Assessment Of Surface Water Quality Research Articles

Case study on water quality index for wastewater treatment in Mumbai

Abstract The traditional wastewater treatment process is laborious and demanding in terms of time, energy, and space. With rapid advancements, there's a quest for more efficient techniques that can achieve comparable treatment outcomes while minimizing these demands. This study proposes a solution by employing ozone as an Advanced Oxidation Process (AOP) to expedite the treatment while enhancing the water quality. The Water Quality Index (WQI) offers a consolidated representation of overall water quality by considering multiple quality parameters. Although typically used for assessing surface water quality, this study utilizes WQI to gauge the enhancement in parameters post-treatment. The research investigates the impact of varied ozone doses on raw sewage samples collected from four different sites in Mumbai, focusing on parameters such as dissolved oxygen, turbidity, hardness, chemical oxygen demand (COD), and WQI. The results demonstrate a notable percentage enhancement in WQI, ranging from 30 to 60% across various sites within a short 25-minute timeframe, attributed to the application of ozone.

Assessment of Surface Water Quality Using Entropy-WQI, Fuzzy-TOPSIS Analysis, Irrigation Indices and Spatial Interpolation Approaches in Mahanadi River Basin, Odisha, India

The current study is aimed at the assessment of surface water quality in the Mahanadi River, Odisha and its suitability for agricultural and consumption purposes, utilizing various indices of water quality such as Entropy Water Quality Index, Osmotic Pressure, Potential Salinity, Residual Sodium Carbonate, Sodium Adsorption Ratio and Kelly Index. Multi-criteria decision-making (MCDM) mechanisms namely, fuzzy-TOPSIS modeling and GIS tools were used; additionally, the suitability of river water for industrial uses was evaluated using indices such as Ryznar Stability Index and Puckorius scaling index. From 2019 to 2023, samples from 19 sampling stations were collected and 21 physical and chemical parameters were evaluated and compared with the normative recommendations advised by WHO. The dispersion of surface water quality on land use changes was discovered using GIS approaches. Additionally, using ArcGIS software, the spatial variability of hydrological processes was determined using the IDW interpolation approach. The pH levels of certain sampling points were slightly above the acceptable limit. Tests revealed that the Total coliform (TC) and turbidity levels in the water samples exceeded critical limits, particularly in areas of the urban river basin that were irrigated with wastewater. The calculated values of EWQI lie between 14.6 and 1066. Entropy WQI values designated 2 locations (ST-8, 19) out of 19 sampling locations as poor category and another one testing point (ST-9) as extremely poor category. The study found that 84.21% of the water samples were of excellent quality for drinking, while 15.78% of locations had poor or extremely poor water quality. However, some indices were favorable for the usage of the water for irrigation purposes. Magnesium hazard (MH) readings at two sampling sites were above 50%, indicating that they were inappropriate for irrigation. USSL (United States Salinity Laboratory) diagrams categorized the water samples as C1-S1 (low salinity and low sodium) for almost 18 sites and C4-S3 (very high salinity and high sodium) for only ONE sample, respectively, suggesting river water’s irrigation suitability. Further, Piper diagrams revealed that most investigated waters were Ca2+-Mg2+-Cl- water type. In a later stage, from Gibb’s diagram, it was found that most samples fall under the rock-water dominance. Based on the above and all other investigation results, it was concluded that water is suitable for irrigation and drinking purposes in all sites, except for three locations. The reason may be due to long-term use of wastewater, anthropogenic activities, over-extraction of surface water and changes in land use patterns. To sum up, it is advantageous to combine physicochemical properties, EWQI, fuzzy-TOPSIS, and GIS tools to evaluate surface water suitability for consumption and agriculture and their regulating variables. The strategy utilized in this work will aid the water management authorities in ensuring the supply of safe water for stakeholders.

