Water Quality Analysis Research Articles

Social Media and Artificial Intelligence for Sustainable Cities and Societies: A Water Quality Analysis Use-case

Crowd-sourcing has been widely explored for monitoring and feedback on infrastructure and services, such as air and water quality analysis. However, the traditional methods of crowd-sourcing for feedback and analysis of water quality, such as offline and online surveys, have several limitations, such as the limited number of participants and low frequency due to the labor involved in conducting such surveys. Social media analytics could overcome these challenges by providing a more sustainable and cost- effective water quality monitoring and analysis tool. This paper explores the potential of social media analytics in such applications by proposing a Natural Language Processing (NLP) framework to automatically collect and analyze water-related posts from social media for data-driven decisions. The proposed framework is composed of two components, namely (i) text classification, and (ii) topic modeling. For text classification, we propose a merit-fusion-based framework incorporating several Large Language Models (LLMs) combined in a late fusion method with optimal weights. In topic modeling, we employed the BERTopic library to discover the hidden topic patterns in the water-related tweets. We also analyzed relevant tweets originating from different regions and countries to explore global, regional, and country-specific issues and water-related concerns. We also collected and manually annotated a large-scale dataset, which is expected to facilitate future research on the topic.

Groundwater Quality of the Lower Rio Bravo Aquifer in the Northern Zone of Tamaulipas

Objective: The main objective is to evaluate the quality of groundwater used by the population of the ejidos of Reynosa, Tamaulipas. These wells are used for domestic consumption in rural households and for irrigation of sorghum crops in rainfed agriculture systems. Theoretical Framework: Water supply sources in the northern region of Tamaulipas are experiencing a progressive depletion due to the scarcity of rainfall and the high temperatures characteristic of the region. This challenge is compounded by population growth, which has increased the demand for water. One possible solution to this problem is the exploitation of groundwater resources. However, monitoring activities on the quality of this resource are sporadic, with records dating back to 2006, and in the municipalities of Reynosa and Río Bravo there is almost no culture within the framework of good management practices for sustainable development in the use of groundwater in the lower Río Bravo basin. Method: The approach for the analysis of water quality is carried out in wells located in the northern region of the municipalities of Reynosa and Río Bravo, Tamaulipas, through the linkage with the president of Rural Development District 156 to take samples in wells that are mostly used to supply water to crops and, in some cases, for cleaning activities in farms. Specifically, a detailed physicochemical analysis of the water resource is carried out with the purpose of issuing an opinion on its quality, which will make it possible to determine its potential uses and establish guidelines for sustainable and adequate management in its exploitation. Results and Discussion: In the northern region of the state of Tamaulipas, the use of land for agriculture and the exploitation of the oil industry has been constantly punished. It is a latent fact that agricultural activity represents a significant risk of salinization and groundwater contamination due to the intensive use of agrochemicals. This risk is exacerbated by urban growth, which contributes to water resource contamination through industrial discharges and bacteriological contamination from inadequate wastewater management in population centers. These activities are the main sources of deterioration of groundwater quality and have worsened over time. In addition, the geological context of the region, characterized by stratigraphic formations with natural salinity, further contributes to the complexity of this problem. Research Implications: The results obtained in the development of the project highlight the need for continuous monitoring of economic activities and population growth in the region, to avoid contamination of the aquifer to such levels that for a possible use, specific techniques would have to be implemented that would increase the cost of the water resource, as well as its disposal. Originality/Value: The study of water quality in the aquifer of Río Bravo in the northern region of Mexico represents a considerable challenge, since it is an area affected by problems of insecurity, which makes sampling difficult. However, safe and reliable access to farms and ranches in the area was possible with the cooperation of their owners. This made it possible to carry out adequate sampling and obtain accurate in situ parameters, guaranteeing the veracity of the data obtained.

Protecting the Safe Water Chain in Refugee Camps: An Exploratory Study of Water Handling Practices, Chlorine Decay, and Household Water Safety in South Sudan, Jordan, and Rwanda.

