Fecal and Coliform Levels as Indicative Factors in Deterioration of the Water Quality of

Author(s):  
EUKENE OPORTO BENSIG ◽  
MARY JOYCE L. FLORES ◽  
FLEURDELIZ F. MAGLANGIT

The use of surface waters such as rivers for domestic, agricultural andindustrial purposes have made them vulnerable to pollution leading to impairedwater quality. The water quality of Lahug River in Cebu City was evaluated usingcoliforms as indicators, in relation with physicochemical parameters such as biological oxygen demand (BOD), conductivity, dissolved oxygen (DO), nitrate,pH, phosphate, salinity, temperature, total dissolved solids (TDS) and totalsuspended solids (TSS). Sampling was done once a month from November 2011to April 2012 in three stations covering the upstream, midstream and downstream.The multiple tube fermentation technique was used for the analysis of coliforms.The level of these indicator bacteria increased from the upstream towards thelower reaches of the river especially in the months of February to April; however,the difference in values across time was not significant. This implies that therewas a continuous fecal pollution in the river. There were no statistically significantcorrelations between FCs and TCs with the physicochemical parameters. Anegative relationship was observed among FCs and TCs with pH, TSS, DOand nitrate (p>0.05). These results suggest the presence of sewage and organicpollutants in the river.Keywords: Aquatic Ecology, water quality, coliform, physicochemical parameters,experimental design, Philippines

2015 ◽  
Vol 16 (SE) ◽  
pp. 395-403
Author(s):  
Abbas Ghaffari Habib ◽  
Seyed Hadi Khatami

In Bahar County (Iran), rivers are among the important sources of water for the agricultural sector. Therefore, this research evaluated the parameters of temperature, pH, Total Dissolved Solids (TDS), turbidity, nitrate, total phosphate, dissolved oxygen (DO), Biological Oxygen Demand (BOD5), and fecal coliform at five stations for five months (from February 2015 to June 2015) to determine water quality in the rivers. Based on this evaluation, the NSFWQI index was calculated and, finally, the routes of the rivers were zoned. The best water quality was recorded at Station Number 3 with the NSFWQI Value of 80 in January, and the worst at Station Number 5 (latgah) with the NSFWQI Value of 37 in June. Based on the mean NSFWQI indices, water quality was Medium at Stations Number 1, 2, and 4, good at Station Number 3, and bad at Station number 5.


2013 ◽  
Vol 5 (2) ◽  
pp. 213-218 ◽  
Author(s):  
MS Islam ◽  
TR Tusher ◽  
M Mustafa ◽  
S Mahmud

The study was conducted to investigate the effects of solid waste and industrial effluents on the water quality of Turag River. Both the upstream and downstream sampled water from the selected points were analyzed for color, odor, pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), biological oxygen demand (BOD), copper (Cu), cadmium (Cd), iron (Fe), lead (Pb) and zinc (Zn) concentrations. Results of the study showed that the color of water was light to dark black and emitted noxious smell due to the industrial effluents. The upstream water was slightly alkaline with comparatively high DO content while low concentration of other parameters. The water after the solid waste and effluents received points as well as middle and downstream points was slightly alkaline with higher levels of other parameters when compared with upstream point. The minimum and maximum values of pH, EC, TDS, DO and BOD were 7.24-7.61, 425-2277 ?S/cm, 239-1349 ppm, 1.22-3.66 ppm and -2.44-0.86 ppm, respectively. The continuous dumping of waste materials resulted in a marked increase in the concentration of metals in the river water varied in the order of Fe > Zn > Pb > Cu > Cd. The study concluded that the downstream water in the river was almost polluted and unsuitable for human consumption and aquaculture purposes.DOI: http://dx.doi.org/10.3329/jesnr.v5i2.14817 J. Environ. Sci. & Natural Resources, 5(2): 213-218 2012


2009 ◽  
Vol 6 (3) ◽  
pp. 898-904
Author(s):  
D. Ilangeswaran ◽  
R. Kumar ◽  
D. Kannan

