and the sea lice's infectious copepodid stage. Knowledge about the vertical distribution and diel migration patterns of the planktonic sea lice stages are inevitably a premise for such water-depth-dependent avoidance technologies to be efficient; however, not many studies have investigated diel vertical migration patterns of sea lice in situ or in relevant scales. In this work, we aimed to monitor the diel migration of L. salmonis copepodids in the vertical plane without the influence of hydrographical forces, using sufficient water column depth of 11 m, natural thermoclines, and natural exogenous light conditions. We followed a cohort of copepodids over the course of 4 days and measured their vertical distribution in the water column twice per hour in a custom made mesocosm, using automatic particle detection and machine learning to analyse position and migration patterns. The L. salmonis copepodid population displayed reverse diel migration, and we found a statistically significant interaction between depth and time. During the day, copepodids were found in the upper 1 m of the water column, before the majority of the population descended to 1–2 m depth during night-time. A small fraction of the population remained in the upper part of the water column also during night-time. A significantly higher fraction of the copepodid population resided in the upper metre during daylight hours compared to other depths. These results could be utilised as input in sea lice dispersal models which are important management tools in today's sea lice prevention strategies and regulatory frameworks. [ABSTRACT FROM AUTHOR]

China is increasingly facing significant challenges related to its water resources, with these pressures further intensified by the unequal distribution of water across the country. This imbalance risks creating disparities in welfare and environmental conditions between regions. As one of the largest consumers of water, the industrial sector plays a crucial role in exacerbating these challenges. However, existing research on China's industrial water footprint often lacks scope and neglects regional water scarcity. This study addresses these gaps by using a multi-regional input-output model to assess China's industrial water footprint comprehensively. We integrate this analysis with quantitative measures of water scarcity that include ecological environmental flow requirements, exploring the link between industrial water use and regional water scarcity. Our findings reveal that a mere 10% of provincial sectors are responsible for an overwhelming 64% of the industrial water footprint. Furthermore, in 26 out of 31 provinces, the indirect industrial water footprint exceeds 50% of the total water scarcity, highlighting the extensive impact of industrial activities on regional water resources. These insights highlight the complex patterns of industrial water consumption in China and their implications for regional water scarcity, offering guidance for policy and cross-regional collaboration on sustainable water management. [ABSTRACT FROM AUTHOR]

The morphology of the water jet in the far field is a discrete flow consisting of multiple disorganized discrete single droplets. However, the stress distribution and dynamic evolution of the coal surface under the impact of a single droplet is still unclear, which makes it difficult to obtain the key factors affecting the coal stress. In this paper, a mathematical model for coal surface stress distribution and dynamic evolution under single droplet impact was established, the stress concentration characteristics and the key affecting factors of coal surface were studied, and the synergistic effects of these factors on the stress distribution and damage characteristics were explored. The results show that the impact velocity of the droplet is the main controlling factor in determining the coal surface's stress distribution and dynamic evolution. The principal stresses are concentrated by compressive stress in the center of the droplet-coal contact area, and the radial stress is concentrated by tensile stress in the edge of the contact area. The principal stresses have the same evolutionary trend with time and the stress attenuation decreases with increasing distance between the material point and the center of the contact area. The droplet's impact velocity and the Poisson's ratio of coal synergistically affect the stress distribution and damage on the coal surface by changing the value of the principal stresses and the proportionality between the principal stresses, respectively. The results lay a theoretical foundation for clarifying the parameter adjustment and the coal damage mechanism under discrete flow impact. Highlights: A mathematical model for surface stress distribution and dynamic evolution of coal under single droplet impact is established. Stress concentration characteristics of coal surface under single droplet impact are revealed. The impact velocity of the droplet affects the stress distribution and damage on the coal surface by changing the value of the principal stresses. The Poisson's ratio of coal affects the stress distribution and damage on the coal surface by changing the proportionality between the principal stresses. [ABSTRACT FROM AUTHOR]