Аналіз стану умов відтворення аборигенних іхтіопопуляцій Стир-Горинського гідроекологічного коридору на території Західного Полісся України

Purpose. To investigate the state of reproduction conditions, current and in dynamics since 1922, for native ichthyopopulations (NI) of the Styr-Horyn Hydroecological Corridor (HEC) on the territory of the Western Polissiya of Ukraine. Methodology. The Styr-Horyn HEC was studied according to the following parameters: hydrological regime and duration of water stay on the floodplain; state of the basin surface; speed of channel flow; amount of water exchange; quality of aquatic environment; natural-temporal changes of the channel, floodplains, tributary network; number of ecotones; qualitative and quantitative characteristics of fish juveniles. The hydrological regime was studied using the analysis of runoff hydrographs located in the Volyn, Rivne, and Zhytomyr regions starting from 1922. To assess water quality, KND No. 211.1.4.010-94, “Methodology of ecological assessment of surface water quality by relevant categories”, SOU – 05.01.37-385: 2006, was used. Ichthyological studies were carried out in the field and laboratory according to standard methods with the use of identification keys primarily using the data of test catches and the classification of V. G. Nikolskyi. Statistical and mathematical analysis was performed using the Delfi programming language, relevant computer programs (Mathcad, Excel, Xara) and formulas, including authors’ ones. Findings. An analysis of the Styr-Horyn HEC was carried out on the basis of restorative ichthyoecology using the basin principle and riskology approaches. The hydroecological and ichthyoecological factors affecting the reproduction of NI were studied. The natural fish reproduction localities (NFRL) in this region have been identified. Originality. For the first time, a comprehensive analysis of the state of the reproduction conditions of the Styr-Horyn HEC on the territory of the Western Polissiya of Ukraine was carried out starting from 1922. In addition, a prognostic assessment of the NFRL of this HEC on the territory of Ukraine has been provided. Practical value. The conducted studies are already successfully used in the work of higher educational institutions of Ukraine in the field of training “Aquatic bioresources and aquaculture”.In addition, they are used by fish protection authorities in several regions of Ukraine, in particular for certification of wintering grounds. In the future, their implementation is planned at the level of the national environmental protection policy and in the preparation of regulatory documents regarding the determination of the damage caused and the extent of the damage. Keywords: Pripyat River, Horyn River, Styr River, hydroecology, ichthyoecology, Western Polissiya, hydroecological corridor, natural fish reproduction localities, spawning grounds, wintering grounds, fish migrations, native ichthyofauna.

Deep optimization of water quality index and positive matrix factorization models for water quality evaluation and pollution source apportionment using a random forest model

Effective evaluation of water quality and accurate quantification of pollution sources are essential for the sustainable use of water resources. Although water quality index (WQI) and positive matrix factorization (PMF) models have been proven to be applicable for surface water quality assessments and pollution source apportionments, these models still have potential for further development in today's data-driven, rapidly evolving technological era. This study coupled a machine learning technique, the random forest model, with WQI and PMF models to enhance their ability to analyze water pollution issues. Monitoring data of 12 water quality indicators from six sites along the Minjiang River from 2015 to 2020 were used to build a WQI model for determining the spatiotemporal water quality characteristics. Then, coupled with the random forest model, the importance of 12 indicators relative to the WQI was assessed. The total phosphorus (TP), total nitrogen (TN), chemical oxygen demand (CODCr), dissolved oxygen (DO), and five-day biochemical oxygen demand (BOD5) were identified as the top five significant parameters influencing water quality in the region. The improved WQI model constructed based on key parameters enabled high-precision (R2 = 0.9696) water quality prediction. Furthermore, the feature importance of the indicators was used as weights to adjust the results of the PMF model, allowing for a more reasonable pollutant source apportionment and revealing potential driving factors of variations in water quality. The final contributions of pollution sources in descending order were agricultural activities (30.26%), domestic sewage (29.07%), industrial wastewater (26.25%), seasonal factors (6.45%), soil erosion (6.19%), and unidentified sources (1.78%). This study provides a new perspective for a comprehensive understanding of the water pollution characteristics of rivers, and offers valuable references for the development of targeted strategies for water quality improvement.

Assessment of surface water quality in a highly anthropised semi-arid catchment (Case of Wadi El Hatab Basin, Tunisia, North Africa)

Assessment of surface water quality in a highly anthropised semi-arid catchment (Case of Wadi El Hatab Basin, Tunisia, North Africa)

Monitoring and Assessment of Surface Water Quality Using Physicochemical Parameters and Indexical Approaches in El Manzala Lake, Egypt.

