First Evidence of Amoebae–Mycobacteria Association in Drinking Water Network

2014 ◽  
Vol 48 (20) ◽  
pp. 11872-11882 ◽  
Author(s):  
Vincent Delafont ◽  
Faïza Mougari ◽  
Emmanuelle Cambau ◽  
Michel Joyeux ◽  
Didier Bouchon ◽  
...  
Keyword(s):  
Drinking Water ◽  
Water Network

scholarly journals Evaluation the water quality of the potable water network in Al-Shuala/ Baghdad City

2019 ◽  
Vol 13 (28) ◽  
pp. 116-124
Author(s):  
Zainab Bahaa Mohammed
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Drinking Water ◽  
Quality Index ◽  
Potable Water ◽  
Total Hardness ◽  
Water Network ◽  
Conductivity Water ◽  
Total Dissolved Solid

In this research, the water quality of the potable water network inAl-Shuala Baghdad city were evaluated and compare them with theIraqi standards (IQS) for drinking water and World HealthOrganization standards (WHO), then water quality index (WQI) werecalculator: pH, heavy metals (lead, cadmium and iron), chlorides,total hardness, turbidity, dissolved oxygen, total dissolved solid andelectrical conductivity. Water samples are collected weekly duringthe period from February 2015 to April 2015 from ten sites. Resultsshow that the chlorides, total dissolved solid and electricalconductivity less than acceptable limit of standards, but totalhardness and heavy metals in some samples higher than acceptablelimit of standards while the other parameter is good.WQI shows thatresults is excellent and good for drinking for all location and monthsexcept site (2) gave higher value (65.184) in March and site (9) gavehigh value (57.78, 57.23) at March and April indicate that sites ispoor for drinking water.

Dynamics of bacterial communities before and after distribution in a full-scale drinking water network

2015 ◽  
Vol 74 ◽  
pp. 180-190 ◽  
Author(s):  
Joline El-Chakhtoura ◽  
Emmanuelle Prest ◽  
Pascal Saikaly ◽  
Mark van Loosdrecht ◽  
Frederik Hammes ◽  
...  
Keyword(s):  
Drinking Water ◽  
Bacterial Communities ◽  
Full Scale ◽  
Water Network ◽  
Before And After

Waterborne norovirus outbreak in a municipal drinking-water supply in Sweden

2011 ◽  
Vol 139 (12) ◽  
pp. 1928-1935 ◽  
Author(s):  
M. RIERA-MONTES ◽  
K. BRUS SJÖLANDER ◽  
G. ALLESTAM ◽  
E. HALLIN ◽  
K.-O. HEDLUND ◽  
...  
Keyword(s):  
Drinking Water ◽  
Water Supply ◽  
Gastrointestinal Symptoms ◽  
Control Measures ◽  
Drinking Water Supply ◽  
Water Network ◽  
Public Network ◽  
The Public ◽  
Increased Risk ◽  
Stool Samples

SUMMARYDuring Easter 2009, almost 200 people resident in a small Swedish village fell ill with gastrointestinal symptoms. We conducted a retrospective cohort study and a molecular investigation in order to identify the source of the outbreak. Residents living in households connected to the public water network were at an increased risk of developing disease (relative risk 4·80, 95% confidence interval 1·68–13·73) compared to those with no connection to the public network. Norovirus genotype GI.3 was identified in stool samples from six patients and in a sample from the public water network. Contamination of one of the wells supplying the public water network was thought to be the source of the outbreak. This is a description of a norovirus outbreak linked to a municipal drinking-water supply in Sweden. Information from epidemiological and molecular investigations is of utmost importance to guide outbreak control measures and to prevent future outbreaks.

scholarly journals Short-term demand forecast using a bank of neural network models trained using genetic algorithms for the optimal management of drinking water networks

2016 ◽  
Vol 19 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Hector Rodriguez Rangel ◽  
Vicenç Puig ◽  
Rodrigo Lopez Farias ◽  
Juan J. Flores
Keyword(s):  
Genetic Algorithms ◽  
Drinking Water ◽  
Distribution Networks ◽  
Water Networks ◽  
Economic Costs ◽  
Water Network ◽  
Demand Forecast ◽  
Short Term ◽  
Neural Network Models ◽  
Efficient Management

Efficient management of a drinking water network reduces the economic costs related to water production and transport (pumping). Model predictive control (MPC) is nowadays a quite well-accepted approach for the efficient management of the water networks because it allows formulating the control problem in terms of the optimization of the economic costs. Therefore, short-term forecasts are a key issue in the performance of MPC applied to water distribution networks. However, the short-term horizon demand forecast in a horizon of 24 hours in an hourly based scale presents some challenges as the water consumption can change from one day to another, according to certain patterns of behavior (e.g., holidays and business days). This paper focuses on the problem of forecasting water demand for the next 24 hours. In this work, we propose to use a bank of models instead of a single model. Each model is designed for forecasting one particular hour. Hourly models use artificial neural networks. The architecture design and the training process are performed using genetic algorithms. The proposed approach is assessed using demand data from the Barcelona water network.

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