The efficiency of water distribution at primary, secondary, and tertiary levels in the Indus Basin Irrigation System (IBIS) has historically suffered due to poor design, suboptimal operation, and water scarcity. To address these issues, the system has been designed with ungated irrigation outlets to ensure equitable water allocation at secondary and tertiary levels. This research evaluates the hydraulic performance of three irrigation outlets: adjustable proportional module (APM), adjustable orifice semi-module (AOSM), and open flume (OF) using a physical model study. A distributary channel model with these outlets was constructed at the Centre of Excellence in Water Resources Engineering, where discharge coefficients (Cd) were calibrated and measured under various hydraulic and geometric conditions, including free and submerged flow conditions, and with adjustments to flow depths and outlet settings. The results showed variability in Cd values under free flow and submerged flow conditions with APM and AOSM ranging from 6.07 to 8.20 and 0.56 to 0.74, respectively, and OF between 2.46 and 4.31. Additionally, the behavior of outlet tampering on Cd values was also assessed under three scenarios: tampering with the half wing wall (1st), tampering with the full wing wall (2nd), and lowering the bed level downstream of the outlet (3rd). The increase in Cd values for APM and AOSM was + 10.84% and + 14.49% under 1st scenario, + 17.12% and + 22.36% under 2nd scenario, and + 24.25% and + 26.30% under 3rd scenario, respectively. The results reveal that even minor tampering with outlet structures can lead to significant deviations in performance, highlighting the importance of maintaining stringent control over outlet configurations to ensure equitable and efficient water distribution. There is a critical need for rigorous, site-specific calibration of irrigation outlets to optimize their performance under local conditions and redesigning outlet structures to minimize the impacts of tampering, thereby enhancing the overall sustainability of water use in large-scale irrigation systems. The findings from this study provide essential insights for irrigation engineers and policymakers tasked with upgrading and maintaining irrigation infrastructure. By adopting a more customized approach to outlet design and management, it is possible to significantly improve water use efficiency and achieve more sustainable irrigation practices. [ABSTRACT FROM AUTHOR]

An analytical estimate is given to the transformation of the water-management and amelioration complex of Crimea under the conditions of deficiency of water resources based on the system and information-analytical approaches with the use of methods of logical and comparative analysis, and qualitative and quantitative analysis of statistical data. An abrupt change in the structure of freshwater intake was revealed. In 2014–2022, the leaks and losses in the water distribution system in the Republic of Crimea increased by 44%. Here, from 0.5 to 1.8% of the network length, requiring replacement is replaced every year; the respective number in Sevastopol is from 0.1 to 1.3%, which is extremely low. The mean daily water consumption by the population of the Republic of Crimea, taking into account the increase in the number of vacationers in this period decreased from 134 to 101 L, and that in Sevastopol City, from 184 to 98 L. Now, only 3/4 of the urban population of the Republic of Crimea and 2/3 of its rural population receive high-quality drinking water. After the closure of the North-Crimean Channel, the area of irrigated lands decreased by 7–8 times. The abrupt increase in water deficiency in agriculture has led to a rapid increase in the most efficient irrigation method—drip irrigation. The role of irrigation in the production of key agricultural products is demonstrated. It is shown that the proportion of polluted wastewaters increases, and the proportion of wastewater treated to a standard level decreases. In the Republic of Crimea, both decrease and increase in the discharged mass of individual pollutants was recorded. Water quality in most Crimean rivers does not deteriorate. In 2022, >97% of the major pollutants contained in wastewaters of Sevastopol City were discharged directly into the Black Sea, and the main watercourses (the rivers of Chernaya, Belbek, Kacha) were not polluted by them. [ABSTRACT FROM AUTHOR]

Groundwater levels vary from region to another and sometimes in different zones in the same country due to different boundary conditions and extraction rates. Therefore, understanding intricate aquifer systems and predicting how they will react to hydrological changes require the use of groundwater models. In Egypt, the groundwater levels in the Nile Delta aquifer decrease causing problems to the delta ecosystem while it is rising in Aswan area due to the presence of Nasser Lake causing several damages to the city's buildings and infrastructures. In order to maximize its benefits and lessen the harm brought on by inadequate groundwater management in the city of Aswan, the height of the groundwater level in that city was examined, appraised, and groundwater management scenarios were established in this study. To achieve the objectives of the study, a simulation of Aswan aquifer's groundwater system is built based on a quasi-three-dimensional transient groundwater flow model using MODFLOW. The model was calibrated and verified. Four management scenarios are tested. The fifth scenario, in this scenario, the four scenarios combined together at the same time and with the same conditions and ratios were proposed to be implemented. The results of the proposal to implement the four scenarios together showed that the rates of decline in groundwater levels in the last stage will be 12.44%. The study results reveal that a better understanding of the simulated long-term average spatial distribution of water balance components is useful for managing and planning the available water resources in the Aswan aquifer. [ABSTRACT FROM AUTHOR]