Monitoring and Assessment of Surface Water Quality Using Physicochemical Parameters and Indexical Approaches in El Manzala Lake, Egypt.

Water Quality Estimation Using Gaofen-2 Images Based on UAV Multispectral Data Modeling in Qinba Rugged Terrain Area

This study presents an innovative method for large-scale surface water quality assessment in rugged terrain areas, specifically tailored for regions like the Qinba Mountains. The approach combines the use of high-resolution (10 cm) multispectral data acquired by unmanned aerial vehicles (UAVs) with synchronized ground sampling and 1 m resolution multispectral imagery from China’s Gaofen-2 satellite. By integrating these technologies, the study aims to capitalize on the convenience and synchronized observation capabilities of UAV remote sensing, while leveraging the broad coverage of satellite remote sensing to overcome the limitations of each individual technique. Initially, a multispectral estimation model is developed for key water quality parameters, including chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP), utilizing data from UAVs and coordinated ground samples. Subsequently, a comparison is made between the spectral band ratios (R/G and NIR/G) obtained from the UAV data and those from the Gaofen-2 satellite data, revealing a substantial similarity. Ultimately, this integrated methodology is successfully employed in monitoring water quality across a vast area, particularly along the midstream of the Hanjiang River in the Qinba Mountain region. The results underscore the feasibility, advantages, improved efficiency, and enhanced accuracy of this approach, making it particularly suitable for large-scale water quality monitoring in mountainous terrain. Furthermore, this method reduces the burden associated with traditional ground-based spectral acquisitions, paving the way for a more practical and cost-effective solution in monitoring vast water bodies.

Assessment of surface water quality using the Water Quality Index (WQI) and multivariate statistical analysis (MSA), around tannery industry effluent discharge areas

Abstract The study attempted to assess the water quality around the tannery effluent discharge areas for suitability for irrigation purposes using different indices (Water Quality Index (WQI)) and statistical analysis in Savar Upazilas in Dhaka, Bangladesh. The samples were collected three times, from monsoon 2021 to pre-monsoon 2023. The analysis results showed that the concentrations of various parameters at most of the sampling points exceeded the surface water standard. Pollution levels were found in the following order: pre-monsoon, post-monsoon, and monsoon. At SW1 point, the CWQI, WWQI, and MWQI of the surface water quality showed a ‘poor’ category. The IWQI values showed that the surface water at all the sampling points was suitable for irrigation purposes, except for the SW1 sampling point. The NPI indicates that EC, BOD, COD, TSS, Cl−, Na+, and NO3--N parameters were potentially responsible for polluting most sampling sites. Multivariate statistical analyses like principal component analysis, cluster analysis, and Pearson correlation matrix showed significant anthropogenic intrusions of these variables in surface water in the area. A strong correlation between these parameters indicated their common origin, i.e., poorly treated tannery industry effluent entered the surface water, suggesting an improvement in the efficiency of the Central Effluent Treatment Plant (CETP).

Assessment of surface water quality in the lower Sebou by physicochemical and microbiological approach and the impact of tributaries (Oued Beht and Oued Swaret) during the summer season

The study consists in assessing the quality of the surface waters of the Lower Sebou (from dam to Sebou mouth), by studying the impact of anthropic activities and the tributaries flowing into the Sebou (Oued Beht and Oued sawaret), and by analyzing the various physico-chemical and bacteriological parameters such as : temperature, pH, conductivity, TSS, turbidity, DCO, DBO5, total phosphorus, NO -, NO -, NH4+, SO 2-, Cl-, Mg2+, Ca2+, alkalinity, total and faecal coliforms bacteria, total and faecal streptococci. Nine stations were sampled in mid-September 2021. The water analyzed showed high values: for temperature, from 24.7 to 31.1°C; for alkalinity, from 170.80 to 207.40 mg/L; for total phosphorus, from 0.01 to 1.75 mg/L; for ammonium, from 0.03 to 16.56 mg/L; for nitrite from 0.206 to 0.676 mg/L; for turbidity from 23 to 596 mg/L; for chemical oxygen demand from 50.88 to 168 mg/L; for biochemical demand for oxygen in 5 days from 16 to 58 mg O2/L; for faecal coliforms from 30 to 4500000 B/ml. The statistical analysis is encouraging, showing a temporal evolution in the overall quality of the lower Sebou.