In refugee and internally displaced person settlements, hygienic water handling and free residual chlorine (FRC) are crucial for protecting water against recontamination after distribution up to the household point-of-consumption. We conducted a secondary analysis of water quality and water handling data collected in refugee camps in South Sudan, Jordan, and Rwanda using statistical and process-based modeling to explore how water handling practices affect FRC decay and household FRC outcomes. The two practices that consistently produced a significant effect on FRC decay and household FRC were storing water in direct sunlight and transferring water between containers during household storage. Samples stored in direct sunlight had 0.22-0.31 mg/L lower household FRC and had FRC decay rates between 2 and 3.7 times higher than samples stored in the shade, and samples that were transferred between containers had 0.031-0.51 mg/L lower household FRC and decay rates 1.65-3 times higher than non-transferred samples in sites in which the effect was significant, suggesting that humanitarian responders should aim to provide additional water storage containers to prevent water transferring in households and encourage water-users not to store water in direct sunlight. By contrast, the effect of the three recommended hygienic water handling behaviors (clean, covered containers and drawing by tap or pouring) was mixed or inconclusive. These inconclusive results were likely due to imbalanced or unreliable approaches to gathering the data, and we recommend that hygienic water handling practices that mechanistically provide a physical barrier against recontamination should always be promoted in humanitarian settings.

Management of Broodstock for Pacific White Shrimp (Litopenaeus vannamei) at the Center for Superior Shrimp and Shellfish Broodstock Production (BPIU2K) Karangasem, Bali

Shrimp (Litopenaeus vannamei), as it directly impacts the quality and quantity of larvae produced for aquaculture. This study investigates the management practices at the Center for Superior Shrimp and Shellfish Broodstock Production (BPIU2K) in Karangasem, Bali, focusing on the broodstock selection, breeding, and maintenance processes. The research evaluates the performance of broodstock in terms of growth, reproductive health, and overall productivity, aiming to optimize practices for sustainable shrimp farming. Data was collected through direct observation, water quality analysis, and broodstock health assessments. The findings highlight the importance of proper environmental conditions, nutritional management, and genetic selection in enhancing the reproductive success of L. vannamei. The study also discusses challenges faced by the facility, including disease management and genetic diversity, offering recommendations for improving broodstock management to ensure consistent, high-quality shrimp production. The number of male broodstock in the maintenance tank was around 250, and female broodstock was around 200, with a survival rate of 70%. This research contributes to advancing sustainable aquaculture practices and improving the shrimp farming industry in Indonesia.

Statistical analysis of water quality and cyclone impacts along the south Odisha coast, east coast of India

Water quality along south Odisha coast (25km stretch), east coast of India was studied collecting monthly samples at 10 different sampling stations from June 2008 to March 2011 and June 2012 to May 2017. The samples were analysed for salinity, dissolved oxygen (DO), total suspended solids (TSS) and pH. In addition, river discharge, siltation, rainfall and wind speed data were also collected from 2008 to 2017 at the study region and their impacts on coastal water quality were assessed along with the impacts of cyclonic storms. Anomalies of water quality parameters and their seasonal variability were assessed. Spatio-temporal variation of these parameters and multivariate statistical techniques such as factor analysis, correlation coefficient and, descriptive statistics were applied to the observed datasets. Results indicate that, salinity is positively correlated with wind speed at 0.05 significance level while negatively correlated with river discharge. TSS is positively correlated with siltation at 0.01 significance level. DO values are also positively correlated with strong wind speed. Nutrient driven primary production helps pH to be higher at Rushikulya river mouth during monsoon and post-monsoon as compared to at all other stations. Throughout the year, the study environment remains alkaline. Due to impacts of cyclonic storms, water quality parameters show significant reduction in salinity and enhancement in TSS, DO and pH during the post-cyclone period while the seasonal trend is maintained during the pre-cyclone period. Factor analysis reveals the factors controlling the hydrographic behaviour of seawater. The spatial variation in coastal water quality is very high and dominates over the temporal variation. Importance of coastal water quality assessment in relation to coastal ecosystem and disaster is discussed.

