No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Assessment of water quality and apportionment of pollution sources of an urban lake using multivariate statistical analysis
Abstract
The Lake Gulshan has gained special attention to restore its water quality for public health safety, congenial lake bund, and aquatic lives as the lake is a popular recreational place and neighbourhood of critical residential and diplomatic zones. Therefore, this study assessed water quality and pollution sources of Lake Gulshan, located in the city of Dhaka in Bangladesh during dry and wet seasons, using the water quality index (WQI) rating system, Principal Component Analysis (PCA), and Positive Matrix Factorization (PMF) model. Extremely low levels of dissolved oxygen (as low as 0.2 mg/L in the dry season and 0.8 mg/L in the wet season) in the lake water suggest that it is almost impossible for any living organisms to survive. Consequently, high levels of biochemical oxygen demand (BOD, a measure of biodegradable organic matter up to 80 mg/L), Phosphate, and Nitrate (indicators of eutrophication potential as far as 5.06 mg-P/L and 228 mg-N/L) were detected in the lake water, indicating severe anthropogenic pollution. A strong correlation (Pearson with 2-tailed t-test, r = 0.85 in the dry season, r = 0.76 in the wet season, p
... In recent years, various studies have assessed the water quality and heavy metal concentrations in Dhaka's lakes, for example, Ferdoushi et al. (2016), Islam et al. (2014), Kazi et al. (2009), Miah et al. (2017, Nabila et al. (2022), Rahman et al. (2021), and Uddin et al. (2023), but only a few have focused on critical issues like eutrophication, which affects nearly every urban lake. However, immediate focus is needed for restoration and conservation due to increasing nitrate and phosphate levels, along with declining water transparency. ...
... TDS is significant to EC (r = 0.992, p < 0.01). Factor −2 is the intrusion of salts from soil, wastewater, and other human activities (Hashan & Moniruzzaman, 2022;Liu et al., 2012;Nion et al., 2020;Rahman et al., 2021). Factor-3 (15% of the total contribution) consists of turbidity (58.44%), ...
... Chl-a is strongly significant to NO 3 − (r = 0.974, p < 0.01), and turbidity is significant to pH (r = 0.926, p < 0.01) and TDS (r = 0.892, p < 0.01). Factor-4 (44% of the total contribution) denotes the presence of large amounts of phytoplankton that was greatly witnessed in lake water which resulted in the color formation to be green (Dodds, 2007;Kazi et al., 2009;Nion et al., 2020;Rahman et al., 2021). Visualization in fingerprint is done in Fig. S2 and factor contributions are noted in Fig. 10. ...
Urban lakes are vital to ecosystems, providing essential services and recreational spaces in densely populated megacities. However, rapid urbanization and anthropogenic activities, particularly eutrophication driven by macronutrient accumulation, severely threaten these water bodies. This study underscores the critical need for continuous trophic state monitoring to sustain fish, wildlife, and plant ecosystems. The trophic status of Dhanmondi, Gulshan, and Banani Lakes in Dhaka City, Bangladesh, was assessed using Carlson’s Trophic State Index (CTSI) and Burn’s Trophic Level Index (BTLI), based on chlorophyll a (Chl-a), total phosphorus (TP), Secchi disc depth (SD), and total nitrogen (TN). Water samples from five sites per lake were analyzed for physicochemical parameters from June 2023 to May 2024, revealing monthly and seasonal variations. The study revealed that Dhanmondi Lake’s CTSI ranged from 69.3 to 79.5 (June 2023 to March 2024), indicating initial “Eutrophic” conditions progressing to “Hypereutrophic.” Gulshan Lake consistently showed “Hypereutrophic” conditions, with CTSI values between 84.1 and 97.3. Banani Lake was “Eutrophic” in June and July 2023, transitioning to “Hypereutrophic” from August 2023 to May 2024 (84.1–97.7). The Trophic Level Index (TLI) showed the “Hypereutrophic” status with a progressive monthly escalation for all the lakes. The Water Quality Index (WQI) categorized the lakes as “Poor” to “Very Poor” from June to August 2023, becoming “Unsuitable” from September 2023 to May 2024, indicating significant anthropogenic stress. Principal component analysis (PCA) identified nutrient infiltration, soil erosion, waste discharge, and organic residue accumulation as key pollution drivers. The study advocates for a multi-sectoral strategy to regulate nutrient loading and mitigate eutrophication, emphasizing best management practices for urban lake conservation.
Graphical abstract
... Principal component analysis (PCA) is another robust dimension reduction technique that interprets the variance in an original set of inter-correlated variables by converting them into an independent and uncorrelated variable, referred to as principal components (PCs). PCA identifies the most influential parameters of water quality that are not detectable by simple correlation analysis by preserving much of the original information (Rahman et al. 2021;Azhari et al. 2022;Mechal et al. 2024). ...
... DO levels < 3 mg/L pose a grave concern for the survival of fish, and a minimum range of 4-5 mg/L is essential for aquaculture (Iwegbue et al. 2023). Low levels of DO can lead to negative outcomes including the death of aquatic organisms and foul smell due to the generation of hydrogen sulfide (Rahman et al. 2021). The Bheemasandra Lake had extremely low levels of DO and could not be detected in both seasons, which demonstrates the serious pollution risks in these waters. ...
... Prior to the monsoons, PC1 contributed to 28.95% of the total variance, exhibiting strong factor loadings for Ca 2+ , TH, Mg 2+ , TDS, and EC and moderate loadings for PO 4 3− and Cl − . PC1 represented the influence of both geological/rock-water interactions and anthropogenic activities owing to the strong loadings for inorganic pollutants (Ahmad et al. 2024) and organic point source pollutants (TDS and PO 4 3− ), as elucidated by Rahman et al. (2021). Ca 2+ and Mg 2+ salts were predominantly responsible for elevated TH and EC of the water (Gulgundi and Shetty 2018). ...
An integrated approach combining water quality indices (WQIs), multivariate data mining, and geographic information system (GIS) was employed to examine the water quality of Bheemasandra Lake, located adjacent to a sewage treatment plant (STP) in Tumakuru city, India. The analysis of 22 lake water samples, examined before and after the monsoons, revealed that the physicochemical parameters namely — electrical conductivity, biochemical oxygen demand, turbidity, total dissolved solids, ammoniacal nitrogen, nitrates, phosphates, magnesium, total hardness, total alkalinity, and calcium — exceeded the acceptable limits stipulated by national and international standards. The Canadian Council of Ministers of the Environment WQI (pre-monsoon: 25.3; post-monsoon: 33.9) and weighted arithmetic WQI (pre-monsoon: 3398; post-monsoon: 2093) designated the water as unsafe for drinking. Irrigation WQIs (sodium adsorption ratio, sodium percentage, residual sodium carbonate, magnesium hazard, permeability index, and potential salinity) implied water’s suitability for irrigation. However, electrical conductivity indicated otherwise. Industrial WQIs (Larson–Skold Index, Langelier Index, Aggressive Index, and Puckorius Scaling Index) illustrated scaling propensity and the chloride sulfate mass ratio alluded galvanic corrosion potential. Hierarchical cluster analysis gathered 22 sampling points into two clusters (cluster 1: relatively lower polluted regions; cluster 2: highly polluted regions) for each season based on similarities in water features. Principal component analysis extracted four (79.07% cumulative variance) and six (87.14% cumulative variance) principal components before and after the monsoons, respectively. These components identified the primary pollution sources as urban sewage and natural lithological processes. WQI maps, created using the inverse distance weighted interpolation technique, enhanced the visualization of spatial–temporal variations. This study highlights the dire consequences of urbanization, STP pollution, and sewage management failures, necessitating that concerned authorities should implement policies and measures to curb the negative impacts on the environment and public health.
... Multivariate statistical models are utilized to determine patterns of variability in random variable samples. There are multiple statistical models that were used in the investigation of the water quality of surface waters and groundwater such as the cyclostationary processes (Boudou and Viguier-Pla 2021), soil and water assessment tool (Kim and Kim 2021), positive matrix factorization (Rahman et al. 2021), water quality index (WQI) (Uddin et al. 2021), exploratory factor analysis (Kim et al. 2017), and principal component analysis (PCA) (Karamizadeh et al. 2013). Among these tools, PCA is commonly utilized over the other statistical models. ...
... It is a powerful multivariate analytic method for selecting the most notable features in a dataset. This is commonly used to provide qualitative information on contaminated sources in a system (Rahman et al. 2021). PCA reduces the multidimensionality of data to small proportions while maintaining most of the information of the original data and its variability (Karamizadeh et al. 2013). ...
The Mananga River in the Philippines has been classified as a Class A river in 1997. Since then, the river has significantly deteriorated due to pollution, especially in the downstream area around Talisay in the Cebu region. In this study, the water quality parameters – namely, dissolved oxygen (DO), biological oxygen demand (BOD), and total suspended solids (TSS) – were assessed using principal component analysis (PCA). Water quality data were obtained from the Department of Environmental and Natural Resources–Environmental Management Bureau Region 7. The water samples were collected on a quarterly basis from 2016–2019. The effect of weather conditions on water quality and significant relationships between the water quality parameters were determined. In addition, the comparison of water quality in each sampling station was investigated. Results show that about 84.3% of the total variance in water quality can be attributed to two significant principal component scores. Evident correlations were observed such as DO and BOD are negatively correlated, whereas a positive correlation exists between DO to RH and wind speed, BOD to temperature, and TSS to wind speed. Furthermore, negative correlations are observed between DO to temperature and wind direction, BOD to rainfall, and TSS to wind direction and rainfall. In the overall analysis of the results, the heavier the influence of a variable, the more likely it is to contribute to affecting the water quality. Therefore, this can alter the overall distribution within the plots and the correlations among the variables. The findings are a predictive measure of future changes and trends in the Mananga River. Therefore, the results of the present work will be used in environmental monitoring, environmental management, and assistance for the rehabilitation of the Mananga River using PCA.
... Numerous studies have been conducted globally to assess water quality (Ejaz et al. 2024;Hussein et al. 2024;Mohseni et al. 2024;Rahman et al. 2021;Ren et al. 2023;Sakaa et al. 2022;Wong et al. 2020;Wong et al. 2021;Zhang et al. 2023). Hussein et al. (2024) assessed groundwater quality for irrigation purposes using the Water Quality Index (WQI) in the Wilaya of Naama watershed in southwestern Algeria. ...
Identifying the primary pollution source poses a challenge in river watersheds characterized by diverse land-cover types and mixed pollution sources. We addressed this challenge by focusing on the major tributaries influencing the water quality of the Mankyung River’s mainstream, successfully identifying the primary pollution source. Additionally, it identified the limiting nutrient for algal growth in the Mankyung River, proposing an alternative strategy to enhance water quality and mitigate algal growth. Positive matrix factorization (PMF) was employed to discern pollution sources in major tributaries, namely Jeonju-cheon and Iksan-cheon, impacting mainstream water quality. For Jeonju-cheon, pollution from urban and agricultural areas, including wastewater treatment plants, emerged as the primary source. For Iksan-cheon, pollution from urban and agricultural areas predominated. The nitrogen-to-phosphorus ratio and correlation analysis revealed that total phosphorus is the limiting factor for algal growth. Furthermore, scenarios to improve water quality and reduce algal growth were developed, and the Environmental Fluid Dynamic Code (EFDC) was used in the simulation, while the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) was used in water quality assessment. The findings demonstrated improved water quality and decreased algal blooms in the downstream Mankyung River region. This research provides a foundation for applying PMF, the EFDC, and the WQI in tracking pollution sources and enhancing water quality in rivers.
... When these pollutants degrade, they can lead to long-lasting toxic effects, like DDE. These are known as stock pollutants with a lower absorption rate, leading to their buildup in water resources and causing toxic effects as their concentrations rise (Kibambe et al. 2020;Kasonga et al. 2021;Rahman et al. 2021). Another category involves pollutants that can be absorbed and have their toxicity levels reduced through dilution. ...
