Assessment of some water quality parameters of Kaptai lake, Bangladesh: a multivariate analysis

Water quality in five southern Louisiana commercial crawfish (Procambarus clarkii and P. acutus acutus) ponds was monitored from November 1982 through May 1983. Two ponds were planted with rice (Oryza sativa) and three ponds had volunteer terrestrial and semi-aquatic vegetation as crawfish forage. Water quality was poorest in November, April, and May when water temperatures exceeded 18"C. However, only dissolved oxygen (DO) attained concentrations low enough (<1.0 mg/liter) to be acutely toxic to crawfish. Free carbon dioxide (CO2) attained levels (12.0 mg/liter) that could potentially harm crawfish during periods of low DO (<2.0 mg/liter). The temperature, pH, free CO2, nitrate, total phosphorus, biochemical oxygen demand (BOD), chlorophyll a, total hardness, and total alkalinity did not differ significantly among rice ponds and ponds with volunteer vegetation. The DO, nitrite, total nitrogen, and chemical oxygen demand (COD) were highest in rice ponds (P<0.05). The soluble inorganic phosphorus (SIP) and conductivity were highest in ponds with volunteer vegetation (P<0.05). Free CO2, SIP, conductivity, and total alkalinity levels were positively correlated with an increase in macrophytic biomass (P<0.10). Nitrite, total nitrogen, COD, BOD, turbidity, temperature and DO decreased with increased vegetative biomass. Crawfish catch was positively correlated with total ammonia, BOD, COD, and water temperature, and negatively correlated with total phosphorus, total nitrogen, SIP, total alkalinity, and DO. The toxicity of hydroxyl and hydrogen ions (i.e., pH), ammonia, and nitrite to juvenile P. clarkii was determined in static acute toxicity tests. The 96-hour LC50’s of hydroxyl and hydrogen ions to P. clarkiiwere 10^-3.88 moles OH /liter (pH 10.12) and 10^-3.21 moles H /liter (pH 3.21). The 96-hour LC50’s of ammonia and nitrite to P. clarkii were 2.65 mg NH3-N/liter and 5.94 mg N02-N/liter, respectively.

The present investigation deals with the seasonal variations in physico-chemical characteristics and abundance of zooplankton population in Dora Beel, Kamrup District of Assam. The survey was undertaken from March, 2022 - February, 2023 and done in four different seasons viz. Monsoon, Pre-monsoon, winter and Post-monsoon. The physico-chemical studies include the seasonal study of water temperatures, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), pH and Free Carbon dioxide (CO2 ). The result of water analysis reveals that in winter season water temperature and free CO2 were minimum but dissolved oxygen was maximum. In the monsoon season water temperature and BOD were maximum but DO was in minimum level. Free carbon dioxide was maximum but BOD was minimum in post-monsoon. The pH level was minimum in pre-monsoon season and maximum in post-monsoon. A total 24 numbers of zooplankton species were recorded belonging to five different planktonic groups such as Protozoa, Rotifera, Cladocera, Ostracoda and Copepoda. The post-monsoon season observe as peak abundance season for all the zooplanktons and pre-monsoon as low abundance season. Protozoa is the dominant group (based on abundance) followed by Rotifera, Cladocera and Copepoda. But the number of species was highest in Rotifera group. The Copepoda and Ostracoda were the lowest abundant group.

