2134/9095 Ahmed Moustafa Ahmed Moustafa Deducing water parameters in rivers via statistical modelling Loughborough University 2011 Acoustic-Doppler Online Drinking Water Sensors Turbidity Colour Conductivity Flow Rive 2011-11-18 13:14:08 Thesis https://repository.lboro.ac.uk/articles/thesis/Deducing_water_parameters_in_rivers_via_statistical_modelling/9579212 Advanced monitoring of water quality in order to perform a real-time hazard analysis prior to Water Treatment Works (WTW) is more of a necessity nowadays, both to give warning of any contamination and also to avoid downtime of the WTW. Downtimes could be a major contributor to risk. Any serious accident will cause a significant loss in customer and investor confidence. This has challenged the industry to become more efficient, integrated and attractive, with benefits for its workforce and society as a whole. The reality is that water companies are not yet prepared to invest heavily in trials, before another company announces its success in implementing a new monitoring strategy. This has slowed down the development of the water industry. This research has taken the theoretical idea that the use of advanced online monitoring technique in the water industry would be beneficial and a step further; demonstrating by means of a state-of-the-art assessment, usability trials, case studies and demonstration that the barriers to mainstream adoption can be overcome. The findings of this work have been presented in four peer-reviewed papers. The research undertaken has shown that Turbidity levels in rivers can be measured from the rivers’ mean flow rate, using either Doppler Ultrasound device for real-time readings or based on past performance history. In both cases, the Turbidity level can also help estimate both the Colour and Conductivity levels of the subject river. Recalibration of the equations used is a prerequisite as each individual river has its own unique “finger print”.