Operational management of trunk main discolouration risk

Despite significant on-going investment, water companies continue to receive an unacceptable number of discolouration related customer contacts. In this paper, data from intensive distribution system turbidity monitoring and cluster analysis of discolouration customer contacts indicate that a significant proportion of these contacts are due to material mobilising from the trunk main system, and operational flow increases are shown to have a higher discolouration risk than burst incidents. A trunk main discolouration incident highlighting this risk is discussed, demonstrating the need for pro-active trunk main risk assessments. To identify the source of the material event flow rates were modelled using the PODDS (prediction of discolouration in distribution systems) discolouration model. Best practice pro-active management is demonstrated in a case study where the PODDS model is used to implement managed incremental flow changes on a main with known discolouration risk with no discolouration impact to customers and significant cost savings

Identifying Sampling Interval for Event Detection in Water Distribution Networks

It is a generally adopted policy, albeit unofficially, to sample flow and pressure data at a 15-min interval for water distribution system hydraulic measurements. Further, for flow, this is usually averaged, whereas pressure is instantaneous. This paper sets out the findings of studies into the potential benefits of a higher sampling rate and averaging for flow and pressure measurements in water distribution systems. A data set comprising sampling at 5 s (in the case of pressure), 1 min, 5 min, and 15 min, both instantaneous and averaged, for a set of flow and pressure sensors deployed within two DMAs has been used. Engineered events conducted by opening fire hydrants/wash outs were used to form a controlled baseline detection comparison with known event start times. A data analysis system using support vector regression (SVR) was used to analyze the flow and pressure time series data from the deployed sensors and hence, detect these abnormal events. Results are analyzed over different sensors and events. The overall trend in the results is that a faster sampling rate leads to earlier event detection. However, it is concluded that a sampling interval of 1 or 5 min does not significantly improve detection to the point at which it is worth the added increase in power, communications, and data management requirements with current technologies. It was discovered that averaging pressure data can result in more rapid detection when compared with using the same instantaneous sampling rate. Averaging of pressure data is also likely to provide better regulatory compliance and provide improved data for EPS hydraulic modelling. This improvement can be achieved without any additional overheads on communications by a simple firmware alteration and hence, is potentially a very low cost upgrade with significant gains

Modelling and flow conditioning to manage discolouration in trunk mains

This paper presents predictive discolouration modelling and subsequent field trial results for a cast iron trunk main network. This enabled a UK water company to propose an ‘operational flow conditioning’ maintenance plan that reduces discolouration risk, improves network resilience and asset condition and yet does not require the trunk main to be decommissioned for invasive cleaning. This represents substantial time and cost benefits. Pre-and-post trial turbidity monitoring data is also presented which identified a daily flux of material, a factor in the regeneration of material layers that have been shown to cause discolouration when mobilised. Additional data detecting the occurrence of pressure transients is also presented, a possible cause of contaminant ingress and asset failure

Succession of bacterial and fungal communities within biofilms of a chlorinated drinking water distribution system

Understanding the temporal dynamics of multi-species biofilms in Drinking Water Distribution Systems (DWDS) is essential to ensure safe, high quality water reaches consumers after it passes through these high surface area reactors. This research studied the succession characteristics of fungal and bacterial communities un der controlled environmental conditions fully representative of operational DWDS. Microbial communities were observed to increase in complexity after one month of biofilm development but they did not reach stability after three months. Changes in cell numbers were faster at the start of biofilm formation and tended to decrease over time, despite the continuing changes in bacterial community composition. Fungal diversity was markedly less than bacterial diversity and had a lag in responding to temporal dynamics. A core-mixed community of bacteria including Pseudomonas, Massillia and Sphingomonas and the fungi Acremonium and Neocosmopora were present constantly and consistently in the biofilms over time and conditions studied. Monitoring and managing biofilms and such ubiquitous core microbial communities are key control strategies to ensuring the delivery of safe drinking water via the current ageing DWDS infrastructure

Influence of hydraulic regimes on bacterial community structure and composition in an experimental drinking water distribution system

Microbial biofilms formed on the inner-pipe surfaces of drinking water distribution systems (DWDS) can alter drinking water quality, particularly if they are mechanically detached from the pipe wall to the bulk water, such as due to changes in hydraulic conditions. Results are presented here from applying 454 pyrosequencing of the 16S ribosomal RNA (rRNA) gene to investigate the influence of different hydrological regimes on bacterial community structure and to study the potential mobilisation of material from the pipe walls to the network using a full scale, temperature-controlled experimental pipeline facility accurately representative of live DWDS. Analysis of pyrosequencing and water physico-chemical data showed that habitat type (water vs. biofilm) and hydraulic conditions influenced bacterial community structure and composition in our experimental DWDS. Bacterial community composition clearly differed between biofilms and bulk water samples. Gammaproteobacteria and Betaproteobacteria were the most abundant phyla in biofilms while Alphaproteobacteria was predominant in bulk water samples. This suggests that bacteria inhabiting biofilms, predominantly species belonging to genera Pseudomonas, Zooglea and Janthinobacterium, have an enhanced ability to express extracellular polymeric substances to adhere to surfaces and to favour co-aggregation between cells than those found in the bulk water. Highest species richness and diversity were detected in 28 days old biofilms with this being accentuated at highly varied flow conditions. Flushing altered the pipe-wall bacterial community structure but did not completely remove bacteria from the pipe walls, particularly under highly varied flow conditions, suggesting that under these conditions more compact biofilms were generated. This research brings new knowledge regarding the influence of different hydraulic regimes on the composition and structure of bacterial communities within DWDS and the implication that this might have on drinking water quality

