QUALTR: Software for Simulating Output from Water Treatment Plants in the Face of Extreme Events

  • Mrinmoy MajumderEmail author
  • Paulami De
  • Rabindra Nath Barman


Water treatment plants (WTPs) are responsible for supplying treated water to domestic, industrial, and agricultural users. When water is treated, the quality is upgraded to a predetermined standard. Most WTPs take water in from surface water sources like rivers or wetlands, although the quality of surface water follows a uniform trend. The amount and time of waste influx are predictable and depend upon the domestic, industrial, and agricultural consumers. But during an extreme event like rainfall the surface runoff contaminates the water bodies by washing out both inorganic and organic impurities from the watershed. Such impurities include toxic materials used in fertilizers, cleaning agents, human or animal wastes, etc. In summary, after a storm, surface runoff increases the level of pollutants in water bodies, and WTPs that take in water from those bodies must adjust their chemical dosing to control and maintain the prescribed quality standard. But if the sudden degradation of water quality is not monitored in real time, the contaminated water will be delivered to consumers. The supply of low-quality water can compromise public health and consumer satisfaction and may even create a health hazard that would be expensive and difficult to control. That is why the present investigation will try to introduce a software that can predict the status of treated water with respect to changes occurring in various related quality parameters of the surface water as well as the amount of chemical dosing. If the software is linked with a ­real-time monitoring system, then it can alert plant managers well in advance of an incoming quality hazard. A neural network was selected as the prediction ­algorithm due to its ability to identify complex relationships between nonlinear variables. The potential of the software was verified with the help of real-time quality data of source water and the corresponding pattern of dosing followed in a small urban WTP.


Water treatment plants Simulation software Neuro-genetic models 

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Mrinmoy Majumder
    • 1
    Email author
  • Paulami De
    • 1
  • Rabindra Nath Barman
    • 2
  1. 1.School of Hydro-Informatics EngineeringNational Institute of Technology Agartala, BarjalaJiraniaIndia
  2. 2.Department of Production EngineeringNational Institute of Technology Agartala, BarjalaJiraniaIndia

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