Aqua-stream: an IoT based smart water management system for sustainable living

<p class="03IJISAEAbstract">Aqua-stream, an innovative internet of things (IoT) enabled water management system, utilizes the power of long short-term memory (LSTM) networks, a sophisticated time-series forecasting machine learning technique with Kafka. Aqua-stream seamlessly integrates LSTM within the Kafka streaming architecture for efficient real-time data processing, ensuring quick responses to emerging water management needs. LSTM is employed for real-time anomaly detection, dynamically analyzing streaming data to prevent leaks through automated shut-off valves. The system’s comprehensive dashboard utilizes LSTM insights for live water quality analysis; adaptive scheduling based on individual preferences and personalized recommendations, enhancing cost-effective water management. This streamlined approach extends to the smart gardening system, where LSTM guides automation for optimal plant care incorporating sensors to monitor soil moisture, temperature, and sunlight levels. This system automatically adjusts watering and lighting to ensure optimal conditions for plant growth. Users can control and monitor their garden remotely via a smartphone, facilitating plant care while saving water and energy. Aqua-stream redefines home water management, offering a holistic solution that combines intelligent water conservation with smart gardening for a sustainable and connected living experience. Aqua-stream represents a seamless integration of LSTM-based machine learning and IoT technologies, offering an intelligent, yet simplified, solution for sustainable and connected living.</p>

Assessment of the dynamics of heavy metal contamination in the alluvial aquifer of the Drean plain, El Taref (North-Eastern Algeria) using GIS indices and water quality analysis

The study was conducted to assess the quality of shallow groundwater in the Drean plain, with a focus on the concentration of heavy metals. The indices employed included the water quality index (WQI), heavy metal pollution index (HPI), and metal index (MI). Spatial distribution maps of heavy metals, as well as pollution indices, were developed based on twenty samples. The physicochemical parameters, including T, pH, EC, DO, and TDS, were measured using standard techniques. Heavy metals, including iron (Fe), lead (Pb), zinc (Zn), chromium (Cr), manganese (Mn), and cadmium (Cd), were analysed through spectrophotometry. The average concentrations of Mn, Cr, Cd, and Pb exceeded the World Health Organization (WHO) drinking water standards, with respective values of 0.16 mg/L, 0.06 mg/L, 0.28 mg/L, and 0.38 mg/L. According to the water quality index (WQI), which ranges from 21 to 800, approximately 50% of the water samples was classified as highly polluted and therefore not recommended for consumption. According to the metal index (MI), the average value is 6.77, with 80% classified as highly polluted. The average value of the heavy metal pollution index (HPI) was 2201, indicating that the water in the plain is severely polluted for consumption, with 100% of the samples classified as unfit for consumption. The study underlines the urgency of reducing the health risks to the urban population and recommends continuous monitoring of the area to assess the evolution of the pollution.

Seasonal Dynamics of Caligus clemensi Infestation in European Seabass and Flathead Grey Mullet Integrating Morphological, Molecular, Immunological, and Environmental Perspectives

This case study investigates the seasonal prevalence, morphological characteristics, molecular identity, host immune response, and environmental factors influencing Caligus clemensi infestations in farmed European seabass and flathead grey mullet at a single marine fish farm. A total of 600 fish (400 seabass, 200 mullet) were examined over one year, revealing seasonal fluctuations in parasite prevalence and intensity. C. clemensi infestation peaked in winter for seabass (75% prevalence) and spring for grey mullet (80% prevalence), with notable declines in summer and autumn for both species. Morphological analysis confirmed C. clemensi as the causative agent, exhibiting sexual dimorphism and characteristic features including a quadrilateral cephalothorax and disk-shaped lunules. Molecular characterization of the 18S rRNA gene corroborated the morphological identification, with phylogenetic analysis revealing a well-supported monophyletic clade for C. clemensi within the family Caligidae. Quantitative real-time PCR demonstrated significantly elevated interleukin-1β (IL-1β) expression in infected fish, indicating a robust inflammatory response. Grey mullet and seabass exhibited high IL-1β upregulation. Histopathological examination revealed severe gill tissue damage, vascular changes, and hepatic steatosis in infected fish. Water quality analysis identified several parameters exceeding permissible limits, including total suspended solids (4800-5100 mg/L), total dissolved solids (32000 mg/L), sulfates (2300 mg/L), and chlorides (18000 mg/L). These elevated levels, likely associated with nearby oil production and refining activities, created conditions conducive to parasite proliferation. The high total suspended solids might provide substrates for C. clemensi settlement and attachment, while increased dissolved ions could stress fish and reduce their parasite resistance. This multidisciplinary case study revealed complex host-parasite interactions between C. clemensi and farmed marine fish, highlighting the need for improved water quality and targeted parasite control to enhance aquaculture sustainability in the Suez Canal region.

