scholarly journals Drinking water quality monitoring using trend analysis

2013 ◽  
Vol 12 (2) ◽  
pp. 230-241 ◽  
Author(s):  
Jani Tomperi ◽  
Esko Juuso ◽  
Mira Eteläniemi ◽  
Kauko Leiviskä
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Measurement Data ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Linear Functions ◽  
Economic Losses ◽  
A Minor

One of the common quality parameters for drinking water is residual aluminium. High doses of residual aluminium in drinking water or water used in the food industry have been proved to be at least a minor health risk or even to increase the risk of more serious health effects, and cause economic losses to the water treatment plant. In this study, the trend index is developed from scaled measurement data to detect a warning of changes in residual aluminium level in drinking water. The scaling is based on monotonously increasing, non-linear functions, which are generated with generalized norms and moments. Triangular episodes are classified with the trend index and its derivative. The severity of the situations is evaluated by deviation indices. The trend episodes and the deviation indices provide good tools for detecting changes in water quality and for process control.

scholarly journals Investigation of water quality changes in drinking water supplied from Sitlee water treatment plant on River Tawi to Old Jammu City, Jammu, J&K, India

2018 ◽  
Vol 10 (2) ◽  
pp. 601-607
Author(s):  
Poonam Kundan ◽  
Deepika Slathia
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Water Treatment ◽  
Water Samples ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Quality Parameters ◽  
Faecal Coliform ◽  
Quality Changes ◽  
Distribution Point

In the present study, an attempt has been made to evaluate the water quality changes in River Tawi water treated at Sitlee water treatment plant, and supplied for drinking to Old Jammu City, Jammu, J&K, India. Water samples from the treated water unit of Sitlee water treatment plant and around ten houses from the distribution point (Old Jammu City) were analyzed monthly for various physicochemical parameters for a period of one year (February 2014 to January 2015). The study indicated deterioration of drinking water quality during its passage through the distribution network which has been attributed to the leakages and defects in the old pipe system supplying water to the Jammu city. Comparison of analyzed water quality parameters with the drinking water standards prescribed by World Health Organization (WHO) and Bureau of Indian Standards (BIS) indicated that parameters like DO (7.49-8.24mg/l), calcium(49.93-67.08mg/l), magnesium(16.14-25.21mg/l) and potassium(6.99-7.93mg/l) were almost nearing the desirable limits but were within the permissible limits and parameters like turbidity(3.5-8.17 NTU) and total hardness(78.87-120.50mg/l) were above the desirable limits in the water samples collected from the distribution point. The collected primary data for the thirteen water quality parameters has been used to calculate the Arithmetic Water Quality Index(WQI) which has shown monsoon increase with higher values at distribution point(65.65). One time microbial analysis (MPN/100ml) for total and faecal coliform has indicated presence of faecal coliform (<1/100ml) in water samples from eight households at distribution point which indicates contamination of water with human faecal matter during its passage through the distribution network. According to microbial standards laid down by Central Pollution Control Board (2008), water contaminated with faecal coliform is unfit for drinking without conventional treatment.

scholarly journals Design methodology to determine the water quality monitoring strategy of a surface water treatment plant in the Netherlands

2020 ◽  
Vol 13 (1) ◽  
pp. 1-13
Author(s):  
Petra Ross ◽  
Kim van Schagen ◽  
Luuk Rietveld
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Design Methodology ◽  
Treatment Plant ◽  
Cost Effective ◽  
Water Treatment Plant ◽  
Quality Standards ◽  
Water Quality Monitoring ◽  
Daily Basis ◽  
Multiple Parameters

Abstract. The primary goal of a drinking water company is to produce safe drinking water fulfilling the quality standards defined by national and international guidelines. To ensure the produced drinking water meets the quality standards, the sampling of the drinking water is carried out on a regular (almost daily) basis. It is a dilemma that the operator wishes to have a high probability of detecting a bias while minimizing their measuring effort. In this paper a seven-step design methodology is described which helps to determine a water quality (WQ) monitoring scheme. Besides using soft sensors as surrogate sensors for parameters currently not available online, they can possibly provide a cost-effective alternative when used to determine multiple parameters required through one single instrument.

scholarly journals Quality of Drinking Water from Springs in Palestine: West Bank as a Case Study

