Abstract The water-stressed Barind Tract (BT) in northwest Bangladesh faces critical challenges in meeting irrigation and domestic water demands, with groundwater tables declining at rates of 0.09–0.39 m per year due to over-extraction and limited natural recharge through thick clay aquitards (21–39 m). This study evaluates the potential for managed aquifer recharge (MAR) potential across three districts of BT (Godagari, Niamatpur and Mohanpur) using integrated horizontal flow treatment units. We analyzed 376.68 km of re-excavated Kharies (natural canals) and 257.01 acres of Beels (water reservoirs), incorporating seventeen years (2005–2021) of groundwater monitoring data and nineteen years of rainfall analysis (2002–2020). Field-verified recharge rates of 29 L/min for Kharies and 162.7 L/min for Beels were used to calculate potential MAR installations using the rational formula. Our analysis identified 3,315 feasible MAR installation sites (3,251 in Kharies: Godagari-966, Niamatpur-2276, Mohanpur-9; and 64 in Beels: Godagari-4, Niamatpur-14, Mohanpur-46), capable of recharging 27.10 million m3 annually from 50.61 million m3 of surface runoff, achieving 53.5% utilization efficiency. Groundwater monitoring showed declines of 6.6 m in Godagari, 5.24 m in Niamatpur, and 1.6 m in Mohanpur over the study period. Annual rainfall averaged 1231 mm, 1414 mm, and 1132 mm respectively, with 90% occurring during May–October monsoon periods. Performance monitoring of existing MAR installations demonstrated successful water quality maintenance within national drinking water standards (ECR 2023), with parameters including calcium (59.03–63.87 mg/L), iron (0.58–0.86 mg/L), and pH (7.26–7.29) remaining within acceptable limits while achieving groundwater level improvements up to 2.01 m. The integrated treatment units overcame natural recharge limitations of 2–3 mm/day through thick clay aquitards, achieving 10,000-fold improvement in infiltration rates. This assessment provides a scalable and replicable methodology for sustainable groundwater management strategies in water-stressed regions globally, with phased implementation of identified MAR installations offering a pathway to reverse groundwater depletion trends.
Abstract Composite fouling, arising from microbial and inorganic interactions, compromises the reliability of reclaimed-water distribution systems. We evaluated permanent magnetic fields (PMF; 300–800 mT) and electromagnetic fields (EMF; AC and pulsed DC) in a full-scale reclaimed-water distribution loop. Under the tested conditions, EMF—particularly pulsed DC—reduced total foulant mass by up to 51.7% (p < 0.05) and was associated with lower biofilm biomass, mineral scaling, and particulate accumulation. 16S rRNA profiling indicated co-occurring declines in community diversity and simpler co-occurrence networks under EMF. X-ray diffraction indicated a relative enrichment of aragonite (vs. calcite) and decreases in dolomite and quartz within deposits across all magnetic-field treatments. Field-induced oxidative conditions and interfacial changes were consistent with processes that may hinder microbial attachment and crystal nucleation. Collectively, the results suggest that EMF can outperform PMF for composite-fouling control in reclaimed-water systems and motivate optimization of field strength and waveform and validation across additional water qualities and hydraulics.
Amin Mohammadpour, Ehsan Gharehchahi, Mohammadali Baghapour
et al.
Abstract Water quality is a crucial index of human health and environmental sustainability. The present study aimed to apply deterministic, probabilistic, and ML techniques, such as RF, DT, KNN, XGB, SVR, and GB, to classify the water quality in the southern region of Iran. The levels of TDS and alkalinity exhibited the greatest deviation from the standards set by the EPA, WHO, and BIS. The WQI findings revealed that 88.30% of the data were classified as excellent or good quality when employing the deterministic method. Conversely, 97.77% fell within these categories when the Monte Carlo simulation approach was used. The models were meticulously assessed using a set of statistical metrics, including R2, MAE, RMSE, MSE, and PREI. The results show that the RF and XGB were highly effective in predicting WQI. The factors influencing the WQI, identified by RF and XGB methodologies and based on MLP, were TDS and SO4 2− within the study area. According to the Piper diagram, the predominant groundwater type in the study region was HCO₃−–Na⁺, influenced by seawater intrusion, geological properties, and human activities. The deterministic method showed that the HI values exceeded the threshold of 1 in 51%, 2.13%, and 2.13% of the samples for children, teenagers, and adults, respectively. In contrast, the Monte Carlo simulation approach indicated that the HI values exceeding 1 were 34.8% for children, 2.9% for teenagers, and 0.4% for adults. Moreover, the HI was significantly affected by fluoride concentration, ingestion rate, and their interaction. The study's findings emphasized sustainable water management in this area.
