Water Quality Research Articles

Temperature and feeding frequency: interactions with growth, immune response, and water quality in juvenile Nile tilapia

Abstract Background Water temperature and feeding frequency are critical abiotic factors regulating the growth and immune function of aquatic organisms. This study investigated the effects of water temperature and feeding frequency on growth and immune function in Nile tilapia (Oreochromis niloticus) over two months. A total of 360 juvenile fish (average weight: 20.00 ± 1.26 g) were divided into six groups, each with three replicates, based on a combination of three water temperatures (26, 28, and 30 °C) and two feeding frequencies (either 1 or 2 meals per day). Results At 30 ºC and 28 ºC, water electrical conductivity and total dissolved salts increased, while total ammonia nitrogen and dissolved oxygen rose slightly in groups fed twice daily, with a significant interaction between temperature and feeding frequency. The group at 30 ºC with two meals per day showed the highest final body weight (FBW). The interaction between temperature and feeding frequency significantly influenced FBW, total feed intake, and body thickness. Fish at 30 ºC exhibited upregulated hepatic growth hormone receptor 1 and insulin-like growth factor 1, while those at 28 ºC with one meal per day, as well as those at 30 ºC regardless of meal frequency, also showed increased expression of hepatic fatty acid binding protein and intestinal cluster of differentiation 36. Fish at 30 ºC had upregulated leptin levels and downregulated cholecystokinin, while those at 26 ºC displayed the opposite trend, particularly with one meal daily. Higher temperatures significantly boosted serum IgM, superoxide dismutase (SOD), and lysozyme (LYZ) levels, with meal frequency also affecting malondialdehyde, IgM, and SOD levels. Additionally, 30 ºC enhanced the hepatic expression of mucin-like protein (muc), oligo-peptide transporter 1 (pept1), interleukin 1, nf-κB, complement C3, lyz, sod, catalase, and glutathione peroxidase, with twice-daily meals having a more pronounced effect. Conversely, 28 ºC with one meal per day upregulated some of these genes, such as muc, pept1, and sod. Conclusions Overall, 30 ºC with two meals per day significantly improved the growth and health of juvenile Nile tilapia, while 28 ºC with two meals maintained satisfactory performance.

Establishing Optimal Machine Learning Models for Monitoring Water Quality in Vietnam’s Upper Ma River

This study aims to establish the optimal regression model for predicting total suspended solids (TSS) and Turbidity based on in situ data and spectral regions of Sentinel-2 images. Various machine learning models were evaluated, including Multilayer Perceptron Regression (MLPR), Random Forest Regression (RFR), AdaBoost Regression (ABR), Multiple Linear Regression (MLR), and K-Nearest Neighbors Regression (KNNR). These models were applied to different band combinations of spectral regions: visible (VIS), near-infrared (NIR), shortwave-infrared (SWIR), VIS+NIR (VNIR), and VIS+NIR+SWIR (VNIR+SWIR). The study results revealed that the MLR model, while not the best performer during training (R2 = 0.89 for TSS and R2 = 0.66 for turbidity), did not exhibit overfitting, with corresponding R² values in testing being 0.80 and 0.42, respectively. Variable selection for MLR models identified optimal spectral bands: B3, B5, B6, B8, B11, and B12 for TSS, and B4, B8, B11, and B12 for Turbidity. The final no-intercept multiple linear regression models achieved R2 = 0.88 for TSS and R2 = 0.62 for turbidity. Performance metrics for TSS were superior, with lower MAE, MSE, and RMSE compared to Turbidity. This study underscores the efficacy of using MLR models with selected spectral bands for accurate and generalizable predictions of TSS and turbidity.

Enhanced purification efficacy of the microflocculation–ultrafiltration process for raw water quality from multiple sources during heavy rainfall

ABSTRACT In this study, we utilized direct ultrafiltration (UF) and integrated microflocculation–ultrafiltration (MF–UF) processes to treat raw water from four distinct sources, covering both dry and heavy rainfall periods. We assessed the effectiveness of microflocculation (MF) as a pretreatment to enhance treatment efficiency under complex water conditions, focusing on its role in mitigating membrane fouling. The results demonstrated the superior adaptability of UF membranes when combined with MF pretreatment, particularly in managing high turbidity during heavy rainfall, a challenge for standalone UF processes in meeting regulatory standards. This integrated approach notably improved UV254 removal efficiency from approximately 60–80%. Additionally, excitation–emission matrix spectroscopy revealed that while the MF–UF process is effective in removing dissolved organic matter (DOM), it faces limitations with high DOM concentrations in raw water. Comparative analysis of membrane flux between the two methods showed that MF pretreatment reduces filtration time, enhances flux rates, and significantly decreases membrane fouling. Finally, scanning electron microscopy further provided insights into the structure and morphology of UF membrane surface filter cakes, illustrating how MF pretreatment contributes to the sustained efficiency of membrane flux.