Water pollution, driven by a variety of enduring contaminants, poses considerable threats to ecosystems, human health, and biodiversity, highlighting the urgent need for innovative and sustainable treatment approaches. Ozone-based advanced oxidation processes (AOPs) have demonstrated significant efficacy in breaking down stubborn pollutants, such as organic micropollutants and pathogens, that are not easily addressed by traditional treatment techniques. This review offers an in-depth analysis of ozonation mechanisms, covering both the direct oxidation by ozone and the indirect reactions facilitated by hydroxyl radicals, emphasizing their effectiveness and adaptability across various wastewater matrices. Significant progress in the combination of ozonation with additional technologies, including UV irradiation, hydrogen peroxide (H₂O₂), catalytic systems, and biological treatments, is examined, highlighting their effectiveness in enhancing pollutant breakdown, increasing biodegradability, and reducing secondary pollution. Hybrid methods, including catalytic ozonation and ozone-biological treatment, show significant enhancements in process efficiency and cost-effectiveness, while effectively tackling challenges associated with energy use and byproduct generation. Despite the promising possibilities, obstacles remain, such as scalability issues, high operational costs, and the risk of generating potentially harmful transformation products. Cutting-edge approaches, including the creation of sophisticated catalysts, integration of processes, and refinement of reactor designs, are suggested to address these challenges and improve the real-world implementation of ozone-based advanced oxidation processes. This review highlights the significant potential of ozone-based advanced oxidation processes as sustainable approaches for wastewater treatment, providing an essential route to environmental conservation and safeguarding public health.
... At the same time, these are more susceptible to polycyclic aromatic hydrocarbon (PAH) bioaccumulation than natural and shallow lakes in the same geographic region [40]. Thus, managing the runoff requires and encourages the separate use of sewers for domestic and stormwater networks for a better quality of water and strengthening policy for water pollution control management [41]. ...
The water quality of many lakes around the world have declined due to continuous urbanization with runoffs being one of the significant contributors. This narrative review focuses on the presentation of existing papers that dis-cussed runoff as a contributing factor to urban lakes’ declining water quality and the different management approaches that researchers might want to prioritize in future studies. The review paper also explores the different sources of runoffs and the significant contributors to the contamination of lakes in urban areas such as sewage discharges, industrial effluents, and runoff, and their resulting impacts on the quality of these water bodies. Different management practices adopted to enhance Urban Lake water quality such as watershed management, pollution management, stormwater management, and limiting nutrient loading in lakes are also explored in this review paper. The effectiveness of these practices is evaluated, and future research directions are suggested. The findings of this review indicate that runoffs play a significant role in the declining water quality of urban lakes, and effective management practices are necessary to protect these valuable water resources.
... Introduction. Lake pollution has been a growing environmental concern worldwide due to anthropogenic activities (Rahman et al 2021). The proportion of freshwater on earth's surface is only 2.5% of which only 1% is accessible for use. ...
... The high concentrations of Mn in Ventilla during the wet season are due to its presence in the interstitial waters of the sediments [72] and to its slow precipitation kinetics and solubility under reducing conditions [73], which cause a higher concentration in the water column. Direct exposure of mammals to Mn sources such as water causes neurotoxic problems [74]. The high Ba concentrations in Atuén and Cabildo during both seasonal periods are due to the availability of this element, which occurs naturally in all igneous, metamorphic, and sedimentary soils and rocks [75], suggesting its presence in water sources. ...
Cattle ranching is a fundamental economic activity in northern Peru, where proper management of water resources is crucial. This study, a pioneer in the region, evaluated water quality and its suitability for human consumption, vegetable irrigation, and livestock production. It is also the first study to document the presence of metals and metalloids in vulnerable areas because they are located at the headwaters of river watersheds. The spatiotemporal evaluation of physicochemical parameters, metals, and metalloids was performed in five micro-watersheds (Cabildo, Timbambo, Pomacochas, Atuen, and Ventilla) from water samples collected in the dry season (October 2017) and wet season (March 2018). The parameters were analyzed using microwave plasma atomic emission spectrometry. The results were contrasted with international and Peruvian quality standards related to dairy cow production. The highest values of pH, total dissolved solids, and electrical conductivity were reported during the dry season, and the highest turbidity during the wet season. Of the metals evaluated, arsenic (As) was omnipresent in all the micro-watersheds, followed by lead (Pb).
In contrast to World Health Organization regulations, concentrations of As, cadmium (Cd), Pb, and iron represent a risk; according to Peruvian regulations, As and Pb exceed the concentrations established for use in animal drinking water and vegetable irrigation, and according to water guidelines for dairy cattle, concentrations of As, Pb, Cd, and Al exceed the permitted limits. The high concentrations of these metals in the study area are attributable to a synergy between natural factors, such as Andean geology and livestock activity. The data reported will allow for proper water resource management, pollution prevention, and the design and adoption of mitigation measures.
... The combined effects of several quality parameters facilitates the identification of weighted variables with the greatest impact on the alteration. In other words, it could measure how suitable is the studied water for use (Rahman et al., 2021;Gayer et al., 2021). However, one of the main problems reported by Uddin et al. (2021) creates uncertainty in the use of WQI. ...
La revista Tecnura es una publicación institucional de la Facultad Tecnológica de la Universidad Francisco José de Caldas, de carácter científico-tecnológico. Las áreas de interés están enfocadas a todos los campos de la ingeniería, como la electrónica, telecomunicaciones, electricidad, sistemas, industrial, mecánica, catastral, civil, ambiental, entre otras. La revista está dirigida a docentes, investigadores, estudiantes y profesionales interesados en la actualización permanente de sus conocimientos y el seguimiento de los procesos de investigación científico-tecnológica, en ingenierías. Tiene como misión divulgar resultados de proyectos de investigación en el área de las ingenierías, a través de la publicación de artículos originales e inéditos.
... This increased metabolic activity can lead to a higher BOD and, consequently, a lower WQI. Similarly, low dissolved oxygen levels can indicate poor oxygen saturation in water, affecting the survival of aquatic organisms and contributing to lower WQI scores (Meshesha et al. 2020;Pandit et al. 2023;Rahman et al. 2021b). The correlation matrix for heavy metals revealed their respective influences on the construction of the WQI (Fig. 6b). ...
The Turag River, located in Dhaka, Bangladesh, has emerged as a pivotal case study for assessing water pollution. It faces multiple sources of pollutants, including industrial discharges, municipal sewage, agricultural runoff, and urban effluents, which significantly impact water quality. This study employed an integrated approach, combining a Water Quality Index (WQI), machine learning algorithms (MLA), and geographic information system (GIS), to comprehensively evaluate the Turag River’s water quality. Thirty water samples, spanning from the river's mouth to its most polluted areas, were collected and analyzed for various physicochemical parameters (e.g., temperature, pH, DO, BOD, TDS, turbidity, total hardness, and transparency) and heavy metal concentrations (e.g., Na, Mn, Cr, As, Ca, Pb, Zn, Cu, and Fe). The results were assessed against standards set by the World Health Organization (WHO) and the Department of Environment (DoE) of Bangladesh. Our findings revealed a significant deterioration in water quality downstream, primarily driven by intensified human activities. Physicochemical parameters indicated that most samples fell within the “poor” to “unfit for consumption” categories, while heavy metals exhibited a range from excellent” to “unfit for consumption.” This study not only advances our understanding of water pollution dynamics but also equips decision-makers with critical insights to safeguard public health, protect water resources, and sustain vital clean waterdependent economic activities. Furthermore, it highlights the urgency of implementing effective pollution control measures to restore ecological equilibrium of the Turag River and similar waterbodies elsewhere.
... This might result in lower quantities of physiologically accessible oxygen, which can result in species extinction in the aquatic system. (Sarasota County, 2023) A significant study has shown shocking results of DO 0.2 mg/L to 3.20 mg/L (standard 4.5 to 8 mg/L) in the studied lake water which is almost impossible for any living organism to survive (Kalimur Rahman, 2021). This study backs and explains the reason for the odor from the very lake. ...
The paper portrays a linear model for synchronous prediction of the dissolved oxygen (DO) level in a protected urban lake by using independent variables in real-time monitoring of the water quality parameters. Multi-linear regression and machine learning techniques were applied to the Dissolved Oxygen (DO) using the basic four parameters of Water Quality Index (WQI). Three real-time industry standard sensors PHEHT, CTZN, OPTOD were used for sampling, data was then interpolated through ArcGIS kriging method. 25 correlations were checked through the ML algorithm, a correlation heat map was produced and the top five relations were taken under consideration and validated by r-score and root mean squared error (RMSE) to develop the linear regression model. The performance of the model was validated through the RMSE, mean squared error (MSE), and mean absolute error (MAE) the r2 accuracy came to 0.983 when it is checked against the sample data. The suggested model can be used as a technique for unknown or malfunctioned sensor’s null DO data prediction.
... Based on the 2015-2035 Jember Regency Master Plan, the Patrang, Sumbersari, and Kaliwates districts will be developed as an urban system (Perda Kabupaten Jember No.1, 2015). Thus, in line with an expected increase in population and various community activities, the potential for pollution in the Bedadung River will also increase (Puspita et al., 2020;Rahman et al., 2021). River water pollution in urban areas is caused by industrial and household waste. ...
Land use influences the water quality of rivers. The variety of community activities in urban areas and a poor domestic sewage system are thought to affect the water quality of the Bedadung River, Jember Regency, Indonesia. Point source pollution is the dominant cause of degradation in the quality of the water in the Bedadung River, as identified by dissolved oxygen (DO) and Biochemical Oxygen Demand (BOD). This study was conducted to determine the potential point source pollution load of the Bedadung River in an urban area using land use information and pollution load-BOD data. All data were combined and processed using a Geographical Information System (GIS). The data were analyzed and plotted on a map depicting the distribution of potential point source pollutant loads in the Bedadung River urban area segment in Jember Regency. The results of the land use analysis in the urban area segment show that paddy fields accounted for 18.97% of the total study area, with fields at 5.98%, gardens at 12.85%, and rivers at 12.25%, while settlements covered the largest land area, on 49.96%. The results for the potential point source pollution load show that Kaliwates village had the highest potential pollution load value, at 13.966 kg/day. The lowest was Antirogo village, at 0.004 kg/day, while the total point source pollution load was 36.31 kg/day. An evaluation of point source pollution impact is required to control river pollution in urban areas, namely the development of communal Waste Water Treatment Plant (WWTP) in urban area segments.
... Furthermore, a combination of three methods (WQI, PCA and PMF) has been employed to analyze the pollution reason of Gulshan Lake in Dhaka City, Bangladesh, in the dry season. The result indicated that the pollution was mainly due to the urban garbage point source pollution, and the contribution of surface runoff source in the rainy season accounted for 41.80% (Rahman et al., 2021). Similarly, based on the investigation of HACA and PCA models, it was speculated that the downstream pollution of Yamuna River (India) was attributed to the excessive discharge of untreated/partially treated sewage (Sameer & Ashok, 2021). ...
In order to understand the sources of pollutants and the temporal and spatial distribution characteristics of the water quality in Cihu Lake, China, the monitoring data of seven water quality indicators from 12 sampling sites from 2015 to 2019 were selected, and the temporal and spatial variation laws of the water quality and pollution sources were analyzed by the use of the multivariate statistical analysis method. The results show that nitrogen and phosphorus pollution in the lake is dominant. The average concentrations of total nitrogen (TN) and total phosphorus (TP) exceed the surface water quality Class III standards by 1.6 and 2.2 times, respectively. Spatially, the results of the cluster analysis showed that the water quality in Cihu Lake can be categorized into three regions: the northern half of the lake, the southern half of the lake, and the canal entering the lake. Temporally, the water quality in these three regions can be classified into three categories: March to May (the northern half of Cihu Lake), September to November (the southern half of Cihu Lake), and September (the canal entering Cihu Lake). The discriminant analysis results showed that NH3-N, TN, CODCr, and BOD5 are the main factors that affect the uneven spatial distribution of the water quality of Cihu Lake, while TN, DO, and CODMn are the main factors that affect the temporal difference in the northern half of Cihu Lake, and NH3-N, TP, CODCr, DO, CODMn, TN, and TP are the main factors affecting the temporal difference in the southern half of Cihu Lake and the canal entering Cihu Lake. It was found that the water pollution in the study area can be mainly attributed to the incoming water and urban domestic pollution. The main pollution sources for the canal entering Cihu Lake and the southern half of Cihu Lake are the water from the sewage treatment plant and the domestic sewage that has not been intercepted, while the northern half of Cihu Lake is mainly affected by surface runoff, mixed rainwater and sewage, and internal pollution.
... PCA and MLRA are used to evaluate the contribution of climate, urbanization, and nutrient load to changes in water chemical characteristics [27]. Multivariate statistical analysis is applied to the evaluation of water quality and the analysis of pollution sources in urban lakes [28]. Akbar et al. used PCA and GIS to analyze risk factors affecting groundwater quality [29]. ...