Various samples of groundwater were collected from different areas of Kandarvakottai and Karambakudi of Pudukkottai District, Tamilnadu and analyzed for their physicochemical characteristics. The results of this analysis were compared with the water quality standards of ISI, WHO and CPHEEO. In this analysis the various physicochemical parameters such as pH, electrical conductivity, turbidity, total dissolved solids, Cl-, F-, SO42-, PO43-, NO3-, NO2-, CN-, Nas+, K+, NH3, Mn, Fe, Ca & Mg hardnessetc., were determined using standard procedures. The quality of groundwater samples were discussed with respect to these parameters and thus an attempt were made to ascertain the quality of groundwater used for drinking and cooking purposes in and around Kandarvakottai and Karambakudi areas.


Author(s):  
Vasudha Lingampally ◽  
V.R. Solanki ◽  
D. L. Anuradha ◽  
Sabita Raja

In the present study an attempt has been made to evaluate water quality and related density of Cladocerans for a period of one year, October 2015 to September 2016. Water quality parameters such as temperature, PH, total dissolved solids, dissolved oxygen, biological oxygen demand, total alkalinity, total hardness, chlorides, phosphates, and nitrates are presented here to relate with the abundance of Cladocerans. The Cladoceran abundance reflects the eutrophic nature of the Chakki talab.


Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1037 ◽  
Author(s):  
Jesús Prieto-Amparán ◽  
Beatriz Rocha-Gutiérrez ◽  
María Ballinas-Casarrubias ◽  
María Valles-Aragón ◽  
María Peralta-Pérez ◽  
...  

Water quality is relevant due to the complexity of the interaction of physicochemical and biological parameters. The Irrigation District 005 (ID005) is one of the most important agricultural region in Chihuahua, México; for that reason, it was proposed to investigate the water quality of the site. Water samples were collected in two periods: Summer (S1) and Fall (S2). The samples were taken from 65 wells in S1, and 54 wells in S2. Physicochemical parameters (PhP) such as Arsenic (As), Temperature, Electrical Conductivity (EC), Oxide Reduction Potential (ORP), Hardness, pH, Total Dissolved Solids (TDS), and Turbidity were analyzed. The data were subjected to statistical principal component analysis (PCA), cluster analysis (CA) and spatial variability tests. In both seasons, the TDS exceeded the Mexican maximum permissible level (MPL) (35% S1, 39% S2). Turbidity exceeded the MPL in S1 (29%) and in S2 (12%). Arsenic was above the MPL for water of agricultural use in 9% (S1) and 13% (S2) of the wells. The PCA results suggested that most variations in water quality in S1 were due to As, pH and Temperature, followed by EC, TDS and Hardness; while in S2 to EC, TDS and Hardness, followed by As and pH.


2016 ◽  
Vol 8 (1) ◽  
pp. 58-65
Author(s):  
Sadhana Pradhanang

The assessment of water quality of Karra River in Hetauda, Nepal was carried out by determining the changes in the concentration levels of eight physico-chemical parameters (pH, Electric conductivity (EC), bicarbonate, dissolved oxygen (DO), silica, chemical oxygen demand (COD), phosphate and nitrate). The samples were collected from upstream, industrial belt and downstream of the Karra River. The Karra River is the dumping ground for industrial effluents of Hetauda industrial district (HID). On analysis, the concentrations of most of the physico-chemicals parameters were found to be above the prescribed limits for industrial wastewater into inland surface waters. Dissolved Oxygen was found to be in the range of 0.49- 8.47 mg/L while COD, nitrate and phosphate were recorded in the range of 8.3-367 mg/L, 0.35- 78.22 mg/L and 0.01-1.64 mg/L, respectively. Concentrations of most of these parameters were within the prescribed limits in the samples collected from upstream and downstream, revealing the river still in good condition at these points indicating less human interference at the head water region and good self-purification capacity at downstream. However the concentrations of the pollutants’ parameters are higher at the sample points just after effluent discharge.Journal of Hydrology and Meteorology, Vol. 8(1) p.58-65