AVALIAÇÃO MULTIVARIADA DA QUALIDADE DAS ÁGUAS SUPERFICIAIS E ÁGUA FINAL DE ABASTECIMENTO PÚBLICO DE BELÉM, PARÁ, BRASIL

MULTIVARIATE ASSESSMENT OF SURFACE WATER QUALITY AND FINAL PUBLIC WATER SUPPLY IN BELÉM, PARÁ, BRAZIL. The present study investigated the sources of variability in the water quality of surface springs that supply the Metropolitan Region of Belém (Pará, Brazil), as well as the treated water produced by the main water treatment station in the region. Data provided by Companhia de Saneamento do Pará were used, referring to physical-chemical and bacteriological analyzes carried out in the period from 2010 to 2020. In addition, precipitation data were considered in this study, in units of mm of rain, obtained by consulting the database of the National Institute of Meteorology. The application of principal component analysis, as an exploratory data analysis tool, allowed the grouping of the most relevant parameters of the results and proved to be efficient in reducing the data set, explaining more than 65% of the total variance, in all objects of study. Thus, it was possible to observe a general profile of the quality of surface water investigated, and, in this way, demonstrate the impact of urban pressure on the environment, as well as the need for maintenance and conservation of surface water resources.

Assessment of Surface Water Quality Based on Landsat 9 Operational Land Imager Combined with GIS and IOT

Assessment of Surface Water Quality Based on Landsat 9 Operational Land Imager Combined with GIS and IOT

Surface water and groundwater quality assessment using the WQI method and human health risk assessment (HHR) in the lower seybouse (Annaba Plain), northeast Algeria

Surface water and groundwater quality assessment using the WQI method and human health risk assessment (HHR) in the lower seybouse (Annaba Plain), northeast Algeria

Assessment and modeling of surface water quality for drinking and irrigation purposes using water quality indices and GIS techniques in the Inaouene watershed, Morocco

Assessment and modeling of surface water quality for drinking and irrigation purposes using water quality indices and GIS techniques in the Inaouene watershed, Morocco

Assessment of surface water quality: Case study of Oued Fez catchment areas (Morocco)

Under sustainable development conditions, water quality and quantity play a crucial role in meeting basic human needs. To meet the growing demand for water, surface water quality management is an important aspect. Consequently, water quality must be monitored and assessed via the use of innovative techniques, such as water quality index (SEQ-Water).For that purpose, water quality of Oued Fez catchment areas was evaluated according to Moroccan water quality guidelines by using the weighted quality index (SEQ-Water), physicochemical parameters, trace elements and bacteriological characterization. Five Sites were chosen after a diagnosis based on different criteria such as activity and density of population. These sites were Amont oued Fez (S1), Oued Fez (S2), Oued Ljawahir (S3), Oued Tgat (S4) and Oued Ain Smen (S5). Physicochemical quality was determined by evaluating Chemical Oxygen Demand (COD), total Kjeldhal nitrogen (NTK), suspended solids (SS), nitrates (NO3-), nitrites (NO2-), ammonium (NH4+), sulphates (SO42-), total phosphorus (TP) and trace elements (Cr, Cd, Cu, Ni, Co, Pb and Zn). Bacteriological analyses were carried out by testing enumeration of total coliforms (TC) and fecal coliforms (FC).Except Oued Ain Smen, physico-chemical parameters exceed by far the Moroccan standards of surface water quality. High concentrations of Se, Cd, Pb and As were detected. Fecal and total coliforms were also present at all sites, and varied from 1150 CF/100 mL to 100,000 CF/100 mL. All results were statistically validated with a p value < 0.05. Overall quality of the water sites assessed basing on the concept of the weight quality index, showed high pollution of the Oued Fez catchments. System based on the concept of the weighted quality index (SEQ-Water) is a suitable method to monitor point sources of pollution in surface water, and could provide a crude guideline for selecting the priorities of possible preventative measures in the proper management of the surface water resources.To summarize, it would be dangerous to use water from these rivers for domestic and agricultural purposes without some form of physical and chemical treatment. Sensitization of the authorities on the extent of water pollution of this Oued and the harmful consequences for man and the ecosystem should be urgent and mandatory.