Abstract This study presents a comprehensive analysis of flood hazard mapping in Ankara, the capital of Türkiye, highlighting the critical vulnerability of this major urban center to climate-related disasters. By applying advanced boosting algorithms—specifically, XGBoost, GradientBoost, and CatBoost—along with hyperparameter optimization through the Fick’s law algorithm (FLA), this research introduces an innovative methodology aimed at improving the reliability and accuracy of flood hazard assessments in Ankara’s urban landscape. The analysis utilizes an extensive dataset that integrates topographic, meteorological, hydrological, and anthropogenic variables to provide critical insights into the dynamics of urban flooding with a focus on Ankara’s vulnerability. This approach is novel in that it incorporates FLA for hyperparameter optimization, marking a significant advancement in flood hazard modeling and achieving higher model accuracy and generalizability. Notably, among the various determinants of flood hazard identified, elevation emerges as the most influential factor affecting flood risk in Ankara. This finding underscores the complex relationship between urban geography and flood hazards, and highlights the need for targeted urban planning and infrastructure development strategies to effectively mitigate flood risk. The implications of this research extend beyond the local setting, contributing valuable insights to the global discourse on climate change adaptation and urban resilience. By combining cutting-edge machine learning techniques with in-depth geographic analysis, this study offers a scalable and innovative model for flood hazard assessment and management, providing a critical tool for cities around the world facing similar challenges.
Networked urban systems facilitate the flow of people, resources, and services, and are essential for economic and social interactions. These systems often involve complex processes with unknown governing rules, observed by sensor-based time series. To aid decision-making in industrial and engineering contexts, data-driven predictive models are used to forecast spatiotemporal dynamics of urban systems. Current models such as graph neural networks have shown promise but face a trade-off between efficacy and efficiency due to computational demands. Hence, their applications in large-scale networks still require further efforts. This paper addresses this trade-off challenge by drawing inspiration from physical laws to inform essential model designs that align with fundamental principles and avoid architectural redundancy. By understanding both micro- and macro-processes, we present a principled interpretable neural diffusion scheme based on Transformer-like structures whose attention layers are induced by low-dimensional embeddings. The proposed scalable spatiotemporal Transformer (ScaleSTF), with linear complexity, is validated on large-scale urban systems including traffic flow, solar power, and smart meters, showing state-of-the-art performance and remarkable scalability. Our results constitute a fresh perspective on the dynamics prediction in large-scale urban networks.
This article presents applied research on line balancing within the modern garment industry, focusing on the significant impact of intelligent hanger systems and hanger lines on the stitching process, by Lean Methodology for garment modernization. It explores the application of line balancing in the modern garment industry, focusing on the significant impact of intelligent hanger systems and hanger lines on the stitching process. It aligns with Lean Methodology principles for garment modernization. Without the implementation of line balancing technology, the garment manufacturing process using hanger systems cannot improve output rates. The case study demonstrates that implementing intelligent line balancing in a straightforward practical setup facilitates lean practices combined with a digitalization system and automaton. This approach illustrates how to enhance output and reduce accumulated work in progress.