Water bodies in urban parks are important for scenic and recreational areas, yet algal bloom problems seriously affect public use; therefore, it is important to study the features of algal density (AD) changes and environmental driving factors (EDFs) for water body management. In this study, five scenic water bodies in urban parks of Xinxiang City are taken as the objects for studying the AD and nine environmental indicators from March to October 2021, in accordance with time-series monitoring. The features of AD change in different layers of the water bodies are analyzed, and the main environmental impact factors of AD changes are screened by Pearson correlation analysis and principal components analysis (PCA), with main EDFs further extracted according to multiple linear regression analysis (MLRA), and multiple regression equation established. According to the data, ADs at different depth layers increase at first and then decrease with time, reaching the peak in August. According to the PCA, three principal components (PCs) are extracted in the 0.5 m and 1.0 m water layer, the variance contribution of which is 87.8% and 87.3%, respectively. The variance contribution of four PCs extracted in the 1.5 m water layer is 81.7%. After MLRA, it is found that the main EDFs of algal density in the 0.5 m water layer are electrical conductivity (EC), dissolved oxygen (DO), and water temperature (WT), in the 1.0 m water layer are WT and DO, and in the 1.5 m water layer are WT, DO, total nitrogen (TN), and EC. Generally speaking, WT and DO are decisive factors affecting AD. The EDFs’ leads to the AD changes in different water layers are analyzed, and it is proved that stratification occurs in scenic water bodies in urban parks. This study is expected to provide basic data and a theoretical basis for ecosystem system protection and water quality management of scenic water bodies in urban parks.
... Seasonal variation in Lake Pomacochas, which can also be considered a peri-urban lake due to its proximity to the town of Florida-Pomacochas, suggests that municipal wastewater is the major contributor pollutant in the dry season. The main concentration variation source in parameters in the wet season is due to surface runoff and soil leaching processes (Rahman et al., 2021). The analysis of water parameters at depth shows significant differences because the elements that enter the lake tend to adsorb, mobilize, and settle to the bottom (Tang et al., 2016). ...
Lakes are water bodies that play an essential role as water sources for humanity, as they provide a wide range of ecosystem services. Therefore, this study aimed to evaluate Lake Pomacochas, a high Andean lake in the north of Peru. A variety of parameters were studied, including physicochemical parameters such as temperature (T°C), dissolved oxygen (DO), potential hydrogen (pH), electrical conductivity (EC), turbidity, total dissolved solids (TDS), biochemical oxygen demand (BOD), alkalinity, and chlorides hardness; the concentrations of nitrates, nitrites, sulfates, and ammonium; elements such as aluminum (Al), calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), and boron (B); as well as metals and metalloids such as zinc (Zn), cadmium (Cd), copper (Cu), lead (Pb), and arsenic (As). In addition, pH, Zn, and Cu were evaluated at the sediment level. It is important to note that all parameters evaluated in the water matrix showed significant differences in the seasonal period and depth levels. In comparison, the parameters evaluated at the sediment level had no significant differences between the seasonal period and sampling points. As for the seasonal period, the variables that were higher for the dry season were electrical conductivity, total dissolved solids, and lead while that for the wet season were biochemical oxygen demand, zinc, magnesium, turbidity, calcium, dissolved oxygen, temperature, and potential hydrogen. At the depth levels, parameters such as total dissolved solids, lead, and arsenic had similar behavior for the three depths evaluated. According to national standards, latent contamination by cadmium and lead was found in the lake water from the ecological risk assessment. However, by international standards, all sampling stations showed a high level of contamination by cadmium, lead, zinc, copper, and arsenic, which represents a potential risk for the development of socioeconomic activities in the lake. At the same time, the evaluation of sediments did not present any potential risk.
... All projected findings, except one upstream location, have revealed low water quality. Through 12 inputs and one output, the neural network model was trained and verified using the number of hidden layers (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20), hidden layer neurons (5, 10, 15, 20, and 25), transfer training, and learning functions. According to their research, artificial neural network with eight hidden layers and 15 hidden neurons accurately predicted the WQI with an accuracy of 0.93. ...
Various pollutants have had a substantial impact on the quality of water in recent years. The quality of water directly impacts human health and the environment. The water quality index (WQI) is an indicator of effective water management. Water quality modelling and prediction have become essential in the fight against water pollution. The research aims to build an efficient prediction model for river water quality and to categorize the index value according to the water quality standards. The data has been collected from eleven sampling stations located in various locations across the Bhavani River, which flows through Kerala and Tamilnadu. The water quality index is determined by 27different parameters affecting water quality like dissolved oxygen, temperature, pH, alkalinity, hardness, chloride, coliform, etc. Data normalization and feature selection are done to construct the dataset to develop machine learning models. Machine learning algorithms such as linear regression, MLP regressor, support vector regressor and random forest has been employed to build a water quality prediction model. Support vector machines (SVM), naïve bayes, decision trees, MLP classifiers, have been used to develop a classification model for classifying water quality index. The experimental results revealed that the MLP regressor efficiently predicts the water Quality index with root mean squared error as 2.432, MLP classifier classifies the water quality index with 81% accuracy. The developed models show promising output concerning water quality index prediction and classification.
... Turag River has the highest level of organic forms of discharge, as observed among all the rivers in Dhaka City. Outfalls with greater COD levels are more likely to include industrial pollutants comprising inorganic and organic chemicals, which indicates a higher toxicity level than samples with lower COD levels (48). Minerals, alkalis, certain colloidal and dissolved solids in water, some acids, sulfates, metallic ions, etc., are all included in the total dissolved solids (TDS) category (49). ...
Dhaka, the capital city, which is the nerve center of Bangladesh, is crisscrossed by six different rivers. A network of peripheral rivers connects the city and functions as a natural drainage system for a massive amount of wastewater and sewage by the increased number of inhabitants impacting the overall environmental soundness and human health. This study intended to identify and characterize the outfalls along the peripheral rivers of Dhaka city with the assessment of different pollution indices such as comprehensive pollution index (CPI), organic pollution index (OPI), and ecological risk indices (ERI). The study evaluated the status of the pollution in the aquatic system in terms of ambient water quality parameters along the peripheral rivers due to discharge from outfalls with a particular focus on waste load contribution. Among the identified outfalls, the majority are industrial discharge (60%), and some are originated from municipal (30%), or domestic sewers (10%). Water quality parameters such as suspended solids (SS), 5-day biochemical oxygen demand (BOD5), and Ammoniacal Nitrogen (NH3-N) for most of the peripheral rivers deviated by as much as 40–50% from industrial discharge standards by the environment conservation rules, Bangladesh, 1997. Based on the CPI, the rivers Buriganga, Dhaleshwari, and Turag could be termed as severely polluted (CPI > 2.0), while the OPI indicated heavy organic pollutant (OPI > 4) contamination in the Dhaleshwari and Buriganga rivers. The associated pollution indices demonstrate a trend for each subsequent peripheral river with significant pollution toward the downstream areas. The demonstrated waste loading map from the outfalls identified sources of significant environmental contaminants in different rivers leading to subsequent ecological risks. The study outcomes emphasize the necessity of systematic investigation and monitoring while controlling the point and non-point urban pollution sources discharging into the peripheral rivers of Dhaka city.
... The deterioration of sanitary status. The identification of these pollutants and the paths of their inflow from the catchment to surface waters in the city area will allow us to select the appropriate solutions based on the use of environmental biotechnologies that will minimize their degrading effects on the aquatic environment [28][29][30][31]. ...
The aim of this study was to assess the efficiency of the innovative SED-BIO system in limiting the inflow of pollutants to Jelonek Lake. The analyses were conducted in the Gniezno Lake District in Greater Poland (the western part of Poland). Physical and chemical analyses were conducted in the years 2016-2019. The results demonstrate that the system is highly effective in the reduction of such nutrients as nitrogen (NO3 −-63%; NH4 +-14.9%) and phosphorus (PO4 3−-19.3%). Although the presence of cyanobacteria was confirmed practically throughout the whole monitoring period of the system (2016), the specimens found in most samples were not toxigenic genotypes with a potential to produce microcystins. Microcystins (3 μg•L −1) were detected only once, immediately after the SED-BIO system had been installed in the river and pond, which demonstrates that this natural toxin was eliminated from the additional pool of contaminants that might be transported to Jelonek Lake.
Effective monitoring and predicting surface water quality are vital for sustainable water resource control. Traditional in-situ techniques are regularly constrained by their time-consuming nature and restrained spatial coverage. This study seeks to develop a predictive version that combines physio-chemical water quality parameters with remote sensing indices derived from the Sentinel-2A dataset to enhance accuracy and spatial attainment. The research focuses on four urban tanks in Coimbatore namely Krishnampathy, Selvampathy, Kumaraswamy and Ukkadam Periyakulam. The physio-chemical parameters for assessing the water quality which include pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Dissolved oxygen (DO), Calcium (Ca), Magnesium (Mg), Total hardness, Chloride (Cl-), Carbonate (Co3-) and Bicarbonate (HCo3-) have been measured, additionally for the detection of surface water extent using remote sensing indices namely Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Water Ratio Index, Normalized Difference Chlorophyll Index (NDCI) indices which were extracted from sentinel-2A datasets. The parameters such as EC, TDS, Ca2+, Cl- and Total hardness show a high coefficient of determination (R2). Correlation and regression techniques have been employed to integrate these datasets, resulting in the development of a robust predictive model. By combining these two information sources, the model is constructed using stepwise regression analysis. The model's accuracy turned into established towards ground-truth records, showing large improvements whilst far away Remote sensing indices had been covered.
Despite potential contamination, tap water remains the primary source of drinking in megacities. However, the sources of heavy metal(oid)s contamination and associated health hazards have not been thoroughly addressed in many developing cities, including Dhaka. Therefore, we made the first attempt to assess tap water quality in Dhaka City using indices, identify pollution sources with state-of-the-art techniques, and quantify associated health risks. Tap water samples from 35 locations were collected and analyzed for physicochemical properties and heavy metal(loid)s concentrations. While most parameters were within acceptable ranges, Hg (1.18 ± 0.15 µg/L) exceeded safety thresholds with concerns for Mn (51.08 ± 2.3 µg/L) and Fe (177.34 ± 5.6 µg/L). The calculated indices indicated that Dhaka City’s tap water ranged from unfit (Heavy Metal Evaluation Index, HEI: 2.61), very poor (Heavy Metal Pollution Index, HPI: 95.67, Water Quality Index, WQI: 37.76), moderately affected (Metal Index, MI: 2.61, Synthetic Pollution Index, SPI: 0.96) to slightly polluted (Single-factor Index, Pij: 2.61, Nemerow Pollution Index, NPI: 1.41), healthy but not tasty (Taste Index, TI: 1.8, Health Index, HtI: 10.41), with Matuail, followed by Jurain, being the most contaminated. Non-carcinogenic health risk (NCR) values revealed that children were twice as susceptible to health risks from Pb, Co, and As. Alongside, Carcinogenic health hazards risk (CR) expressed potential cancer risks from Cr<Ni<Cd<As<Pb. Positive Matrix Factorization, Principal Component Analysis, and Pearson analysis identified industries like steel, battery, paint, tanneries, etc. as dominating pollution sources. This study provides evidence to support improved water management and distribution systems in Dhaka and other megacities.
The discharge of domestic sewage and waste oil from fishery activities can cause adverse impacts on coastal seawater in bays and estuaries. The Bohai Sea near Tianjin features strong water closure and weak self‐purification ability. The objective evaluation and analysis of pollution characteristics are crucial for assessing the quality of coastal seawater. This evaluation is essential for the sustainable development of traditional marine fisheries and serves as a powerful tool for government decision‐making. To this end, we constructed an entropy weight‒grey correlation technique for order preference by similarity to an ideal solution (TOPSIS) model (EWGCT) based on the traditional TOPSIS evaluation approach to evaluate the water quality of five fishing ports and operation areas. The spatial distribution characteristics, pollution characteristics, and key impactful indicators were identified via a geographic information system (GIS) and multivariate statistical analysis. The results show that (1) the EWGCT has the ability to rank water quality universally and evaluate it based on the comprehensive impact of all pollution factors; (2) petroleum (PETRO) was affected mainly by the waste oil discharged, and suspended solids (SS), dissolved inorganic phosphate (DIP), and fecal coliform bacteria (FCB) were affected mainly by the domestic sewage discharged; and (3) effective management of fishing vessel discharge is important for ensuring the quality of the seawater environment. By establishing the EWGCT, the reliability and rationality of the evaluation results are verified, which can provide a reference for the formulation of development strategies for coastal cities.