Effects of source-sink landscape proximity on the spatial–temporal water quality from the perspective of cost distance in an agricultural watershed

Spatial patterns of source-sink landscapes play a critical role in assessing surface water quality. However, this relation may be different due to various proximity of source-sink landscapes. The effect of the source-sink landscape proximity on surface water quality remains poorly understood. The impact of source-sink landscape proximity on the spatial–temporal water quality were quantified based on field monitoring data (2013–2019) in an agricultural watershed. A new approach considering the cost distance of landscape types, slope, and vegetation on the transformation of nutrients from one point to water bodies was used to construct different buffer zones which reflected very high, high, moderate, low, very low proximities, while the subwatershed represented the very low proximity. Then the effects of the source-sink landscape proximity were assessed based on sub-watershed and other four buffers. The resutls showed that the TN and NO3−-N were the main non-point source pollution indices with significant spatial variation (p < 0.05). The water quality index (WQI) was higher during the dry season than during the wet season, indicating that the sampling sites also experienced seasonal variations. The multi-scale analysis demonstrated the significance of the source-sink landscape proximity in improving the quality of surface water. A stronger correlation between the ratios of sink landscape and the main water quality parameters (the TN and NO3−-N) was observed in the low proximity zone, suggestiong that the low proximity zone with moderate non-point source pollution risk was a critical region in water quality management. The results provide important insights into understanding the effects of the source-sink landscape proximity on water quality and how scientific and effective measures can be made to improve water quality.

Rapid assessment of surface water quality using statistical multivariate analysis approach: Oder River system case study

Many physicochemical and biological monitored parameters must be taken into consideration to fully evaluate the surface water environmental condition. However, there are situations where a simple and rapid assessment of the poor water quality situations is critically important. This work presents a universal methodology for monitoring of many parameters simultaneously and early detection out-of-control samples in a real-time mode. The approach uses multivariate statistical quality control chart based on Principal Component Analysis (PCA) model with two well-known measures of abnormal behaviour in a process or system: Hoteling's T2 statistics and Q-statistic. The proposed TQ_PCA quality index provides on-line assessment of the water sample quality, with no specific knowledge and assumptions about control limits for monitored parameters required. A water sample is assessed through the simple control chart using the PCA model established for training/reference samples. The power of the proposed index has been tested using water quality data from the Oder River, including the time of the largest ecological disaster in recent European river history. The proposed index showed excellent analysis performance for physicochemical water quality dataset from Polish stations and physicochemical and biological water quality dataset from German/Frankfurt station, confirming earlier reports. There were consecutive number of alarms reported by the statistical index, a month prior to the disaster when there were no evident changes in the individual parameters. The method presented in this study demonstrated capability of assessment of the major water quality parameters, whose changes preempt the uncommon event. The presented TQ_PCA index could be easily extended to any research involving a large dataset of monitoring parameters from any industrial chemical process.

Assessment of surface and ground water quality around Korba Coalfield, India: an integrated approach of water quality index, multivariate statistics analysis and GIS technique

Assessment of surface and ground water quality around Korba Coalfield, India: an integrated approach of water quality index, multivariate statistics analysis and GIS technique

Artificial Intelligence for Surface Water Quality Evaluation, Monitoring and Assessment