Detecting and mitigating leaks in water distribution networks are vital for water conservation. Machine-learning-based (ML) acoustic leak detection models were introduced as effective alternatives for leak management. However, ML model training requires sufficient labeled data, which hinders related development. To address this challenge, this study employed contrastive learning (CL) for leak detection using limited labeled signals. Experimental results indicate that flip-x and amplitude scaling are optimal combinations for contrastive learning. Besides, ablation and t-distributed stochastic neighbor embedding (t-SNE) results reveal that increasing the model depth does not always yield performance improvement, and five convolutional blocks are more suitable for the leak detection problem in this study. Comparison experiments demonstrate that contrastive learning outperforms supervised learning (SL) when trained with insufficient labeled data. The out-of-sample validation results indicate that the proposed leak detection model is robust and effective in unexplored pipelines. The proposed framework significantly advances ML-based leak detection research and supports sustainable water management practices. [ABSTRACT FROM AUTHOR]

Microplastics are tiny plastic particles with a usual diameter ranging from ~ 1 μ to 5 µm. Recently, microplastic pollution has raised the attention of the worldwide environmental and human concerns. In human beings, digestive system illness, respiratory system disorders, sleep disturbances, obesity, diabetes, and even cancer have been reported after microplastic exposure either through food, air, or skin. Similarly, microplastics are also having negative impacts on the plant health, soil microorganisms, aquatic lives, and other animals. Policies and initiatives have already been in the pipeline to address this problem to deal with microplastic pollution. However, many obstacles are also being observed such as lack of knowledge, lack of research, and also absence of regulatory frameworks. This article has covered the distribution of microplastics in water, soil, food and air. Application of multimodel strategies including fewer plastic item consumption, developing low-cost novel technologies using microorganisms, biofilm, and genetic modified microorganisms has been used to reduce microplastics from the environment. Researchers, academician, policy-makers, and environmentalists should work jointly to cope up with microplastic contamination and their effect on the ecosystem as a whole which can be reduced in the coming years and also to make earth clean. [ABSTRACT FROM AUTHOR]

As the urban population increases, the consumption of water resources is also increasing. Safely and effectively supplying water to cities has become an issue that urgently needs to be addressed. The purpose of this research is to substantially reduce the number of contaminants in water distribution networks (WDNs) by using valve control, ensuring that the water infrastructure is not impacted by the adverse effects of wastewater. In addition, an improved parallel binary gannet algorithm (IPBGOA) is proposed and combined with this approach to solve the optimization problem of WDN contamination efficiently. The proposed method is compared with the gannet optimization algorithm (GOA), particle swarm optimization (PSO), differential evolution (DE), the grey wolf optimization (GWO), and the genetic algorithm (GA) on synthetic benchmark networks in simulation experiments. The evidence from the study indicates that the algorithm proposed in this paper is significantly more efficient and reliable than the comparison methods. [ABSTRACT FROM AUTHOR]

Low organic matter content is one of the main constraints in arid and semiarid regions. This constraint and its negative influences on soils and plant growth may be alleviated by biochar (BC). Furthermore, improving soil physical and hydraulic attributes by application of biochar has received increased attention. Therefore, in the present study, the effects of sugarcane bagasse-derived biochar on the structural stability, water availability, and pore-size distribution (PSD) of three texturally different calcareous soils collected from different agro-climatologically regions were examined during a long-term experiment. Low and high-temperature biochars, produced in a muffle furnace by the traditional slow pyrolysis method at 300 °C (BC300) and 600 °C (BC600) were evaluated. Pots (15 kg) were filled with three different silty-clay Inceptisols (SCInc), silty-clay-loam Alfisols (SCLAlf), and loam Aridisols (LArid) soils mixed with 0 (control), 1, 2, and 3 w/w% of BC300 and BC600 during 540 days of incubation. The high energy moisture characteristic (HEMC) data was modeled using a modified van Genuchten function to quantify aggregate stability through stability ratio (SR) and structural stability index (SSI). The plant available water (PAW), least limiting water range (LLWR), and integral water capacity (IWC) were calculated with two matric suctions (h) of 330 cm for field capacity (FC) and 15,000 cm for permanent wilting point (PWP). Then the integral energy (EI) values were calculated (EIIWC). Results indicated that the incorporation of 3 w/w% biochar significantly (p < 0.01) increased SR (35 to 100%) and SSI (21 to 28%) indices in all three soils. Biochar significantly increased modal suction (MS) in LArid soils (5 to 158%); whereas, decreased MS of the other soils (3 to 43%). MS, SR, and SSI of BC300 and BC600-treated soils were not significantly different. PAW, LLWR, and IWC significantly decreased in the SCInc (18 to 61%, 8 to 44%, and 6 to 35%) and SCLAlf (8 to 44%, 18 to 35%, and 20 to 47%) soils and increased in LArid (4 to 54%, 3 to 61%, and 24 to 111%) soil with increasing biochar doses. There were no changes in EIIWC in biochar-treated LArid soil where PAW, LLWR, and IWC increased. Biochar increased EIIWC across the studied soil from 1% to 3.38 folds, thereby increasing the gradient of water potential to absorb the available water. Soil and soil-biochar mixtures exhibited heterogeneous and multimodal pore-size distribution (PSD). Biochar promoted the PSD peaks related to water-transmitting pores in SCInc and SCLAlf soils while decreased in LArid soil. In conclusion, results indicated that among the applied levels of biochar, the application of 3 w/w% biochar is suggested as a suitable way to improve soil physical behavior and structural stability. [ABSTRACT FROM AUTHOR]