Urban lakes are vital to ecosystems, providing essential services and recreational spaces in densely populated megacities. However, rapid urbanization and anthropogenic activities, particularly eutrophication driven by macronutrient accumulation, severely threaten these water bodies. This study underscores the critical need for continuous trophic state monitoring to sustain fish, wildlife, and plant ecosystems. The trophic status of Dhanmondi, Gulshan, and Banani Lakes in Dhaka City, Bangladesh, was assessed using Carlson’s Trophic State Index (CTSI) and Burn’s Trophic Level Index (BTLI), based on Chlorophyll a (Chl-a), Total Phosphorus (TP), Secchi Disc Depth (SD), and Total Nitrogen (TN). Water samples from five sites per lake were analyzed for physicochemical parameters from June’23 to May’24, revealing monthly and seasonal variations. The study revealed that Dhanmondi Lake's CTSI ranged from 69.3 to 79.5 (June'23 to March'24), indicating initial "Eutrophic" conditions progressing to "Hypereutrophic". Gulshan Lake consistently showed "Hypereutrophic" conditions, with CTSI values between 84.1 and 97.3. Banani Lake was "Eutrophic" in June & July'23, transitioning to "Hypereutrophic" from August’23 to May’24 (84.1-97.7). The Trophic Level Index (TLI) showed the "Hypereutrophic" status with a progressive monthly escalation for all the lakes. The Water Quality Index (WQI) categorized the lakes as "Poor" to "Very Poor" from June to August’23, becoming "Unsuitable" from September’23 to May’24, indicating significant anthropogenic stress. Principal Component Analysis (PCA) identified nutrient infiltration, soil erosion, waste discharge, and organic residue accumulation as key pollution drivers. The study advocates for a multi-sectoral strategy to regulate nutrient loading and mitigate eutrophication, emphasizing best management practices for urban lake conservation.
Urban lakes serve as vital ecological and recreational anchors within built environments, essential for enhancing urban resilience. Evaluating lake health predominantly focuses on water quality, assessing indicators such as nutrient levels, toxicity, pH balance, and water clarity to monitor changes. This study proposes a comprehensive evaluation framework that systematically describes specific spatiotemporal manifestations and periodic exogenous regulation characteristics across five dimensions: physical structure, water quality, shoreline dynamics, external regulation, and social service. Furthermore, it introduces an urban lake health assessment model based on synergistic development to evaluate the integrated development and interaction between water environments and social services. This model is applied across urban lakes in various developmental stages in China. Key findings include: 1) Urban development often impacts lake health disparately, with varying degrees of synergy observed between water environments and social services across different urban lakes. However, shifts in urban ideologies and improvements in governance, along with protective policies and project implementations, have contributed to improving water quality to some extent. 2) Engineering interventions do not consistently correspond with improvements in water quality, and governance measures sometimes yield mixed outcomes, underscoring the necessity for systematic solutions to lake health. Restoring hydrological processes emerges as crucial for enhancing sustainability.
Over the last several years, many more contaminants have had a substantial impact on the quality of the water. It directly affects both the environment and human health. The WQI serves as a gauge for effective water management. The fight against water pollution benefits from knowledge about water quality, including how to model it for predictions. Establishing a trustworthy prediction model for river water quality that can determine the index value based on river water quality requirements is the study's main goal. In order to determine which characteristics were important in determining the quality of river water, this study will examine and contrast the performance of many classification models and algorithms. Eleven sample sites have been selected for the data collecting process, which are dispersed among various locations along the river that flows through Kerala and Tamil Nadu. The dissolved oxygen content, temperature, pH, hardness, chloride, and other seven environmental parameters that impact the quality of water are used to calculate the water quality index. Water quality prediction model is developed using supervised machine learning methods, such as logistic regression and support vector repressor. To classify the water quality index, a classification model was created using SVM classifiers. The SVM classifier classifies the water quality index with an accuracy of 83%, whereas the logistic repressor predicts the water quality index well. The developed models performed well in terms of categorization and prediction of the water quality index.
Beira Lake, located in Colombo, Sri Lanka, has suffered severe anthropogenic impacts, with previous restoration attempts failing due to a limited understanding of pollutant dynamics. Aiming to fill this gap, a comprehensive study was conducted during dry and wet seasons to assess the spatiotemporal water pollution of Beira Lake, employing key physicochemical parameters, numerical indices, and remote sensing analysis. The water pollution index (WPI) results categorize Beira Lake as highly polluted, with WPI values ranging from 2.38 ± 0.92 in the wet season to 2.53 ± 1.32 in the dry season. Comparatively higher COD levels recorded in the Beira Lake network, especially for Gangarama Lake show significant pollution levels during both the dry and wet seasons, e.g., the highest COD levels, at 306.40 mg/L, were observed during the wet season. The Trophic State Index (TSI) results indicate eutrophic and hypereutrophic conditions in Beira Lake, which are particularly pronounced during the wet season. The heavy metal pollution index (HPI) results suggest elevated heavy metal concentrations in Beira Lake, especially in the wet season. Combined with field investigation results, a remote sensing data analysis between 2016 and 2023 reveals significant improvements in water transparency, suggesting positive effects of recent management interventions. Parameters demanding attention include COD, nitrate, and total phosphate levels due to their consistent exceedance of permissible limits. The PCA results of indices correlations between wet and dry seasons offer valuable insights into the complex dynamics of Beira Lake’s water quality. The study makes recommendations for restoring Beira Lake, including stringent pollution controls, regular dredging, green infrastructure implementation, implementing new rules and regulations, and community engagement.
The article considered the ecological index of water quality, which is used for planning water protection activities, developing water protection measures, carrying out ecological and ecological and economic zoning, ecological mapping; water pollution index, which is determined by hydrochemical indicators; modified Horton water quality index models; the Water Quality Index is proposed by the Canadian Council of Ministers of the Environment; the Said index, which is used to assess the quality of water for general use; water quality index in the river subbasin in a certain year; The Nemerov Pollution Index, which is used to comprehensively assess water, precipitation, or soil quality, and the Oregon Water Quality Index. Advantages and disadvantages of water quality and pollution indices are determined.
Rapid unplanned urbanization is always associated with environmental degradation which plays a direct role in the quality of life. Poor environmental quality is linked to premature death, cancer, long-term damage to respiratory and cardiovascular systems, etc. Using a case study of the Kolkata Metropolitan Area (KMA), the Urban Environmental Quality (UEQ) index has been constructed using a geoinformatics platform in the dimensions of the physical environment and built environment encompassing urban greenery, NO 2 , SO2, PM 2.5, PM 10, road induced pollution, land surface temperature, built-up area and noise followed by an exploration of its spatial pattern. KMA is the largest urban agglomeration in eastern India and the second-largest in India with a population of 13.2 million as per the 2001 census. Using the Urban Environmental Quality (UEQ) index, this study tried to find out the poor Environmental Quality area through multi-criteria analysis in KMA. Based on the relative importance of controlling the outdoor environment, criteria weights for nine parameters have been derived through the analytical hierarchy process (AHP). The UEQ index was prepared by combining parameters rating and corresponding weight. Polycentric growth of urban centers leads to appropriate spatial matches to low environmental quality. Although the UEQ in the peripheries is being affected by suburbanization in a few instances, the majority of the areas have better environmental quality.
Internet of things is enabling the world to become smarter and more amendable, and it connects the digital and physical worlds together. The Internet of things relies on resource-limited devices ranging from domestic appliances to personal devices. There is an ever-increasing number of device connected to the Internet every day that attract the attention of hackers. Adversaries deploy a range of advanced persistent threat (APT) strategies to successfully compromise these systems, one of which is the botnet attack. The IoT is potentially vulnerable to attacks launched by intelligent botnets, since these botnets detect network weaknesses and exploit them for the launch of different attacks similar to DDoS attacks. In order to provide efficient security against botnet attack to the IoT devices and network, several methods have emerged; recent and most effective mechanism is a deep learning mechanism. Our paper reviewed the security threats in IoT and several existing deep learning approaches to address the detection of botnets in the IoT environment. Furthermore, we also investigated the attack class, datasets, merits and demerits of existing deep learning approaches.KeywordsBotnetInternet of thingsSecurity threatsApplicationsDeep learning
Object detection has made immense improvements in natural images during the last decade but not so much in aerial images. Detection of miniature objects in aerial images remains challenging as they contain only a few pixels and extremely large input sizes. Moreover, tiny objects are easily fooled by the backstory and increase the difficulty of accurate detection. Many algorithms are used for object detection purposes, and YOLOR is one of them. YOLOR “You Only Learn One Representation” is a one-stage detector. It is specially made for object detection, whereas other algorithms include object classification or analysis. In CNN, only, one task is carried out at a time, whereas YOLOR is a unified model useful for multitasking purposes. In this paper, we discussed tiny object detection in aerial images using YOLOR. Based on our research, we found that the AI-TOD dataset contains object instances in eight categories, with 86% of the objects being smaller than 16 pixels in size. The AI-TOD can be used to assess the performance of a variety of small objects. The mean size of objects is approximately 12.8 pixels, which is considerably smaller than the other datasets.KeywordsDeep learningExplicit knowledgeImplicit knowledgeTiny object detectionNeural network
Exploratory data analysis enables researchers to understand the characteristics of the primary data concerning various statistical measures. This paper illustrates the exploratory data analysis performed on river water quality data. Water samples taken every day for five years from eleven sampling points positioned along the Bhavani River stretch exposed to man-made and seasonal factors have been considered for the study. The quality of river water has been separated between spatial pollution from anthropogenic causes and temporal pollution from seasonal variation. Examining the distribution, outliers, and anomalies of the data is critical to having a better grasp of the data and highlighting points from datasets that need to be investigated. Twenty-seven independent water quality parameters like nitrate, phosphate, fluoride, total coliform, alkalinity, turbidity, pH, temperature, etc., were used to find the water quality index and to build a prediction model. A river water quality dataset with 10,560 instances and 33 attributes collected from eleven stations on the Bhavani River was analysed. Box plots, heatmaps, pair plots, and histograms were used to conduct exploratory data analysis of experimental data in a way to differentiate between the sources of variation in water quality. The distributions of the attributes and their correlations were studied, which may suggest suitable solutions for data pre-processing requirements. The analytical results of the exploratory data analysis of river water quality data have been reported with visualizations.
The presence of several contaminants in waterbodies raises global pollution and creates major risks to mankind, wildlife, as well as other living organisms. Development of an effective, feasible, cost-effective and eco-friendly approach for treating wastewater that is discharged from various industries is important for bringing down the deposition of contaminants into environment. Advanced oxidation process is an efficient technique for treating wastewater owing to its advantages such as high oxidation efficacy and does not produce any secondary pollutants. Advanced oxidation process can be performed through various methods such as ozone, Fenton, electrochemical, photolysis, sonolysis, etc. These methods have been widely utilized for degradation of emerging pollutants that cannot be destroyed using conventional approaches. This review focuses on wastewater treatment using advanced oxidation process. A brief discussion on mechanism involved is provided. In addition, various types of advanced oxidation process and their mechanism are explained in detail. Challenges faced during wastewater treatment process using oxidation, electrochemical, Fenton, photocatalysis and sonolysis are discussed elaborately. Advanced oxidation process can be viewed as potential approach for treating wastewater with certain modifications and solving challenges.
Human settlements are guided by the proximity or availability of a natural resource such as river or lake basins containing set of streams. The harmonious development of human activity and natural conditions along watershed areas needs close attention and in-depth study. In this paper, the urban agglomerations and ecological spaces in the Yangtze River Delta, China, the Chao Lake Basin and its surrounding watershed ecosystem is taken as research subject for its serious environmental degradation problems during social and economic development. This paper adopted an effective machine learning algorithm (kernel-ELM) to extract land use and land /cover information, and to analyze the land use/cover pattern evolution rules of the Chao Lake Basin with long term Landsat imagery. Subsequent studies were then carried out to demonstrate the flood-affected area and its ecological impact in the basin in 2020, to reveal the occupation on land cover types. The results indicate Conclusions are drawn from the experiment results: (1) There has been significant change in cultivated land, forest land and construction land out of six key land cover types with dynamic degree of −10.17%, 4.61, 67.04% respectively. (2) Algae bloom pollution was extracted from pattern classification results and it was up to 15% of the total water area by the year 2018. (3) The occupation on land use/cover types of the flood was revealed. The results prove effective application of remote sensing technology in environmental analysis and planning for data-driven evaluation of governing policy. This work serves as a scientific basis for environmental management and regional planning in the Chao Lake Basin and can be served as a basis and a reference for evaluating an ecological policy and its impact for other economic developing watershed human settlements with ecological issues.
