Abstract This study evaluated physicochemical parameters and heavy metal contamination in the Dehloran watershed during the dry (September 2020) and wet (March 2021) seasons. Surface water samples (n = 62) were selected based on natural conditions and river accessibility, and groundwater samples (n = 10) were collected from low-lying areas. Physicochemical parameters covering organic load, ionic composition, nutrients, and salinity (e.g., BOD, COD, DO, EC, pH, TDS, major cations–anions, and turbidity) and heavy metals (As, Cd, Cr, Cu, Fe, Zn) were analyzed using standard methods and ICP‑MS. Paired t-test revealed significant (p < 0.05) seasonal contrasts: EC, TDS, Ca, Cl, SO4, Cu, Cr, and As were elevated in the dry season, whereas DO, TH, HCO3, and Mg increased during the wet season. Surface water had higher quality (IRWQISC = 36.4) than groundwater (IRWQIGC = 15.5), likely reflecting agricultural and anthropogenic impacts, with better quality observed upstream than downstream. Toxic parameter values were also slightly higher in surface water (IRWQIST = 55.3) than in groundwater (IRWQIGT = 54.3). PCA extracted four principal components in both seasons, dominated by salinity hardness and heavy metal factors. Piper plots revealed Ca–SO4 facies associated with gypsum rich Gachsaran formation and regional sulfur and bituminous springs. Wilcox classification showed over 60% of samples as highly saline, limiting irrigation suitability. Results from the heavy metal evaluation index (HEI) and contamination index (Cd) consistently indicated overall low levels of heavy metal contamination. These findings provide quantitative evidence supporting targeted mitigation and sustainable water resource management in semi-arid basins.
Abstract The growing urgency to transition toward clean energy systems has heightened interest in marine renewable energy (MRE) as a sustainable solution for coastal regions facing environmental degradation from fossil fuel use. This study applies the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method to evaluate and rank MRE options, offshore wind, tidal, and wave energy, based on four key criteria: Efficiency, Cost, Emissions, and Resource Availability. Expert judgment was used to derive weighted preferences, and a structured decision matrix facilitated performance scoring and ranking. The analysis identified Efficiency as the most influential factor, with offshore wind energy emerging as the top alternative due to its strong performance and scalability. The results offer a practical, adaptable framework for supporting energy planning in coastal zones, enabling decision-makers to balance environmental protection and operational feasibility.
David Simchi-Levi, Konstantina Mellou, Ishai Menache
et al.
Supply Chain Management requires addressing a variety of complex decision-making challenges, from sourcing strategies to planning and execution. Over the last few decades, advances in computation and information technologies have enabled the transition from manual, intuition and experience-based decision-making, into more automated and data-driven decisions using a variety of tools that apply optimization techniques. These techniques use mathematical methods to improve decision-making. Unfortunately, business planners and executives still need to spend considerable time and effort to (i) understand and explain the recommendations coming out of these technologies; (ii) analyze various scenarios and answer what-if questions; and (iii) update the mathematical models used in these tools to reflect current business environments. Addressing these challenges requires involving data science teams and/or the technology providers to explain results or make the necessary changes in the technology and hence significantly slows down decision making. Motivated by the recent advances in Large Language Models (LLMs), we report how this disruptive technology can democratize supply chain technology - namely, facilitate the understanding of tools' outcomes, as well as the interaction with supply chain tools without human-in-the-loop. Specifically, we report how we apply LLMs to address the three challenges described above, thus substantially reducing the time to decision from days and weeks to minutes and hours as well as dramatically increasing planners' and executives' productivity and impact.
Large Language Models (LLMs) have recently enabled natural language interfaces that translate user queries into executable SQL, offering a powerful solution for non-technical stakeholders to access structured data. However, one of the limitation that LLMs do not natively express uncertainty makes it difficult to assess the reliability of their generated queries. This paper presents a case study that evaluates multiple approaches to estimate confidence scores for LLM-generated SQL in supply chain data retrieval. We investigated three strategies: (1) translation-based consistency checks; (2) embedding-based semantic similarity between user questions and generated SQL; and (3) self-reported confidence scores directly produced by the LLM. Our findings reveal that LLMs are often overconfident in their own outputs, which limits the effectiveness of self-reported confidence. In contrast, embedding-based similarity methods demonstrate strong discriminative power in identifying inaccurate SQL.
