scholarly journals Physicochemical interaction with faecal bacteria in characterisation of beach water quality, Gulf of Guinea, Ghana

2021 ◽  
Author(s):  
Lailah Gifty Akita ◽  
Juegen Laudien ◽  
Charles Biney ◽  
Mark Akrong
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Agricultural Waste ◽  
Physicochemical Interaction ◽  
Western Africa ◽  
Faecal Analysis ◽  
Faecal Bacteria ◽  
Beach Water Quality ◽  
Beach Water

Abstract Human activities such as industrial and agricultural waste discharges directly in the coastal areas increasingly contribute to pollution in coastal waters of Western Africa. The study employed physicochemical and faecal analysis to understand water pollution along the coast of Ghana. The physicochemical parameter such as temperature, salinity, electrical conductivity, pH, dissolved oxygen concentration, dissolved oxygen saturation, total dissolved solids, and redox potential) were measured in situ while water samples were collected determination of total suspended solids, nutrients, chlorophyll-a, and faecal bacteria. The abundance of total coliforms (4061.6 ± 4159.14 CFU/100 ml water), Escherichia coli, and Enterococcus spp. varied significantly (p < 0.05) among the beaches. The high amount of faecal bacteria suggest microbial contamination, possible ecosystem, and health risks to water resource users. This baseline study provides evidence of coastal water contamination to improve beach water quality standards to ensure safe environmental health.

scholarly journals Waterborne illness and injury: a feasibility study of a site-specific predictive model for beach water quality at Beachway Park in the City of Burlington

2021 ◽  
Author(s):  
Ramien Sereshk
Keyword(s):  
Water Quality ◽  
Predictive Model ◽  
Real Time ◽  
Site Specific ◽  
E Coli ◽  
Time Basis ◽  
A Site ◽  
Persistence Model ◽  
Beach Water Quality ◽  
Beach Water

It is commonly assumed that the persistence model, using day-old monitoring results, will provide accurate estimates of real-time bacteriological concentrations in beach water. However, the persistence model frequently provides incorrect results. This study: 1. develops a site-specific predictive model, based on factors significantly influencing water quality at Beachway Park; 2. determines the feasibility of the site-specific predictive model for use in accurately predicting near real-time E. coli levels. A site-specific predictive model, developed for Beachway Park, was evaluated and the results were compared to the persistence model. This critical performance evaluation helped to identify the inherent inaccuracy of the persistence model for Beachway Park, which renders it an unacceptable approach for safeguarding public health from recreational water-borne illnesses. The persistence model, supplemented with a site-specific predictive model, is recommended as a feasible method to accurately predict bacterial levels in water on a near real-time basis.

Daily prediction of marine beach water quality in Hong Kong

2012 ◽  
Vol 6 (3) ◽  
pp. 164-180 ◽  
Author(s):  
W. Thoe ◽  
S.H.C. Wong ◽  
K.W. Choi ◽  
J.H.W. Lee
Keyword(s):  
Water Quality ◽  
Hong Kong ◽  
Beach Water Quality ◽  
Beach Water

scholarly journals Predicting ‘very poor’ beach water quality gradings using classification tree

2015 ◽  
Vol 14 (1) ◽  
pp. 97-108 ◽  
Author(s):  
Wai Thoe ◽  
King Wah Choi ◽  
Joseph Hun-wei Lee
Keyword(s):  
Water Quality ◽  
Hong Kong ◽  
Linear Models ◽  
Classification Tree ◽  
Classification Trees ◽  
Water Quality Prediction ◽  
E Coli ◽  
Poor Water Quality ◽  
Beach Water Quality ◽  
Beach Water

A beach water quality prediction system has been developed in Hong Kong using multiple linear regression (MLR) models. However, linear models are found to be weak at capturing the infrequent ‘very poor’ water quality occasions when Escherichia coli (E. coli) concentration exceeds 610 counts/100 mL. This study uses a classification tree to increase the accuracy in predicting the ‘very poor’ water quality events at three Hong Kong beaches affected either by non-point source or point source pollution. Binary-output classification trees (to predict whether E. coli concentration exceeds 610 counts/100 mL) are developed over the periods before and after the implementation of the Harbour Area Treatment Scheme, when systematic changes in water quality were observed. Results show that classification trees can capture more ‘very poor’ events in both periods when compared to the corresponding linear models, with an increase in correct positives by an average of 20%. Classification trees are also developed at two beaches to predict the four-category Beach Water Quality Indices. They perform worse than the binary tree and give excessive false alarms of ‘very poor’ events. Finally, a combined modelling approach using both MLR model and classification tree is proposed to enhance the beach water quality prediction system for Hong Kong.

Effect of the South Bay Ocean Outfall (SBOO) on ocean beach water quality near the USA–Mexico border

2008 ◽  
Vol 18 (2) ◽  
pp. 149-158 ◽  
Author(s):  
Richard Gersberg ◽  
Jürgen Tiedge ◽  
Dana Gottstein ◽  
Sophie Altmann ◽  
Kayo Watanabe ◽  
...  
Keyword(s):  
Water Quality ◽  
The South ◽  
The Usa ◽  
Mexico Border ◽  
Ocean Outfall ◽  
Beach Water Quality ◽  
Beach Water
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