The study assesses the characteristics of two lakes located in close vicinity to each other in identifying the status of the lakes based on Designated Best Use (DBU) criteria for optimum utilization and use. Further, the study reports the characteristic assessment of the lakes for two seasons with sampling carried out in August and October months of 2019 and samples collected at different depths and locations to present the comprehensive existing water quality conditions of the lake. The study utilized about twenty parameters evaluated experimentally for determination of Water Quality Indices. In this context, different water quality indices including National Sanitation Foundation Method (NSFWQI) and BIS 10500 (BISWQI) were utilized in determining the indices. The WQI were determined depth wise and a weighted average method was utilized in presenting the overall WQI of the lakes which represents the true water quality based on depth wise evaluation. Hence, the study represents both spatial and temporal variations in the lake water quality. The overall classification of water quality for both the lakes using the NSFWQI methodology was good for both the sampling periods. Similarly, the overall water quality was categorized to be excellent for both the sampling periods using the BISWQI. Further, a new approach in determining water quality indexing is presented through introduction of a Modified Water Quality Index (MWQI) which utilizes the maximum number of parameters and thereby provides a means to reduce ambiguity and eclipsing problems of WQI. Using this newly developed MWQI, the water quality was categorized to be excellent and good for samples collected in August and October respectively for both the lakes. However, conservative estimation considering spillover effects may lead to classification of good category using MWQI. The Heavy Metal Pollution Index (HMI) were classified to be good for both the lakes and sampling periods. Spectral characterization of water samples revealed the presence of oxygen (O), tantalum (Ta), sodium (Na) and Zinc (Zn). However, further monitoring studies are being carried out to cover a period of 1 year to observe if there is a change in water quality due or any seasonal variations.
Water bodies are a vital and prolific resource to our environment. They provide a variety of amenities and services to communities across the world such as drinking water, food, travel, recreation, wildlife, aesthetic appeal, economic development, etc. This case study deals with the importance of the Gulshan lake, areas of problem in the lake water resulting in pollution and shrinkage of lake-water in the rapidly urbanizing city of Dhaka, and how the impact of this problems can be minimized by initiating some controlling measures. Bulk of the problems has been identified throughout the study are owing to accelerated demographic pressure, urbanization, land encroachment and land fill, disposition of increased volume of domestic and industrial waste. The lakes having suffered accelerated eutrophication, ecosystem of the lake is tremendously stressed and now it is gradually turning in to a hazardous sewer-the contaminated waters of which are still being consumed. To amend this critical situation, some approaches have been mentioned in the study. Water exchange method, water hyacinth based hydroponics method and proper implementation of DPSIR (drivers, pressure, state, impacts and responses) monitoring model are those pillar which may prove advantageous in the longer run.
The proportion of freshwater on earth’s surface is only 2.5% of which only 1% is accessible for use. In this context, lakes are one of the most important water resources and have been used as a source of water supply for human consumption and in general accounts for about 0.3% of the total surface water body sources. As such, the conditions of lakes have been in constant deterioration due to increased anthropogenic activities surrounding them. In principle, the quality of lake water (or other surface sources) is evaluated using various physico-chemical and biological parameters selected on the Designated Best Use (DBU) of the water body (lake) for various purposes. Consequently, the use of Water Quality Index (WQI) is an important tool used for designating the quality of lake water. In general, natural lakes are confined bodies of water lacking a strong flow for self-cleansing of its water and therefore leading to accumulation of various impurities. In such cases, the quality of these impurities are determined using different indices like Heavy Metal Index (for heavy metals), eutrophication potential (due to nutrients) and other associated indices system. The determination of existing properties helps in determination of future trends of such pollutants and thereby the quality of the lake water in future scenario. Different modelling techniques are used for prediction of futuristic changes in lake water quality including watershed models, ground water models and lake models. The present study gives an overview and critically evaluates the literature on all aspects of water quality to give an insight of the various tools and techniques used for complete water quality monitoring and management.
Based on the analysis of multi-year monitoring data on atmospheric air contamination in the vicinity of Lake Karachay, Reservoir V-9, a model is suggested here for carry-over of radionuclides (trace elements) in the form of water aerosols from the reservoir surface area. The concept of fractionation (accumulation) coefficients is introduced for different radionuclides present in V-9 Reservoir water aerosols as compared to the reference radionuclide ¹³⁷Cs. The range of possible fractionation coefficient values is estimated for ¹³⁴Cs, ⁹⁰Sr, 103,106Ru, ⁹⁵Zr+ ⁹⁵Nb, ¹²⁵Sb, ¹⁴⁴Ce and Pu radionuclides. It is shown that, for a numerical assessment of radioactive pollution of the atmosphere with water aerosols, it is convenient to express the capacity of the source of releases as a product of three factors: (1) the activity concentration in the reservoir water, (2) the effective rate of generation of water aerosol volume from the reservoir surface area (~ 20 cm³ m⁻² year⁻¹ in relation to the reference radionuclide ¹³⁷Cs), and (3) the fractionation coefficient of the radionuclide under consideration in water aerosols as compared to the reference nuclide. It is proposed here to model transfer and dispersion of water aerosols in the atmosphere using the standard Gaussian model, and it is shown that this allows estimation of atmospheric pollution in the vicinity of the reservoir with acceptable accuracy.
Gulshan Lake is an urban waterbody in the most exclusive area of Dhaka city, which is confronting a heavy load of pollution by anthropogenic activities. Prior studies were reviewed to analyze the trends of pollution. Rise of ammonia (eutrophication), lack of dissolved oxygen, and toxic heavy metals (as Pb, Cr, Cd, etc.) increase are the leading factors to drive the lake towards an environmental catastrophe. The presence of various pathogenic organisms is also increasing the health risk among the neighboring population. Beneficent minerals are at the lowest level to comply drinking water requirement. Recent results measuring pollution are dire compared to 20 years before. There are many worst-case examples worldwide, which may be the fate of the lake. If urgent steps are not taken to restore the environment, the possibility of transformation into an ecological dead zone is a reality.
In this article, two statistical methods of diffusion of particles are proposed for modeling the transport of pollutants in Lake Valencia (Venezuela). Both methods use as velocity field on the lake surface solutions of the Saint-Venant equations. The two procedures are compared through Monte Carlo simulation. Furthermore, as a novelty an algorithm to randomly generate the initial positions of the particles using information obtained from a satellite image is designed. Résumé : Dans cet article deux méthodes de diffusion de particules sont proposés pour modéliser le transport de polluants à la surface du Lac de Valencia (Venezuela). Les deux méthodes utilisent comme champ de vitesses sur la surface du lac les solutions de l'équation de Saint-Venant. Ces deux procédures sont comparées à l'aide d'une simulation de Monte Carlo. De plus, et comme une nouveauté, un algorithme qui utilise l'information obtenue d'une image satellite est construit pour générer les positions initiales des particules.
Dhaka, the capital of Bangladesh, is the eleventh largest megacity city in the world, with a population of 18.2 million people living in an area of 1528 km2. This city profile traces the trajectories of its urban development to becoming a megacity and characterizes its emerging challenges due to informal urbanization and climate change impacts. Due to rapid population growth and uncontrolled urbanization, Dhaka currently faces various socio-economic and environmental challenges in aspects such as providing basic urban services; reliable transportation framework; constant water and energy supply; effective sanitation; sustainable waste management and affordable housing. Moreover, the urban setting has further deteriorated as Dhaka is already facing various adverse impacts of climate change. Studies predict that most of the urban sectors, public health and surrounding agriculture and fisheries in Dhaka will be severely impacted by climate change. Dhaka is trying to transform its existing “incremental development” model to an “integrated development” framework in order to effectively mitigate its extreme urban challenges. The future of Dhaka city significantly relies on the successful execution of integrated infrastructure and service planning, development, and management practices, operating under an accountable and good governance system.
Gulshan-Banani-HatirJheel Lake area is the busiest region within the capital city of Bangladesh and is under the Dhaka North City Corporation. Hatirjheel lake area has been transformed into transportation hub to minimize traffic congestion. The area was constructed under Bangladesh Army and Śpecial Works Organization’ (SWO). Recently, the Government of the Peoples Republic of Bangladesh has taken up a project for the development of Gulshan-Banani Lake, as it will be linked with Hatirjheel project widening facilities for the city dwellers. These lake areas remain almost unused throughout the year. There are housings on the both sides of these lakes and a slum near the Banani Lake. At present road transport is the only mode of transport for accessing with other parts of the Dhaka city and travellers face severe traffic jam during working hours. A study has been carried out by one of the present author about the possibility to build a waterways network for passengers transport through these lakes. Present study aims at the development of a suitable design of boat for the Gulshan-Banani-HatirJheel Lake.
Onondaga Lake is a 12-square-kilometer urban lake located in Syracuse, New York, USA. The legacy of industrialization and municipal development since the late nineteenth century resulted in impaired water quality and contamination of lake sediments. A comprehensive lake restoration plan was developed following two decades of intensive multidisciplinary technical studies. The restoration plan includes removal of approximately 1.5 million cubic meters of lake sediments (completed November 2014, one year ahead of schedule); transport of the dredge slurry through a 6.5-kilometer-long, double-walled pipeline; and dewatering in geotextile tubes strategically placed in a dedicated 20‑hectare upland confined facility. More than 160 hectares of the lake received an engineered cap to isolate the remaining contamination after dredging and provide a habitat restoration surface. The deepest portion of the lake will be monitored for ongoing natural recovery. The restoration and design process involved close coordination and discussions with multiple regulatory agencies and stakeholders and was supported by several technical studies, including: 1) development of sediment and fish tissue remedial goals; 2) detailed evaluations of capping, dredging and upland containment, natural recovery, and nitrate addition to the lower part of the lake water column (to limit production of methyl mercury); and 3) integration of habitat restoration into the lake-wide cleanup effort. As one of the largest sediment capping projects constructed to date, the multi‑function cap design incorporated several innovative components, including site-specific biodegradation and reactive media (activated carbon [AC] for contaminant sequestration and siderite amendment for pH control) to ensure remedial performance requirements for long‑term chemical isolation and habitat restoration were met. The innovative capping concepts were developed through multiple years of field investigations, laboratory and bench-scale studies, and field pilot testing. In addition, state-of-the-science contaminant migration and cap effectiveness modeling studies were conducted to evaluate the required layering of the cap and to optimize the amendment media and required dosage for the various layers. Successful integration and regulatory acceptance of these unique design features provided opportunities for significant optimization of raw material needs (cap thickness and amendment dose). The innovative study methods also resulted in streamlined and efficient construction, while retaining environmental effectiveness. Construction began with a field pilot project in 2011, followed by full-scale field implementation in 2012; sediment removal was completed in 2014 and lake capping was completed in 2016. Details of the study methodology, analysis of amendment and cap effectiveness (laboratory testing and modeling), and construction verification methods and monitoring results are presented in this paper.
Burullus Lake is the second largest lake along the Mediterranean Sea and represents one of the most subjected lakes to pollution at the delta’s coastline. The present study explores the use of Landsat data and GIS for assessing water pollution at Burullus Lake, Egypt. Multi-spectral Landsat-8 OLI image dated 2015 provided the necessary information to this study. Radiometric and atmospheric corrections were applied to the image. Land use/cover map was obtained to identify natural resources and types of human activities in the area surrounding the Lake. Three previously developed water quality empirical models for BOD, total nitrogen (TN) and total phosphorus (TP) were applied on the calibrated image. Then, a GIS model was generated to identify areas recording high levels of BOD, TN and TP. Results confirmed that the Lake water is subjected to pollution from multiple sources; particularly domestic and agricultural drains. Shallow water (i.e. Lake Shores), where human activities are influencing, reported high levels of water studied pollutants. The model indicated that south western and north eastern parts of the Lake are the most polluted parts, recording relatively high levels of BOD, TN and TP; >4.46mgL⁻¹, >18.33mgL⁻¹ and >15.59mgL⁻¹, respectively. Results were ascertained based on water quality investigations in relevant research studies on the Lake. It was concluded that Burullus Lake is extensively subjected to interrupting human activities which have a great negative impact on water quality. Also data-observation techniques and water quality empirical models were successful in assessing and mapping water pollution.