The Poma River in Arunachal Pradesh serves as the primary habitat for Aborichthys uniobarensis, an ornamental fish species endemic to biodiversity hotspot. The present study aimed to investigate the habitat characteristics of Aborichthys uniobarensis within the Poma River. Given the species' predominant presence in this river, understanding the water quality of the Poma River is crucial for further biological research, and of course conservation aspect of this fish species within in-situ as well ex-situ habitat. Over a two-year period (January 2018 to December 2019), the study assessed various physicochemical parameters (pH, water temperature (WT), dissolved oxygen (DO), biochemical oxygen demand (BOD), total dissolved solids (TDS), free carbon dioxide (FCO2), alkalinity, total hardness, electrical conductivity (EC), and salinity) at three sites along the Poma River with seasonal comparisons. Water samples were randomly collected in the morning between 6 a.m. to 10 a.m. Samples were analysed based on the standard methods of APHA (2012). The results indicated consistent conditions across sites but significant variations by season and year (Kruskal-Wallis and Mann-Whitney tests). Minimum values recorded were pH 6.29, WT 18.62°C, DO 6.55 mgL-1, BOD 3.85 mgL-1, TDS 29.78 mgL-1, FCO2 3.89 mgL-1, alkalinity 37.25 mgL-1, total hardness 23.71 mgL-1, EC 57.22 µs/cm, and salinity 0.05 ppt, while maximum values were pH 7.42, WT 25.43°C, DO 7.80 mgL-1, BOD 5.42 mgL-1, TDS 71.12 mgL-1, FCO2 6.48 mgL-1, alkalinity 59.34 mgL-1, total hardness 45.62 mgL-1, EC 117.33 µs/cm, and salinity 0.07 ppt. Simpson correlation tests revealed significant positive and negative correlations among the parameters. PCA analysis highlighted that WT, DO, pH, TDS, BOD, and FCO2 (both physical and chemical factors) have a greater influence on supporting A. uniobarensis, other fish species and the overall health of the river. As the values of habitat parameters were within the acceptable range, the River Poma is congenial for A. uniobarensis along with other species available in this particular riverine habitat.

Water analysis is essential to preserve and protect the natural ecosystem, which depends on their physical, chemical and biological characteristics; these are directly linked with human welfare. This study was evaluated the physicochemical features of water and their relationships in Sindphana Dam near Shirur Kasar, Breed district, Maharashtra state, India between January and December 2012. This study shows the water quality parameters were fluctuated during the summer, monsoon and winter seasons in Sindphana Dam. In this study, air temperature was positively related to water temperature, transparency and pH while it was negatively related to electric conductivity and dissolved oxygen (DO). The water temperature was positively related to air temperature, transparency and pH, while it was negatively related to electric conductivity and DO. Water transparency also negatively related to turbidity, electric conductivity, biochemical oxygen demand (BOD) and chemical oxygen demand (COD). Electric conductivity was positively related to turbidity, BOD and COD. The pH was negatively related to electric conductivity, DO, BOD and COD. The study indicated that the Sindphana Dam water quality parameters were acceptable limits for aquatic biota. Bangladesh J. Zool. 49 (3): 403-410, 2021

Rivers are important source of fresh water which is important for the sustenance and welfare of the society. The present study deals with the assessment of water quality parameters and with the population of phyto- and zoo-plankton of Himalayan Bhagirathi river in Uttarkashi, Uttarakhand (India). The samples were collected from the study area during summer, monsoon, and winter seasons for water quality and phyto- and zoo-plankton analysis. The air temperature, depth temperature, pH, total alkalinity, total dissolved solids (TDS), dissolved oxygen (DO), turbidity, free CO2, electric conductivity (EC), biological oxygen demand (BOD) and total hardness were determined. The study revealed that DO was maximum in winter (12.35 ± 0.25 mg L-1) and minimum in June to September (9.75 ± 0.25 mg L-1). The Bhagirathi water contained maximum DO in colder month, followed by a gradual decrease to its lowest value during June to September. BOD, an important indicator of pollution status of a water body, was high during summer perhaps due to low discharge at river. BOD was high in monsoon (4.4 ± 0.14 mg L-1) and low in winter (1.5 ± 0.14 mg L-1). The study revealed low river flow during winter. Bacillariophyceae was maximum (442 units L-1) in February and minimum (18 units L-1) in July. Chlorophyceae was maximum (80 units L-1) in January and minimum (6 units L-1) in August, while Myxophyceaewas maximum (34 units L-1) in February and minimum in June and Xanthophyceae was not recorded at this site. The maximum number of zooplankton genera was observed during winter and minimum in rainy season. The study showed that there is an urgent need to have proper water management in rainy and summer seasons so as to restore the water quality of this river.