Ichthyobodo necator infection as a first record in cultured Dicentrarchus labrax: morphomolecular characterization and infestation patterns in correlation to water quality parameters

Abstract Ichthyobodo necator is a damaging and economically important protozoan parasite; however, its clinical patterns and incidence, correlated to environmental factors, are still poorly understood. This study provides the first report of Ichthyobodo necator infestation among Dicentrarchus labrax. We recorded significant mortalities in the cultured D. labrax of average size (5.92 g weight, and 11.55 cm length) in El-Max Station, National Institute of Oceanography and Fisheries, NIOF, Egypt, during the period extending from early summer to early fall (June to October) 2023. Behavioral and gross lesions of the infested fish were recorded; besides, dead and moribund fish were collected. Wet smears of the skin and gill of the affected fish were examined by compound light microscopy. Moreover, water samples from the affected ponds were collected and examined for their physicochemical parameters. The bodonid biflagellated Ichthyobodo necator (Henneguy) C. Pinto, 1928 was isolated from the skin and gills and identified based on specific morphological characteristics. DNA sequencing of PCR products and phylogenetic analysis confirmed identification, with clustering of the current isolates with I. necator isolates from different fish species. The multivariate analysis revealed a positive correlation between the prevalence and infestation intensity of Ichthyobodo, increased temperature levels, decreased dissolved oxygen DO, and also correlated with higher ammonia, and pH values. Additionally, the elevated concentrations of iron, calcium, magnesium, zinc, and copper in pond water were positively correlated with infestation and mortalities. These water parameter levels promote respiratory distress, accelerated prevalence, and infestation intensities of I. necator, particularly during the infestation peak in August and September. This study bridges the knowledge gap regarding I. necator parasite infestations and their correlation with water quality parameters.

Habitat Assessment of Bocachico (Prochilodus magdalenae) in Ciénaga de Betancí, Colombia, Using a Habitat Suitability Index Model

This study evaluates the habitat of the Bocachico fish (Prochilodus magdalenae) in the Ciénaga de Betancí, Colombia, using a habitat suitability index (HSI) model. Wetlands like the Ciénaga de Betancí are under significant pressure from anthropogenic activities, affecting biodiversity and ecosystem health. The Bocachico, a species of immense cultural and economic importance, faces habitat degradation and fragmentation. Using hydrodynamic and water quality data, a numerical model (EFDC+ Explorer 11.5), and field data collected from multiple sampling campaigns, we assessed habitat suitability based on five key parameters: water temperature, dissolved oxygen, ammonia nitrogen, velocity, and depth. The model results indicated that environmental conditions in the wetland remained relatively stable during the dry season, with an average HSI score of 0.67, where 9% of the wetland area displayed acceptable conditions, and the remaining 91% displayed medium conditions. The wet season, on the other hand, had an average HSI score of 0.64, with 7.2% of the area in the acceptable suitability range, and the remaining 92.8% in the medium category. Variations in HSI were primarily driven by ammonia nitrogen levels, water velocity, and depth. Despite limited fluctuations in the HSI, areas of low suitability were identified, particularly in regions impacted by human activities. These findings have practical implications for conservation strategies, providing valuable insights for the sustainable management and conservation of the Ciénaga de Betancí, informing strategies for improving habitat conditions for the Bocachico, and supporting wetland restoration efforts.