This study aimed to develop Multi-Year Reservoir Operation Model (MYROM) to optimize water allocation in multi-purpose and multi-year reservoir. MYROM relied on Ant Colony Optimization (ACO) method to address non-linear optimization challenges associated with multiple objectives. In addition, water availability in the reservoir was assessed, which was an analysis of constraints in minimizing water shortages at study location. The weighted priority for each type of water use was then obtained from a model that followed ACO method. This priority weighting was carried out to provide an assessment regarding decisions related to water management, particularly in determining the sequence of use for various purposes, such as irrigation, domestic and industrial water supply, or hydroelectric power generation. The model used was tested at Wonorejo multi-purpose Reservoir in East Java, Indonesia using historical water availability and use from 2003 to 2021. The simulation results showed that MYROM succeeded in allocating water through the minimization of shortages by proposing parameters α = 1, β = 2, and ρ = 0.4, with the number of ants (m) = 100 in the water demand variable. In addition, the water demand variable was in the form of hydropower, irrigation needs, and raw water needs with a period of 10 days for the next 5 years. Based on these results, the use of MYROM with specified parameter values could serve as a practical approach to improve the planning of reservoir water allocation operations. In addition, this showed that the performance of future water allocation planning model depended on predicted water availability data.
Hamid Reza Tajdari, Ali Soleymani, Nosratolah Montajabi
et al.
Abstract This study aimed to investigate the effect of salinity and water stress on the physiological and functional characteristics of winter wheat (Triticum aestivum L.) under the foliar application of plant growth regulators (PGRs). The experiment was carried out as a split plot based on a randomized complete block design with three replications in two environments. In each environment, water stress at two irrigation levels (after 90 and 120 mm of pan evaporation) and with two EC of 1.5 and 10 dS/m in the main plots and spraying of PGRs including salicylic acid (SA), gibberellic acid (GA3), and cytokinins (CK) (purine) content with a concentration of 100 ppm and the control treatment (spraying solution with normal water) were placed in subplots. Results indicated that all treatments caused significant increases in functional and qualitative characteristics and yield of Triticum aestivum L. The saline environment and irrigation level after 120 mm of pan evaporation caused a reduction in grain yield in all traits except for seed proline, seed nitrogen content, and seed protein content. Also, the combined foliar application of GA3 + CK + SA increased yield in most traits. The highest RWC of flag leaves was observed in the foliar application of GA3 + SA (3.36 kg/ha) and then in the foliar application of GA3 + SA + CK (57.87 kg/ha). GA3 interacts with PGR spraying to balance another development under saline and non-saline conditions.
Qianyao Si, Higor C. Brito, Priscila B. R. Alves
et al.
Abstract Rapid urbanization and escalating climate change impacts have heightened stormwater-related concerns (e.g., pluvial flooding) in cities. Understanding catchment dynamics and characteristics, including precise catchment mapping, is essential to accurate surface water monitoring and management. Traditionally, topography is the primary data set used to model surface water flow dynamics in undisturbed natural landscapes. However, urban systems also contain stormwater drainage infrastructure, which can alter catchment boundaries and runoff behavior. Acknowledging both natural and built environmental influences, this study introduces three GIS-based approaches to enhance urban catchment mapping: (1) Modifying DEM elevations at inlet locations; (2) Adjusting DEM elevations along pipeline paths; (3) Applying the QGRASS plug-in to systematically incorporate infrastructure data. Our evaluation using the geographical Friedman test (p > 0.05) and Dice Similarity Coefficient (DSC = 0.80) confirms the statistical and spatial consistency among the studying methods. Coupled with onsite flow direction validation, these results support the feasibility and reliability of integrating elements of nature and built infrastructure in urban catchment mapping. The refined mapping approaches explored in this study offer improved and more accurate and efficient urban drainage catchment zoning, beyond using elevation and topographic data alone. Likewise, these methods bolster predictive stormwater management at catchment scales, ultimately strengthening urban stormwater and flooding resilience.
Water supply for domestic and industrial purposes, Environmental sciences
Alberto Zaragoza, Rajat Kumar, Jose Martín Roca
et al.
Glycerol acts as a natural cryoprotectant by depressing the temperature of ice nucleation and slowing down the dynamics of water mixtures. In this work we characterize dynamics -- diffusion, viscosity, and hydrogen-bond dynamics -- as well as density anomaly and structure of water mixtures with 1\% to 50\% w/w glycerol at low temperatures via molecular dynamics simulations using all-atom and coarse-grained models. Simulations reveal distinct violations of the Stokes-Einsten relation in the low temperature regime for water and glycerol. Deviations are positive for water at all concentrations, and positive for glycerol in very dilute solutions but turning negative in concentrated ones. The all-atom and coarse-grained models reveal an unexpected crossover in the dynamics of the 1% and 10 % w/w glycerol at the lowest simulated temperatures. This crossover manifests in the diffusion coefficients of water and glycerol, as well as in the viscosity and lifetime of hydrogen-bonds in water. We interpret that the crossover originates on the opposing dependence with glycerol concentration of the two factors controlling the solution's slow-down: the increase in tetrahedrally coordinated water and the dynamics and clustering of the glycerol molecules. We anticipate that this dynamic crossover will also occur for solution of water with other polyols.