AbstractThis paper investigates the suitability of groundwater for domestic and agricultural use in the Rafsanjan plain, southwest part of the Daranjir–Saghand basin, Iran. Fifty-five groundwater samples were collected and analyzed by six methods including the water quality index (WQI), Schoeller diagram, irrigation water quality (IWQ) parameters, Piper diagram, US salinity diagram and Wilcox diagram. The spatial distribution maps of chemical parameters and groundwater quality indices were plotted using the IDW method in GIS. The results showed a low concentration of major ions in the southeastern part and a high concentration from the central part towards northwestern part of the plain. The concentration of major ions in groundwater was strongly affected by groundwater flow, geological setting and the existence of the evaporative layers in the studied area. Moreover, results revealed that most of samples exceeded the acceptable limits recommended by the WHO and ISIRI1053 standards for domestic and agricultural purposes. In most of the wells, groundwater was classified into saline and very hard categories. The analyses based on WQI values indicated that above 87% of water samples were unsuitable for drinking purposes. IWQ parameters expressed that 85%, 67%, 32%, 51%, 43% and 50% of samples had EC > 3000, Na% > 60%, MAR > 50%, KR > 1, SAR > 9 and Cl− > 350, respectively, which were unsuitable for irrigation use. The dominant hydrochemical facies of water was Na–Cl–SO4 type, and 63% and 22.8% of samples were categorized as C4S4 and C4S3 class, with very high-salinity–high-sodium hazards and very high-salinity–high-sodium hazards, respectively. It indicated that most irrigated lands in this study area were affected by different levels of salinity and sodicity hazards that caused decreases in plant growth and crop productivity. The results can assist decision-makers and planners in prioritizing groundwater resources management in the region.
Neda Bagherlou, Elnaz Ghasemi, Parvin Gharbani
et al.
Abstract This study presents the preparation of SiO2/g-C3N5@NiFe2O4 nanophotocatalyst for the removal of betamethasone from aqueous solutions. The SiO2/g-C3N5@NiFe2O4 nanophotocatalyst was synthesized using the solvothermal method, and its structure and optical properties were characterized and confirmed through XRD, FESEM, EDX, DRS, BET, VSM and PL analysis. Photocatalytic removal of betamethasone was optimized using a central composite design. The band gap of pure g-C3N5, NiFe2O4, and SiO2/g-C3N5@NiFe2O4 was obtained 2.4 eV, 2.7 eV, and 1.4 eV, respectively using the Tauc plot. The F-value of 909.88 and Lack of Fit F-value of 0.41 confirm the obtained model is significant. Also, the value of R 2 = 0.9988 along with R 2adja = 09977 demonstrates excellent model performance. Maximum removal efficiency of betamethasone was approximately 87.15% under the following optimal conditions: nanophotocatalyst dosage of 0.005 g/50 mL, a betamethasone concentration of 20 mg/L, and an irradiation time of 40 min under visible light. This performance closely aligns with the actual value of 80.65%. In conclusion, the SiO2/g-C3N5@NiFe2O4 nanophotocatalyst demonstrates excellent photocatalytic ability for the removal of betamethasone from aqueous solutions.
Saanu Emmanuel Kosemani, Oluwadamilare Emmanuel Obayemi, Oluwafisayo Ayodeji
et al.
Abstract This study highlights the importance of managing fishpond effluent to minimize its impact on aquatic environments. Fish effluents are a major concern worldwide in aquatic environments. It also provides information on the impacts of effluents on the water quality index of streams when released into aquatic environments. Streams and fishponds were sampled bimonthly for two annual cycles, covering different sampling stations both upstream and downstream of the fishpond effluents at 50-m intervals. Water quality parameters associated with in situ conditions were determined in the field. In the laboratory, other physicochemical parameters were determined via proper standard protocols. The results of the study revealed that water quality parameters such as turbidity, total suspended solids, total solids, conductivity, total dissolved solids, dissolved oxygen, biological oxygen demand and organic matter recorded in water samples collected from 50 m upstream at the point of effluent discharge were significantly (p < 0.05) different from those recorded at other sampling stations. The WQI value of the discharge point was higher than the WQI recorded in both the upstream and downstream sections of the stream. The findings of this study showed that the point of discharge of fishpond effluents is particularly concerning for the receiving stream compared with other sampling points. This localized area has experienced marked deterioration in water quality, posing significant threats to the health and biodiversity of aquatic ecosystems. The effluent's impact, though slight when dispersed in the receiving waterbody, underscores the necessity for adequate management practices to mitigate its adverse effects. Effective strategies, including regular monitoring, effluent treatment, and sustainable pond management, are imperative to ensure the long-term health and resilience of the aquatic environment.