This study investigated the prospective effect of ApnA enzyme under different concentrations (µL/100 mL soymilk) compared to chemical (pH, MgCl2, and K-carrageenan, respectively) as tofu coagulants. The resultant tofu samples were analyzed for compositional analysis, thermal properties, water distribution, and microstructure properties. The higher concentration of enzyme used, the higher resulted moisture content of tofu. ApnA enzyme increased the cross-linking through protein molecules and trapped more water within the gel network. Tofu samples prepared by different concentrations of ApnA enzyme displayed significantly less freezable water content (15.44, 12.84, and 19.46 g/100 g). In particular, 800 µL ApnA/100 mL soymilk formed an interconnected gel matrix with regular distribution with almost invisible cavities. The thermal pretreatment and the increased coagulation time might encourage this irregular structure. On the other hand, the gel network coagulated using the reduction of pH showed a weaker gel due to an accelerated acidification. [ABSTRACT FROM AUTHOR]

This study investigated the presence and distribution of mercury in water bodies under the influence of artisanal and small-scale mining (ASGM) activities in Tanzania, which continue to predominantly rely on mercury for gold extraction. Various water bodies available for domestic and animal use in mining communities were sampled from surface water sources in ASGM settlements during the rainy and dry seasons. Water samples were analysed using cold vapour atomic fluorescence spectrophotometer (CVAFS). The results indicate that most of water sources had THg levels above the WHO guideline of 1.0 µg/L (1000 ng/L) for safe drinking water. The levels were significantly higher during the wet season ranging from 3.4 to 96.3 µg/L, whereas the range was from 0.84 to 2.12 µg/L during the dry period. The higher THg values during the wet season are likely a result of increased lateral transport (e.g. via enhanced runoff) and physical properties of the waterways. Transportation and resuspension of matrix-bound mercury from surface soils and inflow of contaminated water from unprotected tailings were also observed to be potential means of lateral mercury transport. The lowest concentrations (0.846 µg/L) were observed in water samples from the Mabubi River, upstream of a mining village. Downstream of the mining village in the same river, higher concentrations were observed in the Nungwe Bay region of Lake Victoria. In other surveyed mining settlements where there were no nearby rivers, pool water indicated high concentrations of THg, including levels above thresholds for safe human use. Immediate stringent measures are needed in order to ensure human and animal safety at ASGM mining settlements. Future investigation is suggested to focus on the distribution of mercury in different media, assessing the prevalence of different mercury species, and investigating the influence of weather and hydrological conditions on the impacts of mercury to organisms as part of the strategies to mitigate mercury pollution. [ABSTRACT FROM AUTHOR]

An accurate estimation of leakages in water distribution networks is of primary importance for the definition of strategies aimed at ensuring an efficient management of water resources and avoiding water waste. However, in the case of methods based on water balance—such as the Minimum Night Flow method—inaccurate assessment of the minimum night consumption (MNC), e.g. the assumption of fixed MNC values from the literature, can heavily mislead the quantification of leakage level. This study aims at providing insights into the variability of MNC and the related drivers. In greater detail, hourly water consumption data of approximately 200 users are collected over a period of two years and subjected to a multi-phase methodology to obtain a detailed characterization of MNC, with and without considering the users affected by post-meter leakages. The study demonstrates that factors such as seasonality or the presence of post-meter leakages may strongly impact the MNC—the values of which can significantly deviate from the literature references—and thus lead to significant misestimation of network leakages in water systems. Highlights: A methodology for the statistical analysis of minimum night consumption (MNC) based on the daily water-consumption profiles at the user level is proposed. The methodology is applied to hourly-resolution water-consumption data collected over two years in a sample of over 200 users. Occupancy rate, seasonality, and presence of post-meter leakages affect MNC statistics. [ABSTRACT FROM AUTHOR]

