Modelling Bacterial Biomass in a Non-chlorinated Drinking Water Distribution System

Abstract Water quality can deteriorate as it travels through a drinking water distribution system (DWDS). The DWDS offers reaction surfaces and contact time and, thus, acts as a bioreactor where biofilms develop that influence biomass dynamics. Under normal operational conditions the biofilm is in a steady state and the exchange of biomass between the biofilm and the bulk water phase is in equilibrium. When this equilibrium is disturbed, e.g. by a hydraulic incident, there is a potential of release of biomass from the biofilm leading to higher concentrations of biomass in the drinking water. This could lead to a discolouration event and may have an impact on microbial water quality. The main issue for a water company is to know where in the network the risk of these disturbances of the equilibrium is the largest and what control measures can be taken. The goal of our research is to combine and improve water quality models and a hydraulic network model to determine high and low risk locations in the DWDS with respect to bacterial biomass. As a first result a conceptual model, with parameter values based on internationally published laboratory and in situ measurements in the DWDS, has been developed.

[1]  W. R. Furnass Modelling both the continual accumulation and erosion of discolouration material in drinking water distribution systems , 2015 .

[2]  Joby Boxall,et al.  Modeling Discoloration in Potable Water Distribution Systems , 2005 .

[3]  S. Pirt Maintenance energy: a general model for energy-limited and energy-sufficient growth , 1982, Archives of Microbiology.

[4]  Cass T. Miller,et al.  Bacterial regrowth model for water distribution systems incorporating alternating split-operator solution technique , 2004 .

[5]  D. Karl,et al.  Cellular nucleotide measurements and applications in microbial ecology. , 1980, Microbiological reviews.

[6]  M. V. van Loosdrecht,et al.  A thermodynamically based correlation for maintenance gibbs energy requirements in aerobic and anaerobic chemotrophic growth , 1993, Biotechnology and bioengineering.

[7]  E R Cornelissen,et al.  Threshold concentration of easily assimilable organic carton in feedwater for biofouling of spiral-wound membranes. , 2009, Environmental science & technology.

[8]  Dick van der Kooij,et al.  Biofilm formation on surfaces of glass and Teflon exposed to treated water , 1995 .

[9]  J. Vrouwenvelder,et al.  Elucidation and control of biofilm formation processes in water treatment and distribution using the Unified Biofilm Approach. , 2003, Water science and technology : a journal of the International Association on Water Pollution Research.

[10]  Dick van der Kooij,et al.  Effect of water composition, distance and season on the adenosine triphosphate concentration in unchlorinated drinking water in the Netherlands. , 2010 .

[11]  Pierre Servais,et al.  Development of a model of BDOC and bacterial biomass fluctuations in distribution systems , 1994 .

[12]  Patrick Laurent,et al.  « Développement d'un modèle décrivant les variations de CODB et de biomasse bactérienne dans les réseaux de distribution » , 1995 .

[13]  Joby Boxall,et al.  Field studies of discoloration in water distribution systems: model verification and practical implications. , 2010 .

[14]  Pierre Villon,et al.  DYNAMIC MODELLING OF BACTERIAL GROWTH IN DRINKING WATER NETWORKS , 1996 .

[15]  W. Hoogenboezem,et al.  Variability of invertebrate abundance in drinking water distribution systems in the Netherlands in relation to biostability and sediment volumes. , 2012, Water research.

[16]  W.A.M. Hijnen,et al.  Threshold concentrations of biomass and iron for pressure drop increase in spiral-wound membrane elements. , 2011, Water research.

[17]  J. C. van Dijk,et al.  Simulating Nonresidential Water Demand with a Stochastic End-Use Model , 2013 .

[18]  Ameet J Pinto,et al.  Bacterial community structure in the drinking water microbiome is governed by filtration processes. , 2012, Environmental science & technology.

[19]  J. Vreeburg,et al.  Shared failure data for strategic asset management , 2013 .