The sacred river Ganga in Kanpur city, Uttar Pradesh, India, underwent physio- chemical analysis in the month of Nov 2022. Three samples from each of the ten locations in Kanpur city were collected over two days and analyzed various physicochemical parameters: temperature, pH, total alkalinity (TA), biological oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total dissolved solids (TDS), chlorides, electric conductivity (EC), nitrate, and total hardness (TH). Pearson correlation analysis was conducted in SPSS to examine relationships between these parameters. The investigation highlights significant trends in water quality parameters along different sites. The Bithoor site exhibited better DO levels (7.32 mg L-1) and a slightly alkaline pH (8.31), indicating relatively healthier water conditions. In contrast, the Sarsaiya ghat site maintained stable BOD (22.25 mg L-1), chloride levels (16.99 mg L-1), and alkalinity (450.15 mg L-1), suggesting a more buffered but still impacted ecosystem. The Jajmau site showed the highest levels of BOD (38.78 mg L-1) and TDS (270.78 mg L-1), coupled with an elevated pH of 8.67 and chloride concentration of 21.12 mg L-1, pointing to higher organic pollution and industrial effluents. A notable negative correlation was observed between DO and other water quality parameters, reinforcing the trend of declining oxygen levels with increasing pollution. Conversely, pH, temperature, COD, BOD, TA, TH, TDS, chloride (Cl-), EC, sulfate (So₄ ²-), and nitrate (No₃ -) exhibited positive correlations, demonstrating a progressive deterioration of water quality from upstream to downstream. The Ganga river's water quality needs to be routinely checked to conduct appropriate treatment. The findings hold critical relevance for environmental policymakers, offering evidence-based insights for the development of sustainable water resource management strategies. Addressing the pollution of the Ganga is essential to restore its sanctity and safeguard public health, support aquatic ecosystems, and ensure long-term socio-economic sustainability.

This study was carried out to understand how land use patterns influence surface water quality in Tien Giang Province using remote sensing and statistical approaches. Surface water quality data were collected at 34 locations with the frequency of four times (March, June, September, and November) in 2019. Water quality parameters were used in the analysis, including pH, temperature, electrical conductivity (EC), total suspended solids (TSS), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), ammonium (N-NH4+), nitrite (N-NO2−), nitrate (N-NO3−), sulfate (SO42−), orthophosphate (P-PO43−), chloride (Cl−), total nitrogen (TN), total phosphorus (TP), and coliform. The relationship between land use patterns and water quality was analyzed using geographic information techniques (GIS), remote sensing (RS), statistical approaches (cluster analysis (CA), principal component analysis (PCA), and Krustal–Wallis), and weighted entropy. The results showed water quality was impaired by total suspended solids, nutrients (N-NH4+, N-NO2−, P-PO43−), organic matters (BOD, COD), and ions (Cl− and SO42−). Kruskal–Wallis analysis results showed that all water quality parameters in the water bodies in Tien Giang Province were seasonally fluctuated, except for BOD and TN. The highest levels of water pollutants were found mostly in the dry season (March and June). The majority of the land in the study area was used for rice cultivation (40.64%) and residential (27.51%). Water quality in the study area was classified into nine groups corresponding to five combined land use patterns comprising residential–aquaculture, residential–rice cultivation, residential–perennials, residential–rice–perennial, and residential–rice–perennial crops–aquacultural. The concentrations of the water pollutants (TSS, DO, BOD, COD, N-NH4+, N-NO2−, Cl−, and coliform) in the locations with aquaculture land use patterns (Clusters 1 and 2) were significantly larger than those of the remaining land use patterns. PCA analysis presented that most of the current water quality monitoring parameters had a great impact on water quality in the water bodies. The entropy weight showed that TSS, N-NO2−, and coliform are the most important water quality parameters due to residential–aquaculture and residential–rice cultivation; EC, DO, N-NH4+, N-NO2−, Cl−, and coliform were the significant variables for the land use type of residential–perennial crops; N-NO2−, P-PO43−, and coliform for the land use pattern of residential–rice cultivation–perennial crops) and N-NH4+, N-NO2−, Cl−, and coliform for the land use pattern of residential–rice cultivation–perennial crops–aquaculture. The current findings showed that that surface water quality has been influenced by the complex land use patterns in which residential and rice cultivation may have major roles in causing water impairment. The results of the water quality assessment and the variation in water properties of the land use patterns found in this study provide scientific evidence for future water quality management.