The design of the reactant gas flow field structure in bipolar plates significantly influences the performance of proton exchange membrane fuel cells (PEMFCs). In this study, we introduced four innovative U-shaped flow field designs, namely: In-Out Multi-U, Out-In Multi-U, Distro In-Out Multi-U, and Distro Out-In Multi-U. To investigate the impact of these various flow fields on PEMFC performance, we conducted computational fluid dynamics (CFD) numerical simulations, validated through model experiments. Our results indicate that the Distro Out-In Multi-U flow field offers notable advantages compared to the conventional parallel flow field (CPFF) and conventional serpentine flow field (CSFF). These benefits include reduced inlet and outlet pressures, lower liquid water content, more uniform liquid water distribution, and a more even current density distribution. Furthermore, the Distro Out-In Multi-U design demonstrates improved efficiency, consuming less H2 (91.9%) than the CSFF while achieving a higher net power density output (10.1%). As a result, for the same power output, the Distro Out-In Multi-U utilizes only 83.5% of the H2 consumed by the CSFF. In summary, the U-shaped structured flow field exhibits superior output performance, enhanced energy efficiency, and improved resistance to flooding. These findings suggest that the U-shaped flow field design holds significant potential as a reactive flow field for PEMFCs. [ABSTRACT FROM AUTHOR]

Water film thickness (WFT) is a primary factor influencing the flowability of cement mortar and gypsum slurry. However, conventional WFT calculation models have overlooked the impact of fiber surface properties on flowability. This study addresses this issue by introducing a parameter called the residual moisture distribution coefficient into the residual moisture distribution coefficient (RMDC) and the WFT calculation model. Thirty-six groups of basalt fiber-Phosphogypsum composite slurry with varied mix proportions were designed and assessed for their flowability and packing density. The RMDC and WFT were derived from fitting with the improved model. Finally, a basalt fiber-Phosphogypsum composite slurry flowability prediction model based on WFT was established, laying a foundation for the design and further application of fiber-gypsum composite flowability. [ABSTRACT FROM AUTHOR]

Safeguarding the drinking water quality remains a challenge from the production site to the tap. Alternatively to chemical disinfection, biostable drinking water could serve as a more sustainable approach to produce microbially safe drinking water and to maintain the microbial quality in the drinking water distribution system (DWDS). In this study, the potential of hydrogen-oxidizing bacteria (HOB) to produce biostable drinking water was examined in a continuous trickling filter supplied with hydrogen gas. A biofilm was naturally enriched for 5 months and the bacterial regrowth, invasion potential, and nutrient composition of the water were determined. Treatment improved the biostability significantly, and it is hypothesized that nutrient limitation, especially phosphorous, was a driving force. As a result, the regrowth and invasion potential were lowered, as shown with specific biostability bioassays. Overall, this study demonstrates the proof-of-concept of HOB for producing biostable drinking water through nutrient limitation. [ABSTRACT FROM AUTHOR]

The performance of a PEM fuel cell that uses hydrogen as the fuel and pure oxygen as the oxidant strongly depends on water management, which has been primarily studied in a single-channel domain. Therefore, there is a need to examine water distribution throughout the entire fuel cell domain, including both the anode and cathode sides. Liquid water can cause flooding in the gas diffusion layer, catalyst layer, and channels, reducing the active surface area of the catalyst and, consequently, the reaction rate. Phase transfer between liquid water and water vapor influences the buildup of liquid water in these domains. In the present work, a three-dimensional, non-isothermal, two-phase numerical model incorporating both the cathode and anode domains has been developed to study water distribution. This model includes water phase transition in the gas diffusion layer, catalyst layer, and channels. The mixed flow distributor is used to analyze water formation and distribution throughout the domain. The study shows that using pure oxygen at the inlet increases the ohmic region in the polarization curve and decreases concentration losses, which could be important for applications such as spacecraft. Additionally, the effects of liquid water accumulation in the porous layers on reactant transport and cell performance are investigated. [ABSTRACT FROM AUTHOR]

Due to extensive irrigation and successive drought periods, most aquifers of north Morocco are overexploited. Soil-water characteristic curve and soil hydraulic properties are important for agricultural water management and modeling of the water flow in unsaturated soils. The experimental determination of some of these parameters in the laboratory or in-situ requires expensive equipment and time consuming. The main objective of this work is to predict the water distribution process in unsaturated soil, based, on the one hand, on the hydrodynamic parameters ( , , , , ) and, on the other hand, by using the two-dimensional numerical software Hydrus-2D model, from in situ measurements of cumulative infiltration and water content. The experimental tests were carried out in the experimental station of the M'nasra area located in the north of Morocco by using the disc infiltrometer which allows measuring the infiltration flow in the soil. The results obtained from this estimation of the parameters allow simulating and controlling the evolution of water flow and solute transport in the unsaturated zone. Furthermore, the results of the statistical analysis have also shown the feasibility of the Hydrus-2D to simulate the movements of water in the vadose zone. [ABSTRACT FROM AUTHOR]