Aquifer vulnerability assessment in the oaxacan complex: integrating the DRASTIC methodology, TEM, and water quality analysis

Aquifer vulnerability assessment in the oaxacan complex: integrating the DRASTIC methodology, TEM, and water quality analysis

A state-of-the-art review on the quantitative and qualitative assessment of water resources using google earth engine.

Water resource management is becoming essential due to many anthropogenic and climatic factors resulting in dwindling water resources. Traditionally, geographic information systems (GIS) and remote sensing (RS) have long been instrumental in water resource assessment and management as the satellites or airborne units are periodically utilized to collect data from large areal extent. However, these platforms have limited computational capability and localized storage systems. Recently, these limitations have been overcome by the application of Google Earth Engine (GEE) that offers a faster and more reliable cloud-based GIS and remote sensing platform that leverages its parallel processing capabilities. Thereby, in recent years, GEE has witnessed rapid and accelerated adoption and usage in a wide variety of domains, including water resource monitoring, assessment and management. However, no systematic studies have been made to review the GEE application in water resource management. This review article is a maiden attempt towards developing an understanding of the functioning of GEE and its application in water resource assessment, covering both of its aspects viz (a) water quantity and (b) water quality. The review further attempts to illustrate its capabilities in real-world utility, through a case study conducted to analyze water quality and quantity of lake mead, a reservoir of Hoover Dam, Nevada (USA), at a monthly scale for a 3-year period spanning from 2021 to 2023. The results of this case study showcase the applicability of GEE to the water resource quantity and quality monitoring, assessment and management problems. The review further discusses the existing challenges with the application of GEE in water resource assessment and the scope for further improvement. In conclusion, after tackling the existing challenges with GEE, the application of GEE in water resources has huge potential for management planning of our water resources by addressing the forthcoming challenges.

Causes, influencing factors, and prediction modeling of crystallization blockage of tunnel drainage blind pipe in non-karst area

The complete functioning of the tunnel drainage system is critical in ensuring the stability of tunnel lining structures and safe operations. Therefore, the issue of crystalline blockage in the tunnel drainage system needs to be solved urgently. In this study, the formation mechanism of tunnel crystallization defects in non-karst areas was investigated, and the influencing factors of calcium ion dissolution of shotcrete were evaluated by field investigation. Also, the sampling analysis was carried out to determine the ionic composition and content of seepage water. The source and composition of crystallites were determined by X-ray diffraction (XRD), inductively coupled plasma mass spectrometry (ICP-MS), and field-emission scanning electron microscope (SEM). The mechanism and role of pH in CaCO3 crystal formation were explored by simulation using MINTEQ 3.1 software. In addition, a new accelerated leaching test model was developed to examine the flow rate, concentration, and temperature effects on Ca2+ leaching rate in shotcrete. The analysis of water quality and crystal showed that the white and yellow crystals in the tunnel were calcite-type calcium carbonate, occurring as a paste. Micro-morphology of new crystals showed densely-distributed prismatic spherical and scaly crystal structure. The other parts were irregular squares, spindles, rhombuses, and other forms of scattered distribution. The Ca2+ originated from the shotcrete. The accelerated leaching test demonstrated that the optimal test conditions for the leaching rate of Ca2+ in shotcrete were a flow rate of 4 L/min, concentration of 5 mol/L, and temperature of 20 °C. Based on these findings, the prediction model of the Ca2+ leaching rate of shotcrete is established.

