Temporal variability in water quality parameters—a case study of drinking water reservoir in Florida, USA

2012 ◽  
Vol 185 (5) ◽  
pp. 4305-4320 ◽  
Author(s):  
Gurpal S. Toor ◽  
Lu Han ◽  
Craig D. Stanley
2020 ◽  
Vol 20 (5) ◽  
pp. 1862-1870
Author(s):  
Jung Eun Lee ◽  
Seok-Jae Youn ◽  
Myeongseop Byeon ◽  
Soon-Ju Yu

Abstract In 2012, a large concentration of geosmin was found in the Paldang reservoir, which is the primary source of drinking water in Seoul, Korea. In June and September 2012, we measured the concentrations of cyanobacteria and actinomycetes, and geosmin, to identify the source of geosmin in the Paldang reservoir. A total of 68 water samples were collected from two sampling sites (Sambong, Paldang), and used to analyze the correlation between cyanobacteria, actinomycetes, and geosmin. The cell density attained a maximum of 24,722 cells/mL on August 11, 2012 and geosmin occurred at a high concentration of 3,934 ng/L on August 13 in Sambong. After July 31, 2012 a rapid increase in growth and cell density occurred with a peak value of 11,568 cells/mL on August 6, 2012. At the same time, the geosmin concentration increased to 3,157 ng/L in Paldang. The number of cyanobacteria positively correlated with geosmin concentration (R2 = 0.84, P < 0.0001), while actinomycetes were not significantly correlated with geosmin (R2 = 0.01, P = 0.709). In addition, the number of actinomycetes was associated with increased turbidity (R = 0.507). Among the various water quality constituents, temperature affected cyanobacteria in the Paldang reservoir (R = 0.803). These results suggest that cyanobacteria are the main source of geosmin in the Paldang reservoir, which might be providing useful information for managing the unpleasant taste of its drinking water.


2008 ◽  
Vol 8 (2) ◽  
pp. 173-180
Author(s):  
M. L. Tran ◽  
J. Bahng ◽  
S. Pankratz ◽  
I. H. Suffet

Urban runoff from five storms during the 2003–2004 and 2004–2005 rainy seasons was sampled at the exit point of runoff diversion forebays leading to engineered retention ponds to protect a drinking water reservoir. Samples were collected from three different drainage areas both years and were analysed for water quality parameters including total dissolved solids, electrical conductivity (EC), dissolved organic carbon, bacterial count and nutrients in the water phase. In the second year of the study, samples were also taken at the entry point into the forebays and analysed to determine if the forebays contributed to removal of analytes prior to diversion in the retention ponds. EC, which had been used as the determining factor of whether runoff is used to recharge or diverted to holding ponds, did not relate to nutrient levels. This indicated that EC is insufficient to determine water quality because runoff with low EC may contain high levels of nutrients that can support eutrophication. Monitoring of nutrients themselves is essential for decisions.


2021 ◽  
Vol 192 ◽  
pp. 116848
Author(s):  
Ming Su ◽  
Yiping Zhu ◽  
Zeyu Jia ◽  
Tingting Liu ◽  
Jianwei Yu ◽  
...  

2020 ◽  
Vol 25 (4) ◽  
pp. 565-579
Author(s):  
Azadeh Golshan ◽  
Craig Evans ◽  
Phillip Geary ◽  
Abigail Morrow ◽  
Zoe Rogers ◽  
...  

2016 ◽  
Vol 78 (11) ◽  
Author(s):  
Manutha Appa Rwoo ◽  
Hafizan Juahir ◽  
Nor Malisa Roslan ◽  
Mohd Ekhwan Toriman ◽  
Azizah Endut ◽  
...  

This case study characterizes the drinking water quality by using the multivariate technique. The spatial variation of the physico-chemical and heavy metals parameters toxicity with the drinking water quality based on 28 water treatment plants in Selangor, Malaysia from 2009 to 2012 was evaluated. The objectives of this study are to analyze the physio-chemical activities and heavy metals activities in the collected drinking water samples from the treatment plants, and to detect the source of pollution for the most revealing parameters. The discriminant analysis (DA) and the principal component analysis (PCA) are the chemometric techniques used to investigate the spatial variation of the most significant physico-chemical and heavy metal parameters of the drinking water samples. The classification matrix accuracy for standard mode of DA, forward stepwise and backward stepwise for the physico-chemical and heavy metal parameters are excellent. PCA highlighted 13 significant parameters out of 18 physico-chemical water quality parameters and 14 significant parameters out of 16 heavy metal parameters. PCA was carried out to identify the origin and source of pollution of each water quality parameters. For that reason, this study proves that chemometric method is the principle way to explain the characteristic of the drinking water quality.


2020 ◽  
Vol 79 (17) ◽  
Author(s):  
Johanna M. Blake ◽  
Jeb E. Brown ◽  
Christina L. Ferguson ◽  
Rebecca J. Bixby ◽  
Naomi T. Delay

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