Water supply for domestic and industrial purposes, Environmental sciences
We consider the problem of reconstructing the seabed topography from observations of surface gravity waves. We formulate the problem as a classical inverse scattering problem using the mild-slope equation, and analyze the topographic dependence of the forward and inverse problem. Moreover, we propose a useful model simplification that makes the inverse problem much more tractable. As water waves allow for observations of the full wave field, it differs quite a lot from the classical inverse scattering problems, and we utilize this to prove a conditional stability result for the inverse problem. Last, we develop a simple and fast numerical inversion method and test it on synthetic data to verify our analysis.
This paper investigates how the granularity of supply-chain data affects the propagation of economic shocks through production networks. Using newly constructed establishment-level supply chains with product-level information links for Japan, we simulate disruption dynamics under alternative definitions of network nodes and input classifications. We show that defining inputs at the product level generates substantially larger propagation effects than industry-based classifications, indicating that coarse industry measures overstate input substitutability and underestimate systemic vulnerability. While establishment-level networks generally amplify shock propagation relative to firm-level networks, this effect is quantitatively modest, reflecting opposing forces of increased network complexity and greater substitution possibilities. We further demonstrate that incorporating establishment-level geographic information is critical for assessing region-specific shocks, as firm-level networks tend to overstate the impact of shocks originating in major metropolitan areas. Overall, our results highlight the importance of granular information on products, establishments, and geography for accurately evaluating supply-chain resilience and systemic risk.
Katarzyna Kołodziej, Michał Cholewa, Przemysław Głomb
et al.
Calibration is a critical process for reducing uncertainty in Water Distribution Network Hydraulic Models (WDN HM). However, features of certain WDNs, such as oversized pipelines, lead to shallow pressure gradients under normal daily conditions, posing a challenge for effective calibration. This study proposes a calibration methodology using short hydrant trials conducted at night, which increase the pressure gradient in the WDN. The data is resampled to align with hourly consumption patterns. In a unique real-world case study of a WDN zone, we demonstrate the statistically significant superiority of our method compared to calibration based on daily usage. The experimental methodology, inspired by a machine learning cross-validation framework, utilises two state-of-the-art calibration algorithms, achieving a reduction in absolute error of up to 45% in the best scenario.
The technical evolution of domestic multi-functional electricity meter is deeply discussed. With the rapid development of the domestic power market and the continuous innovation of technology, the domestic multi-functional electricity meters have experienced the transformation from simple billing to complex multi-functional, from a single application to a wide range of fields. This transformation has not only driven the rapid development of electricity meter technology, but also met the increasing power demand and management requirements. This paper expounds the concept of multi-function meter, the working principle and algorithm of digital multiplier, the initiation and evolution of multi-function electricity meter standard, and the initiation and evolution of domestic multi-function electricity meter products. Although the domestic independent production of multi-functional meter has made great achievements in performance, but in the reliability and key process technology still need to be improved. In addition, the development of communication technology also provides a new opportunity for the progress of electricity meter technology. The application of the new technology provides a more convenient and efficient way for the data transmission and remote management of electricity meters. Domestic multi-functional electricity meters have made remarkable achievements in technology evolution and application and expansion, but they still face some challenges and opportunities. In the future, with the continuous development of the power market and the promotion of smart grid construction, domestic multi-functional electricity meters need to continue to strengthen technological innovation and product research and development, improve the reliability and competitiveness of products, in order to meet higher application needs and market requirements.
Alexander Windmann, Philipp Wittenberg, Marvin Schieseck
et al.
In Industry 4.0, Cyber-Physical Systems (CPS) generate vast data sets that can be leveraged by Artificial Intelligence (AI) for applications including predictive maintenance and production planning. However, despite the demonstrated potential of AI, its widespread adoption in sectors like manufacturing remains limited. Our comprehensive review of recent literature, including standards and reports, pinpoints key challenges: system integration, data-related issues, managing workforce-related concerns and ensuring trustworthy AI. A quantitative analysis highlights particular challenges and topics that are important for practitioners but still need to be sufficiently investigated by academics. The paper briefly discusses existing solutions to these challenges and proposes avenues for future research. We hope that this survey serves as a resource for practitioners evaluating the cost-benefit implications of AI in CPS and for researchers aiming to address these urgent challenges.