A Comprehensive Review of Advanced Treatment Technologies for the Enhanced Reuse of Produced Water

Produced water (PW) is considered to be the largest source of industrial wastewater associated with oil and gas extraction operations for industrial production. It is a mixture of organic and inorganic compounds that has high complexity in terms of various characteristics. Globally, the volume of PW is increasing along with the expansion of gas and oil fields, leading to major impacts on the environment. Existing treatment technologies involve partially treating the PW through removing the suspended solids, heavy metals, without removing organic components and re-injecting the water underground using water disposal injection wells. The treatment process consists of a primary treatment unit to remove the particles, followed a secondary biological or chemical processing treatment, while the final treatment stage involves the use of a tertiary treatment unit to improve the water quality and remove the remainder of the undesired components. Moreover, while PW is considered one of the available options to be utilized as a water source, no alternate advanced treatment options on a commercial scale are available at present due to the limitations of existing PW treatment technologies, associated with their maintainability, sustainability, cost, and level of quality improvement. As such, research focused on finding an optimal treatment approach to improve the overall process continues to be conducted, with the aim of reusing the water instead of injecting it underground. This literature review discusses the latest advanced technologies for PW treatment aimed at reusing the full stream capacity of PW and eliminating the need for wastewater disposal via injection. It is concluded that researchers should focus on hybrid treatment technologies in order to remove the pollutants from PW, effectively allowing for its reuse.

An Assessment of Drinking Water Quality in the Chief Albert Luthuli Local Municipality, South Africa: A Case Study of the Elukwatini Water Supply Scheme

This study analysed the water quality of 156 samples collected from 13 different points within the Chief Albert Luthuli Local Municipality between January and December 2021, focusing on compliance with the South African National Standard 241 (SANS 241). Microbiological assessments revealed widespread contamination, with heterotrophic plate counts (HPCs) exceeding the recommended range in nearly all samples. The median HPC levels were particularly concerning, with the untreated source (RE000) exhibiting a median of 2555 CFU/mL. Total coliforms and Escherichia coli were present at alarming levels, indicating significant faecal contamination; the highest total coliform count, 2420 CFU/100 mL, was recorded at RE000. Physically, while all samples complied with electrical conductivity standards (0–70 µS/cm), turbidity levels showed variability, with nine samples exceeding the acceptable threshold of 1 NTU. The highest turbidity, 7.55 NTU, was recorded at the untreated source (RE000). Chemically, pH levels fell within safe ranges (6.0–9.0), with all samples being compliant with standards. However, only one sample (E001) met the free chlorine standard of 0.3–0.6 mg/L, suggesting inadequate disinfection practices. The untreated source was classified as ‘Unsuitable for drinking’ (WQI = 207.27). These findings highlight the critical need for enhanced monitoring and remediation strategies to improve drinking water safety in the region.

Analysis of Existing Area, Clean Water Treatment, and Distribution Network Evaluation in Nagari Magek, Agam Regency, West Sumatra

Nagari Magek Village in Agam Regency, West Sumatra, faces significant challenges in managing clean water resources. To address these challenges comprehensively, a holistic approach is essential, involving through area analysis, water treatment, and evaluation of distribution networks to ensure efficient and equitable water distribution. It is crucial to adhere to the principles of water resource conservation, utilization, and management as stipulated in Law Number 17 of 2019 on water resource management, which must be observed to ensure legal clarity in water management practices. The community service team handles clean water problems in Nagari Magek by designing a clean water treatment system that includes aeration, sedimentation, and filtration units. This process improves water quality by reducing yellowish color and eliminating unpleasant odors. However, the capacity of the treatment plant is not able to meet the increasing water demand, while the galvanized pipe distribution network has not been functioning optimally. Based on simulations using EPANET 2.2 software, it was found that the water flow speed in the pipes was still below the optimal range due to the diameter of the pipes being too large. The solution applied was to increase the processing discharge to 10 L/s (0,01 m3/s), which succeeded in increasing the flow rate according to the regulatory criteria. This recommendation improves the efficiency of the distribution system and ensures better water quality for the people in Nagari Magek.

Genome sequences of toxigenic cyanobacteria from a bloom in Lake Mattamuskeet, North Carolina (United States)

AbstractLake Mattamuskeet, the largest lake in North Carolina, USA, has undergone decades‐long eutrophication causing reduced water quality and promoting cyanobacterial blooms that may produce toxins. It is therefore necessary to evaluate the cyanobacterial diversity of the lake and their toxigenic potential. We present draft genomes of Microcystis, Pelatocladus, Raphidiopsis, and Umezakia strains isolated from Lake Mattamuskeet. The whole‐genome shotgun projects for Umezakia ovalisporum BLCC‐F208, Microcystis sp. BLCC‐F209, Microcystis sp. BLCC‐F210, Pelatocladus sp. BLCC‐F211, U. ovalisporum BLCC‐F215, and Raphidiopsis BLCC‐F218 have been deposited in GenBank under accession numbers JBHFLK000000000, CP169647, JBHFLL000000000, JBHFLM000000000, JBHFLN000000000, and JBHFLO000000000, respectively. Based on the genomic analysis, several biosynthetic gene clusters (BCGs) with varying degrees of similarity to known toxic and bioactive compound gene clusters were identified across the different cyanobacterial strains.