Dissolved oxygen (DO) as one of the most fundamental parameters of water quality plays a vital role in aquatic life. This study was conducted to predict DO, biological oxygen demand (BOD), and chemical oxygen demand (COD) in an intensive rainbow trout rearing system with different biomass (B). The multilayer perceptron (MLP) and the radial basis function (RBF) neural networks were employed for evaluating the impacts of food parameters (crude protein (CP), consumed feed (CF)), fish parameters (different values of B, and weight gain (WG)), and water quality parameters including temperature (T) and flow rate (Q) on variation of DO, BOD, and COD concentrations. This study's results showed that although both MLP and RBF neural networks are capable to estimate DO, BOD, and COD concentrations, RBF neural network showed better performance compared to MLP neural network. The results of sensitivity analysis indicated that the parameter CF has the highest effect on DO concentration estimation. Independent variables CF, CP, WG, and B showed the highest to the lowest rank of impacts on BOD estimation, respectively. The results also illustrated a decreasing trend of the effects on the estimation error of COD changes simulation by all independent variables, including B, T, WG, CF, CP, and Q, respectively. RBF neural network based on better stability and generalization ability with average root mean square error (RMSE) and mean absolute percentage error (MAPE) values of less than 0.12 and 3% was superior to MLP in DO, BOD, and COD concentration prediction. Moreover, CF was identified as the most effective factor in estima12tion process. Based on the present study results, there are direct relationships between DO, BOD, and COD concentrations and water quality parameters, fish parameters, and food parameters. Food parameters relative to fish and water quality parameters imposed the greatest effects. Improvement in feeding process such as application of intelligence feeding methods and change in fish diet and feeding time can considerably reduce losses in production system. Graphical abstract.

In this study, seasonal and spatial variations in physicochemical parameters of water and proximate composition of Macrobrachium macrobrachion from Badagry Creek and Ologe Lagoon were examined. Samples of water and M. macrobrachion were collected from both stations on a monthly basis for six months. The physicochemical parameters monitored were pH, temperature, total suspended solids, total dissolved solids, total solids, total alkalinity, free carbondioxide, conductivity, salinity, dissolved oxygen, biochemical oxygen demand, ammonia and turbidity, while the proximate composition parameters were moisture content, crude protein, crude fibre, carbohydrate, crude lipids and ash. It was observed that alkalinity, salinity, dissolved oxygen, temperature and ammonia determined for both sample stations were within recommended limit of Food and Agricultural Organization, except pH for Badagry creek. There was no significant difference (p > 0.05) in seasonal variations of most physico-chemical parameters in both stations except for pH in Ologe lagoon, and electrical conductivity (EC), total dissolved solids (TDS) and total solids (TS) in both stations. Also, with the exception of EC, TDS and TS, there was no significant difference for spatial variation of physico-chemical parameters between the two stations. Moisture content, lipid and ash contents showed significant seasonal variation in Ologe lagoon, while crude protein and crude fibre recorded no significant difference. For Badagry creek, with the exception of moisture content, all other proximate composition parameters showed significant difference. However, there was no significant spatial variation in proximate composition between the prawns in Ologe lagoon and Badagry creek. There were gradual effects of season on water quality and proximate composition but these effects still support growth and survival of the prawn. However, regulatory measures should be put in place to protect these water bodies from direct/indirect human activities that can cause adverse damages.