The precursors of deterioration of immaculate Kashmir Himalaya water bodies are apparent. This study statistically analyzes the deteriorating water quality of the Sukhnag stream, one of the major inflow stream of Lake Wular. Statistical techniques, such as principal component analysis (PCA), regression analysis, and cluster analysis, were applied to 26 water quality parameters. PCA identified a reduced number of mean 2 varifactors, indicating that 96% of temporal and spatial changes affect the water quality in this stream. First factor from factor analysis explained 66% of the total variance between velocity, total-P, NO3–N, Ca2+, Na+, TS, TSS, and TDS. Bray-Curtis cluster analysis showed a similarity of 96% between sites IV and V and 94% between sites II and III. The dendrogram of seasonal similarity showed a maximum similarity of 97% between spring and autumn and 82% between winter and summer clusters. For nitrate, nitrite, and chloride, the trend in accumulation factor (AF) showed that the downstream concentrations were about 2.0, 2.0, and 2.9, times respectively, greater than upstream concentrations.
Ever increasing population, urbanization and modernization are posing problems of sewage disposal and contamination of surface waters like lakes. Natural water gets contaminated due to weathering of rocks, leaching of soils and mining processing, etc. Various types of problems in lake which cause nutrient enrichment in lake have been reviewed. Land use change and longer growing seasons could increase the use of fertilizers with subsequent leaching to watercourses, rivers and lakes, increasing the risk of eutrophication and loss of biodiversity. Water quality can be assessed by various parameters such as BOD, temperature, electrical conductivity, nitrate, phosphorus, potassium, dissolved oxygen, etc. Heavy metals such as Pb, Cr, Fe, Hg, etc. are of special concern because they produce water or chronic poisoning in aquatic animals. Harmful algal blooms are becoming increasingly common in freshwater ecosystems globally. Pollution by plastic debris is an increasing environmental concern in water bodies, where it affects open-water, shoreline and benthic environments. Surface water densities of plastics are as high as those reported for areas of litter accumulation within oceanic gyres. Different methods have been used to analyse the water quality of lake such as Hyperion, water quality index and hazard quotient. It is recommended that pollution prevention and water re-use should be adopted in combination with the recycling of nutrients in controlled urban agriculture.
Gulshan-Baridhara lake located in and around Gulshan, Banani and Baridhara, has always been Dhaka’s most exclusive residential area mainly because of the pristine lake. The lake is elongated in a north south direction and surrounded mainly by residential areas and some industrial units as well. To evaluate the pollution level of the sediment of the lake, samples were collected from 4 selected locations in 4 different seasons. Four different media were used to study the aerobic heterotrophic, enteric and related bacterial count. Aerobic heterotrophic bacterial count was in the range of 1.1 × 10 4 to 1.2 ×10 6 cfu/g in sediment sample, while enteric and related bacterial count in 3 different media (SS agar, MacConkey agar and Cetrimide agar) were 1×10 0 to 1.5×10 4 cfu/g, 1×10 0 to 6×10 4 , and 1×10 0 to 1.1×10 3 cfu/g in sediment, respectively. Out of 23 bacterial isolates 18 were Gram-positive and 5 were Gram-negative. Among the Gram-positive, all were rod shaped spore former and under the genus Bacillus. Out of 5 Gram-negative isolates 2 were the member of Pseudomonas , remaining 3 strains were Escherichia , Aeromonas and Enterobacter . Total nitrogen and phosphorus level along with the presence of different bacterial strains clearly indicated that Gulshan lake sediment was polluted with the chemical and bacterial pollutants. DOI: http://dx.doi.org/10.3329/jasbs.v38i2.15596 J. Asiat. Soc. Bangladesh, Sci. 38(2): 155-161, December 2012
Bacterial isolates, Bacillus firmus (LS-31) were collected from eutrophic Gulshan lake, Dhaka sediments and introduced to stimulate inorganic nutrient regeneration in the laboratory. The bacteria stimulated net regeneration of dissolved inorganic nitrogen and inorganic phosphorus in the water by about two folds at both the incubation temperatures (26°C and 30°C). These results suggest that the application of B. firmus would be promising for the stimulation of inorganic nutrient regeneration at the eutrophic environment.Bangladesh J. Zool. 41(1): 73-78, 2013
Background and Objectives: Aydughmush dam was built on Aydughmush River at !"km in
southwest of Mianeh City. The dam is multipurpose and its main aims are the spring floods control,
supplying potable water for villages and providing irrigation water. Different pollutants which
probably discharge to the river finally enter to the dam reservoir so; this study focuses on evaluating
the quality of the dam reservoir.
Materials and Methods: In this cross sectional study standard field parameters including dissolved
oxygen, temperature, Biochemical and chemical oxygen Demand, Most Probable Number of
Coliforms, Fecal Coliform, Turbidity, Total Dissolved Solids, Total Solids, pH, conductivity and
others were measured at eight different stations during the spring and summer in 2010. Sampling
points were selected on the basis of their importance. Water quality index was calculated using water
quality index calculator given by National Sanitation Foundation (NSF) information system.
Results: The highest value of WQI of the samples was 84.89 in A3 station in July while the lowest
value was 67.96 in A2 station in May. The lower value of WQI has been found mainly due to the
slightly lower value of DO in the dam reservoir water. Most of the water samples were found within
Good category of National Sanitation Foundation Water Quality Index (NSF-WQI). Comparison
of the measured parameters based on the sampling stations and various months by variance and
t-student analysis showed a significant relationship for some parameters(P<0.05). Nutrient budget
determination indicates that the concentration of phosphate, nitrite, nitrate and ammonia at inlet are
higher than outlet of the dam reservoir.
Conclusion: The calculated (WQI) showed good water quality. Based on the results of NSFQWI
calculations, the dam reservoir water quality is suitable for various purposes
Key words: Water Quality Index, NSFWQI, Dam Reservoir, Water Quality
Ciambulawung River is located in Lebakpicung Kampong close to Halimun Salak National Park. Ciambulawung River is used for micro-hydro power plant (capacity 10.000 Watt). The purpose of this study was to determine the water quality status of Ciambulawung River. The pollution index ranged 0.56 – 0.78 and NSF-WQI ranged 87 – 88. Hence the river water quality is considered good. Based on these indices it is concluded that communities living along river bank and micro-hydro power plant did not negatively affect the water quality of Ciambulawung River.
The precursors of deterioration of immaculate Kashmir Himalaya water bodies are apparent. This study statistically analyzes the deteriorating water quality of the Sukhnag stream, one of the major inflow stream of Lake Wular. Statistical techniques, such as principal component analysis (PCA), regression analysis, and cluster analysis, were applied to 26 water quality parameters. PCA identified a reduced number of mean 2 varifactors, indicating that 96% of temporal and spatial changes affect the water quality in this stream. First factor from factor analysis explained 66% of the total variance between velocity, total-P, NO3–N, Ca2+,Na+,
TS, TSS, and TDS. Bray-Curtis cluster analysis showed a similarity of 96% between sites IV and V and 94%between sites II and III. The dendrogram of seasonal similarity showed a maximum similarity of 97% between spring and autumn and 82% between winter and summer clusters. For nitrate, nitrite, and chloride, the trend in accumulation factor (AF) showed that the downstream concentrations were about 2.0, 2.0, and 2.9, times respectively, greater than upstream concentrations.
The Zarivar Lake a freshwater lake in west of Kurdistan Province is home for large number of native plant and animal species therefore water quality and health of the lake are vital for conservation of these species. The present study aimed at evaluation of the Zarivar Lake using NSF-WQI as an indicator of water quality. WQI is a suitable tool to examine and classify spatial and temporal variations in water quality and pollution loads in a water body. Seven sites were selected in different parts of the lake for sampling. Water samples were taken and placed in dark bottle, kept in ice box to prevent any change in chemical properties of samples prior to transportation to the lab for further analyses. Nitrite, Nitrate, Orthophosphate, NH 4 + , NH 3 , Iron, salinity, Electron Conductivity (EC) and pH were measured in all sites. Electron Conductivity was 295-426 µS.cm -1 and pH varied between 7.28-8.35. Concentrations of examined chemicals were PO 4 3-: 0.019-1.45 mg l -1 ، NO3-:0.6 mg l -1 ، NO2: 0.001-0.011 mg l -1 ، NH 4 + :< 0.11-11.33 mg l -1 which indicated trophic status of the lake. Water quality assessment was carried out based on values obtained for nine factors including dissolved oxygen (DO), Fecal Coliform, BOD, pH, water temperature (o C), Phosphate, Nitrate, Total Suspended Solid (TSS) and turbidity. The highest value was recorded for Nitrate and lowest for fecal coliform. The study showed based on WQI indicator the Zarivar Lake is a low or slightly polluted basin with an average water quality.
Water samples were collected from four selected sites of the Gulshan lake during four different seasons. Four different media were used to study the aerobic heterotrophic, enteric and related bacterial abundance. Aerobic heterotrophic bacterial abundance ranged between 1×10 6 and 9×10 6 cfu/100 ml, while enteric and related bacterial abundance in SS agar, MacConkey agar and Cetrimide agar media ranged between 1×10 3 and 3×10 5 cfu/100 ml, between 1×10 4 and 1×10 7 , and between 1×10 0 and 1.4×10 3 cfu/100 ml, respectively. Among 40 bacterial isolates 14 were selected out of which seven were Gram-positive and seven were Gram-negative. Among Gram-positive isolates, six were rod-shaped spore former belonging to Bacillus and Lactobacillus, while another one was coccoid in shape and under the genus Planococcus. Out of seven Gram-negative isolates, two were the members of Pseudomonas, remaining five were Morganella, Neisseria, Escherichia, Aeromonas and Enterobacter. Inorganic nutrients like NH4 +-N, NO3-N, NO2-N and PO4-values were found to be satisfactory from pollution point of view. The presence of different bacterial isolates indicate that the Gulshan lake water was polluted with chemical and bacterial pollutants.
Gulshan Lake is the recreationally most important semi-natural freshwater lake of Dhaka City. Although it was built solely for residential purpose, over the years many commercial buildings and industries have been set up here. Water quality as well as the eminent scenic view of Gulshan Lake is deteriorating day by day due to land encroachment and various types of untreated household and industrial wastes discharged directly into it. In the present study an environmental quality assessment of the Gulshan Lake was done. Water and sediment samples were analyzed by reactor based Neutron Activation Analysis (NAA) method. Standardization was achieved through relative method using the certified reference material (CRM) IAEA-Soil-7. Quality control (QC) test was performed to investigate the reliability of the analysis by measuring chromium and other major and trace element contents in CRMs viz. IAEA-1633b (coal fly ash) and IAEA-SL-1 relative to IAEA- Standard reference material (SRM) Soil-7. Concentrations of elements such as Cr, As, Co, Eu, Fe, Hf, K, La, Na, Sb, Sc, Sm, Th, U, and Zn were determined. The studied physico-chemical parameters were pH, DO, BOD, turbidity, EC, salinity, temperature, TSS, and TDS. Turbidity, EC, BOD and salinity values were found higher than the DoE standard. On the other hand DO value (0.91 to 2.31 ppm) was found lower than the standard value (4 ppm) in surface water for aquatic life. Probably this is the main reason of fish mortality in the Gulshan Lake.
In an effort to develop a watershed-wide water quality management plan for the Buffalo River, NY, the Erie County Department of Environment and Planning has begun a pilot watershed management project for Cazenovia Creek, one of three major tributaries. In support of the management project a water sampling effort covering four events and two non-events for 25 different analytes at 12 sites was conducted between 4/24/96 and 7/10/96. The National Sanitation Foundation (NSF) Water Quality Index (wQI) was one of the analytical tools used to summarize the data. Essentially, the WQI converts the concentration data for nine analytes into one offive water quality classes, ranging from ·very bad" to· excellent". Based on the WQI values, water quality typically was in thegood" range. The sites nearest the headwaters had the highest water quality rating with significant decreases in water quality occurring downstream, particulary in urban-impacted areas. Water quality also was significantly impacted by stonn events. High fecal colifonn levels (>200 microorganisms/100 ml) are ofparticular concem at the majority of sites.