The study utilizes a dataset with seven critical constraints and creates models that are estimated based on various metrics. The goal is to categorize and properly predict the water quality index (WQI) using the suggested models. The outcomes show that the implied models can accurately assess water quality and forecast WQI with high rates of success. Temperature, pH, dissolved oxygen (DO), conductivity, total dissolved solids (TDS), turbidity, and chlorides (Cl-) are some of the six crucial factors used in the study’s dataset. The mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R2) are some of the metrics used to develop and assess the Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) models. The study also makes use of heat maps and correlation graphs to shed further light on the connections between various water quality measures. The color-coded values of the seven parameters, which represent the water quality level of the sample, are displayed on the heat map. The link between the two parameters is shown by the correlation graph between TDS and turbidity, which depicts their correlation coefficient. The study’s results show how effective machine learning algorithms may be as a tool for observing surface water quality. Himachal Pradesh is the tourist hub, so with the rapid increase in the volume of surface water contamination, the application of artificial intelligence will give a better view of data analytics and help with prediction and modeling. It was obtained from the study that the mean square error and root mean square error of ANN and LSTM lie between 0.52–6.0 and 0.04–0.21, respectively. However, the LSTM model’s accuracy is 95%, which is higher than the ANN model. The study highlights the importance of leveraging machine learning techniques in water quality monitoring to ensure the protection and management of water resources. With advancements in machine learning, artificial intelligence (AI) techniques have emerged as a promising tool for surface water quality monitoring. The major goal of the study is to explore the potential of two types of machine learning algorithms, namely artificial neural networks (ANNs) and long short-term memory (LSTM) models, for surface water quality monitoring.

Assessment of Long-Term Surface Water Quality in Mekong River Estuaries Using A Comprehensive Water Pollution Index

Surface water quality (SWQ) has been degraded in the Mekong River Basin under increasing pressures of population growth, economic development, and global climate change. This study employed the comprehensive water pollution index (CWPI) to assess the spatio-temporal variation of SWQ in the downstream Mekong River estuaries. Eight water quality parameters were measured between 2005 and 2021 at 21 sampling sites downstream of the Mekong River. These parameters included total suspended solids (TSS), biological oxygen demand (BOD5), chemical oxygen demand (COD), ammonia (N-NH4+), nitrate (N-NO3-), phosphate (P-PO43-), iron (Fe), and total coliform. Most of the monitoring locations in the estuaries of Ham Luong, Cua Dai, Ba Lai, and Co Chien exhibited slightly to moderately polluted conditions, as indicated by the CWPI values ranging from 0.67-2.91, 0.41-2.20, 0.27-3.02, and 0.37-2.95, respectively. TSS and Fe concentrations consistently exceeded the allowable limits, while the majority of values for N-NH4+, N-NO3-, P-PO43-, and coliform remained within acceptable thresholds. Additionally, parameters indicative of organic pollution, namely BOD5 and COD, displayed a noticeable upward trend between 2005 and 2021. SWQ exhibited significant spatial and temporal variations with TSS, organic matter, nutrients, and iron being the main areas of concern. These findings can provide guidance to policymakers involved in the assessment and enhancement of water quality in the presence of pollutant compounds that lead to a decline in water quality.

Risks of Surface Water Pollution in Southern Vietnam

The study was carried out to assess surface water quality and ecological risks in water bodies in the southern region of Vietnam. The study used monitoring data at 58 locations, which were collected in March, May, June, July, August, October, November, and December of 2022, with 11 water quality parameters (temperature, pH, DO, TSS, BOD, COD, NH4+-N, NO3--N, Fe, Pb, and Cd). Comprehensive pollution index (CPI), ecological risk level, and multivariate statistical analysis methods were utilized. The values of CPI showed that the surface water quality was mildly polluted, moderately polluted, and severely polluted, accounting for 37.93, 46.93, and 15.52%, respectively. In particular, heavy pollution was concentrated in the water bodies of the Sai Gon and Vam Co Rivers. TSS, BOD, COD, NH4+-N, and Fe had a moderate to high level of risk, while water samples contaminated with NO3--N, Pb, and Cd had a level of risk from low to safe. High levels of risk were concentrated in the water bodies of the Sai Gon River and Vam Co River, typically BOD and COD. Based on the impact level, the positions were classified into five groups, with the locations on the Sai Gon River and Vam Co River (Groups 4 and 5) being affected by various waste sources in the inner city of Ho Chi Minh City. The PCA results presented three sources, such as discharge from residential areas, soil erosion, and agriculture, that have caused water quality fluctuations and increased the impact on the water quality of water bodies. Measures to protect water resources according to environmental protection laws must be implemented soon to minimize ecological risks from water-polluting sources. Doi: 10.28991/CEJ-2023-09-11-06 Full Text: PDF