Present work deals with the seasonal variations in physico-chemical parameters of river Mula at Pune city. Water samples were collected monthly from selected sampling stations (Station I- Wakad; IIAundh and III-Dapodi) in winter, summer and monsoon seasons during October 2007 to September 2008. The analysis was carried out for temperature, pH, dissolved oxygen (DO), free carbon dioxide (free CO 2 ), total alkalinity, total hardness, biological oxygen demand (BOD), chemical oxygen demand (COD), chloride, nitrate and phosphate. It was observed that, temperature, chloride, BOD, COD, total alkalinity, total hardness, nitrate and phosphate content was high during summer than winter and less during monsoon seasons. Whereas, the DO content decreased in the summer and increased in the winter followed by monsoon seasons. The quality of water at station II and station III were high in term of nutrient loads, due to influent domestic wastewater. These results suggest that the water quality of river Mula is adversely affected and impaired by the discharge of domestic waste.

In this study, some physico-chemical parameters of seven selected sampling sites (SSs) along the northern coastal line of Gökova Bay were investigated monthly. Then collected data were evaluated through the multivariate statistical analyses. Monthly distribution of water quality parameters was created using box plot across the SSs. When the parameters were examined with Spearman's rho correlation, the highest positive correlations were found to be between DO (Dissolved oxygen)‒SO (Saturated oxygen), EC (Electrical conductivity)‒Salt (Salinity), DO‒BOD5 (Biological oxygen demand), SO‒BOD5, TP (Total phosphorus)‒PO4 (Ortho-phosphate), while the highest negative correlations were found to be between WT (Water temperature)‒DO, EC‒NO3 (Nitrate nitrogen), Salt‒NO3, WT‒SO. When Kruskal Wallis Test was applied to water quality parameters, WT, DO, SO, SUS (Suspended solids), TP, NO2, PO4, NH4, NO3, BOD5 differed significantly in terms of sampling months (p

This study presents the assessment of selected water quality parameters (WQP) distribution at Putrajaya Lake during the dry and wet season using spatial analysis. The WQP used in this study were dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonia-nitrogen (NH3-N), total suspended solid (TSS), pH and temperature. Total thirteen water samples were obtained during both dry and wet seasons from May 2015 until March 2016 distributed throughout the areas. To explore the WQP distribution, Inverse Distance Weighted (IDW) was employed. The results have shown that mean values of WQ concentration during dry and wet season are varies accordingly. The highest value parameters of water quality during dry season which are COD (17.2 mg/L), DO (7.11 mg/L) and NH3N (0.94 mg/L). Meanwhile on the wet season, the highest values are recorded for BOD (5.27 mg/L), pH (7.62 mg/L) and TSS (18.4 mg/L) respectively. This has indicated that the concentration of WQP in the lake changed seasonally. Furthermore, among the WQPs; DO, TSS and COD have exhibited significant relationship between others for both seasons.

As one of the most valued and treasured natural resources, today many lakes in the world face degradation of their water quality due to nutrient enrichment, toxic contamination, and hydrological modification from their drainage areas. Among various water quality impairments, dissolved oxygen (DO) depletion is often a leading stressor in lake systems. Despite numerous studies on DO in deep water lakes in temperate regions, the knowledge of DO dynamics in eutrophic shallow lakes in subtropical regions is still limited. This thesis research conducted intensive DO monitoring in an eutrophic shallow lake in south Louisiana to characterize diel cycles of DO to determine trophic state changes, develop a deterministic model that can predict hourly change in DO of a water body with high-time resolution weather parameters, and develop a rapid field method of predicting biochemical oxygen demand (BOD) using chlorophyll-a fluorescence. DO concentrations in the studied lake were recorded at 15-minute intervals during 2012-2014, along with other water quality parameters. Field trips were made to measure lake water fluorescence and collect water samples for BOD and nutrient analysis. Additionally, a comparative study was done to discern trophic state changes over the past 5 years. The research yielded a substantial set of findings and conclusions to the research questions initially proposed. A comparison of diel DO cycles between 2008-2009 and 2013-2014 successfully revealed a clear intensification of eutrophication in the studied lake, indicating that analyzing the change in diel DO ranges can improve the current methods for classifying trophic states and assessing the change of eutrophication status of water bodies. A one-dimensional, deterministic DO model was developed for estimating the hourly change of source and sink components of DO, such as photosynthesis, re-aeration, respiration, BOD and sediment oxygen demand. The modeling yielded successful results of simulating high-time fluctuation of DO in the studied lake overall and showed good predictability for extreme algal bloom events. There was a linear, positive relationship between chlorophyll a fluorescence and BOD, and the relationship appeared to be stronger with the 10-day BOD (r2 = 0.83) than with the 5-day BOD (r2 = 0.76).