The present work aims at assessing the water quality index (WQI) in the surface water of Sankey tank and Mallathahalli lake situated in Bangalore Urban district by monitoring three sampling locations within Sankey tank (viz., A, B and C) and Mallathahalli lake (viz., Inlet, Centre and outlet) for a period of 3 months from March to May 2012. The surface water samples were subjected to com-prehensive physico-chemical analysis involving major cations (Ca 2? , Mg 2? , Na ? , K ? , Fe 2?), anions (HCO 3 -, Cl -, SO 4 2-, NO 3 -, F -, PO 4 3-) besides general parameters (pH, EC, TDS, alkalinity, total hardness, DO, BOD, COD, CO 2 , SiO 2 , colour, turbidity). For calculating the WQI, 14 parameters namely, pH, electrical conductivity, total dis-solved solids, total hardness, alkalinity, calcium, magne-sium, sodium, potassium, chloride, sulphate, nitrate, fluorides and iron were considered. SAR values indicated that both Sankey tank and Mallathahalli lake waters are excellent (S1) for irrigation, while electrical conductivity values classified these lake water, respectively under medium salinity (C2) and high (C3) salinity category. Correlation between SAR and electrical conductivity revealed that Sankey tank water is C2S1 (medium salinity-low sodium) type while Mallathahalli lake water is C3S1 (high salinity-low sodium) type. Sankey tank and Malla-thahalli lake water were, respectively hard and very hard in nature. Further, it is apparent from WQI values that Sankey tank water belongs to good water class with WQI values ranging from 50.34 to 63.38. The Mallathahalli lake water with WQI value ranging from 111.69 to 137.09, fall under poor water category.
22 Physico-chemical variables have been analyzed in water samples collected every three months for two and a half years from three sampling stations located along a section of 25 km of a river affected by man-made and seasonal influences. Exploratory analysis of experimental data have been carried out by box plots, ANOVA, display methods (principal component analysis) and unsupervised pattern recognition (cluster analysis) in an attempt to discriminate sources of variation of water quality. PCA has allowed the identification of a reduced number of “latent” factors with a hydrochemical meaning: mineral contents, man-made pollution and water temperature. Spatial (pollution from anthropogenic origin) and temporal (seasonal and climatic) sources of variation affecting quality and hydrochemistry of river water have been differentiated and assigned to polluting sources. An ANOVA of the rotated principal components has demonstrated that (i) mineral contents are seasonal and climate dependent, thus pointing to a natural origin for this polluting form and (ii) pollution by organic matter and nutrients originates from anthropogenic sources, mainly as municipal wastewater. The application of PCA and cluster analysis has achieved a meaningful classification of river water samples based on seasonal and spatial criteria.
A set of quantitative analytical data from the alluvial aquifer of the Pisuerga river, located at the north-east of Valladolid (Spain), has been processed by multivariate statistical techniques in order to investigate the evolution of the groundwater composition between two surveys. The original matrix consisted of 16 physico-chemical variables, determined in 32 groundwater samples collected in 32 sampling sites of the aquifer. The surveys were carried out in October 1994, at the end of the irrigation and low water period just before autumn rains, and in April–May 1995 at the beginning of the irrigation and high water period and after the recharge of aquifer. The experimental 64×16 matrix was analysed by Principal Component Analysis (PCA), and the resulting Principal Components (PCs) and Varimax rotated PCs (VFs) analysed by means of box and bivariate plots. The exploration of the correlation matrix allowed to uncover strong associations between some variables (sulphate, chloride, hydrogencarbonate, sodium, potassium, magnesium, calcium and electrical conductivity) as well as a lack of association between the others (pH, nitrate, and trace metals). PCA showed the existence of up to five significant PCs which account for 71.39% of the variance. Two of them can be initially assigned to ‘mineralization’ whereas the other PCs are built from variables indicative of pollution. Box and bivariate plots of the two first PCs showed that ‘mineralization’ is maintained through surveys and that trace elements increase from the first to the second survey in all zones, as a possible consequence of soil leaching caused by the rise of the groundwater level. Varimax rotation allowed to ‘break up’ the ‘mineralization’ PC into two VFs, assigned respectively to ‘natural’ mineralization and to ‘saline’ man-made contamination (sodium and chloride). Box and bivariate plots of VFs confirmed the existence of a differential ‘natural’ mineralization pattern, now ascribed exclusively to dissolution of geological materials, as well as the presence of a zone with unusually high levels of ‘saline’ contamination attributed to leakages from sanitary systems. The plot of VFs also allowed to visualise seasonal variations, identifying a process of dilution of the ‘natural’ mineralization during the recharge of the aquifer, and an increase of the ‘saline’ contamination, assigned to a variety of non-natural causes.
Water quality index (WQI) has been calculated for different
groundwater sources i.e. dug wells, bore wells and tube wells at Khaperkheda
region, Maharashtra (India). Twenty two different sites were selected in post
monsoon, winter and summer season. And water quality index was calculated
using water quality index calculator given by National Sanitation Foundation
(NSF) information system. The calculated WQI showed fair water quality rating
in post monsoon season which then changed to medium in summer and winter
seasons for dug wells, but the bore wells and hand pumps showed medium
water quality rating in all seasons where the quality was slightly differs in
summer and winter season than post monsoon season, so the reasons to import
water quality change and measures to be taken up in terms of groundwater
quality management are required.
The application of different multivariate statistical approaches for the interpretation of a complex data matrix obtained during the period 2004-2005 from Uluabat Lake surface water is presented in this study. The dataset consists of the analytical results of a 1 year-survey conducted in 12 sampling stations in the Lake. Twelve parameters (T, pH, DO, PO(-3)(4), NH(4)-N, NO(2)-N, NO(3)-N, SO(3-)(4), BOD, COD, TC, FC) were monitored in the sampling sites on a monthly basis (except December 2004, January and February 2005, a total of 1,296 observations). The dataset was treated using cluster analysis, principle component analysis and factor analysis on principle components. Cluster analysis revealed two different groups of similarities between the sampling sites, reflecting different physicochemical properties and pollution levels in the studied water system. Three latent factors were identified as responsible for the data structure, explaining 77.35% of total variance in the dataset. The first factor called the microbiological factor explained 32.34% of the total variance. The second factor named the organic-nutrient factors explained 25.46% and the third factor called physicochemical factors explained 19.54% of the variances, respectively.
Water quality index (WQI) is one of the most important and valuable tool used for assessing the overall water quality as it presents the final form in a single value. The concept and development of the WQI was initially developed by Horton in 1965. Since then many other transformations have occurred in the determination of WQI as proposed by different scientists and researchers. The index tends to facilitate the effective management of numerous water sources for both surface and groundwater and specifies their suitability for various uses. In general, continuous monitoring and assessments of different water quality parameters are highly complex in nature leading to generation of large voluminous datasets which are often difficult to interpret and is often uneconomical. In this context, the WQI incorporates the complex nature of different water quality parameters and helps to form a connection among these, culminating in a single value categorizing the water and this information is presented to different governmental, public agencies and regulatory authorities. The review paper presents detailed and operational descriptions along with mathematical calculations providing an insight about the development and the utility of WQIs. It has been observed that though there are many index methods available but no one single method is recognized globally to fulfill the objective of water quality management. The review also presents WQIs in an easy and streamlined manner which may be further used to have a reliable data for attaining quality of water.
Water is a prime natural resource, which is a basic need for entire living system on this planet and a precious natural asset. Planning management and development of this natural resource needs to be governed by national perspective. As Bangalore does not have perineal river to supply sufficient water for entire city. The major water supply to the city are river Cauvery, ground water which is being rejuvenated by the lakes. Our present study is a review on heavily polluted BELLANDHUR LAKE which is estimated about 130 years old. The total catchment area of this lake is about 178.54sq this lake remains full throughout the year because of the sewage water about 1000MLD from Bangalore city which is being deployed into the lake without being treated efficiently and rain water which is been carried by its catchment area is getting polluted with various wastes.
Study shows the verity of waste which is being discarded by the industries and domestic effluents into the lakes directly and indirectly and how these wastes makes the lake unfit for usage of this water and create problem to public.
This study also reviews the estimations of hazardous wastes, with the help of references evaluating how the waste has turned itself into a toxic substance which is disturbing the ecosystem and how the toxic substance has caused physicals and chemical changes in the lake.
The study also provides an in site for rejuvenation and bring back life in to the lakes and make it fit for domestic use by creating artificial floating islands to help reduce the harmful components from the lake and to recommend de-silting and de-weeding the water bodies.
The present study quantifies the pollution potential of the leachate and its effects on surrounding groundwater in the vicinity of four nonengineered dump sites in the study regions of Solan, Mandi, Sundernagar, and Baddi in Himachal Pradesh in India. The analysis primarily focused on the determination of leachate characteristics for determination of the leachate pollution index (LPI), groundwater characterization at different downstream distances using the water quality index (WQI), and heavy metal pollution index (HPI) to study the effects of leachate pollution on groundwater. Characterization of leachate samples revealed that most of the physicochemical parameters and heavy metals were in excess of the permissible limits for the study regions of Himachal Pradesh. The water quality improved with an increase in downstream distance from the dumpsite per the indexing method. Principal component analysis (PCA) was carried out to determine the components arising from natural and anthropogenic components while hierarchical cluster analysis (HCA) was used to determine and identify the regions of low, moderate, and high pollution zones in the groundwater.
This paper presents the results of -Cs-137 and Pb-210 dating of sediments from the northern and western basins of Lago Maggiore and the southern basin of Lago di Lugano. Vertical distributions of Cs-137 in sediment cores taken in 2017/18 were compared to those of the sediment cores taken almost two decades ago at the same positions. This comparison showed that Cs-137 peaks do not alter their shape significantly over time and Cs-137 remains a reliable time-marker for many decades. Pb-210 dating using for the first time the piecewise "constant rate supply" (CRS PW) model constrained with Cs-137 time-markers is performed for sediment cores of Lago Maggiore and Lago di Lugano. "Event-linked" mass accumulation rates (MARs) were derived from the CRS PW model. In combination with the dry bulk density, organic matter content, K-40 and Pb-210 activity concentrations, these "event-linked" MARs were used for the identification of one or more event layers (turbidites, detrital layers) in 1-cm thick sediment samples. "Continuous" mean MARs which are independent of the event layers were estimated: in Lago Maggiore sediment cores they are 0.066-0.090 g/cm2/yr; in Lago di Lugano they vary in the range of 0.032-0.057 g/cm2/yr with higher values in the time interval 1963-1986 as compared to 1986-present.
Bacillus cereus LW-17 enhanced net regeneration of dissolved inorganic nitrogen and phosphorus in the Gulshan lake water by about two-folds at temperatures of 26°C and 30ºC, respectively. Application of Bacillus cereus LW-17 would be promising for improvement of polluted environment.DOI: http://dx.doi.org/10.3329/bjb.v42i2.18043 Bangladesh J. Bot. 42(2): 349-353, 2013 (December)
This book reports on the latest advances in concepts and further developments of principal component analysis (PCA), addressing a number of open problems related to dimensional reduction techniques and their extensions in detail. Bringing together research results previously scattered throughout many scientific journals papers worldwide, the book presents them in a methodologically unified form. Offering vital insights into the subject matter in self-contained chapters that balance the theory and concrete applications, and especially focusing on open problems, it is essential reading for all researchers and practitioners with an interest in PCA.
Houjing River, located in Kaohsiung City, is one of the most seriously contaminated rivers in Taiwan. This study analyzed the concentrations of heavy metals (As, Cd, Cr, Cu, Pb, Ni, Zn and Hg) in sediments and water samples collected from this river. Analysis of contamination factor ( ) and potential ecological risk factor ( ) of heavy metals in water showed that there were low grades of contamination and potential ecological risk for all heavy metals, suggesting that heavy metals in water were less likely to pose risks to the ecosystem. However, sentiment samples were found to have severe contamination levels based on ranges found in sediment quality guidelines (SQG). The average Cu concentration was almost twice as high as the upper standard values in all the guidelines. Multi-element indices were used to evaluate the synergistic effects of different metals at the sampling sites. The calculated results of different indices, the modified degree of contamination (mCd), Nemerow pollution index (PN) and potential ecological risk index (RI), were in good accordance. ‘Heavy’ contamination and ‘severe’ ecological risk were found at three sites, Demin, Zhuwai and Renwu. Cadmium and copper contributed the highest to the ecological risk there. Results of positive matrix factorization modeling identified four sources of heavy metal pollution in both sediments and water. Heavy metal contamination in the Houjing River is attributed to companies carrying out various industrial processes along the riverbank, including traditional metal-plating, plastic manufacture and semi-conductor packaging. Therefore, future pollution control and management plans should emphasize the strict regulation of discharge from these industrial activities.