Evaluating the water quality of the rice–fish co-culture pattern based on the modified NSF water quality index model

The rice–fish co-culture pattern, a sustainable agricultural production method, plays a significant role in enhancing farmland ecological and economic benefits. However, few studies have evaluated the water quality of this system using the water quality index (WQI). In this study, improvements were made to the United States National Sanitation Foundation WQI (NSFWQI), including indicator selection, weight calculation, and sub-indexing, using principal component analysis (PCA), a minimum data set (MDS), linear function equations, and a comprehensive water quality assessment of the double-cropping rice–fish (DRF) co-culture and (DR) rice patterns. The results showed that using PCA; pH, dissolved oxygen (DO), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and the Shannon–Wiener index were selected from 11 water quality indicators to construct the MDS for WQI calculation. Based on the WQI results, the DRF had a negative impact on water quality, with the Shannon–Wiener index the greatest contributor to the WQI (22.9 %), consistently ranging between 1 and 3. Although total phosphorus (TP) and chemical oxygen demand (COD) were not included in the MDS for the WQI calculation, their significant increase during the late rice season in the DRF indicated water quality deterioration, further validating the accuracy of the improved NSFWQI. The improved NSFWQI model provides a more objective analysis of water quality under the rice–fish co-culture pattern. Compared with existing water quality evaluation methods, this approach offers advantages such as comprehensiveness, low cost, and standardization, and presents an effective alternative for water quality assessment.

Using Dominant Phytoplankton as Assessment of Water Quality: Water Resource Case Studies of University in Chatuchak District

The use of dominant phytoplankton as a water quality indicator was studied. Samples from 6 stations (S1-S6) were collected. From the study, 6 divisions of 34 genera of phytoplankton, i.e. Euglenophyta, Chlorophyta, Bacillariophyta, Chromophyta, and Pyrrhophyta were found, and the significant phytoplankton genera were Euglena, Phacus, and Tetraedron. By analysing water quality assessment in terms of scores by AARL-SPP Score using these three dominant genera, it was found that stations S1–S4 had a moderate level of water quality and stations S5–S6 had a moderate-polluted level of water quality. When the relationship between phytoplankton species and the water quality parameters were analysed by stepwise multiple regression analysis, the results showed that the prominent genus Merismopedia of Cyanophyta (Blue-green algae), correlated with transparency, salinity, chlorophyll a, and soluble phosphate while the genus Oscillatoria correlated with the total suspended solids, Chlorophyll a content, transparency, pH, temperature, and ammonia-nitrogen. The correlation indicates the high rate of phytoplankton growth was due to reduced water quality. According to water quality standards for surface water, the water quality was classified in Category 3.

Assessment of groundwater quality of unconfined aquifers in an urbanized area using the water quality index method.

This study performed an evaluation of the groundwater quality of unconfined aquifers in Yangzhou, located in the Yangtze River Delta, eastern China. The study area is the source area of the Eastern Route (ER) of the South-to-North Water Diversion Project (SNWDP), typical of the lower alluvial plain of the lower Yangtze River. Water samples from monitoring wells and domestic wells were collected to analyze common variables (pH, EC), major ions, trace metals, etc. The water quality index method was employed to evaluate groundwater quality in both eastern and western parts of the study area. The study found that the groundwater hydrochemistry is typical of HCO3-Ca and HCO3-Na, similar between the eastern and western parts of the study area. In addition, the eastern part of the study area is more affected by nitrate pollution than the western part due to agricultural activities. The water quality analysis suggests that the groundwater in the western region was slightly better than that in the eastern region. The comparison between different scenarios indicates that the water quality using only major ions can differ significantly from that using all chemical parameters, but may offer some preliminary insights into the groundwater quality useful for conducting further more detailed analysis. Our study shows that using the combination of major ions and heavy metals could provide relatively robust results of the groundwater quality in our study area. Our study has important implications for the assessment of groundwater quality in regions with similar conditions.

