Predictive water quality modelling and resilience flow conditioning to manage discolouration risk in operational trunk mains

Abstract

This paper presents predictive discolouration modelling and subsequent field trial validation 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 are 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 are also presented, a possible cause of contaminant ingress and asset failure. After six months a second flow trail was conducted and modelled, confirming the regeneration of particulate discolouration material across the range of mobilising forces applied during the trial. It also indicated full layer development, or maximum discolouration risk, may occur in just over two years for this cast iron main. This highlights the need for appropriate maintenance strategies, such as periodic flow conditioning identified here, to mitigate discolouration risk and help safeguard water quality.

Quantity and quality benefits of in-service invasive cleaning of trunk mains

“…However, a complete conclusion about the inorganic particles responsible for the observed discolouration cannot be drawn from this sampling study alone as undisturbed sampling data from the trunk main were unavailable. Also, the previous work has indicated that biological processes impact on material accumulation and hence influence discolouration risks (Gauthier et al, 1999;Husband et al, 2016).…”

“…Recent studies have indicated that biofilms are a key component of the discolouration process. facilitating inorganic particle absorption within the organic matrix (Douterelo et al, 2014;Husband et al, 2016). PODDS concepts are well accepted for smaller diameter pipes in the distribution system and have started to be shown to be valid for large diameter transmission mains (Husband and Boxall, 2015).…”

Modelling the impact of water temperature, pipe, and hydraulic conditions on water quality in water distribution networks

“…Although significant insights have been gained through these studies, the controlled conditions under which experiments are performed may be significantly different from real systems. Further, by relying on operational data, models have been applied in studying relations between controlling factors of instabilities in water distribution systems (Sadiq et al 2008;Tabesh et al 2009;Ramos-Martínez et al 2014;Husband & Boxall 2015;Kutyłowska 2019). However, classical linear regression-based models that have been applied in many of these studies do not often consider the potentially stochastic nature of the dependence of water quality on pipe characteristics, operating conditions, and temperature.…”

Decreasing the Discoloration Risk of Drinking Water Distribution Systems through Optimized Topological Changes and Optimal Flow Velocity Control

“…Such models for a range of materials can be used to simulate and predict turbidity as a result of hydraulic changes introduced by burst events, sudden increase in demand, rezoning etc. or potentially to prioritise flushing (Husband and Boxall 2015). Although these predictive tools are man-hour intensive at the moment and so have limited scalability in improving the effect of dedicated flushing (Vreeburg and Boxall 2007), with decreasing equitment costs (eg.…”