There is limited existing research that identifies the optimum rehabilitation strategy, taking utility decision-makers' risk attitudes into account. The objective of this study is to detect the critical pipes of a water distribution network (WDN) for rehabilitation, maximizing the post-earthquake serviceability of the WDN while minimizing the risk of choosing a specific rehabilitation strategy. For that purpose, a multi-objective optimization framework is formulated. System Serviceability Index (SSI) is quantified to represent the serviceability of a WDN after an earthquake. One of the two objective functions in the optimization problem maximizes the expected SSI value. The second objective function minimizes the value at risk (VaR) or conditional value at risk (CVaR) of the decision-making. The solution methodology comprises five steps: pipe seismic repair rate calculation, hydraulic modeling, and analysis, Monte Carlo simulation, nondominated sorting genetic algorithm (NSGA) for optimization, and nondominated or Pareto-optimal rehabilitation strategies identification. The proposed approach is applied to a WDN to demonstrate its effectiveness. The proposed approach offers a range of nondominated or Pareto-optimal rehabilitation strategies facilitating the decision-making based on tradeoffs between post-earthquake serviceability and risk within a specific budget limit. The proposed approach outperforms existing methods by providing risk-averse decision-makers with a set of optimal rehabilitation strategies with known risk levels. [ABSTRACT FROM AUTHOR]

Highlights: A method to investigate water consumption based on pressure data is developed. The method exploits the headloss-flowrate equation to obtain water-consumption data. The method is validated on a real case study, resulting in an average error of 2.3%. Limitations affecting the installation of domestic flow meters are overcome. Insights into the features of individual water-consumption events are provided. In the era of digital transformation of water distribution networks, an increasingly important role is played by smart metering technologies, which allow detailed characterization of water consumption up to the end-use (i.e., domestic-fixture) level. To this end, smart flow meters make the collection of water-consumption data at high temporal resolution possible, but their installation can be unfeasible due to technical and economic limitations. As an alternative to the traditional flow-measurement-based methods for end-use characterization, a pragmatic method to obtain information about end-use water consumption exclusively based on pressure data is proposed in this study. In particular, a dual-phase methodology is developed, exploiting (i) pressure data collected at two sections of the user's inlet pipeline and (ii) the pressure-flowrate relationship to discriminate between internal and external water-use events and estimate the household water-consumption time series, which is then subjected to individual-event analysis. The results obtained on a real case study undergone to 1-s resolution pressure monitoring over about one month and a half confirm the method's effectiveness in obtaining the flowrate time series with an average error of about 2.3% and successfully identifying water-consumption events along with their features. [ABSTRACT FROM AUTHOR]

In South Korea, performance of irrigation systems can be improved through hardware changes, such as canal linings and the installation of control structures, as well as through operational improvements, such as proper and timely operation, and improved communication between water supply agencies and water users. Improving irrigation water delivery performance through canal networks is one of the most economically essential options in meeting growing water demands and sustaining the productivity of irrigated agriculture. In this study, for the purpose of evaluating the efficient use of water resources in agricultural productions and operations, we analyzed the distribution of amount of water for each irrigated area and irrigation efficiency using a hydraulic-hydrological model, EPA-SWMM (United States Environmental Protection Agency Storm Water Management Model). In addition, we assessed agricultural water supply and water supply vulnerability using irrigation efficiency indicators. As a result of the agricultural water distribution simulation, the canals located in the upstream showed a high irrigation efficiency of more than 60%, and the canals located in the downstream showed a low irrigation efficiency of less than 50%. Based on the results, the critical areas can be successfully identified where water is scarce in the irrigation area and monitoring the spatio-temporal agricultural water distribution can be more effectively realized. [ABSTRACT FROM AUTHOR]