2020 ◽  
Vol 5 (4) ◽  
pp. 482-488
Author(s):  
S.O. Oladeji

Evaluation of physicochemical parameters namely alkalinity, biological oxygen demand (BOD), chemical oxygen demand (COD), conductivity, dissolved oxygen (DO), hardness, pH and total dissolved solids (TDS) in the wastewater samples collected from Muhammad Ayuba dam in Kazaure, Nigeria. The study was conducted during harmattan season for a period of three months from November, 2019 – January, 2020. All the parameters were analysed using conventional methods. The results showed their concentrations were in the range of 1.00 – 1.50 mg/L for alkalinity, 3.00 – 3.45 mg/L for BOD, 12.45 – 24.00 mg/L for COD, 745 – 1200 µS/cm for conductivity, 5.50 – 6.30 mg/L for DO, 1.82 – 2.45 mg/L for hardness, 7.20 – 7.90 for pH and 410 – 440 mg/L for TDS. The concentrations of these parameters in the wastewater were observed less than World Health Organization (WHO) tolerance limits with exception of electrical conductivity that was above 1000 µS/cm after four weeks of investigation. This study revealed gradual build-up of various ions in the dam water due to the mixing of contaminated wastewater from the adjacent community. Therefore, the periodical monitoring of different physicochemical parameters of the dam water should put in place as to evaluate their environmental impacts and possible potential risks.


2020 ◽  
Vol 42 ◽  
pp. e2
Author(s):  
Késia Gomes da SIlva Cavalcanti ◽  
Darlan Ferreira Da Silva ◽  
Neuriane SIlva Lima ◽  
Rita De Cássia Mendonça ◽  
Wallace Ribeiro Nunes Neto ◽  
...  

The Corda river is the main source of fresh water for recreation, leisure, supply and irrigation to the municipality of Barra do Corda - MA. The objective of the present study was to evaluate the physicochemical parameters of Corda river’s water using the methodology described by the American Public Health Association. The water samples were collected in the seasonal period spanning between February and September of the year of 2018. The parameters which were analyzed during the study were pH, conductivity, turbidity, total dissolved solids and salinity, besides concentrations of nitrite, nitrate, and total phosphorus. Three principal components were identified during the PC Analysis. Those components explain more than 74% of the total variance observed during the rainy and dry season. Axis 1and 2 included variables which were related to quality of water and could be affected by the change in seasons. The results indicated that pH (7.11), P (2,82 mg L-1), NO3- (3,23 mg L-1), turbidity (35.82 NTU) and conductivity (35.83 µS/cm) parameters were most affected by changing from rainy to dry season.


Author(s):  
Sipra Mallick ◽  
F Baliarsingh

Water quality index (WQI), a technique of rating water quality, is an effective tool to access quality and ensure sustainable safe use of water for drinking. The main objective of the present study is to access the surface water quality of Kathajodi river for knowing the suitability of drinking purpose by calculating the WQI. Samples were collected from selected locations during different seasons (winter, summer, rainy) over a period of 3 years (2011, 2012, 2013). Water quality assessment was carried out for the parameters like pH, total dissolved solids, total suspended solids, Alkalinity, Biological Oxygen Demand(BOD), Dissolved Oxygen(DO), Chloride, Nitrate, Alkalinity, Total Hardness, Calcium, Magnesium. The main objective is to develop a model to assess and predict the water quality changes of Kathajodi River Basin Odisha, India using neural networks and compared with the statistical methods. The result shows the proposed ANN prediction model has a great potential to simulate and predict the strongly correlated parameters like TSS (Total Suspended Solids), TDS(Total Dissolved Solids), Alkalinity, BOD(Biological Oxygen Demand)with Mean Square Error (MSE) : TSSMSE = 1.78 ; TDSMSE = 0; AlkalinityMSE = 3.77 and BODMSE = 8E-03.The Neural Network model has been compared with Linear Regression model to find out the best modelling approach for the study area. And it is concluded that the neural network model is superior to Linear Regression Model.


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