A study was conducted to evaluate level of water pollution and its influence on heavy metal contaminations of lake water of Dhaka metropolitan city. The water samples were collected from lakes of Dhaka metropolitan city during February to March, 2008. The chemical analysis of water samples included pH, EC, As, Cu, Mn, 'ln. Pb and Cd. Analysis of lake water samples was done at the Central Laboratory of Bangladesh Agricultural University, Mymensingh. The concentrations of heavy metal of lake water were recorded as: in case of pH = 6.95, in case of EC = 22.44 (?scm-1), in case of Cu = 0.018 ppm, in case of Zn = 0.274 ppm, in case of Mn = 0.084 ppm, in case of As = 0.002 ppb, in case of Pb = 0.002 ppm and in case of Cd = 0.044 ppm. The pH value of lakes water range from 5.34 to 7.68, an indication of slightly acidic to alkaline in nature. The average EC value for lakes water ranged from 17.61 to 34.61 ?Scm-1 where EC value varied from 14.24 to 33.48 ?Scm-1 in the lake water.DOI: http://dx.doi.org/10.3329/jesnr.v5i2.14841 J. Environ. Sci. & Natural Resources, 5(2): 345-348 2012
In this study, principal component analysis (PCA), factor analysis (FA), and the absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling technique were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, 15 years (2000–2014) dataset of 12 water quality variables covering 16 monitoring stations, and approximately 35,000 observations was used. The PCA/FA method identified five and four potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules and causes were explained. The APCS-MLR apportioned their contributions to each water quality variable. Results showed that the point source pollution discharges from anthropogenic factors due to the discharge of agriculture waste and domestic and industrial wastewater were the major sources of river water contamination. Also, the studied variables were categorized into three groups of nutrients (total kjeldahl nitrogen, total phosphorus, total phosphate, and ammonia-N), water murkiness conducive parameters (total suspended solids, turbidity, and chlorophyll-a), and salt ions (magnesium, chloride, and sodium), and average contributions of different potential pollution sources to these categories were considered separately. The data matrix was also subjected to PMF receptor model using the EPA PMF-5.0 program and the two-way model described was performed for the PMF analyses. Comparison of the obtained results of PMF and APCS-MLR models showed that there were some significant differences in estimated contribution for each potential pollution source, especially in the wet season. Eventually, it was concluded that the APCS-MLR receptor modeling approach appears to be more physically plausible for the current study. It is believed that the results of apportionment could be very useful to the local authorities for the control and management of pollution and better protection of important riverine water quality.
In the study, multivariate statistical methods including principal component analysis (PCA)/factor analysis (FA) and cluster analysis (CA) were applied to analyze surface water quality data sets obtained from the Huaihe River segment of Bengbu (HRSB) and generated during 2 years (2011–2012) monitoring of 19 parameters at 7 sampling sites. The results of PCA for 7 sampling sites revealed that the first four components of PCA showed 94.89% of the total variance in the data sets of HRSB. The Principal components (Factors) obtained from FA indicated that the parameters for water quality variations were mainly related to heavy metals (Pb, Mn, Zn and Fe) and organic related parameters (COD, PI and DO). The results revealed that the major causes of water quality deterioration were related to inflow of industrial, domestic and agricultural effluents into the Huaihe River. Three significant sampling locations—(sites 2, 3 and 4), (sites 1 and 5) and (sites 6 and 7)—were detected on the basis of similarity of their water quality. Thus, these methods were believed to be valuable to help water resources managers understand complex nature of water quality issues and determine the priorities to improve water quality.
Concentrations of heavy metals in water and sediment samples of Buriganga River in the capital city Dhaka, Bangladesh, were studied to understand the level of heavy metals and their source apportionment. The results showed that the mean concentrations of heavy metals both in water and sediment samples were very high and, in most cases, exceeded the permissible limits recommended by the Bangladesh government and other international organizations. Significantly higher concentrations of Pb, Cr, Mn, Co, Ni, Cu, Zn, As, and Cd were found in sediment samples. However, average concentrations of metals both in water and sediment samples were above the effect range median. The heavy metal pollution index (HPI) and degree of contamination (C
d) yielded different results in water samples despite significant correlations between them. The heavy metal evaluation index (HEI) showed strong correlations with HPI and C
d and provided better assessment of pollution levels. The enrichment factor (EF) and geoaccumulation index (I
geo) showed the elevated value of Cr, Pb, and Cd in access of background values. The measured elements were subjected to positive matrix factorization (PMF) and examining correlations in order to explain the content, behavior, and source apportionment of metals. PMF resulted in a successful partitioning of variances into sources related to background geochemistry and contaminant influences. However, the PMF approach successfully demarcated the major sources of metals from tannery, paint, municipal sewage, textiles, and agricultural activities.
A study was conducted to evaluate the level of water pollution and its influence on the chemical properties of river water of Dhaka metropolitan city. The water samples were collected from forty five locations of Dhaka metropolitan city during February to March, 2008. Analysis of the major chemical contaminations of river water samples containing Cu, Zn, Mn, As, Pb and Cd was conducted at the Central Laboratory of Bangladesh Agricultural University, Mymensingh. The heavy metal concentrations of river water were recorded as in case of Cu = 0.006 ppm, in case of Zn = 0.021 ppm, in case of Mn = 0.075 ppm, in case of As = 0.003 ppb, in case of Pb = 0.002 ppm and in case of Cd = 0.012 ppm, respectively. The pH of river ranged from 6.28 to 7.61. The EC values were 17.61 to 34.61 ?Scm-1, revealed that all the water samples were low salinity and also excellent for irrigation. According to drinking water (Potable water) and public water standard, Mn and Cd toxicity were detected in river water. For aquaculture standard Mn and Cd were found at harmful level for all living organism. Some water were found unsuitable due to higher concentration of Mn over the recommended limit but other ions like Zn, As, and Pb were within the 'safe limit'.DOI: http://dx.doi.org/10.3329/jesnr.v5i2.14842 J. Environ. Sci. & Natural Resources, 5(2): 349-353 2012
Sources affecting surface sediment samples at the western Bay of İzmit were investigated using a relatively new type of factor analysis: positive matrix factorisation (PMF). PMF uses estimates of the error in data to provide optimum data point scaling and applies the non-negativity constraints to the factors. The PMF results presented in this study are compared with the previously published factor analysis (FA) results to determine whether similar sources can be apportioned. A multi-element data set, generated by analysing sediment samples by inductively coupled plasma-atomic emission spectrometry (ICP-AES), was used in the comparison. To identify the sewage factor with the FA, dummy variables were also added to data set. Three, four and five sources were resolved with the FA without dummy variables (FAW), FA with dummy variables (FAD) and with the PMF, respectively. Among the resolved factors, three sources were common in all approaches: the iron and steel industry, the paint industry and crustal sources. The sewage factor was identified with the FAD and PMF. The PMF also resolved the motor vehicle factor. In this particular study, PMF allowed us to separate the anthropogenic factor obtained in the two factors, one representing the discharges from industries and the other representing discharges from sewage. The PMF method resolved 97% of the sediment mass concentrations and showed a significantly higher source resolution than the previously derived FA model.
Over the last four decades, a number of environmental indices including water quality indices and air pollution indices have been formulated and used. Usually, the indices are formulated based either on studies conducted by the indices' developers, or are formulated based on the Delphi technique, which takes into account the opinion of experts. In 1970, Brown used the Delphi technique to formulate a water quality index (WQI) for the National Sanitation Foundation (NSF) of the United States. However, it has been observed that the procedure followed for the formulation of the index does not accurately represent the opinion of the experts who responded to questionnaires. In this technical note, the shortcomings in the formulation of the NSF-WQI are brought out and possible improvements in the development of this index are presented.
To date, different water-quality indices (WQIs) categorizing water bodies have flourished in the literature. While this type of index has normally been applied to data sets from manual monitoring programs, we focus attention on the analysis of data from automated sampling networks, from which measurements of a small number of physico-chemical variables are usually obtained from different locations with high temporal resolution.To deal with data of this nature, we compare different indices for the physico-chemical evaluation of water quality. As a result, we select the WQI of the Canadian Council of Ministers of the Environment (CCME WQI) as the most suitable. Our interest in using this WQI rests on its flexibility for selecting parameters as well as the possibility of modifying the objectives to be met by each variable according to the specific end use of the water.We perform a sensitivity analysis for the CCME WQI in order to select the best procedure for calculating it according to input data.Finally, we apply the CCME WQI to simulated data sets describing three different environmental scenarios corresponding to episodes of discharge of urban wastewater, eutrophication and risk to fish. From this comparison and according to the specific objectives we define in this work, we rank sensitivity in CCME WQI performance in the following order: (1) urban wastewater; (2) eutrophication; and, finally, (3) risk to fish.
Hydrogeochemical investigations are carried out in and around Perumal Lake, Cuddalore district, South India in order to assess
its suitability in relation to domestic and agricultural uses. The water samples (surface water=16; groundwater=12) were
analyzed for various physicochemical attributes like pH, electrical conductivity (EC), sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), chloride (Cl−), bicarbonate (HCO3
−), sulfate (SO4
2−), phosphate (PO4), silica (H4SiO4) and total dissolved solids (TDS). Major hydrochemical facies were identified using Piper trilinear diagram. Hydrogeochemical
processes controlling the water chemistry are water–rock interaction rather than evaporation and precipitation. Interpretation
of isotopic signatures reveals that groundwater samples recharged by meteoric water with few water–rock interactions. A comparison
of water quality in relation to drinking water quality standard proves that the surface water samples are suitable for drinking
purpose, whereas groundwater in some areas exceeds the permissible limit. Various determinants such as sodium absorption ratio
(SAR), percent sodium (Na%), residual sodium carbonate (RSC) and permeability index (PI) revealed that most of the samples
are suitable for irrigation.
KeywordsHydrogeochemistry–Groundwater quality–Chemical weathering–Stable isotope–Perumal Lake
Understanding the spatial distribution and apportioning the sources of water pollution are important in the study and efficient management of water resources. In this work, we considered data for 13 water quality variables collected during the year 2004 at 46 monitoring sites along the Qiantang River (China). Fuzzy comprehensive analysis categorized the data into three major pollution zones (low, moderate, and high) based on national quality standards for surface waters, China. Most sites classified as "low pollution zones" (LP) occurred in the main river channel, whereas those classified as "moderate and high pollution zones" (MP and HP, respectively) occurred in the tributaries. Factor analysis identified two potential pollution sources that explained 67% of the total variance in LP, two potential pollution sources that explained 73% of the total variance in MP, and three potential pollution sources that explained 80% of the total variance in HP. UNMIX was used to estimate contributions from identified pollution sources to each water quality variable and each monitoring site. Most water quality variables were influenced primarily by pollution due to industrial wastewater, agricultural activities and urban runoff. In LP, non-point source pollution such as agricultural runoff and urban runoff dominated; in MP and HP, mixed source pollution dominated. The pollution in the small tributaries was more serious than that in the main channel. These results provide information for developing better pollution control strategies for the Qiantang River.
Factor analysis is applied to 28 groundwater samples collected from wells in the coastal blackfoot disease area of Yun-Lin, Taiwan. Correlations among 13 hydrochemical parameters are statistically examined. A two-factor model is suggested and explains over 77.8% of the total groundwater quality variation. Factor 1 (seawater salinization) includes concentrations of EC, TDS, Cl(-), SO(4)(2-), Na(+), K(+) and Mg(2+), and Factor 2 (arsenic pollutant) includes concentrations of Alk, TOC and arsenic. Maps are drawn to show the geographical distribution of the factors. These maps delineate high salinity and arsenic concentrations. The geographical distribution of the factor scores at individual wells does not reveal the sources of the constituents, which are instead, deduced from geological and hydrological evidence. The areas of high seawater salinization and arsenic pollution correspond well to the groundwater over-pumping area. Over-pumping of the local groundwater causes land subsidence and gradual salinization by seawater. The over-pumping also introduces excess dissolved oxygen that oxidizes the immobile minerals, releases arsenic by reductive dissolution of arsenic-rich iron oxyhydroxides and increases the arsenic concentration in water. The over-extraction of groundwater is the major cause of groundwater salinization and arsenic pollution in the coastal area of Yun-Lin, Taiwan.