Water quality assessment involves the determination of a number of parameters using several analytical methods which are often tedious and time consuming. Artificial Neural Network (ANN) was used in this study to model the relationship between fifteen (15) water quality parameters used to predict other two (2) related parameters in other to reduce the burden of long experimental procedures. Water samples were collected from six (6) point and non point sources of pollution along Asa River in Ilorin during the peak of rainy season (June–Aug, 2014) and peak of dry season (Nov–Jan, 2015). Physical and chemical parameters inputted into the models include pH, turbidity, total dissolved solids, temperature, electrical conductivity, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, hardness, chloride, sulphate, phosphate, calcium, magnesium and nitrate. The output models include: biochemical oxygen demand (BOD) and dissolved oxygen (DO). The three layer feed-forward model with back-propagation multi-layer perception (MLP) models architecture of 15-9-1 for BOD and 15-13-1 for DO yielded optimal results with 9 and 13 neurons in hidden layer for BOD and DO respectively. The ANN was successfully trained and validated with 83% and 17% of the data sets respectively. Performance of the models was evaluated by statistical criteria of average error (AE) and mean square error (MSE). The correlation coefficients of ANN models for prediction of BOD and DO were 0.9525 and 0.9556 respectively. Sensitivity analysis was also carried out to identify the most significant input-output relationship. Hence, the ANNs was able to show remarkable prediction performance to predicting the BOD and DO in Asa River, Ilorin.DOI: http://dx.doi.org/10.5755/j01.erem.72.3.14120

Deterioration of water quality of lakes and reservoirs has become major global concerns that impose serious environmental impacts for both aquatic and terrestrial environments. In the current study, many parameters like temperature (Temp), electric conductivity (EC), dissolved oxygen (DO), turbidity (TU), pH, biological oxygen demand (BOD), chemical oxygen demand (COD), total alkalinity (TA), total dissolved solids (TDS), total organic carbon (TOC), nitrate(NO3−), phosphate (PO43−) and chlorophyll a (chl-a) were determined. The study covered the Angereb reservoir and its tributaries on a monthly basis from January to March 2019 at five sampling stations in accordance with APHA 2017 guide lines for physicochemical analysis. The values of all the investigated parameters, except DO (at AU, AD, KU and KD), COD and TU, were below the maximum permissible limits set by WHO. Thus, the findings for DO, TU and COD demonstrated that remedial actions should be taken to improve the quality of the water in the reservoir and its tributaries. Multivariate statistical methods (PCA and CA) were applied to detect spatial and temporal variations of water quality parameter. The first three principal components were enough to develop the PCA score plot which explained about 71.32% of the total variance in the dataset. The PCA and CA have provided similar information; grouped the 24 samples into 3 significant clusters showing spatial variations but minimal temporal variations were observed within the samples collected in the period of January in the reservoir site. The water quality parameters, TU and BOD, were moderately positively loaded on the space of the first principal component and were found to be associated with each other, whereas the EC and TDS have shown moderate negative loading and positively associated with each other. This study suggested PCA and CA methods found to be useful tools for monitoring and controlling water quality parameters for selected sampling stations of surface water.