Francisco de Arriba-Pérez, Silvia García-Méndez, Javier Otero-Mosquera
et al.
New technologies such as Machine Learning (ML) gave great potential for evaluating industry workflows and automatically generating key performance indicators (KPIs). However, despite established standards for measuring the efficiency of industrial machinery, there is no precise equivalent for workers' productivity, which would be highly desirable given the lack of a skilled workforce for the next generation of industry workflows. Therefore, an ML solution combining data from manufacturing processes and workers' performance for that goal is required. Additionally, in recent times intense effort has been devoted to explainable ML approaches that can automatically explain their decisions to a human operator, thus increasing their trustworthiness. We propose to apply explainable ML solutions to differentiate between expert and inexpert workers in industrial workflows, which we validate at a quality assessment industrial workstation. Regarding the methodology used, input data are captured by a manufacturing machine and stored in a NoSQL database. Data are processed to engineer features used in automatic classification and to compute workers' KPIs to predict their level of expertise (with all classification metrics exceeding 90 %). These KPIs, and the relevant features in the decisions are textually explained by natural language expansion on an explainability dashboard. These automatic explanations made it possible to infer knowledge from expert workers for inexpert workers. The latter illustrates the interest of research in self-explainable ML for automatically generating insights to improve productivity in industrial workflows.
Budi Heri Pirngadi, Deden Syarifudin, Viera Mustika Octaviani
Subdistrict Bojongsoang and its surroundings are based on the 2016-2036 Bandung Regency Spatial Planning, the designated area where the industry is. Currently, there are 125 existing industries operating. The area is also included in groundwater withdrawal through well artesian on a massive scale, including into the national protected area (CAT: Groundwater Basin) Bandung - Soreang Area. Excessive groundwater extraction poses challenges coupled with significant water demand from society and industry. This will result in deteriorated groundwater conditions that require prompt restoration, having already suffered damage. On the other hand, there is Bojongsoang WWTP, which can treat wastewater at 2800 l/s; meanwhile, at the moment, this capacity processing is utilized about 37-40% or about 100m3/day. This research uses a descriptive method. The research results prove that reusing water from Bojongsoang WWTP could produce raw water for the necessity industry of 300 l/s.
Budi Heri Pirngadi, Deden Syarifudin, Viera Mustika Octaviani
Subdistrict Bojongsoang and its surroundings are based on the 2016-2036 Bandung Regency Spatial Planning, the designated area where the industry is. Currently, there are 125 existing industries operating. The area is also included in groundwater withdrawal through well artesian on a massive scale, including into the national protected area (CAT: Groundwater Basin) Bandung - Soreang Area. Excessive groundwater extraction poses challenges coupled with significant water demand from society and industry. This will result in deteriorated groundwater conditions that require prompt restoration, having already suffered damage. On the other hand, there is Bojongsoang WWTP, which can treat wastewater at 2800 l/s; meanwhile, at the moment, this capacity processing is utilized about 37-40% or about 100m3/day. This research uses a descriptive method. The research results prove that reusing water from Bojongsoang WWTP could produce raw water for the necessity industry of 300 l/s.
Christian Chukwuemeka Nzeanorue, Ogba Samuel Nnana, Shittu Sarah Victoria
et al.
Water is an essential and valuable resource in daily life, making its conservation crucial to prevent adverse effects. Storing water for domestic, industrial, agricultural, and other purposes is particularly important. Safe drinking water is increasingly becoming polluted due to the growing population and their demands for urbanization and industrialization. At the household level, some people leave electric water pumps running and either go to work or sleep, forgetting to turn off the pumps when the water container is full. This highlights the need for a reliable and continuous water supply. IoT plays a significant role in environmental monitoring, particularly in disaster management, early warning systems, and environmental data analytics. One major challenge in urban cities is water management, especially with the rapid growth of urbanization, necessitating sustainable urban development plans. To address these issues, we propose a "Water Level Monitoring System" solution. This paper presents an IoT-based water monitoring system for real-time applications. The system's sensors measure the water level in the tank, and the data is sent to a cloud server, allowing users to view it on a remote dashboard. This system can be used efficiently by both homeowners and industrial users, as well as other water utilities.