Naser Mehrdadi, Afshin Takdastan, laleh Khosravipour
et al.
Nowadays, the contamination of water resources with antibiotics are known as one of the major pollutants in the environment due to their widespread use, toxicity, causing drug resistance, and lasting effects. This study was designed to evaluate the efficiency of the advanced oxidation process of sodium persulfate activated with steel industry slag in the presence of ultraviolet rays, solution temperature, and pH aimed at eliminating the Azithromycin antibiotic from aqueous and effluent media. In the present study, the effect of the variables, including pH, solution temperature, reaction time, initial concentration of antibiotics, sodium persulfate concentration, and UV ray intensity was examined on the process efficiency. A High-Performance Liquid Chromatography (HPLC) machine was also used to measure the concentration of the Azithromycin antibiotic. According to the study results, under optimal and certain conditions in which sodium persulfate: 2 mM, pH: 2, iron ions level in the steel industry slag: 0.4 g/l, UV intensity: 8 watts, and during 60 minutes, the elimination efficiency rates of Azithromycin antibiotic, COD, and TOC were obtained as 91%, 57/4%, and 43/8%, respectively with a mineralization level higher than 55%. The rate of Azithromycin antibiotic removal was directly related to the concentrations of iron ions, sodium persulfate, UV intensity, and the temperature. However, increase in the pH from 2 to 10 led to decrease in the process efficiency from 81% to 43%, and enhance in the initial concentration of Azithromycin antibiotic from 5 to 50 mg/l also reduced the removal rate of the antibiotic from 73% to 43%. The research revealed that the advanced oxidation process of sodium persulfate activated by steel industry slag in the presence of ultraviolet rays can be used as a proper method with high efficiency to eliminate the high concentration of antibiotics found in a real sewage sample.
Chisato Nishimagi, Masami Yanagihara, Yiming Fang
et al.
Recently, microplastic (MP) contamination of the aquatic environment has been reported. Marine MP pollution (especially terrestrial-sourced MPs derived from vehicle tires) is considered a global problem because marine organisms may ingest toxic substances. In this study, we analyzed the generation and occurrence of tire-derived MPs (TMPs) that originate from tire dust on roadways and also focused on driving behavior. The results suggested that the number of TMPs increased in proportion to the increase in traffic volume within the range of 10,000–30,000 vehicles/day. The influence of driving behavior was explored by comparing the number of TMPs at distances of 30, 50 and 70 m from the stop line and by assuming a difference in braking behavior. Traffic video was recorded in conjunction with sampling and was analyzed in parallel with the TMPs. The results demonstrated that brakes were applied for an acceleration rate of over −10 m/s2 at distances of 60 and 80 m from the stop line, which resulted in an approximate increase of 28% in the number of TMPs at approximately 70 m. With these results, it can be concluded that the number of TMPs increases due to the traffic volume and braking behavior.
HIGHLIGHTS
The number of MPs tended to increase with the traffic volume.;
Tire dust increased after rainfall and reached a plateau after a certain period.;
Braking affected the number of MPs, as suggested by vehicle behavior analysis.;
River, lake, and water-supply engineering (General), Water supply for domestic and industrial purposes
Fikret Basic, Christian Steger, Christian Seifert
et al.
With the advent of clean energy awareness and systems that rely on extensive battery usage, the community has seen an increased interest in the development of more complex and secure Battery Management Systems (BMS). In particular, the inclusion of BMS in modern complex systems like electric vehicles and power grids has presented a new set of security-related challenges. A concern is shown when BMS are intended to extend their communication with external system networks, as their interaction can leave many backdoors open that potential attackers could exploit. Hence, it is highly desirable to find a general design that can be used for BMS and its system inclusion. In this work, a security architecture solution is proposed intended for the communication between BMS and other system devices. The aim of the proposed architecture is to be easily applicable in different industrial settings and systems, while at the same time keeping the design lightweight in nature.