The single-channel-serpentine proton exchange membrane water electrolyzer (PEMWE) has the potential to be a crucial element in the linking of power, transport, heating, and chemical industries in the foreseeable future of sustainable energy systems. Its performance is influenced by a number of factors. Within the many factors affecting their performance, the external operating parameters have a significant effect on the temperature distribution of the internal components as well as the moisture distribution. In this paper, a single-channel-serpentine flow field electrolyzer (SFFE) is built to address the simulation deficiencies of a conventional single-channel proton exchange membrane electrolyzer, and to more intuitively represent the effects of single-channel-serpentine external environmental parameters on the internal performance of the electrolyzer, in order to assess the effects of different voltages, operating temperatures, and inlet flow rates on the distribution of heat, the distribution of liquid water and gases, and the susceptibility to cross-penetration sites. The results show that when the operating voltage drops below 2.2 V, the liquid-saturated water undergoes a greater impact. Specifically, the voltage increase from 1.6 to 2.2 V results in a significant decrease from 0.97 to 0.79, corresponding to an 18.6% drop. That is, when the voltage is 2.2 V, the liquid water content ensures the adequacy of the reaction, while the inhibitory effect of bubble formation occurs at the beginning. Therefore, 338.15 K and 2.2 V are the most recommended experimental conditions. [ABSTRACT FROM AUTHOR]

Currently, more and more lakes around the world are experiencing outbreaks of cyanobacterial blooms, and high-precision and rapid monitoring of the spatial distribution of algae in water bodies is an important task. Remote sensing technology is one of the effective means for monitoring algae in water bodies. Studies have shown that the Floating Algae Index (FAI) is superior to methods such as the Standardized Differential Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) in monitoring cyanobacterial blooms. However, compared to the NDVI method, the FAI method has difficulty in determining the threshold, and how to choose the threshold with the highest classification accuracy is challenging. In this study, FAI linear fitting model (FAI-L) is selected to solve the problem that FAI threshold is difficult to determine. Innovatively combine FAI index and NDVI index, and use NDVI index to find the threshold of FAI index. In order to analyze the applicability of FAI-L to extract cyanobacterial blooms, this paper selected multi-temporal Landsat8, HJ-1B, and Sentinel-2 remote sensing images as data sources, and took Chaohu Lake and Taihu Lake in China as research areas to extract cyanobacterial blooms. The results show that (1) the accuracy of extracting cyanobacterial bloom by FAI-L method is generally higher than that by NDVI and FAI. Under different data sources and different research areas, the average accuracy of extracting cyanobacterial blooms by FAI-L method is 95.13%, which is 6.98% and 18.43% higher than that by NDVI and FAI respectively. (2) The average accuracy of FAI-L method for extracting cyanobacterial blooms varies from 84.09 to 99.03%, with a standard deviation of 4.04, which is highly stable and applicable. (3) For simultaneous multi-source image data, the FAI-L method has the highest average accuracy in extracting cyanobacterial blooms, at 95.93%, which is 6.77% and 13.26% higher than NDVI and FAI methods, respectively. In this paper, it is found that FAI-L method shows high accuracy and stability in extracting cyanobacterial blooms, and it can extract the spatial distribution of cyanobacterial blooms well, which can provide a new method for monitoring cyanobacterial blooms. [ABSTRACT FROM AUTHOR]

Benthic macroinvertebrates play a crucial role in river ecosystems. The cascading dams had altered the characteristics of the river environment, consequently impacting the spatial distribution of these organisms. We compared water physicochemical and benthic macroinvertebrates collected in July 2021 among sites located above and below a series of dams. The impact of high-density cascading dams on benthic macroinvertebrates and physicochemical characteristics were analyzed in the Oujiang River mainstem. Our results revealed a noticeable change in the benthic macroinvertebrates from upstream to downstream in the Oujiang River. Due to the construction of dams, with the increase of water depth, the ecologically sensitive taxa (Ephemeroptera, Plecoptera, Trichoptera) disappeared as we moved from the natural river sections to the upstream sections of the dams. In contrast, Bivalves and Oligochaetes, which are well-suited for still water, exhibited an increasing trend. However, the species number, biomass, and biodiversity index significantly decreased. The downstream sections of dams affected by the discharge of low-temperature water had a relatively low number of Oligochaete species. The CCA analysis revealed that total nitrogen, water depth, and water temperature were the main factors influencing benthic macroinvertebrates in the mainstream of Oujiang River. The contribution rates of these factors were 21.1, 16.4, and 4.5%, respectively. These findings can be valuable for supporting ecological management and biodiversity conservation in mountainous rivers with high-density barrage dams. [ABSTRACT FROM AUTHOR]