Improving the technology of drinking water purification at the water treatment facilities of the Chernorechensk reservoir during the flood period

The paper considers the natural and technical aspects that contribute to the supply of substandard quality water to the water treatment facilities of the city of Sevastopol during the flood period, which caused repeated shutdown of water treatment facilities. Options for retrofitting the existing water supply and purification scheme are considered, with the determination of the enlarged cost. The paper presents a technological justification for the application of a two-stage sedimentation scheme, which can be implemented within the framework of existing equipment and a small technological re-equipment.

Seasonal Variation of Physicochemical Properties in the Lower River Benue, Nigeria

The study investigates the impact of seasonal changes on water quality in the River Benue, Nigeria. Conducted over eighteen months from January 2020 to June 2021, the research focuses on three locations: Ibi, Lau, and Mayo-Ranewo. Key physicochemical parameters such as temperature, pH, turbidity, conductivity, Biochemical Oxygen Demand (BOD), hardness, dissolved oxygen (DO), fluoride, and nitrate were measured to assess water quality. The findings reveal significant seasonal variations in these parameters, influenced by rainfall patterns, land use, and anthropogenic activities. Temperature ranged from 25.56°C to 30.70°C, remaining within acceptable limits for tropical waters, supporting stable biological processes. However, turbidity levels exceeded recommended values, indicating the presence of suspended solids that could impair water quality and harm aquatic life. Total dissolved solids (TDS) and conductivity showed potential contamination risks, likely due to agricultural runoff and urban discharges. Dissolved oxygen (DO) levels were generally adequate, especially during the wet season, enhancing oxygen content through increased photosynthetic activity and water inflows. However, BOD spiked with rainfall, signalling organic pollution and potential eutrophication risks. Seasonal shifts in pH and water hardness reflected changes in runoff and photosynthesis, with values largely within acceptable ranges for aquatic life. Fluoride and nitrate concentrations increased in the wet season, primarily due to agricultural runoff, highlighting the influence of land-based activities on water quality.

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.

Future land use maps for the Netherlands based on the Dutch One Health Shared Socio-economic Pathways.

To enable detailed study of a wide variety of future health challenges, we have created future land use maps for the Netherlands for 2050, based on the Dutch One Health Shared Socio-economic Pathways (SSPs). This was done using the DynaCLUE modelling framework. Future land use is based on altitude, soil properties, groundwater, salinity, flood risk, agricultural land price, distance to transport hubs and climate. We also account for anticipated demand for different land use types, historic land use changes and potential spatial restrictions. These land use maps can be used to model many different health risks to people, animals and the environment, such as disease, water quality and pollution. In addition, the Netherlands can serve as an example for other rapidly urbanising deltas where many of the health risks will be similar.

Research on information leakage in time series prediction based on empirical mode decomposition.

Time series analysis predicts the future based on existing historical data and has a wide range of applications in finance, economics, meteorology, biology, engineering, and other fields. Although the combination of decomposition techniques and machine learning algorithms can effectively solve the problem of predicting nonstationary sequences, this kind of decomposition-integration-prediction strategy of the prediction method has serious defects. After the decomposition of the division of the training set and the test set, the information of the test set in the process of decomposition of the information leakage ultimately shows a high accuracy of the prediction of the illusionary. This paper proposes three improvement strategies for this type of "information leakage" problem: sliding window decomposition (SW-EMD), single training and multiple decomposition (STMP-EMD), and multiple training and multiple decomposition (MTMP-EMD). They are combined with a bidirectional multiscale temporal convolutional network (MSBTCN), bidirectional long- and short-term memory network (BiLSTM), and attention mechanism (DMAttention), which introduces a dependency matrix based on cosine similarity to be applied to water quality prediction. The experimental results show that the model achieves good performance in the prediction of three water quality indicators (pH, DO and KMnO4), and the accuracies of the three models proposed in this paper are improved by 1.958% and 0.853% in terms of the RMSE and MAPE, respectively, compared with those of the mainstream LSTM models. The key contributions of this study include the following: (1) three methods are proposed to improve the class EMD decomposition, which can effectively solve the problem of "information leakage" that exists in the current models via class EMD decomposition; (2) the CEEMDAN-MSBTCN-BiLSTM-DMAttention model structure is innovated by combining improved class EMD decomposition methods; and (3) the three improved decomposition methods proposed in this paper can effectively solve the problem of "information leakage" and optimize the prediction model at the same time. This study provides an effective experimental method for water quality prediction and can effectively address the problem of "overfitting" models via class EMD decompositions during model training and testing.

