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detection of changes in the water quality. A sensor data fusion module evaluates the data of water quality sensors. The module learns the normal water quality ranges and patterns from historical data. The online simulation model is used for plausibility, check-of-the- event detection. • Optimal sensor placement: Enables the optimal placement of a defined number of quality sensors in a real-world network (hydraulic state, physical/chemical parameters). It enables the user (e.g., WDN operators) to find optimal locations for early warning detection systems (Propato and Piller, 2006; Deuerlein et al., 2010). • Online simulator: Provides real-time, reliable flow, pressure, and water quality parameter values of the whole water network. The calculations are based on the available online measurement data of hydraulic parameters (e.g., inflow in the network, demand, flow, and pressure values) and water quality parameters. • Enhanced water quality simulator: Provides more reliable water quality simulation results. In most of the actual available WDN simulation software tools (e.g., EPANET), a complete mixing of substances at junctions is assumed. Detailed experimental and simulation-based study of the transport of conservative substances in real-world water drinking networks showed that under various flow conditions the complete mixing assumption does not hold (Shen 2008, Braun 2105). The water quality models PORTEAU (Irstea) and EPANET-MSX has been enhanced so that the non-ideal mixing at junctions is considered. • Online contaminant source identification and mitigation of risks: Provides the location (or at least candidates) of a contamination source. A backtracking algorithm that uses the data of historical measurements has been implemented. The merit of offline methods (e.g., Propato et al., 2007) and pseudo real-time ones (Preis and Ostfeld, 2011) has been studied and compared to the developed online solution method. As a result of water quality sensor alarms, the possible localizations of the intrusion of contaminant can be calculated. • Risk analysis and impact assessment: Risk analysis and impact evaluation (real impacts and perceived ones) will be performed for the three aspects of sustainability: environmental, social, and economical, combined with technical innovation. The SMaRT-Online WDN toolkit improves the observability of water quality and quantity in the distribution network in near real time. It acts as an early warning system as well as decision-support system in case of contamination events. Furthermore, it supports a better understanding of the physical and biochemical processes in the pipe systems — e.g., it is possible to use it offline for training of staff by use of simulation. Project SAFEWATER Innovative tools for the detection and mitigation of CBRN- related contamination of drinking water events Similar to the aims of the project SMaRT Online WDN , the European FP7 ("Seventh Framework Programme for Research and Technological Development") project SAFEWATER (Oct. 2013 to Dec. 2016) aims at developing a comprehensive event detection and event management solution for drinking water security management and mitigation against major deliberate, accidental, or natural CBRN-related contaminations (see SAFEWATER (2016)). The comprehensive SAFEWATER solution, comprising enhanced near-real-time sensors, an advanced decision support system, online hydraulic propagation models, and an all-encompassing event management system wateronline.com n Water Innovations 17 WATERQUALITYANALYSIS Figure 1. In case of a toxic contamination of the water distribution network, the water suppliers will be supported by the SMaRT-Online WDN security management toolkit.