After precipitation, reference evapotranspiration (ETO) plays a crucial role in the hydrological cycle as it quantifies water loss. ETO significantly impacts the water balance and holds great importance at the basin level because of the spatial distribution of managing water resources. Large scale teleconnection indices (LSTIs) play a vital role by influencing climatic variables and can be pivotal in determining ETO and its predictive variables. This study aimed to model and forecast annual ETO in Iran's basins by utilizing LSTIs and employing various machine learning models (MLMs) such as least squares support vector machine, generalized regression neural network, multi-linear regression (MLR), and multi-layer perceptron (MLP). Initially, climate data from 122 synoptic stations covering six and 30, main and sub basins were collected, and annual ETO values were computed using the Food and Agriculture Organization 56 (PMF 56) Penman–Monteith equation. The correlations between these values and 37 LSTIs were examined within lead times ranging from 7 to 12 months. Through a stepwise approach, the most influential predictor indices (LSTIs) were selected as input datasets for the MLMs. The findings revealed the significant influence of factors such as carbon dioxide (CO2), Atlantic multidecadal oscillation, Atlantic Meridional Mode, and East Atlantic on annual ETO. Overall, all MLMs performed well in terms of the Scatter Index during both training and testing phases across all sub-basins. Furthermore, the MLP and MLR models displayed superior performance compared to other models in the training and testing evaluations based on various assessment metrics. [ABSTRACT FROM AUTHOR]

Estuaries are generally considered to be important sources of atmospheric CO2. However, the differences between estuaries, and inadequate observations of partial pressure of CO2 in estuarine water (pCO2water) hamper global estuarine CO2 budgeting. In this study, the longitudinal distribution of CO2 in the waters of Modaomen (MSE) and Lingdingyang (LSE), two sub-estuaries of the Pearl River Estuary (PRE), and its influencing mechanism are studied. The change in the distribution of pCO2water along the distance from the upstream estuary to the ocean between LSE and MSE was significantly different. pCO2water at the LSE ranges from 238 to 7267 µatm, whereas the MSE ranges from 406 to 3078 µatm. Stronger microbial respiration and relatively long water retention times were the main influences that led to higher pCO2water at LSE than at MSE. Seasonally, the increase of soil CO2 into the water in the upstream basin caused by precipitation is the potential influencing factor that the water pCO2water in the flood season is higher than in the dry season. PRE was a net source of atmospheric CO2 with an average annual water–air flux of 41.2 ± 33.3 mmol m−2 day−1. Our results suggest that the differences in longitudinal gradients of pCO2water between estuaries in the same region and the effects of different gas transport velocity models on CO2 emission estimates need to be considered in estuarine CO2 emission budgeting. [ABSTRACT FROM AUTHOR]

Drinking water distribution systems must safely meet the expected demand for water. However, sudden pipe breaks can limit the continuous supply of drinking water. As operating pressure is among the factors affecting the probability of pipe breaks, a methodology was developed in this study to identify the pressure covariates that affect the frequency of water distribution pipe breaks. Five pressure covariates obtained from hydraulic simulations based on measured pressure and flow rate time series were evaluated using a likelihood ratio test to compare the maximum likelihood function values of a pipe break model calibrated with no covariates with those of the same model calibrated with a single pressure covariate. This pipe break model was calibrated using the recorded history of pipe breaks over a six-year period and applied to two district metered areas in the water distribution network of Quebec, Canada. The results indicated that the maximum and mean pressure covariates were significantly associated with the occurrence of pipe breaks. [ABSTRACT FROM AUTHOR]

Due to their superior technical and hydraulic performance and minimal environmental impact, porous weirs have emerged as a feasible alternative to traditional impermeable solid weirs in water transmission and distribution systems. This research study assesses the hydraulic performance of porous broad-crested weirs (PBCWs) with sloping crests. To accomplish this, 30 PBCW models were designed and tested under various operating conditions, including free and submerged flow scenarios. A comparative analysis was conducted to evaluate the performance of PBCWs with and without sloping crests, with the results being compared against a solid broad-crested weir (SBCW) model. The findings revealed that PBCWs with an upstream crest slope exhibited an average increase of 38% in the discharge coefficient compared to similar SBCWs. Similarly, PBCWs with a downstream crest slope demonstrated an average increase of 28% in the discharge coefficient. Additionally, PBCWs with sloping crests showcased heightened sensitivity to changes in tailwater levels compared to PBCWs with horizontal crests, with PBCWs featuring an upstream crest slope being more responsive than those with a downstream crest slope. Finally, leveraging extensive experimental data, empirical equations were derived using nonlinear multi-variable regression and gene-expression programming techniques to accurately represent the free flow discharge coefficient and submerged flow discharge reduction factor. [ABSTRACT FROM AUTHOR]