Advancements in Hydroponic Systems: A Comprehensive Review

Hydroponics, the practice of growing plants without soil using mineral nutrient solutions in water, represents a significant shift in agricultural methodologies. Modern hydroponic systems have evolved substantially since the early 20th century, with advancements in system design, automation, nutrient management, and environmental control enhancing efficiency, scalability, and applicability. This review examines recent innovations that have addressed traditional challenges and created new opportunities for hydroponic cultivation. Hydroponics offers advantages over traditional soil-based agriculture, including precise nutrient control, reduced water usage, and the elimination of soil-borne diseases and pests. These benefits are critical in addressing modern agricultural challenges such as soil degradation, water scarcity, and the need for increased food production for a growing global population. Hydroponic systems can be implemented in diverse environments, making them adaptable solutions for enhancing food security and sustainability. Key developments in various hydroponic systems are highlighted, including the Nutrient Film Technique (NFT), Deep Water Culture (DWC), Ebb and Flow, Aeroponics, Wick Systems, and Drip Systems. Innovations in these systems focus on optimizing nutrient delivery, oxygenation, and integrating sensors for precise control, improving overall performance and yield. Technological advancements, such as automation and control systems, sensors, and monitoring technologies, have revolutionized hydroponic farming by enabling real-time data collection and environmental management. The integration of the Internet of Things (IoT) and smart farming practices, combined with data analytics and machine learning, has further optimized system performance and decision-making. LED lighting and vertical farming techniques have maximized space utilization and improved crop yields, particularly in urban environments. Advances in nutrient solutions, disease management, and water quality have optimized plant health and resource efficiency. Economic and environmental considerations, including cost-benefit analyses and comparisons with traditional agriculture, highlight the potential for hydroponics to offer better returns on investment and reduce environmental impact. Despite the significant progress, challenges such as high initial setup costs and technical complexities remain. Future research opportunities and interdisciplinary collaborations are essential to address these challenges and drive further innovation in hydroponic farming.

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.

An Experimental Study on Concrete Strength Optimization with Surkhi as

Concrete is a widely used construction material, with sand as key component. However, excessive extraction of sand has led to a significant environmental consequences, including erosion, ecological imbalance, habitat destruction, and water quality issues. This study aims to develop an economical and sustainable alternative to traditional sand-based concrete while maintaining its structural integrity. It explores the potential of using Surkhi (a waste product from burnt clay bricks) as a partial replacement of sand in concrete. For this study, 120 concrete cube samples were prepared in the laboratory.Concrete cubes of M20 and M25 grades were prepared using design and nominal mixes, with different proportions of Surkhi (0%, 10%, 20%, 30%, and 40%) and tested to evaluate the workability, cost-effectiveness, and compressive strength. Compressive strength tests were conducted on concrete cubes at 7 and 28 days to investigate their mechanical properties. The results shows that a 10% replacement of sand with Surkhi optimizes the strength and workability of concrete without compromising its performance, thus supporting sustainable construction practices. However, the negative impact in concrete strength due to addition of higher proportions of Surkhi should be carefully considered. Furthermore, a cost analysis indicates that replacing sand with Surkhi can help to reduce the production costs, while promoting its use as an eco-friendly alternative. The findings provides valuable insights into the potential of Surkhi to reduce environmental damage and costs without compromising performance at moderate replacement levels. However, further research is recommended to assess the long-term durability and structural integrity of Surkhi-based concrete in various applications.