Radon (222Rn), an inert gas, is considered a silent killer due to its carcinogenic characteristics. Dhaka city is situated on the banks of the Buriganga River, which is regarded as the lifeline of Dhaka city because it serves as a significant source of the city’s water supply for domestic and industrial purposes. Thirty water samples (10 tap water from Dhaka city and 20 surface samples from the Buriganga River) were collected and analyzed using a RAD H2O accessory for 222Rn concentration. The average 222Rn concentration in tap and river water was 1.54 ± 0.38 Bq/L and 0.68 ± 0.29 Bq/L, respectively. All the values were found below the maximum contamination limit (MCL) of 11.1 Bq/L set by the USEPA, the WHO-recommended safe limit of 100 Bq/L, and the UNSCEAR suggested range of 4–40 Bq/L. The mean values of the total annual effective doses due to inhalation and ingestion were calculated to be 9.77 μSv/y and 4.29 μSv/y for tap water and river water, respectively. Although all these values were well below the permissible limit of 100 μSv/y proposed by WHO, they cannot be neglected because of the hazardous nature of 222Rn, especially considering their entry to the human body via inhalation and ingestion pathways. The obtained data may serve as a reference for future 222Rn-related works.
Hot water supply is a daily necessity for various purposes ranging from industrial to domestic usage. However, the availability of hot water supply is dependent on reliable energy systems to heat the water. The load shedding plan declared the energy crisis in South Africa. Therefore, exploring alternative energy methods for hot water supply is critical, especially renewable energy resources. The use of natural resources such as solar energy to heat water is highly impacted or limited by the resources and environmental conditions existing at the area of interest. The use of the solar water heating system based on Bellville; South Africa was the undertaken study. This study reports on the experimental investigation that was conducted on a 50 L water geyser, which was solar-based. The test rig that was constructed and tested was an active solar water heating system. It was tested over a period of 10 days under the environmental conditions experienced in mid-winter season of South Africa. A 20 tubed evacuated tube collector unit was used, and it was found that in mid-winter of the highest water temperature that the system could reach was above 65 °C and the lowest was 30 °C. Intriguing outputs were found in the study which revealed that, on the days that yield the highest solar irradiation did not necessarily produce the hottest water temperature. Therefore, scrutinizing the impact of other parameters that contributed to the overall water temperature output was necessary. From the tests it was observed that the wind velocity together with other environmental parameters effectively had an impact on the water temperature yield by an evacuated tube system.
The presence of organic, inorganic and biological pollutants in natural water supply are the major indices of water pollution. The application of green nanoparticles in water treatment is one of the promising ways of eradicating these pollutants and providing safe and quality water for domestic, agricultural and industrial purposes. Our research was intended to evaluate the decontamination and disinfecting potentials of C. papaya silver nanoparticles on water and wastewater samples. The green silver nanoparticles were formed using aqueous C. papaya leaf extract and characterized using standard nanotechnological techniques while decontamination and disinfecting potentials of the green silver nanoparticles were examined through physicochemical, heavy metal and bacteriological analysis. The results revealed the spectral and morphological profiles were in conformity with the characteristics of silver nanocrystals. There were significant reductions (P < 0.05) in physicochemical, heavy metal and bacterial qualities of the four water samples at higher (0.5 mg/L) and lower (0.25 mg/L) doses of the green silver nanoparticles and their decontamination and disinfection efficiencies were comparable to the positive control calcium hypochlorite. These findings suggest that C. papaya silver nanoparticles could be exploited in restoring the quality of water and wastewater.
Water is an important resource on the surface of the earth. Some areas however have low supply and consumption of water than the others. In some cities across the world, water scarcity has become a serious challenge which residents undergo on daily basis. Therefore, this study investigated water consumption across different wards in Minna Town, Niger State, Nigeria. The study used multistage cluster sampling methods of different wards where 400 questionnaires were administered and interviews conducted. The result showed that most residents in Minna Town used the water supply for domestic purposes than industrial and agriculture purposes. Kpakungu (17.8%) had the highest domestic use of water. However, Limawa B, Soje and Kpakungu with 12.5% each were the three wards with the highest rates of industrial water consumption. Nasarawa B (29%) and Soje (15%) had the highest consumption of water supply for agricultural purposes. It was found that high density areas had the highest consumption rate of water and the Chanchaga Water Board could not adequately supply the required quantities of water for Minna residents. Therefore, the study has recommended that the government and city planners should improve water supply, develop and enforce a good water management framework that will meet the water needs of Minna residents without further delay.