In this paper, we give the first rigorous justification of the Benjamin-Ono equation as an internal water wave model on the physical time scale. Let $\varepsilon$ be the small parameter measuring the weak nonlinearity of the waves, $μ$ be the shallowness parameter, and $γ\in (0,1)$ is the ratio between the densities of the two fluids. To be precise, we first prove the existence of a solution to the internal water wave equations for a two-layer fluid with surface tension, where one layer is of shallow depth and the other is of infinite depth. The existence time is of order $\mathcal{O}(\frac{1}{\varepsilon})$ for a small amount of surface tension such that $\varepsilon^2 \leq\mathrm{bo}^{-1} $ where $\mathrm{bo}$ is the Bond number. Then, we show that these solutions are close, on the same time scale, to the solutions of the BO equation with a precision of order $\mathcal{O}(μ+ \mathrm{bo}^{-1})$. In addition, we provide the justification of new equations with improved dispersive properties, the Benjamin equation, and the Intermediate Long Wave (ILW) equation in the deep-water limit. The long-time well-posedness of the two-layer fluid problem was first studied by Lannes [Arch. Ration. Mech. Anal., 208(2):481-567, 2013] in the case where both fluids have finite depth. Here, we adapt this work to the case where one of the fluid domains is of finite depth, and the other one is of infinite depth. The novelties of the proof are related to the geometry of the problem, where the difference in domains alters the functional setting for the Dirichlet-Neumann operators involved. In particular, we study the various compositions of these operators that require a refined symbolic analysis of the Dirichlet-Neumann operator on infinite depth and derive new pseudo-differential estimates that might be of independent interest.
Ports are striving for innovative technological solutions to cope with the ever-increasing growth of transport, while at the same time improving their environmental footprint. An emerging technology that has the potential to substantially increase the efficiency of the multifaceted and interconnected port processes is the digital twin. Although digital twins have been successfully integrated in many industries, there is still a lack of cross-domain understanding of what constitutes a digital twin. Furthermore, the implementation of the digital twin in complex systems such as the port is still in its infancy. This paper attempts to fill this research gap by conducting an extensive cross-domain literature review of what constitutes a digital twin, keeping in mind the extent to which the respective findings can be applied to the port. It turns out that the digital twin of the port is most comparable to complex systems such as smart cities and supply chains, both in terms of its functional relevance as well as in terms of its requirements and characteristics. The conducted literature review, considering the different port processes and port characteristics, results in the identification of three core requirements of a digital port twin, which are described in detail. These include situational awareness, comprehensive data analytics capabilities for intelligent decision making, and the provision of an interface to promote multi-stakeholder governance and collaboration. Finally, specific operational scenarios are proposed on how the port's digital twin can contribute to energy savings by improving the use of port resources, facilities and operations.
<p>In Canada, more than 80% of energy in the residential sector is used for space heating and domestic hot water (DHW) production. This study aimed to model and compare the performance of four different systems, using solar energy as a renewable energy source for DHW production. A novel microchannel (MC) solar thermal collector and a microchannel-based hybrid photovoltaic/thermal collector (PVT) were fabricated (utilizing a microchannel heat exchanger in both cases), mathematical models were created, and performance was simulated in TRNSYS software. A water-to-water heat pump (HP) was integrated with these two collector-based solar systems, namely MCPVT-HP and MCST-HP, to improve the total solar fraction. System performance was then compared with that of a conventional solar-thermal-collector-based system and that of a PV-resistance (PV-R) system, using a monocrystalline PV collector. The heat pump was added to the systems to improve the systems’ efficiency and provide the required DHW temperatures when solar irradiance was insufficient. Comparisons were performed based on the temperature of the preheated water storage tank, the PV panel efficiency, overall system efficiency, and the achieved solar fraction. The microchannel PVT-heat pump (MCPVT-HP) system has the highest annual solar fraction among all the compared systems, at 76.7%. It was observed that this system had 10% to 35% higher solar fraction than the conventional single-tank solar-thermal-collector-based system during the wintertime in a cold climate. The performance of the two proposed MC-based systems is less sensitive than the two conventional systems to collector tilt angle in the range of 45 degrees to 90 degrees. If roof space is limited, the MCPVT-HP system is the best choice, as the MCPVT collector can perform effectively when mounted vertically on the facades of high-rise residential and commercial buildings. A comparison among five Canadian cities was also performed, and we found that direct beam radiation has a great effect on overall system solar faction.</p>