To the Studies on Pollution of Under Ground Water Mau City

The study focuses on the environmental evaluation and classification of the Mau City area, located in the eastern part of Uttar Pradesh, India. The investigation covers an area of approximately 20 km2 and includes a diverse population in terms of socio- economic, cultural, and geographical characteristics. The population data reveals significant growth, with a population increase from 168,716 in 1991 to 2,205,968 in 2011. Animal populations, including cattle and poultry, have also shown an increasing trend from 2018 to 2020. Fertilizer usage data between 2017 and 2020 indicates fluctuations in the consumption of nitrogen, phosphorus, and potassium, demonstrating potential agricultural impacts on the environment. Water quality analysis is a major part of this study, employing various methods to determine salinity, dissolved oxygen, biological oxygen demand (BOD), and chemical oxygen demand (COD). Salinity was measured through titration with silver nitrate, while oxygen levels were analyzed using different methods, including dissolved oxygen (DO) analysis. Results indicate variations in water quality across different sampling sites (S1-S6), with key parameters such as pH, turbidity, temperature, and bacterial contamination being recorded monthly for the years 2019 and 2020.The research also involves the collection and analysis of water samples using various devices, including water samplers, bottom samplers, and biological samplers. Methods such as the EDTA method for water hardness, the gravimetric method for sulfate determination, and the colorimetric analysis for iron and chromium concentrations were utilized to evaluate the pollutants in the water. The study provides critical insights into water quality degradation, highlighting the presence of various pollutants, including nitrates, sulfates, and heavy metals like chromium, copper, and iron.

Validation of water quality parameters using ion balancing and electrochemical approaches: a case study

ABSTRACT The present study validates the accuracy of water quality analysis for twenty geo-referenced water samples from a watershed of Gaya district, Bihar, using ion balancing and electrochemical approaches. Analytical data were presented using box plots, Gibbs diagram and descriptive statistics. Regression equations of various chemical parameters and ionic strength with electrical conductivity (EC) are reported for routine conversion and outlined mathematical equations for data validation. The pH and EC of the water samples varying from 4.9 to 8.7 and 190 to 800 µS cm−1, respectively. Calcium (Ca2+), magnesium (Mg2+), sodium (Na+) and potassium (K+) varied from 0.88 to 2.53, 0.4 to 1.6, 0.8 to 3.75, and 0.01 to 0.22 meq L−1 whereas, bicarbonate (HCO3 –), chloride (Cl–) and sulphate (SO4 2–) ranged from 1.3 to 6.0, 0.25 to 1.5 and 0.01 to 0.6 meq L−1, respectively. Consistency between calculated and measured values judged the correctness based upon relative error (RE %) of the water analysis data. Overall RE on an average of ca. 6% and 5% is reported regarding consistency between the calculated and measured specific conductivity ( calc. and .) and ionic strength ( calc. and .), respectively and difference was statistically non-significant. The ion balancing method showed very good to good analytical data quality for 80% of water samples, while electrochemical approaches (EC and ionic strength) indicated good to moderately good analytical data quality for 85% of the investigated samples. Taking cognisance of the outcome of all validation approaches, an overall 20% rechecking of water samples including (sample ID S3, S8, S13 and S14) is proposed for better analytical data quality for further data mining operations.

A Comprehensive Review of Water Quality Analysis

The effluent discharge of domestic wastewater and industrial effluents into watercourses has necessitated the development of monitoring systems with the purpose of characterizing levels of pollution. Substantial levels of pollution in emerging nations have been exacerbated by rapidly growing populations and inefficient enforcement of sustainable management initiatives. The Water Quality Index (WQI) can help fill the gap between water quality reporting and monitoring by offering a simple and effective way to assimilate and communicate results from a large amount of data. WQIs are the kind of communication tools that can facilitate knowledge sharing between scholars and the general public. The degradation of natural water resources, such as lakes, streams, and estuaries, is the most significant problem facing humanity. Water that is not clean has far-reaching effects on all aspects of life. Water resource management is therefore essential if it is to maximize water quality. If data are analyzed and water quality can be predicted in advance, water pollution may be efficiently addressed. Although this subject has been the subject of numerous earlier studies, additional research is still required to fully understand the effectiveness, reliability, accuracy, and application of the present approaches to water quality management. In this research work, a comprehensive review has been conducted on water quality assessment using artificial techniques. It reviews 75 research works on water quality analysis. The data collected in each research work have been analyzed. Moreover, the type of water resource surface water, groundwater, drinking water as well has been analyzed. The parameters considered in each work are “Dissolved Oxygen (DO), Potential of Hydrogen (pH), Biochemical Oxygen Demand (BOD), Total Dissolved Solids (TDS), and Chemical Oxygen Demand (COD), chloride, hardness, alkalinity, nitrate–nitrite”. In addition, the Artificial Intelligence technique utilized for water quality analysis is also assessed. Finally, the research gaps identified in water quality detection are exhibited.