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Azza Daghara ◽  
Issam A. Al-Khatib ◽  
Maher Al-Jabari
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
West Bank ◽  
Field Work ◽  
Quality Parameters ◽  
Total Hardness ◽  
Residual Chlorine ◽  
The West ◽  
A Minor ◽  
Physical And Chemical

The shortage of fresh water creates acute challenges in the West Bank of Palestine. Springs provide a main water resource in the West Bank. Investigating springs’ water quality is essential step for promoting their public use. The aim of this research is to assess the microbiological and physiochemical quality parameters of drinking water from springs. The study methodology included sampling through field work and laboratory testing for water quality parameters using standard procedures. The study area covered all locations containing licensed springs by the Palestinian Water Authority in the West Bank of Palestine. The number of collected samples was 127 covering 300 springs. The chemical, physical, and biological parameters for each sample were measured. Then, the obtained characteristics were evaluated based on national and international quality standards (PSI and WHO). The investigated parameters included temperature, pH, EC, total hardness, concentrations of nitrate, sodium ions, total chlorine, residual chlorine, turbidity, and total and faecal coliforms. Most of investigated physical and chemical parameters were within the acceptable standard limits. However, the turbidity and chloride and nitrate concentrations exceeded standard limits. The findings indicate that only a minor fraction of the samples (2%) requires chlorination treatment, while most of the springs (97% of samples) are classified as possessing no risk.

scholarly journals Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6671
Author(s):  
Sharif Hossain ◽  
Christopher W.K. Chow ◽  
Guna A. Hewa ◽  
David Cook ◽  
Martin Harris
Keyword(s):  
Machine Learning ◽  
Drinking Water ◽  
Real Time ◽  
Learning Algorithm ◽  
Measurement Data ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Kernel Functions ◽  
Support Vector ◽  
Organic Nitrate

The spectra fingerprint of drinking water from a water treatment plant (WTP) is characterised by a number of light-absorbing substances, including organic, nitrate, disinfectant, and particle or turbidity. Detection of disinfectant (monochloramine) can be better achieved by separating its spectra from the combined spectra. In this paper, two major focuses are (i) the separation of monochloramine spectra from the combined spectra and (ii) assessment of the application of the machine learning algorithm in real-time detection of monochloramine. The support vector regression (SVR) model was developed using multi-wavelength ultraviolet-visible (UV-Vis) absorbance spectra and online amperometric monochloramine residual measurement data. The performance of the SVR model was evaluated by using four different kernel functions. Results show that (i) particles or turbidity in water have a significant effect on UV-Vis spectral measurement and improved modelling accuracy is achieved by using particle compensated spectra; (ii) modelling performance is further improved by compensating the spectra for natural organic matter (NOM) and nitrate (NO3) and (iii) the choice of kernel functions greatly affected the SVR performance, especially the radial basis function (RBF) appears to be the highest performing kernel function. The outcomes of this research suggest that disinfectant residual (monochloramine) can be measured in real time using the SVR algorithm with a precision level of ± 0.1 mg L−1.

Influence of molecular weight distribution of organic substances on the removal efficiency of DBPS in a conventional water treatment plant

2000 ◽  
Vol 41 (10-11) ◽  
pp. 43-49 ◽  
Author(s):  
C-N. Chang ◽  
A. Chao ◽  
F-S. Lee ◽  
F-F. Zing
Keyword(s):  
Water Quality ◽  
Molecular Weight ◽  
Water Treatment ◽  
Weight Distribution ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Quality Parameters ◽  
Organic Substances ◽  
Raw Water ◽  
Unit Operations

The objective of this study is to investigate how the molecular weight distribution of the organic substances affects their treatment efficiencies and the reduction of disinfection by-products (DBPs) in the various unit operations of a full-scale water treatment plant. The results indicate that the membrane with a smaller molecular weight cut-off is more effective for removing the organic substances and its associated water quality parameters from the raw water. For example, using the membrane with a molecular weight cut-off of 0.5 K (500 daltons), the removal efficiency of DOC from the raw water sample can be as high as 88%. Removal efficiencies of other water quality parameters such as UV254 absorbance, THMFP and AOXFP are generally between 65–69%. When undergoing the various unit operations in the conventional water treatment plant, most organic substances are removed in the coagulation process followed by sedimentation.

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