Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps

Blokker, Mirjam; Furnass, Will; Machell, John; Mounce, S. R.; Schaap, Peter G.; Boxall, Joby

doi:10.3390/environments3020010

Cited by 33 publications

(29 citation statements)

References 25 publications

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“…These ordered, colour contour maps enable the researcher to visually identify similar patterns between some of them; this would mean that similar levels of different variables typically matched over time. That is, the visual inspection of the component planes of the SOM provides a rapid and intuitive means of examining the covariance between the selected variables in order to obtain an increased understanding of the system [26], especially in complex problems with several potential variables involved (e.g., [27]). Based on the conclusions of these first steps, a more in-depth analysis could be performed, and a simple prediction model was developed.…”

Section: Discussionmentioning

confidence: 99%

Analysis and Modelling of Taste and Odour Events in a Shallow Subtropical Reservoir

Bertone

O’Halloran

2016

Environments

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Understanding and predicting Taste and Odour events is as difficult as critical for drinking water treatment plants. Following a number of events in recent years, a comprehensive statistical analysis of data from Lake Tingalpa (Queensland, Australia) was conducted. Historical manual sampling data, as well as data remotely collected by a vertical profiler, were collected; regression analysis and self-organising maps were the used to determine correlations between Taste and Odour compounds and potential input variables. Results showed that the predominant Taste and Odour compound was geosmin. Although one of the main predictors was the occurrence of cyanobacteria blooms, it was noticed that the cyanobacteria species was also critical. Additionally, water temperature, reservoir volume and oxidised nitrogen availability, were key inputs determining the occurrence and magnitude of the geosmin peak events. Based on the results of the statistical analysis, a predictive regression model was developed to provide indications on the potential occurrence, and magnitude, of peaks in geosmin concentration. Additionally, it was found that the blue green algae probe of the lake's vertical profiler has the potential to be used as one of the inputs for an automated geosmin early warning system.

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Section: Discussionmentioning

confidence: 99%

Analysis and Modelling of Taste and Odour Events in a Shallow Subtropical Reservoir

Bertone

O’Halloran

2016

Environments

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“…These parameters were chosen for multiple reasons. For example, changes in residual chlorine are linked with pollution by chemicals like ammonia and biofilm growth; chlorine reactions with corrosion products and COD could most likely explain low residual chlorine levels at the end of the network, where water age can be high [21]. The low residual chlorine levels in the Mukono reservoir and areas that follow are more likely due to this reason.…”

Section: Choice Of Water Quality Parametersmentioning

confidence: 99%

“…Higher turbidity levels are often associated with higher levels of viruses, parasites and some bacteria [22]. There can be correlations between water age and chlorine levels [21]. Exposure to extreme pH values results in irritation to the eyes, skin, and mucous membranes [23].…”

Section: Choice Of Water Quality Parametersmentioning

confidence: 99%

Managing Water Quality in Intermittent Supply Systems: The Case of Mukono Town, Uganda

Sakomoto

Lutaaya

Abraham

2020

Water

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Intermittent water supply networks risk microbial and chemical contamination through multiple mechanisms. In particular, in the cities of developing countries, where intrusion through leaky pipes are more prevalent and the sanitation systems coverage is low, contaminated water can be a public health hazard. Although countries using intermittent water supply systems aim to change to continuous water supply systems—for example, Kampala city is targeting to change to continuous water supply by 2025 through an expansion and rehabilitation of the pipe infrastructure—it is unlikely that this transition will happen soon because of rapid urbanisation and economic feasibility challenges. Therefore, water utilities need to find ways to supply safe drinking water using existing systems until gradually changing to a continuous supply system. This study describes solutions for improving water quality in Mukono town in Uganda through a combination of water quality monitoring (e.g., identifying potential intrusion hotspots into the pipeline using field measurements) and interventions (e.g., booster chlorination). In addition to measuring and analyses of multiple chemical and microbial water quality parameters, we used EPANET 2.0 to simulate the water quality dynamics in the transport pipeline to assess the impact of interventions.

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“…This type of modelling has provided insight into the self-cleaning effect and shown that the self-cleaning velocity that has to be reached at 50 % of the days is 0.20 to 0.25 m s −1 in the tertiary network (Blokker et al, 2010b(Blokker et al, , 2011cSchaap and Blokker, 2011). With SIMDEUM, a better prediction of the residence time will be available, and the study of the relation between the residence time and the water quality may also improve Blokker et al, 2016).…”

Section: Research In the Dwdsmentioning

confidence: 99%

Review of applications for SIMDEUM, a stochastic drinking water demand model with a small temporal and spatial scale

Blokker

Agudelo-Vera

Moerman

et al. 2017

Drink. Water Eng. Sci.

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Abstract. Many researchers have developed drinking water demand models with various temporal and spatial scales. A limited number of models is available at a temporal scale of 1 s and a spatial scale of a single home. The reasons for building these models were described in the papers in which the models were introduced, along with a discussion on their potential applications. However, the predicted applications are seldom re-examined. SIMDEUM, a stochastic end-use model for drinking water demand, has often been applied in research and practice since it was developed. We are therefore re-examining its applications in this paper. SIMDEUM's original purpose was to calculate maximum demands in order to design self-cleaning networks. Yet, the model has been useful in many more applications. This paper gives an overview of the many fields of application for SIMDEUM and shows where this type of demand model is indispensable and where it has limited practical value. This overview also leads to an understanding of the requirements for demand models in various applications.

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Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps

Cited by 33 publications

References 25 publications

Analysis and Modelling of Taste and Odour Events in a Shallow Subtropical Reservoir

Analysis and Modelling of Taste and Odour Events in a Shallow Subtropical Reservoir

Managing Water Quality in Intermittent Supply Systems: The Case of Mukono Town, Uganda

Review of applications for SIMDEUM, a stochastic drinking water demand model with a small temporal and spatial scale

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