Online modelling of water distribution systems: a UK case study

Hydraulic simulation models of water distribution networks are routinely used for operational investigations and network design purposes. However, their full potential is often never realised because, in the majority of cases, they have been calibrated with data collected manually from the field during a single historic time period and, as such, reflect the network operational conditions that were prevalent at that time, and they are then applied as part of a reactive, desktop investigation. In order to use a hydraulic model to assist proactive distribution network management its element asset information must be up to date and it should be able to access current network information to drive simulations. Historically this advance has been restricted by the high cost of collecting and transferring the necessary field measurements. However, recent innovation and cost reductions associated with data transfer is resulting in collection of data from increasing numbers of sensors in water supply systems, and automatic transfer of the data to point of use. This means engineers potentially have access to a constant stream of current network data that enables a new era of "on-line" modelling that can be used to continually assess standards of service compliance for pressure and reduce the impact of network events, such as mains bursts, on customers. A case study is presented here that shows how an online modelling system can give timely warning of changes from normal network operation, providing capacity to minimise customer impact

Development and field validation of a burst localisation methodology

Reducing water loss through bursts is a major challenge throughout the developed and developing world. Currently burst lifetimes are often long because awareness and location of them is time- and labor-intensive. Advances that can reduce these periods will lead to improved leakage performance, customer service, and reduce resource wastage. In water-distribution systems the sensitivity of a pressure instrument to change, including burst events, is greatly influenced by its own location and that of the event within the network. A method is described here that utilizes hydraulic-model simulations to determine the sensitivity of potential pressure-instrument locations by sequentially applying leaks to all potential burst locations. The simulation results are used to populate a Jacobian matrix, quantifying the different sensitivities. This matrix may then be searched to identify different instrument locations to achieve required goals: maximising overall sensitivity to all potential events or selective sensitivity to events in different network areas. It is shown here that by searching this matrix to optimize such selective sensitivity, while minimising instrument numbers, it is possible to provide useful burst-localization information. Results are presented from field studies that demonstrate the practical application of the method, showing that current standard network models can provide sufficiently accurate quantification of differential sensitivities and that, once combined with event-detection techniques for data analysis, events can effectively be localized using a small number of instruments

Impact of hydraulic interventions on chronic and acute material loading and discolouration risk in drinking water distribution systems

This paper presents results from an intensive long term investigation in three comparable trunk mains and downstream impact of non-invasive, in-service flow conditioning to manage discolouration risk. Findings show that flow conditioning, the careful regular increase in flows to mobilise small amounts of material from cohesive layers formed at the pipe wall, provides immediate risk mitigation and system resilience benefits. Evidence is presented showing longer term risk reduction in the trunk mains and a 25% discolouration risk reduction in the downstream networks. Whilst the flow conditioning produced an acute but short duration controlled mobilisation of material from the trunk main, longer term downstream monitoring showed reduced chronic or background material loading. It is proposed this change is due to altering the material exchange behaviour and volumes bound within cohesive layers that develop on bulk water/infrastructure interfaces. The paper provides evidence that flow conditioning is an efficient strategy to manage discolouration risk and improve consumer water quality throughout water distribution systems

Water quality event detection and customer complaint clustering analysis in distribution systems

Safe, clean drinking water is a foundation of society and water quality monitoring can contribute to ensuring this. A case study application of the CANARY software to historic data from a UK drinking water distribution system is described. Sensitivity studies explored appropriate choice of algorithmic parameter settings for a baseline site, performance was evaluated with artificial events and the system then transferred to all sites. Results are presented for analysis of nine water quality sensors measuring six parameters and deployed in three connected district meter areas (DMAs), fed from a single water source (service reservoir), for a 1 year period and evaluated using comprehensive water utility records with 86% of event clusters successfully correlated to causes (spatially limited to DMA level). False negatives, defined by temporal clusters of water quality complaints in the pilot area not corresponding to detections, were only approximately 25%. It was demonstrated that the software could be configured and applied retrospectively (with potential for future near real time application) to detect various water quality event types (with a wider remit than contamination alone) for further interpretation