Prevalence of Child Fever, Acute Respiratory Infection, and Diarrhea and Their Risk Factors in Sierra Leone

Sierra Leone has the fourth-highest child mortality rate in Sub-Saharan Africa. This retrospective study aimed to estimate the nationwide prevalence of fever, acute respiratory infection (ARI), and diarrhea in children under 5 years in Sierra Leone, and to identify the risk factors associated with these diseases. We extracted patient information from the 2019 Sierra Leone Demographic and Health Survey data. Data were analyzed using multivariate logistic regression. In total, 8659, 8652, and 8650 children were included in the analyses of fever, ARI, and diarrhea, respectively. The analysis revealed that the nationwide prevalence rates of fever, ARI, and diarrhea were 16.8%, 14.2%, and 7.2%, respectively. Children aged 12–23 months were found to be the most susceptible. Compared to children consuming unimproved water, the highest prevalence rates of fever, ARI, and diarrhea were observed among children residing in households with tube wells or boreholes. The adjusted odds ratio for diarrhea prevalence among children drinking water from household tube wells or boreholes was 1.47 (95% confidence interval: 1.17–1.84, p < 0.001). This study has several limitations, including recall bias due to parental reporting. We suspect that the diseases may be associated with potential water contamination in tube wells or boreholes. We recommend national-level periodic inspections of water quality and community-level education on water supply management.

Algorithm for monitoring water quality parameters in optical systems based on artificial intelligence data mining.

Due to the increasingly serious water environment pollution, the difficulty of Water Quality Monitoring (abbreviated as WQM for convenience) is also constantly increasing, which puts forward more requirements for the capabilities of various aspects of WQM systems. However, the current WQM method has drawbacks such as slow speed, long monitoring time, complex operation, poor stability, and the inability to obtain accurate information on water pollution in the first time, as well as the generation of toxic and harmful secondary pollutants after some measurement parameters are tested. To address these issues and ensure water quality safety, this paper investigated the algorithm for monitoring water quality parameters using artificial intelligence data mining optical systems. This article applied an artificial intelligence data mining system to detect water quality and designed various system through this method to improve system performance. To verify the actual effectiveness of artificial intelligence data mining systems, this article selected 10 water plants as experimental research subjects and compared the differences between traditional WQM methods and WQM methods based on artificial intelligence data mining systems in terms of WQM time, accuracy, sensitivity, and protective performance. The experimental results showed that the optical system based on artificial intelligence data mining took an average of 2.7 days in WQM and the average accuracy was 85.95%. The average sensitivity value was 84.19% and the average protective score was 8.46 points. This indicated that artificial intelligence data mining optical technology had vital significance and value for WQM.

Assessing the impact of human activities on the health condition of the Lukosi River catchment using selected physico-chemical parameters as indicators of water quality

The Lukosi River catchment plays a crucial role in the economic and ecological framework of the country, serving as a major contributor to the Great Ruaha River (GRR). This study aimed to assess the impact of human activities on the health of the Lukosi River by analyzing key water parameters. Three sampling sites across the catchment were selected, and water samples were collected and analyzed using the American Public Health Association technique. A one-sample t-test was used to measure the significance of the difference between the measured water quality parameters and the water quality criteria established by the Tanzania Bureau of Standards (TBS) and the World Health Organization (WHO). The results revealed mean values for various parameters: pH (8.67 ± 0.57), temperature (24.803 ± 1.361°C), EC (93.30 ± 3.34 mgL−1), BOD (14.85 ± 1.49 mgL−1), TDS (46.95 ± 1.55 mgL−1), total hardness (27.53 ± 1.28 mgL−1), DO (3.4 ± 0.53 mgL−1), turbidity (109.83 ± 40.99 mgL−1), NO2 (79.04 ± 0.73 mgL−1), Cu (6.07 ± 0.60 mgL−1), Ca (7.88 ± 0.36 mgL−1), Mn (0.16 ± 0.07 mgL−1), Cl (7.58 ± 3.97 mgL−1), F (0.12 ± 0.0008 mgL−1), SO4 (20.42 ± 4.12 mgL−1), Mg (1.92 ± 0.13 mgL−1), Zn (0.14 ± 0.11 mgL−1), Fe (3.56 ± 0.15 mgL−1), and NH3 (4.67 ± 0.51 mgL−1). Parameters such as DO, turbidity, NH3, NO3, and BOD significantly (p = 0.05) exceeded the permissible limits set by the TBS and the WHO. Furthermore, elements including Fe and Cu exceeded allowable limits. Moreover, the WQI was used to indicate that the water in the catchment is unsuitable for sustaining aquatic organisms and is unfit for domestic use. Household questionnaires and direct observations identified key human activities in the catchment: gardening (78.3%), agriculture (68%), livestock keeping (50%), sand mining (21%), and brick-making (21%). Less prevalent were car washing (7%) and fishing (4%). These findings underscore the urgent need for conservation efforts and sustainable management practices to safeguard the Lukosi River catchment (LRC).