Analysis of Natural Water Quality in the Dniester River Basin for Economic Utilization

Analysis of Natural Water Quality in the Dniester River Basin for Economic Utilization

Water Quality Analysis of a 300 Mvar Large-Scale Dual Internal Water Cooling Synchronous Condenser External Cooling System and Exploration of Optimal Water Treatment Agent Dosage at Different Temperatures

The external cooling water system of a 300 Mvar dual internal water cooling synchronous condenser at a certain ultra-high voltage converter station continued to exhibit significant scaling and corrosion, even with regular addition of scale and corrosion inhibitors. To solve this problem, the external cooling water of the synchronous condenser was sampled and tested periodically, with the main test items including conductivity, pH value, turbidity, hardness, alkalinity, and other water quality parameters directly related to corrosion and scaling. The trends of these parameters over time were also analyzed. The results showed that as the operation time increased, the cooling water became concentrated during multiple circulation cycles, and the various dissolved or suspended substances underwent a certain degree of enrichment. However, the addition of scale and corrosion inhibitors did not dynamically adjust according to the changes in water quality, and there was always an excessive dosage. Thus, using the external cooling water as the experimental sample, static scale inhibition tests and rotating coupon corrosion tests were conducted to evaluate the scale and corrosion inhibition performance of the commercial AS-582 scale and corrosion inhibitor used at this ultra-high voltage converter station under different conditions. Considering the more obvious corrosive tendency of this water sample, the focus was on testing its corrosion inhibition performance. When the dosage was 600 ppm, the scale inhibition effect was optimal, with an inhibition rate of 92.15%. The corrosion inhibition effect of this scale and the corrosion inhibitor were significantly related to water temperature. At 25 °C, when the dosage was 500 ppm, the corrosion inhibition effect was optimal, with an inhibition rate of 86.79%. However, when the temperature increased to 40 °C, the corrosion inhibition effect under each dosage was significantly worse, unable to meet the requirements, and the use of other corrosion inhibitors in combination was necessary. This work will provide a reference for the scientific use of scale and corrosion inhibitors.

Selection of priority watershed for water environment management.

As part of the National Water Management Basic Plan, this study conducted research to identify priority management watersheds in the Yeongsan River basin to respond to changes in water environmental conditions and improve water quality. Analysis of water quality over the past decade revealed that points located in the middle and lower of the Yeongsan River exceeded the target water quality standards. As based on the results, pollution sources and loads indicated that the W-1 watershed, classified as urban areas, exhibited high levels in residential, industrial, and urban landuse characteristics, whereas the W-6 watershed, classified as rural areas, showed high levels in livestock farming, aquaculture, and agricultural landuse (wet and dry filed) categories. To understand the impact of point source (PS) and non-point source (NPS) pollution within the watershed, load duration curve (LDC) analysis was conducted, indicating that downstream segments of all flow ranges exceeded the target water quality standards, necessitating management of both PS and NPS. Multivariate log-linear analysis also confirmed the influence of PS and NPS, suggesting that watershed management should concurrently address both types of pollution. Based on the results, priority management watershed rankings were derived through the calculation of standard and integrated indicators, with the analysis indicating the following order: W-1 > W-6 > W-3 > W-4 > W-2 > W-5 > W-7 > W-8. PRACTITIONER POINTS: Priority management watersheds that urgently need water environment management can be identified. The priority management watershed rankings were derived through the calculation of integrated indicators data on BOD, TP concentration, and loads. Serve as a guide for future diagnostic assessments of pollution sources and the development of effective management strategies. Anticipated to significantly contribute to the establishment of robust water quality management practices in the basin.